Automatically generated PDF from existing images. - BIT Mesra

3.4.6 Number of books and chapters in edited volumes published per teacher during the last one year (2019-2020) (15)

3.4.6.1: Total number of books and chapters in edited volumes / books published, and papers in national/international conference-proceedings year wise during the last one year (2019-2020)

Sl. No.Name of the

teacher

Title of the book/chapters

publishedTitle of the paper

Title of the

proceedings of the

conference

Name of the conferenceNational /

International

Year of

publication

ISBN/ISSN

number of the

proceeding

Affiliating Institute

at the time of

publication

Name of the

publisherDeptt

1Rupesh Kumar

Sinha

Facial Expression

Recognition using

Convolutional Neural

Network and SoftMax

function on Captured Images

Proceedings of the

Fourth International

Conference on

Communication and

Electronics Systems

(ICCES 2019)

International Conference

on Communication and

Electronics Systems

(ICCES 2019)

International 2019ISBN: 978-1-7281-

1261-9

B. I. T. Mesra,

RanchiIEEE Xplore ECE

2Vibha Rani

Gupta

Characterization of

Laminated Paper based

Substrate for the ISM Band

Antenna Design

Lecture Notes in

Engineering and

Computer Science:

Proceedings of The

World Congress on

Engineering and

Computer Science

2019

Lecture Notes in

Engineering and Computer

Science: Proceedings of

The World Congress on

Engineering and Computer

Science 2019

International 2019ISBN: 978-988-

14048-7-9

B. I. T. Mesra,

Ranchi

Newswood

LimitedECE

3Vibha Rani

Gupta

Multiband Antenna Design

for Smartphone Covering 2G,

3G, 4G and 5G NR

frequencies

3rd International

Conference on Trends in

Electronics and

Informatics (ICOEI 2019)

International 2019

Electronic ISBN:

978-1-5386-9439-8,

DVD ISBN: 978-1-

5386-9438-1 Print

ISBN: 978-1-5386-

9440-4

B. I. T. Mesra,


4Vibha Rani

Gupta

Paper Based Conformal

Antenna

3rd International

Conference on Trends in

Electronics and

Informatics (ICOEI 2019)

International 2019

Electronic ISBN:

978-1-5386-9439-8,

DVD ISBN: 978-1-

5386-9438-1 Print

ISBN: 978-1-5386-

9440-5

B. I. T. Mesra,


5Vibha Rani

Gupta

Propagation Characteristics

of SIW and Waveguide: A

Comparison

5 th International

Conference on

Nanoelectronics, Circuits

& Communication

Systems (NCCS-2019)

International 2019B. I. T. Mesra,

RanchiSpringer ECE

6Vibha Rani

Gupta

Noval Compact planar 4-

Element MIMO Antenna for

4G/5G Applications

5 th International

Conference on


& Communication

Systems (NCCS-2019)


RanchiSpringer ECE

7Prajna Parimita

Dash

Analysis of NOMA: in

Capacity Domain

Proceeding:

International

Symposium on 5G &

Beyond for Rural

Upliftment 2020

International Symposium

on 5G & Beyond for Rural

Upliftment 2020

International 2020

e-

ISBN: 9788770222

174

B. I. T. Mesra,

RanchiRiver ECE

8Prajna Parimita

Dash

Animal tracking in wildlife

footage with Quantum

Particle Filter (QPF)

18th International

Conference on Information

Technology


RanchiIEEE ECE

9 Vijay NathDesign of 2-30GHz Low

Noise Amplifier: A Review

5th

International

Conference on


& Communication

Systems (NCCS-2019)


RanchiSpringer ECE

10 Vijay Nath

Ad Hoc Network using

UAVs in Indian Farms: A

Review

5th

International

Conference on


& Communication

Systems (NCCS-2019)


RanchiSpringer ECE

11 Vijay Nath

Designing of low noise

amplifier and voltage

controlled oscillator for

satellite receiver in ku band

5th

International

Conference on


& Communication

Systems (NCCS-2019)


RanchiSpringer ECE

12 S. K. Ghorai

BER Performance of hybrid

PLC-VLC system with

OFDM

2020 International

Conference on Computer,

Electrical &

Communication

Engineering (ICCECE)


RanchiIEEE ECE

13 S. K. Ghorai

Performance of MIMO-VLC

System for Different

Radiation Patterns of LED in

Indoor Optical wireless

Communication System

2019 IEEE International

Conference on Advanced

Networks and

Telecommunications

Systems (ANTS)


RanchiIEEE ECE

14 Nisha Gupta

Design Simulation and

Analysis of a Polarization-

Independent Ultrathin

Pixelated Metasurface

Absorber

2019 IEEE MTT-S

International Microwave

and RF Conference

(IMARC)


RanchiIEEE ECE

15 Priyank Saxena

Quantification of Cartilage

loss for Automatic Detection

and Classification of

Osteoarthritis using Machine

Learning approach

10th

ICCCNT International 2019B. I. T. Mesra,

RanchiIEEE ECE

16Manoj Kumar

Mukul

Recognition Of SSVEP-BCIs

System Using EMD Based

Threshold Detection Method

ICIMMI-2019 International 2019B. I. T. Mesra,

RanchiSpringer ECE

17Manoj Kumar

Mukul

Early Epileptic seizure

detection

10th INTERNATIONAL

CONFERENCE ON

COMPUTING,

COMMUNICATION

AND NETWORKING

TECHNOLOGIES

(ICCCNT) 2019


RanchiIEEE ECE

18Sitanshu Sekhar

Sahu

Stacked auto-encoder based

Time-frequency features of

Speech signal for Parkinson

disease prediction

IEEE International

Conference on Artificial

Intelligence and Signal

Processing


RanchiIEEE ECE

http://10icccnt.com/







19Sitanshu Sekhar

Sahu

Boosting predictions of Host-

Pathogen protein interactions

using Deep neural networks

IEEE International

Students' Conference on

Electrical, Electronics and

Computer Science


RanchiIEEE ECE

20Sitanshu Sekhar

Sahu

Effect of Dimensionality

Reduction on Classification

Accuracy for Protein–Protein

Interaction Prediction

Advanced Computing and

Intelligent EngineeringInternational 2020

B. I. T. Mesra,

RanchiSpringer ECE

21Sitanshu Sekhar

Sahu

Prediction of Protein

Interactions in Rice and Blast

Fungus Using Machine

Learning

IEEE International

Conference on Information

Technology


RanchiIEEE ECE

22Sitanshu Sekhar

Sahu

Improved Face detection

using YCbCr and Adaboost

Computational Intelligence

and Data MiningInternational 2020

B. I. T. Mesra,

RanchiSpringer ECE

23Sitanshu Sekhar

Sahu

Image Encryption using

Modified Rubik’s Cube

Algorithm

Advances in

Computational IntelligenceInternational 2020

B. I. T. Mesra,

RanchiSpringer ECE

24Sitanshu Sekhar

Sahu

Improved fractal-SPIHT

hybrid image compression

algorithm

IEEE International

Conference on Computing,

Communication and

Networking Technologies

(ICCCNT)


RanchiIEEE ECE

25Sitanshu Sekhar

Sahu

A Closed loop robust

controller for SSHI based

piezoelectric energy harvester

Computer-Aided

Developments in

Electronics and

Communication


Ranchi

Taylor &

FrancisECE

26Sitanshu Sekhar

Sahu

Intelligent Speech Signal

Processing

Intelligent Speech Processing

in the Time-Frequency

Domain

International 2019PP: 153-169 ISBN:

978-0-12-818130-0

B. I. T. Mesra,

RanchiElsevier ECE

27Sitanshu Sekhar

Sahu

Smart Biosensors in

Medical Care

Energy harvesting via human

body activitiesInternational 2020

ISBN:

9780128207819

B. I. T. Mesra,

RanchiElsevier ECE

28 Srikanta Pal

Metasurface aided

Biophysical Differentiation

of Radiated Cancer Cells: C-

band to THz perspective

IEEE nternational

Conference on Electronics,

Computing and

Communication

Technologies, CONECCT

2020


RanchiIEEE ECE

29 Srikanta Pal

Meta sensing Ovarian Cancer

Cells at THz from C Band

Radiation

6th International

Conference on

OPTRONIX


RanchiECE

30 Srikanta Pal

A THz Metasurface Coated

SoC For SPR Excited

Carcinoma Sensing


On Electrical And

Electronics Engineering

(ICE3 2020)


RanchiIEEE ECE

31 Srikanta Pal

Dual-Band Triple Mode

OAM Generation Using

Annular Slot Microstrip

Radiator

7th International

Conference on Signal

Processing and Integrated

Networks (SPIN 2020)


RanchiIEEE ECE

32 Srikanta Pal

OAM Wave Generation

Using Inner feed Annular

Slot Microstrip Radiator

7th International

Conference on Signal

Processing and Integrated

Networks (SPIN 2020)


RanchiIEEE ECE

33 Srikanta PalDesign of 2-30GHz Low

Noise Amplifier: A Review

5th International

Conference on


& Communication

Systems (NCCS-2019)


RanchiSpringer ECE

34 Srikanta Pal

Ad Hoc Network using

UAVs in Indian Farms: A

Review

6th International

Conference on


& Communication

Systems (NCCS-2019)


RanchiSpringer ECE

35 Srikanta Pal

Designing of low noise

amplifier and voltage

controlled oscillator for

satellite receiver in ku band

5th International

Conference on


& Communication

Systems(NCCS-2019)


RanchiSpringer ECE

36 Srikanta Pal

A Biodegradable THz

Metasensor For Malignancy

Apoptosis


on Electrical, Electronics

and Computer Engineering

(UPCON)


RanchiIEEE ECE

37 Srikanta Pal

A THz Biodegradable Meta-

sensor For Malignant Cell

Drug Efficacy

Nanophotonics and

Micro/Nano Optics


2019 (NANOP 2019)


RanchiECE

38 Srikanta Pal

Fast Principal Component

Auto-Regressive Algorithm

for Estimation of Parameters

of Radar Interference Signal

IEEE International

Conference on Computing,

Communication and

Networking Technologies


RanchiIEEE ECE

39 Swati PrasadSpeaker Identification under

Adverse Conditions

American Physical Society

March MeetingInternational 2020

B. I. T. Mesra,

Ranchi

Conference

ProceedingECE

40 Sanjeet Kumar

Design of an Energy-

Efficient Cooperative MIMO

transmission scheme based

on Centralized and

Distributed Aggregations

Advances in

Computational

Intelligence, Advances in

Intelligent Systems and

Computing

International 2019ISBN: 978-981-13-

8222-2

B. I. T. Mesra,

RanchiSpringer ECE

Facial Expression Recognition using Convolutional

Neural Network and SoftMax function on Captured

Images

Ashish Deopa, Abhishek Sinha, Aditya Prakash, Rupesh Kumar Sinha

Electronics & Communication Engineering

Birla Institute of Technology, Mesra

Ranchi, India

Abstract - Facial Expression Recognition is an extremely

interesting topic of research owing to the uniqueness

attached to emotions of different humans. Deep Learning is

a novel zone within the domain of machine learning which is

exceedingly efficient in image classification problems.

Methods of Deep Learning, (CNN) Convolutional Neural

Networks in particular, have been used with great precision

for the purpose of feature extraction.

This paper categorizes each facial image into one of the

seven human emotion classes by making use of a specially

designed Convolutional Neural Network which employs four

subsequent sets of layers and a loss function. The model has

been trained and tested on the FER2013 data set from

the Kaggle Facial Expression Recognition Challenge, which

consists of 35,887, 48-by-48-pixel pictures of human faces,

which are grayscale in nature, each with a label of one of the

7 emotion categories. The model gives an accuracy of about

64%.

Keywords: Facial Emotion Recognition, Deep Learning, CNN,

Convolutional Neural Network.

I. INTRODUCTION

Facial expression is a perceptible manifestation of the

cerebral activity, physiology, psychology, temperament,

intentions and state of mind of a person. Facial

Expressions are vital for social interactions as they

provide cues and guide conversations. It is also an

essential mode of non-verbal communication, the study of

which can make lives easier for all human beings. David

Matsumoto declared that there are seven basic human

emotions, namely sadness, happiness, anger, surprise,

disgust, fear and neutral. and each term is a family of

connected emotions. [1] It has also been seen that it is

easier to differentiate between emotions which are

genuine than among those that are unfelt. Facial

Expression Recognition has continued to remain an

inspiring and challenging problem in computer vision and

continues to pique the interest of researchers because the

way in which people show their expressions varies and

this difference makes the objective of classification into

categories exceptionally tedious. Facial Expression

Recognition in computer vision because the difference in

people’s way of expressing Computer vision is a domain

that provides computers with instincts and intelligence

that is comparable to humans. It works towards training

computers to perceive things in the same way as humans

do, process that input and then provide the required

output. However, this is a rather tedious task.

The edge between the physical and the digital world is

continuously blurring. This has given rise to Human-

Computer interaction. These new modes of interaction

usually require the capture of the observable behaviour of

the user for which artificial perception techniques like

computer vision are useful. Vast strides in technology and

artificial intelligence have made Human-Computer

interaction very feasible and detection of human emptions

by machines is one of the most trending subjects that is

being researched. [2] Due to the vast applications of

emotion recognition in areas of Human-Computer

Interaction, various methods have been applied. Facial

expression recognition usually utilizes a three-tier training

involving Face Acquisition [3], Feature Extraction [4] and

Classifier Construction [5,6]. In [7], the writers proposed

four stages for recognition: face extraction, pre-

processing, principle component analysis (PCA) and

classification. Later, some works [8, 9] exhibited that

combination of facial feature extraction stage and

classifier construction stage can benefit the process of

emotion recognition. A model to evaluate facial

representation based on statistical local characteristics and

binary patterns was devised in [10]. Lajevardi et al. used

K-NN classifier to classify the selected features [11]. A

different technique was proposed in [12], which made use

of the 2-D discrete cosine transform, over the picture of

the face, as a feature detector and a constructive feed

forward neural network, with a concealed layer, as an

emotion classifier.

However, due to a surge in the availability of

computational power and increasingly huge training

databases to train and test the models, the machine

Proceedings of the Fourth International Conference on Communication and Electronics Systems (ICCES 2019)IEEE Conference Record # 45898; IEEE Xplore ISBN: 978-1-7281-1261-9

978-1-7281-1261-9/19/$31.00 ©2019 IEEE 273

Authorized licensed use limited to: Birla Institute of Technology. Downloaded on December 10,2020 at 10:55:09 UTC from IEEE Xplore. Restrictions apply.

