• 복식문화연구
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• 제25권4호
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• pp.529-542
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• 2017

The purpose of this study is to utilize technology as basic data for smart clothing product research and development. This technology can recognize user's motion according to characteristics types and functions of wearable smart clothing products. In order to analyze the case of motion recognition products, we searched for previous research data and cases referred to as major keywords in leading search engines, Google and Naver. Among the searched cases, information on the characteristics and major functions of the 42 final products selected on the market are examined in detail. Motion recognition for smart clothing products is classified into four body types: head & face, body, arms & hands, and legs & feet. Smart clothing products was developed with various items, such as hats, glasses, bras, shirts, pants, bracelets, rings, socks, shoes, etc., It was divided into four functions health care type for prevention of injuries, health monitor, posture correction, sports type for heartbeat and exercise monitor, exercise coaching, posture correction, convenience for smart controller and security and entertainment type for pleasure. The function of the motion recognition smart clothing product discussed in this study will be a useful reference when designing a motion recognition smart clothing product that is blended with IT technology.

• 한국통신학회논문지
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• 제18권9호
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• pp.1269-1282
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• 1993

본 논문에서는 종래의 결정론적 방법과 신경망을 이용하여, 인쇄체 한자를 인식하는 방법을 제안하였다. 먼저 한자를 구성하는 획성분의 4방항백터를 추출하였다. 다음에 구해진 방향벡터에 무게중심의 메쉬를 만든 다음, 각 메쉬내의 흑화소 길이로 8$\times$8의 특징 매트릭스를 구성하였다. 정규화한 특징 매트릭스 값은 14의 문자형식으로 1차 분류하기위해 신경망에 입력으로 하였고, 이 분류된 문자는 부수를 인식하는 부수인식 신경망에서 다시 2차분류하였다. 마지막으로 2차분류된 문자는 입력한사와 표준한자와의 유사도를 적용하여 최종인식을 행하였다. 본 알고리즘이 한자의 인치에 유효함을 보였다.

• 대한지리학회지
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• 제46권4호
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• pp.554-566
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• 2011

소비 자본주의는 상품 물신화 전략을 통해 상품에 내재되어 있는 실재적인 지리적 지식을 상상적인 지리적 지식으로 대체시켜 나간다. 이로 인해 현대의 소비자 세계 속에서 학생들은 상품의 실재 세계와 단절되고 상품이 가지는 지리적 삶을 망각하게 됨으로써 결국 자신과 상품을 관계적으로 사고 할 수 있는 능력이 약화되고 있다. 그래서 학생들은 상품의 글로벌 네트워크 속에서 자신이 가지는 위치의 의미와 자신과 상품 네트워크 사이의 상호 관계성으로 인해 발생되는 환경 문제를 윤리적으로 인식하지 못하게 된다. 이러한 문제 의식과 현실 상황 속에서 본 연구는 햄버거 커넥션을 사례로 상품 소비와 윤리의 관계를 살펴보면서 학생들로 하여금 관계적 사고를 통해 상품과 학생 자신의 관계를 바라볼 수 있는 안목을 가질 수 있도록 하는 것이 지리 교육의 역할임을 주장하고자 한다.

• 패션비즈니스
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• 제19권4호
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• pp.21-36
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• 2015

The purpose of this study is to classify the stress into groups and analyze their differences in self-consciousness, and appearance management behavior. Questionnaires were administered to 377 middle and high school girls living in Deagu metropolitan City. Frequency, factor analysis, reliability analysis, cluster analysis, ANOVA, Duncant-test, and t-test are all used for data analysis. Our findings show that stress developed due to several reasons: the categories are as follows into grades-related low stress, exam-related high stress, and society-related high stress. For the purposes of our study, we labeled self-consciousness as a combination of being socially and privately self-consciousness and showing signs of social anxiety. Appearance management behavior deals with esthetic plastic surgery, clothing harmony, weight management, hair management, health care, skin care, and meal management. Stress shows a significant correlation with the sub-variable self-consciousness and appearance management behavior. The groups show a significant difference in the self-consciousness, and appearance management behavior. There is also a significant difference among stress, self-consciousness and appearance management behavior by grade. The students in seemed to recognize that their appearance can be improved by dressing up and managing their outwardly appearance. Teachers should educate students to have the variety of views on the meaning of beauty. In addition, schools need to develop programs to educate student about appearances, as the student's interests differ due to the stress type of the adolescent.

