• 법제연구
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• 제53호
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• pp.109-147
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• 2017

1990년대 중반 북한의 식량난이 원인으로 발생한 탈북자 문제는 2000 년대 들어와 외부정보의 유입, 민주화 자유에 대한 갈망 등의 이유로 북한으로부터 탈출이 이어지고 있다. 또한 북한을 탈북하여 중국에 머물고있는 탈북자는 난민으로 인정받지 못하고 강제송환을 비롯한 각종 인권침해에 노출되고 있는 실정이다. 북한에서 탈출한 탈북자는 정치난민에해당되는지, 즉 국제법상 난민에 해당되는지의 여무, 난민으로 인정받지못하는 경우 국제인권법상 인권보호 규정에 의한 보호의 가능성과 방법이 무엇인지 생각하지 않으면 안 된다. 탈북자의 난민인정 문제는 개별국가의 주권문제이기는 하나, 난민협약상, UNHCR상의 고유한 권리로서보호받아야 주체로 넓은 의미에서 난민문제로 다뤄야 할 것이다. 향후, 북한으로부터 대량 탈북과 이로 인한 난민문제 발생에 대비하여 탈북자의 난민인정과 국제적 인권보호의 필요성에 대해 개별국가, UN총회, 인권이사회의 결정, UNHCR의 적극적 지원 등 국제간 연대가 필요하다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권11호
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• pp.1147-1155
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• 2005

본 논문은 단순한 형태의 개인 착인 및 검증방법의 한계를 극복하여 절도나 누출에 의해 도용될 수 없고 변경되거나 분실할 위험성이 없는 새로운 형태의 인증 방법인 홍채인식을 연구하였다. 사람의 홍채는 태어날 때 한번 정해지면 평생 변화하지 않는 특성을 가지고 있으며, 개개인별로 모양이 모두 다른 것으로 알려져 있다. 이에, 본 논문에서는 홍채영상 취득 시 조명에 의한 동공의 크기 변화에 민감하지 않은 2차원의 홍채패턴을 취득하여, 2차 가버 웨이블릿과 퍼지 선형판별분석기법(LDA)을 이용하여 특징 벡터를 추출하고 인식한다. 인식과정에서는 상관관계 계수를 이용하여 다른 홍채의 특징간과 매칭값을 측정하고 유사도가 가장 큰 대상을 찾게 된다. 이때, 입력영상에 대하여 4개 방향의 가버 웨이블릿을 거쳐 얻어진 4개의 상관관계 계수 간 중 가장 큰 값을 갖는 대상자를 인식 대상자로 선정하므로 오인식될 확률을 최소화 할 수 있다. 제안한 알고리듬의 유용성을 확인하기 위해 대상자 50명에 대하여 각각 6회씩 촬영한 두 가지 데이타베이스(CASIA, CBNU)를 이용하였으며, 실험 결과 $90\%$ 이상의 인식률을 얻었다.

• 대한임베디드공학회논문지
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• 제15권1호
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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.

• 한국생활과학회지
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• 제5권1호
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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.

• 한국지능시스템학회논문지
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• 제13권6호
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• pp.716-721
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• 2003

본 논문에서는 사람의 생태학적, 행동학적 특성을 이용하여 개인을 인식하는 생체인식 기법의 하나인 홍채인식을 다루었다. 사람의 홍채는 태어날 때 한번 정해지면 평생 변화하지 않는 특성을 가지고 있으며, 개개인별로 모양이 모두 다른 것으로 알려져 있다. 이에, 본 논문에서는 홍채영상 취득시 조명에 의한 동공의 크기 변화에 민감하지 않은 2차원의 홍채패턴을 취득하고, 2D Gabor 필터와 48개의 분할된 섹터로부터 특징 값을 추출한다. 인식과정에서는 correlation 계수를 이용하여 서로 다른 홍채의 특징 값에 대해 유사도를 측정하고 가장 큰 값을 갖는 대상을 찾게 되는데, 이때, 3개의 필터를 거쳐 얻어진 영상에 대해 최고의 값을 인식 대상자로 인정하므로 오인식 될 확률을 최소화 할 수 있다. 제안한 알고리듬의 유용성을 확인하기 위해 대상자 10명에 대해 5회씩 촬영한 데이터베이스에 대해 실험한 결과 90% 이상의 높은 인식률을 얻었다.

• 대한인간공학회지
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• 제30권1호
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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.

• 품질경영학회지
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• 제23권3호
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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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• 제9권1호
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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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• 제11권11호
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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.

• 데이타베이스연구회지:데이타베이스연구
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• 제34권3호
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• pp.45-57
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• 2018

주행 중에 발생하는 졸음은 큰 사고로 직결될 수 있는 매우 위험한 운전자 상태이다. 졸음을 방지하기 위하여 운전자의 상태를 파악하는 전통적인 졸음 감지 방법들이 존재하지만 운전자들이 가지는 개개인의 특성을 모두 반영한 일반화 된 운전자 상태 인식에는 한계가 있다. 최근에는 운전자의 상태를 인식하기 위한 딥 러닝기반의 상태인식 연구들이 제안되었다. 딥 러닝은 인간이 아닌 기계가 특징을 추출하여 보다 일반화된 인식모델을 도출할 수 있는 장점이 있다. 본 연구에서는 운전자의 상태를 파악하기 위해 이미지와 PPG를 동시에 학습하여 기존 딥 러닝 방식보다 정확한 상태 인식 모델을 제안한다. 본 논문은 운전자의 이미지와 PPG 데이터가 졸음 감지에 어떤 영향을 미치는지, 함께 사용되었을 때 학습 모델의 성능을 향상시키는지 실험을 통해 확인하였다. 이미지만을 사용했을 때 보다 이미지와 PPG를 함께 사용하였을 때 3%내외의 정확도 향상을 확인했다. 또한, 운전자의 상태를 세 가지로 분류하는 멀티모달 딥 러닝 기반의 모델을 96%의 분류 정확도를 보였다.