• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.363-372
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• 2008

In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.254-258
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• 2004

In this paper, we propose a robust speech recognition system under noisy environments. Since the presence of noise severely degrades the performance of speech recognition system, it is important to design the robust speech recognition method against noise. The proposed method adopts a new distance measure technique based on stochastic probability instead of conventional method using minimum error. For evaluating the performance of the proposed method, we compared it with conventional distance measure for the 10-isolated Korean digits with car noise. Here, the proposed method showed better recognition rate than conventional distance measure for the various car noisy environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2142-2161
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• 2018

Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter ${\lambda}$, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.

• Communications for Statistical Applications and Methods
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• v.20 no.1
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• pp.23-28
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• 2013

We propose a version of Cook's distance (called local distance) in the multivariate linear model. The proposed version is a matrix, while the existing version of Cook's distance (called global distance) is a scalar. The existing Cook's distance is the trace of the proposed Cook's distance. In addition, we argue that the proposed Cook's distance has a more natural extension of the Cook's distance in the univariate linear model than the existing Cook's distance. An illustrative example based on a real data set is given.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.43-55
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• 2016

This study estimated land prices using instance-based learning. A k-nearest neighbor method was utilized among various instance-based learning methods, and the 10 distance metrics including Euclidean distance were calculated in k-nearest neighbor estimation. One distance metric prediction which shows the best predictive performance would be normally chosen as final estimate out of 10 distance metric predictions. In contrast to this practice, an ensemble technique which combines multiple predictions to obtain better performance was applied in this study. We applied the gradient boosting algorithm, a sort of residual-fitting model to our data in ensemble combining. Sales price data of farm lands in Haenam-gun, Jeolla Province were used to demonstrate advantages of instance-based learning as well as an ensemble technique. The result showed that the ensemble prediction was more accurate than previous 10 distance metric predictions.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.284-288
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• 2005

Internet-based distance learning is proliferated, but justifying its educational effectiveness is challenging. Investigation into the problems is important and fundamental for the study on the educational effectiveness. In this study, problems of Internet-based distance learning are structured by four categories as environmental problems, student problems, course design problems and operational problems. Based on a survey of distance education participants, problems are analysed. Also, analysis from the point of demographic differences such as sex, job existence and age is performed.

• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1242-1250
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• 2021

Detection of outliers deviating normal data distribution in high dimensional data is an important technique in many application areas. In this paper, a distance-based outlier detection method using landmarks in high dimensional data is proposed. Given normal training data, the k-means clustering method is applied for the training data in order to extract the centers of the clusters as landmarks which represent normal data distribution. For a test data sample, the distance to the nearest landmark gives the outlier score. In the experiments using high dimensional data such as images and documents, it was shown that the proposed method based on the landmarks of one-tenth of training data can give the comparable outlier detection performance while reducing the time complexity greatly in the testing stage.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.549-560
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• 2005

Web-based distance teacher training should focus on increasing self-directed problem solving skills of trainers by problem-based instruction(PBL). Performance assessment evaluates achievement of learning goals through the practical performance learning to solve problems in the real situation. This study proposes a web-based performance assessment model for the distance teacher training. It reflects fairness and objectiveness issues of performance assessment which elementary teachers are concerned about through the survey on distance teacher training, and relieves instructors from overload of managing and scoring performance tests. The proposed model provides problem-based learning situations, interactions between individuals and groups, and web-based cooperative evaluation and the peer evaluation.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.105-115
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• 2012

In this paper, we propose a correction method using phoneme unit segmentation to solve misrecognition of Korean Texts in signboard images using weighted Disassemble Levenshtein Distance. The proposed method calculates distances of recognized texts which are segmented into phoneme units and detects the best matched texts from signboard text database. For verifying the efficiency of the proposed method, a database dictionary is built using 1.3 million words of nationwide signboard through removing duplicated words. We compared the proposed method to Levenshtein Distance and Disassemble Levenshtein Distance which are common representative text string comparison algorithms. As a result, the proposed method based on weighted Disassemble Levenshtein Distance represents an improvement in recognition rates 29.85% and 6% on average compared to that of conventional methods, respectively.

• Structural Engineering and Mechanics
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• v.56 no.1
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• pp.49-56
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• 2015

Dynamic compaction (DC) is a useful method for improvement of granular soils. The method is based on falling a tamper (weighting 5 to 40 ton) from the height of 15 to 30 meters on loose soil that results in stress distribution, vibration of soil particles and desirable compaction of the soil. Propagation of the waves during tamping affects adjacent structures and causes structural damage or loss of performance. Therefore, determination of the safe or critical distance from tamping point to prevent structural hazards is necessary. According to FHWA, the critical distance is defined as the limit of a particle velocity of 76 mm/s. In present study, the ABAQUS software was used for numerical modeling of DC process and determination of the safe distance based on particle velocity criterion. Different variables like alluvium depth, relative density, and impact energy were considered in finite element modeling. It was concluded that for alluvium depths less than 10 m, reflection of the body waves from lower boundaries back to the soil and resonance phenomenon increases the critical distance. However, the critical distance decreases for alluvium depths more than 10 m. Moreover, it was observed that relative density of the alluvium does not significantly influence the critical distance value.