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ONGOING PROJECTS Pacific Atlantic Network for Technical Education and Research The PANTHER project f o r m o b i l i t y f u n d i n g o f 1 . 2 5 m i l l i o n e u r o s was awarded under Erasmus Mundus Action II, which manages scholarship programmes funded by the European Commission. The total funding is for 4 years from Nov. 2014 – Nov. 2018.

The Partner universities involved are: Warsaw University of Technology (programme coordinator- Poland); Dublin Institute of Technology (Ireland); University of the Basque Country (Spain), Ecole Centrale de Nantes (France); Budapest University of Technology and Economics (Hungary); Griffith University, (Australia); University of New South Wales (Australia); Auckland University of Technology (New Zealand).

The project offers PhD, postdoc and staff scholarships for citizens of European Union, Australia and New Zealand with the goal of developing research collaboration between the universities of these countries. The programme is focused on engineering and technology, mainly in the research areas of Aeronautics and astronautics, Power, renewable energy and new energy sources, Sensing technologies and Automation and control systems.

At the Management Selection Committee Meeting held on 9th & 10th June in Warsaw, Poland, screening and selection of doctorate/ academic staff for mobility took place. Prof. Nikola Kasabov, member of the Management Committee and Scientific Co-ordinator for New Zealand was represented by Joyce D’Mello Admn. Manager for the project in AUT. At the meeting, for the first cohort of the mobility, AUT was awarded funding to host for research, 3 staff, 1 postdoc and 2 Phd students from Europe, totalling to approximately 120,000NZD.

PANTHER Management Committee Meeting held on 9th & 10th June 2015 in Warsaw, Poland.

China Tripartite Project KEDRI was awarded 26,620 nzd from ENZ for the project which is for one year till June 2016.

The Government has approved funding for ENZ to support the initiation and development of international education relationships between New Zealand and China.

In 2001, the Ministry of Education in China created a partnership programme between prestigious eastern universities and universities developing in the Western Inlands of China, known as the “Two Brothers” arrangement. In 2005, the New Zealand and Chinese Ministries of Education subsequently agreed to formally support and promote tripartite relationships between New Zealand and China, in which a New Zealand university is joined as the ‘third brother’ to an existing ‘Two Brothers’ arrangement. Both the New Zealand and the Chinese governments have agreed to commit funding to support this bilateral initiative.

A Memorandum of Understanding was signed in July 2008 and renewed in 2012 for an international cooperative project between KEDRI, AUT, Xinjiang University and Shanghai Jiao Tong University (“the Partners”). During this time the Partners have developed a programme for joint research and dissemination of results by way of publications and workshops held in both New Zealand and China.

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AUT has agreed to develop relationships with Shanghai Jiao Tong University and Xinjiang University by continuing collaborative research in the following areas;

1. Intelligent information systems for online visual exploration; and

2. Understanding and prediction of ecological and environmental problems.

ENZ has agreed to provide AUT up to $26,620 incl GST in funding to develop and strengthen their collaborative tripartite relationship in China.

SRIF – INTELLECT 2 project KEDRI was awarded the SRIF funding for 100000nzd

MEDTECH CoRE collaborative project with the Bioengineering Institute, University of Auckland Dr Peng from University of Auckland and Prof. Kasabov applied successfully for a project funded for 30,000 NZD to be completed in 2015.

TEACHING KEDRI coordinated and taught 2 papers at the School of Computer and Mathematical Sciences (SCMS): -

• Neuroinformatics (Semester 1) • Bioinformatics (Semester 2) KEDRI was

involved in teaching and project supervision of the paper “Data Mining and Knowledge Engineering”.

NEW PHD AND MASTERS STUDENTS New PhD students: Anne Wendt is a PhD student at KEDRI under the supervision of Prof. Nikola Kasabov, A/Prof. Lubica Benuskova (University of Otago), and Dr. Grace Wang (Faculty of Health and Environmental Sciences, AUT). Her thesis explores computational brain-like modelling of cognitive processes of audio-visual information perception and processing. Anne received a BSc in Business Information Systems from DHBW Mannheim (Germany) and a MCIS (First Class) from AUT. She was awarded a Yearly Scholarship for Graduates by the German Academic Exchange Service (2012), the Eagle

Technology Scholarship for the top first year postgraduate student in Computer and Information Sciences progressing to complete an MCIS degree from AUT (2013), and the PhD scholarship by the School of Computer and Mathematical Sciences at AUT (2015).

