• 한국정보과학회논문지:시스템및이론
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• 제32권7호
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• pp.377-392
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• 2005

컴퓨터 시스템이 등장한 이후 시스템 성능을 측정하고 분석하기 위한 많은 연구가 시스템 모델링, 성능 측정, 감시, 그리고 성능 예측 등 여러 분야에서 진행되었다. 그럼에도 불구하고, 각 성능 관련 분야를 하나로 묶는 통합 프레임워크에 관한 연구는 거의 이루어지지 않았다. 특히 TMO(Time-Triggered Message-Triggered Object) 실시간 프로그래밍 모델의 경우, 간단한 감시 도구를 제외하고 성능 측정 도구나 분석 프레임워크가 없어, TMO 모델 기반 시스템 및 태스크를 분석하는데 어려움이 있다. 이에 따라, 본 논문에서는 TMO 모델 기반의 동적 분석 프레임워크인 TDAF(TMO based Dynamic Analysis Framework)를 제안한다. TDAE는 성능 측정 및 분석 단계를 전체적으로 다루며, 구성 요소인 부하 모델, 성능 모델, 그리고 보고 모델을 유기적으로 결합하여 보다 신뢰할 수 있는 정보를 개발자에게제공한다. 이를 지원하기 위해 기존 부하 모델에 TMO 모델을 결합하여 확장한 부하 모델을 제안하고, TMO 객체 부하를 파악할 수 있는 부하 계산 알고리즘을 제안한다. 또한 TMO 객체 부하를 고려하여 성능 측정지수를 구현한 성능 알고리즘과, 부하 및 성능을 기초로 실시간 태스크의 주기 및 데드라인을 도출할 수 있는 보고 모델과 알고리즘을 제안한다. 마지막으로 부하 계산 알고리즘의 타당성을 입증하기 위한 실험을 수행하고 그 결과를 제시한다.

• Asia pacific journal of information systems
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• 제21권2호
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• pp.19-42
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• 2011

This paper proposes a new framework to predict decision performance by investigating the cognitive fit of decision makers. We assume that every decision maker has two kinds of schema: emotional and rational. Cognitive fit is believed to have a close relationship with the two schemata and decision performance. In the literature on decision performance there is few studies investigating the relationship between the two schemata and cognitive fit. Therefore, our research purposes are twofold: (1) to provide a theoretical basis for the proposed framework describing the causal relationships among the two schemata, cognitive fit. and decision performance, and (2) to empirically prove its validity in the application to an Internet shopping environment. Based on the questionnaires from 104 respondents, we used a second order, confirmatory factor analysis (CFA) model to extract valid constructs, and a structural equation model (SEM) to calculate path coefficients and prove the statistical validity of our proposed research model. The experimental results supported our research model.

• 한국군사과학기술학회지
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• 제12권4호
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• pp.407-414
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• 2009

This paper describes a conceptual model for the performance analysis simulator of a weapon launching system. The system performance analysis simulator is envisioned to provide an integrated analysis environment in which the system performance and operational effectiveness can be analyzed in more rapid and efficient way. The conceptual model for the simulator describes a referent independently of specific technology and implementation, and it can be used to transform the simulator requirements into the simulator system specifications.

• 한국공간구조학회논문집
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• 제21권1호
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• pp.87-94
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• 2021

The purpose of this paper is to improve the inappropriate analysis results when the end of the brace on braced frame is applied as pinned connection in practice. The stiffness of the gusset plate connection on the braced frame has the amount of between pinned and rigid connection, and the analysis model that applies the stiffness of the connection must be used for accurate performance evaluation. In this study, the stiffness of the gusset plate designed by the balanced design procedure are quantified, and applied to the analysis model to simulate the gusset plate connection. The proposed model was verified through nonlinear static analysis (pushover analysis) of SAP2000. The effect of the connection on the seismic performance of the braced frame was analyzed by comparing the proposed model and pinned model. As a result, it was confirmed that the performance of the braced frame was evaluated conservatively in practice, and the ductility was overestimated. Therefore, it is important to consider the connection for accurate and economical performance evaluation.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2000년도 추계학술대회 및 정기총회
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• pp.275-278
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• 2000

This paper focuses on a performance analysis model for optimizing the freight terminal design and layout using AutoMod simulator and numerical analysis. We developed a model to analyze the freiht terminal performance per unit time and the material handling cost based on both throughput and waiting due to conjestion. We developed computer program for this model and some sample results by both numerical method and AutoMod simulator are compared.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.524-528
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• 2008

The HEMU-400X(High-speed Electric Multiple Unit 400km/h eXperimental) project starts in 2007. It is required to analysis and simulate the train performance throughout the project life cycle for a successful completion of the project. This paper is devoted to the development of a train performance analysis model for the high-speed electric multiple unit 400km/h experimental. The model consist of running resistance model, train model, traction model and braking model. So, this paper represents the results of the train performance analysis.

• Geomechanics and Engineering
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• 제29권3호
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• pp.369-376
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• 2022

Accurately evaluating and predicting the performance of facilities is a key task in establishing a maintenance strategy for facilities. The importance of performance evaluation is becoming more pronounced, especially when the aging of facilities requires a huge budget. In this study, performance assessment models were developed for road and railway tunnels. Delphi analysis was performed to identify sub-elements necessary to evaluate the performance of a tunnel. The relative importance of the evaluation factors was derived from the AHP analysis. The correlation analysis was performed between each assessment factor and the final result to verify the significance of the model. For the correlation analysis, the survey data measured through precision safety diagnosis in tunnels in use was applied. The cost effectiveness analysis was also conducted according to the scenarios with different composition of performance factors in order to improve the practical applicability of the evaluation model developed in this study.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.71-79
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• 2016

This study proposes a performance model of a shared bus multi-processor system and analyzes the effect of input/output types on system performance and overload of shared resources. This system performance model reflects the memory reference time in relation to the effect of input/output types on shared resources and the input/output processing time in relation to the input/output processor, disk buffer, and device standby places. In addition, it demonstrates the contribution of input/output types to system performance for comprehensive analysis of system performance. As the concept of workload in the probability theory and the presented model are utilized, the result of operating and analyzing the model in various conditions of processor capability, cache miss ratio, page fault ratio, disk buffer hit ratio (input/output processor and controller), memory access time, and input/output block size. A simulation is conducted to verify the analysis result.

• International Journal of Advanced Culture Technology
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• 제11권3호
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• 한국자동차공학회논문집
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• 제24권5호
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• pp.581-587
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• 2016

Braking is a basic and an important safety feature for all vehicles, and the final braking performance of a vehicle is determined by the vehicle's ABS performance and tire performance. However, the combination of excellent ABS and tires will not always ensure good braking performance. This is due to the fact that tire performance has non-linearity and uncertainty in predicting the repeated increase and decrease of wheel slip when activating the ABS, thus increasing the uncertainty of tire performance prediction. Furthermore, existing studies predicted braking performance after using an ABS that used a wheel slip control as a controller, which was different from an actual vehicle's ABS that controlled angular acceleration, therefore causing a decrease in the prediction accuracy of the braking performance. This paper reverse-designed the ABS that controlled angular acceleration based on the information on brake pressure, etc., which were obtained from vehicle tests, and established a braking performance prediction analysis model by combining a multi-body dynamics(MBD) vehicle model and a magic formula(MF) tire model. The established analysis model was verified after comparing it with the results of the braking tests of an actual vehicle. Using this analysis model, this study analyzed the braking effect by vehicle factor, and finally designed a tire that had optimized braking performance. As a result of this study, it was possible to design the MF tire model whose braking performance improved by 9.2 %.