• Archives of design research
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• v.13 no.2
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• pp.15-24
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• 2000

The demands of golf car is being increased with increment in golf population, gradually proceeding to the trend of popularization, but domestic golf car industry is not so mature as it cope with the need of this market appropriately. Most import golf cars of high price have occupied the domestic market from the viewpoint of the its demands. Although the import golf car provided bad after-sales services and very expensive components, those demand's breadth continue to rise steadily. We decide to have to approach an appropriate time to develop the competitive model native to korean style in the field of golf car, since we have established our foundation in auto industry. At this point we try to analyze the golf car expected from a competition and the present state of golf car industry inside and outside of the country through this study. We attempt to derive the precondition for design development of a proper model to possess competitive power in foreign market from now on.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.17 no.4
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• pp.282-288
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• 2007

그 동안 많은 역학연구를 통해서 금속가공유(metalworking fluid, MWFs) 노출과 여러 조직에서 암 발생 위험과의 관계를 밝혔지만, 금속가공유 종류(비수용성, 수용성, 합성, 준합성)별로 구분된 위험은 아직 완전하게 규명되지 않았다. 역학조사에서 금속가공유 노출을 대체할 수 있는 인자(surrogate)로서 정성적(qualitative), 명목적(ordinal) 혹은 준정량적인(semi-quantitative) 변수들(금속가공유에 대한 노출 유무, 노출 정도: 높음, 낮음 등, 직업 유무, 근무기간 등)을 이용하여 금속가공유 노출을 평가하였다. 이러한 노출평가방법은 기본적으로 금속가공유 노출 강도(intensity)가 고려되지 않을 뿐만 아니라 노출 분류 오류(misclassification)도 항상 존재할 수 있어 금속가공유 노출은 물론이고 종류별 위험을 밝히기 어렵다. 일부 역학연구에서 금속가공유 종류별 누적 노출양(cumulative exposure level)과 암위험과의 관계를 밝혔다. 이러한 연구결과들은 모두 금속가공유 종류별로 과거노출을 추정할 수 있는 자료(정량적인 노출평가자료, 과거직업력, 취급했던 금속가공유 종류 등)가 잘 기록되어 있는 1개의 대규모 자동차공장에서 나온 것들이다. 따라서 금속가공유에 대한 노출자료가 부족하고 사용특성에 대한 기록이 없거나 부족한 일반 인구나 산업을 대상으로 한 역학연구에서는 금속가공유의 종류별 위험을 밝히는것은 불가능하다. 금속가공유 종류별로 과거 노출에 대한 확률(probability)을 추정하는데 일반적으로 활용할 수 있는 노출확률 메트릭스를 개발하는 것이 필요하다.

• Journal of Korean Society for Atmospheric Environment
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• v.7 no.1
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• pp.73-80
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• 1991

인류가 산업발전 등으로 인해 석유등 화석연료를 사용함에 따라 대기오염은 날로 악화되어 1952년 런던스모그 같은 참사를 맞이하였고 이에 각국은 이러한 대기 오염물질을 저감하기 위하여 노력한 결과 대기 오염물질은 낮아지고 있으나 이에 반해 이산화탄소 배출량 증가에 따른 지구 온난화 현상과 오존층 파괴는 지역적인 환경문제에서 번세계적인 환경문제로 확산 전개되고 있다. 특히 산업혁명후 화석연료의 급격한 사용증가로 인한 이산화탄소 배출량 증가는 지구를 온나화시키고 수십년 후에는 환경에 심각한 영향을 주게 되는 것은 의심할 여지가 없는 것으로 이는 지구환경문제 중에서 금회 최대의 과제로 대두되게 되었다. 이에 따라 1985년 UNEP 관리 이사회를 필두로 "지구환경보전에 관한 동경회의", "대기오염 및 기후변동에 관한 노드윅 회의", "백악관회의", "휴스톤 Summit" 등에서 이 문제가 거론되기 시작하여 '90. 8월에는 스웨덴에서 온난화에 대한 과학적 인식과 대책의 메카니즘을 정하기 위한 IPCC 4차 회의가 각국 대표들이 참석한 가운데 정치, 경제, 과학의 문제로 등장하여 우리생활의 근본을 좌우할 다각적인 논의가 진행된 바 있다. 또한 미국, 영국, 일본 등 선진국들의 정상이 모이는 G7 회담 등에서 논의되고 있는 것들 중 정치적인 문제를 제외하고는 환경문제를 가장 많이 다룬다는 외신보도를 우리는 여러번 접한바 있다. 현재 국제적 환경문제로 가장 관심이 집중되고 있는 문제 중 몇가지를 소개하면 우선 <몬트리올의 정서에 의한 오존층 보호>를 들 수 있겠고, 최근 국제 협약 제정을 추진하고 있는 "지구온난화 방지에 관한 기후협약" 그리고 유해폐기물의 국제교역에 관한 "바젤협약"과 함께 새로이 제기된 "생물학적 다양성 협약"등이 거론되고 있으며, 이에 덧붙여 미국의 "자동차배출가스 규제"도 우리나라 산업에 큰 영향을 미칠 것으로 판단된다. 본 논문은 이중 대기와 관련된 오존층 보호와 지구온난화 대책에 대한 국제회의 등에서 현재까지 논의되었거나 토의될 내용에 대하여 기술하고 특히 금년부터 집중적으로 국제협상이 진행될 지구온난화 문제에 대한 최근의 국제동향 우리나라의 입장을 기술하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1036-1044
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• 2012

