Kuo-Chu Chang

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Stochastic simulation approaches perform probabilistic inference in Bayesian networks by estimating the probability of an event based on the frequency that that· event occurs in a set of simulation trials. This paper describes the evidence weighting mechanism, for augmenting the lo�ic sampling stochastic simulation algo­ rithm l5]. Evidence weighting(More)
In almost all situation assessment problems, it is useful to dynamically contract and ex­ pand the states under consideration as assess­ ment proceeds. Contraction is most often used to combine similar events or low probability events together in order to reduce computa­ tion. Expansion is most often used to make distinctions of interest which have(More)
Target tracking using multiple sensors can provide better performance than using a single sensor. One approach to multiple target tracking with multiple sensors is to first perform single sensor tracking and then fuse the tracks from the different sensors. Two processing architectures for track fusion are presented: sensor to sensor track fusion, and sensor(More)
Information in the battlefield comes from reports from diverse sources, in distinct syntax, and with different meanings. There are many kinds of uncertainty involved in this process, e.g., noise in sensors, incorrect, incomplete, or deceptive human intelligence, and others, which makes it essential to have a coherent, consistent, and principled means to(More)
Mixture distributions such as Gaussian mixture model (GMM) have been used in many applications for dynamic state estimation. These applications include robotics, image and acoustic processing, distributed tracking, and multisensor data fusion. However, the recursive processing of the mixture distributions incurs rapidly growing computational requirements.(More)
BACKGROUND Interferon (IFN)-based therapies could eradicate hepatitis C (HCV) and reduce the risk of hepatocellular carcinoma (HCC). However, HCC could still happen after sustained virological response (SVR). We aimed to develop a simple scoring system to predict the risk of HCC development among HCV patients after antiviral therapies. METHODS From 1999(More)
In order to induct a Bayesian network from data, researchers proposed a variety of score metrics based on different assumptions. The score metric that performs best is of interest. In this paper, we compared the performance of five score metrics: UPSM, CUPSM, DPSM, BDe, and MDL; resulting from five different assumptions: uniform prior, conditional uniform(More)
BACKGROUND Formation of advanced glycation end-products (AGEs) on collagen within the arterial wall may be responsible for the development of diabetic vascular injury. This study focused on investigating the role of aminoguanidine (AG), an inhibitor of AGE formation, in the prevention of noninsulin-dependent diabetes mellitus (NIDDM)-derived arterial(More)
BACKGROUND We determined the effects of NIDDM on haemodynamic parameters describing arterial wall elasticity and cardiac hypertrophy in rats administered streptozotocin (STZ) and nicotinamide (NA), using the aortic impedance analysis. METHODS Male Wistar rats at 2 months were administered intraperitoneally 180 mg kg(-1) of NA, 30 min before an intravenous(More)
Situational awareness and prediction are essential elements of information fusion. Both involve various types of uncertainty and require a sound automated inferential process. Probabilistic ontologies support uncertainty management in se-mantically aware systems, and facilitate modular, interoperable systems. This paper describes the process of developing a(More)