• Title/Summary/Keyword: Training Cost

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Food Ingestion, Assimilation and Conversion Efficiency of Mulberry Silk­worm, Bombyx mori L.

  • Rahmathulla V. K.;Haque Rufaiel S. Z.;Himantharaj M. T.;Vindya G S.;Rajan R. K.
    • International Journal of Industrial Entomology and Biomaterials
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    • 제11권1호
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    • pp.1-12
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    • 2005
  • Feed conversion efficiency contributes directly or indirectly on the cost benefit ratio of silkworm rearing and is considered to be an important physiological criterion for evaluating the superiority of silkworm breeds/hybrids. Food intake, assimilation and conversion of indigenous as well as exotic silkworm races are well studied by many researchers. In this review, an attempt has been made to consolidate works on feed conversion aspects of indigenous and exotic silkworm races. The paper also deals with the effect of various factors viz., nutritional, environmental and feeding on food assimilation and conversion parameters of mulberry silkworm.

Incremental Multi-classification by Least Squares Support Vector Machine

  • Oh, Kwang-Sik;Shim, Joo-Yong;Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.965-974
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    • 2003
  • In this paper we propose an incremental classification of multi-class data set by LS-SVM. By encoding the output variable in the training data set appropriately, we obtain a new specific output vectors for the training data sets. Then, online LS-SVM is applied on each newly encoded output vectors. Proposed method will enable the computation cost to be reduced and the training to be performed incrementally. With the incremental formulation of an inverse matrix, the current information and new input data are used for building another new inverse matrix for the estimation of the optimal bias and lagrange multipliers. Computational difficulties of large scale matrix inversion can be avoided. Performance of proposed method are shown via numerical studies and compared with artificial neural network.

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The Application of BP and RBF Neural Network Methods on Vehicle Detection in Aerial Imagery

  • Choi, Jae-Young;Jang, Hyoung-Jong;Yang, Young-Kyu
    • 대한원격탐사학회지
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    • 제24권5호
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    • pp.473-481
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    • 2008
  • This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.

Reinforcement learning-based control with application to the once-through steam generator system

  • Cheng Li;Ren Yu;Wenmin Yu;Tianshu Wang
    • Nuclear Engineering and Technology
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    • 제55권10호
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    • pp.3515-3524
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    • 2023
  • A reinforcement learning framework is proposed for the control problem of outlet steam pressure of the once-through steam generator(OTSG) in this paper. The double-layer controller using Proximal Policy Optimization(PPO) algorithm is applied in the control structure of the OTSG. The PPO algorithm can train the neural networks continuously according to the process of interaction with the environment and then the trained controller can realize better control for the OTSG. Meanwhile, reinforcement learning has the characteristic of difficult application in real-world objects, this paper proposes an innovative pretraining method to solve this problem. The difficulty in the application of reinforcement learning lies in training. The optimal strategy of each step is summed up through trial and error, and the training cost is very high. In this paper, the LSTM model is adopted as the training environment for pretraining, which saves training time and improves efficiency. The experimental results show that this method can realize the self-adjustment of control parameters under various working conditions, and the control effect has the advantages of small overshoot, fast stabilization speed, and strong adaptive ability.

차량 간 범퍼높이 차이가 수리비에 미치는 영향 (The Effect of Bumper Mismatch on Vehicle Repair Cost)

  • 최동원;박인송;홍승준
    • 한국자동차공학회논문집
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    • 제18권1호
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    • pp.99-104
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    • 2010
  • It is a frequent occurrence in urban traffic - a low-speed collision in which one vehicle hits the back of another. The vehicles often sustain expensive damage. Bumpers can reduce this damage, but only line up so the initial contact in an impact is bumper to bumper. Then the bumpers on the colliding vehicles have to absorb the crash energy, keeping damage away from expensive sheet metal, lights, and other components. In real world accidents, Bumper mismatches in crashes are increasing, and the resulting repair costs from low-speed collisions are escalating. In this study, we investigated the bumper rail height and analyzed their effects on repair cost. Futhermore, Our 16kph front-into-rear crash tests demonstrates bumper mismatch problem.

