• Journal of the Korean Solar Energy Society
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• v.29 no.4
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• pp.48-57
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• 2009

Energy demands for hotels in Korea are surveyed and statistically analyzed to develop calculation models for a simulation. Daily energy loads of 16 hotels located in Seoul, Busan, Daegu, Inchon, and Daejon are analyzed based on energy log sheets. Detailed hourly loads are field measured for 3 hotels that are carefully selected among the surveyed. One of the salient features for energy consumption by hotels is their weekly periodicity. Relatively large values of deviations are observed for both heat and electricity loads through the country. The mains factors are: location, hotel grade (luxuriousness) and insulation. Detailed quantitative information such are annual average, daily variation, and hourly patterns are provided.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.33 no.12
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• pp.53-63
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• 2017

The purpose of this study is to present an integrated analysis for energy use and its patterns as vertical locations of the dwelling units in apartment buildings which are located in an urban area and constructed by a renowned contractor. In order to enhance the effectiveness of the method, the original data of electricity, water, and gas bills which directly reflect the energy use are sorted and analyzed into several groups as vertical locations in each building. And also, by use of comparing and contrasting the data on a monthly and yearly basis, the accuracy of analyses for seasonal energy use and its patterns is strengthened. Comparative analyses used in this study describe the results that vertical locations of dwelling units do not have much influence on electricity and water usage, but are closely related with gas usage for a heating season. According to the analysis of gas usage, the units on the ground and right above pilotis need enhancement in the insulations for heating to mitigate energy loss. Also, the analysis for the middle floor units in each group describe the fact that the gas usage of the units on the ground is consumes 1.5 times greater than that of the typical floors. Therefore, enhanced insulation strategies need to be considered against the adverse condition that the heat loss increases as the wall facing the outside air increases or as the wind velocity increases through the pilotis.

• Transactions of the KSME C: Technology and Education
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• v.4 no.1
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• pp.27-34
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• 2016

This preliminary study investigated data mining-based methods to assess and predict the performance of geothermal heat pump(GHP) system. Data mining is a key process of the knowledge discovery in database (KDD), which includes five steps: 1) Selection; 2) Pre-processing; 3) Transformation; 4) Analysis(data mining); and 5) Interpretation/Evaluation. We used two analysis models, categorical and numerical decision tree models to ascertain the patterns of performance(COP) and electrical consumption of the GHP system. Prior to applying the decision tree models, we statistically analyzed measurement database to determine the effect of sampling intervals on the system performance. Analysis results showed that 10-min sampling data for the performance analysis had highest accuracy of 97.7% over the actual dataset of the GHP system.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.1
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• pp.80-86
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• 2011

Vertical open display cabinets are widely used in shopping mall, supermarkets, retail stores. Maintaining the temperature of foods in the display cabinet is vitally important to retailers to ensure optimal food quality and safety. The purpose of this study is to reduce the infiltration of air and heat loss from ambient space to display cabinet. The three-dimensional Computational Fluid Dynamics(CFD) simulation is used for the analysis of air flow patterns and temperature distribution in refrigerated display cabinets. Under several operating conditions which vary both the inner and outer jet velocities in the range from 0.3 to 1.1 m/s, simulations were carried out. This paper presents a performance of display cabinets with single jet and double jet. The energy consumption due to thermal entrainment ratio is plotted with varying Re. It was found that the double jet system is better than single jet system in terms of temperature distribution and energy saving.

• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.3
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• pp.149-156
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• 2018

Traditional medicines (TM) in Korea, China, and Japan share most of the theories and therapeutic tools, but there are also differences due to their unique histories and cultures. Here, we aim to identify the differences in the utilization of TM theory between three countries by analyzing herb usage data in terms of the related traditional theories. Herb usage data of each country was collected from "Investigation of Korean medicine use and herbal medicine consumption survey" (Korea), "Analytical report on circulation of key Chinese medicinal materials" (China), and "Survey report on raw material crude drug usage" (Japan). Fifty five herbs with sixty features belonging to five theoretical categories (four properties, five tastes, targeting meridians, treatment strategies, and herbal parts) were selected and analyzed. Weight Sum Model (WSM) and Network-Based Group Features (NBGF) were used to compare the theoretical characteristics of TM between three countries. For the statistical evaluation, we developed and applied Herb Set Enrichment Analysis (HSEA) for WSM and NBGF results. HSEA for WSM results revealed the kidney meridian were targeted more in Korea than Japan, while the spleen meridian were targeted more in Japan than Korea. Herbs with sour taste were used more in Japan than China. HSEA for NBGF results found that NBGF including warm, neutral, sweet, and tonifying features were more dominant in Korea and than Japan, while NBGF including cold, bitter, heat-clearing features were more dominant in Japan than the others. These results suggest that TM in Korea, China, and Japan have unique aspects of practice patterns and theoretical utilization.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.1
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• pp.16-24
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• 1999

Residual stress is one of the causes which make defects in engineering components and materials. And interest in the measurement of residual stress exists in many industries. There are commonly used methods by which residual stresses are currently measured. But these methods have a little demerits. time consumption and other problems. Therefore we devised a new experimental technique to measure residual stress in materials with a combination of laser speckle pattern interferometry, finite element method and spot heating. The speckle pattern interferometer measures in-plane deformations while the heating provides for very localized stress relief. FEM is used for determining heat temperature and other parameters. The residual stresses are determined by the amount of strain that is measured subsequent to the heating and cool-down of the region being interrogated. A simple model is presented to provide a description of the method. In this paper, the ambiguity problem for the fringe patterns has solved by a phase shifting method.