• Journal of Information Processing Systems
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• v.8 no.4
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• pp.685-692
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• 2012

B frame bi-directional predictions and the DIRECT mode coding of the H.264 video compression standard necessitate a complex mode decision process, resulting in a long computation time. To make H.264 feasible, this paper proposes an image backtrack-based fast (IBFD) algorithm and evaluates the performances of two promising fast algorithms (i.e., AFDM and IBFD). Evaluation results show that an image backtrack-based fast (IBFD) algorithm can determine DIRECT mode macroblocks with 13% higher accuracy, as compared with the AFDM. Furthermore, IBFD is shown to reduce the motion estimation time of B frames by up to 23% with a negligible quality degradation.

• Journal of the Korean Solar Energy Society
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• v.34 no.4
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• pp.23-29
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• 2014

Recently, in power system studies, Multiple Energy Carriers (MECs) such as Energy Hub has been broadly utilized in power system planners and operators. Particularly, Energy Hub performs one of the most important role as the intermediate in implementing the MECs. However, it still needs to be put under examination in both modeling and operating concerns. For instance, a probabilistic optimization model is treated by a robust global optimization technique such as multi-agent genetic algorithm (MAGA) which can support the online economic dispatch of MECs. MAGA also reduces the inevitable uncertainty caused by the integration of selected input energy carriers. However, MAGA only considers current state of the integration of selected input energy carriers in conjunctive with the condition of smart grid environments for decision making in Energy Hub. Thus, in this paper, we propose an immune algorithm based Multiple Energy Carriers System which can adopt the learning process in order to make a self decision making in Energy Hub. In particular, the proposed immune algorithm considers the previous state, the current state, and the future state of the selected input energy carriers in order to predict the next decision making of Energy Hub based on the probabilistic optimization model. The below figure shows the proposed immune algorithm based Multiple Energy Carriers System. Finally, we will compare the online economic dispatch of MECs of two algorithms such as MAGA and immune algorithm based MECs by using Real Time Digital Simulator (RTDS).

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1797-1805
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• 1993

An algorithm for the threshold decision from the maximum mismatching correlation value in a direct-sequence spread-spectrum system is presented. This algorithm is named the TDMMC(Threshold Decision from the Maximum Mismatching Correlation value). The purpose of the algorithm is to set the decision threshold in the system which will provide large probability of signal detection. Using this algorithm, the proper setting of the threshold for various SNRs is possible. An additional block called the Threshold Block is used to improve the system performance. The result from the computer simmulation has shown that appling the TDMMC to the noncoherent DS/SS-CSK system can achieve performance improvement.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1058-1062
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• 2008

In clinical decision support system(CDSS), unlike rule-based expert method, appropriate data-driven machine learning method can easily provide the information of individual feature(clinical test) for disease classification. However, currently developed methods focus on the improvement of the classification accuracy for diagnosis. With the analysis of feature importance in classification, one may infer the novel clinical test sets which highly differentiate the specific diseases or disease states. In this background, we introduce a novel CDSS that integrate a classifier and feature selection module together. Random forest algorithm is applied for the classifier and the feature importance measure. The system selects the significant clinical tests discriminating the diseases by examining the classification error during backward elimination of the features. The superior performance of random forest algorithm in clinical classification was assessed against artificial neural network and decision tree algorithm by using breast cancer, diabetes and heart disease data in UCI Machine Learning Repository. The test with the same data sets shows that the proposed system can successfully select the significant clinical test set for each disease.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.48-56
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• 2009

We propose a fast intra mode skip decision algorithm for H.264/AVC video encoding. Although newly added MB encoding algorithms based on various prediction methods increase compression ratio, they require a significant increase in the computational complexity because we calculate rate-distortion(RD) cost for all possible MB coding modes and then choose the best one. In this paper, we propose a fast mode decision algorithm based on an adaptive motion vector map(AMVM) method for H.264/AVC video encoding to reduce the processing time for the inter frame. We verify that the proposed algorithm generates generally good performances in PSNR, bit rates, and processing time.

• Journal of Forest and Environmental Science
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• v.30 no.1
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• pp.45-49
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• 2014

This study was tried to find out the applicability of decision support system for forest land use conversion, which developed based on algorithm for forest land-use conversion. Decision support system developed by Ministry of Safety Administration is free from the existing licensed laws omission. And it made the input requirements for each value of the final result so that you can determine whether the permit was available by the laws and regulations related to the algorithm for forest land use conversion. Also, in order to do field surveys, equal sampling interval method is used to extract samples for the operability by comparing and analyzing the actual area. As a result, 88 areas of total 100 areas are able to get permission by the decision support system for forest land use conversion, and it means if there is enough data with sufficient research, it can make the availability permits easily.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2330-2332
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• 1998

This paper suggests a method to recognize the various defect patterns of cold mill strip using binary decision tree automatically constructed by genetic algorithm. The genetic algorithm and K-means algorithm were used to select a subset of the suitable features at each node in binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes by a linear decision boundary. This process was repeated at each node until all the patterns are classified into individual classes. The final recognizer is accomplished by neural network learning of a set of standard patterns at each node. Binary decision tree classifier was applied to the recognition of the defect patterns of cold mill strip and the experimental results were given to demonstrate the usefulness of the proposed scheme.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.63-69
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• 1999

The research trend of the simulation optimization has been focused on exploring continuous decision variables. Yet, the research in discrete decision variable area has not been fully studied. A new research trend for optimizing discrete decision variables ha just appeared recently. This study, therefore, deals with a discrete simulation method to get the system evaluation criteria required for designing a complex probabilistic discrete event system and to search the effective and reliable alternatives to satisfy the objective values of the given system through a on-line, single run with the short time period. Finding the alternative, we construct an algorithm which changes values of decision variables and a design alternative by using the stopping algorithm which ends the simulation in a steady state of system. To avoid the loss of data while analyzing the acquired design alternative in the steady state, we provide background for estimation of an auto-regressive model and mean and confidence interval for evaluating correctly the objective function obtained by small amount of output data through simulation with the short time period. In numerical experiment we applied the proposed algorithm to (s, S) inventory system problem with varying Δt value. In case of the (s, S) inventory system, we obtained good design alternative when Δt value is larger than 100.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12C
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• pp.1039-1045
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• 2008

The H.264/AVC video coding standard shows extremely higher coding efficiency, but it causes high computational complexity. Especially, the intra mode decision using the rate-distortion method requires many computations. Thus, the efficient intra mode decision methods have been proposed by decreasing the encoding complexity. In this paper, we propose an efficient intra mode decision algorithm using $4{\times}4$ integer transform coefficients in the conversion of MPEG-2 to H.264 standard. It is shown that the proposed algorithm reduces encoding time and complexity compared to the conventional algorithm, while showing similar PSNR performance.