• Journal of Korean Society of Forest Science
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• v.95 no.1
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• pp.50-54
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• 2006

Biomass expansion factors and stem density values were commonly used in converting stand volumes into total carbon stocks for the purpose of national inventories of greenhouse gas emissions and carbon sequestration. The objective of this study was to examine the influence of stand age classes on aboveground and total biomass expansion factors, and stem density values in Chamaecyparis obtusa species. A total of 25 representative sample trees based on the three different stand age classes were destructively sampled to measure green weights and dry weights of the major four(root, stem, branch and foliage) portions of C. obtusa species grown in Jangseung-gun of southern Korea. According to the results of this study, as stand age classes increase, total biomass expansion factors tended to be decreased with the ranges from 3.64 to 1.44, while the stem density values tended to be slightly increased with the ranges from $0.35(g/cm^3)$ to $0.44(g/cm^3)$. There were statistically significant differences in biomass expansion factors and stem density values between stand age classes, but became nearly constant after 30 years old for C. obtusa species. This information could be very useful to improve a national-scaled inventory of greenhouse gas emissions and carbon sequestration for the C. obtusa species by applying different biomass expansion factors and stem density values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.222-230
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• 2016

HEMIRE is a 6,000-meter-class remotely operated vehicle (ROV) that has been developed for observation and sampling of objects of interest on the deep seabed. We first carried out deep-seabed exploration around the slopes of the Hupo Bank and the Ulleung Basin in the East Sea in June 2015. Over two weeks, a total of 10 dives were made from a support ship, the R/V Onnuri, at eight stations with water depth ranging between 194 and 2,080 m. The dive times ranged from 1 to 6 hours, depending on the operating conditions. We obtained the following results: 1) video images of the deep seafloor; 2) red snow crab density data (a major fishery resource) and inventories of deep-sea fauna, including an unrecorded organism; 3) specific topographies such as canyons slopes; 4) an undisturbed sediment core obtained using a push corer; and 5) observations of the seabed surface covered with discarded anthropogenic waste material.

• Analytical Science and Technology
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• v.26 no.5
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• pp.333-339
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• 2013

This study was conducted to build up the inventories of Pb isotopic compositions of major Pb pollution sources in South Korea. Since non-ferrous metal smelters are one of major anthropogenic sources, two smelters for zinc, each one of smelter for lead and copper were selected for the study. The Pb concentrations and isotopic compositions of metal ores, wastewater, sludge, metal rod and produced sulfuric acid were analysed to understand the Pb isotopic patterns in environment. The isotopic ratio, $^{206}Pb/^{207}Pb$, of zinc ores from zinc smelter were in the range of 1.179~1.198 and the ratio of waste, flue gas and products samples were 1.105~1.147. This results implied that the isotopic patterns of output samples showed mixing patterns between two distinct metal ore soerces. In 2011, major importing countries of zinc ore were Australia, Peru and Mexico. Thus Pb isotopic patterns from zinc smelter is originated from the mixing patterns between less radiogenic Australian ores and more radiogenic South America's ores. Lead smelters also showed the same mixing patterns with those of zinc smelters. However copper smelter showed same Pb isotopic patterns with more radiogenic South America's ores.

• Smart Media Journal
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• v.7 no.1
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• pp.16-23
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• 2018

In this paper, we used the Deep Neural Network (DNN) to predict the number of daily spectators of Gwangju - KIA Champions Field in order to provide marketing data for the team and related businesses and for managing the inventories of the facilities in the stadium. In this study, the DNN model, which is based on an artificial neural network (ANN), was used, and four kinds of DNN model were designed along with dropout and batch normalization model to prevent overfitting. Each of four models consists of 10 DNNs, and we added extra models with ensemble model. Each model was evaluated by Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The learning data from the model randomly selected 80% of the collected data from 2008 to 2017, and the other 20% were used as test data. With the result of 100 data selection, model configuration, and learning and prediction, we concluded that the predictive power of the DNN model with ensemble model is the best, and RMSE and MAPE are 15.17% and 14.34% higher, correspondingly, than the prediction value of the multiple linear regression model.

• KDI Journal of Economic Policy
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• v.28 no.1
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• pp.117-144
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• 2006

This study is to analyze the existence of the real buffer effect that reflects the effect of beginning-of-period inventory stocks effect on the demand for fixed investment, and the financial buffer effect indicates the substitution effect between end-of-period inventory stock and the source of financing for fixed investment. I use panel data of 361 Korean listed non-financial firms during 1990-2003. After the crisis, it also observed whether the relationship between inventory stocks and fixed investment has altered or not. I review the theoretical connection between inventory stock and fixed investment through the paper by Bo(2004) and estimate the investment model by the method of GMM-SYS. The results show negative relation between end-of-period inventory stock and fixed investment in the whole period and each period classified, also it confirms that the relation between fixed investment and end-of-period investment is significantly negative. It can be interpreted through two aspects that firms not only use inventory stock as a buffer in response to unexpectedly high demand, but also utilize inventory stock as a source of financing for fixed investment. The results imply that firm's decision-making is much correlated with production-and-inventory stock adjustment, decision-making about fixed investment, and decision-making about financial affairs.

