• Journal of Forest and Environmental Science
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• v.8 no.1
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• pp.21-33
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• 1992

This study was performed to investigate the hardness of wood related to the wood surface, sap and heartwood, early and latewood, specific gravity, annual ring width and moisture content on major Korean tree species such as Pinus koraiensis, Abies holophylla, Larix leptolepis and Quercus valiabilis. The results were summarized as follows: 1. The arithmetic mean values of wood hardness on cross section were respectively $8.0kg/mm^2$ on Quercus valiabilis, $7.4kg/mm^2$ on Larix leptolepis, $5.1kg/mm^2$ on Pinus koraiensis and $4.7kg/mm^2$ on Abies hollophylla. 2. Generally hardness of wood on cross section was greater than the others and the proportion of cross section hardness to radial was respectively 2.8 on Quercus valiabilis, 2.6 on Larix leptolepis, 3.8 on Pinus koraiensis, and 4.1 on Abies holophylla and that proportion was tend to be decrease as specific gravity increased. 3. It was recognized that the hardness of sap and heartwood was different from each of the tree species and generally heartwood hardness was somewhat greater than sapwood. 4. Generally latewood hardness with in a ring was greater than earlywood and the proportion of earlywood hardness to latewood decreased as specific gravity increased. 5. The relations between hardness of wood and specific gravity show a high positive correlation on all sample tree species. 6. The values of hardness decreased with increasing annual ring width. 7. Hardness of wood on Abies holophylla was greatest in oven dried wood and it was decreased as moisture content increased, but not changed with moisture content abve F.S.P.. The proportion of oven dried wood hardness to green are respectively 3.0 on cross, 2.4 on radial and 1.9 on tangential section.

• Sleep Medicine and Psychophysiology
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• v.4 no.1
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• pp.107-119
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• 1997

Objectives: The psychophysiologic response pattern between healthy subjects and patients with generalized anxiety disorder, and the relationship among anxiety rating scales and those patterns in patients were examined. Methods: Twenty-three patients with generalized anxiety disorder(AD) and 23 healthy subjects were evaluated by Hamilton Rating Scale for Anxiety(HRSA) and State-Trait Anxiety Inventory before baseline stressful tasks. Subjective Units of Distress were evaluated just before baseline period, immediately after stressful tasks, at the end of the entire procedure, and psychophysiologic measures, i.e., skin temperature(ST), electromyographic activity(EMG), heart rate(HR), electrodermal response(EDR) during baseline & rest and during two psychologically stressful tasks (mental arithmetic, TM; talk about a stressful event, TT) were also evaluated. Results: 1) AD group showed significantly higher EMG level during rest after stressful tasks and higher HR level during all period except TM compared to control group. 2) AD group showed lower change in the startle response(SR) of ST, in the SR & the recovery response(RR) of EMG during TM, and in the RR of EDR immediately after TM than control group. AD group showed that the RR of EDR was significantly lower than the SR during stressful tasks. 3) We found that there was significantly negative correlation between state anxiety and the RR of EDR after TT in AD group. We also found that there were significantly positive correlations between HRSA score and the SRs of EDR during stressful tasks, and between state anxiety and the SR of EDR during TT. Conclusion: Our results suggest that patients with generalized anxiety disorder show higher autonomic arousal than healthy subjects and decreased physiologic flexibility or reduced autonomic flexibility.

• Journal of Soil and Groundwater Environment
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• v.11 no.5
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• pp.20-34
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• 2006

This study was undertaken to assess the anthropogenic impact on trace metal concentrations (Zn, Cu, Pb, Cr, Ni, and Cd) of roadside sediments (N = 70) from No.7 national road within the watershed of Hoidong Reservoir in Pusan City and to estimate the potential mobility of selected metals using sequential extraction. We generally found high concentrations of metals, especially Zn, Cu and Pb, affected by anthropogenic inputs. Compared to the trace metal concentrations of uncontaminated stream sediments, arithmetic mean concentrations of roadside sediments were about 7 times higher for Cu, 4 times higher for Zn, 3 times higher for Pb and Cr and, 2 times higher for Ni and As. Speciation data on the basis of sequential extraction indicate that most of the trace metals considered do not occur in significant quantities in the exchangeable fraction, except for Cd and Ni whose exchangeable fractions are appreciable (average 29.3 and 25.8%, respectively). Other metals such as Zn (51.4%) and Pb (45.2%) are preferentially bound to the reducible fraction, and therefore they can be potentially released by a pH decrease and/or redox change. Copper is mainly found in the organic fraction, while Cd is highest in the exchangeable fraction, and Cr and Ni in the residual fraction. Considering the proportion of metals bound to the exchangeable and carbonate fractions, the comparative mobility of metals probably decreases in the order of Cd>Ni>Pb>Zn>Cr>Cu. Although the total concentration data showed that Zn was typically present in potentially harmful concentration levels, the data on metal partitioning indicated that Cd, Ni and Pb pose the highest potential hazard for runoff water. As potential changes of redox state and pH may remobilize the metals bound to carbonates, amorphous oxides, and/or organic matter, and may release and flush them through drain networks into the watershed of Hoidong Reservoir, careful monitoring of environmental conditions appears to be very important.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.29-39
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• 1999

An earlier study of the effect of rain found that the capacity of freeway systems was reduced, but did not address the effects of rain on the nature of traffic flows. Indeed, the substantial variation due to the intensity of adverse weather conditions is entirely rational so that its effects must be considered in freeway facility design. However, all of the data in Highway Capacity Manual(HCM) have come from ideal conditions. The primary objective of this study is to investigate the effect of rain on urban freeway traffic flows in Seoul. To do so, the relations between three key traffic variables(flow rates, speed, occupancy), their threshold values between congested and uncontested traffic flow regimes, and speed distribution were investigated. The traffic data from Olympic Expressway in Seoul were obtained from Imagine Detection System (Autoscope) with 30 seconds and 1 minute time periods. The slope of the regression line relating flow to occupancy in the uncongested regime decreases when it is raining. In essence, this result indicates that the average service flow rate (it may be interpreted as a capacity of freeway) is reduced as weather conditions deteriorate. The reduction is in the range between 10 and 20%, which agrees with the range proposed by 1994 US HCM. It is noteworthy that the service flow rates of inner lanes are relatively higher than those of other lanes. The average speed is also reduced in rainy day, but the flow-speed relationship and the threshold values of speed and occupancy (these are called critical speed and critical occupancy) are not very sensitive to the weather conditions.

