• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1236-1239
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• 2002

When we see an object, we usually can say what it is easily even for the case where the object isn't shown in the frontal view. However, it is difficult to believe that all views of every object we have ever seen are fully memorized in our brain. Possibly, when an object is shown, we have some typical views of the object in our brain through our past experience and reconstruct the view to recognize what the presented object is. Non-negative Matrix Factorization (NMF) is one of the methods to extract the basis images from sample data set. The prominent feature of this method is that the reconstructed image is obtained by only additions of the basis images with suitable positive weights. So NMF can be seen more biologically plausible method than any other feature extraction methods such as Vector Quantization (VQ) and principal Component Analysis (PCA). In this paper, we adopt NMF to extract the aspect features from the set of images, which consists of various views of a given object. Some experiments are shown how much well NMF can extract the aspect features than any other methods such as VQ and PCA.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.281-286
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• 2003

Since National Geographic Information System was started, paper maps have been made with computer aided editing of digital map, instead of etching map-size negative film. Automated paper mapping system's necessity is growing more and more, because digital map has changed into Ver.2.0 which include attributes of feature. Therefore, in this study we try to analyze correlation of the digital map feature code and the 1/5,000 topographic map specifications which is necessary for paper mapping automatization using digital map Ver.2.0, and try to develop fundamental modules which will play a core role in automated paper mapping system.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.321-328
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• 2004

Since National Geographic Information System was started, topographic maps have been made with computer aided editing of digital map, instead of etching map-size negative film. topographic mapping system's necessity is growing more and more, because digital map has changed into Ver.2.0 which include attributes of feature. On the basis of the previous study for analyzing correlation between the digital map feature code and the 1/5,000 topographic map specifications and trying to develop fundamental modules which will play a core role in topographic mapping system, in this study, we apply some 1/5,000 digital maps Ver.2.0 to topographic mapping system have implemented and try to analyze the result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.168-182
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• 2020

Spoofing attacks, especially replay attacks, pose great security challenges to automatic speaker verification (ASV) systems. Current works on replay attacks detection primarily focused on either developing new features or improving classifier performance, ignoring the effects of feature variability, e.g., the channel variability. In this paper, we first establish a mathematical model for replay speech and introduce a method for eliminating the negative interference of the channel. Then a novel feature is proposed to detect the replay attacks. To further boost the detection performance, four post-processing methods using normalization techniques are investigated. We evaluate our proposed method on the ASVspoof 2017 dataset. The experimental results show that our approach outperforms the competing methods in terms of detection accuracy. More interestingly, we find that the proposed normalization strategy could also improve the performance of the existing algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.5
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• pp.578-584
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• 2011

In mechanical cutting process, burr was generated at workpiece by cutting tool generally. It is working disturbance during manufacturing process. Besides burr was taken shape relatively large size more micro scale machining than macro scale machining. Many researches have been studied to remove micro burr(de-burring), because it was negative effect for accuracy of machining shape. However, micro de-burring was constrained by burr height, micro feature and so on. In this paper, experimental research was carried out to compare de-burring characteristics of $Al_2O_3$ abrasive and polymer.

• ETRI Journal
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• v.33 no.2
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• pp.240-250
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• 2011

To enable a relevance feedback paradigm to evolve itself by users' feedback, a reinforcement learning method is proposed. The feature space of the medical images is partitioned into positive and negative hypercubes by the system. Each hypercube constitutes an individual in a genetic algorithm infrastructure. The rules take recombination and mutation operators to make new rules for better exploring the feature space. The effectiveness of the rules is checked by a scoring method by which the ineffective rules will be omitted gradually and the effective ones survive. Our experiments on a set of 10,004 images from the IRMA database show that the proposed approach can better describe the semantic content of images for image retrieval with respect to other existing approaches in the literature.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.294-299
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• 2023

