• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.107-116
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• 2010

The vehicle travel time between locations in a downtown is greatly influenced by both complex road conditions and traffic situation that changes real time according to various external variables. The customer's demands also stochastically change by time period. Most vehicle routing problems suggest a vehicle route considering travel distance, average vehicle speed, and deterministic demand; however, they do not consider the dynamic external environment, including items such as traffic conditions and stochastic demand. A realistic vehicle routing problem which considers traffic (smooth, delaying, and stagnating) and stochastic demands is suggested in this study. A mathematical programming model and hybrid genetic algorithm are suggested to minimize the total travel time. By comparing the results considering traffic and stochastic demands, the suggested algorithm gives a better solution than existing algorithms.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.531-542
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• 2018

Building energy demands have highly risen in modern society; thus, It is necessary to reduce building energy demands especially commercial buildings adopting a curtain wall architecture. Curtain wall architectures have a high ratio of windows which is a vulnerable in heat insulations as cladding. In order to complement insulation performance of windows in these buildings, there are various methods adopted often such as installing blinds, wing wall and films. There are two suggestions of this paper. 1) WWR (Window-to-Wall Ratio) makes a impaction of energy demands in buildings. 2) Another one is an efficiency of blind systems which are installed in buildings in order to reduce cooling demands. It is also critical to make fundamental model for low-energy building construction by processing a lot of simulation As a result by this study, 1) an external blind system is more useful for reducing cooling energy demands rather than an internal blind system. 2) Buildings which have a large window require more amount of cooling demands. In case of WWR 45%, it needs more cooling energy rather than WWR 15% model's 3) Adopting blind system would reduce energy demands. WWR 45% model with external blind systems reduces about 4% of cooling energy demands compared to same model without any blind systems.4) it is necessary to study an efficiency of blind systems combined with renewable energy and it will be possible to reduce more energy demand in building significantly.

• Journal of Korean Society of Forest Science
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• v.99 no.1
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• pp.36-46
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• 2010

The purpose of this research was to derive political suggestion to increase the demand for forest visit by analyzing the demand of forest visitors, focusing on the residents of Seoul and capital areas. The determinants of demand, which is the number of forest visit in a year, were analyzed by independent variables; six factors from factor analysis on selective attributes, demographic characteristics, and other variables related with the general matters when visiting a forest. As a result, among the independent variables, selective attribute (tourism resource factor), gender (male), and residency (Seoul) were found out to have positive(+) effect on demand for forest visit. However, other selective attribute (external factor of forestry), occupation (white-collar employee), and level of education (over college graduate) were found out to have negative(-) effect on demand for forest visit. Based on these results, implications for the expansion of demand for forest visits were derived.

• Journal of IKEEE
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• v.23 no.1
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• pp.127-133
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• 2019

Electric power demand forecasting is one of the important research areas for future smart grid introduction. However, It is difficult to predict because it is affected by many external factors. Traditional methods of forecasting power demand have been limited in making accurate prediction because they use raw power data. In this paper, a probability-based CRBM is proposed to solve the problem of electric power demand prediction using raw power data. The stochastic model is suitable to capture the probabilistic characteristics of electric power data. In order to compare the mid-term power demand forecasting performance of the proposed model, we compared the performance with Recurrent Neural Network(RNN). Performance comparison using electric power data provided by the University of Massachusetts showed that the proposed algorithm results in better performance in mid-term energy demand forecasting.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.79-85
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• 2009

In this study, the effects of psychosocial stress (box color and precision demand) on muscle activity were evaluated in laboratory setting. Eight subjects performed sagittally symmetric lifting tasks. Box color (yellow, black), precision demand (yes, no), and box weight (5%MVC, 10%MVC, 15 %MVC) were varied and surface EMG signals from seven muscles(medial deltoid right, biceps brachii right, lateral triceps right, latissimus dorsi right, erector spinae right, external oblique right, internal oblique right) were recorded. EMG signals were band-pass filtered($10{\sim}400\;Hz$), rectified, RMS smoothed and normalized (NEMG). Analysis of variance tests were conducted on the total NEMG (TNEMG: the sum of the seven muscles' NEMGs) and on the individual muscle's NEMGs. Box color had no effect on the TNEMG and on the seven muscles activities(p>0.05). When precision demand was required at the end point of lifts, the mean NEMG showed higher values than no precision demand conditions: TNEMG (14% increase) and medial deltoid(40% increase), biceps brachii(10% increase), lateral triceps(26% increase), latissimus dorsi(25% increase) muscles. Those increases showed more conspicuous as the box weight increased in the muscles of medial deltoid, lateral triceps, and latissimus dorsi.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.

• The Journal of Bigdata
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• v.5 no.2
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• pp.111-120
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• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.

• The Journal of Information Technology
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• v.4 no.1
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• pp.97-108
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• 2001

This thesis is about the design and implementation of the system for controlling Avatar, user's alter ego in a simulated world using the EAI(External Authoring Interface) technology to be able to control VRML(Virtual Reality Modeling Language). In this thesis, user's Avatar described in VRML language embodied interactions to move and show an expression by JAVA according to a user's demand. In the future, this would be able to develop into a research to try to embody and construct a simulated society based on web for the purpose of various integration of society such as cyber government, lecture, trial performance, and auction.

• Journal of Distribution Research
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• v.1 no.2
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• pp.141-172
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• 1996

This study is to investigate global logistics strategies of Korean electronics companies. in terms of service parts. According to the survey, Korean electronics companies were pursuing multi-level global logistics network such as global, continental, national, regional and service center echelon for improving the efficiency of service parts global logistics. Especially there was a tendency of developing new continental distribution centers. And the companies were exploiting efficiency through inventory control by multi-level echelon, demand forecasting by the product life cycle and supply and service lead time management. But there were some insufficient factors for the efficiency of global logistics operation at the construction of worldwide real time logistics information system and pursuit of the efficiency on the whole network including subcontractors. For the future competitive advantage of the Korean electronics companies, the following are suggested: 1) the establishment of arranged logistics channel adjusting each company's global strategy, 2) the construction of worldwide real time logistics information system, 3) the reengineering of all logistics procedures such as order processing, shipping, inventory control, etc., 4) the enhancement of the ratio of the supply from the external companies and the internal manufacturing subsidiaries at each continent, 5) and the pursuit of operational internalization of external subcontractors.

• Journal of the Korean housing association
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• v.11 no.3
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• pp.87-98
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• 2000

This study derives problems of external space utilization site from on-site observation and questionnaire survey in order to suggest solutions for the problems. The main results are follows. First, fences as visual boundaries of apartment site play some negative roles - separation of space and heterogeneity of circumstance. This study suggests green fences to cure this problem. Second, residents want to change space use - ground to be used as green space or space for relaxation in stead of parking lots, elevator hall as social space, and underground as bike parks or health centers. Third, rooftop space, used as empty space or machine storage space, should be designed to be utilized as relaxation space by making easy to enter and exit.