• 대한인간공학회지
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• 제27권4호
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• pp.45-58
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• 2008

Ergonomic techniques have been required to analyze the effectiveness of functional clothing design improvement in a systematic and analytic manner. The goals of the present study are to: (1) comprehensively and analytically examine the effectiveness of clothing improvement by using the relationship analysis between clothing design components (D) and ergonomic evaluation measures (E) and (2) prove the usefulness of cost-effectiveness analysis for clothing design optimization. The cost effectiveness analysis is comprised of the preliminary evaluation based on expertise and the in-depth evaluation where the D-E relationship analysis is applied. As a result of the cost effectiveness analysis applied to flame-proof clothing, an optimal design was identified by analyzing costs and qualitative/quantitative effects. In the preliminary evaluation, the expected effectiveness of each design alternative on wear efficiency and wear comfort was estimated. In the in-depth evaluation, however, the effectiveness of each design alternative was analyzed by quantitative evaluation in a wearing test using a questionnaire prepared based on the D-E relationship analysis. It was concluded that the D-E relationship analysis and the cost-effectiveness analysis are useful for comprehensive evaluation and optimization of functional clothing design.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.42.2-42
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• 2002

We discuss a neural network solver for the inverse optimization problem. The problem is that find functional relations between input and output data, which are include defects. Finding the relations, predictions of the defect parts are also required. The part of finding the defects in the input data is an inverse problem . We consider the meanings to solve the problem on the neural network system at first. Next, we consider the network structure of the system, the learning scheme of the network, and at last, examine the precision on the numerical calculations. In the paper, we proposed the high-precision learning method for plural three-layer neural network system that is series-connect...

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.430-434
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• 2007

본 논문은 NTIS ITAMS 현행 시스템의 기능 구현에 대한 현황을 분석하고, ITA 관련 정보와 산출물을 보다 효율적으로 생성 및 분석하여 활용할 수 있는 ITA 관리시스템의 기능 개선을 위한 고도화 방안을 제시하고자 한다.

• Journal of applied mathematics & informatics
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• 제19권1_2호
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• pp.19-32
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• 2005

It is shown that the problem of minimizing (maximizing) a quadratic cost functional (quadratic gain functional) given the dynamics dx = (fx + gu)dt + hdb(t, a) where b(t, a) is a fractional Brownian motion of order a, 0 < 2a < 1, can be solved completely (and meaningfully!) by using the dynamical equations of the moments of x(t). The key is to use fractional Taylor's series to obtain a relation between differential and differential of fractional order.

• 한국경영과학회지
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• 제32권3호
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• pp.17-31
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• 2007

In this paper, we consider a service system with bi-functional servers, which can switch between the primary service room and the secondary room. A service policy is characterized by the switching paints which depend on the queue length in the primary service room and the service level requirement constraint of the secondary room. The primary service room is modeled as a Markovian queueing system and the throughput of the primary service room is function of the total number of bi-functional servers. the buffer capacity of the primary service room, and the service policy. There is a revenue obtained from throughput and costs due to servers and buffers. We study the problem of simuitaneously determining the optimal number of servers, buffer capacity, and service policy to maximize profit of the service system, and develop an algorithm which can be successfully applied with the small number of computations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.816-839
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• 2023

In a random vector functional link (RVFL) network, shortcomings such as local optimal stagnation and decreased convergence performance cause a reduction in the accuracy of illumination correction by only inputting the weights and biases of hidden neurons. In this study, we proposed an improved regularized random vector functional link (RRVFL) network algorithm with an optimized grey wolf optimizer (GWO). Herein, we first proposed the moth-flame optimization (MFO) algorithm to provide a set of excellent initial populations to improve the convergence rate of GWO. Thereafter, the MFO-GWO algorithm simultaneously optimized the input feature, input weight, hidden node and bias of RRVFL, thereby avoiding local optimal stagnation. Finally, the MFO-GWO-RRVFL algorithm was applied to ameliorate the performance of illumination correction of various test images. The experimental results revealed that the MFO-GWO-RRVFL algorithm was stable, compatible, and exhibited a fast convergence rate.

• 대한인간공학회지
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• 제31권6호
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• pp.733-740
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• 2012

Objective: The present study systematically analyzed the characteristics of ergonomic layout optimization methods by a comprehensive literature survey. Background: Although layout design methods for ergonomic placement of controls and displays on a console have been developed, understanding of their characteristics is lacking. Method: The present study analyzed layout optimization papers published past 20 years from the following four aspects: optimization model, optimization algorithm, design principle, and constraint/assumption. Results: The existing layout optimization methods based on various optimization techniques consider only a partial set of four layout principles(importance, frequency of use, sequence of use, and functional grouping) and two ergonomic criteria(visibility and reach). In addition, the existing methods oversimplify components in various sizes, shapes, and angles by assuming the equality of the components in size and shape. Conclusion: A more effective layout optimization method is needed which considers the layout principles and ergonomic criteria in a comprehensive manner and reflect the diversity of components in size and shape. Application: The identified characteristics on the existing layout optimization methods can be applicable to development of a better ergonomic console layout design method.

• 품질경영학회지
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• 제46권1호
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• pp.39-74
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• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.239-247
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• 2008

In a resource-limited wireless communication environment, various approaches to meet the ever growing application requirements in an efficient and transparent manner, are being researched and developed. Amongst many approaches, cross layer technique is by far one of the significant contributions that has undoubtedly revolutionized the way conventional layered architecture is perceived. In this paper, we propose a Universal Cross Layer Framework based on vertical layer architecture. The primary contribution of this paper is the functional architecture of the vertical layer which is primarily responsible for cross layer interaction management and optimization. The second contribution is the use of optimization cycle that comprises awareness parameters collection, mapping, classification and the analysis phases. The third contribution of the paper is the decomposition of the parameters into local and global network perspective for opportunistic optimization. Finally, we have shown through simulations how parameters' variations can represent local and global views of the network and how we can set local and global thresholds to perform opportunistic optimization.

• Journal of applied mathematics & informatics
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• 제26권1_2호
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• pp.355-364
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• 2008

Under pathological stress stimuli, dynamics of a biological system can be changed by alteration of several components such as functional proteins, ultimately leading to disease state. These dynamics in disease state can be modeled using differential equations in which kinetic or system parameters can be obtained from experimental data. One of the most effective ways to restore a particular disease state of biology system (i.e., cell, organ and organism) into the normal state makes optimization of the altered components usually represented by system parameters in the differential equations. There has been no such approach as far as we know. Here we show this approach with a cardiac hypertrophy model in which we obtain the existence of the optimal parameters and construct an optimal system which can be used to find the optimal parameters.