• Fashion & Textile Research Journal
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• v.2 no.3
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• pp.246-252
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• 2000

The purpose of this study was to analyze the characteristics of the factor structure in Clothing Silhouette Image and the differences of Image Evaluation related to Grouping of Line and Grouping of Body Emphasis using Silhouette Image Factor and Life Space as variables. Clothing Silhouette Image was estimated by the photographs of 9 Life Spaces ${\times}$ 23 Clothing Silhouettes with 15 semantic differentiated by-polar scales. The major finding were : The factor structure of Clothing Silhouette Image were found to include 4 factor dimensions-Capability Evaluation, Function, Activity. It was clear that Silhouette Image were affected by Life Spaces. There were the differences of Image Evaluation related to Grouping of Line and Grouping of Body Emphasis. There were the differences of Life Space Evaluation related to Grouping of Line and Grouping of Body Emphasis. Therefore it is important to considerate Life Space for selecting Clothing Silhouette.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.649-660
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• 1998

Steel making in Mini Mill consists of three major processing stages: molten steel making in an electric arc fuenace, slab casting in a continuous caster, and hot rolling in a finishing mill. Each processing stage has its own lot grouping criterion. However, these criteria in three stages are conflicting with each other. Therefore, delveloping on efficient lot grouping algorithm to enhance the overall productivity of the Mini Mill is an extremely difficult task. The algorithm proposed in this paper is divided into three steps hierarchically: change grouping, cast grouping, and roll grouping. An efficient charge grouping heuristic is developed by exploiting the characteristics of the orders, the processing constraints and the requirements for the downstream stages. In order to maximaize the productivity of the continuous casters, each cast must contain as many charges as possible. Based on the constraint satisfaction problem technique, an efficient cast grouping heuristic is developed. Each roll consists of two casts satisfying the constraints for rolling. The roll grouping problem is formulated as a weighted non-bipartite matching problem, and an optimal roll grouping algorithm is developed. The proposed algorithm is programmed with C language and tested on a SUN Workstation with real data obtained from the H steel works. Through the computational experiment, the algorithm is verified to yield quite satisfactory solutions within a few minutes.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.61-75
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• 1995

In a microcellular personal communication service (PCS) it is required to minimize the paging and location updating signals. We propose a multi-layered location registration scheme to reduce the paging and updating signals. In this scheme the subscribers are grouped by their characteristics (velocity and call arrival rate) and are served by appropriately sized location registration area. In order to group the subscriber, we define subscriber grouping problem (SGP). Proposition are examined to solve the grouping problem. The performance of the proposed subscriber grouping algorithm is tested with examples. Simulation results indicate that the subscriber grouping procedure is effective for designing the multi-layered location registration scheme.

• Journal of the Korea Convergence Society
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• v.4 no.3
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• pp.35-41
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• 2013

Grouping problem with similarities between DNA sequences are studied. The similaritymeasure and the distance measure showed the complementary characteristics. Distance measure can be obtained by complementing similarity measure, and vice versa. Similarity measure is derived and proved. Usefulness of the proposed similarity measure is applied to grouping problem of 25 cockroach DNA sequences. By calculation of DNA similarity, 25 cockroaches are clustered by four groups, and the results are compared with the previous neighbor-joining method.

• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.291-300
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• 2010

Group-based learning is known to be an effective means to improve scholastic achievement in online learning. Therefore, there are some previous researches for the group-based learning. A lot of previous researches define factors for grouping from the characteristics of classes, teacher's decision and students' preferences and then generate a group based on the defined factors. However, many algorithms proposed by previous researches depend on a specific class and is not a general approach since there exist several differences in terms of the need of courses, learners, and teachers. Moreover it is hard to find a automatic system for group generation. This paper proposes a grouping system which automatically generate a learner group according to characteristics of various classes. the proposed system automatically generates a learner group by using basic information for a class or additional factors inputted from a user. The proposed system defines a set of rules for learner grouping which enables automatic selection of a learner grouping algorithm tailored to the characteristics of a given class. This rule based approach allows the proposed system to accommodate various learner grouping algorithms for a later use. Also we show the usability of our system by serviceability evaluation.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3336-3346
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• 2022

