• Korean Journal of Human Ecology
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• v.17 no.2
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• pp.305-313
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• 2008

This subject investigated visual evaluation of preference and fitness level of set-in sleeve in sleeve types(form)and studied suitable sleeve type at silhouette and targeted female students in twenties. The results of study were as follows: 1. Visual evaluation factors in set-in sleeve of sleeve types were selected 6 factors; the 1st factor is decorativeness, the 2nd factor is attractiveness, the 3rd factor was activeness, the 4th factor was feminine, the 5th factor was charming and 6th factor was a figural element. Decorativeness and attractiveness factors in visual evaluation of sleeve types were the most important level. 2. The visual evaluation differences of sleeve types in set-in sleeve were as follows; in the 1st factor, S and P2 were the most decorative sleeve type. in the 2nd factor, S, P2 and P3 are the most attractive sleeve type. in the 3rd factor, B and P3 were the most active sleeve type. in the 4th factor, L was the most feminine sleeve type. in the 5th factor, P1, L and P3 were charming sleeve type. in the 6th factor, P3 was evaluated that it shows narrowened shoulder sleeve types. 3. The analysis result of preference and wearing level in each sleeve types were as follows. 20's female university students like to wear S, P1, P2 and P3 sleeve types and the most favorite sleeve types are S, P2 and P3. 4. The analysis result of silhouette set-in sleeve in sleeve types; S, B and P2 in H-type silhouette, P2, S and P1 in A-type silhouette, B and P3 in O-type silhouette, L and P3 in X-types silhouette were show the most suitable sleeve types.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.43-50
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• 1990

In conventional function analysis, the function values are evaluated by experts, which are treated as exact values. For many cases, it is often difficult to evaluate the function values of a certain subject because the criteria of evaluation are very vague. This paper presents a new function evaluation method using fuzzy set. The purpose of the method is to minimize the difference among experts by recognizing an intersection point of membership function as a representative value.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.30-38
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• 2012

Sentiment analysis is concerned with extracting and analyzing different kinds of user sentiment expressed in a variety of social media such as blog and twitter. Although sentiment analysis techniques are actively studied for these days, evaluation sets are not developed yet for Korean sentiment analysis. In this paper, we constructed an evaluation set for Korean sentiment analysis. To evaluate sentiment analysis systems more throughly, each sentence in our evaluation set is tagged with the polarity of the sentiment as well as the category and the strength of the sentiment. We divide kinds of sentiment into 7 positive categories and 15 negative categories. Each category is given the strength of the sentiment from 1 to 3. Our evaluation set consists of 3,270 sentences extracted from various social media. For each sentence, 5 human taggers assigned the category and the strength of the sentiment expressed in the sentence. The ratio of inter-taggers agreement was 93% in the polarity, 70% in the category, 58% in the strength of sentiment. The ratio of inter-taggers agreement our evaluation set is a bit higher than other evaluation sets developed for German and Spanish. This result shows our evaluation set can be used as a reliable resource for the evaluation of sentiment analysis systems.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.5
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• pp.597-606
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• 1998

The purposes of the study were 1) to evaluate the visual image of colored Korean traditional dress for woman 2) to analyze the colors and, color combinations effect on the image perception using gestalt theory. The research method was a quasi-experimental with a between subjects design. The experimental materials developed for the study were a set of stimuli and a response scale. The stimuli was consisted of 17 drawings of females wearing Korean tradinational dress, by using CAD simulation. A response scale consisted of semantic differential scales. The subjects were 1138 undergraduate students of Taejon city, Chungnam province and Chungbuk province. Their responses to the semantic differential scales were analyzed using factor analysis, one-way ANOVA, Duncan's multiple range test, 1-test. Results were as follows; 1) The image of the stimulus was consisted of the 4 different dimensions.(sociability, evaluation, visibility, attractiveness) 2) Clothing colors had significant effects on image perception of the evaluation dimension, visibility dimension and attractiveness dimension in the mono-color set. The blue showed the most positive image on the evaluation dimension, and the yellow and the gray showed negative image on the same dimension. The yellow showed the most salient image and the gray showed the least salient image on the visibility dimension. The red showed the most attractive image and the green showed the least attractive image on the attractiveness dimension. 3) In hi-color set stimulus, the perceived image was influenced by color combinations. The yellow blouse-the red skirt set showed the most sociable image on the sociability dimension. The blue blouse-the green skirt set showed the most positive image on the evaluation dimension. The yellow blouse-the red skirt set showed the most salient image and the blue blouse-the green skirt set showed the least salient image on the visibility dimension. And the red blouse-the yellow skirt set showed the most attractive image on the attractiveness dimension. On conclusion the visual image of Korean traditional dress wearer was affected by dress colors and color combinations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.23
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• pp.57-64
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• 1991

