• Journal of the Korean earth science society
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• v.26 no.6
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• pp.477-488
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• 2005

Fossil photographs in science and earth science textbooks on the 7th curriculum including those of elementary, middle and high school, are analyzed to estimate the adequacy and scientific significance focusing on the locality and scale. The results show that most of the textbooks have included various types of fossil photographs: 32 in elementary textbooks, 50 in middle school and 109 in high school. However, the presentation of scientific information on each photographs is insufficient. Only $68\%$ of the elementary textbooks designates locality and only $6\%$ includes scales. Among middle and high school textbooks, 40 and $16\%$ of photographs describe locality, and 14 and $18\%$ of photographs exhibit scale, respectively. More scientific and appropriate presentation of fossil photographs, such as locality and scale, is needed to enhance educational effect.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.245-253
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• 2011

Due to the imprudent spending of the fossil fuels, the environment was contaminated seriously and the exhaustion problems of the fossil fuels loomed large. Therefore people become taking a great interest in alternative energy resources which can solve problems of fossil fuels. The wind power energy is one of the most interested energy in the new and renewable energy. However, the plants of wind power energy and the traditional power plants should be balanced between the power generation and the power consumption. Therefore, we need analysis and prediction to generate power efficiently using wind energy. In this paper, we have performed a research to predict power generation patterns using the wind power data. Prediction approaches of datamining area can be used for building a prediction model. The research steps are as follows: 1) we performed preprocessing to handle the missing values and anomalous data. And we extracted the characteristic vector data. 2) The representative patterns were found by the MIA(Mean Index Adequacy) measure and the SOM(Self-Organizing Feature Map) clustering approach using the normalized dataset. We assigned the class labels to each data. 3) We built a new predicting model about the wind power generation with classification approach. In this experiment, we built a forecasting model to predict wind power generation patterns using the decision tree.

• Journal of The Korean Association For Science Education
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• v.24 no.6
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• pp.1106-1117
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• 2004

The purposes of this study were to analyze types of scientific emotion word and to investigate the relationship between the ISE(Index of Scientific Emotion) and the ability of science-knowledge generation in subjects' scientific observation and rule-discovery. The subjects were asked to perform four scientific tasks. The tasks were developed that are suitable for scientific observation and rule-discovery. In performing tasks, the subjects were asked to describe their generated science-knowledge and scientific emotion through self-report questionnaire, performing each task. The strength of their scientific emotion was also measured using adjective emoticon check lists. In subjects' scientific observing, they showed 33.3% of interest emotion which was the biggest, 15.0% of acceptance emotion, and 11.3% of love emotion, respectively. In scientific rule-discovering, types of emotion were shown as 23.8% of interest, 21.5% of disgust, and 10.8% of acceptance, respectively. In addition, ability of science-knowledge generation was significantly correlated to ISE.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.217-239
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• 2009

As gas hydrate is recently emerging as a new energy source to solve environmental and exhaustion problems caused by fossil energy, Korea is working on a gas hydrate development project under a 10-year plan from 2005 to 2014. Gas hydrate is expected to have a big effect on the economy and society of Korea, which is largely depending on energy imports besides water energy and atomic energy. However, it is uncertain whether the project will produce successful results. Thus, it is very important to improve its validity and to propose effective execution strategies by evaluating the value of the project in advance. Thus, this study intended to include new information, which had not been evaluated in existing methods, and to reduce biases or errors in value evaluation results by applying a fuzzy risk analysis to the real option model in order to evaluate the value of a gas hydrate development project. It is advantageous that the real option model based on the fuzzy risk analysis modelizes the vagueness and inexactness of intangible element judgment into an appropriate language scale so as to evaluate these elements clearly and integrate them with estimated financial performance results. The application of the fuzzy risk analysis makes it possible to conduct an analysis by dissolving a decision-making issue with complicated and various attributes into several simplified problems. With the continuing high oil prices and today's demand of clean energy, the necessity of energy resources and technology development projects keeps growing. Amid this situation, it is expected that these study results will contribute to proposing a guideline not only for gas hydrate projects but also for policy decision-making related to future energy industries.