In general, a number of severe accident scenarios derived from Level 2 probabilistic safety assessment (PSA) are typically grouped into several categories to efficiently evaluate their potential impacts on the public with the assumption that scenarios within the same group have similar source term characteristics. To date, however, grouping by similar source terms has been completely reliant on qualitative methods such as logical trees or expert judgements. Recently, an exhaustive simulation approach has been developed to provide quantitative information on the source terms of a large number of severe accident scenarios. With this motivation, this paper proposes a machine learning-based categorization method based on exhaustive simulation for grouping scenarios with similar accident consequences. The proposed method employs clustering with an autoencoder for grouping unlabeled scenarios after dimensionality reductions and feature extractions from the source term data. To validate the suggested method, source term data for 658 severe accident scenarios were used. Results confirmed that the proposed method successfully characterized the severe accident scenarios with similar behavior more precisely than the conventional grouping method.

• KSBB Journal
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• v.27 no.1
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• pp.40-44
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• 2012

The laboratory animal group separation is dividing animal population into subgroups, which have similar average and standard deviation values among the subgroups, based on the biological characteristics such as body weight, glucose level in blood, etc. Although group separation is very important and initial step in experimental design, it needs a labor intensive process for researchers because of making similar average and standard deviation values among the subgroups using the raw biological characteristics. To reduce the labor cost and increase the efficiency of animal grouping, we developed a web program named as laboratory animal group separation (LAGS) program. This LAGS uses biological characteristics of population, number of group, and the number of elements per each subgroup as input data. The LAGS automatically separates the population into each subgroup that has similar statistical data such as average and standard deviation values among subgroups. It also provides researchers with the extraordinary data generated in the process of grouping and the final grouping results by graphical display. Through our LAGS, researchers can validate and confirm results of laboratory animal group separation by just a few mouse clicks.

• Journal of Ocean Engineering and Technology
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• v.16 no.3
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• pp.46-53
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• 2002

In the study, the interaction characteristics among incident waves, run-up and internal waterlevel at core layer of breakwaters were investigated. The effect of core materials on the internal waterlevel characteristics are also discussed using the results with both regular and irregular wave tests. The main results obtained are as follows; The higher internal waterleve was observed under the permeable breakwater with core layer of the lower permeability than with the higher one. And, the internal waterlevl decreased as far as the distance from the toe. In the irregular wave test, the grouping characteristics of incident waves make large fluctuation of the waterlevel. Especially, breakwaters internal waterlevel appeared to affect the hydraulic characteristics on slope.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.124-132
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• 2011

In a modern electronic warfare, radar signal environments become more denser and complex. Therefor the capability of reliable signal analysis techniques is required for ES(Electronic warfare Support) system to identify and analysis individual emitter signals from received signals. In this paper, we propose the new signal grouping algorithm to ensure the reliable signal analysis and to reduce the cost of the signal processing steps in the ES. The proposed grouping algorithm uses KDE(Kernel Density Estimator) and its CDF(Cumulative Distribution Function) to compose windows considering the statistical distribution characteristics based on the radar frequency modulation type. Simulation results show the good performance of the proposed technique in the signal grouping.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.263-269
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• 2012

Grouping of characters in a 3D game can be very effective to play. An 3D game characters grouping method is proposed using Object Feature vector depending on their characteristics. In the case of NMT, the constitution of pattern is regular and directive. But MT is not. Such characteristic is extracted using Gabor Filter, then character is grouped. Through experiment, we obtain accuracy of more than 80% for grouping method using each feature. Thus, using this property, characters could be grouped effectively and it draws the game more speed and strategic actions as a result.