The preliminary, advanced and final evaluation of R&D project is essential in order to reduce loss of resource and opportunity and to minimize uncertainty resulting from optimal selection and efficient progress of R&D project. This thesis examined characteristics of deterministic evaluation, economical evaluation, and OR-approach evaluation as theoretical methodology of evaluation of R&D project applicable to food industry in Korea by using scoring method, one of deterministic evaluations. In addition, this thesis divided the evaluation factors for preliminary evaluation of R&D project into 5 groups and 30 factors on basis of the environment of domestic companies and set up the standard of each evaluation factors and contains marking-selecting way. But, generally, the evaluation model by this thesis, as the conditions of the business company environment are different to each other, contents to be set up evaluation factors, evaluation standard and decision method conforming to each the environment of the business companies with referring to as one standard of evaluation project for selecting R&D project.

• Journal of the Korea Society for Simulation
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• v.10 no.2
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• pp.61-74
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• 2001

The reliability evaluation of the large scale network becomes very complicate according to the growing size of network. Moreover if the reliability is not constant but follows probability distribution function, it is almost impossible to compute them in theory. This paper studies the network evaluation methods in order to overcome such difficulties. For this an efficient path set algorithm which seeks the path set connecting the start and terminal nodes efficiently is developed. Also, various variance reduction techniques are applied to compute the system reliability to enhance the simulation performance. As a numerical example, a large scale network is given. The comparisons of the path set algorithm and the variance reduction techniques are discussed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.46-53
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• 2019

When a partitioned structure is derived from a data set using a clustering algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of data. This problem is known as the order bias problem. Many algorithms in machine learning fields try to achieve optimized result from available training and test data. Optimization is determined by an evaluation function which has also a tendency toward a certain goal. It is inevitable to have a tendency in the evaluation function both for efficiency and for consistency in the result. But its preference for a specific goal in the evaluation function may sometimes lead to unfavorable consequences in the final result of the clustering. To overcome this bias problems, the first clustering process proceeds to construct an initial partition. The initial partition is expected to imply the possible range in the number of final clusters. We apply the data centric sorting to the data objects in the clusters of the partition to rearrange them in a new order. The same clustering procedure is reapplied to the newly arranged data set to build a new partition. We have developed an algorithm that reduces bias effect resulting from how data is fed into the algorithm. Experiment results have been presented to show that the algorithm helps minimize the order bias effects. We have also shown that the current evaluation measure used for the clustering algorithm is biased toward favoring a smaller number of clusters and a larger size of clusters as a result.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.5
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• pp.17-26
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• 2022

In this study, in order to establish the criteria for evaluation of importance by the type of facility specialized for agricultural reservoirs, an expert group consisting of a total of 167 members who were in management, or specialized in the fields of design, research, and diagnosis were organized, and the importance for facilities was set with application of the AHP technique. The importance of dam body, spillway, and intake structure composing a reservoir were set at 59%, 24%, and 17%, and the importance of dam crest, upstream slope, and downstream slope constituting a dam body was set at 32%, 31%, and 37%, respectively. In addition, the importance of approach channel, regulated channel, chute channel, and stilling basin consisting a spillway was set at 15%, 44%, 26%, and 15%, and the importance of inclined conduit and outlet conduit consisting an intake structure was set at 35% and 65%, respectively. The safety grade of the reservoirs evaluated by applying the newly presented importance values in this study showed the rearrangement of the grades with a change of 11% compared to the previous grades. In this way, the newly established criteria are expected to be utilized as basic data with strategic importance in reservoir safety management and disaster prevention as well as the operation of systems in the future.