Abstract— In this paper, a simple Inset fed Microstrip patch

antenna for ISM band on laminated paper-based substrate is

presented for the first time. Paper has emerged as one of the low

costs, flexible, eco-friendly organic substrate which is

extensively used for wearable body area network (WBAN)

applications. But, one of the most important drawbacks of

paper-based substrate is that, it is hydrophilic which degrades

the performance characteristics of the designed antenna. To

mitigate the problem of performance degradation due to

ambient humidity of the environment and prolong the lifetime of

paper-based electronics, the designed antenna is printed on the

paper-based substrate laminated with transparent sheet. The

design of the antenna requires the RF characterization of paper

with lamination in terms of dielectric constant and loss tangent.

Two methods, a cavity perturbation and a transmission line

method are utilized for RF characterization of the laminated

paper-based substrate. Finally, an inset fed microstrip patch is

designed for 2.4 GHz which covers ISM band in free space. Also,

its performance characteristics in the vicinity of human body

(human arm) is analyzed in terms of SAR which is found to be

within the SAR limit provided by FCC guidelines. The

simulation and measurement results are in good agreement

which confirms the characterization of substrate and the

designed antenna is suitable for body area network.

Index Terms— BAN, laminated Paper based Substrate,

transparent sheet, SAR, WLAN.

I. INTRODUCTION

In last few years, flexible electronics has emerged as an

attractive candidate for wearable body area network

applications. Several low-cost flexible substrates like cotton

textile, polyester, PET, denim, jute, wool, leather, rubber have

been mentioned in many researches for flexible electronics

[1-2].

In this decade, paper has emerged as one of the ultimate

solution for low cost flexible electronics due to its low profile

and conformability.[3] Many antennas have been reported in

recent years on paper based substrate like PIFA for WLAN

[4], Z shaped CPW fed monopole for GPS[5], RFID UHF

antenna [6-7] and GPS, Wimax, Hiperlan/2, WLAN [8-10].

Manuscript received 1st July, 2019 revised August 3rd, 2019.

S. Kumari is pursuing Ph.D from Department of Electronics and

Communication Engineering, Birla Institute of Technology, Mesra, Ranchi,

Jharkhand, India-835215. Phone: +91 9431591755, e-mail:

sakshi501@gmail

V. R. Gupta is working as professor in the Department of Electronics and

Communication Engineering, Birla Institute of Technology, Mesra, Ranchi,

Jharkhand, India-835215 e-mail: [email protected]

But none of the above has addressed the problem due to

humidity. The electrical characteristics of the paper is bound

to change, when humidity is absorbed by the paper. Hence in

the humid environment the characteristic of the designed

antenna will also change. In this paper the designed antenna is

proposed on the laminated paper based substrate. Lamination

of the paper avoids the absorption of the humidity by the

paper.

The design process requires the characterization of the

laminated paper. Two electromagnetic methods, transmission

line method [11-12] and cavity resonator method [13-14] are

utilized for the RF characterization i.e. dielectric constant (εr)

and loss tangent (tan δ) of the paper and the transparent sheet.

Transmission line method characterizes the substrate over the

range of the frequency, whereas the resonant method gives

more accurate results at a particular frequency.

II. MATERIAL CHARACTERIZATION

The material characterization of paper has already been

performed by many researchers in recent years using and

transmission line method [11-12.], cavity perturbation method

[13-14], T resonator [15], ring resonator method [16] But as

Paper is an unconventional substrate with its wide accessibility

of different types that varies in texture, coating, thickness,

density including its relative permittivity and loss tangent.

Therefore, its electromagnetic characterization (dielectric

constant and loss tangent) is an essential step prior to any

on-paper antenna design. Moreover, the transparent sheet

used for laminating the paper substrate also need

characterization.

A. Cavity Resonator Method

The first method that is adopted for material characterization

is cavity resonator method which gives exact values of relative

permittivity and loss tangent at desired frequency. The

measurement set up consists of vector network analyzer

(VNA), and 85071E Split post dielectric resonators (SPDR).

The measurement of dielectric properties involves the

measurement of resonant frequency and quality factor of an

unloaded cavity (empty) and loaded cavity with material under

test. The cylindrical shaped solid sample of paper is prepared

and used for test. The dielectric constant of material under test

(MUT) is calculated on the basis of variation in volume,

frequency and Q-factor. Fig. 1 demonstrates the measurement

set up for dielectric characterization of paper substrate.

The formulas used for the material characterization are as

follows [17]:

Real part of the dielectric constant is:

S. Kumari, Member IAENG and V. R. Gupta

Characterization of Laminated Paper based

Substrate for the ISM Band Antenna Design

Proceedings of the World Congress on Engineering and Computer Science 2019 WCECS 2019, October 22-24, 2019, San Francisco, USA

ISBN: 978-988-14048-7-9 ISSN: 2078-0958 (Print); ISSN: 2078-0966 (Online)

WCECS 2019

Multiband Antenna Design for Smartphone Covering

2G, 3G, 4G and 5G NR frequencies

Arumita Biswas

CMTS Department

BSNL

Kolkata, India

Vibha Rani Gupta

Department of Electronics & Communication Engineering

Birla Institute of Technology, Mesra

Ranchi, India

Abstract—This paper proposes a novel compact MIMO

antenna that can work over frequency ranging from 1.65 GHz to

4.3 GHz. The non-uniform monopole radiating elements have

been designed to cover 2G, 3G, LTE and 5G New Radio frequencies. The identical antenna elements are placed over the

non-ground area and require no additional decoupling structure

for isolation improvement as mutual coupling between the

elements is well below the threshold. FR4 substrate with

dielectric constant 4.4, thickness 1.6mm and loss tangent 0.02 is used as ground with dimension of 120mm x 65 mm. IE3D

simulation software is employed to optimize the designed

antenna. Antenna characteristics including return loss, gain and

radiation pattern are discussed for bands under consideration.

The diversity performance is calculated and found much better

than industrial standards.

Keywords—ECC; Long Term Evolution; monopole; multiband

antenna; 5G New Radio

I. INTRODUCTION

Mobile communication industry is experiencing huge

transformation with every passing day. New generations and standards are being developed in order to provide voice, data

and multimedia services at enhanced speed to the registered subscribers. The introductions of new wireless technologies

and growing user demands have encouraged mobile industry to

shift from 2nd

Generation to 4th

Generation [1]. At World Radio communication Conference 2015 a decision was taken to

allocate 3.4 GHz – 3.6 GHz (3.5 GHz C band) for future broadband mobile service, for 5G beam-forming and for 5G

multi-antenna structure [2]. This encouraged service providers to use this band for future 5G system in-order to achieve an

easy roll-out [3].

The 5th

Generation of mobile communication requires lower latency, reduced energy consumption and higher data

rate. MIMO antennas, with multiple antennas at transmit and receive end aids to provide this solution by enhancing the

channel capacity [4]. Theoretically the capacity of MIMO antenna system should enhance linearly to the number of

identical antenna elements however due to correlation between the closely spaced antenna elements the enhancement gets

affected [5]. Hence MIMO antenna design for Smartphone

with restricted size imposes great difficulty for antenna designers.

Presently mobile communication network is a

heterogeneous network that offers subscribers to toggle between 2G/3G/4G networks on basis of available signal

strength. Hence it is essential that the antenna system for future Smartphone should be designed to support frequencies of all

the mobile generation standards. Several researchers have

contributed in designing antenna for 5G bands [1-4], [7-10]. However while most of the researchers have focused on

designing antenna for only one particular generation few have designed to include 4G and 5G bands only [1], [6]. In this

paper a single planar antenna structure in MIMO configuration is designed to work over 2G, 3G, 4G and 5G NR frequencies.

This will aid subscribers to avail undisrupted service even when signal strength reduces for particular mobile generation

in an area. Table I lists the mobile communication standards

that can be supported using the proposed antenna.

II. DESIGN DETAILS

The resonant length of planar monopole antenna can be

computed using the following equation,

𝐿 = λ/4 = c/4f√ (1)

where,

f= resonant frequency in Hz,

c = velocity of light = 3 x108 m/sec

λ = wavelength and

εr = dielectric constant

For designing the antenna to work over multiple mobile

generations two bands were taken into consideration – the first ranging from 1.4 GHz to 2.7 GHz with centre frequency at 2.05

GHz that would cover 2G, 3G and 4G frequencies and second band from 3.4 GHz to 4.2 GHz with centre frequency at 3.8

GHz that would cover 4G and 5G bands. Using (1) monopole length for each centre frequency was computed and obtained as

17.44 mm and 9.4 mm respectively. These two monopoles

were superimposed to result in a single non-uniform planar monopole element. Optimization technique was employed

using IE3D simulation software and finally the antenna dimension selected was: L1= 10mm, L2=7mm, W1= 8mm,

W2=6mm, G=3mm. This antenna was printed on the non-ground area. FR4 substrate with dielectric constant 4.4 and loss

Proceedings of the Third International Conference on Trends in Electronics and Informatics (ICOEI 2019)IEEE Xplore Part Number: CFP19J32-ART; ISBN: 978-1-5386-9439-8

978-1-5386-9439-8/19/$31.00 ©2019 IEEE 84


Paper Based Conformal Antenna

Shivali Singh Sakshi Kumari Vibha Rani Gupta

Department of E.C.E, Department of E.C.E, Department of E.C.E,

Birla Institute of Technology, Birla Institute of Technology Birla Institute of Technology

Mesra, Ranchi, Jharkhand Mesra, Ranchi, Jharkhand Mesra, Ranchi, Jharkhand

[email protected] [email protected] [email protected]

Abstract—This paper presents the design of a conformal

antenna on one of the most attractive, flexible, low cost, easily

available substrate i.e. paper for 5.2 GHz wireless local area

network (WLAN) band. The extraction of the substrate

characteristics such as the dielectric constant and dielectric

loss is performed using the cavity perturbation technique. The

flat substrate is bent with different radii and the effects of

curvature are studied and analyzed in terms of return loss,

bandwidth, gain, and radiation pattern.

Keywords— Paper based Substrate, WLAN, Conformal antenna

I. INTRODUCTION

In recent years, innovation in wireless communication has

enabled the design and development of intuitive and compact

devices. Wearable antennas are the most popular researched

antenna in recent years. They have many applications in

wearable electronics, defense, automobile industry, satellite.

In Body Area Network (BAN), wearable antenna plays a

significant role [1]-[3]. Important aspects of the design of an

antenna are cost-efficient, low profile and lightweight.

However, in practical applications, wearable antenna faces

many challenges. When a person moves, it is very strenuous to

maintain an antenna flat on the body. Hence the antenna

should be flexible, can be bent and made conformal to any

surface and at the same time, the performance of the antenna

should not be disturbed [4]-[6]. In order to design a flexible

and conformal antenna, a flexible substrate is used in a place

of a rigid substrate. Conformal antenna resists mechanical

strain up to a certain limit which depends on substrate material

[7]-[10]. In this work, the paper is used as a flexible substrate

to design an antenna for WLAN band and analyzed under

different bending conditions.

II. ANTENNA DESIGN

The approach towards the design of wearable conformal antenna starts with the characterization of paper as a substrate. Paper is eco-friendly, recyclable and cheaper. There is a wide variety of paper available in the market so its dielectric properties need to be characterized prior to antenna design. The cavity perturbation method is used for material characterization [11]-[12]. The dielectric constant and loss tangent is found 2.82 and 0.035 respectively for 1.6mm thick paper at 5.2 GHz.

A. Planar Microstrip Patch Antenna

The most common configuration rectangular radiating patch

is used because of their ease of fabrication, simplicity in

modelling, low cross polarization and especially attractive

radiation characteristics [13]-[14]. The proposed rectangular

conducting patch of size Wpatch × Lpatch is printed on the one

side of the substrate of dimension Wsub × Lsub and conducting

ground plane of dimension Wg × Lg on another side. Inset fed

is used of dimensions Wf × Lf to excite the radiating patch.

Fig.1 shows the geometry of proposed antenna design and the

optimized dimensions are tabulated in Table I.

Fig.1. Proposed Antenna Design

TABLE I. Dimensions of Antenna

Antenna Parameter Dimensions(mm)

Substrate Width (Wsub) 30

Substrate Length (Lsub 26

Patch Width (Wpatch) 18.8

Patch Length (Lpatch) 16.7

Ground Width (Wg) 30

Ground Length (Lg) 26

Feed Length (Lf) 11

Feed Width (Wf) 4

Inset Gap (Ig) 0.5

Inset Length (Li) 5.2

Inset width (Wi) 5

Proceedings of the Third International Conference on Trends in Electronics and Informatics (ICOEI 2019)

IEEE Xplore Part Number: CFP19J32-ART; ISBN: 978-1-5386-9439-8

978-1-5386-9439-8/19/$31.00 ©2019 IEEE 170


12/14/2020 Propagation Characteristics of SIW and Waveguide: A Comparison | SpringerLink

https://link.springer.com/chapter/10.1007%2F978-981-15-7486-3_50 1/6

Propagation Characteristics of SIW andWaveguide: A Comparison

Nanoelectronics, Circuits and Communication Systems pp 551-559 | Cite as

Sheelu Kumari (1) Email author ([email protected])Vibha Rani Gupta (1) Shweta Srivastava (2)

1. Department of Electronics and Communication Engineering, Birla Institute ofTechnology, Mesra, , Ranchi, India2. Department of Electronics & Communication Engineering, Jaypee Institute ofInformation Technology, , Noida, India

Conference paperFirst Online: 18 November 2020

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Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 692)

Abstract

Substrate-integrated circuit (SIC) technology has provided the most successful solutionsfor microwave and millimeter wave technology and expected to be the only technologyuseful in terahertz frequency range. Substrate-integrated waveguide (SIW) has proveditself the most used guided-wave structure in this technology, but includes one additionalloss called leakage loss along with the other two losses found in conventional waveguides,i.e., dielectric loss and conduction loss. In this paper, different losses found in SIWs andconventional waveguides operating in different frequency bands from C band to K bandare calculated and compared. It is found that the total losses in SIWs are comparable tothat for the waveguides. Propagation characteristics of both the structures are found tobe almost same. HFSS software is used to simulate the designed structures.

Index Terms

Conduction loss Dielectric loss Leakage loss Propagation characteristic

Substrate-integrated waveguide Waveguide This is a preview of subscription content, log in to check access.

References

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4. Analysis of NOMA: In Capacity Domain Saurabh Srivastava, Dept. of EC, BIT, Mesra, Ranchi, India [email protected] Prajna Parimita Dash, Dept. of EC, BIT, Mesra, Ranchi, India [email protected]

Sanjay Kumar, Dept. of EC, BIT, Mesra, Ranchi, India [email protected]

ABSTRACT

Non-orthogonal multiple access (NOMA) is supposed to be used for forthcoming 5G cellular networks. In this paper, the expressions for the channel capacities for symmetric and asymmetric NOMA networks have

been analyzed. The performance measure of user spectral efficiency and the sum-rate bounds, for the NOMA and the existing OMA networks have been compared. Furthermore, analysis of user rate and capacity of

NOMA network has been carried out and observed that the NOMA capacity region varies as a function of the power allocation factor. The corresponding models have been developed for both uplink and downlink, and

simulated with MATLAB. The experimental results show that even in the symmetric channel conditions, NOMA is able to perform and provides the same spectral efficiency as OMA.

