• Economic and Environmental Geology
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• v.21 no.3
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• pp.309-318
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• 1988

South Korea has about 50 useful mineral commodities for the mineral resources, among 330 kinds of minerals desoribed. In 1986, she exported 14 mineral commodities of silver, lead, tungsten, molybdenite, ceramic minerals, limestone and graphite etc... And the component ratio of mining industry in the gross national production (GNP) of South korea maintains 1.5% during last five years(1982 to 1986).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.824-827
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• 2011

Needs for Smart Grid development are increasing all over the world as a solution to its problem according to depletion of energy resources, climatic and environmental rapidly change and growing demand for electrical power. Especially decentralized power is attracting world's attention. In this mood a new era for a unit scale of decentralized power environment is on its way in building. However there is a problem to have to be solved in the uniformity of power quality because the amount of power generated from renewable energy resources such as wind power and solar light is very sensitive to climate fluctuation. And thus this paper tries to suggest an energy management algorithm on basis of real time monitoring for meteorological data. The proposed EMS model embodies the method for predicting the power generation by monitoring and analyzing the climatic data and controling the efficient power distribution between the renewable energy and the existing power. The ultimate goal of this paper is to provide the technological basis for achieving zero-energy house.

• Journal of the Korean Home Economics Association
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• v.18 no.1
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• pp.67-82
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• 1980

The objectives of the study were to determine 1) energy uses for residential requirements, 2) if energy consumption and adoption of energy conservation attitudes and practices vary with independent variables family size, stage of family life cycle, homemaker's level of education, income, heating system, and number of electrical household items, and 3) if there is a correlation between energy conservation attitudes and practices. Questionnaires were given to the randomly selected homemakers I Seoul in the summer (September, 1979) and the winter (February, 1980). Analysis of variance and correlation were used to analyzed the data which consisted of 537 usable responses of 895 returned in the summer and 554 responses of 794 returned in the winter. The results are as follows: 1) The order of consumption rate of the direct energy uses for residential requirements was found to be heating and air conditioning, cooking, refrigeration, T.V., lighting, and miscellaneous. 2) Energy consumption and adoption of energy conservation attitudes and practices were significantly related to family size, homemaker's level of education, and the stage of family life cycle. (1) Families of five members revealed higher scores in attitudes and practices than families less than five or more than six. (2) The higher the homemaker's level of education, the more energy consumption and the higher scores I attitudes and practices were found. (3) Families in the middle stage of family life cycle tend to use more energy than younger or older families, but their scores in attitudes and practices were high. 3) There was a significant correlation between energy conservation attitudes and practices. However, the scores of the conservation practices were not as good as the attitudes. It may be attributed to either a lack of knowledge and/or financial difficulties, or a dissonance between the concept and implementation of energy conservation. 4) Recommendations for the energy-saving and energy-related public policies are: (1) to use such human resources as attitudes, values, feelings of agreement, and cooperation, as well as nonhuman resources for the energy conservation, (2) to develop a educational program and a creative system I order to implement energy conservation programs, and (3) to consider direct as well as indirect energy uses I selecting goods and services.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.43-43
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• 2018

Mutation breeding by radiation is useful for improving various crop species. Up to now, a total of 170 soybean mutant varieties have been released in the world, which is the second most registered varieties after rice. Despite the economic importance of soybean, there have been no TRAP marker system studies on genetic relationships between/among mutant lines. To develop a strategy of Mutant Diversity Pool (MDP) conservation, a study on the genetic diversity of 210 soybean mutant lines (8 cultivars and 202 mutants) was performed through a TRAP analysis. Sixteen primer combinations amplified a total of 551 fragments. The highest (84.00%) and lowest (32.35%) polymorphism levels were obtained with primers MIR157B + Ga5 and B14G14B + Ga3, respectively. The mean PIC values 0.15 varied among the primer combination ranging from 0.07 in B14G14B + Sal2 to 0.23 in MIR157B + Sa4. Phylogenetic, principal component analysis (PCA) and structure analysis indicated that the 210 lines belong to four groups based on the 16 combination TRAP markers. AMOVA showed 21.0% and 79.0% variations among and within the population, respectively. Overall, the genetic similarity of each cultivar and its mutants were higher than within other mutant populations. Our results suggest that the TRAP marker system may be useful for assessing the genetic diversity among soybean mutants and help to improve our knowledge of soybean mutation breeding.

