• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.72-77
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• 2011

Dynamic Line Rating (DLR) techniques have been greatly worthy of notice for efficiently increasing transmission capacity as well as controlling load-flow in overhead transmission lines, in comparison with the existing power system operating with Static Line Rating (SLR). This paper describes an utilization method to implement DLR control system for old transmission lines built in the first stage using the ground clearance design standard with lower dips. The suggested DLR system is focused on designing as temperature control system rather than current/load control system. Based on several performance for conductor temperatures, it is shown that DLR system with efficiency can be implemented.

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.39-44
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• 2009

Entering in the time of high oil price, seriousness of an energy effect sector has given a huge impact and the importance of energy is growing. Especially, building energy occupying 24% of total demand of energy is expected to be possible to reduce energy demand more than other section. To reduce the building energy consumption, this study analyzes function and thermal performance of Super window by heat experimental apparatus. Super window is a 2-track low-e glazing window for high insulation efficiency. By applying the results of this experiment to building energy efficience rating tool, this study compares energy efficiency rates depending on a region.-Jeju, South, Central. And it shows how much does Super window reduce Building energy consumption.

• Health Policy and Management
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• v.15 no.1
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• pp.97-117
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• 2005

This study was designed to compare the differences m results of supervisor and subordinate rating. Data was collected from personnel evaluation and subordinate rating results for middle managers(n=68) in hospital from 3rd January to 20th March in 2004. Supervisor rating consisted of performance, ability and attitude evaluation. Subordinate rating consisted of leadership, ability and attitude evaluation. Collected data included sociodemographic characteristics, work department, work level, years of work, years at present level and whether working in a patient serving department. The difference of standardized supervisor and subordinate rating score was used to define groups as 'higher in supervisor rating group'. Groups were defined in total score, ability score and attitude score. Main results were as follows: 1. In total score, sectional chiefs were apt to be 'higher in subordinate rating group' while chief clerks were apt to be 'similar group' or 'higher in supervisor rating group'. Staffs in patient serving department were likely to be 'higher in supervisor rating group' and staffs in non-patient serving department were likely to be 'higher in subordinate rating group'. All these results were statistically significant. 2. In ability score, there were no statistically significant differences in age, sex, years of education, work department, work level, years of work and whether working in a patient serving department among 'higher in supervisor rating group', 'similar group' and 'higher in subordinate rating group'. 3. In attitude score, staffs in the department of medical affairs and the department of administration were apt to be 'higher in subordinate rating group'. Staffs in the department of nursing were apt to be 'higher in supervisor rating group'. Staffs in a patient serving department were likely to be 'higher in supervisor rating group' and staffs in a non-patient serving department were likely to be 'higher in subordinate rating group'. All these results were statistically significant. 4. Logistic analysis about total score showed that sectional chiefs had higher Odds Ratio(OR) to be in 'higher in subordinate rating group'. Staffs in a non-patient serving department had higher OR to be in 'higher in subordinate rating group'. Both these results were statistically significant. 5. Logistic analysis about ability score showed that sectional chiefs had higher OR to be in 'higher in subordinate rating group'. Staffs in a non-patient serving department had higher OR to be in 'higher in subordinate rating group'. These results were not statistically significant. 6. Logistic analysis about total score showed that sectional chiefs had higher OR to be in 'higher in subordinate rating group', but the difference was not statistically significant. Staffs in a non-patient serving department had significantly higher OR to be in 'higher in subordinate rating group'. In conclusion, there is no clear superiority between supervisor and subordinate rating in personnel evaluation. It would be better to use a mixed model. It's also suggested to use an intervening rate of application or scores considering work levels and work department in personnel evaluation. These results would be helpful for hospitals planning a supervisor and subordinate rating system for personnel evaluation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.221-226
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• 2021

Collaborative filtering based recommender systems recommend user-preferrable items based on rating history and are essential function for the current various commercial purposes. In order to determine items to recommend, prediction of preference score for unrated items is estimated based on similar rating history. Previous studies usually employ two methods individually, i.e., similar user based or similar item based ones. These methods have drawbacks of degrading prediction accuracy in case of sparse user ratings data or when having difficulty with finding similar users or items. This study suggests a new rating prediction method by integrating the two previous methods. The proposed method has the advantage of consulting more similar ratings, thus improving the recommendation quality. The experimental results reveal that our method significantly improve the performance of previous methods, in terms of prediction accuracy, relevance level of recommended items, and that of recommended item ranks with a sparse dataset. With a rather dense dataset, it outperforms the previous methods in terms of prediction accuracy and shows comparable results in other metrics.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.605-615
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• 2017

Recently, financial supervisory authority of Korea and international credit rating agencies have been concerned about a stand-alone rating that is calculated without incorporating guaranteed support of parent companies. Guaranteed by parent companies, most foreign subsidiaries keeps good credit rate in spite of weak financial status. However, what if the parent companies stop supporting the foreign subsidiaries, they could have a probability to go bankrupt. In this paper, we have validated a credit rating model through statistical measurers such as performance, calibration, and stability for Korean companies owning foreign subsidiaries.