Keywords—OMA, NOMA, rate-region, spectral efficiency, power allocation factor

INTRODUCTION

The mobile communication has come through various generations over a little span of time. The motivating factor for every next generation is marked with higher user data rate and enhanced user service. Though the current 4G cellular standard provides a high data rate, the requirement of highdata rate is massively increasing. Moreover, the variety of user services such as massive machine type communication (mMTC), ultra-reliable low latency communication (URLLC) and enhanced Mobile Broadband (eMBB) demand new architectures and configurations for the upcoming 5G cellular services.

It is also expected that the number of connected devices to reach 29 billion by 2022 [1], out of which 1.5 billion would be Internet of Things (IoT) devices. These massive connections characterize high connection volumes as well as small data traffic volumes and on the other contrary, they require ultra-reliability, availability, low latency high throughput etc. The current 4G cellular is not able to fulfil these diverse requirements, as the 4G vision is centred on cellular mobile and not focused on these diversified cases. Thus, 5G has to come up with the solutions to the above cases. The next generation mobile networks (NGMN) alliance provides the vision for 5G, while discussing these cases [2]. Specifically, it mentions the improvements required in spectral efficiency of the cell (bps/Hz/cell) and user spectral efficiency (bps/Hz/user) for supporting the massive connectivity between users as well as devices.

The major objective in the cellular generations has been to achieve a larger user capacity, and inturn a larger sum-capacity. A large sum-rate signifies an efficient network by maximizing each user’s throughput to its capacity. So, the objective across the generations has been to maximize the sum-rate. Moreover, the 5G network is also supposed to cater a number of other key performance indicators such as a reduced latency (user-plane) of about 1 ms for eMBB and URLLC applications; and energy efficiency in eMBB use case [3]. The above performance indicators suggest a new waveform design or specifically a multiple access scheme that provides a higher spectral efficiency, high energy efficiency, lower latency, more user-fairness and massive connectivity for device to device communication and IoT.

Since the waveform design has been the most fundamental aspect of the physical layer, the signalling and multiple access formats have significantly changed over the cellular generations. The analog Frequency Modulation (FM) and Frequency Division Multiple Access (FDMA) based 1G systems got transformed into a digital Time Division Multiple Access (TDMA)/FDMA based 2G systems. The focus of all the global 3G systems was on Code Division Multiple Access (CDMA).Further, due to increasing bandwidth requirements Orthogonal Frequency Division Multiple Access (OFDM) that was adopted in 4G, as (Orthogonal Frequency Division Multiple Access (OFDMA). OFDM offered several advantages compared to its predecessors, like

Animal tracking in wildlife footage with QuantumParticle Filter (QPF)

Prajna Parimita DashDept. of ECE

Birla Institute of Technology, MesraRanchi,India

[email protected]

Sudhansu Kumar MishraDept. of EEE

Birla Institute of Technology, MesraRanchi,India

[email protected]

Dipti PatraDept. of Electrical EngineeringNational Institute of Technology

Rourkela, India

[email protected]

Abstract—Animal behavior analysis in wildlife footage is apreoccupying domain in the society of wildlife biologist. Inwildlife video, tracking of a particular animal in a herd isvery challenging task due to its unpredictable motion, as wellas analogous appearance with others. In order to deal with theseissues, in the work we have proposed a maneuvering trackerthat uses the notion of quantum measurement in Particle filter.The proposed Quantum Particle Filter (QPF) based trackingtechnique efficiently handles the abrupt motion of the animalin a video. Subjective and objective evaluation of the proposedmethod has been accomplished and compared with other state-of-the-art methods. Some wildlife videos from the publicly availablebenchmark data sets are used for experiments. The results showsthe superiority of the proposed method over others.

Index Terms—Animal tracking, Particle filter, Quantum Par-ticle Filter

I. INTRODUCTION

Study and analysis of animal behavior and their habitats

remain a key interest of many environmental scientists and

wildlife biologists from several decades. In this domain,

tracking a single or many animals in a wildlife footage is an

abetment step. Tracking of an animal, wandering in a herd is

very challenging due to its unpredictable motion and behavior.

Partial and total occlusion, analogous appearance with other

members of the herd etc. escalate the difficulty in tracking.

In visual object tracking, the estimation and localization of

the position and motion of the target object, in the subsequent

frames is the most crucial task. The prime objective of the

tracker is to generate the trajectory of an object over time,

by localizing its position in every frame of the video. The

task of detection and tracking is accomplished by jointly

estimating the object region and its correspondence. Statistical

correspondence is an effective approach, which figures out

the tracking problem as a state estimation problem by taking

the model uncertainties and measurements into account. The

statistical methods use the state space approach to model

the object properties like position, velocity, acceleration etc.

The most popularly used statistical approaches for object

tracking are the Kalman Filter (KF) [1] and Particle Filter

(PF) [2]. KF works with the linear Gaussian model where the

estimation of state is performed by computing the parameters

of the posterior in a recursive manner. But, in many real

time applications, the object state is not Gaussian and the

estimation with KF is not acceptable. Furthermore, posteriors

in computer vision are never unimodal. In such scenario, the

state estimation is performed using PF.

The rest part of the paper is organized as follows. Section II

includes the related work, section-III contains some prerequi-

site to the proposed work. In section-IV Proposed method has

been described briefly followed by the experimental results in

section-V. The conclusion is presented in section VI.

II. RELATED WORK

The uncertainty associated with the visual data together

with the uncertainty associated with the target′s dynamics [3]

is a major difficulty in visual tracking. In contemplation of

these uncertainties, Recursive Bayesian Filtering (RBF) is a

potential approach, that continuously estimates the posterior

probability density function (pdf) over the parameter space of

the target model [4]. The mean of the posterior is taken as

the estimate of the target′s state, i.e., the position. The first

solution to the Bayesian estimate approximates the posterior

by a single mode Gaussian distribution is the Kalman Filter

(KF) [5]. The KF has been adopted extensively in various

object tracking problems in the past decades [6]–[10]. In

[11], Baxter et al. proposed the Extended Kalman Filter

(EKF), by combining the motion information along with a

prior assumption about the person’s position. However, these

approaches are limited to the constraint that the posterior need

to be uni-modal and in some cases, distribution has to be

Gaussian. These constraints usually violated in visual tracking

problems.

Particle Filter (PF) is a potent solution to the aforesaid

problems of KF in the field of tracking and is extensively used

by many researchers [12]–[14]. In PF the approximation of the

posterior distribution in each step is carried out by multiple

weighted particles. Therefore, PF based trackers are included

in Multiple Hypothesis Trackers (MHT) family. Afterward,

the posterior is computed through two steps: sampling, and

propagating the particles through the dynamic model and

weight updating according to the appearance of the target

object.The variance of the estimated state, number of particles

and the strategy of allocation determine the performance of

the tracker. As a consequence, more number of particles, and

effective strategies for particle allocation are the requisites


12/14/2020 Design of a 2–30 GHz Low-Noise Amplifier: A Review | SpringerLink

https://link.springer.com/chapter/10.1007/978-981-15-7486-3_64 1/5

Design of a 2–30 GHz Low-NoiseAmplifier: A Review


Krishna Datta (1) Email author ([email protected])Srikanta Pal (1) Vijay Nath (1)

1. VLSI Design Group, Dept. of Electronics and Communication Engineering, BirlaInstitute of Technology, , Mesra, Ranchi, India


28 Downloads


Abstract

LNA is the first component after an antenna in any RF receiver system and thereforeplays a key role in determining most of the key parameters of the RF receiver like noisefigure, gain, linearity, and stability. For designing an LNA, its effect on every of theseparameter has to be kept in mind. In this paper, the steps of designing a wideband LNAin the RF band 2–30 GHz have been studied with references from various previous worksdone on wideband LNAs and some application-based approaches on the discussed band.The technology studied has been restricted to Cadence CMOS technology.

Keywords

LNA Wideband UWB ZigBee Bluetooth Topology This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

A piece of thanks goes to Prof. M. K. Mishra, Vice-chancellor, BIT Mesra Ranchi forproviding us with infrastructure and facility to carry out the research work.






12/14/2020 Ad Hoc Network Using UAVs in Indian Farms: A Review | SpringerLink


Ad Hoc Network Using UAVs in IndianFarms: A Review


Shivanta Sahoo (1) Email author ([email protected])Yash Gupta (1) Vijay Nath (1) Srikanta Pal (1)

1. Wireless Communication, Department of ECE, B.I.T. Mesra, , Ranchi, India


27 Downloads


Abstract

Agriculture is repeatedly affected by threats like wild animals, insects, droughts andfloods. It is important to safeguard the farmland from various natural disasters andmaintains the quality of crops to meet the consumer demand. For this purpose, theGovernment of India (GOI) has presented a number of rural plans all through the nationto assist the agriculture sector. The farmers need to monitor their crops to ensure thefinal product is undamaged and well grown. With the help of UAVs, the informationrelated to the farmland could be gathered and sent to the farmer from time to time. Butmany of the Indian farms are located in deep remote areas with erratic geographicalconditions where telecommunications or Internet services are difficult to maintain. So,the motivation of this research is to provide the farmers of our country with properaccess to communication and monitoring farmland by using UAVs connected together byan ad hoc network. The ad hoc network will be able to maintain direct line of sightcommunication with uninterrupted connectivity in hilly areas and mountains. Theseconnected UAVs can scan the crops and act as surveillance from intrusions.

Keywords

Agriculture Ad hoc network Unmanned aerial vehicles (UAV)

Communication technologies Download conference paper PDF





https://link.springer.com/content/pdf/10.1007%2F978-981-15-7486-3_65.pdf

12/14/2020 Designing of Low-Noise Amplifier and Voltage-Controlled Oscillator for Satellite Receiver in Ku Band | SpringerLink


Designing of Low-Noise Amplifier andVoltage-Controlled Oscillator for SatelliteReceiver in Ku Band


Vishnu Anugrahith Sateesh (1) Sanjay Kumar Surshetty (1) Email author ([email protected])Vidushi Goel (1) Deepak Prasad (1) Vijay Nath (1) Srikanta Pal (1)

1. Department of ECE, Birla Institute of Technology, , Mesra, India


29 Downloads


Abstract

In this project, design of low-power Ku band CMOS voltage-controlled oscillator andlow-noise amplifier for satellite communication is proposed. The proposed LNA provideslow input impedance, low noise figure, and high gain which makes it suitable for use insatellite receivers to amplify low-power signals. This NMOS LC VCO has main advantagein low phase noise and low power. This VCO is designed on concept of negativeresistance generated by MOSFETs impedance which reduce the phase noise. This circuitis designed using UMC 90 nm CADENCE ADE. For this circuit, we use 1.2 V powersupply. Its average phase noise is −109.18 dBc/Hz at 1 MHz offset. The oscillator requiresapprox. 0.001127 of chip area. It is highly useful for satellite communication.

Keywords

Low-noise amplifier Noise figure NMOS LC VCO MOSFETS Phase noise Power

Offset This is a preview of subscription content, log in to check access.

Notes

mm2






BER Performance of OFDM based hybrid PLC-VLC system

Ajit Kumar Dept. of Electronics & comm.

Engineering Birla Institute of Technology, Mesra

Ranchi, Jharkhand [email protected]

S.K.Ghorai Dept. of Electronics & comm.



Atanu Chaudhury Dept. of Electronics & comm.



Abstract: In the present paper, the BER performance of integrated power line communication Multiple-input multiple-output visible light communication (PLC-MIMO-VLC) system has been analysed using OFDM modulation technique. The Orthogonal Frequency Division multiplexing (OFDM) technique has been used to mitigate the effect of impulsive noise and Intersymbol interference (ISI) introduced due to multipath propagation in PLC system. The simulation has been done for two scenarios using Line-of-sight (LOS) and LOS plus first reflection (L-R1) signals in MIMO-VLC channel. In the scenario 1, the separation between LED is taken as 0.6m and in scenario 2, the separation is 0.2m. For scenario 1, it has been found that for BER of 10-5, the LOS signal outperforms L-R1 signal by a gain-margin of 15 dB in SNR. For scenario 2, the BER increases by a gain margin of 20 dB and 6 dB for LOS and L-R1 signals respectively as compared with scenario 1.

Keywords: PLC, OFDM, MIMO, VLC, BER

I. INTRODUCTION

In the past few years, there has been rapid increase in the number of users for high speed voice, video and data transmission. However, the existing power line infrastructure and unregulated license-free bandwidth of visible light communication when integrated prove to be ubiquitous in fulfilling these demands. This integrated hybrid PLC-VLC (HPV) system has triple advantages of illumination along with power and data transmission.

Though PLC has been an emerging field of communication in home area network of smart grid, still there are lots of challenges due to additive and multiplicative noises in the PLC system. Additive noises mainly include background noise and impulsive noise. The multiplicative noise leads to fading in the received signal strength. Since SNR is one of the metric to measure the relative power of noise compared to signal hence it is used to predict the performance of the system. The correctness of the system in digital communication system is measured using bit error rate (BER) by deciding whether received bit is erroneous or not.

In [1], authors have studied the effect of Rayleigh fading over the BER performance of the PLC system in

the presence of Nakagami-m additive noise. They have derived BER expression for Rayleigh fading PLC channel and verified the theoretical results with the simulated BER results. In the environment where channel is interfered by impulsive noise, OFDM can perform better than single carrier system because it spreads the effect of impulsive noise over multiple symbols due to discrete Fourier transform (DFT) algorithm. In this context, it is necessary to consider OFDM in BER analysis for HPV system. For broadband PLC, the BER performance of the OFDM system has been theoretically investigated by deriving a formula for BER under the impulse noise and multipath effects [2]. They investigated that only heavily distributed impulsive noise would interfere the OFDM system and compared the adverse effect of multipath with impulsive noise. It has been found that in order to overcome the effect of multipath, large number of carriers are required with optimum guard interval. BER performance for 4×4 MIMO-VLC system has been simulated using LOS and LOS plus diffused signal under different spatial separation of transmitter and receiver [3]. It has been shown that not only LOS but higher order reflection signal should be considered as it has significant impact on BER performance. However, all these authors have not shown BER performance of integrated PLC-VLC system.

