• Nuclear Engineering and Technology
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• v.30 no.5
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• pp.416-423
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• 1998

Many studies for the perforated plates have been done, especially on the subject of static behavior and stress distribution in the plate. Equivalent elastic properties are one of the successive concepts for this problem. However little effort was taken to get their dynamic characteristics. In this paper finite element modal analysis was performed for the perforated plates having square and triangular hole patterns. An attempt to use existing equivalent elastic properties into the modal analysis of the plate was carried out. To verify feasibility of the finite element models, modal test was also performed on one typical perforated plate. System parameters such as natural frequencies and mode shapes were extracted and compared with the analysis results.

• Korean Journal of Community Nutrition
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• v.6 no.3
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• pp.371-379
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• 2001

The present study was conducted to determine whether the food shortage situation in North Korea has affected its people differentially according to social class. We performed a literature search on North Korean books and documents on food and nutrition. We also conducted a mail survey on North Korean defectors to estimate the energy and nutrient intake and the practice of foraging for wild foods at the time of food crisis in North Korea. The subjects were 150 adults, 104 men and 46 women, aged 20 years and older, who resettled in the South Korea after the food crisis. The mean energy intakes for men and women were estimated to be 1,260 kcal and 980.6 kcal, respectively, which were far less than 2,900 kcal and 2,600 kcal, the intake levels recommended for North Korean men and women, respectively. Thirty seven percent of the subjects reported a lack of foods adequate enough for work and other daily activities, and fifty seven percent reported a routine use of wild foods such as roots, grass, stalks, and tree bark with an average of 4 items per day. Food consumption patterns on a typical day were different by social classes with the high class people consuming an affluent diet in the midst of a severe food shortage.

• KIEAE Journal
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• v.13 no.5
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• pp.51-57
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• 2013

Energy saving starts by knowing how much energy is being consumed. A building factor is easier than any other things in energy saving. Since, especially, it is closely connected with user's space-use-patterns and manager's utility-operation-style. An energy metering system lets building users know about energy consumption pattern in buildings and measure energy in real time. Development and materialization of metering systems need more careful plans, so that they depend on a demand of individual facilities and available infrastructures they used to use. But, so far, there is no guidelines how to install metering systems. This paper suggested how to install meters and researched a method for how to analyze by using metered data. For that, Green Building in KIER is used as a test bed. As the results, nevertheless the smallest number of meters is basically one for the whole building energy measuring, it is too limited in analysis. So we needed to add the sort of fuel and utility types and found that it depends on all cases. For this reasons, a guideline should be created in order to install meters as soon as possible. It would be suggest a way to save more energy in building factor.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.451-460
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• 2013

This paper presents the necessary elements and data flow in developing a monitoring system of energy usage for apartment houses with a Smart TV. Energy consumption data in each home are collected and analyzed in the HUB station by way of measuring instruments. And the amount of energy usage, such as electricity, gas, hot water, heating, water and other utilities are displayed through the Smart TV application. Energy consumption Database in the HUB station are processed and displayed in the browser of a Smart TV through XML, JAVASCRIPT and Flash. Smart TV users can get the energy consumption status through the energy consumption analysis display of the Smart TV application and improve the energy efficiency by comparing the usage patterns with neighboring houses. And the application display energy usage information, consumption ranking, rates to user as well. Furthermore, usage of last month or year can be compared to help to reduce the energy usage. The proposed system can provide the information about the amount of energy use to be reduced and the warning on the waste of energy.

• Korean Institute of Interior Design Journal
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• v.21 no.2
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• pp.35-45
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• 2012

The development of digital media made the change of architectural paradigm from tectonic to the surface and pattern. This means the transition to the new kind of materiality and the resurrection of ornament. This study started as an aim to apply biological pattern to architectural design from the new perception of pattern. Architectural patterns in the early era appeared as ladders, steps, chains, trees, vortices. But since 21st century, we can find patterns in nature like atoms and molecular structures, fluid forms of dynamics and new geometrical pattern like fractal and first of all biological patterns like viruses and micro-organisms, Voronoi cells, DNA structure, rhizomes and various hybrids and permutations of these. Pattern became one of the most important elements and themes of contemporary architecture through the change of materiality and resurrection of ornament with the new perception of surface in architecture. One of the patterns that give new creative availability to the architectural design is biological pattern which is self-organized as an optimum form through interaction with environment. Biological patterns emerge mostly as self-replicating patterns through morphogenesis, certain geometrical patterns(in particular triangles, pentagons, hexagons and spirals). The architectural application methods of biological patterns are direct figural pattern of organism, circle pattern, polygon pattern, energy-material control pattern, differentiation pattern, parametric pattern, growth principle pattern, evolutionary ecologic pattern. These patterns can be utilized as practical architectural patterns through the use of computer programs as morphogenetic programs like L-system, MoSS program and genetic algorithm programs like Grasshoper, Generative Components with the help of computing technology like mapping and scripting.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.1
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• pp.37-46
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• 2019