• Asian Journal of Business Environment
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• v.8 no.1
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• pp.23-29
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• 2018

Purpose - The purpose of this research is to make a comparative assessment of People Credit Funds (PCFs) ranking in Vietnam between the Circular No. 42/2016/TT-NHNN dated December 20, 2016 with the Decision No. 14/2007/QD-NHNN dated 09/4/2007 issued by the Governor of the State Bank. Research design, data, and methodology - This study is mainly based on the Circular No. 42/2016/TT-NHNN dated December 20, 2016 and the Decision No. 14/2007/QD-NHNN dated 09/4/2007 issued by the Governor of the State Bank on PCFs ranking. Results - The study paper has shown positive changes in PCFs ranking in Vietnam in accordance with the Circular No. 42/2016/TT-NHNN, such as increasing Capital Adequacy Ratio (CAR), maintaining CAR, improving assets quality, developing indicators of governance, management and control capability. These changes have implications for the development and efficient performance of PCFs in Vietnam. Conclusions - The classification and evaluation of PCFs will contribute to its healthy development. These finding support PCFs to understand more about rating methodology, significance of rating system and the importance of improving their rating. PCFs in Vietnam desire to develop their business effectively, they need to understand exactly and comply fully with regulations related to their field of operations.

• KIEAE Journal
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• v.15 no.5
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• pp.75-82
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• 2015

Purpose: The first grade of Korea's Building Energy Efficiency Rating System(BEERS) is required for new government office buildings as a mandatory measure to reduce greenhouse gas emission. However, there is no specific criteria about performance that which level should apply to energy-saving design element for obtaining Building Energy Efficiency Rating 1st grade. Therefore, Certification status should be analyzed firstly, about the office building which is certificated. Certification analysis for office buildings acquired certification therefore should be done first. Method: In this study, Certification status(Office buildings acquired Building Energy Efficiency Rating Certification)was analyzed by classified year, region, specific scale etc. And we analyzed statistically by eliciting an average value of each element influencing to the amount of energy. Result: Energy demands were gradually decreased due to revision of thermal insulation standards for enhanced u-value. Energy consumptions were different from the kind of equipment and yearly trends applied depending on the size of the building. Total primary energy consumptions were influenced by heat source types and the primary energy scale factors.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.7
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• pp.66-73
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• 1995

Rating systems of bevel gears(straight, spiral, and zerol bevel gears) which are commonly used as power transmission devices for non-papallel axes are developed on the personal computer, which analyze and/or evaluate the gear design and the service performance at the point of view of strength and durability. The typical considerations of the ratings are the bending strength, the surface durability, and the scoring resistance. The ratings are carried out using the reliable standards of AGMA & Gleason Works. Therefore, the system is built so that the variables or factors considered differently in those standards and the strength, dura- bility, and scoring partially in Gleason are appraised seperately by each method, and a series of the estimation processes is integrated into the system so as to compare each result. The developed rating systems can be used in the initial stage of gear design process, and also a better design can be performed by the evaluation of the initial design at the view point of gear strength and durability. Additionally, it is useful for the trouble-shooting of bevel gear system and to the purpose of introducing the methods for maintaining design strength in service, with appraising the gear strength after design or with appraising the influencing factor as a whole. Therefore, this rating systems can help the aim of design automation of bevel gears.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.510-514
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• 2004

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is known to be the most successful recommendation technology, but its widespread use has exposed some problems such as sparsity and scalability in the e-business environment. In this paper, we propose a recommendation methodology based on Web usage mining and product taxonomy to enhance the recommendation quality and the system performance of original CF-based recommender systems. Web usage mining populates the rating database by tracking customers' shopping behaviors on the Web, so leading to better quality recommendations. The product taxonomy is used to improve the performance of searching for nearest neighbors through dimensionality reduction of the rating database. Several experiments on real e-commerce data show that the proposed methodology provides higher quality recommendations and better performance than original collaborative filtering methodology.