• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.343-347
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• 2004

Landuse information is used to plan land use, urban and environmental management as base data. And, demand for landuse information is rising due to ecological consideration in urban area. But existing method to extract landuse information from aerial photographs or satellite images is difficulte to describe sufficient urban landuses. Also landuse information need to be linked with statistical data because statistical data is used to make decision for urban planning and management with landuse. Therefore this study aims to examine the landuse classification method using statistical unit data and 1:1,000 digital topographic data. for the purpose, the method was applied to a part of metropolitan Seoul. The results of study shows that total accuracy is 95%. For the future, the method will be effectively applicable for the city maintenance.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.101-105
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• 1998

A large system predictor, which can perform prediction of sales trend in a huge number of distribution centers, is presented using neural predictive model. There are 20,000 number of distribution centers, and each distribution center need to forecast future demand in order to establish a reasonable inventory policy. Therefore, the number of forecasting models corresponds to the number of distribution centers, which is not possible to estimate that kind of huge number of accurate models in ERP (Enterprise Resource Planning)module. Multilayer neural net as universal approximation is employed for fitting the prediction model. In order to improve prediction accuracy, a sequential simulation procedure is performed to get appropriate network structure and also to improve forecasting accuracy. The proposed simulation procedure includes neural structure identification and virtual predictive model generation. The predictive model generation consists of generating virtual signals and estimating predictive model. The virtual predictive model plays a key role in tuning the real model by absorbing the real model errors. The complement approach, based on real and virtual model, could forecast the future demands of various distribution centers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.429-430
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• 2018

The introduction of mobile devices increased the need to apply limitations such as mobile devices' memory, speed, energy, and bandwidth on the designs of searching images. There is a demand to reduce such limitations on searching images on the mobile phone. Hence, this paper proposes a design that adds tags on pictures to manage the images in mobile environment, allowing efficient searches and deletion of duplicate files based on the similarities of the images. The proposed method does not compromise its efficiency by increasing costs; it also reduces the volume of data needed for mobile devices.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1150-1152
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• 1998

Recently, our electric industry confronts a structural change and high competiveness environment in the course of deregulation. Rapid growth in electricity demand, financial need for new power plant construction, and envionmental problems have led to search for more efficient energy production and energy conservation techmologies. Especially, residential and commercial buildings consumes 40% of electricity demands and building energies are increasing more and more in Korea. The purpose of this paper is to analyze the electricity use of commercial buildings by end-use. Also, we will use it as a basic informations of DSM potential evaluation and evaluation process based on different approach by sector and type of potential.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.83-90
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• 1999

Centralized safety stock in a periodic replenishment system which consists of one central warehouse and m regional warehouse can reduce backorders allocation the centralized safety stocks to regional warehouse in a certain instant of each replenishment cycle. If the central warehouse can not monitoring inventories in the regional warehouse, then we have to predetermine the instant of allocation according to demand distribution and this instant must be same for all different replenishment cycle. However, transition of inventory level in each cycle need not to be same, and therefore different instant of the allocation may results reduced shortage compare to the predetermined instant of allocation. In this research, we construct a dynamic model based on the assumption of monitoring inventories inventories in the regional warehouse everyday, and develop an algorithm minimize shortage in each replenishment cycle using dynamic programming approach.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.98-103
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• 2021

Recently, as the need for food resources has increased both domestically and internationally, support for the agricultural sector for stable food supply and demand is expanding in Korea. However, according to recent media articles, the biggest problem in rural communities is the unstable profit structure. In addition, in order to confirm the profit structure, profit forecast data must be clearly prepared, but there is a lack of auxiliary data for farmers or future returnees to predict farm income. Therefore, in this paper we analyzed data over the past 15 years through time series analysis and proposes an artificial intelligence farm income prediction algorithm that can predict farm household income in the future. If the proposed algorithm is used, it is expected that it can be used as auxiliary data to predict farm profits.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.145-150
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• 2019

Due to the development of science and technology and the emergence of new industries, the environmental change of the digital contents industry is rapidly progressing. The scope of technological development in the digital contents industry is affecting not only the entertainment industry but also various industries. Recently, with the development of digital convergence using realistic content, games, video, and VR have provided new opportunities for the growth of the content industry. The researcher determined that a new education system would need to be changed as the digital contents industry developed. For this purpose, an AHP questionnaire was conducted for experts with a high basic understanding of the education platform based on previous studies. We proposed a platform model for human resource development as an education system that meets the demand of digital contents industry. The education system for nurturing talents needed by future society should include elements that can interest the learning of users. The platform should not be approached from a system point of view, but should be developed from the content and user's point of view, considering the platform's original purpose.

• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.31-57
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• 2019

Myanmar's current power situation remains severely constrained despite being richly endowed in primary energy sources. With low levels of electrification, the demand for power is not adequately met. Cooperation in energy has been a major focus of future initiative for all developed and developing nations. If we want to solve climate change, and change our energy infrastructure, we need to be innovative and entrepreneurial in energy generation. This paper will help us in examining Bayesian MCMC Analysis for the parameters estimation among the arrival rates of disaster occurrences, firm's expected income-based electricity tariffs, and estimated R&D investment expenses in new energy industry. Focusing on Japan's electric power business, we would like to search the potential for innovative initiatives in new technological energy industry for the regional development and ecological sustainability in Myanmar.

• Annals of Clinical Neurophysiology
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• v.23 no.1
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• pp.35-45
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• 2021

The utility and accuracy of intraoperative neurophysiological monitoring (IONM) has evolved greatly following the recent development of new devices for neurophysiological testing and advances in anesthesiology. Until recently, the need for IONM services has been limited to large academic hospitals, but the demand for neurophysiologists with expertise in IONM has grown rapidly across diverse types of hospital. The primary goal of the Korean Society of Intraoperative Neurophysiological Monitoring (KSION) is to promote the development of IONM research groups and to contribute to the improvement of fellowship among members and human health through academic projects. These guidelines are based on extensive literature reviews, recruitment of expert opinions, and consensus among KSION board members. This version of the guidelines was fully approved by the KSION, Korean Association of EMG Electrodiagnostic Medicine, the Korean Society of Clinical Neurophysiology, the Korean Academy of Rehabilitation Medicine, and the Korean Neurological Association.

• The Journal of Information Systems
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• v.30 no.4
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• pp.71-94
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• 2021

Purpose The purpose of this study is to verify impacts of factors, representing Push-Pull-Mooring(PPM) on switch intention to OTT(Over-The-Top) service in demand for content and to find relationship between factors through empirical analysis. Design/methodology/approach This study designed a research model by deriving factors affecting the intention to switch on OTT service based on the Push-Pull-Mooring framework and researches on OTT service. To test the hypothesis, a total of 357 responses were collected from individuals with experience in using OTT service and analyzed using SPSS26 and SmartPLS3.0. Findings According to the empirical analysis result, this study confirmed that the push, pull, and mooring factors proposed in this study had a significant effect on switching intention on OTT service. In addition, this study confirmed that both low switching cost and need for variety had a significant effect except for hypothesis H8.