Conference Program

To download the full conference program click on   APCASE 2017 Conference program

To download  the conference proceedings  click on   APCASE 2017 proceedings (extended abstracts)


Friday, 10th of November 2017

Registration  (2.00pm – 6.00pm)

Workshop 1   (3.00pm – 5.00pm)

Presenter: Luke Brandt, Rabbit Forms (Studio), Zgierz/Lodz, Poland.

Title: Workshop on Application, Design and the Technology of 3D Printing.

Abstract: If you ever wanted to get a hands-on experience with 3D Printers but never had a chance, then this is the workshop for you.  The popularity and awareness of 3D Printing technology are expanding at an enormous rate.     It Various technological barriers is breaking every day in modelling, design and manufacturing. What was impossible only just a few months ago is possible right now.  Everyone involved in Computer Assisted System Engineering and ICT needs to know at least the basic understanding of 3D printers and their capability. And yes, you’ll be able to gain exposure to the main facets of 3D Printing including 3D Scanning, 3D Modelling, smart materials, preparing the file for print, and finally, 3D Printing. This workshop provides a hands-on introduction and training of 3D printing technology for researchers, designers, engineers, technologists and hobbyists. This class is suitable for both novices and those more experienced with 3D Printing.

Bio: Luke (Lukasz) Brandt is passionate about modern technology and creative thinking. He studied engineering, computer science and he graduated from the Faculty of Design and Interior Architecture at the Academy of Fine Arts in Łódź. Poland.  Luke is a professional industrial designer, experimenter, an educator and 3D printing evangelist. One of his goal aims is to disseminate knowledge about 3D printing in the community at large. This goal is realised through the organisation of a variety of training, community-oriented events, workshops using 3D printers and rapid prototyping techniques. Luke Brandt engages in a variety of educational projects in collaboration with various institutions, museums, cultural centres. He collaborates with various educational institutions and universities, as well as, research centres and FabLabs. He provided hundreds of sessions and workshops on 3D printing technology. He has delivered virtually thousands of hours of training related to 3D printing design methods and additive manufacturing.



Saturday, 11th of November 2017

Registration  (8.00am – 6.00pm)
Welcome Speeches  (9.00am – 9.30am)
Keynote Speeches (9.30am – 12.30pm)

Presenter 1: Prof Robin Braun (PhD), University of Technology, Sydney, Australia

Title: Can we use new ways of modelling complex systems to optimise student learning?

Abstract: Students and the way they learn, combined with the learning programs and environments we provide for them are complex and intractable systems. They create the wonderful emergent properties of learning, capability and creativity. The fundamental question is this. Can we model the process using new agent-based modelling paradigms to both predict and optimise these emergent properties? This talk will explore both the learning system and the modelling paradigm, using NetLogo to see if the two can ever meet and if this may be useful to us.

Bio: Prof Robin Braun received the B.Sc.(Hons) from Brighton University in the UK, and the M.Sc.(Eng) and PhD from the University of Cape Town, South Africa in 1980, 1982 and 1986 respectively. Professor Braun started his academic career in 1986 at the University of Cape Town, where he was director of the Digital Communications Research Group. He moved to the University of Technology, Sydney, Australia, in 1998, where he occupies the Chair of Telecommunications Engineering. Prior to moving to academia, he spent 10 years in the industry, mostly with Philips and Plessey, where he worked on the design of precision electronic distance measuring equipment. His recent work has been in network protocols and Software Defined Networks. He has a strong interest in radar and remote sensing. Dr Braun has been active in the IEEE and URSI for many years, serving as URSI Commission C representative, as well as chairing and being on the technical committees of a number of international conferences or TPC chair, including ITHET since 2006. Professor Braun’s primary interests are in communications networks and sensor networks. He is interested in their theoretical constructs, middleware for their resources, routing algorithms and embedding such networks in feedback control systems. He has a deep interest in Complex Systems and their modelling. Professor Braun is a committed academic with a deep interest in new teaching paradigms and his current major work at UTS is the introduction of an engineering degree majoring in Data Engineering.


