• Journal of Distribution Science
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• v.22 no.7
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• pp.73-82
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• 2024

Purpose: This study aims to identify the assessment criteria on textile and apparel supply chain management performance. Research design, data, and methodology: An integrated method of Delphi, quantitative survey, and ANP, in which Delphi with Kamet principle was applied to define the set of criteria, quantitative survey with reliability and validity test was utilized to ensure the match between the set of criteria and the whole textile and apparel industry, and ANP was used to derive weights of these criteria. Results: The set of supply chain management performance evaluation criteria composes of seven criteria namely order fulfillment quality, agility, costs, asset management, information sharing, innovation, and product development and 19 sub-criteria. Conclusions: This study theoretical contribution is the proposition of the set of evaluation criteria on supply chain performance. Regarding practical contribution, the study findings are guidelines for T&A companies in assessing and improving their supply chain capability. However, the findings are only for Vietnamese T&A context. Future research, therefore, may be expanded to other regions or countries' T&A industry. Additionally, future step to this study may be the utilization of other techniques of MCDM or methodological approaches like multiple regression, PLSSEM in defining weights of criteria or performance evaluation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.2
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• pp.208-213
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• 2012

In this paper, the radial error of a rotary table at five-axis machine tool is evaluated by utilizing ISO 230-2 and estimation method using double ball-bar. The geometric error of a rotary table is defined as position dependent geometric errors or position independent geometric errors according to their physical character. Then estimation method of geometric errors using double ball-bar is simply summarized including measurement path, parametric modeling and least squares approach. To estimate representative radial error, offset error, set-up error which affect to the double ball-bar data, mean value of measured data including CCW/CW-direction are used at estimation process. Radial errors are separated from measured data and used for evaluation with ISO 230-2. Finally, suggested evaluation method is applied to a rotary table at five-axis machine tool and its result is analyzed to improve the accuracy of the rotary table.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3935-3949
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• 2021

With the rapid development of Internet and big data technology, various online social network platforms have been established, producing massive information every day. Hot topic discovery aims to dig out meaningful content that users commonly concern about from the massive information on the Internet. Most of the existing hot topic discovery methods focus on a single network data source, and can hardly grasp hot spots as a whole, nor meet the challenges of text sparsity and topic hotness evaluation in cross-network scenarios. This paper proposes a novel hot topic discovery method across social network based on an im-proved LDA model, which first integrates the text information from multiple social network platforms into a unified data set, then obtains the potential topic distribution in the text through the improved LDA model. Finally, it adopts a heat evaluation method based on the word frequency of topic label words to take the latent topic with the highest heat value as a hot topic. This paper obtains data from the online social networks and constructs a cross-network topic discovery data set. The experimental results demonstrate the superiority of the proposed method compared to baseline methods.

• Geomechanics and Engineering
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• v.33 no.3
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• pp.231-242
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• 2023

This paper represents a comparative study in which Gene Expression Programming (GEP), Group Method of Data Handling (GMDH), and multiple linear regressions (MLR) were utilized to derive new equations for the prediction of time-dependent bearing capacity of pile foundations driven in cohesive soil, technically called pile set-up. This term means that many piles which are installed in cohesive soil experience a noticeable increase in bearing capacity after a specific time. Results of researches indicate that side resistance encounters more increase than toe resistance. The main reason leading to pile setup in saturated soil has been found to be the dissipation of excess pore water pressure generated in the process of pile installation, while in unsaturated conditions aging is the major justification. In this study, a comprehensive dataset containing information about 169 test piles was obtained from literature reviews used to develop the models. to prepare the data for further developments using intelligent algorithms, Data mining techniques were performed as a fundamental stage of the study. To verify the models, the data were randomly divided into training and testing datasets. The most striking difference between this study and the previous researches is that the dataset used in this study includes different piles driven in soil with varied geotechnical characterization; therefore, the proposed equations are more generalizable. According to the evaluation criteria, GEP was found to be the most effective method to predict set-up among the other approaches developed earlier for the pertinent research.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.86-91
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• 2008