Authors in [4] have explored the possible application of hybrid broadband PLC and VLC system with OFDM modulation. They have shown a feasible demonstration which supports over 48 Mbps data rate within a bandwidth of 8 MHz using single LED. Ha. Ma et al. [5] have proposed hybrid PLC-VLC system utilizing spatial-optical (SO) OFDM technique. In their work, SO-OFDM was applied across multiple luminaires to overcome inter-luminaire interference which improves the signal-to-interference-plus-noise ratio (SINR) at the user. In [6], an estimation of the magnitude of transfer function ofcascaded PLC-VLC channel has been done using Welch method. For an inter-building scenario, BER performance of hybrid PLC-VLC system has been investigated using phase shift keying (PSK) mapping in PLC and color shift keying (CSK) in VLC system [7]. In their work, they have investigated the BER performance by varying the

This research work is sponsored by University Grants commission (UGC) fellowship.


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Performance of MIMO-VLC System for Different Radiation Patterns of LED in Indoor Optical wireless

Communication SystemAjit Kumar

Electronics & comm. Engg. Birla Institute of Technology, Mesra


S.K.Ghorai Electronics & comm. Engg.

Birla Institute of Technology, Mesra Ranchi, Jharkhand

[email protected]

Abstract- In the present paper, bit error rate (BER) performance of multiple-input multiple-output MIMO-visible light communication (VLC) system has been investigated using three different distinct radiation patterns of LED for a room of size 5m×5m×3m. Two different scenarios have been considered for BER performance analysis using line-of-sight (LOS) and LOS plus first reflection (L-R1) signals. In the first scenario, the four PDs of 4×4 MIMO system are kept at the centre of the room whereas in the second scenario the Photodetectors (PDs) are placed at the corner of the room. For LOS signal in the scenario-1, the BER for Lambertain and Batwing radiation pattern LEDs are same whereas using Elliptical it is less than those patterns. For L-R1 signal in scenario-1 and scenario-2, the BER using Batwing is least followed by Lambertian and then Elliptical. The BER performance using all three radiation patterns are same using LOS signal for scenario-2.

Keywords- Radiation pattern, MIMO, VLC, BER

I. INTRODUCTION

The light emitting diode (LED) is the present most energy efficient and rapidly developing lighting technology which has led to the emergence of visible light communication (VLC) as a promising technique for high speed indoor wireless communications. Unlike traditional lighting sources, the LEDs last longer, are more durable and have better lighting quality. Though LED emits light in a specific direction, reducing the need for reflector and diffuser but from communication point of view, they must be reflected to the desired direction. In this context, different types of radiation pattern of LED have been discussed in [1-2]. The rapid development of LED technology and improved manufacturing efficiency have motivated the researchers to explore different types of radiation pattern like Elliptical, Batwing etc. apart from the already existing Lambertian radiation pattern.

However, in spite of so many advantages, LED has one drawback of limited modulation bandwidth which becomes hindrance for high data rate transmission in VLC system. To sort out this limitation, MIMO system is implemented where different lights transmit different information [3]. This

improves the overall data rate, reliability of transmission and lighting coverage area inside the room.

The important aspect in VLC system is that signal from LED reaches the photodetector through not only LOS but also NLOS path. Since the signal strength of NLOS signal is weak as compared to LOS signal and therefore maximum workers exclude it in their research analysis. But NLOS signal can’t be excluded due to the fact that there are many practical scenarios in which unobstructed optical path may not be available due to various room configurations. The intersymbol interference caused by multiple reflections becomes hindrance for high bit rate system. Hence for complete analysis, NLOS along with LOS component should be considered to determine SNR which is used to to predict the performance of the system.

There are many research works in which BER performance of MIMO-VLC system has been investigated. Shangyu et al. [4] have demonstrated the feasibility of a LMS-volterra based joint MIMO equalizer for indoor VLC system. They have successfully achieved a data rate of 1.26 Gb/s for a transmission distance of 1m with BER below 7% FEC limit of 3.8×10-3. Srinivas et al. [5] have proposed optimal precoder and diagonal precoder for MIMO-VLC system to reduce the channel correlation. It has been shown that 2.4 dB less SNR is required to achieve 10-5 BER by optimal precoder as compared to diagonal precoder. The BER performance of 4×4 MIMO system using LOS and LOS plus diffused signal has been investigated [6]. It has been shown that the higher order reflection shows more significant change in BER performance as compared to LOS signal.

However, all these research works have been carried out using only Lambertian radiation pattern of LED. Deohao et al. [7] have proposed tuned elliptical Lambertian beam of LED. From simulated frequency response, they found that the elliptical beam offers higher transmission bandwidth than circular Lambertian beam. Yinlu et al. [8] have investigated the impact of LED’s radiation pattern on received power inside the room. It has been observed that that LED with sharp radiation pattern has bigger received power variation. Jupeng et al. [9] have investigated on coverage area, optical path loss, RMS delay spread, impulse and frequency response using three types of distinct radiation pattern Lambertian, Elliptical

This research work is financially supported by University Grant commissionfellowship

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Design Simulation and Analysis of a Polarization-Independent Ultrathin Pixelated Metasurface Absorber

Manish Mathew Tirkey #1 and Nisha Gupta #2, Senior Member, IEEE #Department of Electronics and Communication Engineering, Birla Institute of Technology

Mesra, Ranchi 835215, India [email protected] [email protected]

Abstract — A polarization independent, ultrathin, planar, and conformal microwave absorber is presented for X-band application. An efficient metasurface absorber comprising of an array of pixelated unit cells over a grounded lossy substrate is designed using a simple simulation-driven approach. Subsequently, the absorption mechanism of the proposed absorber is demonstrated by means of straightforward analytical expressions derived from the transmission line approach. Finally, the equivalent circuit model is validated by performing the simulation of the lumped equivalent circuit of the absorber. The notable features of the proposed absorber are its design on a λ0 154⁄ (0.177 mm) ultrathin substrate and its absorptivity characteristics of over 94% at 11.03 GHz for all angle of polarization. Also, the proposed absorber maintains more than 80% absorptivity up to 45° incident angle and demonstrates its suitability for conformal applications.

Index Terms — conformal absorber, lumped equivalent circuit model, metasurface, microwave absorber, polarization independent, ultrathin.

I. INTRODUCTION

The magnificent evolution of metamaterials has evoked an astonishing attentiveness on thin electromagnetic (EM) wave absorbers [1] attributing to the inflated practical applications. The implementation of thin absorbing structures is essential for shrinking the radar signature of targets, alleviating electromag-netic interference (EMI), and solving electromagnetic compatibility (EMC) issues, as well as for its utilization in power imaging, Radio Frequency Identi-fication (RFID), and many more applications [2], [3]. The most effective EM absorber designs are fabricated by considering a periodic array of resonant surfaces printed over a grounded dielectric substrate [4]. Perfect absorption can be achieved by suitably designing these resonant surfaces, and the absorption characteristics can be enhanced by introducing adequate losses in the structure. The undesirable wave reflections occurring at the top interface of the absorber can be avoided by matching the impedance of these resonant structures with the impedance of the free space at the resonance. Hence, a perfect absorber is realized when all incident EM energy is absorbed and dissipated in the form of thermal energy [4].

Use of conformal EM absorbers in the military and commercial applications has become one of the primary requirements in this modern electronic world. As a result, a large number of thin EM absorber designs have been studied in the last few years by exploiting metamaterial structures [5]–[8], metasurface

(MS) [9], frequency selective surface (FSS) [10], [11], and artificial impedance surface (AIS) [12]. Some of these structures are also designed by applying suitable topology optimization algorithms [13] for improved results. Several recent articles emphasized the use of resistive sheet [14] and lumped elements [15], [16] in place of printed metallic surfaces to realize a lossy thin absorber. However, the reduction of absorber thickness to the lowest possible level while maintaining other absorber characteristics such as polarization insensitivity and incidence angle independence has made this task even more challenging [17].

In this work, a metasurface absorber (MSA) is proposed to tackle the aforementioned problems by adopting a straightforward design methodology. The absorber is realized through an array of pixelated unit cells at the top of a grounded lossy dielectric substrate. The physical mechanisms of the MSA and its resonant absorption can be very well conceived by employing a transmission line model. Simple circuital model and the expressions for the lumped circuit elements of the MSA are derived by considering the effect of metal and dielectric losses of the material.

Fig. 1. Proposed pixelated design of the MSA.


Quantification of Cartilage loss for Automatic Detection and Classification of Osteoarthritis

using Machine Learning approachABHINAV KUMAR

ECE BIT MESRA, RANCHI

[email protected]

PRIYANK SAXENAECE

BIT MESRA, [email protected]

Abstract— Knee Osteoarthritis (OA) is musculoskeletal ailment and a measure cause of chronic disability. It is well known that the plain radiographs fail to detect the early OA changes and the best possible way to measure its progression is to quantify the articular cartilage loss. In this work, a computer aided diagnosis method using machine learning approach is proposed to predict knee OA severity from the radiographs based on the Ahlbäck grading scale. To achieve this objective, the loss of articular cartilage is quantified by measuring the minimum joint space width and is used for classifying OA to different classes. Different supervised classifiers such as KNN, SVM and Random forest are tested on Osteoarthritis initiative data set. KNN yields the highest accuracy among them. The results validates the effectiveness of the proposed method when compared with other existing methods and achieves an accuracy of 97%.

Keywords—Osteoarthritis, Articular cartilage, Machine learning, Medical Imaging, SVM, KNN, Random Forest.

I. INTRODUCTION

Osteoarthritis (OA) is a non-inflammatory, degenerative conditions of joints characterized by degeneration of articular cartilage [1]. The articular cartilage provides load balancing across the joints but altered forms of load spreading or theconditions that produce the increased load transfer speed upthe progress of osteoarthritis (OA). Articular cartilage is the thin tissue structure that turns into irregular shapes in advanced OA stages. Among the different types of osteoarthritis, the most common type is Knee OA and is the main reason of disability among the people [2]. An early knee OA diagnosis is crucial for clinical treatment to be effective but difficult in clinical practice. The plain radiographs failed to provide the progression of knee OA because the imaging modality uses two-dimensional projection and also degeneration of articular cartilage cannot be directly seen in plain radiographs [3].Eventually, the cartilage loss is indirectly estimated by joint space width and bony changes i.e. osteophytes as shown in figure 1.Other than aforementioned limitations of plain radiographs, OA diagnosis is also highly dependent on the subjectivity of the practitioner. Keeping this in view, the proposed computer aided diagnosis method using machine learning approach could be used an objective tool to support clinical decisions. Secondly, with increasing accuracy these methods can lead to

Figure 1: A normal knee and an affected knee joint by OA[4].

better diagnosis. To analyze knee OA some radiographic features such as joint space area (JSA), the minimum joint space width (MJSW) and osteophyte area are used. Among all, MJSW is the recommended feature. Kellgren & Lawrence(KL) and Ahlbäck grading systems are the two standard grading systems which predicts the knee OA severity on a five-point scale based on the assessment of joint space width[5] [6].

II. RELATED WORK

The existing state of the art methods provide image classification-based solutions to quantify the knee OA severity. These methods are primarily based on the study of anatomical structures such as deviations in joint space width or osteophytes formation to assess knee OA severity using radiography-based semi-quantitative scoring systems like KL grading [7] [8].Most of the existing state of the art methods perform localization of the knee joints before quantifying the severity. A multi-purpose medical image classifier uses a set of features based on texture, contrast, pixel-statistics and features from image transforms to automatically assess knee OA severity in radiographs. Manually controlled features for localizing the knee joints has been proposed [9]. Another method based on manually controlled features for self-assessment scoring system associating the risk factors and radiographic knee OA features using multivariable logisticregression models have been proposed which usesadditionally Artificial Neural Network (ANN) to improve theoverall scoring performance [10].Manually controlled features often simplify machine learning tasks but suffers few limitations. The manual approach of feature selection is often very time consuming and requires knowledge of a domain expert [11]. These features are

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Recognition of SSVEP-BCIs System Using EMD Based Threshold Detection Method

Mukesh Kumar Ojha1, Manoj Kumar Mukul2

1Research Scholar, Electronics and Communication Engineering, BIT Mesra, Ranchi, Jharkhand 835215, India.

Email: [email protected] 2Assistant Professor, Electronics and Communication Engineering,

BIT Mesra, Ranchi, Jharkhand 835215, India.

Abstract: Brain computer interface (BCIs) based on Steady state Visual Evoked Potential (SSVEP) receiving more attention currently because of high information transmission rate (ITR), reduced training period and simple design configuration than other EEG based BCI System. Accurate recognition of SSVEP from EEG signal is difficult task in BCI system. Plenty of frequency recognition based techniques are available to enhance accuracy for multichannel brain signal. At the same time, single channel SSVEP receives more attention due to its simplicity in usability and configuration. This motivates to evaluate the presence of SSVEP Signal from single channel EEG Signal. A non linear decomposition technique called Empirical mode decomposition with aim to extract the SSVEP Signal is applied on EEG Signal. The emd technique decomposes the EEG Signal into several oscillating wave called intrinsic mode function (IMFs).The IMFs in which SSVEP Signal is prominent, is considered for further evaluation. Finally, Fast Fourier transform (FFT) based threshold detection method is applied on IMFs in which SSVEP Signal is prominent to measure the detection accuracy and result is compared with conventional single channel power spectral density analysis (PSDA) Method. Key Words: Steady state Visual Evoked Potential (SSVEP), Brain computer interface (BCI), Empirical Mode Decomposition (EMD), Power Spectrum Density Analysis (PSDA), Intrinsic Mode Function (IMF). 1. INTRODUCTION Brain computer Interface (BCI) is a direct communication between human brain and external machine through which intention of brain signal is translated into certain command to control the external machine [1]. The most commonly used brain signal to design the BCI Systems is event related potential (ERP), P300 and Steady State Visual evoked potential (SSVEP) [2-4]. Due to the simple system configuration, less training time and high information transmission rate (ITR), SSVEP based BCI becomes more promising topic of research in the field of BCI system [10],[12]. Steady-state visual evoked potential (which can be recorded from the scalp over the visual cortex with maximum amplitude at the occipital region. SSVEP is Neuron response evoked over occipital region of brain with the same frequency as the repetitive visual stimulus. Brain produces electrical sinusoidal wave at same frequency of visual stimulus during retina excitation. With this concept, the SSVEP based BCI system uses multiple visual stimulus that flicker at different frequency simultaneously.

The subjects are required to focus on stimulus they intend to select, which elicits the corresponding stimulus frequency into recorded brain signal [3]. To recognize the frequency of SSVEP Signal, several frequency detection technique is widely investigated and reported into literature [2-12] either using multiple channels or using single channel in recent time. Multi-channel detection method such as canonical correlation Analysis (CCA), minimum energy combination and Independent component Analysis (ICA) make use of multichannel brain signals and covariance information of brain signal, result in high signal to noise ratio and hence improved detection accuracy [9-16].

