• Journal of Korea Water Resources Association
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• v.37 no.6
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• pp.449-460
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• 2004

The purpose of this study is to test the applicability of neuro-fuzzy system for monthly dam inflow forecasts by using weather forecasting information. The neuro-fuzzy algorithm adopted in this study is the ANFIS(Adaptive neuro-fuzzy Inference System) in which neural network theory is combined with fuzzy theory. The ANFIS model can experience the difficulties in selection of a control rule by a space partition because the number of control value increases rapidly as the number of fuzzy variable increases. In an effort to overcome this drawback, this study used the subtractive clustering which is one of fuzzy clustering methods. Also, this study proposed a method for converting qualitative weather forecasting information to quantitative one. ANFIS for monthly dam inflow forecasts was tested in cases of with or without weather forecasting information. It can be seen that the model performances obtained from the use of past observed data and future weather forecasting information are much better than those from past observed data only.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.977-987
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• 2014

Many of the recent performance evaluation of clustering schemes in wireless sensor networks considered one sink node operation and fixed sink node location without mentioning about any network application requirements. However, application environments have variable requirements about their networks. In addition, network performance is sufficiently influenced by different sink node location scenarios in multi-hop based network. We also know that sink location can influence to the sensor network performance evaluation because of changed multipath of sensor nodes and changed overload spots in multipath based wireless sensor network environment. Thus, the performance evaluation results are hard to trust because sensor network is easily changed their network connection through their routing algorithms. Therefore, we suggest that these schemes need to evaluate with different sink node location scenarios to show fair evaluation result. Under the results of that, network performance evaluation results are acknowledged by researchers. In this paper, we measured several clustering scheme's performance variations in accordance with various types of sink node location scenarios. As a result, in the case of the clustering scheme that did not consider various types of sink location scenarios, fair evaluation cannot be expected.

• International journal of advanced smart convergence
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• v.2 no.2
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• pp.40-42
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• 2013

Recent medical industry is an aging society and the application of national health insurance, with state-of-the-art research and development, including the pharmaceutical market is greatly increased. The nation's health care industry through new support expansion and improve the quality of life for the research and development will be needed. In addition, systemic administration of basic medical supplies, or drugs are needed, the drug at the same time managing how systematic analysis of pharmaceutical ingredients, based on data through the purchase of new medicines and pharmaceutical ingredients automatically classified by analyzing the statistics of drug purchases and the future a system that can predict a patient is needed. In this study, the drugs to the patient according to the component analysis and predictions for future research techniques, k-means clustering and k-NN (Nearest Neighbor) Comparative studies through experiments using the techniques employ a more efficient method to study how to proceed. In this study, the effects of the drugs according to the respective components in time according to the number of pieces in accordance with the patient by analyzing the statistics by predicting future patient better medical industry can be built.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.57-64
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• 2009

In this paper, 30 main cities are clustered based on precipitation, temperature, wind speed, photo period, and humidity. We found that the resulting clusters has strong relationships with geographical locations. These results make sense because, although Korea is a small country, Korean weather is known to have strong locality. The largest number of clusters is found when wind speed is used as an interested variable for clustering and the smallest number of clusters is found when photo period is used. The large number of clusters based on wind speed indicates that wind speed is affected easily by local geography.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.117-126
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• 1989

In this paper, a new placement algorithm for gate array lay out design is proposed. The proposed algorithm can treat the variable-sized macrocells and by considering the I/Q pad locations, the routing between I/Q pads and the internal region of a chip can be automated effectively. The algorithm is composed of 3 parts. which are initial partitioning, initial placement and placement improvement. In the initial placement phase, a given circuit is partitioned into 5 sub-circuits, by clustering method with considers connectivities of cells not only with I/Q pads but also with related partitioned groups is used repeatedly to assign a unique position to each cell. In the placement improvement phase, the concept of probabilistic wiring density is introduced, and cell moving algorithm is proposed to make the density in a chip even.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.190-207
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• 2015

In the combustion engineering, to decrease pollution and increase production efficiency, and to optimally keep solid burning material amount constant in a burner online, it needs a smart method to detect the amount variation of the burning materials in a high temperature environment. This paper presents an online machine vision system for automatically measuring and detecting the burning material amount inside a burner or a boiler. In the camera-protecting box of the system, a sub-system for cooling is constructed by using the cooling water circulation techqique. In addition, the key and intelligent step in the system is to detect the pile profile of the variable burning material, and the algorithm for the pile profile tracing was studied based on the combination of the gey level (color) discontinuity and similarity based image segmentation methods, the discontinuity based sub-algorithm is made on the quaternion convolution, and the similarity based sub-algorithm is designed according to the region growing with multi-scale clustering. The results of the two sub-algoritms are fused to delineate the final pile profile, and the algorithm has been tested and applied in different industrial burners and boilers. The experiements show that the proposed algorithm works satisfactorily.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.6
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• pp.789-793
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• 2008

The gayal (Bos frontalis) in China is a very rare semi-wild and semi-domestic bovine species. There still exist remarkable divergences on the gayal's origin and taxonomic status. In the present study, the cytochrome b (Cyt b) gene entire sequences (1,140 bp) of 11 gayals in Yunnan China were analyzed. Combined with other bovine Cyt b sequences cited in GenBank, the phylogenetic trees of genus Bos were reconstructed by neighbor-joining (NJ) and maximum parsimony (MP) methods with Bubalus bubalis as outgroup. Sequence analysis showed that, among 1,140 sites compared for 11 gayals, 95 variable sites (8.33% of all sites) and 6 different haplotypes were observed, showing abundant mitochondrial genetic diversity in gayals. Both NJ and MP trees demonstrated that gayals in this study were markedly divided into three embranchments: one embranchment clustering with Bos gaurus, another clustering with Bos taurus, and the third clustering with Bos indicus. The result of phylogenetic analysis suggested that the gayal might be the domesticated form of the gaur, and a great proportion of the gayal bloodline in China was invaded by other bovine species.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.548-553
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• 2004

In this paper we propose modified LBG algorithm to minimize quantization errors. When we apply conventional LBG algorithm for speaker verification system, problems that result from small amount of training data can be generated. That is, quantization error comes from fixed-sized codebook without any consideration for speaker characteristics and splitting vector in the wrong direction worsen performance of speaker verification system. So, we propose modified clustering method that has variable sized codebook according to speaker characteristics and makes right splitting direction by finding the farthest member away from mean and then find another member from the member. Simulation results show effectiveness of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.7 s.238
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• pp.1013-1021
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• 2005

In this paper, we developed an automatic design optimization system for parametric shape optimization of cooling passages inside axial turbine blades. A parallel three-dimensional thermoelasticity finite element analysis code from an open source system was used to perform automatic thermal and stress analysis of different blade configuration. The developed code was connected to an evolutionary optimizer and built in a design optimization system. Using the optimization system, 279 feasible and optimal solutions were searched. It is provided not only one best solution of the searched solutions, but also information of variation structure and correlation of the 279 solutions in function, variable, and real design spaces. To explore design information, it is proposed a new interpretation approach based on evolutionary clustering and principal component analysis. The interpretation approach might be applicable to the increasing demands in the general area of design optimization.