• 한국식품영양학회지
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• 제37권4호
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• pp.197-210
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• 2024

This study aims to develop a deep learning model to monitor rice serving amounts in institutional foodservice, enhancing personalized nutrition management. The goal is to identify the best convolutional neural network (CNN) for detecting rice quantities on serving trays, addressing balanced dietary intake challenges. Both a vanilla CNN and 12 pre-trained CNNs were tested, using features extracted from images of varying rice quantities on white trays. Configurations included optimizers, image generation, dropout, feature extraction, and fine-tuning, with top-1 validation accuracy as the evaluation metric. The vanilla CNN achieved 60% top-1 validation accuracy, while pre-trained CNNs significantly improved performance, reaching up to 90% accuracy. MobileNetV2, suitable for mobile devices, achieved a minimum 76% accuracy. These results suggest the model can effectively monitor rice servings, with potential for improvement through ongoing data collection and training. This development represents a significant advancement in personalized nutrition management, with high validation accuracy indicating its potential utility in dietary management. Continuous improvement based on expanding datasets promises enhanced precision and reliability, contributing to better health outcomes.

• 한국산림과학회지
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• 제98권3호
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• pp.351-356
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• 2009

본 연구는 전통적인 empirical 생장모델에 환경 인자를 독립변수로 사용하여 이를 환경 인자에 대한 생장 모델의 변화를 분석하여 정도가 높은 생장 모형 구축 가능성 여부를 판단하였다. 이를 위하여 기본적으로 추정된 편백의 수고 및 직경 생장모델에 각 지역의 환경 인자인 평균 기온, 평균 강수량, 고도, 토양의 유기질 함유량을 독립 변수로 추가 하였다. 수고 생장 모델은 Gompertz 다형방정식에 점근 변수인 ${\alpha}$에 온도 고도 인자의 2독립 변수로 도입하여 모델의 정도를 향상 시킬 수 있었다. 직경 생장 모델 또한 Gompertz 다형방정식에 연평균 강수량과 해발고를 도입한 모델이 정도가 높은 것으로 나타났다. 환경 인자를 도입하기 전과 후의 모델의 정도 향상을 비교 했을 때 아주 뚜렷하게 모델의 향상은 나타나지 않았으나 일정 비율의 정도를 향상 시킬 수 있었다. 이는 생장 모델을 구축하기 위한 데이터 조사의 어려움 및 투자할 수 있는 예산을 감안하여 모델의 정도를 향상시키기 위하여 비교적 쉽게 구할 수 있는 환경 인자들의 이용 가능성이 많은 것으로 판단된다.

• Journal of Information Processing Systems
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• 제16권4호
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• pp.809-819
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• 2020

Gender prediction accuracy increases as convolutional neural network (CNN) architecture evolves. This paper compares voting and ensemble schemes to utilize the already trained five CNN models to further improve gender prediction accuracy. The majority voting usually requires odd-numbered models while the proposed softmax-based voting can utilize any number of models to improve accuracy. The ensemble of CNN models combined with one more fully-connected layer requires further tuning or training of the models combined. With experiments, it is observed that the voting or ensemble of CNN models leads to further improvement of gender prediction accuracy and that especially softmax-based voters always show better gender prediction accuracy than majority voters. Also, compared with softmax-based voters, ensemble models show a slightly better or similar accuracy with added training of the combined CNN models. Softmax-based voting can be a fast and efficient way to get better accuracy without further training since the selection of the top accuracy models among available CNN pre-trained models usually leads to similar accuracy to that of the corresponding ensemble models.

• 재활복지공학회논문지
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• 제10권3호
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• pp.221-228
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• 2016