However, the use of multi-channel signal leads the complexity in the implementation of real time BCI System. Thus, in order to reduce the complexity in implementation of real time BCI System,

Abstract— In this paper, we have implemented a special case of Blind Source Separation (BSS) algorithm i.e. AMUSE algorithm using Independent Component Analysis (ICA) methodology in addition with Empirical Wavelet Transform (EWT) to detect epileptic seizures in advance. The proposed method has been studied on EEG Signals obtained from CHB-MIT Scalp EEG Database. Here, we have extracted independent components and chose five components having the least standard deviation after applying BSS Algorithm. Decomposition of signals into epochs, each of two seconds, is performed and three features are extracted from each one second of the two second long joint instantaneous amplitudes and frequencies, which has been obtained after employing Hilbert-Huang Transform. The extracted features of different oscillatory levels have been processed and joint feature vectors have been computed using Hadamard product for better distinction between seizure and non-seizure instances. Two well-known classifiers, Random Forest and KNN has been applied with the help of WEKA software upon 4 patients which resulted in average accuracy of 99.46% with RF classifier and 99.32% using KNN classifier.

Keywords—Blind Source Separation, Independent Component Analysis, Empirical Wavelet Transform, Hilbert-Huang Transform

I. INTRODUCTION

Epilepsy is a chronic neurological disorder of the brain which is defined as having two or more unprovoked seizures. It arises when certain nerve cells in our brain misfire or they start firing in a synchronized manner. These seizures culminates in various stages from pre-ictal topostictal. The symptoms of seizures can vary from simple lapses of attention to muscle jerks and convulsions. To detect these seizures, EEG is generally preferred due to its high temporal resolution. The current statistics estimates approximately 70 million individuals suffering from epilepsy. Hence, an automatic seizure detection approach would lead to facilitation of the monitoring and therapy of epileptic patients in real-time. In [1], epileptic seizures are detected using the concepts of EWT and keeping in mind the multivariate and random nature of EEG signals. They have employed these concepts on multivariate synthetic signals, and also on multivariate EEG scalp database obtained from CHB-MIT. The proposed method develops time-frequency plane for multivariate signals and builds patient specific models for EEG seizure detection

Shoeb et al., in [2] devised a seizure detector and studied on EEG database taken from CHB-MIT. They passed two seconds long EEG signal epochs through eight filters having range of 0.5 to 25 Hz. Then, energy was measured at the output of each filter and feature vector was formed by measuring the energy of the output of each filter. Its accuracy was 96% with failure rate of 2 incorrect detections during one hour recording. Zabihi et al [3] devised a novel patient-specific seizure detection approach proposed based on the dynamics of EEG signals by employing phase space representation. Then, reconstruction of the trajectories of seizure and non-seizure segments is done. Later on, Principal Component Analysis (PCA) was used to reduce the dimension of phases and Linear Discriminant Analysis (LDA) for classification purpose.Utilization of adaptive signal decomposition techniqueshelps in decomposition of EEG signals into frequencybands which are also adaptive in nature. Recently, the concept of multivariate modulated oscillation has been proposed, for modelling the joint oscillatory structure [4].In [5], Osorio et al. employed the concept of band-passfilter which having finite duration response, which were wavelet based for seizure detection. They computed themedian of each EEG epochs, which were passed through a filter and a foreground sequences was generated. Later on, ratio calculation of foreground was done and compared with a predefined threshold in which they achieved 100 percent sensitivity.In this proposed work, BSS Algorithm [6] is implemented using AMUSE over all 23 channels since no exact knowledge is available of either the channel or the sources.This is performed with the help of Independent Component Analysis where independent components are found with the help of AMUSE algorithm. This algorithm deals with extraction of multiple unknown sources from a mixture by employing the concepts of Eigen Vector Decomposition. Here, 23 channels were chosen upon which AMUSE algorithm is employed to find the independent components of signal. Later on, these component values are arranged in ascending order of standard deviation values. After this operation, only 5 components are taken into further consideration. These signals are segmented into epochs of 2 second duration and empirical wavelet transform is applied to capture the non-stationary nature of EEG signal and. This helps in extraction of MODEs from each epochs to find the Fourier support spectrum and further to obtain joint instantaneous amplitudes and frequencies. Further, 3 features are extracted from each epochs belonging to different oscillatory levels.

IEEE - 45670

Early Epileptic Seizure Detection Satvika Anand, Dr. M K Mukul

[email protected],[email protected]

Electronics and Communication Department, BIT Mesra

Ranchi-835215



Abstract: Proper classification between normal and

Parkinson affected people is an important topic in recent

years. From the last two decades, the number of methods

has been proposed for the classification of Parkinson's

affected and healthy people. Most of them based on a

shallow structured network classifier. In this study stacked

auto-encoder deep neural network framework is

introduced to classify Parkinson affected and healthy

people voice signals. The present study uses a spectrogram

and scalogram of speech signals as input to the stacked

autoencoder deep network. The extracted features are

tested with a support vector classifier (SVM) and a

Softmax classifier. Highest classification accuracy of up to

87 % with a spectrogram and 83 % with scalogram are

obtained using Softmax classifier. The softmax classifier

performed better than SVM. The proposed deep neural

network may be a new window for further research.

Index term: Parkinson disease, stacked auto encoder, Time-

frequency image, STFT, CWT, deep learning.

1. INTRODUCTION

PD is a neurodegenerative disorder privileged in old age.

Millions of people worldwide affected by this disease [1]. The

people with PD have less control to utter their voice. In several

aspects, the voice signal is affected. Their voice becomes more

slurred, breathy, hoarse, or softer. In the medical field, these

speech changes are defined in terms of dysarthria (motor

speech), hyphophonia (weak voice) and tachyphenia(fast-

talking). The PD affected voice signal lost their irregularity.

Biswajit Karan is with the Birla Institute of Technology, Mesra, Ranchi

India (phone: 09470549164; e-mail: [email protected]).

Sitanshu Sekhar Sahu is with the Birla Institute of Technology, Mesra,

Ranchi, India (e-mail [email protected]).

Kartik Mahto is with the Birla Institute of Technology, Mesra, Ranchi

India (e-mail: [email protected]).

This effect can be detected using TF features. Several studies

have been conducted for the assessment of PD people. In this

study, various speech signal processing algorithm has been

utilized to extract useful features for PD assessment. These

features and various machine learning algorithms directly

affect the accuracy and reliability of the PD diagnosis system.

Most of the studies are based on the start of art acoustic

features [2, 3, 4], spectral and cepstral features[5,6], Empirical

mode decomposition based features, various and wavelet

features [7,8]. From all previous studies, it has been found the

most of the study based on the time domain, frequency

domain, or spectral and cepstral domain. A very view study

has been conducted based on TF frequency representation.

T.Villa-Canas et al [9] used TF based technique based on

Wigner Ville distribution and reported classification accuracy

72 % between Parkinson and healthy speakers. Convolution

neural network approach is presented by J. C. Vasquez-Correa

et al.[10] in three different languages. Autoencoder based TF

features concept for PD detection is introduced the first time in

this study. We proposed TF autoencoder based features which

effectively captures both time and frequency domain aspect of

the speech signal. The proposed autoencoder based TF

features are extracted using STFT and CWT based TF

representation (TFR). The extracted features from TFR

representation are fed into the Softmax classifier. We also

compare the extracted features using, SVM. According to the

results, the proposed approach provides the accuracies up to

87 % as compared to the SVM classifier. The study is steps

towards the robust classification of speech impairment.

Figure1: Proposed methodology

2. MATERIALS AND METHODS

Data Sources: In this work PC-GITA database [9] is used

which consists of a voice sample of 50 PD and 50 normal

people. All speakers are Colombian native speakers. The

database is well balanced in terms of age and gender. The

speakers performed different speech tasks, sustained

phonation, word, and monologue, read a text, sentence and

Stacked auto-encoder based Time-

frequency features of Speech signal for

Parkinson disease prediction

Biswajit Karan, Sitanshu Sekhar Sahu, and Kartik Mahto

Department of Electronics and Communication Engineering, Birla Institute of technology, Mesra, Ranchi

2020 International Conference on Artificial Intelligence and Signal Processing (AISP)

978-1-7281-4458-0/20/$31.00 ©2020 IEEEAuthorized licensed use limited to: Birla Institute of Technology. Downloaded on December 14,2020 at 09:45:37 UTC from IEEE Xplore. Restrictions apply.

2020 IEEE International Students’ Conference on Electrical, Electronics and Computer Science

978-1-7281-4862-5/20/$31.00 ©2020 IEEE

Boosting predictions of Host-Pathogen protein interactions using Deep neural networks

Satyajit Mahapatra, Sitanshu Sekhar Sahu Department of Electronics and Communication Engineering

Birla Institute of Technology Mesra Ranchi India [email protected], [email protected]

Abstract— The initiation of the infection process in a living organism starts with the interaction of host protein with the pathogen protein. So, the prediction of this host-pathogen protein interaction (HPI) can help in drug design and disease management strategy. Investigation of HPI by high-throughput experimental techniques is expensive and time-consuming. Therefore computational techniques have come up as an effective alternative for the prediction of these interactions. In this paper, a Deep neural network-based HPI prediction model is proposed. In the proposed technique first, the variable-length protein sequences are encoded into fixed-length input by using a Local descriptor based feature extraction method. These features are used as input to DNN based predictor. An exhaustive simulation study shows 91.70% and 87.30% accuracy on Human- Bacillus Anthracis and Human- Yersinia pestis datasets. Keywords— Infectious diseases, Host-Pathogen interactions, Machine learning, Deep neural networks

1. INTRODUCTION

In a living organism, protein-protein interaction (PPI) plays an essential role in carrying out numerous biological processes [1-3]. PPI’s can be categorized into intraspecies and interspecies interactions. The protein interactions within a single organism are called intraspecies PPI whereas the interaction between different organisms is called interspecies PPI [4]. The interspecies interactions are otherwise called as host-pathogen interactions (HPI). Many infectious diseases like Ebola, HIV, Plague, and Cholera are caused due to the interaction of the viral and bacterial pathogen with human hosts thereby causing millions of deaths every year. PPI can be predicted by using experimental and computational techniques. Identification of PPI using experimental techniques time-consuming and expensive. So computational techniques can be used as an effective alternative to predict the protein interactions. Several computational techniques especially deep neural network-based techniques have been proposed for the prediction of protein-protein interaction. DeepPPI [5] proposed by Du et al., uses a fusion of features and deep neural networks for the prediction of PPI. Zang et al. [6] have proposed an ensemble DNN (EsnDNN) for the prediction of protein interactions. The EsnDNN extracts information pattern from the local descriptor, autocovariance descriptor, and multiscale continuous and discontinuous local descriptor separately and fuses it for prediction. Hashemifar et al. [7] have proposed DPPI which used position-specific scoring matrix (PSSM) and convolutional neural network (CNN) for prediction of PPI. Wang et al. [8] have proposed a

fusion of CNN and feature selective rotation forest (FSRF) for the prediction of PPI. Patel et al. [9] have proposed a deepinteract for the prediction of PPI. All the above mentioned deep learning techniques have achieved 94.43%, 95.29%, 94.55%, 97.75% and 92.67% accuracy on the prediction of intraspecies interaction in Saccharomyces cerevisiae. None of the above techniques have been used for the prediction of intraspecies protein-protein interactions. Therefore it is necessary to develop a deep learning-based model for effective prediction of host-pathogen interactions (HPI). In this paper, a DNN based HPI prediction model has been proposed. The main contribution of the paper is outlined below The new DNN based architecture uses two separate

networks to extract the information contained in the raw features of host and pathogen proteins.

The fusion of extracted information provides a better representation as compared to the raw features.

2. MATERIALS AND METHODOLOGY

2.1 Materials For the development and assessment of model two interspecies datasets used by Kosesoy et al. [10]. The first dataset is the interaction between Human and Bacillus Anthracis, which contains 3090 positive and 9500 negative interactions. The second database consists of interaction between Human and Human- Yersinia pestis, which contains 4097 positive and 12500 negative interactions. The negative interaction pairs are generated by randomly pairing host and pathogen protein sequences for which no interaction exists. For designing any machine learning model an equal number of positive and negative samples are required [6]. So, the number of negative interactions same as the positive interactions are randomly selected from the total negative interaction set. The details of the combination of positive and negative interactions are given in Table 1.

TABLE 1 DETAILS OF THE STANDARD HOST-PATHOGEN

INTERACTION DATASET

Dataset Number of interacting

Pairs

Number of non-interacting pairs

Total PPI

Human-Bacillus [10]

3090 3090 6180

Human-Yesrinia [10]

4097 4097 8194

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12/14/2020 Effect of Dimensionality Reduction on Classification Accuracy for Protein–Protein Interaction Prediction | SpringerLink

https://link.springer.com/chapter/10.1007%2F978-981-15-1081-6_1 1/6

Effect of Dimensionality Reduction onClassification Accuracy for Protein–Protein Interaction Prediction

Advanced Computing and Intelligent Engineering pp 3-12 | Cite as

Satyajit Mahapatra (1) Email author ([email protected])Anish Kumar (1) Animesh Sharma (1) Sitanshu Sekhar Sahu (1)

1. Department of Electronics and Communication Engineering, Birla Institute ofTechnology Mesra, , Ranchi, India

Conference paperFirst Online: 19 February 2020

178 Downloads

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume1082)

Abstract

“Large Dimension” of features derived from protein sequences is a major problem inprotein–protein interaction (PPI) prediction. Thus, reduction of the feature dimensionmay increase the classification accuracy. In this paper, particle swarm optimization(PSO) and principal component analysis (PCA) have been used for dimensionalityreduction of PPI sequence features. The performance of the algorithm has been assessedusing the intraspecies E coli protein–protein interaction database, containing an equalnumber of positive and negative interacting pairs. Standard sequence-based featuressuch as amino acid composition (AAC), dipeptide composition (Dipep), and conjointtriad composition (CTD) are extracted. From the results, it is seen that the PSO-baseddimensionality reduction method provides steady and better performance in terms ofaccuracy when applied to the features.

Key terms

Protein–protein interaction Feature extraction Dimensionality reduction

Machine learning This is a preview of subscription content, log in to check access.






Abstract— Magnaporthe grisea (M.grisea) is the most destructive pathogen cause loss of rice crops every year worldwide. Protein-protein interaction (PPIs) of rice and M.grisea is the key factor of this disease. In this study, an efficient machine learning model is developed to predict the interaction between rice and blast fungus on a genome-scale. From interolog and domain-based method, we obtained 58,379 PPIs. The predicted PPIs are used to developed machine learning model. Testing accuracy of 5-fold cross-validation for these potential PPIs is 88 % and 89 % respectively using amino acid composition (AAC) and conjoint triode (CTD) features. Further the models are tested with other host-pathogen datasets. It predicted fewer PPIs for other host-pathogen databases which confermed that model is specific to rice and blast fungus. The current research work may be a useful resource to plant community to characterize the host-pathogen interaction between rice and M.grisea. Keywords: Rice (Oryza sativa L.); blast fungus (M. grisea), Interlolog, Domain, Support vector machine.

