• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.139-142
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• 1991

The design variables of SLIM used for 3-D conveyor system are optimized by nonlinear programing. Five design variables are selected as independent ones and object function is expressed as a combination of the weight and the normal force of the motor. Maximum flux density in the teeth, primary length and starting thrust are chosen as constraint functions. Goodness factor considering of conveying characteristic is also included in the constraints. In this paper sequential unconstrained minimization technique(SUMT) and variable metric method are used to solve the nonlinear problem.

• Journal of the Korean Society of Costume
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• v.32
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• pp.131-147
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• 1997

The works of the Futurism were developed along with manifestos and statement in publishing " The Foundation and Manifestos of Futurism" Futurist aesthetic and ideological agenda on futurist fashion displayed in mani-festos on clothes. It was propagated in con-summate Futurist style through the written manifestos. The Futurists anticipated much of modern fashion phenomenon. In Futurist Men's Cloth-ing in 1914 they believed continual renual of our today's clothes. Today's clothes is much our today's clothes. Today's clothes is much more simple than yesterday's clothes. The oppositions of the type between yesterday's clothes and today's clothes are mournful=play-ful melancolic-cheerful grey-colorful tradi-tional-emphemeral. Futurist men's clothing is aggressive agile dynamic simple and confor-table hygienic gay luminous volatile asym-metric ephemeral and variable. In general the Futurist argued for clothes that promoted simple and functionality. They made dynamic patterns in textile design and asymmetric geometric cuts in pattern making. They suggested an unconventional matetials and strong bright colors and modificanti. These elements pointed the way to a shim-mering exuberant future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4A
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• pp.379-386
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• 2007

In this paper, we propose an efficient diagnosis algorithm for multiple stuck-at faults. Because of using vectorwise intersections as an important metric of diagnosis, the proposed diagnosis algorithm can diagnose multiple defects in single stuck-at fault simulator. In spite of multiple fault diagnosis, the number of candidate faults is drastically reduced. For identifying faults, the variable weight, positive calculations and negative calculations are used for the matching algorithm. To verify our algorithm, experiments were performed for ISCAS85 and full-scan version of ISCAS89 benchmark circuits.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.59-60
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• 2007

Entropy, one of leading metrics on anomalous traffic, attracts researcher's attention since a packet sampling and a traffic volume impact little on entropy value. In this paper, we apply the entropy metric to a domestic network traffic trace which has real anomalous traffics. We used source IP address/port and destination IP address/port that are important attributes of a packet as entropy variable We found that entropy value of multiple-port DoS attack shows something related to a staircase fashion. Also, we show a Possibility of detection of anomalous traffic on small time scale.

• Asia pacific journal of information systems
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• v.16 no.3
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• pp.193-203
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• 2006

Software reliability prediction is a statistical method to put in place a timely software development practice useful for objective assessment of bidders. The current study suggests one research method that enables reliability assessment of such previous projects by studying user satisfaction and project management history. If incorporated into the existing acquisition process, the reliability assessment method will further enhance objectivity and accuracy in bidder selection process. The GQM(Goal Question Metric) paradigm was used to identify assessment metrics for bidder evaluation and questionnaires were collected from users to create user satisfaction indexes. In addition, 'weight of evidence', the most appropriate categorical method, was used to isolate attributes of each variable that may contribute to reliability assessment.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.483-501
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• 2012