• Journal of the Korean Chemical Society
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• v.64 no.3
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• pp.159-174
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• 2020

The purpose of this study is to examine 'Design Thinking' based Chemistry Class program as an education strategy for core competence of creative convergence talent. The program stages were modified and supplemented into eight stages, including 'Knowledge Understand', 'Empathy', 'Sharing perspective', 'Ideate', '1st Prototype', '1st Test', '2nd Prototype', and '2nd Test', so that the 'Design Thinking Process in Science Education' can be applied to the chemistry class. Considering the linkage between the 2015 and 2009 revised national curriculum, the achievement criteria were selected, and the lesson plans and student activity sheet were developed according to the themes to be met. Four thematic educational programs were developed and applied to Chemistry I for the second grade of high school students from March to August. The results were verified through qualitative data analysis of the class scene and pre- and post-test based on inventories of 'Empathy' 'STEAM educational competence', 'Problem solving process'. As a result of applying the developed program, 'empathy' showed a significant improvement in empathy with others and empathy with the problem situation. In 'STEAM educational competence', there was a significant enhancement in science and design competence. In the 'problem finding process', the problem definition, problem solution design, and problem-solving review were significantly improved in the 'problem-solving process'. The results of this study provided implications for the applicability of design thinking - based chemistry classes and its educational effect.

• Journal of Korean Elementary Science Education
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• v.20 no.2
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• pp.239-254
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• 2001

The in-depth learning course newly established in the 7th National Curriculum of Science is for students who have mastered regular subject matters on a science topic and want to learn it more deeply or by different ways. Individual learners have their own unique intellectual properties. The study examined the effects of in-depth science learning using multiple intelligence activities on the science inquiry abilities and interests of elementary school children. This study involved two fifth-grade science classes in Busan. Each class was assigned to comparison and experimental group. The science topics covered during the period of the study were Units of Matter and Earth. After studying each regular content formulated by the National Curriculum, the students of comparison group experienced traditional practices of in-depth science, whereas those of experimental one performed the Multiple Intelligence(MI) activities related to the content. Students of both groups were pre- and posttested using the inventories of Science Inquiry Ability and Science Interest. Also, after instruction on the topics, students were interviewed to collect more information related to their loaming. The results are as follows. First, the science inquiry abilities of children were increased by using activities based on MI during the in-depth science teaming. Two inquiry processes, that is, the Prediction which is regarded as one of the basic process skills in science and the Generalization regarded as one of integrated process skills showed statistically significant differences between the groups, although the differences of other skills not significant but more improvements in experimental group than comparison one. Second, the in-depth science loaming through MI contributed to the increasing of interests of the children in science. The scores on Science Interest measured in pretest and posttest with the two groups showed st statistically significant difference. For interest in science instruction, children of experimental group showed high level of interest for the various MI activities, and, although the comparison groups' level of the interest was low, they revealed that they want to experience the MI activities in future instruction of science. Interviews with the children randomly selected from the experimental group when they completed the in-depth programs showed that most of them had much interest in MI activities. Especially, they attributed significant meanings to the experiences of teaming with their friends and doing activities that they want to do. These findings have important implications about usefulness of MI in science instruction. The results also highlight the need for science teachers to provide a variety of experiences and to create environments which encourage the children to use MI to learn a science topic.

• Journal of Korean Society of Forest Science
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• v.78 no.3
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• pp.263-273
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• 1989

Accurate and cost-effective classification of forest vegetation is the primary goal for forest management and utilization of forest resources. Aerial photograph and remote sensing are the most frequent and effective method in forest resources inventories. TM and MSS are the principal observing instruments on the Landsat-4 and -5 earth observing satellite. Especially TM has considerably greater spatial, spectral, and radiometric resolution power than MSS, that is, the IFOV of TM at a nadir is 30m compared to 80m for MSS. In this study, we used TM data to classify forest types and compared the result with forest type map manufactured by interpretation of B/W infrared photographs. As a result, land use types were well defined with TM data. But classifying forest types was a little difficult and indistinct. However, the spectral signatures of forest in every season and growing stages remained as problems to be solved, and also the most effective selection and combination method of bands for differentiating the spectral plots among classes.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.57-68
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• 2004

Recently in order to more effectively and scientifically process forest official tasks, which have been focused on documents and inventories, they should be applied with the up-to-date spatial information technologies. Especially, the forest resource information management based on GIS(geographic information system) and aerial orthophoto is expected not only to play an important role as DSS(decision support system) for domestic forest conservation policy and forestry development industry but also to service forest resource information toward people such as the owners of a mountain rapidly. In this study, the important forest information such as digital topography map, digital forest type map, digital forest cadastral map, digital aerial photographs and attribute data were first reprocessed and constructed in DBMS(data base management system). In addition, forest officials could analyze and retrieve forest information by using detail sub-application systems such as forest cadastral retrieval, forest land development information management, reserved forest information management and forest resource information retrieval. For this, the user interface is developed by using Visual Basic 6.0 and MapObjects 2.1 of ESRI based on CBD(component based development) technology. The result of developing this system will not only perform constructing economical forest and better environment but also be the foundation of domestic spatial technology for forest resource management.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.291-299
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• 2020

The purpose of this study was to propose the most cost-effective sampling method, by analyzing the cost of forest resource investigation per sampling method for the planned harvesting area of in Chunyang-myeon, Byeonghwa-gun, Gyeongsangbuk-do, Korea. For this study, three sampling methods were selected: random sampling method, systematic sampling method, and line transect method. For each method, sample size, hourly wage, number of sample points, survey time, travel time, the sample error rate of the estimated average volume, and the desired sampling error rate were used to calculate the cost of forest resource inventories. Thus, 10 sampling points were extracted for each sampling method, and the factors required for cost analysis were calculated via a field survey. As a result, the field survey cost per ha using the random sampling method was found to be have the lowest cost, regardless of the desired sampling error rate, followed by the systematic sampling method, and the line transect method.