• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.1
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• pp.111-118
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• 2002

Currently, the inspection of bridges is conduced for the parts or elements of a bridges and the results of inspection are depicted for those local elements. Therefore, the representative rating of a bridge as a whole bridge system is not presented. The purpose of the present study is to purpose a reasonable method which can yield realistic representative rating for an actual bridge. The purpose method consists of two steps, i.e, visual inspection step and safety assessment step. The importance of members is considered by introducing the weighting factors and the number of spans is also considered to obtain the representative rating of a whole bridge system. The purpose method may be efficiently used to calculate the realistic representative rating bridge structures.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.242-247
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• 2009

Recently an intelligent system is developed for the service what users want not a passive system which just answered user's request. This intelligent system is used for personalized recommendation system and representative techniques are content-based and collaborative filtering. In this study, we propose a prediction system which is based on the techniques of recommendation system using a collaborative filtering and a fuzzy system to solve the collaborative filtering problems. In order to verify the prediction system, we used the data that is user's rating about movies. We predicted the user's rating using this data. The accuracy of this prediction system is determined by computing the RMSE(root mean square error) of the system's prediction against the actual rating about the each movie and is compared with the existing system. Thus, this prediction system can be applied to base technology of recommendation system and also recommendation of multimedia such as music and books.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.83-89
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• 2022

As a representative technique of recommender systems, collaborative filtering has been successfully in service through many commercial and academic systems. This technique recommends items highly rated by similar neighbor users, based on similarity of ratings on common items rated by two users. Recently research on time-aware recommender systems has been conducted, which attempts to improve system performance by reflecting user rating time of items. However, the decay rate uniform to past ratings has a risk of lowering the rating prediction performance of the system. This study proposes a rating time-aware similarity measure between users, which is a novel approach different from previous ones. The proposed approach considers changes of similarity value over time, not item rating time. In order to evaluate performance of the proposed method, experiments using various parameter values and types of time change functions are conducted, resulting in improving prediction accuracy of existing traditional similarity measures significantly.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.89-115
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• 2000

The present study attempts to (1) identify the critical dimensions that affect job performance of computer programmers and (2) clarify the specific behaviors that are related to each performance dimension, and measure them fairly and accurately. In particular, this study focus on producing a Behaviorally anchored Rating Scales (BARS) with a high level of acceptability by both raters and rates. 422 computer programmers from 8 companies participated in the process of developing the scale, which consisted of typical 5 phases. The results demonstrated that 13 performance dimensions were derived and the final job performance rating scale was made by vertically arraying 5 representative behavior anchors order by their scale value for each of 13 dimensions.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.19 no.2
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• pp.89-95
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• 2008

Subjective voice evaluation is necessary and important to assess the voice disorders in addition to objective voice evaluation. Subjective voice evaluation is divided into examiner and examinee subjective voice assessment. The examiner assessment represents perceptual judgment to the patient's voice such as GRBAS scale, Buffalo voice profile, consensus auditory perceptual evaluation of voice (CAPE- V) and so on. The examinee assessment consists of indirect method including voice handicap index (VHI), voice outcome survey (VOS), voice symptom scale (VoiSS), voice related quality of life (V-ROQL) and direct method which is called patient's self-subjective voice rating. This review article describes a general rule, advantages and pitfalls about GRBAS scale, VHI and patient's self-subjective voice rating which are presently most representative voice assessment tools.

• Survey Research
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• v.1 no.2
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• pp.89-115
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• 2000

The present study attempts to (1) identify the critical dimensions that affect job performance of computer programmers and (2) clarify the specific behaviors that are related to each performance dimension, and measure them fairly and accurately. In particular, this study focus on producing a Behaviorally Anchored Rating Scales(BARS) with a high level of acceptability by both raters and ratees. 422 computer programmers from 8 companies participated in the process of developing the scale, which consisted of typical 5 phases. The results demonstrated that 13 performance dimensions were derived and the final job performance rating scale was made by vertically arraying 5 representative behavior anchors ordered by their scale value for each of 13 dimensions.

