• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.97-113
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• 2009

Collaborative filtering(CF) has been a very successful approach for building recommender system, but its widespread use has exposed to some well-known problems including sparsity and scalability problems. In order to mitigate these problems, we propose two novel models for improving the typical CF algorithm, whose names are ISCF(Item-Selected CF) and USCF(User-Selected CF). The modified models of the conventional CF method that condense the original dataset by reducing a dimension of items or users in the user-item matrix may improve the prediction accuracy as well as the efficiency of the conventional CF algorithm. As a tool to optimize the reduction of a user-item matrix, our study proposes genetic algorithms. We believe that our approach may relieve the sparsity and scalability problems. To validate the applicability of ISCF and USCF, we applied them to the MovieLens dataset. Experimental results showed that both the efficiency and the accuracy were enhanced in our proposed models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.61-68
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• 2012

Recommender Systems have gained much popularity among researchers and is applied in a number of applications. The exponential growth of users and products poses some key challenges for recommender systems. Recommender Systems mostly suffer from scalability and accuracy. The accuracy of Recommender system is somehow inversely proportional to its scalability. In this paper we proposed a Context Aware Hybrid Recommender System using matrix reduction for Hybrid model and clustering technique for predication of item features. In our approach we used user item-feature rating, User Demographic information and context information i.e. specific time and day to improve scalability and accuracy. Our Algorithm produce better results because we reduce the dimension of items features matrix by using different reduction techniques and use user demographic information, construct context aware hybrid user model, cluster the similar user offline, find the nearest neighbors, predict the item features and recommend the Top N- items.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.321-327
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• 2013

Impaired naming difficulty is common in normal elderly as well as in patients with neurological impairment. The 60-item Korean version-Boston Naming Test(K-BNT) is one of the most commonly used test for measuring confrontational naming ability. However, age-related cognitive decline may make the elderly difficult concentrating during the 60-item test, therefore, item reduction of the K-BNT would improve test validity and reliability. Thus, the purpose of this study was to develop a short form of the K-BNT based on Item Response Theory(IRT). Considering item-fit index, sex factor, and item difficulty through Rasch analysis, the 15-item K-BNT(i.e., K-BNT-15) was developed. Via administration of the K-BNT-15, we observed age-related decline in naming ability and significantly different performance between the normal elderly and patients with mild cognitive impairment. This study demonstrates the utility of IRT for developing a short-form language evaluation tool. The K-BNT-15 can be effective as a language screening tool to differentiate between normal aging and pathological diseases.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.39-46
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• 2023

Purpose: The small-scale environmental impact assessment system in Korea was introduced and implemented in August 2000, but it has a problem that it cannot guarantee implementation due to the large proportion of qualitative reduction measures for each evaluation item. Therefore, when preparing a small-scale environmental impact assessment, research was conducted on how to improve the existing simple listing-type reduction measures and qualitative evaluation standards to quantitative reduction measures and evaluation standards reflecting regional characteristics. Research design, data and methodology: The small-scale environmental impact assessment system in Korea was introduced and implemented in August 2000, but it has a problem that it cannot guarantee implementation due to the large proportion of qualitative reduction measures for each evaluation item. Therefore, when preparing a small-scale environmental impact assessment, research was conducted on how to improve the existing simple listing-type reduction measures and qualitative evaluation standards to quantitative reduction measures and evaluation standards reflecting regional characteristics. Results: As a result of the analysis of qualitative and quantitative factors, the arithmetic sum of the qualitative factors of the total six projects is 160, accounting for 80% of the total number of reduction measures, and the quantitative factors are 40, accounting for 20%. Among them, the number of qualitative reduction measures reached 97.4% for animal and plant items, and more than 90% for air quality, noise and vibration, and eco-friendly resource circulation items. Conclusions: Therefore, it is necessary to avoid establishing qualitative reduction measures and set quantitative measures as the basis, but to specify the specifications, size, and installation location related to the reduction measures, and to calculate the numerical reduction efficiency.