Zohreh Gholami Doborjeh is a PhD student under the supervision of Prof. Nikola Kasabov. Her topic of study is ‘Spatio- Temporal Brain Data Modelling of Human Behaviour Using Spiking Neural Networks’. Zohreh obtained her Master’s degree in psychology, from Ferdowsi University of Mashhad, Iran, in 2013. She has previous research experiences in Neuromarketing, Cognitive task designing, and EEG and ERP data analysis.

New Master’s student: Parag Ganesh Nayak did his Bachelor of Engineering in Computer Science and Engineering from Thakur College of Engineering and Technology, India in 2011 and then did his Post Graduate Diploma in Computer and Information Sciences from AUT in 2014. He is currently doing his master’s thesis under Prof. Nikola Kasabov.

His thesis title is “Comparative Analysis of Traditional Machine Learning and Spiking Neural Networks for Spatio-Temporal Data Mining (Seismic Data)”, in this study he will be implementing NeuCube (Brain Computer Interface i.e. Spiking neural Networks), as well as NeuCom (Evolving Connectionist Systems) and WEKA (a traditional data mining software) on the seismic data and compare them based on the prediction of accurate and early events as well as the deep learning capacity.

PHD COMPLETIONS: William Edward Paul Davidson and Muhaini Othman defended their PhD thesis successfully.

STAFF APPOINTMENTS Neelava Sengupta, Maryam Gholami Doborjeh and Akshay Raj Gollahalli were appointed as Part time Research Assistants at KEDRI.

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VISITORS AT KEDRI: Assoc. Prof. Hideaki Kawano is currently with the Department of Electrical and Electronics Engineering, the Faculty of Engineering, Kyushu Institute of Technology in Japan. His research interests include image processing and understanding, soft computing, and intelligent systems. Hideaki is presently a visiting professor at KEDRI from June 2nd 2015 to March 31st, 2016. His research topic in KEDRI is on human emotions, consciousness, and neurocomputing.

Pritam Bose, a Master student from the University of Trento, Italy, is a visitor at KEDRI from 16th of Sep 2015 - 11 Dec 2015

Martina Fanghella from the University of Trento, Italy, visitor at KEDRI from 9th of March 2015 - Sep 2015.

Assoc. Prof. Gao Tao from the North China Electric Power University (Seal) China, visitor at KEDRI from the 11th March 2015 - 28th Feb 2016.

EVENTS Conferences: The Neuro-Computing and Evolving Intelligence Conference (NCEI 2015) hosted by KEDRI on 19th & 20th Feb 2015

The conference was attended by 85 participants comprising of large groups from the Chinese Academy of Sciences, Shanghai Jiao tong University and University Technology Malaysia, with whom KEDRI has collaborative agreements. The rest of the attendees were from the UK, Japan, from our partner universities in NZ (UoA, Otago, Canterbury, Lincoln, Victoria), from AUT and from Auckland based companies.

The main highlights of the Conference were:

• A demonstration of a very high quality and world-class research, as commented by the participants from the UK, China and Malaysia.

• Although not funded, the collaborative NZ INTERACT CoRE proposal team continues its interaction and is building momentum.

• The 12 collaborative projects by AUT groups, funded under the umbrella of the SRIF INTELLECTE project were very successful.

• The NeuCube neurocomputing system, that opens new opportunities for both theoretical and application collaborative research, was demonstrated.

RIO Showcase – 23rd August 15: At the expo, KEDRI displayed the first Neurocomputer in Asia-Pacific and the South Hemisphere called NeuCube, based entirely on neuromorphic computations.

