• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• Genomics & Informatics
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• 제11권4호
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• pp.200-210
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• 2013

Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

• 한국군사과학기술학회지
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• 제19권3호
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• pp.319-329
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• 2016

Current research trends of prediction of possible structures, synthesis and explosive characteristics of polynitrogen molecules(PNs) are reviewed. Theoretically PNs are composed only of nitrogen atoms, in which N-N bonds are either single or double bonds, and thus when these molecules decompose, release of enormous energy is accompanied. From the middle of 20th century energetic material chemists have been seeking possible structures and the methods of synthesis of these new materials. As a results, from $N_4$ to $N_{60}$ together with their ions are predicted, and experimental chemists have been trying to synthesize these materials with a few success, including the famous ${N_5}^+$ ion in 1999. Although experimental successes are very rare beyond $N_5$ until today, the author believes that renovative ideas together with sincere efforts will bring someday next generation of high energy materials such as nitrogen fullerene($N_{60}$) in reality.

• 한국정밀공학회지
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• 제21권6호
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• pp.43-51
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• 2004

A method for form error prediction in side wall machining with a flat end mill is suggested. Form error is predicted directly from the tool deflection without surface generation by cutting edge locus with time simulation. Developed model can predict the surface form error about three hundred times faster than the previous method. Cutting forces and tool deflection are calculated considering tool geometry, tool setting error and machine tool stiffness. The characteristics and the difference of generated surface shape in up milling and down milling are discussed. The usefulness of the presented method is verified from a set of experiments under various cutting conditions generally used in die and mold manufacturing. This study contributes to real time surface shape estimation and cutting process planning for the improvement of form accuracy.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.555-564
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• 2001

Wheel-rail noise is normally classified into three catagories ： rolling, squeal and impact noise. In this paper, rolling noise caused by the irregularity between a wheel and rail is analysed as follows： The irregularity between the wheel and rail is assumed as combination of sinusoidal profiles. Wheel-rail contact stiffness is linearized by using Hertzian contact theory, and then contact force between the wheel and rail is calculated. Vibration of the rail and wheel is calculated theoretically by receptance method or FEM depending on the geometry of wheel or rail for the frequency range of 100-5000Hz, important for noise generation. The radiation caused by those vibration is computed by BEM. To verify this analysis tools, rolling noise is calculated by preceding analysis steps using typical roughness data and it is compared with experimental rolling noise data. This analysis tools show reasonable results and used for the prediction of KTX rolling noise.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.512-517
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• 2000

The road traffic noise becomes aggravated due to the rapid increase of vehicles. It has a great effect on the dwelling environment. Therefore we investigate the characteristics and sources of the road traffic noise through grasping the status of the road traffic noise. This report is concerned with the description of the various factors affecting the generation and propagation of outdoor traffic noise. It is particularly concerned with the mathematical interpretation of these processes and the resulting development of prediction techniques which are now broadly used for both the environment impact assessment of road traffic noise and the planning and design of roads and adjoining land use.

• International Journal of Naval Architecture and Ocean Engineering
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• 제1권1호
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• pp.29-38
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• 2009

A ship's screw-propeller produces thrust by rotation and, at the same time, generates rotational flow behind the propeller. This rotational flow has no contribution to the generation of thrust, but instead produces energy loss. By recovering part of the lost energy in the rotational flow, therefore, it is possible to improve the propulsion efficiency. The contra-rotating propeller (CRP) system is the representing example of such devices. Unfortunately, however, neither a design method nor a full-scale performance prediction procedure for the CRP system has been well established yet. The authors have long performed studies on the CRP system, and some of the results from the authors' studies shall be presented and discussed.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.287-296
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• 2022

Today, air pollution is becoming a severe issue worldwide and various policies are being implemented to solve environmental pollution. In major cities, public bicycles are installed and operated to reduce pollution and solve transportation problems, and operational information is collected in real time. However, research using public bicycle operation information data has not been processed. This study uses the daily weather data of Korea Meteorological Agency and real-time air pollution data of Korea Environment Corporation to predict the amount of daily rental bicycles. Cross- validation, principal component analysis and multiple regression analysis were used to determine the independent variables of the predictive model. Then, the study selected the elements that satisfy the significance level, constructed a model, predicted the amount of daily rental bicycles, and measured the accuracy.

• Journal of Korea Artificial Intelligence Association
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• 제1권2호
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• pp.15-20
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• 2023

This study aims to enhance the accuracy of fine dust predictions by analyzing various factors within the local environment, in addition to atmospheric conditions. In the atmospheric environment, meteorological and air pollution data were utilized, and additional factors contributing to fine dust generation within the region, such as traffic volume and electricity transaction data, were sequentially incorporated for analysis. XGBoost, Random Forest, and ANN (Artificial Neural Network) were employed for the analysis. As variables were added, all algorithms demonstrated improved performance. Particularly noteworthy was the Artificial Neural Network, which, when using atmospheric conditions as a variable, resulted in an MAE of 6.25. Upon the addition of traffic volume, the MAE decreased to 5.49, and further inclusion of power transaction data led to a notable improvement, resulting in an MAE of 4.61. This research provides valuable insights for proactive measures against air pollution by predicting future fine dust levels.

• 방송공학회논문지
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• 제23권3호
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• pp.431-436
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• 2018

본 논문에서는 aliasing artifact 없이 영상 품질을 유지하고, 썸네일 생성에 필요한 계산 복잡도를 줄이는 알고리듬을 제안한다. 제안하는 알고리듬은 고속으로 복호화를 진행하기 위해서 TU(Transform Unit)에서는 $4{\times}4$크기마다 경계부분만을 부분 복호화를 수행하고, PU(Prediction Unit)에서는 TU경계부분만을 부분 복호화 한다. 그리고 화면내 예측 모드 방향에 따른 가중치 값을 구하고, 그 값을 이용해서 실제 썸네일 화소를 예측한다. 제안하는 방법은 기존 방법들과 썸네일 추출시간을 비슷하게 유지하면서 썸네일의 품질을 향상시킨다.