• 한국정밀공학회지
• /
• 제16권3호통권96호
• /
• pp.215-221
• /
• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• 한국정밀공학회지
• /
• 제16권5호통권98호
• /
• pp.48-57
• /
• 1999

Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

• 한국재난정보학회 논문집
• /
• 제9권2호
• /
• pp.164-177
• /
• 2013

2010년부터 2013년까지 낙찰자 선정방식이 설계적합 최저가방식, 종합평가방식(입찰가격 조정, 설계점수조정, 가중치기준), 확정금액 최상 설계방식으로 변경되었다. 따라서 이 연구는 국내에서 시행된 변경된 방식에 의한 토목부분 턴키 대안입찰공사의 발주현황, 건수, 수주실적, 낙찰률 범위, 공종별 발주기관별 수주실적, 가중치 낙찰자 수주실적 등의 분석을 통해 국내 낙찰자 결정방식이 건설산업에 미치는 영향, 심의 발주방식 및 운영상의 문제점을 분석하여 제시하였다.

• Structural Monitoring and Maintenance
• /
• 제4권1호
• /
• pp.85-105
• /
• 2017

Monitoring is the most important part of the construction and operation of the embankment dams. Applied instruments in these dams should be determined based on dam requirements and specifications. Instruments selection considered as one of the most important steps of monitoring plan. Competent instruments selection for dams is very important, as inappropriate selection causes irreparable loss in critical condition. Lack of a systematic method for determining instruments has been considered as a problem for creating an efficient selection. Nowadays, decision making methods have been used widely in different sciences for optimal determination and selection. In this study, the Multi-Attribute Decision Making is applied by considering 9 criteria and categorisation of 8 groups of geotechnical instruments. Therefore, the Analytic Hierarchy Process and Multi-Criteria Optimisation and Compromise Solution methods are employed in order to determine the attributes' importance weights and to prioritise of instruments for embankment dams, respectively. This framework was applied for a rock fill with clay core dam. The results indicated that group decision making optimizes the selection and prioritisation of monitoring instruments for embankment dams, and selected instruments are reliable based on the dam specifications.

• 대한치과보철학회지
• /
• 제42권5호
• /
• pp.544-555
• /
• 2004

Statement of problem: Shade selection has traditionally been accomplished by visual examination, which is particularly relevant to the shade selection of anterior teeth, but the subjective nature of visual analysis can lead to errors in shade matching. Recently shade selection systems have been developed to provide a more objective and scientific approach to understanding and clarifying shade selection. Purpose : The purpose of this study was analysis of various shade analyzing equipment with the goal of providing a more objective shade selection. Materials and method: Visual shade matching system selection(Vita Lumin Vacuum shade guide, Vitapan 3D Master shade guide) and mechanical shade matching method($ShadeEye^{(R)}$-EX Chroma Meter, $Shadescan^{TM}$ System) used for this study. The shade guide tap specimens for 10 extracted maxillary anterior teeth were produced by selecting shades using each shade matching system. The accuracy of the selection of shades for the teeth and fabricated specimens were evaluated by analyzing the calculated shade difference(${\Delta}E^*$), using a spectrophotometer and calculating the output of value $L^*,\;a^*,\;b^*$. Results and conclusion: The results show that the average ${\{Delta}E^*$ value (difference of shade) of the shade tap specimens to the actual specimen decreased in the following order: Vita Lumin Vacuum Shade Guide(VL), $ShadeEye^{(R)}$-EX Chroma Meter(SE) Vitapan 3D Master Shade guide(V3), and $Shadescan^{TM}$ System(55) : and that there are significant statistical differences between the VL and SS (p<0.05). In the analysis of the ${\Delta}E^*$ (difference of shade) value,40% of the VL group was found to be less than 3.3 (limit value of shade tap specimens clinically acceptable), 60% in the V3 group, 50% in the SE group, and 80% in the SS group.

• 한국지능시스템학회:학술대회논문집
• /
• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
• /
• pp.283-286
• /
• 2007

This paper proposes a genetic algorithm (GA) approach to instance selection in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in complex problem solving. Nonetheless, compared to other machine learning techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for instance selection in CBR.

• 한국CDE학회논문집
• /
• 제3권4호
• /
• pp.236-242
• /
• 1998

This paper presents a development of computer aided cutting tool selection techniques for rough and finish turning operations. The developed system,. which is one of important activities for computer aided operation planning, firstly implements operation sequencing. Then, from relations of the size of machined area, recommended finishing allowance and maximum depth of cut, a main machining method is selected, a number of cut is calculated, cutting tools including toolholders and inserts are selected, and values for cutting parameters are determined. A cutting tool selection procedure is proposed for toolholders and inserts of ISO code in rough cutting, and some important parameters such as holder style, tool approach angle, tool function and its direction are described in detail. In order to demonstrate the validity of the system a case study is performed.

• 한국지능시스템학회논문지
• /
• 제18권6호
• /
• pp.849-855
• /
• 2008

The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.

• 대한전기학회논문지:전력기술부문A
• /
• 제55권11호
• /
• pp.485-491
• /
• 2006

In this paper, we study the problem of model selection for Support Vector Machine(SVM) predictor for short-term load forecasting. The model selection amounts to tuning SVM parameters, such as the cost coefficient C and kernel parameters and so on, in order to maximize the prediction performance of SVM. We propose that Cross-Validation method can be used as a model selection algorithm for SVM-based load forecasting technique. Through the various experiments on several data sets, we found that the difference between the prediction error of SVM using Cross-Validation and that of ideal SVM is less than 5%. This shows that SVM parameters for load forecasting can be efficiently tuned by using Cross-Validation.

• Journal of Electrical Engineering and Technology
• /
• 제12권3호
• /
• pp.1177-1186
• /
• 2017

This paper presents a torque ripple reduction method of direct torque control (DTC) using fuzzy controller with optimal selection strategy of voltage vectors in a five-phase induction motor. The conventional DTC method has some drawbacks. First, switching frequency changes according to the hysteresis bands and motor's speed. Second, the torque ripple is rapidly increased in long control period. In order to solve these problems, some/most papers have proposed torque ripple reduction methods by using the optimal duty ratio of the non-zero voltage vector. However, these methods are complicated in accordance with the parameter. If this drawback is eliminated, the torque ripple can be reduced compared with conventional method. In addition, the DTC can be simply controlled without the use of the parameter. Therefore, the proposed algorithm is changing the voltage vector insertion time by using the designed fuzzy controller. Also, the optimized voltage vector selection method is used in accordance with the torque error. Simulation and experimental results show effectiveness of the proposed control algorithm.