LING Tok Wang, IEEE Senior Life Member
National University of Singapore, Singapore
Dr LING Tok Wang is a professor of the Department of Computer Science, School of Computing at the National University of Singapore. He was the Head of IT Division, Deputy Head of the Department of Information Systems and Computer Science, and Vice Dean of the School of Computing of the University. Before joining the University as a lecturer in 1979, he was a scientific staff at Bell Northern Research, Ottawa, Canada. He received his Ph.D. and M.Math., both in Computer Science, from University of Waterloo (Canada) and B.Sc.(1st class Hons) in Mathematics from Nanyang University (Singapore). His research interests include Data Modeling, Entity-Relationship Approach, Object-Oriented Data Model, Normalization Theory, Logic and Database, Integrity Constraint Checking, Semi-Structured Data Model, XML Twig Pattern Query Processing, ORA-semantics based XML and Relational Database Keyword Query Processing. He has published more than 230 international journal/conference papers and chapters in books, all in database research areas. He also co-edited 13 conference and workshop proceedings, co-authored one book, and edited one book.
He is an ER Fellow, an ACM Distinguished Scientist, IEEE Senior Life Member, and Senior Member of Singapore Computer Society. He received the ACM Recognition of Service Award in 2007, the DASFAA Outstanding Contributions Award in 2010, and the Peter P. Chen Award in 2011.
Abstract: From Structure-based to Semantic-based: Towards Effective XML Keyword Search
Keyword search in XML has gained popularity as it provides a user-friendly and easy way for users to query the XML data. Existing XML keyword search approaches on XML trees such as Lowest Common Ancestor (LCA) and its variants such as SLCA, MLCA, VLCA, and ELCA, are all LCA-based and they rely on the hierarchical structure of the XML document. This causes serious problems in processing XML keyword queries, such as meaningless answers, duplicated answers, incomplete answers, missing answers, and schema dependent answers. We analyze these serious problems of existing keyword search methods and show that the main reason of causing these problems is due to the unawareness of the Object-Relationship-Attribute (ORA) semantics in XML.
With the knowledge of ORA-semantics in the XML document, we are able to detect duplications of objects and relationship and resolve the first three problems of the LCA-based search approaches.
We present a new novel concept, called Common Relative (CR), and an algorithm based on the CR semantics to ﬁnd more answers beyond LCA, i.e., the missing answers. The algorithm is independent of schema designs of the same data content as well.
We extend the keyword query language to include keywords that match the metadata, i.e., the tag names in XML document, and with group-by and aggregate functions including count, max, min, sum, etc. To process extended keyword queries correctly, we must use the ORA-semantics in the XML document to detect duplications of objects and relationships. Without using ORA-semantics, keyword queries with aggregate functions will be computed wrongly and return incorrect answers.
ORA-Semantics can also be used to improve the quality of many database research areas such as RDB keyword search, data and schema integration, etc.
Chin-Chen Chang, IEEE and IET Fellow
Feng Chia University, Taiwan
Professor Chin-Chen Chang obtained his Ph.D. degree in computer engineering from National Chiao Tung University. His first degree is Bachelor of Science in Applied Mathematics and master degree is Master of Science in computer and decision sciences. Both were awarded in National TsingHua University. Dr. Chang served in National Chung Cheng University from 1989 to 2005. His current title is Chair Professor in Department of Information Engineering and Computer Science, Feng Chia University, from Feb. 2005. Prior to joining Feng Chia University, Professor Chang was an associate professor in Chiao Tung University, professor in National Chung Hsing University, chair professor in National Chung Cheng University. He had also been Visiting Researcher and Visiting Scientist to Tokyo University and Kyoto University, Japan. During his service in Chung Cheng, Professor Chang served as Chairman of the Institute of Computer Science and Information Engineering, Dean of College of Engineering, Provost and then Acting President of Chung Cheng University and Director of Advisory Office in Ministry of Education, Taiwan.
Professor Chang's specialties include, but not limited to, data engineering, database systems, computer cryptography and information security. A researcher of acclaimed and distinguished services and contributions to his country and advancing human knowledge in the field of information science, Professor Chang has won many research awards and honorary positions by and in prestigious organizations both nationally and internationally. He is currently a Fellow of IEEE and a Fellow of IEE, UK. And since his early years of career development, he consecutively won Institute of Information & Computing Machinery Medal of Honor, Outstanding Youth Award of Taiwan, Outstanding Talent in Information Sciences of Taiwan, AceR Dragon Award of the Ten Most Outstanding Talents, Outstanding Scholar Award of Taiwan, Outstanding Engineering Professor Award of Taiwan, Chung-Shan Academic Publication Awards, Distinguished Research Awards of National Science Council of Taiwan, Outstanding Scholarly Contribution Award of the International Institute for Advanced Studies in Systems Research and Cybernetics, Top Fifteen Scholars in Systems and Software Engineering of the Journal of Systems and Software, Top Cited Paper Award of Pattern Recognition Letters, and so on. On numerous occasions, he was invited to serve as Visiting Professor, Chair Professor, Honorary Professor, Honorary Director, Honorary Chairman, Distinguished Alumnus, Distinguished Researcher, Research Fellow by universities and research institutes. He also published over hundreds papers in Information Sciences. In the meantime, he participates actively in international academic organizations and performs advisory work to government agencies and academic organizations.