Presenter 2: Prof Carmen Paz Suárez Araujo (PhD), The University of Las Palmas of Gran Canaria, Spain

Title: Detection and monitoring of environmental pollutants and neurological pathologies using HUMANN-based intelligent systems

Abstract: This presentation discusses detection of environmental pollutants and the non-communicable diseases associated with ageing, as the diagnosis of dementia, are, at present, two different but significant issues in our society. The intelligent computing techniques can be a very good candidate that effectively manage these concerns. HUMANN-based intelligent systems deal with both challenges well. The building block of these systems is the HUMANN and its supervised version, HUMANN-S, for the detection of environmental pollutants and neurological disorders respectively. HUMANN is a biologically plausible feedforward hierarchical unsupervised modular adaptive neural network, which can work in domains with noise and overlapping classes. It works with no prior information of the number of different classes in the data. It deals with non-linear boundary class and with high dimensionality data vectors. It consists of an input layer and three modules hierarchically organised in the neural processing with different neurodynamics, connection topologies and learning laws. These modules are Kohonen, Tolerance and Labelling layers. HUMANN implements the two last stages of the general approach of the classification process, template generation and discrimination (labelling), in a transparent and efficient way. In HUMANN-S, a Perceptron type layer replaces the Labelling one.  HUMANN is appropriate for classification processes, performing blind clustering and the author(s) propose it for providing an intelligent computing solution for detection and monitoring of environmental pollutants including Polychlorinated Biphenyls (PCBs), Polychlorinated dibenzofurands (PCDFs) and Benzimidazole Fungicides (BFs) families of organochlorine compounds usually utilised in agriculture and industry. Use of these pollutants in large quantities may have adverse effects which have been detected after decades of their application. Hence, the detection of these pollutants and their mixtures in the environment is crucial.

Bio: Prof Carmen Paz Suárez Araujo, Professor of Computer Sciences and Artificial Intelligence at the Universidad de Las Palmas de Gran Canaria (ULPGC). She is BS and MS in Physics and PhD. in Computer Sciences. She currently is Director of Intelligent Computing, Perception and Big Data Research Group of ULPGC and Head of Computational Neuroscience Research Division at the Institute of Cybernetics Science and Technology of the ULPGC. The research group of Adaptive Neural Computing and Computational Neuroscience of the ULPGC was also headed for her since 2002 until 2015. She has been Director of Doctorate Programs of Neural Computing in Natural and Artificial Systems of the same University. She has also been Vice-Rector of the University of Las Palmas de Gran Canaria, Vice-Dean and Erasmus Departmental Coordinator of the Faculty of Computer Sciences of this University for many years. Her teaching activity has been essentially developed at the ULPGC, in Computer Sciences Engineering Degree and in PhD. Programs, principally devoted to Cybernetics, Neural Computing, Artificial Perception and Intelligent Computing & ITs in Social and Business fields. She has also been teaching in some Masters concerning with Computer Sciences and Biomedical Computing at the University Pontifical of Madrid and at several others European Universities. She has been Invited Professor in a broad range of European Universities, among others Fachhochschule Brandenburg (Germany), Institute of Chemical Technology of Praga (Czech Republic), University of Birmingham, Johannes Kepler Universitat Linz (Austria), Università degli Studi di Bologna (Italy), Wroclaw University of Technology (Poland). Comenius University (Slovakia), Centro da Complexidade Universidade Clasica de Lisboa, Universidad de Coimbra, Pomeranian University (Poland), etc. She has also done research stays in several universities: the University of Florida, Universidade de Lisboa, Comenius University and currently is the visiting professor at the University of Technology Sydney (UTS). She has an extensive research experience with more than 135 scientific articles and book chapters, 3 edited research books and more than 140 contributions to international and national congresses. Her research work has been award winning for several Spanish and international institutions, like the ULPGC, the Royal Spanish Academy of Doctors and some international conferences. She has also been Project Leader and Investigator of 19 Research in the international, national and regional ambits, Supervisor of Doctoral Thesis and more than 30 Dissertations. She is the referee of a wide range of international scientific journals, international congresses and several international and national Evaluation Agencies. She has been a general chairperson of several international congresses and she has participated as a member of Program Committee of a high number of national and international congresses as well. She has also been invited the speaker in more than 40 seminars and conferences. Her research fields are focused in: Natural and Artificial Neural Networks. Design of New Neural Architectures, Application of Neural Computation in Clinical and Environmental Domains, Biomedicine, Neuroinformatics and Bioinformatics. Intelligent Systems for Decision Making, Computational Neuroscience and Cognitive Computation: Neural communication models and learning.