1. INTRODUCTION

Rice (Oryza sativa) is the main food crop for maximum world population and its productive capacity is largely limited by many abiotic and biotic factors. Among biotic factors, fungus Magnaporthe grisea is the most destructive and as a result 30-40% loss has occurred. Loss due to blast fungus is sufficient to feed around 60 million people. Blast fungus affects the rice plant during its growth period; infect its leaves, panicles, roots, and nodes. It also dangerous to other small grain like wheat. In the last few decades, many prevented measures like fungicides; methods based on biotechnology have been developed to prevent from this disease [1]. To control this disease, plant host resistant ability is an effective and cheaper method. The experimental prediction of PPIs between host and pathogen is lengthy and difficult task [2]. Very few numbers of experimental PPIs between rice and M.grisiea have been

Biswajit Karan is with the Birla Institute of Technology, Mesra, Ranchi India ( e-mail: [email protected]).

Satyajit Mahapatra is with the Birla Institute of Technology, Mesra, Ranchi India (e-mail [email protected]).

Sitanshu Sekhar Sahu is with the Birla Institute of Technology, Mesra, Ranchi, India (e-mail [email protected]).

identified in recent studied which is insufficient to explore the genetic and biochemical mechanism of pathogenicity [3]. Thus, computational method is considered as alternative method for identification of PPIs between rice and M.grisiea. In the last few decades many PPI prediction methods have been developed. Most of the approach followed the data mining approach to gather the relevant information from known PPIs. The method based on interolog, protein domain information, gene ontology annotation, and protein structural information, have been used to construct PPIs in different scale. Wang et al[4] developed the interacting network in rice genome. He et al.[5] constructed a interolog based network to predict PPIs in blast fungus. To the best our knowledge very few interspecies PPIs have been reported in literature. Shiwei Liu et al [6] establish a rice protein interaction network using structural and functional relationships. Li et al.[7] utilized the method of interolog and domain to establish a PPI prediction network between Ralstonia solonacearum and Arabidpsis thaliana. Recently Ma et al [16] predicted 532 potential PPIs between rice and rice blast. The PPIs identified by computational method will be very helpful to find the experimental PPIs. In this study, the machine learning model is developed to predict PPIs between rice and rice blast. The developed model predicted more accurately the experimental PPIs between rice and rice blast whereas it predicted less no PPIs for other host-pathogen database. The machine learning results confirmed that the database is specific to rice and rice blast only. The current research work may be a useful resource to plant community to characterize the host-pathogen interaction between rice and M.grisea.

2. Materials and methods Data Source A total of 11,054 Magnaporthae Griseas (blast fungus) protein sequences are collected from the broad institute. Similarly, 66,153 rice genome protein sequences are collected from MSU Rice Genome Database. A well-analyzed dataset is prepared for computational model development. Generation of positive candidate proteins of Rice for interaction

A set of keywords related to intra-species and interspecies interaction are identified by an exhaustive literature survey[18-

Prediction of protein interactions in rice and blast fungus using Machine Learning

Biswajit Karan, Satyajit Mahapatra, and Sitanshu Sekhar Sahu Department of Electronics and Communication Engineering, Birla Institute of technology, Mesra,

Ranchi, India

33

2019 International Conference on Information Technology (ICIT)

978-1-7281-6052-8/19/$31.00 ©2019 IEEEDOI 10.1109/ICIT48102.2019.00012


12/14/2020 Improved Face Detection Using YCbCr and Adaboost | SpringerLink


Improved Face Detection Using YCbCrand Adaboost

Computational Intelligence in Data Mining pp 689-699 | Cite as

Vishnu Vansh (1) Kumar Chandrasekhar (1) C. R. Anil (1) Sitanshu Sekhar Sahu (1) Email author ([email protected])

1. Department of Electronics and Communication Engineering, Birla Institute ofTechnology, , Ranchi, India

Conference paperFirst Online: 18 August 2019

295 Downloads


Abstract

Accurate face detection plays a crucial role in surveillance and security. It has been achallenging issue because of the fact that human faces are dynamic object with highdegree of variability in their appearance. This paper proposed a method of face detectionwhich involves pre-processing of input images to extract skin tone in YCbCr domainfollowed by Haar cascade classifiers to detect a face in the extracted area. Theseclassifiers are selected by AdaBoost training with help of particle swarm optimization. Onthe exhaustive study on various images, it is elucidated that the proposed approachprovides superior performance compared to the existing Viola–Jones technique. Theproposed algorithm is also able to detect the side or occluded faces in the input image.

Keywords

Face detection YCbCr colour space Adaboost PSO Haar cascade This is a preview of subscription content, log in to check access.

Notes






12/14/2020 Image Encryption Using Modified Rubik’s Cube Algorithm | SpringerLink


Image Encryption Using Modified Rubik’sCube Algorithm

Advances in Computational Intelligence pp 69-78 | Cite as

Rupesh Kumar Sinha (1) Email author ([email protected])Iti Agrawal (1) Kritika Jain (1) Anushka Gupta (1) S. S. Sahu (1)

1. Electronics and Communication Engineering, Birla Institute of Technology, Mesra, ,Ranchi, India

Conference paperFirst Online: 11 July 2019

188 Downloads


Abstract

For multimedia applications, data are developed and transmitted through the networks.These multimedia data should not be accessed by the unauthorized persons as it containsinformation. So, in current scenarios image security and privacy become a major issue incommunication. In this work, we proposed an advanced encryption scheme based onmodified Rubik’s cube algorithm. First, the original image is scrambled using two secretkeys, which is generated using logistic function and shift register method, respectively.Then, with XOR operator, rows and columns of the scrambled image are again mixedusing various means. Performance of the proposed work is assessed with correlationcoefficient and information entropy. From the experimental analysis and securityparameter evaluation, it can be observed that the proposed scheme can resist exhaustiveattack, statistical attack and differential attack.

Keywords

Image security Modified Rubik’s algorithm XOR operator Correlation coefficient This is a preview of subscription content, log in to check access.






1Department of Electronics and Communication Engineering

Birla Institute of Technology, Mesra Ranchi, India

[email protected], [email protected]

Abstract—Image compression play an important role in

efficient data storage and faster transmission in multimedia

applications. In this paper, a hybrid compression algorithm is

proposed combining Quadtree Fractal Image Compression

(FIC) and Set Partitioning in Hierarchical Tress (SPIHT)

techniques for better compression. First the image is

decomposed using wavelet transform. Then Quadtree FIC is

used on the approximation sub-band of the decomposed image

and SPIHT is applied on all the detailed sub-bands. The

performance of the proposed algorithm is assessed on standard

images. Compared with the existing methods, it shows the

superior results providing better PSNR of 37.07, low encoding

time of 1.610 seconds and SSIM of 0.9805 for standard Lena image.

Keywords—Fractal Image Compression, SPIHT, DWT,

Quadtree decomposition

I. INTRODUCTION

In real time applications, image compression techniques

play a significant role in processing large amount of image

data. Without compression, transmission of image data over

bandwidth limited network would be difficult and time

consuming. Several image compression methods are

adopted to utilize the bandwidth and reduce the

computational complexity. The fractal Image compression

(FIC) uses the self-similarity concept to represent an image

block through the contractive transformation coefficients. In FIC, the entire image is divided into range blocks of size

NxN and domain blocks of size 2Nx2N and each range

blocks are compared with all domain blocks. This makes it

slower and complex [1]. In [2], a discrete wavelet transform

(DWT) based Genetic algorithm has been developed to

overcome the limitation of FIC. PSO-RC hybrid Quadtree

partition have been presented in [3] to speed up the encoder

and improve the quality. A prediction based fractal

algorithm for hyperspectral images have been presented in

[4].

Said and Pearlman [5] introduced SPIHT algorithm that applies the set partitioning rules on DWT decomposed

images. To improve the coding efficiency advantages of

different types of set partition coding algorithm have been

combined in [6]. Jin and Lee in [7] developed modified

block-based pass parallel SPIHT algorithm to reduce the

slow processing. An efficient coding scheme using 3D

integer wavelet transform have been presented in [8] to

accelerate the coding time.

Various works on hybrid algorithms are also developed to

speed up the Fractal Image Compression. Davis [9] have

presented a method based on both fractal and wavelet

compression technique. In [10] authors used the hybrid

combination of QPIFS and modified SPIHT to reduce the

encoding time. PCA with Pre-Encoding Discriminant Information can be found in [11].

The fractal-wavelet based methods decompose the images

through discrete wavelet transform and then apply

compression algorithms on sub-bands. In DWT decomposed

images, most of the energy concentration lies in the

approximation sub-band and very less information is present

in detailed sub-bands. To effectively utilize this property,

this paper presents a hybrid Fractal-SPIHT based image

compression method. Fractal image compression using

quadtree partition is applied on approximate sub-band of the

DWT decomposed image and SPIHT is applied on other detail sub-bands to obtain the better quality image with high

compression ratio and less encoding time.

II. METHODOLOGY

A. Fractal Image Compression

Fractal image compression is based on the idea of iIterated

function system (IFS). FIC is based on the fact that most of

the natural images have the property of self-similarity and

they exhibit affine redundancy. In Jacquin’s approach [12],

the entire image is segmented into number of domain and

range blocks. Encoding process consists of affine

transformation matching between the range blocks and

domain blocks which make FIC a slow process. Quadtree method of partitioning is adopted to find the similarity.

B. Quadtree decomposition

In Quadtree partition, entire image is divided into four

squares of equal sizes and checked for homogeneity. If the

blocks are found to be homogeneous, transformation

parameters are stored and if not then, the blocks are further

divided into sub squares. This process is repeated

recursively starting from the whole image and continues till

sizes of squares are small enough to be covered within some

specified tolerance. For homogeneity check the difference of

the maximum and minimum pixel values within the block is compared with the threshold value multiplied with 8 for

uint8 images and 16 for uint16 images. The quality of

reconstructed image in Quadtree decomposition depends on

the selection of threshold value which lies between 0 and 1.

Image quality is better for smaller values of threshold since

more number of pixels passes the significance test

performed during the homogeneity check.

IEEE - 45670

Improved fractal-SPIHT hybrid image compression

algorithm

Anu Sri1, Sitanshu Sekhar Sahu1

10th ICCCNT 2019 July 6 -8, 2019 - IIT, Kanpur,

Kanpur, IndiaAuthorized licensed use limited to: Birla Institute of Technology. Downloaded on December 14,2020 at 09:54:44 UTC from IEEE Xplore. Restrictions apply.

12/14/2020 A Closed loop robust controller for SSHI based piezoelectric energy harvester | Taylor & Francis Group

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A Closed loop robust controller for SSHI based piezoelectric energy harvesterBy Sweta Kumari, Subrat Swain Kumar, SitanshuSekhar Sahu, Aditya Kumar, Prashant Kumar, Bharat Gupta

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12/14/2020 Intelligent Speech Processing in the Time-Frequency Domain - ScienceDirect

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Intelligent Speech Signal Processing2019, Pages 153-173

Chapter 9 - Intelligent Speech Processing in the Time-FrequencyDomainBiswajit Karan, Kartik Mahto, Sitanshu Sekhar Sahu

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https://doi.org/10.1016/B978-0-12-818130-0.00009-X

AbstractSpeech has an important role for communication among human beings. It is not only a tool forcommunication, but also contains ample information about the speaker’s age, emotion, health,and identity. Presently, the importance of speech processing has increased in various fields likeautomatic speech recognition, speaker verification, and pathological speech prediction. Thereforewe need some intelligent speech processing techniques that can be used in various applications.Since speech is a nonlinear and nonstationary type of signal, nonlinear speech analysistechniques such as wavelet packet transformation (WPT) analysis, empirical mode decomposition(EMD), variational mode decomposition (VMD) can be used. The decomposition can be used asan efficient signal processing technique, which can better characterize the speech intelligibility ofa person. It is a data-adaptive technique that captures nonlinear dynamics of the speech signal. Itdoes not complicate the analysis. It is a generalized, compact, and adaptive signal decompositiontechnique that provides a rare and meaningful time domain component known as modes orintrinsic mode function (IMF). These IMFs can extract time domain components of the speechsignal, which consists of both vocal tract and vocal fold information. The nonlinear-based featurewas better in many applications like speaker verification and pathological speech processingcompared to a typical feature like spectral and cepestral features.

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12/14/2020 Energy harvesting via human body activities - ScienceDirect

https://www.sciencedirect.com/science/article/pii/B978012820781900005X 1/3

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Smart Biosensors in Medical CareAdvances in ubiquitous sensing applications for healthcare

2020, Pages 87-106

Chapter 5 - Energy harvesting via human body activitiesSweta Kumari , Sitanshu Sekhar Sahu , Bharat Gupta , Sudhansu Kumar Mishra

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https://doi.org/10.1016/B978-0-12-820781-9.00005-X

AbstractEnergy consumption in wireless sensor network (WSN) is one of the most critical issues. WSNsare conventionally battery operated sensor nodes which have short lifetime due to limited batterypower and replacement of battery regularly is a costly and complicated task. Furthermore, in caseof Wireless Body Area Sensor Network (WBASN), the problem arises due to its increasing cost andbeing uncomfortable in some cases (where replacement takes place). Energy harvesting is one ofthe solutions for any wireless network. There are several novel methods to generate energy fromthe environmental sources such as wind, solar, vibration, biological, and chemical. Besides theseconventional sources, human body, with its many intended and unintended activities, is anothersource of energy. And it offers a reasonable solution to the issue in terms of renewable energy.Based upon appropriate power consumption from different harvesting methods, they can be usedin a better way of required application. Human energy expenditure from different activities andhow do we use that energy as electric sources and their power consumptions have been discussedhere. The demand of a healthcare monitoring network with long life without replacement is alsoresolved by energy harvesting technologies. Here, first we have presented reviews on methods ofenergy harvesting techniques through human activities and, second, those technologies thenwould be used for biological applications (healthcare applications) as well as consumerelectronics. Among all possible way of harvesting technologies (kinetic energy, biological fuel cell,

a a b a

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Metasurface aided Biophysical Differentiation of Radiated Cancer Cells: C band to THz perspective

Abhirupa Saha1, Piyali Basak1, Bhaskar Gupta1, Sanjib Sil2, and Srikanta Pal3, 1Jadavpur University

[email protected] 2Calcutta Institute of Engineering and Management

[email protected] 3Birla Institute of Technology, Ranchi, India

[email protected]

Abstract— A resonating plasmon like behavior is obtained when a metasurface composite is employed to sense and acquire the real-time carcinoma biophysical information. Miniaturization has been done with respect to frequency in order to combat the skin depth challenges of THz considering its non ionization capabilities. If cancerous cells are programmed to be ablated, absorbance property of metasurface is utilized for raising the temperature using thermal analysis. The threshold level of power density for the minimal energy that the cells can absorb without dielectric property changes is determined experimentally in the far field. Metamaterial trapped non radiative decay raises the temperature and the observed changes are applied for explicitly dissipating enough heat to initiate cell death. Thus apoptosis is analyzed with photonic manipulation of the spectroscopic response of cell complex permittivity on a metasurface design and related to the irradiated power density illuminating the sensor during measurement at 4GHz.

