Special Session

Special Session 1:
Intelligent Human-Centred Computing [Call for paper]
 
Special Session Chair:
Azizi Ab Aziz, Universiti Utara Malaysia
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In recent years, scientific research with special focus on human functioning such as cognitive science, bio-psychology, neuroscience, and biomedical sciences have made substantial progress in providing an increased insight in the various physical and mental aspects of human functioning through the development of a number of models. Within these approaches, it opens new opportunities towards the development of personalized and human-centred computing. For example, an intelligent companion agent or robot in our reading room may monitor us and warn us when we are falling into cognitive stress or need some rest. As another example, an elderly person may wear a device with intelligent software that monitors his or her wellbeing and generates a warning or support when a dangerous situation is noticed. The special session can play an important role, for example, to get software developers, researchers, and designers in the bio-psychological, computer science, electronic engineering disciplines interested in human-centric application as a high-potential application area for further developments in their disciplines. As part of the interaction, specifications may be generated for experiments to be addressed by the human-oriented with heavy implementation in computer science.
 

 
Special Session 2:
Web Mining and Content Analytics [Call for paper]
 
Special Session Chair:
Nurfadhlina Mohd Sharef (Universiti Putra Malaysia, Malaysia)
Kazutaka Shimada (Kyushu Institute of Technology, Japan)
Patricia Anthony (Lincoln University, New Zealand)
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Web mining and content analytics continue to be among the fundamental techniques of data science for web due to its ability to extract knowledge from Web data, including Web documents, hyperlinks between documents, usage logs of web sites, etc. A wide range of applications of web mining and content analytics could benefit commercial and research such as recommendation system, sentiment analysis and predictive analytics. Integration of diverse data has posed interesting challenges for bridging structured and unstructured data such as algorithms for large scale content mining, visualization of web data, multi-lingual and cross-lingual analysis, question answering from the web, summarization of multimodal data which need to be solved due to their promising returns. It is indeed pertinent for the scientific community to address and explore the gaps in the existing solutions so that the potential of the web could be exploited to the maximum. The aim of this session is therefore to draw a picture of the recent advances and challenges in evolving Web mining and content analytics and particularly, aims at soliciting contributions dealing with real-world applications.
 

 
Special Session 3:
Web Mining, Services and Security [Call for paper]
Special Session Chair:
Assoc Prof Dr Mohd Farhan Hj MD Fudzee, Universiti Tun Hussein Onn Malaysia
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This special session provides the opportunity for researchers to present their recent work on web mining, services and security. Both are important fields as they largely defined the Internet nowadays. The Web mining, services, and security technologies will redefine the way that companies do business and exchange information in twenty-first century. Ongoing issues in web mining, services, and security including performance of data mining in web, scalability, mobile adaptation, service integration, energy efficiency, and many others are still on the quest. On the other hand the security issues will always grow to preserve integrity with the new requirements that comes over the time.

 
Special Session 4:
Bioinspired Visual Cortex for Computer Vision Applications [Call for paper]
 
Special Session Chair:
Dr. Nur Surayahani Suriani, Universiti Tun Hussein Onn Malaysia
Mohd Helmy Abd Wahab, Universiti Tun Hussein Onn Malaysia
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Humans can easily understand other people’s actions through visual systems, while computers cannot. Studies in biological vision are ranging from purely functional inspiration to methods that utilise models that were primarily developed for explaining biological observations. Bio-inspired visual cortex model would not only shed light into functioning of biological vision but also provide innovative solutions to engineering problems tackled by computer vision. Therefore, bio-inspired computational model is intended to filling the critical gap in computer vision applications.The evolvement of bio-inspired computational model is expected to provide new insights and a starting point for investigators interested in the design of biology-based computer vision applications and pave a way for development of synergistic models of artificial and biological vision. The major aim of this workshop is to bring researchers from different fields to address issues related in visual representation and information processing of natural scenarios faced in computer vision solved by cognitive biological systems. Further contributions are dealing with human computer interactions, biomechanics and smart environment applications.
 

 
Special Session 5:
Advances of Data Stream Processing, Stream Mining and Its Applications [Call for paper]
 
Special Session Chair:
Dr. Mario Diván (Universidad Nacional de La Pampa, Argentina)
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The data stream processing refers to one area in the data management related with the unbounded data arriving in real time from heterogeneous data sources, which requires a new kind of analysis, design, implementation and processing strategy. These unbounded data arrive continuously in an unordered and possibly inconsistent way and there are not control about the data source. So, the stream mining consists in a process oriented to extracting knowledge structures from the continuous data streams. While the Big Data area have worked around the offline big data repositories and its impact is considerable in the now economy, the businesses and the governments each time requires information more updated, precise and current for their operations in this globalized world. The uses of the data stream processing are very wide, their applications come from different sectors such as the telecommunications, health cares, financials, homeland security, between others. Because the data arrive in continuously, possibly inconsistent and unordered the learning strategies for building, updating and applying models in the decision-making processes has changed because the context has changed, and for that reason new approaches are necessaries. The new context defined by the data stream processing requires fitting and evolution in different areas of the data management and data mining, for example and not limited to: data quality, query processing, data storing, memory compression, data processing, processing architecture, clustering, classification, association rules, etc. So, this new context suggests an incremental approach for the data processing, the learning or the applications of the learned models. Today, the current capabilities associated with the computation power does that the demand for getting information at instant be current coin. Moreover, the projected capacities associated with different computing devices foster many applications and researching lines associated with this area. The aim of this session is therefore to draw a picture of the recent advances and challenges in data stream processing, stream mining and particularly, aims at soliciting contributions dealing with real-world applications.

