• Journal of the Ergonomics Society of Korea
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• v.26 no.2
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• pp.45-59
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• 2007

The operating tasks of overhead crane have caused undue stress to the operators from physical, mental, and environmental workload. Existing workload assessment models for musculoskeletal disorders such as OWAS, RULA, and QEC have limited applicability to the crane operating tasks because they focus mainly on physical factors and do not consider the relative importance of each factor. The present study was to develop a workload assessment model customized to overhead crane operation, following a systematic process: (1) analyzing task characteristics, (2) selecting workload factors, (3) developing assessment methods, (4) establishing action levels, and (5) computerizing the assessment model. Based on literature review, worksite survey, and focus group interview, 4 physical factors (awkward posture, static posture, repetitive motion, and excessive force), 6 mental factors (visual demand, auditory demand, task complexity and difficulty, time urgency, work schedule related stress, and safety related stress), and 4 environmental factors (noise, vibration, dust, and temperature) were selected and their rating scales and relative weights were determined. Then, based on the workload assessment results of 8 overhead cranes operated at different workplaces, the action levels of each factor category were established. Finally, the crane operation assessment model was computerized for effective analysis and report preparation. The present approach is applicable to develop a customized workload assessment model for an operating task under consideration.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.249-257
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• 2010

In performance art, actors on the stage play an important role. The purpose of performance art is not in producing expression of superficial or trite pleasure, but in presenting a source of philosophical catharsis regarding essence of a human life. It is actors' responsibility to bring such expression onto the stage. Performance art not only involves technical skills but should be a cultural expression to represent tradition, spirituality and identity of a nation. In Korea, performance art tends to follow Western methods of expression. It is desirable to set a future direction to further develop methodology of expression in performance art. As part of such effort, the research examines how the rhythm of traditional Korean dance and dimension of time and space in performance art are effectively visualized in their relation to "stage direction." The research illustrates characteristics and concepts of Korean dances in terms of inhalation in deliberate hypogastric breathing ("danjeon') and rhythms of exhalation (gutgeori, jajinmori, huimori). Also, the research aims to enhance dramatic effect on the stage, which is distinguished from presentation of ordinary actions, by emphasizing dimension of time and space in visualizing expression.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.30-36
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• 2008

The multimedia that is characterized by multi-media, multi-features, multi-representations, huge volume, and varieties, is rapidly spreading out due to the increasing of application domains. Thus, it is urgently needed to develop a multimedia information system that can retrieve the needed information rapidly and accurately from the huge amount of multimedia data. For the content-based retrieval of moving picture, picture information is generally used. It is generally used when video is segmented. Through that, it can be a structural video browsing. The tasking that divides video to shot is called video segmentation, and detecting the cut for video segmentation is called cut detection. The goal of this paper is to divide moving picture using HMMD(Hue-Mar-Min-Diff) color model and edge histogram descriptor among the MPEG-7 visual descriptors. HMMD color model is more familiar to human's perception than the other color spaces. Finally, the proposed retrieval system is implemented as hardware.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1069-1074
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• 2006

자동차/선박/정보통신기기 등의 각종 제조 산업 분야에서 신제품 개발기간과 비용단축을 위해 제품의 설계/스타일링 단계에서 디자인 및 사용자 사용성/편이성 등에 대해 가상으로 품평하는 기술에 대한 관심이 날로 증가하고 있다. 이상적인 가상 품평 기술은 사용자가 실물에 대한 품평 상황과 동일한 체험을 얻을 수 있도록 해야 한다. 이를 위해서 품평 대상물을 사실적으로 표현할 수 있도록 하는 실사 수준의 고품질 가시화 기술과 사용자가 품평 대상물을 자연스럽게 조작할 수 있는 상호작용 기술이 필요하다. 본 연구는 자동차의 내 외관 디자인 품평을 위한 가상 디자인 품평 시스템의 개발에 관한 것으로, 사실적인 자동차 가시화를 위한 환경 반사, 빛 산란, 범프 매핑등의 고품질 쉐이더 구현 및 저작 기술, 몰입환경에서 품평 작업을 위한 3D GUI 지원, 자동차 각 부품의 사용성/편이성 평가를 위한 운동성 조작 기능, 멀티프로젝션 디스플레이 시스템 및 3 차원 인간 모델, 장갑형 입력장치 지원을 통한 몰입형 가상 품평 환경 구축에 관한 기술 및 구현 방법을 제시하고자 한다.

