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WSEAS TRANSACTIONS
on BUSINESS and ECONOMICS

Issue 11, Volume 4, November 2007
Print
ISSN: 1109-9526
E-ISSN: 2224-2899

 
 

 

 

 

 

 


Title of the Paper:  An Integrated Two-Phased Decision Support System for Resource Allocation

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Authors: Chang-Kyo Suh

Abstract: This paper concerns the design of decision support systems (DSSs) which help financial managers in evaluating proposals for strategic and long-range planning. With the proposed two-phased DSS, projects are first selected from a given pool according to greedy heuristics based on the projectís preferences as well as the projectís efficiency. Then, integer programming with an approximation algorithm is used in the second phase to re-evaluate those proposed projects which met the first phase criteria.


Keywords: Decision Support System, Resource Allocation, Analytic Hierarchy Process, Project Preference
 

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Title of the Paper:  Dynamic Gesture Recognition Based on Dynamic Bayesian Networks

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Authors: Wei-Hua Andrew Wang, Chun-Liang Tung

Abstract: Techniques for recognizing and matching dynamic human gestures are becoming increasingly important with the CCTV surveillance system. To provide consistent dynamic gesture recognition system, Hierarchical Dynamic Vision System (HDVS) which based on dynamic Bayesian networks (DBNs) is proposed for automatically identifying human gestures in this paper. DBNs, directed graphical models of stochastic process, generalize HMM by representing the hidden and observed state in terms of state variables in which can have more complex interdependencies than HMMs systems do. In this paper, hierarchical hidden Markov model (HHMM) is used as the underlying topology in the proposed dynamic system to recognize human gestures with motion trajectories in an indoor scene. A hierarchical HMM, represented by DBN, is structured multi-level stochastic processes. In the low-level processing, both motion trajectories and motion directions generated from hand part is used as features after watershed segmentation. In the high-level processing, human gestures are automatically recognized form the inference of HHMM-DBNs. In this paper, we focus on the following aspects of both system modeling and high-level processing: (1) Completed DBNs structure with HHMM, (2) approaches to human gesture recognition.


Keywords: Hierarchical Dynamic Vision System, dynamic Bayesian network

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