• Economic and Environmental Geology
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• v.52 no.3
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• pp.243-250
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• 2019

The purpose of this study is to pro-actively respond to changes in government R&D policy and start to supplement the limitations of previous KIGAM R&D planning process. We looked out through the existing literature for a variety of R&D planning process, and analyzed the R&D planning process characteristics of each institution through the interview. As a result, we can be derived conclusions and implications from three sides, environmental analysis, demand excavation methods, R&D project configuration and selection method. In the case of environmental analysis and the overall need to enhance the skills and mega trend analysis by market trend analysis. And in the demand side, the institute need to establish challenging and specific R&D goals. In addition, in case of configuration and selection of R&D projects we derived several implications, such as convergence, SME support, resource analysis, selection of long-term project.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.3-36
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• 2015

As of end of 2014, the population engaging in aviation activities for leisure has reached approximately 13 million, where approximately 356 cases involve a general aircraft, 200 cases involve light aircraft, and 636 cases involve an ULM. The industry for leisure has become a very promising industry in line with rapidly rising living standards which are expected to further increase in the future. The demand for such services is expected to increase over time. The purpose of this paper is to review the development and site selection of airfields in anticipation of these developments in the industry. While the government also has experience in the review of airfield location and candidate sites, it is not the government that carries out the actual construction. As such, the feasibility of the site needs to be verified in terms of actual construction. This study identified factors for Site Selection of factors through a review of related documents and existing research reports. A questionnaire was also used to collect the views of experts in the field, which was then analyzed. The Research model was confirmed in the layered form for an AHP analysis. The factors for Site Selection were identified as the technical / operational factors and economic / political elements for a two-stage configuration. The third step consisted of technical and operational elements. The final step is was constructed a total of 11 elements (weather, surface conditions, obstacle limitation surface, airspace conditions, operating procedures, noise problems, environmental issues, availability of facilities, construction and investment costs, contribution to the local economy, accessibility, demand / the proximity of demand). The surveys are conducted for more than 10 General and light aircraft pilots, professionals, and instructor. The analysis results showed a higher level in the technical / operating elements (73.2%) in the first step, while the next step sawa higher level of the operational elements (30.9%) than the other. The factors for Site Selection were any particular elements did not appear high, the weather conditions (17.5%), noise problems (19.8%), the proximity of demand (6%), accessibility (5.7%), environmental issues (11.1%), availability of facilities (8%), airspace conditions (7.9%), obstacle limitation surface (12%), construction and investment costs (4.2%) and to operating procedures (4.9%), contribution to the local economy (3.8%).

• Journal of Energy Engineering
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• v.28 no.4
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• pp.82-93
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• 2019

In this study, a new model is proposed to improve the problem of the decline of predict rate of heat demand on a particular date, such as a public holiday for the conventional heat demand forecasting system. The proposed model was the Four Season Mixed Heat Demand Prediction Neural Network Model, which showed an increase in the forecast rate of heat demand, especially for each type of forecast date (weekday/weekend/holiday). The proposed model was selected through the following process. A model with an even error for each type of forecast date in a particular season is selected to form the entire forecast model. To avoid shortening learning time and excessive learning, after each of the four different models that were structurally simplified were learning and a model that showed optimal prediction error was selected through various combinations. The output of the model is the hourly 24-hour heat demand at the forecast date and the total is the daily total heat demand. These forecasts enable efficient heat supply planning and allow the selection and utilization of output values according to their purpose. For daily heat demand forecasts for the proposed model, the overall MAPE improved from 5.3~6.1% for individual models to 5.2% and the forecast for holiday heat demand greatly improved from 4.9~7.9% to 2.9%. The data in this study utilized 34 months of heat demand data from a specific apartment complex provided by the Korea District Heating Corp. (January 2015 to October 2017).

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.57-64
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• 2002

Since most of the current route selection algorithms use the shortest path algorithm, network resources can not be efficiently used also traffics be concentrated on specific paths resulting in congestgion. In this paper we propose the statistical route selections(SRS) algorithm which adopts a statistical mechanism to utilize the network resource efficiently and to avoid congestion. The SRS algorithm handles requests on demand and chooses a path that meets the requested bandwidth. With the advent of the MPLS it becomes possible to establish an explicit LSP which can be used for traffic load balancing. The SRS algorithm finds a set of link utilizations for route selection, computes link weights using statistical mechanism and finds the shortest path from the weights. Our statistical mechanism computes the mean and the variance of link utilizations and selects a route such that it can reduce the variance and the number of congested links and increase the utilization of network resources. Throughout the simulation, we show that the SRS algorithm performs better than other route selection algorithms on several metrics like the number of connection setup failures and the number of congested links.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1269-1276
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• 2023

