Institute of Technology Management
National Chung Hsing University

John Sum, Professor
BEng, MPhil, PhD, IEEE Senior Member
IJCA Associate Editor, APNNA

Rm 821, College of Social Sci. & Mgt Building
250 Kuo Kuang Road, Taichung 402, Taiwan.
John Sum Photo

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Research Areas

  1. Scheduling Jobs to Minimize the Effect of Multitasking (Analysis, Management)
    (Collaborators: K. Ho, Providence University)
    • Complexity Analysis and Algorithm Design
    • Total weighted completion time
    • Maximum lateness/tardiness
    • Total (weighted) number of late jobs
    • Stress effect

  2. Breast Cancer Research (Analysis)
    (Collaborator: Po-Hsiung Lin, National Chung Hsing University)
    • Early detection of breast cancer using neural networks

  3. Neural Networks (Analysis)
    (Collaborators: K. Ho, Providence University; CS Leung, City University of Hong Kong)
    • Effect of noise on MLP learning (weight noise, random node fault, Langevin noise, chaotic noise)
    • Effect of noise on RNN learning (weight noise, random node fault, Langevin noise, chaotic noise)
    • Early stopping criteria for noise/fault injection-based on-line learning algorithms
    • Fault Tolerant Neural Networks
    • Training and pruning algorithms for FNN & RNN
    • Dynamic Properties of Neural Networks
    • Spike Neural Networks

  4. E-Commerce & Social Networks Technologies (Analysis, Management & Development)
    (Collaborators: K.Ho, Providence University; CS Leung, City University of Hong Kong, H Shen, University of Adelaide, Australia; J. Wu, Temple University, USA)
    • Gnutella P2P networks, Pricing Web Services
    • Combinatorial Auction, E-marketplace, E-shppoing
    • Managing RFID Reader Networks, Sensor Networks
    • Mobile Agent-Based Network Management

  5. Service Science, Management, Engineering and Design (SSME/D)
    Interested students can download the following paper for an idea of service engineering (paper) and the introductory note (7M Byte) for my understanding about SSME.
    • Service Modeling: Resarches in service (operations) management have been conducting for many years. One problem is the lack of common language (i.e. visual models) for both the management professionals and the technical professionals. Management professionals in service marketing and management usuallt focus on the "informal" models like GAP models, SERVQUAL, Service Blueprints, New Service Design and Delivery Models. These models are necessary for measuring quality of a system, identifying the problems in a system and thus leading to a strategic design for the business operations and management strategies. For the technical professionals like computer scientists, software engineers and management scientists, they are speaking of "formal" (mathematical) models like UML, Queueing Models, Markov Models, Service Level Argreements, System Development Process Models, and "System Models". These models are also impoartant in that the models can facilitate a good design of a system by mathematical analysis on or simulating the system. By that, the models can help to predict the performance of the system as well as the potential problems aroused if exceptional situations happen. Thus, it is clear that a good design of a service system could be attained if both management professionals and technical professionals can manage to understand those models.
    • Survey Projects: For all good researches, they rely on good survey. I need someone who can collaborate with me to conduct such surveys. You don't have to worry about searching papers. I have already done. 500+ papers and a couple of books have been downloaded and stored in my notebook. Some of them are very nice survey papers as well. These 500+ papers are sufficent enough for you to start with.
    • Miscellaneous Apart from the problem in service modeling, there are other interesting problems in the area. Other intersting topics include Service Systems, Service Management, Service Analysis and Design, Service Engineering, Service Scheduling.

  6. Intelligent Analysis for Management Decisions (Analysis, Management)
    • SEM, Bayesian SEM, Data Envelopment Analysis
    • AHP, FAHP, GRA, Clustering analysis
    • Applications: Purchasing intention, technology/design innovations, financial markets