Autopilot Design for a Target Drone using Rate Gyros and GPS

  • Rhee, Ihnseok;Cho, Sangook;Park, Sanghyuk;Choi, Keeyoung
    • International Journal of Aeronautical and Space Sciences
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    • 제13권4호
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    • pp.468-473
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    • 2012
  • Cost is an important aspect in designing a target drone, however the poor performance of low cost IMU, GPS, and microcontrollers prevents the use of complex algorithms, such as ARS, or INS/GPS to estimate attitude angles. We propose an autopilot which uses rate gyro and GPS only for a target drone to follow a prescribed path for anti-aircraft training. The autopilot consists of an altitude hold, roll hold, and path following controller. The altitude hold controller uses vertical speed output from a GPS to improve phugoid damping. The roll hold controller feeds back yaw rate after filtering the dutch roll oscillation to estimate the roll angle. The path following controller operates as an outer loop of the altitude and roll hold controllers. A 6-DOF simulation showed that the proposed autopilot guides the target drone to follow a prescribed path well from the view point of anti-aircraft gun training.

빅데이터 기법을 활용한 직업훈련 요구분석 (Analysis of Vocational Training Needs Using Big Data Technique)

  • 성보경;유연우
    • 한국융합학회논문지
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    • 제9권5호
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    • pp.21-26
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    • 2018
  • 본 연구는 고용노동부가 운영하는 직업훈련 통합전산망인 'HRD-NET(http://hrd.go.kr)'을 통해 구직자가 필요로 하는 직업훈련 정보 등이 원활하게 제공되고 있는지를 확인하기 위해 질문게시판을 빅데이터 기법에 가장 최적화된 'R'프로그램을 이용해서 추출하였다. 따라서, 이를 통해 직업훈련제도의 유효성, 적절성, 시각화, 빈도 분석, 연관분석 등을 실시하였으며, 연구결과는 다음과 같다. 첫째, 직업훈련 카드발급 및 동영상 시청, 공인인증서 문제, 등록오류 이 발견되었으며, 둘째, 내일배움카드에 대한 노동관서에서의 관리 및 처리절차가 복잡하고 까다로워 제도개선이 필요한 것으로 나타났다. 또한, 교육훈련의 수강에 있어 훈련직종 및 과정, 훈련기관에 따라서 차등화 된 훈련비 시스템과 환급구조가 애로요인으로 작용하는 것으로 분석되었다. 본 논문 기초로 하여 향후 고용노동부의 훈련시스템 뿐만 아니라 정부부처의 다양한 훈련 전산망시스템에 대한 전반적인 빅데이터 분석을 통한 개선점 등을 연구하고자 한다.

Support Vector Machine Classification Using Training Sets of Small Mixed Pixels: An Appropriateness Assessment of IKONOS Imagery

  • Yu, Byeong-Hyeok;Chi, Kwang-Hoon
    • 대한원격탐사학회지
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    • 제24권5호
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    • pp.507-515
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    • 2008
  • Many studies have generally used a large number of pure pixels as an approach to training set design. The training set are used, however, varies between classifiers. In the recent research, it was reported that small mixed pixels between classes are actually more useful than larger pure pixels of each class in Support Vector Machine (SVM) classification. We evaluated a usability of small mixed pixels as a training set for the classification of high-resolution satellite imagery. We presented an advanced approach to obtain a mixed pixel readily, and evaluated the appropriateness with the land cover classification from IKONOS satellite imagery. The results showed that the accuracy of the classification based on small mixed pixels is nearly identical to the accuracy of the classification based on large pure pixels. However, it also showed a limitation that small mixed pixels used may provide insufficient information to separate the classes. Small mixed pixels of the class border region provide cost-effective training sets, but its use with other pixels must be considered in use of high-resolution satellite imagery or relatively complex land cover situations.

A Study on the Development of a Caddie Education Program for Golf Club in China

  • Du, Xin-Rui;Kim, Sung-Jun;Cho, Sang-Woo
    • 한국응용과학기술학회지
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    • 제36권2호
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    • pp.479-487
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    • 2019
  • The purpose of this study is to present a caddie education program that can improve the performance of golf caddies in China by comparing and analyzing the golf caddie education programs in South Korea and China. Caddie education programs were collected from 4 golf clubs, 3 professional caddie education institutions and 8 public institutions in South Korea and 6 golf clubs and 2 professional caddie education institutions in China. The following results were obtained. Although the caddie training in China is conducted over more time and term than in South Korea, it is necessary to have an education program considering golf expertise and quality of customer service. Therefore, the caddie education program in China is composed of golf related education(golf etiquette, golf practice skill), caddie duty training(safety management, customer service and image making), and training for caddie(fitness management, injury prevention, skin care, and cost-saving etc.). In the future, the Chinese golf club industry will has a potential to develop. In order to provide a consistent and systematic education, manual training on caddie education and training on caddie master to manage caddies should be conducted.