NeuCube is KEDRI developed and patent protected IP owned by AUT, funded by AUT SRIF Funds. It is based entirely on artificial spiking neural networks of thousands and millions of spiking neurons, implemented both in software and hardware. It has the speed of a supercomputer, but consuming 10 times less power. The most important part of NeuCube though is our patented methodology for solving big data problems to be demonstrated as proof of concepts at the RIO expo on: brain data; ecological data for individual stroke prediction (95% accuracy one day ahead); seismic data for predicting earthquakes in ChCh (90% accuracy 6 hours ahead); business and financial data; brain computer interfaces and other.

COLLABORATION KEDRI: 5 Years of Special Cooperation Between 'AUT' and 'PKU'

05/10/2015 – Auckland University of Technology's 'Knowledge Engineering and Discovery Research Institute' (KEDRI) signed an agreement with Key Laboratory of Machine Perception, Peking University, in 2010. This year, the involved parties celebrate five years of cooperation.

The Knowledge Engineering and Discovery Research Institute (KEDRI) signed an agreement with Key Laboratory of Machine Perception, Peking University, in 2010. This year, the involved parties celebrate five years of cooperation. This broadly covers exchange of educational materials and academic publications;

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exchange of faculty members for research, consulting and lecturing; exchange of graduate students for study and research; co-supervision of PhD students; applications for joint research projects funded by China and New Zealand. The collaborative project is currently led at AUT by Professor Nikola Kasabov, Chair of Knowledge Engineering in the School of Computer and Information Sciences.

Several other Chinese tertiary education and research institutions have also joined the project over the period, including: China Academy of Sciences Institute for Automation (joined 2009); Shanghai Jiaotong University and Xinjiang University (joined 2010); Zhejiang University (joined 2014).

Specifically, the objectives of a project of coordination between the above partners included the following:

Development of novel neurocomputing methods and software and hardware technologies for complex spatio-temporal brain data modelling.

Based on the neurocomputing technologies, development of a novel methodology and prototype system for brain-machine interfaces and neurorehabilitation robotics.

Development of personalised modelling methods and systems for stroke data analysis with respect to risk evaluation and outcome prognosis.

2015: Photo Professor Kasabov visits KEDRI partners Dr. Wang and Professor Yang, Shanghai.

It follows that the project has been hugely successful, with large contributions made to joint publications, including the following:

2014 - Zhang, W., Yang, J., Jia, W., Kasabov, N., Jia, Z., & Zhou, L. Unsupervised Segmentation Using Cluster Ensembles. 21st International Conference, ICONIP 2014. Kuching, Malaysia, November 3-6,2014. Neural Information Processing, Lecture Notes in Computer Science, Volume 8836, part III, pp 76-84. doi: 10.1007/978-3-319-12643-2_10.

2014 - Tu, E., Yang, J., Jia, Z., & Kasabov, N. Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework. 21st International Conference, ICONIP 2014. Kuching, Malaysia, November 3-6,2014. Neural Information Processing, Lecture Notes in Computer Science, Volume 8834, part I, pp 86-94. doi: 10.1007/978-3-319-12637-1_11

2014- Hartono, R., Pears, R., Kasabov, N., & Worner, S. (2014). Extracting Temporal Knowledge from Time Series: A Case Study in Ecological Data. In 2014 International Joint Conference on Neural Networks (IJCNN) (pp. 4237-4243). Beijing, China: IEEE. doi:10.1109/IJCNN.2014.6889918

2014 - Tu, E., Kasabov, N., Othman, M., Li, Y., Worner, S., Yang, J., Jia, Z. NeuCube(ST) for Spatio-Temporal Data Predictive Modelling with a Case Study on Ecological Data. In 2014 International Joint Conference on Neural Networks (pp. 638-645). Beijing, China: IEEE. doi:0.1109/IJCNN.2014.6889717

2014 - Wubuli, A., Zhen-Hong, J., Xi-Zhong, Q., Jie, Y., & Kasabov, N. Medical image enhancement based on shearlet transform and unsharp masking. Journal of Medical Imaging and Health Informatics, 4(5), 814-818. doi:10.1166/jmihi.2014.1326

2014 - Ling-Ling, L., Zhen-Hong, J., Xi-Zhong, Q., Jie, Y., & Kasabov, N. White matter lesions change detection in MR images based on fuzzy nearness and non-subsampled shear waves. Journal of Medical Imaging and Health Informatics, 4(6), 953-956. doi:10.1166/jmihi.2014.1348