• Korean Journal of Computational Design and Engineering
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• v.21 no.1
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• pp.69-77
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• 2016

The purpose of this study is to estimate the energy expenditure of working in a clean room for manufacturing embedded needles by ergonomic programs. Embedding needle is one of medical devices and it should be manufactured in a clean room. 3D static strength prediction program was used to analyze the slow movements during embedding needle manufacturing in a clean room. Also the energy expenditure prediction program was used to estimate energy expenditure rates for materials handling tasks to help assure worker safety and health in clean room. The energy expenditures of the tasks were calculated using prediction equations derived from empirical data. The energy expenditure rate of 3.09 kcal/min in a clean room didn't exceed the 3.5 kcal/min action limit guideline for an average 8-hour day set by the National Institute for Occupational Safety and Health (NIOSH). Energy consumption was calculated on the same working conditions as EEPP program, using an average body weight of female 20 years old to 59 years who would be the candidates of the real workers.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.288-297
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• 2003

본 논문은 진화 알고리즘(Evolutionary algorithm)의 기법중의 하나인 유전자 프로그래밍(Genetic programming)을 이용하여 miRNA 유전자를 발굴하기 위한 알고리즘을 소개하고 있다 miRNA는 세포내에서 유전자의 전사를 중지시킴으로써 유전자의 발현을 직접적으로 조절하게 되는 작은 RNA 집단 중의 하나이다. 그러므로 miRNA를 유전체 데이터에서 동정해내는 작업은 생물학적으로 상당히 중요하다. 한편 유전체 데이터에서 miRNA를 동정해내는 알고리즘은 생물학적 실험에서의 시간과 비용을 상당히 절감할 수 있으며, 생물학적으로 miRNA를 동정하는 많은 어려움을 덜어주게 된다. 하지만 계산학적으로 miRNA의 동정은 1차 염기서열상의 통계적인 중요도가 부족하여 기존의 유전자 예측 알고리즘을 적용하기에는 어려움이 있다. 따라서 본 연구에서는 miRNA의 염기서열보다는 2차구조에서 더 많은 유사성을 갖는다는 점을 착안하여, 2차구조내에서 공통적인 구조를 찾아내고, 그 정보를 이용하여 miRNA를 동정해내는 방법으로 접근하였다. 이 알고리즘의 성능평가를 위해 우리는 test set을 이용하여 학습된 모델의 특이도(= 34/38)와 민감도(= 38/67)를 계산하였다. 평가결과 본 알고리즘이 기존의 miRNA 예측 프로그램보다 높은 특이도를 갖고 있으며, 유사한 수준의 민감도를 갖고 있음을 보여 주고 있다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1643-1656
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• 2010

It is necessary to develop a system to judge inferiority of goods to minimize the loss at small factories in which produces various kinds of goods with small amounts. That system can be developed based on HTM theory. HTM is a model to apply the operation principles of the neocortex in human brain to the machine learning. We have to build the trained HTM network to use the HTM-based machine learning system. It requires the knowledge for the HTM theory. This paper presents the design and implementation of the training system to support the development of HTM networks which recognize the molding parts to judge its badness. This training system allows field technicians to train the HTM network with high accuracy without the knowledge of the HTM theory. It also can be applied to any kind of the HTM-based judging systems for molding parts.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.3
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• pp.233-240
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• 2000

A small rivers take advantage of not only a site of superb scenic beauty, a play space, a rest place but also a momentous waters reservoir, a drainage on territory residents. Likewise, part of the most massed a life space to a region dwellers shall be extremely in harmony with coexistence space in that every kind plant, animal over again a human being and so on. For improvement planning of small river, various way and model are presented. But, it's want of ability for small rivers of a adaption many-side and throwing in a lot of financial resources. Because the improvement planning of small river was designed all small river in a county, the priority must be preprocessed. Now, the counties prioritized for improvement planning of small river are a few, and acquisition and manipulation of the data are time-consuming. Geo-Spatial Information System (GSIS) is specifically designed to manage and analyze spatial data. It will be to offer the benefit to the determination of the improvement priority in a small river. The purpose of this study is to offer priority for improvement planning of small river using GSIS. For this purpose, it was developed using Arc/Info software and AML was used as a developing tool.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.43-52
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• 2023

Rubber produced by rubber companies is subjected to quality suitability inspection through rheometer test, followed by secondary processing for automobile parts. However, rheometer test is being conducted by humans and has the disadvantage of being very dependent on experts. In order to solve this problem, this paper proposes a deep learning-based rheometer quality inspection system. The proposed system combines LSTM(Long Short-Term Memory) and CNN(Convolutional Neural Network) to take advantage of temporal and spatial characteristics from the rheometer. Next, combination materials of each rubber was used as an auxiliary input to enable quality conformity inspection of various rubber products in one model. The proposed method examined its performance with 30,000 validation datasets. As a result, an F1-score of 0.9940 was achieved on average, and its excellence was proved.