• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.13-26
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• 2021

Recent drought events in the South Korea and the magnitude of drought losses indicate the continuing vulnerability of the agricultural drought. Various studies have been performed on drought hazard assessment at the regional scales, but until recently, drought management has been response oriented with little attention to mitigation and preparedness. A vulnerability assessment is introduced in order to preemptively respond to agricultural drought and to predict the occurrence of drought. This paper presents a method for spatial, Geographic Information Systems-based assessment of agricultural drought vulnerability in South Korea. It was hypothesized that the key 14 items that define agricultural drought vulnerability were meteorological, agricultural reservoir, social, and adaptability factors. Also, this study is to analyze agricultural drought vulnerability by comparing vulnerability assessment according to weighting method. The weight of the evaluation elements is expressed through the Analytic Hierarchy Process (AHP), which includes subjective elements such as surveys, and the Entropy method using attribute information of the evaluation items. The agricultural drought vulnerability map was created through development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. This vulnerability assessment is calculated the vulnerability index based on the weight, and analyze the vulnerable map from 2015 to 2019. The identification of agricultural drought vulnerability is an essential step in addressing the issue of drought vulnerability in the South Korea and can lead to mitigation-oriented drought management and supports government policymaking.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1281-1291
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• 2015

Compared to the past, people can control end devices via open channel. Although this open channel provides convenience to users, it frequently turns into a security hole. In this paper, we propose a new human-centered security risk analysis method that puts weight on the relationship between end devices. The measure derives from the concept of entropy rate, which is known as the uncertainty per a node in a network. As there are some limitations to use entropy rate as a measure in comparing different size of networks, we divide the entropy rate of a network by the maximum entropy rate of the network. Also, we show how to avoid the violation of irreducible, which is a precondition of the entropy rate of a random walk on a graph.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.63-74
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• 2005

In Electronic Commerce, the latest most of the personalized recommender systems have applied to the collaborative filtering technique. This method calculates the weight of similarity among users who have a similar preference degree in order to predict and recommend the item which hits to propensity of users. In this case, we commonly use Pearson Correlation Coefficient. However, this method is feasible to calculate a correlation if only there are the items that two users evaluated a preference degree in common. Accordingly, the accuracy of prediction falls. The weight of similarity can affect not only the case which predicts the item which hits to propensity of users, but also the performance of the personalized recommender system. In this study, we verify the improvement of the prediction accuracy through an experiment after observing the rule of the weight of similarity applying Vector similarity, Entropy, Inverse user frequency, and Default voting of Information Retrieval field. The result shows that the method combining the weight of similarity using the Entropy with Default voting got the most efficient performance.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.918-932
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• 2021

Evaluation of the collaboration of the upstream and downstream enterprises in the manufacturing supply chain is important to improve their synergistic effect. From the supply chain perspective, this study establishes the evaluation model of the manufacturing enterprise collaboration on the basis of fuzzy entropy according to synergistic theory. Downstream enterprises carry out coordinated capital, business, and information flows as subsystems and research enterprises as composite systems. From the three subsystems, the collaboration evaluation index is selected as the order parameter. The compound fuzzy matter-element matrix is established by using its improved algorithm. Subordinate membership and standard deviation fuzzy matter-element matrixes are constructed. Index weight is determined using the entropy weight method. The closeness of each matter element is then calculated. Through a representative of the home appliance industry, namely, Gree Electric Appliances Inc. of Zhuhai, empirical analysis of data in 2011-2017 from the company and its upstream and downstream enterprise collaboration shows a good trend, but the coordinated development has not reached stability. Gree Electric Appliances Inc. of Zhuhai need to strengthen the synergy with upstream and downstream enterprises in terms of cash, business, and information flows to enhance competitiveness. Experimental results show that this method can provide precise suggestions for enterprises, improve the degree of collaboration, and accelerate the development and upgrading of the manufacturing industry.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.151-156
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• 2011

