• Journal of Legislation Research
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• no.53
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• pp.109-147
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• 2017

North Korean defectors had left North Korea often to escape from food shortages in the mid-1990s. Since the 2000s, the reasons of their flee from North Korea have more resulted from their exposure to external information, and a desire for democracy and freedom. However, North Korean defectors living in China are not recognized as refugees and thus subject to various human rights violations including forced repatriation. It needs to be thought that wether North Korean defectors who escape from North Korea are political refugees under international law. If they are not recognized as refugees in their new countries, it is imperative to consider a possible way to protect their human rights under international law. The problem of recognition of the refugee status of a person is a matter of involving the sovereignty of individual countries, however, the Convention Relating to the Status of Refugees should provide protection of their unique rights, as recognizes by the UNHCR, and their status should be treated as a refugees issue in a broad sense. In the future, it is a necessary to establish international solidarity among individual countries, the UN General Assembly, the decisions of the Human Rights Council and support of UNHCR, to anticipate the need for the refugee recognition and the protection of International Human Rights in preparation for possible mass defections and refugees from North Korea.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1147-1155
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• 2005

This paper deals with Iris recognition as one of biometric techniques which is applied to identify a person using his/her behavior or congenital characteristics. The Iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D Iris pattern having a property of size invariant and using the fuzzy LDA which is further through four types of 2D Gabor wavelet. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use four different matching values obtained from four different directional Gabor wavelet and select the maximum value, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 300 Iris Patterns extracted from 50 subjects and finally got more higher than $90\%$ recognition rate.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.1
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• pp.35-42
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• 2020

In this paper, we propose a method to keep the robot at a distance of 30 to 45cm from the user in consideration of each individual's minimum area and inconvenience by using a 2D LiDAR sensor LDS-01 as the secondary sensor along with a QR code. First, the robot determines the brightness of the video and the presence of a QR code. If the light is bright and there is a QR code due to human's presence, the range of the 2D LiDAR sensor is set based on the position of the QR code in the captured image to find and follow the correct target. On the other hand, when the robot does not recognize the QR code due to the low light, the target is followed using a database that stores obstacles and human actions made before the experiment using only the 2D LiDAR sensor. As a result, our robot can follow the target person in four situations based on nine locations with seven types of motion.

• Korean Journal of Human Ecology
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• v.5 no.1
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• pp.43-53
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• 1996

The purpose of this study was to investigate the actual condition of fashion sales related persons and analyze their different role recognition in women's Ready-To-Wear shops. A questionnaire was administered to 378 fashion sales related persons in department stores and individual shops. Data were analyzed by using crosstabs, $X^2$, t-test, Scheffe's test and ANOVA by using of SPSS PC program. The results of this study were as follows: 1. In the role of fashion salespersons, managers participated highly in the merchandise buying plan, actual merchandise buying and advertisement, and shopmasters participated in the management of salespersons and keeping good relation with customers and display. 2. There was significant difference according to the existence of shopmasters in sales promotion. Shops with shopmasters had regular sales and filed up customer cards. 3. Shopmasters and salespersons attached importance to fashion information, market information, sales result information, and managers attached importance to customer information, enterprise environment information in utilizing of informations. Managers considered customer survey very important but shopmasters and salespersons did not. Shopmasters, managers, and salespersons all attached importance to customers' preference survey as customers' information source. 4. There were significant differences in lifestyle survey, buying method survey, preference survey, street fashion survey, brand identity survey and advertizement effect survey of customers by the different roles of fashion salespersons. 5. There were significant differences in the degree of merchandise knowledge, service and after service in sales service recognition by the different roles of fashion salespersons.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.716-721
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• 2003

This paper deals with the iris recognition as one of biometric techniques which are applied to identify a person using his/her behavior or congenital characteristics. The iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D iris pattern having a property of size invariant and divide it into 24 sectors which are further through three types of 2D Gabor filters. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use three different matching values obtained from three different directional Gabor filters and select the maximum value among them, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 50 iris patterns extracted from 10 subjects and finally get more higher than 90% recognition rate.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.195-202
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• 2011