2014 - Tu, E., Cao, L., Yang, J., & Kasabov, N. (2014). A novel graph-based k-means for nonlinear manifold

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clustering and representative selection. Neurocomputing. doi:10.1016/j.neucom.2014.05.067

AWARDS Dean's Excellence Award for Outstanding Performance in Postgraduate Studies 2015. Elisa Capecci, PhD student of KEDRI received Dean's Excellence Award for Outstanding Performance in Postgraduate Studies 2015

DCT Professional Staff Employee of the Year 2015 On 10th of December, 2015, Joyce D'Mello received the DCT Professional Staff Employee of the Year award.

DCT Allied Staff Employee of the month

Joyce D'Mello was awarded DCT Allied Staff Employee of the month.

Joyce D'Mello received the KEDRI Award for Effort and Professionalism On the 18th of December, Joyce D'Mello received the KEDRI Award for Effort and Professionalism.

E.Capecci and M.Gholami Doborjeh received the KEDRI Award for Efforts & Achievements On the 18th of December, the PhD students Elisa Capecci and Maryam Gholami Doborjeh received the KEDRI Award for Efforts & Achievements.

University Medal At the VC's Excellence Awards on 22nd October 2015, Professor Nikola Kasabov, Director, Knowledge Engineering and Discovery Research Institute, Faculty of Design and Creative Technologies was awarded the University Medal as an AUT staff member for a sustained and outstanding contribution that reflects and enhances the academic development and reputation of the university.

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EVENTS 25th November 2015 - NeuLab Opening NeuLab Opening:

The Vice Chancellor opened KEDRI’s NeuLab, the first and perhaps the only neurocomputing laboratory in NZ, on 25th November at 4 p.m. It is anadvanced data

science laboratory that will have an important role in relation to the global big data challenges. The NeuLab offers advanced generic data analytics owned as IP by AUT, including the NeuCube system based on the latest development of spiking neural networks, an EEG laboratory, VR visualisation, robotic techniques and others. The plan is to make the NeuLab an incubator for new research on complex data that can result in new scientific publications, new PhD studies, new technologies across applications in health, engineering, environment and business through collaborative work at AUT, nationally and internationally.

The Vice Chancellor took the opportunity of awarding the University Medal to Prof. Nikola Kasabov in person as he was unable to attend the VC’s Excellence Awards on 22nd October 2015.

NCEI’15

NCEI'15 CONFERENCE AUT - KEDRI

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VENUE

Auckland University of Technology, WG Sir Paul Reeves Building, level 1, room 126, 2 Governor Fitzroy Place, Auckland 1010 New Zealand.

"INTELLIGENT INFORMATION TECHNOLOGIES FOR BIG DATA"

TOPICS:

• Big and Stream Data Analytics • Spiking Neural Network Computation • High Performance Neuromorphic System • Novel Brain-Computer Interfaces (BCI) • Novel Motion Data Analysis Technology • Predictive Personalised Modelling of non-

Communicable Diseases • Predicting Response to Treatment • Personalised Modelling in Bioinformatics • Predictive Modelling on Ecological and

Environmental Data • Big Data in Radio-Astronomy • Computer Vision and Image Processing for

Dynamic Data Analysis • Visualisation of Scientific Data • Novel Human-Computer Interfaces • Complex System Optimisation • Collaborative and Distributed Systems Design • Selected full papers will be published after the

conference in special issues of Evolving Systems and Springer Series in Bio-/Neuroinformatics.

PUBLICATIONS Book Chapters

• Kasabov, N. (2015). Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic. In J. Kacprzyk, & W. Pedrycz (Eds.), Springer Handbook of Computational Intelligence (pp. 771-782). Springer Berlin Heidelberg. doi:10.1007/978-3-662-43505-2_40

• Kasabov, N. (2015). Integrative computational neurogenetic modelling. In Brain Mapping: An Encyclopedic Reference (Vol. 1, pp. 667-674).

Academic press: Elsevier. doi:10.1016/B978-0-12-397025-1.00349-3

Journals • Wu, H., Gao, L., & Kasabov, N. (2015).