• Journal of Korean Critical Care Nursing
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• v.15 no.3
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• pp.37-50
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• 2022

Purpose : This study aimed to examine the item characteristics of the Korean version of the intensive care experience questionnaire (K-ICEQ) using the Rasch analysis model of the item response theory. Methods : In this methodological study, the validity of the scale was examined, and a secondary analysis was conducted using cohort data of patients who were discharged from the intensive care units (ICU). Data from 891 patients who responded to the K-ICEQ upon ICU discharge were analyzed. The WINSTEP program was used to analyze item characteristics, including item difficulty, fit indices, appropriateness scale, and separation reliability. Results : The difficulty level of all 26 items of the K-ICEQ was appropriate, and the fit indices of the 25 items, except for item 18, were good. The 5-point scale of the K-ICEQ was not appropriate in the three subscales. The item separation reliability was good in all subscales, but did not meet the criteria in terms of respondents. Conclusion : The results of examining the item characteristics of the K-ICEQ revealed a good degree of difficulty, fitness, and item separation reliability. To increase the validity of the K-ICEQ, we suggest the rearrangement of the overall item order, modification of the item description of the "recall of experience" subscale, and reduction of the scale response level.

• The Korean Journal of Emergency Medical Services
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• v.28 no.2
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• pp.7-19
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• 2024

Purpose: To adjust item numbers in a national test, this study used item response theory to examine changes in average scores, reliability, difficulty, and discrimination according to the adjustment of item numbers. Methods: We analyzed the dichotomous coding of correct and incorrect answers of 473 examinees in a mock test conducted in 2023. Additionally, as an explanatory pilot study, we used an online questionnaire to survey experts on their perceptions of the appropriate item numbers for each test subject from January 18, 2024, to February 15, 2024. Results: Regarding the item numbers on the national exam, experts preferred to reduce the number of management of emergency patients (33.14±6.09, p<.05) and advanced emergency medical care: subtopics (104.49±11.55, p<.05), and the total number of questions (217.82±20.95, p<.05). In a simulation set in which items with low item fit were removed after fitting a two-parameter item response theory model, reliability was maintained at .910 until the 5th test consisting of 185 questions with little loss of difficulty, discrimination, and average score, and there was no correlation between item numbers and average score. Conclusion: Experts responded that reducing the number of items on the national exam was appropriate. As a result of the item reduction simulation, there was no significant loss in the average score, difficulty, discrimination, or reliability. More reliable results could be obtained if the results were based on a validity analysis and analyzed using actual national exams.

• The Korean Journal of Food And Nutrition
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• v.29 no.5
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• pp.818-827
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• 2016

This study was conducted to develop and validate the Sugar Intake Reduction Test (SIRT) for young children, and included eating behaviors, attitude, and nutritional knowledge about sugars. A draft version of the SIRT was developed after literature review. The final draft of the SIRT was established after two pilot tests of 5 year old children and an expert group's review, and is comprised of a one on one test between an investigator and a child using picture tools. It contained of 20 questions which included 3 components: eating behaviors (5 items), preference for sugar sweetened food (10 items), and nutritional knowledge about sugars (5 items). The final SIRT was conducted on 181 children 5 (n=100) to 6 (n=81) years old, to examine its item and test adequacies. The passing rate of most items significantly increased with increasing age, and most of the item discrimination also differed significantly between the below and upper score groups. The content validity was given a high score by professionals (mean score 3.9 out of 4). Reliability of all the items in the SIRT was high (Cronbach's ${\alpha}=0.82$). Moreover, the total component and the sub-component scores of the SIRT correlated significantly. Our results indicate that the SIRT is a valid tool to measure sugar intake reduction in young children aged 5~6 years.

• IE interfaces
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• v.11 no.2
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• pp.191-197
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• 1998

Having a reliable standard time data is very important for productivity improvement of any manufacturing company. In this study we present an estimation procedure of standard time data for companies having multi-item extremely small quantity production type and discuss a case study. Included in the discussion are the importance of setup time reduction and the roles of management supervisors, and labor.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.285-290
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• 2009

An association rule mining has been studied to find hidden data pattern in data mining. A realization of fast processing method have became a big issue because it treated a great number of transaction data. The time which is derived by association rule finding method geometrically increase according to a number of item included data. Accordingly, the process to reduce the number of rules is necessarily needed. We propose the T-algorithm that is efficient rule reduction algorithm. The T-algorithm can reduce effectively the number of association rules. Because that the T-algorithm compares transaction data item with binary format. And improves a support and a confidence between items. The performance of the proposed T-algorithm is evaluated from a simulation.

• IE interfaces
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• v.20 no.1
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• pp.41-48
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• 2007

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.