• The Journal of Information Systems
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• v.27 no.2
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• pp.95-114
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• 2018

Purpose The recent concern over environmental problems such as greenhouse gas emission and fine dust contributes increasing interest in renewable energies. However the intrinsic characteristics of renewable energies, intermittent and stochastic generation, might cause serious problems to the stability and controllability of power grid. Therefore countermeasures such as virtual power plant (VPP) must be prepared in advance of the spread of uncontrollable distributed renewable energy resources to be one of major energy sources. Design/methodology/approach This study deals with the design concept of the VPP platform. we proposed as a technology solution for achieving the stability of power grid by guaranteeing a single power profile combining multiple distributed power sources with ICT. The core characteristics of VPP should be able to participate in the grid operation by responding to operation instructions from the system operator, KPX, as well as the wholesale electricity market. Findings Therefore this study includes energy storage device(ESS) as a controllable component as well as renewable energy resources such as photovoltaic and wind power generation. Based on this configuration, we discussed core element technologies of VPP and protype design of VPP solution platform according to system requirements. In the proposed solution platform, UX design for the integrated control center and brokerage system were included as well as ancillary service function to respond to KPX's operation instruction with utilizing the capability of ESS. In addition, a simulator was suggested to verify the VPP operations.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.651-669
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• 2018

This study suggests the prediction model to estimate the specific energy of a pick cutter using a gene expression programming (GEP) and particle swarm optimization (PSO). Estimating the performance of mechanical excavators is of crucial importance in early design stage of tunnelling projects, and the specific energy (SE) based approach serves as a standard performance prediction procedure that is applicable to all excavation machines. The purpose of this research, is to investigate the relationship between UCS and BTS, penetration depth, cut spacing, and SE. A total of 46 full-scale linear cutting test results using pick cutters and different values of depth of cut and cut spacing on various rock types was collected from the previous study for the analysis. The Mean Squared Error (MSE) associated with the conventional Multiple Linear Regression (MLR) method is more than two times larger than the MSE generated by GEP-PSO algorithm. The $R^2$ value associated with the GEP-PSO algorithm, is about 0.13 higher than the $R^2$ associated with MLR.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.735-742
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• 2021

Recently, renewable energy-related power generation facilities have been surging due to the government's "Renewable Energy 3020", "Green New Deal", "2050 Carbon Neutrality" and "K-RE100" policies. Most renewable energy facilities are small and distributed, making it difficult to manage efficiently, and small distributed resources less than 1MW are having a hard time with participating in the market due to the limited sales and avoidance of trading. In particular, the intermittency of renewable energy has a significant impact on the stability of the power grid. The government is seeking to address volatility and intermittency issues through 'small distributed resource brokerage trading, and to expand the systematic resourceization and acceptability of heterogeneous large and small distributed resources. In this work, we intend to apply an AI-based power generation prediction model to a distributed resource brokerage trading system so that it can be utilized as a foundation platform for pioneering new energy business markets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Proceedings of the Korean Institute of Resources Recycling Conference
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• 2005.10a
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• pp.197-197
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• 2005

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1598-1604
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• 2017

Objective: The present study investigated the litter performance of multiparous sows fed 3% and 6% densified diets at farrowing to weaning during summer with mean maximum room temperature of $30.5^{\circ}C$. Methods: A total of 60 crossbred multiparous sows were allotted to one of three treatments based on body weight according to a completely randomized design. Three different nutrient levels based on NRC were applied as standard diet (ST; metabolizable energy, 3,300 kcal/kg), high nutrient level 1 (HE1; ST+3% higher energy and 16.59% protein) and high nutrient level 2 (HE2; ST+6% higher energy and 17.04% protein). Results: There was no variation in the body weight change. However, backfat thickness change tended to reduce in HE1 in comparison to ST treatment. Dietary treatments had no effects on feed intake, daily energy intake and weaning-to-estrus interval in lactating sows. Litter size, litter weight at weaning and average daily gain of piglets were significantly greater in sows in HE1 compared with ST, however, no difference was observed between HE2 and ST. Increasing the nutrient levels had no effects on the blood urea nitrogen, glucose, triglyceride, and creatinine at post-farrowing and weaning time. The concentration of follicle stimulating hormone, cortisol and insulin were not affected by dietary treatments either in post-farrowing or weaning time. The concentration of blood luteinizing hormone of sows in ST treatment was numerically less than sows in HE2 treatment at weaning. Milk and colostrum compositions such as protein, fat and lactose were not affected by the treatments. Conclusion: An energy level of 3,400 kcal/kg (14.23 MJ/kg) with 166 g/kg crude protein is suggested as the optimal level of dietary nutrients for heat stressed lactating sows with significant beneficial effects on litter size.