Inference of cancer progression from somatic mutation data. ScienceDirect, 234-238. doi:10.1016/j.ifacol.2015.12.131

• Gao, T., & Kasabov, N. (2015). A method used for Dotted Data Matrix image processing. Journal of Computational Methods in Science and Engineering, 15, 685-693. doi:10.3233/JCM-150581

• Gholami, M., Wang, G., Kasabov, N., Kydd, R., & Russell, B. (2015). A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data from Healthy versus Addiction Treated versus Addiction Not Treated Subjects. IEEE Transactions on Biomedical Engineering. doi:10.1109/TBME.2015.2503400

• Zhang, Y. -C., Jia, Z. -H., Qin, X. -Z., Yang, J., & Kasabov, N. (2015). Unsupervised detection of different SAR images based on improved NSCT domain image fusion algorithm. Guangdianzi Jiguang/Journal of Optoelectronics Laser, 26(10), 2023-2030. doi:10.16136/j.joel.2015.10.0252

• Wang, J., Li, Q., Jia, Z., Kasabov, N., & Yang, J. (2015). A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain. Optik, 126(20), 2508-2511. doi:10.1016/j.ijleo.2015.06.019

• Liu, L., Jia, Z., Yang, J., & Kasabov, N. (2015). A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking. International Journal of Imaging Systems and Technology, 25(3), 199-205. doi:10.1002/ima.22137

• Capecci, E., Kasabov, N., & Wang, G. Y. (2015). Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment. Neural Networks, 68, 62-77. doi:10.1016/j.neunet.2015.03.009

• Breen, V., Kasabov, N., Kamat, A. M., Jacobson, E., Suttie, J. M., O'Sullivan, P. J., . . . Darling, D. G. (2015). A holistic comparative analysis of

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diagnostic tests for urothelial carcinoma: A study of Cxbladder Detect, UroVysion® FISH, NMP22® and cytology based on imputation of multiple datasets. BMC Medical Research Methodology, 15(1). doi:10.1186/s12874-015-0036-8

• Wu, H., Gao, L., Li, F., Song, F., Yang, X., & Kasabov, N. (2015). Identifying overlapping mutated driver pathways by constructing gene networks in cancer. BMC Bioinformatics. doi:10.1186/1471-2105-16-S5-S3

• Tu, E., Yang, J., Kasabov, N., & Zhang, Y. (2015). Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance. Neurocomputing, 157, 173-186. doi:10.1016/j.neucom.2015.01.020

• Feigin, V., Krishnamurthi, R., Bhattacharjee, R., Parmar, P., Theadom, A., Hussein, P., . . . Tobias, M. (2015). A new strategy to reduce global burden of Stroke. Stroke, 46, 1740-1747.

• Kasabov, N., & Capecci, E. (2015). Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes. Information Sciences, 294, 565-575. doi:10.1016/j.ins.2014.06.028

• Wang, J. -J., Jia, Z. -H., Qin, X. -Z., Yang, J., & Kasabov, N. (2015). Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast. International Journal of Imaging Systems and Technology, 25(1), 7-14. doi:10.1002/ima.22115

• Kasabov, N. (2015). Evolving Connectionist Systems for Adaptive Learning and Knowledge Discovery: Trends and Directions. Knowledge-Based Systems. doi:10.1016/j.knosys.2014.12.032

Conference Papers • Sengupta, N., Scott, N., & Kasabov, N. (2015).

Framework for knowledge driven optimisation based data encoding for brain data modelling using spiking neural network architecture. In Advances in Intelligent Systems and Computing Vol. 415 (pp. 109-118). Springer Verlag. doi:10.1007/978-3-319-27212-2_9

• Gholami Doborjeh, Z., Kasabov, N., & Gholami, M. (2015). ERP Evidence for Predicting

Consumers’ Preferences to Beverage Logos. In 13 International Conference on Neuro-Computing and Evolving Intelligence 2015 (NCEI ‘15). Auckland, New Zealand.