Keywords- Metasurface; Ablation; Terahertz; Biosensor; Apoptosis; Double Split Ring Resonator; C Band; Radiation therapy; Permittivity

I. Introduction

We are not new to the harmful effects of radiation therapy on cells after ablation, apart from its therapeutic beauty it calls for undesired radioactive decays throughout the body. Antennas have been designed for breast cancer holographic imaging [1], while a common metasurface sensor for detection and ablation has been hardly thought about before and it is the scope of this paper. Nowadays, targeted radiation causes to penetrate the areas that should not be affected while trying to reach the intended location of the tumor. Microwave ablation of tissues is of medical concern when it comes to the jeopardizing effects of radiation therapy prescribed for recovering carcinoma patients. The paper detects and examines the effect of various power levels of incident 4GHz band radiation on the cells that are exposed at far field by a C band horn so that the changes and the cellular response can be captured immediately after the exposure while the duration of radiation is varied according to protocols made. For the far-

field experimental work, instead of tissues [2], we have planned to consider the ovarian germ line cancer cells to study their response after letting them get irradiated by the external RF source that is connected to the horn antenna radiating the C band power to the cells. Temperature was checked simultaneously to understand the heating effects of the incident low-power microwave energy and then the temperature effects can be back tracked to conclude the power density that could have been corresponding result of radiation induced heating. Physiological observations can be inferred from electromagnetic response that the carcinoma cells react upon getting subjected to radiation. A cell can be modeled as fig. 1, with CM, RM being cell membrane capacitance and resistance, RC, CC being similar cell cytoplasm parameters.

Fig. 1 A cell modeled as a lumped circuit [3]

Opto-electromagnetic properties of a normal and

mutated cell create dynamic features and contribute to the formation of polaritons at the interface of cell metal dielectric interface when the high frequency incident signal is focused on a metal surface at considerable high frequency till 2THz. At this spectrum the free electrons of the metal and carcinoma cell dielectric gain enough momentum to form a periodic surface wave pattern known as surface Plasmon polariton waves that is important in creating transparency windows through which the cells can be spectrally visible by the


2020 International Conference on Electrical and Electronics Engineering (ICE3-2020)

978-1-7281-5846-4/20/$31.00 ©2020 IEEE

A THz Metasurface Coated SoC for SPR Excited Carcinoma Sensing

Abhirupa Saha #1, Piyali Basak #2, Srikanta Pal *3

#Jadavpur University Kolkata, India

[email protected] [email protected]

*Birla Institute of Technology Ranchi, India

[email protected]

Abstract—A compact system-on-chip based biosensor for detection and monitoring of breast cancer cells has been proposed to provide better spectral signature fetching and the concept is proved. Human body cells are seeded on the meta surface that is excited to study the sensor response in Time domain spectroscopy environment. It replaces conventional techniques to diagnose malignancy, and can measure the efficiency of drug composition with the action duration for complete apoptosis. Resonance is observed at 0.86THz where the sensor controls the Surface Plasmon fields due to the Terahertz incident waves impinging on the meta surface. The implantable system consists of a substrate that degrades along with the meta surface that has been characterized to be showing simultaneously dual negative material nature (DNG).

Index Terms— Terahertz, Metamaterials, Spectroscopy, Biosensor , Implants, Biodegradable, Meta surface.

I. INTRODUCTION

Time domain spectroscopy (TDS) in terahertz spectrum has changed the perspective of differentiating the health of a biological cell; the main component being cellular water content, their molecular orientation causes polarization and thus dispersion with frequency; for malignant cells, the relaxation time factor varies with apoptosis upon getting irradiated at such a high frequency spectrum. THz owns the highest value in imaging and detection, internal reflection from water content of its location can regenerate it, thus combating the deficit of the high frequency range that corresponds to a low skin depth. Due to this reason implants for THz is a challenge, it is proven to be workable for in vitro conditions. If the cells can be cultured and tested in vitro [1, 2], while in vivo biocompatible implant whose degradation starts after drug operation is a promising solution for long term real time monitoring of whether the composition is effective, hence the drug action duration for apoptosis of the existing malignant cells are to be examined for selecting the appropriate patches have been developed to diagnose glucose content [3].

Materials like graphene shows electron gating and hence a good tuning capacity for being used as a

radiating surface with a monopole antenna for a biosensor [4]. Titanium is also a biocompatible material that can be used for in vitro testing with cultured breast cancer cells. Graphene oxide and poly aniline are proven to have an appreciable high frequency response and conductivity for meta structures keeping substrates like polyimide and parylene C.

II. PLASMONIC RESONANCE IN METAMATERIALS

In 1968 with a paper studying materials that are artificially patterned, Victor G. Veselago provided the world with his recipe of a negative refractive index [5] from (1) when both the relative permittivity and permeability are negative constituting metamaterials (MMs). Standard design is that of a double split ring resonator (DSRR) Transition between quadruple and dipole create the suppression of radiative damping.

(1)

Whenever the composite metal dielectric surface is irradiated near to the optical region, if the plasma frequency is reached, there is a transfer of photonic momentum to the electron gas and the surface, magnetic dipoles get canceled out hence non radiative damping prevails. Surface Plasmon polariton (SPP) periodic waves start forming as a result of shortage and excess of electrons in a periodic pattern at the metal dielectric interface, their propagation being confined at the interface only.

(2)

Before studying EIT windows, w obtain the dispersion relation of SPPs above the Plasmon frequency at a dielectric-metal interface by solving Maxwell’s

723Authorized licensed use limited to: Birla Institute of Technology. Downloaded on December 14,2020 at 10:22:13 UTC from IEEE Xplore. Restrictions apply.

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Dual-Band Triple Mode OAM Generation Using Annular Slot Microstrip Radiator

Shailendra singh Electrical Engineering Shiv Nadar University

Dadri, India [email protected]

Madhur Deo Upadhayay Electrical Engineering Shiv Nadar University)


Srikanta Pal Electronics and Communication

Engineering Birla Insitute of Technology

Ranchi, India [email protected]

Abstract— This paper presents a design of a four-port, dual-band uniform circular array (UCA) to generate three orthogonal Orbital Angular Momentum (OAM) modes (OAM mode 0, +1 and -1) at two different frequency 2.45 GHz (ISM band/WLAN) and 5.4 GHz (WLAN). The proposed antenna is designed with the help of four 50-Ohm microstrip line radiator (MLR) having an annular slot on the ground plane. The effect of variation of the physical design parameters (like the length of 50-Ohm MLR, the radius of annular slot and annular slot width) on reflection coefficient and the radiation pattern is shown and discussed.

Keywords—orbital angular momentum antenna, uniform circular array antenna, low profile antenna, defected ground structure, phase pattern of antenna beam.

I. INTRODUCTION Maximum efficiency utilization of the radio spectrum have been always the aim of researchers and for that many novel techniques have been developed. The utilization of different polarization states, high density adaptive coding and different channel sharing techniques have been developed for achieving high data rates and increasing the channel capacity. Multiple-Input Multiple-Output (MIMO) and massive MIMO systems are the very advance techniques to enhance the channel capacity and key of the 5G communication systems and have been widely discussed over the past decades. Degree of freedom (DoF) is consider as the prime factor to enhance the channel capacity and recently the different modes of orbital angular momentum (OAM) waves are considered and used as transmitting channels because different OAM modes do not interfere to each other [1]. OAM beams have helical phase fronts with

phase shifts, where is the OAM mode which can be any positive or negative integer define the twisting degree [2]. The properties of OAM waves, leading to the mode division multiplexing communications by using the twisting degree of the electromagnetic field with different , can increase the channel capacity dramatically without occupying additional frequency spectrum [3-4]. Numerical explanation of developing the OAM attributes in the radio beam is well presented in 2007 by Thide et al [1]. In this study, he explains that an antenna array can generate the OAM beam. Later, an experiment on transmission of the two different OAM modes simultaneously was demonstrated in 2012 by Tamburini et al and this published report [3] increases the interest of researchers in this topic. Since then many different techniques to generate OAM in radio beam have been investigated such as spiral phase plate (SPP) [4], holographic diffraction gratings [5], dielectric resonator antenna [6], time switched array (TSA) [7], meta-

surfaces [8-9], and phased uniform circular antenna (UCA) array [10-11]. UCA array is one of the simplest ways to produce ± order OAM mode with N number of antenna elements. All designs are focused for single frequency and single sided (front beam) antenna beam. This paper present a low profile, dual band and dual sided (front and back) OAM beam generation.

II. ANALYSIS OF UCA ANTENNA

A. Basic Equation of UCA The normalised electric field at point P(r, , ) in

spherical coordinate system is [12-13].

(1)

(2)

Where J is the constant current density vector of the identical patch antenna elements, L is the electric length of the patch element, μ0 is the magnetic permeability in the vacuum, and and k are the angular frequency and wave vector, respectively. n=2 n/N is the angle of the nth array element position where n=1, 2…, N. R is the radius of the array and N is the total number of antenna elements present in the array. The distance between spatial locations of each element to the observation point P is given by:

(3)

The term in equation 2 is prime responsible for linearly increase in phase over azimuth plane which means rotation of phase front of OAM wave. OAM mode l is an integer quantity having plus (+) and minus (-) sign before it which shows the direction of rotation of OAM wave. In the proposed antenna there are four 50-Ohm MLR (N = 4) patch uniformly places as circular array as shown in Fig. 1(b). The OAM mode is generated by applying a specific progressive electrical phase shift at each port. The electrical phase for a particular mode is given by formula n= 2 ln/N. in this regard for OAM mode 0 (l = 0) each port should have 00 progressive phase shift that means all port should have equal electrical phase. For OAM mode 1 (l = 1) the progressive phase shift is 900 which means that if the initial phase for port 1 is o then the electrical phase for port-2 to port-4 should be ( o+900), ( o+1800) and ( o+2700) respectively. To have OAM mode -1 (l = -1) just reverse the order of phase excitation from OAM mode +1.

2020 7th International Conference on Signal Processing and Integrated Networks (SPIN)

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OAM Wave Generation Using Inner feed Annular Slot Microstrip Radiator

Shailendra Singh Electrical Engineering Shiv Nadar University


Madhur Deo Upadhayay Electrical Engineering Shiv Nadar University)


Srikanta Pal Electronics and Communication

Engineering Birla Insitute of Technology

Ranchi, India [email protected]

Abstract— This paper proposes, an annular slot antenna with inner feeding network to generate Orbital Angular Momentum (OAM) waves at 5.4 GHz frequency, for WLAN application. The proposed OAM antenna system is smaller in size because open-ended microstrip lines are used as radiator along with annular slotted ground plane. Parametric variation and far field radiation patterns are presented and discussed. 3D phase patterns proves the generation of OAM waves of different OAM modes using proposed OAM antenna.

Keywords—orbital angular momentum antenna, uniform circular array antenna, low profile antenna, defected ground structure, phase pattern of antenna beam.

I. INTRODUCTION From last decade the role of OAM waves for improving the channel capacity in wireless communication have attracted much attention [1, 2]. OAM is an intrinsic property of electromagnetic (EM) waves [3] like polarization property of EM waves [5] and widely studied in optical physics and optical communication [4, 6 and 7]. In the year 1992 Allen et. al demonstrated that plane phase front of EM wave in the direction of propagation can be transformed in to spiral phase front Laguerre Gaussian (LG) beam, which carries OAM waves of phase factor exp(il ), where l is the topological charge and also called OAM mode . OAM modes in EM waves defines the twisting degree of spiral phase front and theoretical number of OAM modes l are infinite. Different modes of OAM waves are orthogonal to each other. Thus, multipath signals carrying different OAM modes can be transmitted in the same channel at the same time, so the OAM waves can be used to increase communication capacity. Numerical explanation of developing the OAM attributes in the radio beam is well presented in 2007 by Thide et al [8]. In this study, he explains that an antenna array can generate the OAM beam. Later, an experiment on transmission of the two different OAM modes simultaneously was demonstrated in 2012 by Tamburini et al and this published report [9] increases the interest of researchers in this topic. Since then many different techniques to generate OAM in radio beam have been investigated such as spiral phase plate (SPP) [10], holographic diffraction gratings [11], dielectric resonator antenna [12], time switched array (TSA) [13], meta-surfaces [14-15], and phased uniform circular antenna (UCA) array [16-17]. UCA is one of the simplest ways to produce ± lth order OAM mode with N number of antenna elements. All designs are focused for single frequency and single sided (front beam) antenna beam. This paper present a low profile, dual band and dual sided (front and back) OAM beam generation.

II. ANALYSIS OF UCA ANTENNA

A. Basic Equation of UCA The normalized electric field at point P(r, , ) in

spherical coordinate system is [18-19].

(1)

(2)

Where J is the constant current density vector of the identical patch antenna elements, L is the electric length of the patch element, μ0 is the magnetic permeability in the vacuum, and and k are the angular frequency and wave vector, respectively. n=2 n/N is the angle of the nth array element position where n=1, 2…, N. R is the radius of the array and N is the total number of antenna elements present in the array. The distance between spatial locations of each element to the observation point P is given by:

(3)

The term in equation 2 is prime responsible for linearly increase in phase over azimuth plane which means rotation of phase front of OAM wave. OAM mode l is an integer quantity having plus (+) and minus (-) sign before it which shows the direction of rotation of OAM wave. In the proposed antenna, four (N = 4) open ended microstrip line radiator (MLR) of characteristic impedance 50-Ohm are uniformly placed to form circular array as shown in Fig. 1(b). The OAM mode is generated by applying a specific progressive electrical phase shift at each port. The electrical phase for a particular mode is given by formula n= 2 ln/N. in this regard for OAM mode 0 (l = 0) each port should have 00 progressive phase shift that means all port should have equal electrical phase. For OAM mode1 (l = 1) the progressive phase shift is 900 which means that if the initial phase for port1 (Pin 1) is o then the electrical phase for port-2 (Pin 2) to port-4 (Pin 4) should be ( o+900), ( o+1800) and ( o+2700) respectively. To have OAM mode -1 (l = -1) just reverse the order of phase excitation from OAM mode +1.

