Prof. Yusmadi Yah Binti Jusoh
Faculty Of Computer Science And Information Technology, Universiti Putra Malaysia, Malaysia
Research Area: Management Information System, Strategic Information System Planning, Software Project Management
Introduction: Associate Professor Dr. Yusmadi Yah Jusoh is an academician at Department of Software Engineering and Information System, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM) since 1998.Yusmadi is also a certified software tester and a technologist awarded by Malaysian Board of Technologist (MBOT). She is the head of Applied Informatics Research Group at the faculty. Her research interest are in Management Information System, Information System, Information Technology Strategic Planning, and Software Project Management.Her research also related to information systems on the performance measurement of big data systems, software team project, virtual teams, smart campus, social media and healthcare organizational performance. She teaches software project management, software team project management, information systems,electronic commerce and Human Computer Interaction.
Speech Title: Performance Measurement for Big Data Systems
Abstract: Many Big Data Systems (BDS) fails because of lack of knowledge on measuring the performance of BDS. The failure to identify the correct measures will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needs to understand the factors that contribute to the performance of the eco-sustainability metrics for BDS. Therefore, the performance and eco-sustainability measurement of the BDS is examined. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The proposed measurements used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model was validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of their BDS.
Prof. Lu Leng
School of Software, Nanchang Hangkong University, China
Research Area：Biometric identification and authentication, biometric template protection, computer vision
Brief introduction: LU LENG received his Ph.D degree from Southwest Jiaotong University, Chengdu, P. R. China, in 2012. He performed his postdoctoral research at Yonsei University, Seoul, South Korea, and Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China. He was a visiting scholar at West Virginia University, USA, and Yonsei University, South Korea. Currently, he is a full professor at Nanchang Hangkong University. Prof. Leng has published more than 100 international journal and conference papers, including about 60 SCI papers and three highly cited papers. He has been granted several scholarships and funding projects, including five projects supported by National Natural Science Foundation of China (NSFC). He serves as a reviewer of more than 100 international journals and conferences. His research interests include computer vision, biometric template protection and biometric recognition. Prof. Leng is an outstanding representative of "Innovation Talent" of Jiangxi Enterprise in "Science and Technology China" in 2021, received "Jiangxi Youth May Fourth Medal" in 2019, "Jiangxi Hundred-Thousand-Ten-thousand Talent Project" in 2018, "Jiangxi Voyage Project" in 2014, etc.
Speech Title: Advanced Palmprint Recognition
Abstract:Biometric recognition is convenient and reliable, so it has been widely used for identification and verification. Palmprint is a promising biometric modality and has several advantages, including high accuracy, good availability, high acceptability, etc. This speech introduces several advanced palmprint recognition technologies. Since palmprint is a typical biometric modality, its recognition technologies can be conveniently extended to other biometric modalities.
A. Prof. Yongquan Yan
School of Statistics, Shanxi University of Finance and Economics
Research Area: Machine learning, dependable computing, software aging and rejuvenation
Speech Title: Software aging prediction using neural network with ridge.
Abstract: Since software systems become more complex than before, software ageing problems have a big impact on the performance of running software systems. To find software ageing in advance, some prediction methods were used to forecast those parameters which can indicate software ageing occurrences. Since the unsuitable parameters can reduce the prediction ability of an algorithm, in this study, multilayer perceptron (MLP) with ridge is proposed to improve the prediction accuracy of MLP and apply in software ageing problems. The proposed approach is a three-step method. First, a pre-processing process needs to be done by using outlier recognition, dispose, and normalisation. Second, MLP with ridge is proposed and used to optimise network structure. Third, a glowworm swarm optimisation method is utilised to automatically find optimal values of model parameters. In the experimental section, the results indicate that the proposed algorithm owns higher forecast accuracy than other state-of-the-art methods on two levels.
A. Prof. Mabel C. Chou
Department of Decision Sciences, National University of Singapore, Singapore
Research Area:
1. Production Scheduling
2. Logistics and Supply Chain Analysis
3. Operations/Manufacturing Flexibility Design and Analysis
Speech Title: Managing Supply Chain Risk with Process Flexibility
Abstract: The global supply chain is undergoing significant changes as a result of recent international tensions and pandemic-related disruptions. To mitigate the uncertainties arising from these supply shocks, supply chain operators need to effectively cushion the supply-side risks while also hedging against demand uncertainties. In both theory and practice, process flexibility has been proven to be an effective supply chain strategy that enables timely and effective responses to demand uncertainties. This talk aims to shed light on how process flexibility can mitigate supply chain uncertainties with a few case studies.