Previously most of flood prevention efforts have been made for relatively large watersheds near to channel flow. However, as economical development and the expansion of leisure areas to mountainous region, human casualty by flash flood occurs frequently, requiring additional prevention activity. Therefore, to reduce the damage of human lives and property by flash flood, we develop an assessment method for flash flood occurrence for mountainous areas considering various factors involving it. PROMETHEE(Preference Ranking Organization METHod for Enrichment Evaluations) which is one of the MCDM(Multi-Criteria Decision Making) was adopted to assess the contribution of each factor to the risk of the flash flood in the mountainous area. The main evaluation criteria are classified into three categories, namely, the regional and rainfall characteristics, and geographical features. Also, the Entropy method is used to determine the weight of each evaluation criteria without survey. The suggested method based on PROMETHEE with Entropy method is applied to BongHwa region to verify its applicability. After applied, the method successfully assesses the relative risk of flash flood occurrence of each sub region in the BongHwa region. Out of the seventeen sub-regions, five, seven and five of them are evaluated as high-risk, medium-risk, and low-risk, respectively. To verify the results, we searched the historical data of flash flood and the flash flood had occurred in one of high-risk sub-regions at 2008.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6877-6883
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• 2014

The continuous social development has led to increasing pollution in lakes. This study proposed the LVRI (Lake Vulnerability Resilience Indicator) based on the vulnerability assessment of climate change for an environmental risk assessment in lakes sufferign water pollution in an integrated aspect of the characteristics in lake watersheds. A total of 11 representative assessment factors were selected and constructed for 6 lake basins in the Geum River Watershed to calculate the exposure, sensitivity and adaptation indicators in a vulnerability assessment classification system. The weight coefficients for assessment factors of the LVRI were also calculated using the Entropy method. This study also compared the rank results of the lake environmental risk with/without the weight coefficients of assessment factors for the practical application of the proposed lake environmental risk assessment method. The lake environmental risk results estimated in this study can be used for long-term water quality analysis and management in lakes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2677-2684
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• 2009

In this paper, we study a watermarking method based on the informed coding and embedding by means of trellis code and entropy masking. An image is divided as $8{\times}8$ block with no overlapping and the discrete cosine transform(DCT) is applied to each block. Then the 16 medium-frequency AC terms of each block are extracted. Next it is compared with gaussian random vectors having zero mean and unit variance. As these processing, the embedding vectors with minimum value of linear combination between linear correlation and Watson distance can be obtained by Viterbi algorithm at each stage of trellis coding. For considering the image characteristics, we apply different weight value between the linear correlation and the Watson distance using the entropy masking. To evaluate the performance of proposed method, the average bit error rate of watermark message is calculated from different several images. By the experiments the proposed method is improved in terms of the average bit error rate.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.50-57
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• 2006

In Electronic Commerce, the latest most of the personalized recommender systems have applied to the collaborative filtering technique. This method calculates the weight of similarity among users who have a similar preference degree in order to predict and recommend the item which hits to propensity of users. In this case, we commonly use Pearson Correlation Coefficient. However, this method is feasible to calculate a correlation if only there are the items that two users evaluated a preference degree in common. Accordingly, the accuracy of prediction falls. The weight of similarity can affect not only the case which predicts the item which hits to propensity of users, but also the performance of the personalized recommender system. In this study, we verify the improvement of the prediction accuracy through an experiment after observing the rule of the weight of similarity applying Vector similarity, Entropy, Inverse user frequency, and Default voting of Information Retrieval field. The result shows that the method combining the weight of similarity using the Entropy with Default voting got the most efficient performance.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.153-162
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• 2022

The impact of the information technology industry on economic development is becoming increasingly important. In this study, we take China's provincial-level regions from 2015 to 2020 as the research object, comprehensively evaluates the level of their information technology systems by the entropy weight method, and then measures the coupling coordination relationship between the information technology system and the economic development system by the coupling coordination degree model. As a result, we found that the income of the information technology industry, the investment of talents and science research have the most important influence on the level of the information technology system. During the research period, with increasing values, the coupling degree of the two systems was at a high level. Affected by development strategies, diffusion effects and industrial relocation, the coupling degree in the central and western regions has shown a rapid growth trend. The coordination degree of the two systems is relatively low, and 83.9% of the provinces are in the medium-low coordination stage. The information technology industry has obviously promoted economic development. Besides, relevant policies should be introduced to effectively support and guide the high-quality development of the information technology industry and promote the high-level coordinated development of the two systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.139-142
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• 1998

Missing values in data for fuzzy c-menas clustering is discussed. Two basic methods of fuzzy c-means, i.e., the standard fuzzy c-means and the entropy method are considered and three options of handling missing values are proposed, among which one is to define a new distance between data with missing values, second is to alter a weight in the new distance, and the third is to fill the missing values by an appropriate numbers. Experimental Results are shown.