• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.236-240
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• 2004

Stroke-based composite HMMs with articulation states are proposed to deal with 3D spatio-temporal trajectory gestures. The direct use of 3D data provides more naturalness in generating gestures, thereby avoiding some of the constraints usually imposed to prevent performance degradation when trajectory data are projected into a specific 2D plane. Also, the decomposition of gestures into more primitive strokes is quite attractive, since reversely concatenating stroke-based HMMs makes it possible to construct a new set of gesture HMMs without retraining their parameters. Any deterioration in performance arising from decomposition can be remedied by a partial tuning process for such composite HMMs.

• 산업경영시스템학회지
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• 제22권51호
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• pp.231-240
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• 1999

A major concern in Concurrent Engineering is the control and management of workload in a period of process. As a general rule, leveling the peak of workload in certain period is difficult because concurrent processing is comprised of various processes, including overlapping, paralleling looping and so on. Therefore, the workload management with resource constraints is so beneficial that effective methods to analyze design process are momentous. This study presents the Timed Petri Nets approach of precedence logic networks, and provides an alternative for users to analyze constraint processes to resolve conflicts of resources. Another approach to Continuous Time Markov Chain using Stochastic Petri Nets is also proposed. These approaches are expected to facilitate resolving resource constrained scheduling problems more systematically in Concurrent Engineering environment.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2006년도 춘계학술발표회
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• pp.59-64
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• 2006

본 연구는 해양사고 피해규모에 의해 우리나라 수색 구조 구역의 위험성을 평가하였다. 위험성 평가를 위해서 전문가 지식에 기반 한 퍼지로직, 내부-외부 종속법을 이용하였다. 본 연구에서 평가치 중요도 산출을 위해 이용한 퍼지로직은 퍼지 확장원리에 의한 최대최소화 합성이고, 비퍼지화는 무게중심법을 이용하였다. 평가항목에 대한 중요도 산출을 위해서는 내부-외부 종속법을 이용하였으며, 최종 종합 평가 중요도는 마아코브 분석법을 이용하였다. 그 결과 통영, 여수 수색 구조 구역의 위험성이 비교적 높은 것으로 평가되어, 향후 위험성을 경감하기 위해 많은 구조선과 구조장비가 필요 할 것으로 판단된다.

• 해양환경안전학회지
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• 제12권3호
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• pp.219-224
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• 2006

본 연구는 해양사고 피해규모에 의한 우리나라 수색.구조 구역의 위험성을 평가하였다. 이러한 위험성 평가를 위해서 본 연구에서는 전문가 지식에 기반한 퍼지로직과 내부-외부 종속법을 이용하였다. 본 연구에서 이용한 퍼지로직은 퍼지 확장원리에 의한 최대최소화 합성이고, 중요도 산출을 위한 비퍼지화는 무게중심법을 이용하였다. 또한 평가항목에 대한 중요도 산출을 위해서는 내부-외부 종속법을 이용하였으며, 최종 종합 평가 중요도는 마아코브 분석법을 이용하였다. 그 결과 통영, 목포, 여수 수색.구조 구역의 위험성이 비교적 높은 것으로 평가되어, 향후 위험성을 경감하기 위해 우선적으로 구조선과 구조장비가 필요할 것으로 판단된다.

• 전기학회논문지
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• 제62권1호
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• pp.109-119
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• 2013