• Journal of the Korean Society of Costume
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• v.54 no.7
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• pp.91-106
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• 2004

The purpose of this study was to review the previous researches, analyze the clothing image, the make-up image and compare the analyses of clothing image and make-up image. The previous researches of clothing image and make-up image were reviewed in 6 kinds of Journal. The results of previous research review and analysis were followed as : Measuring mean of image are used to similarly that semantic differential technique and summated rating technique. Attention to proposed researcher abstraction image in make-up image, but there is problem that this hard to explain objectivity of image abstraction. There are a lot of occasions that 4 or 5 image factors were extracted by factor analysis. The make-up image researches that presented image stimulus were more than study that do not present. Image words were classified which were compiled words have similar sub image. Grace, activeness, lively. unique, modernity attractive, feminine. sexy and ripeness clothing images were classified factors. which were representative clothing image. Elegance, Sophisticate. romantic, natural, modern and youthfulness make-up image for factor were representative make-up image factors. However the problems were found that some representative image factor included the sub images which were different from some factor image. Compared with representation image words, same image words were used to not agree what clothing image and make-up image. Standardization of word should be made that show that clothing image and make-up image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.138-153
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• 2010

The interactions between people who do not know each other have been greatly increased with the on-going increase of people's cyberspace activities. In this situation, there exist potential risk factors such as the possibility of fraud, so we need a method to reduce or eliminate those risk factors. Concerning this necessity, rating systems are widely used, and many trust metrics calculated from rate values that people give to each other are proposed to help them make decisions. However, the trust metrics decrease the accuracy, and this is caused by the different rating scales and ranges of each person. So, we propose a fuzzy adjustment method to solve this problem. It is possible to catch the exact meaning of the trust value that each person selects through applying fuzzy sets, which improve the accuracy of the trust metric calculated from the trust values. We have applied our fuzzy adjustment method to the TidalTrust algorithm, a representative algorithm for calculating the local scalar trust metric, and we performed an experimental evaluation with four data sets and three evaluation methods.

• KIEAE Journal
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• v.17 no.2
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• pp.13-20
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• 2017

Meteorological data is one of the important factors in the calculation of building energy demand. The purposes of this study are to review the limitations of the typical meteorological data of ECO2 program and to create the new typical meteorological data and then analyze the building energy demands for additional regions which are not included in the existing 13 region in the ECO2 program. The extended typical meteorological data to a total of 33 regions were based on IWEC(International Weather for Energy Calculations) data files and were created in the form applicable to the building energy efficiency rating certification system. As a result of comparing the heating energy demands of a representative region with the surrounding regions in each of five regions in Korea, the variance of Cv(RMSE) ranged from 36% to 344% and MBE ranged from -32% to 190% for the whole regions. This suggests that the difference of heating energy demand may vary greatly depending on the region where the meteorological data is used and the meteorological data of more detailed regions is needed for reliable calculation of building energy demand.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.111-122
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• 2023

The purpose of this study is to verify the factors affecting survival time by estimating survival rate and survival time using non-financial information of social enterprises using credit guarantee in credit guarantee institutions, and provide information to stakeholders to improve survival rate and employ to contribute to maintaining and expanding the As a research method, survival analysis was performed using a non-parametric analysis method, Kaplan-Meier Analysis. As a sample, 621 companies (577 normal companies, 44 insolvent companies) established between 2009 and 2018 were selected as the target companies. As a result of examining the factors affecting survival time by classifying social enterprise representative information and corporate information, representative credit rating, representative home ownership, credit transaction period, and corporate credit rating were derived as significant variables affecting survival time. In the future, financial institutions will be able to induce corporate soundness by reflecting factors that affect survival when examining loans for social enterprises, contributing to job retention and reduction of social costs. Supporting organizations such as the government and private organizations will be able to use it in various ways, such as policy establishment and education and training for the growth and sustainability of social enterprises. With this study as an opportunity, I hope that research will continue with more interest in the factors influencing social enterprise performance as well as corporate insolvency.