• Peng, L., Hou, Z. -G., Kasabov, N., Bian, G. -B., Vladareanu, L., & Yu, H. (2015). Feasibility of NeuCube spiking neural network architecture for EMG pattern recognition. In Proceedings of the 2015 International Conference on Advanced Mechatronic Systems, ICAMechS Vol. 2015-October (pp. 365-369). Beijing, China: IEEE Computer Society. doi:10.1109/ICAMechS.2015.7287090

• Wang, G. Y., Kasabov, N., Capecci, E., Doborjeh, M. G., Kydd, R., & Russell, B. (2015). EEG-based application of the NeuCube framework in addiction research. In 13th International Conference on Neuro- Computing and Evolving Intelligence (NCEI) 2015. Auckland, New Zealand. Retrieved from http://kedri.aut.ac.nz/conferences/ncei15/book-of-abstracts

• Sengupta, N., Scott, N., & Kasabov, N. (2015). Framework for knowledge driven optimisation based data encoding for brain data modelling using spiking neural network architecture. In Advances in Intelligent Systems and Computing Vol. 415 (pp. 109-118). Springer Verlag. doi:10.1007/978-3-319-27212-2_9

• Gholami, M., & Kasabov, N. (2015). Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI and EEG Data. In NCEI 2015. Auckland, New Zealand.

• Kasabov, N. (2015). Neuromorphic Predictive Systems Based on Deep Learning. In Engineering Applications of Neural Networks Vol. 1. Springer. doi:10.1007/978-3-319-23983-5

• Peng, L., Hou, Z. -G., Kasabov, N., Peng, L., Hu, J., & Wang, W. (2015). Implementation of active training for an upper-limb rehabilitation robot based on impedance control. In Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015 (pp. 5453-5458). Institute of Electrical and Electronics Engineers Inc.. doi:10.1109/CCDC.2015.7161769

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• Capecci, E., Espinosa-Ramosy, J. I., Mammone, N., Kasabov, N., Dunn-Henriksenx, J., Wesenberg Kjaer, T., . . . Morabito, C. (2015). Modelling Absence Epilepsy Seizure Data in the NeuCube Evolving Spiking Neural Network Architecture. In Neural Networks Proc. IJCNN 15 (pp. 1-8). IEEE. doi:10.1109/IJCNN.2015.7280764

• Peng, L., Hou, Z. -G., Kasabov, N., Hu, J., Peng, L., & Wang, W. (2015). sEMG-based torque estimation for robot-assisted lower limb rehabilitation.. In IJCNN. IEEE. doi:10.1109/IJCNN.2015.7280449

• Gholami, M., & Kasabov, N. (2015). Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data. In Neural Information Processing (pp. 191-198). Istanbul: Springer International Publishing Switzerland 2015. doi:10.1007/978-3-319-26561-2_23

• Jia, S., Liang, Y., Chen, X., Gu, Y., Yang, J., Kasabov, N., . . . Qiao, Y. (2015). Adaptive Location for Multiple Salient Objects Detection. In Neural Information Processing (pp. 411-418). Istanbul: Springer International Publishing Switzerland 2015. doi:10.1007/978-3-319-26561-2_46

• Zhao, Y., Qiao, Y., Yang, J., & Kasabov, N. (2015). Abnormal Activity Detection Using Spatio-Temporal Feature and Laplacian Sparse Representation.. In Neural Information Processing (pp. 410-418). Istanbul: Springer International Publishing Switzerland 2015. doi:10.1007/978-3-319-26561-2_49

• Li, L., Kasabov, N., Yang, J., & Yao, L. (2015). Poisson Image Denoising Based on BLS-GSM Method. In Neural Information Processing (pp. 513-522). Istabul: Springer International Publishing Switzerland. doi:10.1007/978-3-319-26561-2_61

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Contact Details:

Professor Nikola Kasabov Director of KEDRI

Email: nkasabov@aut.ac.nz Phone: +64 9 921 9506

Joyce D’Mello

Administration Manager of KEDRI Email: joyce.dmello@aut.ac.nz

Physical Address:

Knowledge Engineering & Discovery Research Institute Auckland University of Technology

AUT Tower, Level 7, WT 701, Cnr Rutland and Wakefield str,

Auckland 1010 New Zealand

Web Page: www.kedri.aut.ac.nz