Associate Professor Dr Nazri Kama
Department of Advanced Informatics, Razak Faculty of Technology and Informatics, Universiti Teknology Malaysia, Kuala Lumpur, Malaysia
Speech Title: Software Effort Estimation: Mining the Mind - Minding the Mine
Abstract: In recent years, due to significant evolution in adopting new technologies and development methodologies in the field of software engineering, the developers and researchers are striving to optimize the accuracy of software effort estimation. Studies of software effort estimation have started since 1960s and it has been continuous research due to a lot of arguments and discussions in achieving an accurate effort estimation results. The number of software projects fails due to incomplete requirements and inaccuracy in software estimation. The overestimation and underestimation both are the key challenges for software progress, hence there is a continuous need for an accurate effort estimation. This talk will highlight the best practices, drawbacks, challenges and comparison of accuracy performance associated with the effort estimation models. The primary aim of this talk is to assist the researchers in pursuing their further research on the topic by providing insight into the effort estimation models and techniques.
Introduction to Associate Professor Dr. Nazri Kama:
Dr. Nazri Kama is an Associate Professor and Deputy Dean Research and Innovation of the Razak Faculty of Technology and Informatics at the Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia. He received his Ph.D. from the University of Western Australia, Perth, Australia (2010), specializing in Software Engineering in the areas of Requirements Engineering. He received his B.Sc. Honors in Management Information System (1999) and M.Sc. in Real-time Software Engineering (2001) from the Universiti Teknologi Malaysia. He is an active software engineering researcher at the Software Engineering Research Group and has been successfully leveraging his expertise in various software development projects.
Prof. Osvaldo N. Oliveira Jr.
São Carlos Institute of Physics and Center for Computational Linguistics (NILC)
University of São Paulo, Brazil
Speech Title: Complex networks in natural language processing
Speech Abstract: An overview will be presented of the various applications of complex networks in natural language processing tasks, including summarization, semantic disambiguation, essay evaluation, authorship recognition, evaluation of machine translation and semi-automatic surveys. These applications are based on the finding that the topology and dynamics of the networks established by representing text, e.g. with a word co-occurrence strategy, may correlate with structural and semantic features of the text. In assessing the quality of essays written by high-school students, for instance, the departure from a linear behavior in the dynamics of node linking correlates with poorer writing. For author recognition, the highest performance is achieved with a non-supervised machine learning algorithm with input features containing metrics of the network topology and the semantics of the most important nodes. Node importance can be quantified because text networks are scale free with a degree distribution following a power law. This scale-free property also explains why preservation of network topology in the target language is key for a successful machine translation. The flexibility of the network-based approach is exemplified by using sentences as nodes in creating networks for text summarization, and in establishing semantic fields in a corpus of scientific literature to develop semi-automatic surveys. As with many other areas, natural language processing is bound to rely increasingly on deep learning, and this will be discussed in the context of automatic scoring of written essays.
A short introduction to Prof. Osvaldo N. Oliveira Jr.:
Osvaldo N. Oliveira Jr. is a professor at the São Carlos Institute of Physics, University of São Paulo, Brazil. He obtained his BSc and MSc from the University of São Paulo, a PhD from the University of Wales, Bangor (1990), and an honorary doctorate (Honoris Causa) from the Federal University of Mato Grosso do Sul in 2019. Prof. Oliveira is a member of the Latin American Academy of Sciences, a former president of the Brazilian Materials Research Society, and executive editor of ACS Applied Materials & Interfaces. He has led research into the fabrication of novel materials in the form of ultrathin films obtained with the Langmuir-Blodgett and self-assembly techniques. Most of this work has been associated with fundamental properties of ultrathin films with molecular control, but technological aspects have also been addressed in specific projects. This is the case of an electronic tongue, whose response to a number of tastants is considerably more sensitive than the human gustatory system. In recent years, Prof. Oliveira has pioneered the combined use of methods from distinct fields of science, with the merge of methods of statistical physics and computer science to process text, and use of information visualization to enhance the performance of sensing and biosensing. This pioneering work is associated with the merge of nanotechnology with Big Data Analytics and machine learning, bound to yield developments in technology such as computer-aided diagnosis systems. Prof. Oliveira has also developed strategies for scientific writing, especially targeted for non-native users of English. As of October, 2020, he published over 580 papers in international journals, 3 books, in addition to filing close to a dozen patents, which have received ca. 13,700 citations (h =55, Web of Science) and ca. 20,500 citations (h = 67, Google Scholar). He was awarded with the Scopus Prize from Elsevier in 2006 as one of the most productive Brazilian scientists.