The energy of the building is influenced by the user 's activity due to the population, society, and economic characteristics of the building user. In order to obtain accurate energy information, the difference in the amount of energy consumption by the activities and characteristics of building users should be identified. The purpose of the study is to identify the difference in the amount of energy consumption by the user's activities in the same building, and to analyse the relationship between user's activities and demographic, social and economic characteristics. For research, energy simulation is performed based on actual user activity schedule. The results of the simulation were clustered by using K-Means clustering, a machine learning technique. As a result, four types of users were derived based on the amount of energy consumption. The more energy used in a cluster, the lower the user's income level and older. The longer a user's indoor activity times, the higher the energy use, and these activities relate to the user's characteristics. There is more than twice the difference between the group that uses the least energy consumption and the group that uses the most energy consumption.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.151-165
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• 2021

This paper aims to present a novelty damage detection method to identify damage locations by the simultaneous use of both the energy and displacement damage indices. Using this novelty method, the damaged location and even the damaged floor are accurately detected. As a first method, a combination of the instantaneous frequency energy index (EDI) and the structural acceleration responses are used. To evaluate the first method and also present a rapid assessment method, the Displacement Damage Index (DDI), which consists of the error reliability (β) and Normal Probability Density Function (NPDF) indices, are introduced. The innovation of this method is the simultaneous use of displacement-acceleration responses during one process, which is more effective in the rapid evaluation of damage patterns with velocity vectors. In order to evaluate the effectiveness of the proposed method, various damage scenarios of the ASCE benchmark problem, and the effects of measurement noise were studied numerically. Extensive analyses show that the rapid proposed method is capable of accurately detecting the location of sparse damages through the building. Finally, the proposed method was validated by experimental studies of a six-story steel building structure with single and multiple damage cases.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.220-223
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• 1989

Over the last decade or so, there has been an increase in activity devoted to the development of renewable resources for generating electric energy. Many of these generators are small and can only be economically connected to the distribution system or to ths subtransmission system. Those which involve storage, a secondary source of energy, can provide a means to achieve more efficient use of existing generating plant. Such systems are known collectively as Dispersed Storage and Generation devices, or DSGs. So, in this paper various operation patterns for Battery Energy Storgy System which is considered as one of DSG, are examined.

• Environmental and Resource Economics Review
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• v.14 no.2
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• pp.257-290
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• 2005

Korean energy use in industrial sector has increased more rapidly than other sectors during 1980~2000 periods. Relatively higher increases in industrial sector energy consumption raise questions whether government policy of rationalization of industrial energy use has been effective. In this study, we use 80-85-90 and 90-95-00 constant price input-output table to analyze increases in industrial energy use. Using an adjusted version of structural decomposition model introduced by Chen and Rose (1990), we decompose Changes of energy use into 17 elements. We classify entire industry sector into 32 sectors including four energy sectors (coal and coal products, refined petroleum, electricity and town gas). We then analyze changes of energy use by industrial level to check differences among industrial energy demand structures. Finally, we compare three industries, electronic product manufacturing, metal manufacturing and construction, that represent technology and capital intensive, energy and material intensive and labor and capital intensive industry. As results, we find that high energy using industries make the most effort to reduce energy use. Primary metal, petrochemical and mon-metal industries show improvements in elements such as energy and material productivity, energy and material imports, energy substitution and material substitutions towards energy saving. These results imply that although those industries are heavy users of energy, they put the best effort to reduce energy use relative to other industries. We find various patterns of change in industrial energy use at industrial level. To reduce energy use, electronic product manufacturing industry needs more effort to improve technological change element while construction industry needs more effort to improve material input structure element.

• The Journal of Bigdata
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• v.6 no.1
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• pp.127-132
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• 2021

Korea is both a resource-poor country and a energy-consuming country. In addition, the use and dependence on electricity is very high, and more than 20% of total energy use is consumed in buildings. As research on deep learning and machine learning is active, research is underway to apply various algorithms to energy efficiency fields, and the introduction of building energy management systems (BEMS) for efficient energy management is increasing. In this paper, we constructed a database based on energy usage by device per household directly collected using smart plugs. We also implement algorithms that effectively analyze and predict the data collected using RNN and LSTM models. In the future, this data can be applied to analysis of power consumption patterns beyond prediction of energy consumption. This can help improve energy efficiency and is expected to help manage effective power usage through prediction of future data.