Presenter 3: Prof David Goad, Sydney University and the University of New South Wales, Sydney, Australia

Title: Security and the Internet of Things: Why the next big IT Security Breach will likely be in IoT.

Abstract: This presentation introduces IoT security discussing recent events in IoT Security, common IoT security attack vectors and the newly evolving environment in terms of IoT security standards and regulation.

Bio: David Goad has over 30 years of industry experience having held senior leadership roles with recognized IT brands such as KPMG Consulting, Microsoft and Hitachi Solutions. Being a consummate entrepreneur David has created his own successful IT start-up, built it up to being a global award-winning business and then sold it off.  Currently, as a Post-Graduate Fellow at Sydney University, David teaches at both Sydney University and the University of New South Wales in the areas of Innovation, Business Applications, Digital Business Management and Accounting Information Systems.  David’s research areas are the Internet of Things, Business Models and Innovation. A published author he has presented his work on IoT Architecture at the American Conference on Information Systems ( and has recently published a book on IoT Strategy for Business Directors (  David is a member of the IoT Association of Australia and provides consulting advice to entrepreneurs starting new businesses and to enterprises developing their IoT strategy.

Paper Presentations  (2.00 pm – 6.00 pm) – 2 Parallel Sessions (Sunday, 11th of Nov)

Note: Time limits for each paper presentation is 15 minutes plus 5 minutes for questions.



Sunday, 12th of November 2017

Registration  (8.00am – 6.00pm)
Keynote Speeches (9.00 am -12.30pm)

Presenter 4: Prof Sean He (PhD), University of Technology, Sydney, Australia 

Title: Robust Surgical Endoscope Tracking and Navigation

Abstract: Medical endoscopic procedures with a surgical tool called endoscope are widely performed in minimally invasive surgery (MIS). The endoscopes have been integrated with cameras at their distal tip and directly inserted into the body through natural orifices (e.g., mouth and nose) to observe the interior of hollow organs, e.g., sinuscopes for sinus inspection, colonscopes for colon/rectum cancer detection, angioscopes for examining the lumen of blood vessels, and bronchoscopes for lung and bronchus cancer diagnosis, staging, and treatment. Nowadays, navigated endoscopy is generally agreed to be the next generation of interventional or surgical endoscopy. It usually combines pre- and intra-operative imaging information to guide physicians during endoscopic procedures. However, endoscope three-dimensional motion tracking that spatially and temporally synchronizes various sensory information still remains challenging for developing different endoscopic navigation systems. In this respect, endoscope tracking and navigation aim at fusing the modality information to accurately and robustly locate or fly through the endoscope at any interest of regions. Unfortunately, fusing the multimodal information is still an open issue due to the information incompleteness, e.g., image artefacts, tissue deformation, and sensor output inaccuracy in computer-assisted endoscopic interventions. In this talk, a novel framework of multimodal information fusion is presented to use evolutionary computing for endoscopic navigation systems. As most popular evolutionary computing algorithms, adaptive particle swarm optimizer and differential evolution are modified to precisely localize the endoscope and estimate the movement.

Bio: Prof Sean He, as a Chief Investigator, has received various research grants including four national Research Grants awarded by Australian Research Council (ARC). He is the Director of Computer Vision and Pattern Recognition Laboratory at the Global Big Data Technologies Centre (GBDTC). He is also the Director of UTS-NPU International Joint Laboratory on Digital Media and Intelligent Networks. He is an IEEE Senior Member and has been an IEEE Signal Processing Society Student Committee member. He is a leading researcher in several research areas including big-learning based human behaviours recognition on a single image, image processing based on hexagonal structure, authorship identification of a document and a document’s components (e.g., sentences, sections etc.), network intrusion detection using computer vision techniques, car license plate recognition of high speed moving vehicles with changeable and complex background, and video tracking with motion blur. He has played various chair roles in many international conferences such as ACM MM, MMM, IEEE BigDataSE, IEEE CIT, IEEE AVSS, IEEE TrustCom, IEEE ICPR and IEEE ICARCV. In recent years, he has many high-quality publications in IEEE Transactions journals such as IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems, and IEEE Transactions on Multimedia; and in Elsevier’s journals such as Pattern Recognition, Signal Processing, and Computer Networks. He has also had papers published in premier international conferences and workshops such as ACL, IJCAI, CVPR, ECCV and ACM MM. He has recently been a guest editor for various international journals such as Journal of Computer Networks and Computer Applications (Elsevier), Future Generation Computer Systems (Elsevier) and Signal Processing (Elsevier). He is currently an Advisor of HKIE Transactions.



