• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.834-839
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• 2009

It is a key element that the problem of emotional feature extraction based on facial image to recognize a human emotion status. In this paper, we propose an Advanced AAM that is improved version of proposed Facial Expression Recognition Systems based on Bayesian Network by using FACS and AAM. This is a study about the most efficient method of optimal facial feature area for human emotion recognition about random user based on generalized HCI system environments. In order to perform such processes, we use a Statistical Shape Analysis at the normalized input image by using Advanced AAM and FACS as a facial expression and emotion status analysis program. And we study about the automatical emotional feature extraction about random user.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.646-650
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• 2014

In this paper, in order to avoid the deterioration of the pattern classification performance which results from the curse of dimensionality, we propose a new feature selection method. The newly proposed feature selection method is based on Fuzzy C-Means clustering algorithm which analyzes the data points to divide them into several clusters and the concept of a function with fuzzy numbers. When it comes to the concept of a function where independent variables are fuzzy numbers and a dependent variable is a label of class, a fuzzy number should be related to the only one class label. Therefore, a good feature is a independent variable of a function with fuzzy numbers. Under this assumption, we calculate the goodness of each feature to pattern classification problem. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• ETRI Journal
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• v.41 no.5
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• pp.574-584
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• 2019

A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two-layered self-organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1279-1287
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• 2018

In this paper, a new type of color coordinate conversion is proposed as modified CIEXYZ from RGB to compress the color gamut. The proposed segmentation includes principal component analysis for the optimal projection of a feature vector into a one-dimensional feature. The final step adopted for lip segmentation is Otsu's threshold for a two-class problem. The performance of the proposed method was better than that of conventional methods, especially for the chromatic feature.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.46-53
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• 2001

The purpose of this paper is to develop a new feature selection method for AE signal classification. The neural network of back propagation algorithm is used. The proposed feature selection method uses the difference between feature coordinates in feature space. This method is compared with the existing methods such as Fisher's criterion, class mean scatter criterion and eigenvector analysis in terms of the recognition rate and the convergence speed, using the signals from the defects in welding zone of austenitic stainless steel and in the metal contact of the rotary compressor. The proposed feature selection methods such as 2-D and 3-D criteria showed better results in the recognition rate than the existing ones.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.69-74
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• 2021

Internet access is also increasing as online activities increase due to the influence of Corona 19. However, network attacks are also diversifying by malicious users, and DDoS among the attacks are increasing year by year. These attacks are detected by intrusion detection systems and can be prevented at an early stage. Various data sets are used to verify intrusion detection algorithms, but in this paper, CICIDS2017, the latest traffic, is used. DDoS attack traffic was analyzed using the decision tree. In this paper, we analyzed the traffic by using the decision tree. Through the analysis, a decisive feature was found, and the accuracy of the decisive feature was confirmed by proceeding the decision tree to prove the accuracy of detection. And the contents of false positive and false negative traffic were analyzed. As a result, learning the feature and the two features showed that the accuracy was 98% and 99.8% respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.317-327
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• 2016

The extraction of significant feature points from a video is directly associated with the suggested method's function. In particular, the occlusion regions in trees or people, or feature points extracted from the background and not from objects such as the sky or mountains are insignificant and can become the cause of undermined matching or recognition function. This paper classifies the feature points required for building recognition by using multi-frames in order to improve the recognition function(algorithm). First, through SIFT(scale invariant feature transform), the primary feature points are extracted and the mismatching feature points are removed. To categorize the feature points in occlusion regions, RANSAC(random sample consensus) is applied. Since the classified feature points were acquired through the matching method, for one feature point there are multiple descriptors and therefore a process that compiles all of them is also suggested. Experiments have verified that the suggested method is competent in its algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.191-196
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• 2009

In this paper, we proposed a feature selection method using Binary Particle Swarm Optimization(BPSO) and Mutual information. This proposed method consists of the feature selection part for selecting candidate feature subset by mutual information and the optimal feature selection part for choosing optimal feature subset by BPSO in the candidate feature subsets. In the candidate feature selection part, we computed the mutual information of all features, respectively and selected a candidate feature subset by the ranking of mutual information. In the optimal feature selection part, optimal feature subset can be found by BPSO in the candidate feature subset. In the BPSO process, we used multi-object function to optimize both accuracy of classifier and selected feature subset size. DNA expression dataset are used for estimating the performance of the proposed method. Experimental results show that this method can achieve better performance for pattern recognition problems than conventional ones.

• Journal of Technologic Dentistry
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• v.31 no.3
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• pp.67-85
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• 2009

This study aims to provide the research for dental technician's stress prevention and management with basic materials by understanding dental technician's psychosocial stress level and examining relevant factors. The subject of this study is 255 dental technologists who work mainly in Seoul Gyeonggi district for a month of April of 2009 and I conducted cross-sectional study through self administered survey. The contents of survey include general feature, occupational feature, health behavior feature. I used Karasek's Job Content Questionnaire, JCQ and Psychosocial well-being index, PWI-SF as means of measurement. To compare the level of dental technician's psychosocial stress, I conducted t-test and ANOVA and I measured the factors that are related with psychosocial stress symptom with step by step multiple regressive analysis. According to the result of Cronbach's a value which is yielded to verify the reliability of means of measurement, the reliability of concept is sufficient. The detailed result of this study is as follows. 1. According to the result of analyzing the stress symptom in accordance with general feature and occupational feature, those dental technologists who are older and not married, graduate from junior college, have lower position, work at university hospital or general hospital show lower stress(p<0.05). There is no difference in the level of psychosocial stress with regard to duty related feature, period of service, daily average working hours, monthly average pay. 2. With regard to health behavior feature, those dental technologists who control weight better and have meal more regularly show lower stress(p<0.05). Those dental technicians who smoke, drink liquid and take a suitable sleep show low stress but the difference does not have significance statistically. 3. With regard to the factors of stress in the workplace, those dental technicians who have lower duty related requirement, have higher duty related control ability, have higher social support, have less instability of employment and have less workload and physical burden show lower stress(p<0.05). 4. According to the result of analyzing the factors that influence dental technologist's stress symptom, social support has the most enormous influence on stress symptom. Unstable employment, regular exercise, regular eating, daily average sleeping hours and technological capacity are also important in this order. According to the result of this study, those dental technicians who have higher social support, less instability of employment, do exercise more regularly, take enough sleep more soundly and have higher technological capacity show lower psychosocial stress symptom. Therefore, to adjust appropriately the dental technician's stress and properly maintain and improve the dental technician's mental health, effective management plan that enables dental technicians to maintain smooth human relationships for dental technicians should be sought. In addition, heath education and health management for dental technicians should be given more thoroughly so that they can establish desirable health behavior in daily life.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.38-43
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• 2008

특성 모델(Feature Model)은 소프트웨어 제품 라인 개발 시 도메인 공학 단계에서 제품들 사이의 공통점과 차이점을 모델링하는데 널리 사용된다. 특성 구성(Feature Configuration)은 특성 모델로부터 특정 제품에 포함될 특성들을 선택한 결과이다. 특성 구성은, 특성 모델에 표현되어 있는 여러 가지 제한 조건을 만족해야 한다. 본 논문에서는 특성 모델 작성 기능과 특성 구성 정의 기능을 지원하고 특성 구성의 검증 기능을 지식 기반 시스템인 JESS를 활용하여 구현한 특성 모델링 도구를 제안한다. 본 도구는 자바 언어와의 결합성이 좋은 JESS 시스템을 이용하여 확장성이 좋으며 특성 구성에서의 오류 원인을 명확히 알려주는 장점을 가진다.