• 한국주거학회논문집
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• 제20권2호
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• pp.11-18
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• 2009

After 2004, as the community mixed-support facility in Japan was admitted as a private business of public facilities based on the Special Law for Urban Regeneration, the community mixed-support facilities in Japan are developed into various types with the view of the urban regeneration and urban renewal, more different point of view, and a tendency of establishment of the community facility has been considerably changed for the past twenty years. The reasons of the change are the social demand for the reformation of facility and the modification of subsidy constitution according to the establishment of equal facility. Some examples of that are the construction of lifelong education community and the change into a equivalent society between male and female and the adjusting to the aging and the welfare society and the social situation of more consumption recently, and in order to emerge from former building system, new facilities related to the contents are being expanded. The complex of the community mixed-support facility has an advantage in that it supplies the services for the complex of the community mixed-support facility, constitutes the communal character and the sense of solidarity among residents and can lead the development of region through the exchange of regional information. Through the Japanese community mixed-support facility which has many cases of it, this study would recognize the suggestion, the feature of it and examine the complex types.

• 시스템엔지니어링학술지
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• 제1권2호
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• pp.26-33
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• 2005

In this paper, an algorithm is presented to recognize road based on unpaved test courses image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, gray level slicing, masking and identification of unpaved test courses. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing unpaved road. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning or assistance system.

• 대한안전경영과학회지
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• 제7권1호
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• pp.101-115
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• 2005

This study deals with the procedure of safety improvement, productivity increase ,and tact-time reduction through setting up the system about preventive maintenance. Actually, it is hard to establish and carry out preventive maintenance, even though we recognize the importance of the system concerning time, cost, labor, and so forth. In this study in the viewpoint of cost we are for achieving maximum efficiency by change and reduction of planning process adapted to the special work group. At first we briefly will mention the kind ,the necessity ,and the concept of preventive maintenance ,and then divide the equipment used in the assembly line into the two whether it is necessary or not by way of estimating the breakdown loss ,comparing with general establishment of preventive maintenance and modifying it to the case. At the second step we will establish the operation system of plan management related to production and quality in the special case. Check period and category will be set by dividing the assembly equipment into LCL and Focus in the third step. The forth step will contain the operation procedure in detail. And then we must make check and repair record periodically. Finally, on the basis of the record the selection of checking of significance will be conducted. This results in safety improvement, tact time reduction, and productivity improvement.

• 제어로봇시스템학회논문지
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• 제20권10호
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• pp.1051-1056
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• 2014

In this paper, we introduce an intelligent robotic arc welding system which exploits sensors like as LVS (Laser Vision Sensor), Hall effect sensor, voltmeter and so on. The use of industrial robot is saturated because of its own limitation, and one of the major limitations is that industrial robot cannot recognize the environment. Lately, sensor-based environmental awareness research of the industrial robot is performed actively to overcome such limitation, and it can expand application field and improve productivity. We classify the sensor-based intelligent arc welding robot system by the goal and the sensing data. The goals can be categorized into detection of a welding start point, tracking of a welding line and correction of a torch deformation. The Sensing data can be categorized into welding data (i.e. current, voltage and short circuit detection) and displacement data (i.e. distance, position). This paper covers not only the explanation of the each category but also its advantage and limitation.

• 한국항만학회지
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• 제13권2호
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• pp.303-312
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• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2330-2332
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• 1998

This paper suggests a method to recognize the various defect patterns of cold mill strip using binary decision tree automatically constructed by genetic algorithm. The genetic algorithm and K-means algorithm were used to select a subset of the suitable features at each node in binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes by a linear decision boundary. This process was repeated at each node until all the patterns are classified into individual classes. The final recognizer is accomplished by neural network learning of a set of standard patterns at each node. Binary decision tree classifier was applied to the recognition of the defect patterns of cold mill strip and the experimental results were given to demonstrate the usefulness of the proposed scheme.