In the field of network data analysis, the research of how much the estimation data reflects the population data is inevitable. This paper compares and analyzes the well known MIT Lincoln Lab network data, which is composed of collectable standard information from the network with the KDD CUP 99 dataset which was composed from the MIT/LL data. For comparison and analysis, the protocol information of both the data was used. Correspondence analysis was used for analysis, SVD was used for 2 dimensional visualization and weigthed euclidean distance was used for network data quantification.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.134-143
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• 2011

The selection of meaningful clinical tests and its reference values from a high-dimensional clinical data with imbalanced class distribution, one class is represented by a large number of examples while the other is represented by only a few, is an important issue for differential diagnosis between similar diseases, but difficult. For this purpose, this study introduces methods based on the concepts of both discernibility matrix and function in rough set theory (RST) with two discretization approaches, equal width and frequency discretization. Here these discretization approaches are used to define the reference values for clinical tests, and the discernibility matrix and function are used to extract a subset of significant clinical tests from the translated nominal attribute values. To show its applicability in the differential diagnosis problem, we have applied it to extract the significant clinical tests and its reference values between normal (N = 351) and abnormal group (N = 101) with either cholecystitis or cholelithiasis disease. In addition, we investigated not only the selected significant clinical tests and the variations of its reference values, but also the average predictive accuracies on four evaluation criteria, i.e., accuracy, sensitivity, specificity, and geometric mean, during l0-fold cross validation. From the experimental results, we confirmed that two discretization approaches based rough set approximation methods with relative frequency give better results than those with absolute frequency, in the evaluation criteria (i.e., average geometric mean). Thus it shows that the prediction model using relative frequency can be used effectively in classification and prediction problems of the clinical data with imbalanced class distribution.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.57-71
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• 1988

Checklist method is rapid and comprehensive to evaluate in practice. Check items are commonly rated by subjective utility function; i.e., evaluator's significant judgment. Since human judgment includes fuzziness (vagueness) inherently in spite of its significance, fuzzy set theory is useful in this case. The paper illustrates a evaluation method using fuzzy checklist where check items are rated as fuzzy numbers. Pairwise comparison data is used to determine the weights of check items, since it has comparative advantage for human's fuzzy judgment. Sample of BASIC program is provided for microcomputer. When uncertainty is due to subjectivity or imprecision of data, this method can be applied to practical problems widely.

• Nuclear Engineering and Technology
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• v.39 no.4
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• pp.337-348
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• 2007

A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.198-203
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• 1998

This study, a sub-one of comprehensive research works titled under “Rural Resources Evaluation System”, tried to verify utility/applicability of the developed model system through the case study works on 3 sample villages, Backya, Uyan and Suyu, representing the lowland, upland and seashore villages respectively. From the various surveying and collecting works including the official/statistical data collection, map analysis, insitu investigation, field survey and written material review, the original data set were obtained and manipulated into final input data for resources grading. After then, by the automatized calculation procedure of “Rural Resources Evaluation System”, score results for resources evaluation were finally produced with the total maximum score being 1,000. Through comparing works among score results of 3 case villages and between score results and areal characteristics of each case village, the applicability of the system developed in this study was well confirmed.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.251-259
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• 2006

Evaluation of the work of art with intention of the artist different is not a possibility of free oneself from the limit which estimates an evaluation at value of appreciator. We tried new interpreting about the work of art in this paper. The work of art respects the intention of the artist to make it and interprets intention until now. After critics distinguish by a period, an area that they set to philosophical thought which is the time and interpreted. We set to each one subjectivity and interpreted between artist to make the work of art and appreciator. But in this paper, we tied various criteria which appreciates the work of art. We tried so that we presented the intimacy each other newly. Otherwise we tied with the subjectivity of the individual and are the try to be an objectification low through statistical technique. We looked into the culture and art in the introduction and explain the discussion about the work of art interpreting which the main subject. We set the category 6 area, and explain an each criteria explanation and assessment method. We tried to propose new interpreting as the intimacy to be multivariate data analysis result of the assessment analysis. Stopping from the thing which sees the work of art knows, it will be able to give meaning thing from this research prerequisite.