This paper presents the design of the Safety Programmable Logic Controller (SPLC) used in the Nuclear Power Plants, an analysis of a reliability for the SPLC using a markov model. The architecture of the SPLC is designed to have the multiple modular redundancy composed of the Dual Modular Redundancy(DMR) and the Triple Modular Redundancy(TMR). The operating system of the SPLC is designed to have the non-preemptive state based scheduler and the supervisory task managing the sequential scheduling, timing of tasks, diagnostic and security. The data communication of the SPLC is designed to have the deterministic state based protocol, and is designed to satisfy the effective transmission capacity of 20Mbps. Using Markov model, the reliability of SPLC is analyzed, and assessed. To have the reasonable reliability such as the mean time to failure (MTTF) more than 10,000 hours, the failure rate of each SPLC module should be less than $2{\times}10^{-5}$/hour. When the fault coverage factor (FCF) is increased by 0.1, the MTTF is improved by about 4 months, thus to enhance the MTTF effectively, it is needed that the diagnostic ability of each SPLC module should be strengthened. Also as the result of comparison the SPLC and the existing safety grade PLCs, the reliability and MTTF of SPLC is up to 1.6-times and up to 22,000 hours better than the existing PLCs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권1호
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• pp.37-42
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• 2010

Final year students are normally encountering high pressing in their study. In view of this fact, this research focuses on determining mental states condition of college student in final year based on the psycho-physiological information. The experiments were conducted in two times, i.e., prior- and post- graduation seminar examination. The early results indicated that the student profile of mood states (POMS) in prior final graduation seminar showed higher scores than students in post final graduation seminar. Thus, in this research, relation between biosignal representing by heart rate variability (HRV) and questionnaire responses were evaluated by hidden Markov model (HMM) and neural networks (NN).

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권1호
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• pp.8-16
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• 2014

We consider the visual barcode recognition problem in a noisy video data setup. Unlike most existing single-frame recognizers that require considerable user effort to acquire clean, motionless and blur-free barcode signals, we eliminate such extra human efforts by proposing a robust video-based barcode recognition algorithm. We deal with a sequence of noisy blurred barcode image frames by posing it as an online filtering problem. In the proposed dynamic recognition model, at each frame we infer the blur level of the frame as well as the digit class label. In contrast to a frame-by-frame based approach with heuristic majority voting scheme, the class labels and frame-wise noise levels are propagated along the frame sequences in our model, and hence we exploit all cues from noisy frames that are potentially useful for predicting the barcode label in a probabilistically reasonable sense. We also suggest a visual barcode tracking approach that efficiently localizes barcode areas in video frames. The effectiveness of the proposed approaches is demonstrated empirically on both synthetic and real data setup.

• Journal of Communications and Networks
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• 제18권1호
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• pp.40-49
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• 2016

In this paper, we present a symbol-level iterative source-channel decoding (ISCD) algorithm for reliable transmission of variable-length codes (VLCs). Firstly, an improved source a posteriori probability (APP) decoding approach is proposed for packetized variable-length encoded Markov sources. Also proposed is a recursive implementation based on a three-dimensional joint trellis for symbol decoding of binary convolutional codes. APP channel decoding on this joint trellis is realized by modification of the Bahl-Cocke-Jelinek-Raviv algorithm and adaptation to the non-stationary VLC trellis. Simulation results indicate that the proposed ISCD scheme allows to exchange between its constituent decoders the symbol-level extrinsic information and achieves high robustness against channel noises.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권3호
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• pp.186-199
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• 2013

We pose pattern classification as a density estimation problem where we consider mixtures of generative models under partially labeled data setups. Unlike traditional approaches that estimate density everywhere in data space, we focus on the density along the decision boundary that can yield more discriminative models with superior classification performance. We extend our earlier work on the recursive estimation method for discriminative mixture models to semi-supervised learning setups where some of the data points lack class labels. Our model exploits the mixture structure in the functional gradient framework: it searches for the base mixture component model in a greedy fashion, maximizing the conditional class likelihoods for the labeled data and at the same time minimizing the uncertainty of class label prediction for unlabeled data points. The objective can be effectively imposed as individual mixture component learning on weighted data, hence our mixture learning typically becomes highly efficient for popular base generative models like Gaussians or hidden Markov models. Moreover, apart from the expectation-maximization algorithm, the proposed recursive estimation has several advantages including the lack of need for a pre-determined mixture order and robustness to the choice of initial parameters. We demonstrate the benefits of the proposed approach on a comprehensive set of evaluations consisting of diverse time-series classification problems in semi-supervised scenarios.