• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.337-346
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• 2015

Water body extraction based on backscatter information is an essential process to analyze floodaffected areas from Synthetic Aperture Radar (SAR) image. Water body in SAR image tends to have low backscatter values due to homogeneous surface of water, while non-water body has higher backscatter values than water body. Non-water body, however, may also have low backscatter values in high resolution SAR image such as Kompsat-5 image, depending on surface characteristic of the ground. The objective of this paper is to present a method to increase backscatter contrast between water body and non-water body and also to remove efficiently misclassified pixels beyond true water body area. We create an entropy image using a Gray Level Co-occurrence Matrix (GLCM) and classify the entropy image into water body and non-water body pixels by thresholding of the entropy image. In order to reduce the effect of threshold value, we also propose Water Body Texture Index (WBTI), which measures simultaneously the occurrence of repeated water body pixel pair and the uniformity of water body in the binary entropy image. The proposed method produced high overall accuracy of 99.00% and Kappa coefficient of 90.38% in water body extraction using Kompsat-5 image. The accuracy analysis indicates that the proposed WBTI method is less affected by the choice of threshold value and successfully maintains high overall accuracy and Kappa coefficient in wide threshold range.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.263-271
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• 2003

The wetness index has been frequently used to describe the spatial distribution of the hydrologic status on the platform of the grid based model such as TOPMODEL and THALES. The statistical and spatial distributions of the wetness index are primarily depend upon the flow determinatin algorithm. The comparison among various algorithms and the decision making of the application algorithms are desirable. The entropy is used to evaluate the information transfer patterns of the various flow determination algorithm. The Holmgren's H algorithm and the SDFAA algorithm were found to be the better scheme than the other approaches to maximize the information contents of the wetness index.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.93-105
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• 2001

In the lossless step of Lattice Vector Quantization(LVQ), the lattice codewords produced at quantization step are enumerated into radius sequence and index sequence. The radius sequence is run-length coded and then entropy coded, and the index sequence is represented by fixed length binary bits. As bit rate increases, the index bit linearly increases and deteriorates the coding performances. To reduce the index bits across the wide range of bit rates, we developed a novel lattice enumeration algorithm adopting the set partitioning method. The proposed enumeration method shifts down large index values to smaller ones and so reduces the index bits. When the proposed lossless coding scheme is applied to a wavelet based image coding, the proposed scheme achieves more than 10% at bit rates higher than 0.3 bits/pixel over the conventional lossless coding method, and yields more improvement as bit rate becomes higher.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.201-212
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• 2017

This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.855-859
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• 2007

It is essential to obtain accurate and highly reliable streamflow data for water resources planning, evaluation and management as well as design of hydraulic structures. A new discharge estimation method, which is named 'non-dimensional velocity distribution and index-velocity method,' was proposed in this research. This method showed very close channel discharges which were calculated with the exiting velocity-area method. When velocity-area method is used to estimate channel discharge, it is required to observe point velocities at every desired point and vertical using a current meter like Price-AA. However 'non-dimensional velocity distribution and index-velocity method' is used, it become optional to observe point velocities at every desired point and vertical. But this method can not be applied for the cases of very complex and strongly asymmetric channel cross-sections because non-dimensional velocity distribution by entropy concept may be quite biased from that of natural rivers.

• Journal of the Korean Regional Science Association
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• v.39 no.3
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• pp.3-12
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• 2023

The issue to be discussed is set as the relationship between urban fragmentation and urban heat phenomena. The fragmentation is recognized as a negative form that commonly occurs in the process of urbanization. The purpose of this study is to examine the relationship between urbanization entropy and heat phenomenon by looking at the five major cities in Korea. The employed methods are InVEST Urban Cooling Model and MSPA (Morphological Spatial Pattern Analysis) by using the meteological data for the July 2018. The major results are as follows; First, a low rank correlation(rho=-0.3) is found in the relation between entropy and Cooling Capacity Index (CCi). Second, a very high level of rank correlation is observed between entropy and Average Temperature(℃)(rho=0.9). The implications are that 1) a city with a large degree of sprawling development can have a negative effect on urban heat phenomena; 2) the composition of land use including dispersion and concentration in non-urbanized areas, which has the characteristics of open space, can affect the urban thermal environment. Due to the limited number of case studies, it is appropriate to understand that a possibility, not generalization, is observed between entropy and heat phenomena in urbanized areas.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.307-314
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• 2017

Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.67-81
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• 2020

The rapid climatic changes being caused by global warming are resulting in abnormal weather conditions worldwide, which in some regions have increased the frequency of landslides. This study was aimed to analyze and compare the landslide susceptibility using the Frequency Ratio (FR), Statistical Index, Weight of Evidence, Certainty Factor, and Index of Entropy (IoE) at Woomyeon Mountain in South Korea. Through the construction of a landslide inventory map, 164 landslide locations in total were found, of which 50 (30%) were reserved to validate the model after 114 (70%) had been chosen at random for model training. The sixteen landslide conditioning factors related to topography, hydrology, pedology, and forestry factors were considered. The results were evaluated and compared using relative operating characteristic curve and the statistical indexes. From the analysis, it was shown that the FR and IoE models were better than the other models. The FR model, with a prediction rate of 0.805, performed slightly better than the IoE model with a prediction rate of 0.798. These models had the same sensitivity values of 0.940. The IoE model gave a specific value of 0.329 and an accuracy value of 0.710, which outperforms the FR model which gave 0.276 and 0.680, respectively, to predict the spatial landslide in the study area. The generated landslide susceptibility maps can be useful for disaster and land use planning.

• Korean Journal of Organic Agriculture
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• v.24 no.1
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• pp.1-15
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• 2016

This paper aims to analyze inequality of maize self-sufficiency rate among countries in 1970-2011. Utilizing sub-group consistency of Generalized Entropy and Atkinson inequality index, the estimated maize self-sufficiency rate inequality is further decomposed into two steps' separate country groups. First, lower and upper income groups and then lower, lower middle, upper middle and high income groups are used based on the national classification of the world bank. It is inferred that 1980s' policy intervention and 1990s' Uruguay Round negotiations have different effect on the inequality among four different country groups.