Objective: The aim of this study is to investigate and review the previous researches about objective measuring fatigue caused by visual stimuli. Also, we analyze possibility of alternative visual fatigue measurement methods using facial expression recognition and gesture recognition. Background: In most previous researches, visual fatigue is commonly measured by survey or interview based subjective method. However, the subjective evaluation methods can be affected by individual feeling's variation or other kinds of stimuli. To solve these problems, signal and image processing based visual fatigue measurement methods have been widely researched. Method: To analyze the signal and image processing based methods, we categorized previous works into three groups such as bio-signal, brainwave, and eye image based methods. Also, the possibility of adopting facial expression or gesture recognition to measure visual fatigue is analyzed. Results: Bio-signal and brainwave based methods have problems because they can be degraded by not only visual stimuli but also the other kinds of external stimuli caused by other sense organs. In eye image based methods, using only single feature such as blink frequency or pupil size also has problem because the single feature can be easily degraded by other kinds of emotions. Conclusion: Multi-modal measurement method is required by fusing several features which are extracted from the bio-signal and image. Also, alternative method using facial expression or gesture recognition can be considered. Application: The objective visual fatigue measurement method can be applied into the fields of quantitative and comparative measurement of visual fatigue of next generation display devices in terms of human factor.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.69-83
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• 1995

In a large number of literature on of inspection tasks, one of the most consistent findings is the existence of large and consistent differences among inspectors. It is possible that the individual difference is described by the difference of cognitive skills, because cognitive skills are required more than manual skills in inspection tasks. Therefore, a set of cognitive factors in human information processing may underly human performance in inspection tasks. In this study, a cognitive skill was described as the relative importance of the cognitive factors involved. A hierarchical task analysis and a fuzzy hierarchical analysis were used to represent how the importance of cognitive factors contribute to inspection performance. An experiment was conducted using the computer simulations of PCB inspection tasks. The results revealed that the subject group with better performance showed the importance weights of cognitive factors in the following rank; (attention, perception, judgement, classification, recognition)<(detection)$\ll$(memory). The results of the experiment can serve as a selection criterion for efficient inspection performance and the information of skilled learning for an inspection training program. The usefullness of a hierarchical task analysis and a fuzzy hierarchical task analysis for the analysis of cognitive tasks are also confirmed.

• International Journal of Safety
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• v.9 no.1
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• pp.30-34
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• 2010

A big difference is seen in the perception of self-responsibility concerning safety, as a result of my survey on the safety measures taken in the pipeline construction at workers level between Japan and Indonesia. Specifically, when an accident occurs, a worker in Indonesia will think that the responsibility depends on the person who causes it. However a worker in Japan will think that safety is can only be protected by law and regulations. There is also another difference in the understanding of construction period. It is alright in Indonesia to take 5 times longer period than it takes in Japan if the cost is less. The idea of punctual delivery is very strong in Japan. Through this survey, points which construction industry in Japan could learn from Indonesia came to surface. In addition, over the recent years, several nasty accidents at Japanese sites were caused due to human error to disregard the law. Japanese should arouse the awareness of self-responsibility in this regard. Risk management should be upon self-recognition of each individual worker in both countries. What is important is the "work attitude education", "to grow sense of self-responsibility by thinking on one's own for one's self" in the education curriculum of man to man learning as in technical educational program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5436-5458
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• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

• Database Research
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• v.34 no.3
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• pp.45-57
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• 2018

The drowsiness that occurs in the driving is a very dangerous driver condition that can be directly linked to a major accident. In order to prevent drowsiness, there are traditional drowsiness detection methods to grasp the driver's condition, but there is a limit to the generalized driver's condition recognition that reflects the individual characteristics of drivers. In recent years, deep learning based state recognition studies have been proposed to recognize drivers' condition. Deep learning has the advantage of extracting features from a non-human machine and deriving a more generalized recognition model. In this study, we propose a more accurate state recognition model than the existing deep learning method by learning image and PPG at the same time to grasp driver's condition. This paper confirms the effect of driver's image and PPG data on drowsiness detection and experiment to see if it improves the performance of learning model when used together. We confirmed the accuracy improvement of around 3% when using image and PPG together than using image alone. In addition, the multimodal deep learning based model that classifies the driver's condition into three categories showed a classification accuracy of 96%.