• Journal of Korean Society of Forest Science
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• v.96 no.4
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• pp.477-482
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• 2007

Forest biomass became a topic because we have growing interest in global environmental issues and environment-friendly energy resources. This study was carried out to estimate the forest biomass and develop a program for biomass information management in Korea. The total forest biomass (million ton) were 521 for gross forest, 403 for productive forest and 201 for commercial forest in 2005. Also, the annual biomass production in forest was 20 million ton which was equivalent to 94,290 Gkcal of heating value and about 9 billion won of paraffin oil. The biomass growing rate (every 10year) increased from 4.95% in 1985 to 5.30% in 1995 but turn down 4.46% in 2005. The factors that the forest stock could be converted to the forest biomass have developed according to forest type. Therefore, it is impossible to estimate the exact biomass by tree species. In this reason, the demands of the development of the factors by tree species was raised. In addition, it is on time to develop an equation for estimation of biomass by species using dbh and height as independent factors.

• The Korean Journal of Malacology
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• v.25 no.3
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• pp.213-222
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• 2009

In order to investigate contamination of heavy metal in seawater and cultured oyster, samples were collected November 2003 to July 2004 from 12 sites (13 sites for seawater) along the coast of Tongyeong, Korea. The mean concentrations of metal in oyster tissues were as follows: 0.09 (0.01-0.3) ${\mu}g/l$ for Cd, 0.47 (0.01-1.4) ${\mu}g/l$ for Cr, 0.59 (0.2-2.3) ${\mu}g/l$ for Ni, 1.02 (0.1-4.2) ${\mu}g/l$ for Pb and 0.48 (0.01-3.9) ${\mu}g/l$ for Hg in the seawater, whereas 2.45 (0-5.47) mg/kgDW for Cd, 3.63 (0.10-12.91) mg/kgDW for Cr, 3.2 (0.01-15.73) mg/kgDW for Ni, 3.51 (0.01-6.47) mg/kgDW for Pb and 0.39 (0.004-0.74) mg/kgDW for Hg, respectively. Most metal concentration values were below the permissible range for the related regulations. Mean bioconcentration factors (BCF) for each metal were as follows: 38,964 (1,771-207, 171) for Cd, 9,583 (1,231-80, 162) for Cr, 191 (3-20, 980) for Ni, 1,416 (245-5, 207) for Pb and 180 (5-716) for Hg, respectively. The BCF values from this study corresponded to the transitional phase from the pristine to the contaminated waters. Notably, Cd showed the highest BCF, which suggest that the Pacific oyster could be utilized as a useful biomarker for Cd contamination in sea water. The multidimensional scaling analysis suggested that the metal contaminants are mainly originated from combustion of fossil fuel and accumulated to oyster through food web.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.267-278
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• 2020

ESS is an essential requirement for resolving power shortages and power demand management and promoting renewable energy at a time when the energy paradigm changes. In this paper, we propose a cost-effective ESS Peak-Shaving operation plan through load and solar power generation forecast. For the ESS operation plan, electric load and solar power generation were predicted through RMS, which is a statistical measure, and a target load reduction guideline for one hour was set through the predicted electric load and solar power generation amount. The load and solar power generation amount from May 6th to 10th, 2019 was predicted by simulation of load and photovoltaic power generation using real data of the target customer for one year, and an hourly guideline was set. The average error rate for predicting load was 7.12%, and the average error rate for predicting solar power generation amount was 10.57%. Through the ESS operation plan, it was confirmed that the hourly guide-line suggested in this paper contributed to the peak-shaving maximization of customers.Through the results of this paper, it is expected that future energy problems can be reduced by minimizing environmental problems caused by fossil energy in connection with solar power and utilizing new and renewable energy to the maximum.