Abstract: Turtle Shell Based Information Hiding Mechanism
Steganography is the science of secret message delivery using cover media. A digital image is a flexible medium used to carry a secret message because the slight modification of a cover image is hard to distinguish by human eyes. In this talk, I will introduce some novel steganographic methods based on different magic matrices. Among them, one method that uses a turtle shell magic matrix to guide cover pixels’ modification in order to imply secret data is the newest and the most interesting one. Experimental results demonstrated that this method, in comparison with previous related works, outperforms in both visual quality of the stego image and embedding capacity. In addition, I will introduce some future research issues that derived from the steganographic method based on the magic matrix.
Dr. Sergei Gorlatch
University of Muenster, Germany
Prof. Sergei Gorlatch is an internationally acknowledged expert in the area of algorithms, architectures, software and applications for modern and emerging computer and networked systems. Sergei Gorlatch has been Full Professor of Computer Science at the University of Muenster (Germany) since 2003. Earlier he was Associate Professor at the Technical University of Berlin, Assistant Professor at the University of Passau, and Humboldt Research Fellow at the Technical University of Munich, all in Germany.
Prof. Gorlatch has about 200 peer reviewed publications in renowned international books, journals and conferences. He is often delivering invited talks at international conferences and serves at their program committees. Prof. Gorlatch was principal investigator in several international research and development projects in the field of parallel, distributed, Grid and Cloud algorithms and computing, as well as e-Learning, funded by the European Commission and by German national bodies. Among his recent achievements in the area of data management, communications and future internet is the novel Real-Time Framework (www.real-time-framework.com) developed in his group as a platform for high-level development of real-time, highly interactive applications like multi-player online games, advanced e-Learning, crowd simulations, etc. In the area of high-performance computing, his group has been recently developing a high-level SkelCL library (skelcl.uni-muenster.de/) for efficient programming of parallel algorithms on emerging parallel and distributed many-core systems with accelerators.
Abstract: Distributed Applications Based on Mobile Cloud Computing and Software-Defined Networks
We consider an emerging class of challenging networked
multimedia applications called Real-Time Online Interactive
Applications (ROIA). ROIA are networked applications connecting
a potentially very high number of users who interact with the
application and with each other in real time, i.e., a response
to a user’s action happens virtually immediately. Typical
representatives of ROIA are multiplayer online computer games,
advanced simulation-based e-learning and serious gaming. All
these applications are characterized by high performance and QoS
requirements, such as: short response times to user inputs
(about 0.1-1.5 s); frequent state updates (up to 100 Hz); large
and frequently changing numbers of users in a single application
instance (up to tens of thousands simultaneous users).
This talk will address two challenging aspects of future Internet-based ROIA applications: a) using Mobile Cloud Computing for allowing high application performance when a ROIA application is accessed from multiple mobile devices, and b) managing dynamic QoS requirements of ROIA applications by employing the emerging technology of Software-Defined Networking (SDN).
Tokyo University of Foreign Studies, Japan
Hajime Mochizuki received his PhD in Information Science from Japan Advanced Institute of Science and Technology in Ishikawa, Japan. Since April 2002, Dr. Mochizuki has been with Tokyo University of Foreign Studies, where he is currently an associate professor, the Institute of Global Studies. Earlier he was Associate at School of Information Science Japan Advanced Institute of Science and Technology in Ishikawa, and Lecturer at Faculty of Foreign Studies, Tokyo University of Foreign Studies, all in Japan. His research interests include Natural Language Processing, Language Learning System and Building of Spoken Language Corpus from Closed Caption TV data. He has extensively published in several national and international conferences. He has won the best presentation award in ICACTE 2016. Dr. Mochizuki is a member of the Information Processing Society of Japan (IPSJ), Japanese Society for Information Systems in Education (JSISE), and Association for the Advancement of Computing in Education (AACE).
Abstract: Building a Very Large Spoken Language Corpus from Closed Caption TV and Extracting Practical Formulaic Sequences for Language Learning
Corpus has become one of the most important resources for researches and applications related to computational linguistics, knowledge engineering, and language education. Almost all existing corpora are “written language corpora,” and only a few “spoken language corpora” can be used for research purposes. We have been continually building a large-scale spoken language corpus from closed caption TV data for a language learning system. This talk shows the specific details of a very large spoken language corpus constructed from Japanese closed caption TV (CCTV) data transmitted through digital terrestrial broadcasting. In Tokyo, there are seven major broadcasting stations which organize a Japanese nationwide. Our team have been recording all TV programs with closed caption data during a 24-hour period in every days. They are amount of about 4,200 programs per one month. Our team collected the closed caption data from over 200,000 TV programs from December 2012 to June 2017. The total number of words in our corpus has reached over 900 million morphemes. This talk also shows the details of the formulaic sequences (FS) extracted from the CCTV corpus. We anticipate the existence of sequences of words that occur frequently in the corpus, such as collocations, idioms, and greeting expressions. These sequences of words are referred as formulaic sequences. In second language education and applied linguistics, it is a widely acceptance that appropriately using FSs in particular situations and functions contributes to learners’ language comprehension, production, and fluency. Because TV is a major medium in daily life and many natural or near-natural dialogues and spontaneous sentences are included in TV programs (e.g., documentaries, daily information reports, and dramas), we expect to be able to apply the corpus to language education such as a language e-learning system.