• 자동차안전학회지
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• 제11권3호
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.250-261
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• 2004

A novel method for ab initio prediction of protein tertiary structures, PROFESY (PROFile Enumerating SYstem), is introduced. This method utilizes secondary structure prediction information and fragment assembly. The secondary structure prediction of proteins is performed with the PREDICT method which uses PSI-BLAST to generate profiles and a distance measure in the pattern space. In order to predict the tertiary structure of a protein sequence, we assemble fragments in the fragment library constructed as a byproduct of PREDICT. The tertiary structure is obtained by minimizing the potential energy using the conformational space annealing method which enables one to sample diverse low lying minima of the energy function. We apply PROFESY for prediction of some proteins with known structures, which shows good performances. We also participated in CASP5 and applied PROFESY to new fold targets for blind predictions. The results were quite promising, despite the fact that PROFESY was in its early stage of development. In particular, the PROFESY result is the best for the hardest target T0161.

• Journal of electromagnetic engineering and science
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• 제11권3호
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• pp.220-226
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• 2011

We have proposed a new method to accurately predict the resonance of Fabry-Perot Cavity (FPC) antennas enclosed with conducting side walls. When lateral directions of an FPC antenna are not blocked with metallic walls, the conventional technique is accurate enough to predict the resonance of the FPC antenna. However, when the FPC antenna has side walls, especially for case with only a short distance between the walls, the conventional prediction method yields an inaccurate result, inevitably requiring a tedious, time-consuming tuning process to determine the correct resonant height to provide the maximum antenna gain in a target frequency band using three-dimensional full-wave computer simulations. To solve that problem, we have proposed a new resonance prediction method to provide a more accurate resonant height calculation of FPC antennas by using the well-known resonance behavior of a rectangular resonant cavity. For a more physically insightful explanation of the new prediction formula, we have reinvestigated our proposal using a wave propagation characteristic in a hollow rectangular waveguide, which clearly confirms our approach. By applying the proposed technique to an FPC antenna covered with a partially reflecting superstrate consisting of continuously tapered meander loops, we have proved that our method is very accurate and readily applicable to various types of FPC antennas with lateral walls. Experimental result confirms the validness of our approach.

• 신재생에너지
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• 제18권1호
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• pp.17-28
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• 2022

This paper presents an effective Markov transition matrix (EMTM), which will be used to calculate the wind speed at the target site in a wind farm to accurately predict wind energy production. The existing MTS prediction method using a Markov transition matrix (MTM) exhibits a limitation where significant prediction variations are observed owing to random selection errors and its bin width. The proposed method selects the effective states of the MTM and refines its bin width to reduce the error of random selection during a gap filling procedure in MTS. The EMTM reduces the level of variation in the repeated prediction of wind speed by using the coefficient of variations and range of variations. In a case study, MTS exhibited better performance than other MCP models when EMTM was applied to estimate a one-day wind speed, by using mean relative and root mean square errors.

• International Journal of Advanced Culture Technology
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• 제11권2호
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• pp.381-388
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• 2023

Small-scale environmental impact assessments have limitations in terms of survey duration and evaluation resources, which can hinder the assessment and analysis of the current situation. In this study, we propose the use of drone technology during the environmental impact assessment process to supplement these limitations in the current situation analysis. Drone photography can provide rapid and accurate high-resolution images, allowing for the collection of various information about the target area. This information can include different types of data such as terrain, vegetation, landscape, and real-time 3D spatial information, which can be collected and processed using GIS software to understand and analyze the environmental conditions. In this study, we confirmed that terrain and vegetation analysis and prediction of the target area using drone photography and GIS analysis software is possible, providing useful information for environmental impact assessments.

• 한국식품영양학회지
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• 제16권3호
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• pp.180-186
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• 2003

가열살균 처리시의 온도값을 이용하여 다양한 미생물들의 가열살균 효과를 D값, z값 등의 미생물 내열성 특성치와 kinetic 모델 및 수식을 이용하여 살균치 계산을 컴퓨터를 이용하여 수행함으로써 target 미생물의 살균정도를 예측하고자, Excel과 Visual Basic을 연동하여 작성된 시스템으로 Excel을 기본으로 사용한 프로그램을 개발하였다. 가열살균 target 미생물을 선택하고자 야채식품을 기반으로 하는 식품에서의 미생물을 검토하여, 내열성인 가장 큰 호기성 포자형성균인 Bacillus spp. 계통이 산을 형성하여 맛 등의 품질을 저하시켜 변패를 유발하며, 위생적인 면에서 포자수를 줄이거나 사멸할 필요가 있어서 선택하였다. 병원성 균 중에서 $D_{121.1}$이 0.0065분, z값이 7.8$^{\circ}C$인 Bacillus cereus와 부패현상 관련 균 중에서 $D_{121.1}$이 0.5분, z값이 12$^{\circ}C$인 Bacillus subtilis를 대상으로 해서 개발되었으며, 필요시에는 D값과 z값을 직접 대입하므로서, 여러 가지 미생물에 대해서도 적용이 가능하게 하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2371-2375
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• 2013

Breast cancer is one of the most common malignancies in women around the world. Among the various hormonal types of breast cancer, those that are estrogen receptor (ER) positive account for the majority. Among the estrogen related receptors, estrogen related receptor ${\alpha}$ is known to have a potential role in breast cancer and is one of the therapeutic target. Hence, prediction of novel ligands interact with estrogen related receptor alpha is therapeutically important. The present study, aims at prediction and analysis of ligands from the KEGG COMPOUND database (containing 10,739 entries) able to interact against estrogen receptor alpha using a similarity search and molecular docking approach.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권2호
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• pp.251-254
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• 2016

An energy-efficient object matching accelerator is proposed for mobile object recognition based on matching prediction scheme. Conventionally, vocabulary tree has been used to save the external memory bandwidth in object matching process but involved massive internal memory transactions to examine each object in a database. In this paper, a novel object matching accelerator is proposed based on matching predictions to reduce unnecessary internal memory transactions by mitigating non-target object examinations, thereby improving the energy-efficiency. Experimental results show a 26% reduction in power-delay product compared to the prior art.

• 전기학회논문지
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• 제56권9호
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• pp.1556-1560
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• 2007

Energized power transformers in substations make unwelcome noises which propagate to nearby residential areas. As the excessive noise level become a target of public grievance than ever, utilities are seeking solutions to it. This paper introduce a power transformer noise prediction program which can give utilities effective solutions. Once a noise source is given, the program calculates the propagated noise level at certain points. The estimated result is rendered as noise contour map. To validate the accuracy of the program, the predicted noises are compared to measured one in real substations and proven to be acceptable within a margin of 5 percent.

• 대한산업공학회지
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• 제31권4호
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• pp.334-340
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• 2005

A mouse is an important input device that is used in most of all computer works. A mouse control time prediction model was proposed in this study. Especially, the model described the time of mouse control that made a cursor to move within path constraints. The model was developed by a laboratory experiment. Cursor movement times were measured in 36 task conditions; 3 levels of path length, 3 levels of path width and 4 levels of target's width. 12 subjects participated in all conditions. The time of cursor movement with path constraints could be better explained by the combination of Fitts' law with steering law($r^2=0.947$) than by the other models; Fitts' law($r^2=0.740$), Steering law($r^2=0.633$) and Crossman's model($r^2=0.897$). The proposed model is expected to be used in menu design or computer game design.