Beihang University, China
Topic: An integrated modeling and simulation language and system for M&S based system engineering
Abstract:Modeling and simulation are now leading the way in supporting analyses and development of system of systems. At present, for the development of full-process and full-system modeling and simulation, system modeling languages are often required to cooperate with multi-physics modeling languages and simulation platforms, which makes it challenging to ensure the true unity of the whole system model, the consistency between the various system layers and the traceability of the modeling and simulation process. In response to the above problems, this presentation introduces a new integrated intelligent modeling and simulation language—X language developed by the authors’ team, which supports the description of system-level structure and physical behavior, as well as modeling of complex agent models. Interpreter and engine are developed to enable X language to support the simulation of continuous, discrete event and agent models. Finally, a case study is conducted to verify the modeling and simulation capabilities of the X language.
A short introduction to Prof Lin Zhang: Prof Lin Zhang is a professor of Beihang University. He received the B.S. degree in 1986 from the Department of Computer and System Science at Nankai University, China. He received the M.S. degree and the Ph.D. degree in 1989 and 1992 from the Department of Automation at Tsinghua University, China. From 2002 to 2005 he worked at the US Naval Postgraduate School as a senior research associate of the US National Research Council. He served as the President of the Society for Modeling and Simulation International (SCS), the executive vice president of China Simulation Federation (CSF). He is currently the president of Federation of Asian Simulation Societies (ASIASIM), the president of China Simulation Technology Industry Alliance (CSTIA), a Fellow of SCS, ASIASIM and CSF, a chief scientist of the National 863 Program and National Key R&D Program of China. He serves as the Director of Engineering Research Center of Complex Product Advanced Manufacturing Systems, Ministry of Education of China, Editor-in-Chief and associate editors of 6 peer-reviewed international journals. He authored and co-authored more than 300 papers, 18 books and chapters, among Clarivate Highly Cited Researchers in cross-field. He received the National Award for Excellent Science and Technology Books, the Outstanding Individual Award of National High-Tech R&D Program, the National Excellent Scientific and Technological Workers Awards. His research interests include service-oriented modeling and simulation, cloud manufacturing and simulation, model engineering, model based system engineering, cyber-physical systems, M&S for manufacturing systems, etc.
Professor Xiaofang Zhou, PhD, FIEEE
Otto Poon Professor of Engineering and
Chair Professor of Computer Science and Engineering
Department of Computer Science and Engineering
The Hong Kong University of Science and Technology
A short introduction to Professor Xiaofang Zhou: Dr Xiaofang Zhou is Otto Poon Professor of Engineering and Chair Professor of Computer Science and Engineering at The Hong Kong University of Science and Technology. From 2006 to 2020, he was a Professor of Computer Science at The University of Queensland, leading its Data and Knowledge Engineering (DKE) research group and Data Science Discipline. His research focus is to find effective and efficient solutions for managing, integrating, and analysing large-scale complex data for business, scientific and personal applications. He has been working in the area of spatiotemporal and multimedia databases, data mining, data quality management, big data analytics, and machine learning. He received the Best Paper Awards at WISE 2012&2013, ICDE 2015&2019, DASFAA 2016 and ADC 2019. He was a Program Committee Chair of IEEE International Conference on Data Engineering (ICDE 2013), ACM International Conference on Information and Knowledge Management (CIKM 2016), and International Conference on Very Large Databases (PVLDB 2020). He was a General Chair of ACM Multimedia Conference (MM 2015). He was the Chair of IEEE Technical Committee on Data Engineering from 2015-2018. Professor Zhou is a Fellow of IEEE.