B. Single 50-Ohm MLR with Annular Slot on ground. Single antenna element is shown in Fig. 1(a). MLR with

the annular slot on ground plane is designed and simulated for achieving the desire frequency band 2.45 GHz and 5.4 GHz. FR-4 is used as substrate material with the permittivity of r=4.3, substrate height h=1.6 mm and length and width of substrate is Lsub=110 mm.

2020 7th International Conference on Signal Processing and Integrated Networks (SPIN)

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12/14/2020 Design of a 2–30 GHz Low-Noise Amplifier: A Review | SpringerLink


Design of a 2–30 GHz Low-NoiseAmplifier: A Review


Krishna Datta (1) Email author ([email protected])Srikanta Pal (1) Vijay Nath (1)

1. VLSI Design Group, Dept. of Electronics and Communication Engineering, BirlaInstitute of Technology, , Mesra, Ranchi, India


28 Downloads


Abstract

LNA is the first component after an antenna in any RF receiver system and thereforeplays a key role in determining most of the key parameters of the RF receiver like noisefigure, gain, linearity, and stability. For designing an LNA, its effect on every of theseparameter has to be kept in mind. In this paper, the steps of designing a wideband LNAin the RF band 2–30 GHz have been studied with references from various previous worksdone on wideband LNAs and some application-based approaches on the discussed band.The technology studied has been restricted to Cadence CMOS technology.

Keywords

LNA Wideband UWB ZigBee Bluetooth Topology This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

A piece of thanks goes to Prof. M. K. Mishra, Vice-chancellor, BIT Mesra Ranchi forproviding us with infrastructure and facility to carry out the research work.






12/14/2020 Ad Hoc Network Using UAVs in Indian Farms: A Review | SpringerLink


Ad Hoc Network Using UAVs in IndianFarms: A Review


Shivanta Sahoo (1) Email author ([email protected])Yash Gupta (1) Vijay Nath (1) Srikanta Pal (1)

1. Wireless Communication, Department of ECE, B.I.T. Mesra, , Ranchi, India


27 Downloads


Abstract

Agriculture is repeatedly affected by threats like wild animals, insects, droughts andfloods. It is important to safeguard the farmland from various natural disasters andmaintains the quality of crops to meet the consumer demand. For this purpose, theGovernment of India (GOI) has presented a number of rural plans all through the nationto assist the agriculture sector. The farmers need to monitor their crops to ensure thefinal product is undamaged and well grown. With the help of UAVs, the informationrelated to the farmland could be gathered and sent to the farmer from time to time. Butmany of the Indian farms are located in deep remote areas with erratic geographicalconditions where telecommunications or Internet services are difficult to maintain. So,the motivation of this research is to provide the farmers of our country with properaccess to communication and monitoring farmland by using UAVs connected together byan ad hoc network. The ad hoc network will be able to maintain direct line of sightcommunication with uninterrupted connectivity in hilly areas and mountains. Theseconnected UAVs can scan the crops and act as surveillance from intrusions.

Keywords

Agriculture Ad hoc network Unmanned aerial vehicles (UAV)

Communication technologies Download conference paper PDF





https://link.springer.com/content/pdf/10.1007%2F978-981-15-7486-3_65.pdf

12/14/2020 Designing of Low-Noise Amplifier and Voltage-Controlled Oscillator for Satellite Receiver in Ku Band | SpringerLink


Designing of Low-Noise Amplifier andVoltage-Controlled Oscillator for SatelliteReceiver in Ku Band


Vishnu Anugrahith Sateesh (1) Sanjay Kumar Surshetty (1) Email author ([email protected])Vidushi Goel (1) Deepak Prasad (1) Vijay Nath (1) Srikanta Pal (1)

1. Department of ECE, Birla Institute of Technology, , Mesra, India


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Abstract

In this project, design of low-power Ku band CMOS voltage-controlled oscillator andlow-noise amplifier for satellite communication is proposed. The proposed LNA provideslow input impedance, low noise figure, and high gain which makes it suitable for use insatellite receivers to amplify low-power signals. This NMOS LC VCO has main advantagein low phase noise and low power. This VCO is designed on concept of negativeresistance generated by MOSFETs impedance which reduce the phase noise. This circuitis designed using UMC 90 nm CADENCE ADE. For this circuit, we use 1.2 V powersupply. Its average phase noise is −109.18 dBc/Hz at 1 MHz offset. The oscillator requiresapprox. 0.001127 of chip area. It is highly useful for satellite communication.

Keywords

Low-noise amplifier Noise figure NMOS LC VCO MOSFETS Phase noise Power

Offset This is a preview of subscription content, log in to check access.

Notes

mm2






A Biodegradable THz Metasensor For Malignancy Apoptosis

#1Ms Abhirupa Saha, #2Dr Piyali Basak, *3Dr Bhaskar Gupta

1,2School of Bioscience and Engineering 3Department of Electronics and Communication Engineering

Jadavpur University Kolkata, India

#[email protected] , #[email protected], *[email protected]

Abstract—A unique model of a Metasurface that works as a biosensor to distinguish carcinoma cells on Terahertz time domain spectroscopy has been designed exploiting metamaterials. Cancer cell apoptosis by the action of drug concentration is monitored using the resonating frequency shift of the double split ring resonator inculcating double asymmetry. The structure that controls the plasma response of the metamaterial is explicitly made to degrade after the completion of medication.

Keywords- Metasurface; Terahertz; Biosensor; Apoptosis; Double Split Ring Resonator.

I. INTRODUCTION

The field of artificial dielectrics took birth in the antenna engineering community since the 1940’s, when material properties started getting artificially structured shaping the ε and μ, being entitled as the Left handed material (LHM). Engineering permittivity ε and permeability μ, result in negative refractive-index η, thus reversing Snell’s law, Doppler Effect, Cherenkov Effect and radiation pressure. Metamaterials have always shown unusual properties [1] shuffling stop bands of operation in order to ultimately direct the pass band of the system thus working as a CRLH transmission line. At terahertz frequency, when the structure gets irradiated at sub wavelength range, interaction between the photons and electron dipoles cause a transfer of momentum, magnetic dipole moment cancel out, leading to the occurrence of windows with non bi-anisotropy in each of the unit cell (in the array forming the biosensor). Correspondingly, scaling down of the structure’s initial design makes it comparable to the operating very short wavelength in nanometers and hence the name Nanosensor. Incident polarization controls the coupling between the field components and intensity. The Plasmonic effect and the radiative loss suppression with the degree of asymmetry at metal dielectric interface upon being subjected to optical radiation have been discussed by many research groups [2].

Dr Srikanta Pal Department of Electronics and Communication Engineering

Birla Institute of Technology Ranchi, India

[email protected]

Surface Plasmon Polariton (SPP) waves are photon energy in electrons that consists of a periodic pattern of excess and the deficit of electron, it follows the frequency of excitation of light wave as these coupled oscillations of photons and dipoles create the polaritons that are dispersive in nature. The SPPs are quasi-bound unlike before resonance where large SPP wave vector correspond to small wavelengths, these surface waves decay exponentially into the dielectric and metal junction.

II. BIOCOMPATIBILITY

A. Substrate

First, we consider one of the commonly used materials forsensors which is Polyimide having a permittivity of 3.5, which is suitable for in vitro experimental set up. But when we are developing the sensor for implanting inside the body, the material should be biocompatible at body temperature and also should start degrading just after the action of drug finishes, hence we are to control the lifetime of the sensor with the antenna structure fabricated on the substrate. There have been biocompatible substrates like Silicon Carbide used for monitoring glucose level keeping the sensor close to the adipose tissue layer near the blood vessel to increase the precision [3]. We do not want the sensor to start degrading as soon as it gets implanted; hence we go for biocompatible Zinc alloys and Titanium before trying biopolymers and possible go for grapheme since it is biodegradable and biocompatible too.

B. Metal Radiating Surface

The metal dielectric interface should have enough electrongas so that the incident energy can irradiate the sensor to make it work in the Terahertz Time Domain Spectroscopy (TDS) setting. Hence the metallic array of unit ell that comprises the nanosensor should resonate at desired frequencies, which is only possible if its conductivity and resistivity values are acceptable while being biocompatible when it is working on the substrate. For in-vitro clinical purpose, the radiating

978-1-7281-3455-0/19/$31.00 ©2019 IEEE 1


Fast Principal Component Auto-Regressive

Algorithm for Estimation of Parameters of Radar

Interference Signal

Srikanta Pal ECE Deptt.

Birla Institute Of Technology,Mesra Ranchi, India

[email protected]

Md. Shahnawaz Hussain

IEEE Student Member, ECE Deptt.

Birla Institute Of Technology,Mesra

Ranchi, India

[email protected]

Abstract—The issue of estimation of parameters of radar

interference signal has been addressed by algorithms like Grid

Search–Maximum Likelihood Estimator (GS-MLE) and

Principal Component Auto-Regressive Estimator (PCAR). GS-

MLE algorithm is an optimal algorithm as it achieves the

Cramer-Rao Lower Bound (CRLB) but its time-complexity is

high. Another algorithm, that is, the PCAR Algorithm is a sub-

optimal algorithm but it is comparatively faster. In this paper,

we propose a hybrid method to further reduce the time-

complexity of the PCAR algorithm for large data size (>3000)

at both high SNR (>0 dB) and low SNR (<0 dB). However, the

estimates of parameters obtained by the Fast PCAR algorithm

are reliable only in the SNR range of -20 dB to infinity. This is

validated by comparing the Fast PCAR algorithm with the

CRLB.

Keywords—Principal Component AR algorithm, Grid Search

Maximum Likelihood Estimator, CRLB, QR algorithm, Lanczos

algorithm, singular-value decomposition, eigenvalues, radar

interference

I. INTRODUCTION

Radar interference signal [1] is of great importance due

to its use in practical radar scenario and hence the

importance of estimation of its parameters like frequency,

amplitude, and phase. The well-known algorithm for this

purpose, the Grid Search Maximum Likelihood Estimator

(GS-MLE) [2], is asymptotically optimal. That is, it attains

the Cramer-Rao Lower Bound (CRLB) for a large number

of data samples and gives very good estimates of the signal

parameters. However, it is computationally involved. CRLB

[3] provides a benchmark for the variance of an estimator against which we compare its performance. It also points to the physical impossibility of finding an estimator whose variance is less than this bound. It is used often for feasibility studies in signal processing. Another algorithm is Principal Component Auto-Regressive algorithm (PCAR). This is a suboptimal algorithm as it attains the CRLB for high enough SNRs and produces good estimates but it is computationally less complex [2, 3, 4]. The computational

complexity holds for time-complexity if we assume that

each arithmetic operation takes a certain minimum time [5].

PCAR algorithm involves a calculation, which is the

calculation of the highest eigenvalues of a covariance matrix

formed from the data vector. Generally, this is done using

QR Algorithm. Here, we use a special algorithm called the

Lanczos Algorithm along with QR algorithm for this

purpose. This causes further reduction in time-complexity of

the PCAR algorithm. We call it Fast PCAR algorithm.

II. GRID SEARCH-MAXIMUM LIKELIHOOD

ESTIMATOR ALGORITHM

The Maximum Likelihood Estimator (MLE) [2, 19, 20, 21] algorithm is named thus because it maximizes the log-likelihood function of a signal. The Probability Density Function (PDF) of a signal is termed as the likelihood function of the signal. Then we take the log of the likelihood function which in turn needs to be maximized to give the MLE. This maximization is done using Grid Search (GS) method, that is, search for Global Maxima in a given interval for a given parameter of a signal like frequency. The algorithm is as follows:

Step 1: The signal model selection.

a) The discrete-time model of the signal sample is

given as:

𝑠[𝑛] = ∑ 𝐴𝑖𝑝𝑖=1 cos(2𝜋𝑓𝑖𝑛 + ∅𝑖 ) (1)

where 𝐴𝑖, 𝑓𝑖, ∅𝑖 is the amplitude, frequency and

phase of the 𝑖th sinusoid, 𝑝 is the number of

sinusoids and

𝑛 = 0, 1, …𝑁 − 1

where N is the total number of samples.

b) The data samples are taken to be the signal samples

that are embedded in White Gaussian Noise samples,

that is

IEEE - 45670



AmericanPhysicalSociety

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January 7, 2020

Swati PrasadDepartment of ECE,Birla Institute of Technology, MesraRanchi, Jharkhand, [email protected]

Dear Swati,

The abstract you have submitted, ""Robust Speaker Identification System UnderAdverse Conditions"" has been accepted for oral presentation at the APS MarchMeeting 2020, to be held in Denver, Colorado from March 2–6, 2020.

The APS March Meeting is the largest and most prestigious meeting of physicists inthe world. More than 10,000 papers will be presented by eminent scientists in the fieldof physics, including condensed matter physics, materials physics, biological physics,chemical physics, polymer physics, magnetism, and computational physics.

We hope you can attend this important scientific meeting. We look forward to yourparticipation in Denver.

Sincerely,

Donna GreeneScientific Programs [email protected](301) 209-3290

12/14/2020 Design of an Energy-Efficient Cooperative MIMO Transmission Scheme Based on Centralized and Distributed Aggregations | SpringerL…


Design of an Energy-Efficient CooperativeMIMO Transmission Scheme Based onCentralized and Distributed Aggregations

Advances in Computational Intelligence pp 273-286 | Cite as

Sarah Asheer (1) Email author ([email protected])Sanjeet Kumar (1)

1. BIT, Mesra, , Ranchi, India

Conference paperFirst Online: 11 July 2019

181 Downloads


Abstract

Wireless sensor network (WSN) operates under strict energy constraints; therefore,minimizing energy becomes a key concern in the design of such networks. A cooperativemultiple-input multiple-output (CMIMO) model has been proposed here which utilizesnode cooperation in centralized as well as in distributed aggregation schemes. Thedistributed aggregation scheme has been modified with an optimum number ofaggregator nodes, and the centralized aggregation scheme has been modified with anoptimum number of nodes for long-haul link to the base station. The selection criteria ofthe aggregator nodes and long-haul link nodes for both the schemes are based on theresidual energy level of the nodes. Energy consumption model has been provided toanalyze the effects of cluster size, the number of aggregator nodes and the number ofnodes forming the long-haul link on the average energy consumption. In eachaggregation scheme, most of the sensor nodes periodically go to sleep mode to save theenergy. The proposed modified schemes significantly lower the average energyconsumption as compared to the conventional schemes.

Keywords

CMIMO Data aggregation Aggregator nodes Spatial correlation

Centralized aggregation scheme Distributed aggregation scheme WSN This is a preview of subscription content, log in to check access.






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