 
Special Session 6:
Augmented Reality Applications [Call For Paper]
 
Special Session Chair:
Dr. Nan Md. Sahar, Universiti Tun Hussein Onn Malaysia
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Augmented reality (AR) perceived as the technology of the future.  Several years ago, the term augmented reality are very peculiar to the mass, but today, numerous application emerging every day. All From the steady development of ground breaking augmented realty, where it transforming the way the mass see and learn from their surrounding and is revolutionizing companies’ business models. The ability to bridge the gapped between the digital and real world producing extraordinary experiences. Starting from virtual reality (VR), the virtually processed environment by computer to augmenting the user reality into new perspective and information rich surrounding and now the hybrid of the two world, a mixed reality (MR). Top brands and companies has make a special places for augmented reality on achieving wider market. Virtual fitting room in e-commerce, digital marketing in form of gaming, geolocation based apps suggesting the  navigation for the best burger in town and  life 3D images popping out of a regular books are just a few examples augmented reality has storm it way into our daily routines.
The major aim of this workshop is to bring researchers from different fields to address issues related in augmented reality in term visual representation, information processing and applications into perspective. This will further contribute toward more advanced augmented reality technology implementation.

 
Special Session 7:
Deep Learning Applications [Call for paper]
 
Special Session Chair:
Dr. Nan Md. Sahar, Universiti Tun Hussein Onn Malaysia
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It has always been the ultimate human goal and will be the highest achievement either to mimic, to develop or to create a mind that able to make decision as good as or even better than human brain able to do.  A machines that possessed the same characteristics of human intelligence, an Artificial Intelligence. Artificial Intelligence has been part of our imaginations and bubbling in research labs since a handful of computer scientists rallied around the term in. In the decades since, Artificial Intelligence has alternately been heralded as the key to our civilization’s brightest future, and tossed on technology’s trash heap as a hare brained notion of over-reaching propeller heads. The practically infinite storage , big data movement  along with the availability of GPU that make parallel processing ever faster, cheaper and more powerful has exploded the Artificial Intelligence. From Artificial Intelligence, where human intelligence exhibited by machine move to Machine Learning, the approach to achieve Artificial Intelligence. And now the era of Deep Learning, the technique for implementing the Machine Learning.  Deep Learning has enabled many practical applications of Machine Learning and by extension the overall field of Artificial Intelligence. Deep Learning crunches down tasks in ways that makes all kinds of machine assists seem possible, even likely. Driverless cars, a better preventive healthcare, even better movie recommendations, are all here today or on the horizon. Deep Learning is the present and the future.The major aim of this workshop is to bring researchers from different fields to address issues related to Artificial Intelligences solved by Deep Learning systems. Further contributions toward advancement of Deep learning implementation will be expected.
 

 
Special Session 8:
Sports Informatics and Analytics [Call for paper]
 
Special Session Chair:
Aida Mustapha, Universiti Tun Hussein Onn Malaysia
Noor Azah Samsudin, Universiti Tun Hussein Onn Malaysia
Mohd Helmy Abdul Wahab, Universiti Tun Hussein Onn Malaysia
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Match statistics provide records of meaningful events that occur during the match, such as the score with time, name of scorer or name of injured players. Match statistics also include raw technical data such as the speed, distance, player separation or ball possession. After every match, the data is then processed and analyzed to form an analysis report that can guide both coaches and players in assessing the team performance during the match. While data from match statistics is useful to formulate game strategies, sports data collection begins with physiological data of individual athletes and players during training. Data from physical tests may cover physical skills (e.g., speed, agility, strength, vigor), mental skills (e.g., creativity, calmness, confidence), and technical skills (e.g., finishing, passing, shooting) of individual athletes or players. In the essence, sports informatics deal with the resources, techniques, and applications required to optimize the acquisition, analysis, and use of sports data. With the rise of sports data website covering wide range of sports such as the American football, baseball, rugby, soccer and even golf, sports analytics have become an essential methodology to transform the sports data into meaningful and useful information used for decision making and strategic planning. Sports analytics exploit the full potential of the data through formulation of data-driven approach to design training scheme, prevent injuries, propose game strategies, visualize game flow, analyze opponent strategies or predict match outcome. SAIN ‘18 aims to provide a platform for exchange of research ideas and discussion of practical applications of sports analytics, serving team owners, general managers, coaches, fans, and academics. We invite contributions on both individual or team sports with the objective to improve our understanding of the game or strategies for improving a team or a league. SAIN will be interdisciplinary in nature, and we encourage submissions from both academics and practitioners with a generic interest in sports.