본 논문에서는 EEG 신호 기반 기기 또는 소프트웨어를 사용하기 위해 사용자가 본인의 EEG 신호 정확도를 확인하고, 훈련을 통하여 자신의 EEG 신호 정확도를 향상시킬 수 있는 시뮬레이션 소프트웨어를 제안한다. 실험 데이터로는 풍경사진을 보며 편안한 상태에서 발생되는 신호와 수학문제를 풀며 집중 시에 발생되는 신호를 사용한다. 입력되는 EEG 신호는 독립 성분 분석(Independent Component Analysis, ICA)을 적용하여 잡음을 최소화하고 대역 통과 필터(Band Pass Filter)를 통하여 베타파(${\beta}$, 14-30Hz)만을 취득한다. 취득한 베타파 대역 데이터에서 제곱평균제곱근(Root Mean Square, RMS) 알고리즘을 통하여 특징 정보를 추출하고 지지 벡터 머신(Support Vector Machine, SVM)에 적용하여 분류한다. 분류된 결과는 사용자가 바로 확인할 수 있으며 훈련 전 피험자의 평균 정확도는 79.21%이었던 반면, 연속적인 훈련으로 최고 91.67%의 정확도를 보였다. 이처럼 본 논문에서 개발한 시뮬레이션 소프트웨어는 사용자가 직접 자신의 EEG 신호 정확도를 향상키기는 훈련을 통하여 정확도 향상이 가능하고, EEG 신호 기반으로 이루어진 BCI 시스템의 효율적인 사용을 기대할 수 있다.

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1093-1098
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• 2000

This paper presents an efficient algorithm for including the kinematic calibration data into the motion controller to improve the positioning accuracy of the manipulators. Rather than spending several iterations for finding the inverse solution of the calibrated kinematics, our approach requires only the nominal inverse solution and the calibrated forward kinematics for providing a better position command promptly. Thus, real-time application is guaranteed whenever the manipulators nominal inverse solution can be expressed in a closed form. Experimental results show that the line tracking performances can be remarkably improved by employing our algorithm.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.263-268
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• 2001

Two ways of improvement of the strut for the HCF was made in this paper. The strut for the existing HCF is a passive link, which results the posture of the HCF and related bones. The accuracy of the HCF depends on the accuracy of the strut length. A "digital gage" was proposed to increase the accuracy of the strut by presenting the measuring result as figures in manual mode operation. And a "motorized strut system" was designed for the automated HCF operation. A strut was equipped with a motor, "motorized strut" can be operated manually and automatically. In automatic mode, the HCF operating data is generated by the HCF schedule package in PC and is downloaded to the "motorized strut system" controller. By these two improvements, changes in orthopedic equipments like HCF and other Ilizarov fixators are expected.

• 기술사
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• 제22권3호
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• pp.5-13
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• 1989

A major problem of stopwatch time study is how to do for the accurate and consistent performance rating, which is one of the critical variables to determine the accuracy of work measurement and should be still dependent upon time observer's judgement. Therefore the time observer's ability for the performance rating is very important, and must be improved by correct training method and procedure. This paper developed a new benchmark and benchmark-observation method for the effective performance rating training of assembling and machining operations. The trainees' ability in the accuracy and consistency of the performance rating ,improved significantly after being trained by subject method. The percentage improvement in rating accuracy and consistency values was 34.7% and 49% respectively. In addition, benchmark-practice method for the performance rating training is not significant, so it is proofed that the skill of a certain operation is not important for the improvement of the rating ability.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.393-396
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• 1997

High-speed machining is one of the most effective technologies to improve productivity. Because of the high speed and high feed rate, high-speed machining can give great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut and feed rate are control factors. The effect of the control factors on machining accuracy is investigated using two-way factorial design.

• 한국전산유체공학회지
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• 제21권1호
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• pp.94-102
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• 2016

The present paper deals with accuracy improvement of a bleed boundary condition model used to improve the performance of supersonic inlets. In order to accurately predict the amount of bleed mass flow rates, this study performs a scaling of sonic flow coefficient data for 90-degree bleed holes in consideration of Prandtl-Meyer expansion theory. Furthermore, it is assumed that porosity varies with stream-wise location of the porous bleed plate to accurately predict downstream boundary layer profiles. The bleed boundary condition model is demonstrated through Computational Fluid Dynamics(CFD) simulations of bleed flows on a flat plate with/without an oblique shock. As a result, the bleed model shows the improved accuracy of bleed mass rates and downstream boundary layer profiles.

• 한국정밀공학회지
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• 제19권7호
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• pp.88-96
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• 2002

High-speed machining is one of the most effective technologies to improve productivity. Because of the high speed and high feed rate, high-speed machining can give great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut, feed rate and spindle revolution are control factors. The effect of the control factors on machining accuracy is investigated using two-way factorial design.