The purpose of this study was to apply a multi-metric model of Lentic Ecosystem Health Assessments(LEHA) for environmental impact assessments of Cheongpyung Reservoir during 2005 - 2006 and assessed the ecological model values. The ecosystem model of LEHA was composed of eleven metrics such as biological parameters($B_p$), physical parameters($P_p$), and chemical parameters($C_p$), and determined the rank of ecological health by the criteria. The variables of $B_p$ were metrics of % sensitive species($M_2$, NMS) and insectivore species($M_5$, % $I_n$), which decrease as the water quality degradates, and these metric values were low as 1.5% and 32.4%, respectively. In contrast, the proportions of tolerant species and omnivore species as the other $B_p$ parameters were 43% and 62%, respectively, which indicate a degradation and disturbance of the ecosystem. Riparian vegetation coverage($M_9$, % $V_c$) as a variable of $P_p$, were higher in the 2nd than 1st survey, and decreased toward the dam site from the headwaters. This was due to a habitat simplification(modifications) by frequent bottom dredging of sand and rocks. The variables of $C_p$ were two metrics of specific conductivity($M_{10}$, $C_I$) as an indicator of ionic contents(cations and anions) and the Trophic State Index(TSI) based on chlorophyll-a($M_{11}$, $TSI_{CHL}$) as an indicator of trophic state. These metric values of $C_p$ had high temporal variations, but low spatial variations on the main axis of the reservoir along with the ecological health of a good condition. The environmental impact assessments using the LEHA multi-metric model indicated that the model values of LEHA averaged 30.7 in 1st survey(fair - poor condition) vs. 28 in 2nd survey(poor condition), indicating a temporal variation of the ecological health. The model values of LEHA showed a minimum(28) in the lacustrine zone(S5) and ranged from 29 to 30 in the other locations sampled, indicating a low longitudinal variation. Overall, environmental impact assessments, based on LEHA model, suggest that chemical water quality conditions were in good, but biological conditions were disturbed due to habitat modifications by frequent dredgings in the system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.57-64
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• 2010

Measurements of deflection in load testing of structures are typically obtained with contact instrumentations such as LVDT (Linear-Variable Differential Transformer). LVDT only measure 1-dimensional deformation and in destructive testing is damage to instrumentation, thus prohibiting deflection when the beam is close to failure. Measurements of deflection using non-metric digital cameras are useful for load testing because there are very little cost or beam failure except for cheap targets and measurements in 3-dimensional deflection can obtained rapidly. In this research, deflection of concrete beam was measured using Nikon D80 DSLR camera, and the accuracy was evaluated with comparing the outputs to the LVDT measurements. The results show that the accuracy of terrestrial photogrammetric measurements are ${\pm}$0.5mm, ${\pm}$0.5mm, ${\pm}$0.6mm for each X, Y, Z directions, and the RMSE of comparison to LVDT is ${\pm}$0.57mm.

• Knowledge Management Research
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• v.21 no.1
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.489-498
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• 2004

VLIW processor is considered to be an appropriate processor for the embedded system, provided with high performance and low power con-sumption due to its simple hardware structure. Unfortunately, the VLIW processor often suffers from high memory access latency due to the variable length of I-packets, which consist of independent instructions to be issued in parallel. It is because of the variable I-packet length that some I-packets must be placed over two cache blocks, which are called straddle I-packets, so that two cache accesses are required to fetch such I-packets. In this paper, an expansion buffer cache is proposed to improve not only the instruction fetch bandwidth, but also the power consumption of the I-cache with moderate hardware cost. The expansion buffer cache has a small expansion buffer containing a fraction of a straddle packet along with the main cache to reduce the additional cache accesses due to the straddle I-packets. With a great reduction in the cache accesses due to the straddle packets, the expansion buffer cache can achieve $5{\~}9{\%}$improvement over the conventional I-caches in the $Delay{\cdot}Power{\cdot}Area$ metric.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.537-552
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• 2019

Purpose: The development of information technology makes it easy to utilize high-dimensional categorical data. In this regard, the purpose of this study is to propose a novel method to select the proper categorical variables in high-dimensional categorical data. Methods: The proposed feature selection method consists of three steps: (1) The first step defines the goodness-to-pick measure. In this paper, a categorical variable is relevant if it has relationships among other variables. According to the above definition of relevant variables, the goodness-to-pick measure calculates the normalized conditional entropy with other variables. (2) The second step finds the relevant feature subset from the original variables set. This step decides whether a variable is relevant or not. (3) The third step eliminates redundancy variables from the relevant feature subset. Results: Our experimental results showed that the proposed feature selection method generally yielded better classification performance than without feature selection in high-dimensional categorical data, especially as the number of irrelevant categorical variables increase. Besides, as the number of irrelevant categorical variables that have imbalanced categorical values is increasing, the difference in accuracy between the proposed method and the existing methods being compared increases. Conclusion: According to experimental results, we confirmed that the proposed method makes it possible to consistently produce high classification accuracy rates in high-dimensional categorical data. Therefore, the proposed method is promising to be used effectively in high-dimensional situation.