Thanks to progressive development of IT technology, the number of intelligent devices communicating each other through an In-Vehicle Network(IVN) has been steadily increasing. It is expected that the required network bandwidth and network nodes for vehicle control in 2015 will be increased by two times and one and half times as compared to in 2010, respectively. As a result, many researchers in automotive industry has showed a significant interest on industrial Ethernets, such as EtherCAT and TTEthernet. This paper addresses an analysis on transmission delay and fault recovery performance with an EtherCAT network which is being considered as an IVN. A mathematical model based on the analysis is verified through a set of experiments using an experimental network setup.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.172-178
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• 2015

The control moment gyroscope(CMG) which is well known as an effective high-torque-generating device is applicable to space vehicles, airplanes, ships, automobiles, robotics, etc. for attitude stabilization and maneuver. This paper deals with the overall details of 100Nm-class CMG development for various industrial applications, and provides the activities and results associated with the CMG system-level requirement analysis, the motor subsystem design/manufacturing/integration, the construction of ground support equipment, and the performance test and evaluation. The performance test reveals that the CMG generates the torque output more than 120Nm in as-designed operation of spin motor and gimbal motor.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.399-408
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• 2006

Railroads have been developed as public transportation and made a great contribution to national economic growth. But after the mid-20th century, its qualities have been getting low because of focusing on the investment and development of cars and airplanes. Its role which is getting the excellent merits on the mass transportation, rapid transit, safety, state period, energy efficiency, and prevention of environmental pollution has been reconsidered. Elements of horizontal alignment are needed in the case where the existing railroad lines should be improved or moved. If its design drawing was lost or damaged, it is impossible to recover. It is not easy to repair for it as disasters. We must understand an existing railroad line to bring a function included a basic geography situation. In this study, we acquire, analyze, and process the digital images of the railroad and then reappear shape of three dimension. And we expect to be utilized to construct the facility information by extracting the alignment elements of existing railroad lines reversely.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1159-1191
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• 2017

This study considered technology commercialization as a sort of external R&D of the licensee firm. Then, this study analyzed industrial characteristics of technology commercialization and interactions between internal R&D and technology commercialization from the licensee's viewpoint. Data from NTIS (National science and Technology Information Service) and KED (Korea Enterprise Database) were matched. 7,645 technology commercializations from 1,980 firms were extracted. Afterward, OLS and quantile regression were applied to the extracted data. The impact of technology commercialization on firm growth was concentrated to few high-tech and medium high-tech firms. Technology commercialization was effective in the growth in a year while internal R&D was effective in the growth in two years. The firm size was insiginificant variable. In analysis of 4 selected industries (automobile, electronics, semiconductor, chemistry), the impact was skewed among industries. Though the importance of technology commercialization is widely acknowledged, quantitative analyses like this study are uncommon. Therefore, this study can be useful for the tailored industry solutions for technology commercialization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3210-3219
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• 2015

This study attempts to search for potential users of patents developed by public research institutes, emphasizing the importance of identifying potential users for successful technology marketing. On the basis of the theoretical argument that technological development show path-dependence, we analyzed patent citation network of a technology developed by a Korean public research institute to achieve the purpose of this research. The result shows that the potential users identified from our method are different from the institute's initial expectation. Therefore, we argue that the method using patent citation network is useful and effective for public research institutes' technology marketing. Lastly we suggest a new framework for technology marketing process in public research institutes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.685-690
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• 2008

In numerically evaluating the thermal performance of the heat exchanger, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be directly used without modelling. In this study the applicability of neural networks in modelling superheated water vapor was examined. The multi-layer neural networks consist of an input layer with 2 nodes, two hidden layers with 15 and 25 nodes respectively and an output layer with 3 nodes. Quadratic spline interpolation was also applied for comparison. Neural networks model revealed smaller percentage error compared with spline interpolation. From this result, it is confirmed that the neural networks could be a powerful method in modelling the superheated water vapor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.20-29
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• 2021

In the Industry 4.0 era, artificial intelligence has attracted considerable interest for learning mass data to improve the accuracy of forecasting and classification. On the other hand, the current method of detecting anomalies relies on traditional statistical methods for a limited amount of data, making it difficult to detect accurate anomalies. Therefore, this paper proposes an artificial intelligence-based anomaly detection methodology to improve the prediction accuracy and identify new data patterns. In particular, data were collected and analyzed from the point of view that sensor data collected at vehicle idle could be used to detect abnormalities. To this end, a sensor was designed to determine the appropriate time length of the data entered into the forecast model, compare the results of idling data with the overall driving data utilization, and make optimal predictions through a combination of various sensor data. In addition, the predictive accuracy of artificial intelligence techniques was presented by comparing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the predictive methodologies. According to the analysis, using idle data, using 1.5 times of the data for the idling periods, and using CNN over LSTM showed better prediction results.