Presenter 5: Dr Shui Yu, Deakin University, Melbourne, Australia.

Title: Networking for Big Data: Challenges and Opportunities

Abstract: Big Data is one of the hottest topics in our communities, and networking is an indispensable cornerstone for the fancy big data applications. As a result, there is an emerging research branch, Networking for Big Data (NBD), in networking and communication fields. In this talk, we will first overview the current landscape of this energetic area, and then present the unprecedented challenges in this new domain, and finally discuss the current research directions in the main topics in networking for big data. We humbly hope this talk will shed light for forthcoming researchers to further explore the uncharted part of this promising land

Bio: Dr Shui Yu is currently a Senior Lecturer at School of Information Technology, Deakin University. He is a member of Deakin University Academic Board (2015-2016), a Senior Member of IEEE, and a member of AAAS and ACM, the Vice Chair of Technical Subcommittee on Big Data Processing, Analytics, and Networking of IEEE Communication Society, and a member of IEEE Big Data Standardization Committee.  Dr Yu’s research interest includes Security and Privacy in Networking, Big Data, and Cyberspace, and mathematical modelling. He has published two monographs and edited two books, more than 150 technical papers, including top journals and top conferences, such as IEEE TPDS, IEEE TC, IEEE TIFS, IEEE TMC, IEEE TKDE, IEEE TETC, and IEEE INFOCOM. Dr Yu initiated the research field of networking for big data in 2013. His h-index is 27.  Dr Yu actively serves his research communities in various roles. He is currently serving the editorial boards of IEEE Communications Surveys and Tutorials, IEEE Access, IEEE Journal of Internet of Things, IEEE Communications Magazine, and a number of other international journals. He has served more than 70 international conferences as a member of the organizing committee, such as publication chair for IEEE Globecom 2015 and 2017, IEEE INFOCOM 2016 and 2017, TPC co-chair for IEEE BigDataService 2015, IEEE ATNAC 2014, IEEE ITNAC 2015; Executive general chair for ACSW2017. More information of Dr Yu can be found at

Presenter 6: A/Prof Haiying Xia (PhD), Guangxi Normal University, Guilin, China.

Title: Diagnosis of Diseases Using Robust Vessel Segmentation of Fundus Images

Abstract: Robust vessel segmentation of fundus images is of great interest for better diagnosis of many diseases like diabetic retinopathy, retinopathy of prematurity, vein occlusions and so on. Here, she analyzes several challenging factors existed in vessel segmentation of fundus images. Then two novel methods are explained for segmenting the retinal vessels. Finally, experimental results are conducted to verify the performance of their methods.

Bio: A/Prof Haiying Xia received her B.Sc. in Communication Engineering in 2005 and consecutively M.Sc. in Information and Signal Processing in 2007. She completed her PhD in Circuits and Systems at Huazhong University of Science and Technology in 2011. Since then, Dr Xia has been working at Guangxi Normal University for nearly 4 years.  She has 4 years’ experience of teaching the subjects such as Signal and System, Digital Signal Processing, Digital Image Processing, C++ programming and C programming.  A/Prof Haiying Xia current Research interests include Pattern Recognition, Data mining, AI, Biomedical Image Processing, as well as, Affective Computing.

Workshop 2

Presenter: Prof Robin Braun, University of Technology, Sydney, Australia

Title: Modern Telemetry, Data Engineering and the Future of Software Defined Networking (SDN).

Abstract: This workshop addresses fundamental questions regarding the future and applications of Software Defined Networking. Various concepts, elements and cases studies related to of SDN technology are discussed in the context of 5G models of telecommunication.



Paper Presentations  (2.00 pm – 6.00 pm) – 2 Parallel Sessions (Sunday, 12th of Nov)

Note: Time limits for each paper presentation is 15 minutes plus 5 minutes for questions.