Crop estimation is essential for the multinational meal and powerful demand due to its numerous aspects like soil, rain, climate, atmosphere, and their relations. The consequence of climate shift impacts the farming yield products. We operate the dataset with temperature, rainfall, humidity, etc. The current research focuses on feature selection with multifarious classifiers to assist farmers and agriculturalists. The crop yield estimation utilizing the feature selection approach is 96% accuracy. Feature selection affects a machine learning model's performance. Additionally, the performance of the current graph classifier accepts 81.5%. Eventually, the random forest regressor without feature selections owns 78% accuracy and the decision tree regressor without feature selections retains 67% accuracy. Our research merit is to reveal the experimental results of with and without feature selection significance for the proposed ten algorithms. These findings support learners and students in choosing the appropriate models for crop classification studies.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.133-141
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• 1996

In this paper, a VOD(Video -on-Demand) system is implemented using LAN(Local Area Network). The use of LAN causes the time-delay problem due to its narrow channel limitation, as a result, the service using the conventional LAN used not to be popular. In this paper, to solve these problems, we develop the modified topology, the selection methodology of the network equipment, and the dedicated(improved) protocol. Consequently, we can serve at most 3 or 4 clients at the same time, and we conclude it is necessary to optimize the network buffer size depending on the size of video data.

• Korean Management Science Review
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• v.23 no.3
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• pp.1-11
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• 2006

This study investigates empirically on the business analysis of fixed mobile convergence telecommunication service. As for the stage of empirical analysis, the process was carried out in the order elaboration of a test model, selection of sample, empirical analysis and interpretation of result. We report our Preliminary results on the fixed mobile convergence telecommunication service demand pattern forecasting by Bass model. The results show that the fixed mobile convergence telecommunication service may sustain profitability over the next ten years in the market. In conclusion, the practical implication of the result attained by this study is that in order to create a fixed mobile convergence in the korean business world, practical tools such as WiBro service is no less important than fixed service and Mobile service, and that users may be rightfully encouraged to adopt WiBro service.

• IEMEK Journal of Embedded Systems and Applications
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• v.1 no.1
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• pp.8-13
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• 2006

In mobile ad hoc networks, most of on demand routing protocols such as DSR and AODV do not deal with traffic load during the route discovery procedure. To achieve load balancing in networks, many protocols have been proposed. However, existing load balancing schemes do not consider the remaining available buffer size of the interface queue, which still results in buffer overflows by congestion in a certain node which has the least available buffer size in the route. To solve this problem, we propose a load balancing protocol called Dynamic Congestion Aware Routing Protocol (DCAR) which monitors the remaining buffer length of all nodes in routes and excludes a certain congested node during the route discovery procedure. We also propose two buffer threshold values to select an optimal route selection metric between the traffic load and the minimum hop count. Through simulation study, we compare DCAR with other on demand routing protocols and show that the proposed protocol is more efficient when a network is heavily loaded.

• The Journal of the Korean dental association
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• v.56 no.9
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• pp.512-520
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• 2018

As the demand for natural and beautiful smiles increases, the demand for anterior aesthetic treatment is increasing. Orthodontic treatment is often necessary for esthetic, healthy and natural treatment outcome. Particularly, in the case of middle-aged patients, minor tooth movement limited to anterior teeth is more effective than comprehensive orthodontic treatment which requires a long-term treatment period. Clinician who is in charge of aesthetic dentistry should have the ability to select a case that can be treated with partial orthodontic treatment and to determine the most effective treatment method. This article provides decision flowchart for case selection and choosing the best treatment modality for anterior teeth alignment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1608-1614
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• 2014

Power demand forecasting is an important factor of the peak management. This paper deals with the 15 minutes ahead load forecasting problem in a DC urban railway system. Since supplied power lines to trains are connected with parallel, the load characteristics are too complex and highly non-linear. The main idea of the proposed method for the 15 minutes ahead prediction is to use the daily load similarity accounting for the load nonlinearity. An Euclidean norm with weighted factors including loads of the neighbor substation is used for the similar load selection. The prediction value is determinated by the sum of the similar load and the correction value. The correction has applied the neural network model. The feasibility of the proposed method is exemplified through some simulations applied to the actual load data of Incheon subway system.