Micro ribonucleic acids (miRNAs) can regulate the protein expression levels of genes in the human body and have recently been reported to be closely related to the cause of disease. Determining the genes related to miRNAs will aid in understanding the mechanisms underlying complex miRNAs. However, the identification of miRNA-related genes through wet experiments (in vivo, traditional methods are time- and cost-consuming). To overcome these problems, recent studies have investigated the prediction of miRNA relevance using deep learning models. This study presents a method for predicting the relationships between miRNAs and genes. First, we reconstruct a negative dataset using the proposed method. We then extracted the feature using an autoencoder, after which the feature vector was concatenated with the original data. Thereafter, the concatenated data were used to train a long short-term memory model. Our model exhibited an area under the curve of 0.9609, outperforming previously reported models trained using the same dataset.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.25-37
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• 2000

The trajectories of feature points can be defined by the correspondences between points in consecutive frames. The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. The trajectories of feature points are determined by calculating the matching measure, which is defined as the minimum weighted Euclidean distance between two feature points. The weights are automatically updated in order to properly reflect the motion characteristics. We solve the correspondence problem as an optimal graph search problem, considering that the existence of false feature points may have serious effect on the correspondence search. The proposed algorithm finds a local optimal correspondence so that the effect of false feature point can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O($m^2n$) in the worst case, where m and n arc the number of feature points in two consecutive frames. By considering false feature points and by properly reflecting motion characteristics, the proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.39-47
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• 2012

The opinion of user on a certain product is expressed in positive/negative sentiments for specific features of it. In some cases, they are expressed for a holistic part of homogeneous specific features, or expressed for product itself. Therefore, in the area of opinion mining, name of opinion features to be extracted are specific feature names, holonyms for theses specific features, and product names. However, when the opinion target is described with product name or holonym, sometimes it may not match feature name of opinion sentence to true opinion target intended by the reviewer. In this paper, we present a method to extract opinion targets from opinion sentences. Most importantly, we propose a method to extract true target from the feature names mismatched to a intended target. First, we extract candidate opinion pairs using dependency relation between words, and then select feature names frequently mismatched to opinion target. Each selected opinion feature name is replaced to a specific feature intended by the reviewer. Finally, in order to extract relevant opinion features from the whole candidate opinion pairs including modified opinion feature names, candidate opinion pairs are rearranged by the order of user's interest.

• Korean Journal of Human Ecology
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• v.8 no.2
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• pp.255-273
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• 1999

The purpose of this study was to examine the relationship between characteristics of personality and respondent characteristics of Kinetic Family Drawing for young children. The subjects were 170 children(110 boys and 60 girls). The personal interview contained Personality Characteristic Test for young children(In-Sub Song, 1993) and Kinetic Family Drawing Test(Burns and Kaufman, 1982). Results of the test were analyzed by t-test and ANOVA by SAS program. Results are followings. First, chileren's sex and the general tendency of personal characteristic showed significant difference in the emotional personality among 4 personality characteristics. Girls show more positive tendency than boys in moral, physical, appearance and feature which expressed personal feeling and emotion. Also, girls showed more positive tendency than boys in personal characteristic which showed physical ability. Second, Children's sex and individual characteristic in Kinetic Family Drawing respondent characteristic showed significant difference in own's arm length. Also, Using a rare of paper and chapter 1 of the power among the family showed significant difference in styles and symbols. The boys drew lengther arms compared with their height than the girls. The girls were less complicative, anxious, comparative and aggressive for their family. Third, As a result of the study about the relationship between 4 personal characteristics of children and individual's behavior in Kinetic Family Drawing respondent characteristic, the significant difference is showed in academic personality and social personality had higher completion of their father's feature and drew bigger feet. In socal personality, negative behavior than positive children. Fourth, As a result of the study about the relationship between 4 personal characteristics of children and individual's characteristic, the significant difference were found in academic personality, social personality, family personality and emotional personality. Children with negative academic personality drew longer arms than children with positive academic personality, social personality and family personality. Also, Children with negative emotional personality drew more siblings than children with positive emotional personality. Fifth, The academic personality and the social personality had significant difference in the relationship between 4 personal characteristics of children and dynamics. In social personality, normal children were more tendencious to look at the important person with their mother's direction than positive children. Sixth, In terms of the relationship between 4 personal characteristics of children and mode, academic personality and family personality showed significant difference. Children with negative academic personality used more edge of papers than children with positive academic personality and children with positive academic personality and children with negative family personality fold more papers than children with positive family personality. At last, there were no significant difference between 4 personal characteristics of children and styles as well as symbols.