• Korean Journal of Breeding Science
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• v.42 no.5
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• pp.525-533
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• 2010

In this study, random amplified polymorphic DNA (RAPD) and simple sequence repeat (SSR) analyses were utilized for evaluation of genetic diversity of 34 Korean bred and introduced apple cultivars. Thirty-seven RAPD primers detected a total of 193 polymorphic bands (36.2%) with an average of 5.6. Twenty-six SSR markers generated a total of 112 alleles with an average 4.3 alleles per locus. Genetic diversity of 34 cultivars estimated by polymorphic information content (PIC) value ranged from 0.536 (CH03d12) to 0.952 (CH04c06) with an average of 0.843. By UPGMA (unweighted pair-group method arithmetic average) cluster analysis with 305 polymorphic bands, the apple cultivars were classified four groups by similarity index of 0.640. The 'Seokwang' was included in group I. Group II consisted of 12 cultivars which have 'Golden Delicious' in their pedigree, with the exception of 'Spur Earliblaze' and 'Jonathan'. Group III included 13 cultivars which have usually 'Fuji' in their ancestry and bud sport of 'Fuji' cultivars. Group IV consisted of 8 cultivars with 'Hongro', 'Gamhong', and 'Saenara'. Similarity values among the tested apple cultivars ranged from 0.529 to 0.987, and the average similarity value was 0.647. The similarity index was the highest (0.987) between 'Hwarang' and 'Danhong', and the lowest (0.529) between 'Seokwang' and 'Hwarang'. The genetic relationships among the 34 studied apple cultivars were basically consistent with the known pedigree.

• The Journal of Korean Philosophical History
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• no.27
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• pp.197-222
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• 2009

The Reform Movement(戊戌變法) of 1898 was a boundary tablet of modern history of science and technology which inherited the past and ushered in the future. Kang Youwei(康有爲), as a leader, his scientific thoughts opened up the way of Chinese enlightenity campaign and pushed the development of Chinese modem science and had an important position in modem history of scientific thoughts. The dissertation analyses the source, establishment and content of Kang Youwei. Kang Youwei developed the useful and discarded the useless of the view of implement science held by the Westernized Party, undertook a deep and throughout thinking on the nature of science, had cognition of scientific methods and spirit, by which he criticized negative proneness of ancient Chinese views of science. He put forwards a series of practical suggestions on political reform that provided a solid guarantee and support in system for scientific development. Kang Youwei rooted in the soil of Chinese traditional academic culture, but also western learning in modern western civilization. Kang go through Westernization Movement since the in-depth study of Western natural and inevitable outcome of the social sciences, are giving to science and technology. Although he was originally of Western "science" has a lot of misunderstandings and prejudices, but these shallow hazy perceptual knowledge, his view of science which constitutes the basis of the formation. In the course of scientific inquiry, Kang has begun to explore the essence of scientific development. He has a gut feeling that behind the scientific discovery of the existence of a force, which is the scientific truth and is used to grasp the scientific method. After contact with the Western world, with the traditional "Heaven(天)", and modern Chinese intellectuals began to "axiom(公理)" to recover his traditional "Heaven" of the new understanding is reflected mainly in "Zhutianjiang(諸天講)". "Zhutianjiang" is the Kang Yuwei in the absorption of traditional astronomy knowledge base, will the traditional arithmetic, as well as Buddhism and the West since the twentieth century, new knowledge of astronomy combines written. Kang while recognizing that scientific instruments, is nothing more than an extension of the role of the human senses and make the "Dao(道)" is more clear, but the "artifacts(器物)" caused by the inherent limitations of the limited nature of human knowledge, which is "Heaven" boundless nature of the broad terms, refused to concede defeat to. In reality, the activities of political reform, he gradually recognize this real-world helpless, and he recognized that the real world to achieve common ground of social ideal is impossible, so he chose comfort in life that people really get a stage of "Tianyou(天遊)". This is the cause that his writing "Datongshu(大同書)", at the same time, followed by writing "Zhutianjiang" talk "Tianyou".

• Journal of Life Science
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• v.33 no.7
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• pp.565-573
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• 2023

In light of the complex interactions between the host animal and its resident gut microbiomes, studies of these microbial communities as a means to improve cattle production are important. This study was conducted to analyze the intestinal microorganisms of Holstein (HT) and Jersey (JS), raised in Korea and to clarify the differences in microbial structures according to cattle species through next-generation sequencing. The alpha-diversity analysis revealed that most species richness and diversity indices were significantly higher in JS than in HT whereas phylogenetic diversity, which is the sum of taxonomic distances, is not significant. Microbial composition analysis showed that the intestinal microbial community structure of the two groups differed. In the both groups, a significant correlation was observed among the distribution of several microbes at the family level. In particular, a highly significant correlation (p<0.0001) among a variety of microbial distributions was found in JS. Beta-diversity analyis was to performed to statistically verify whether a difference exists in the intestinal microbial community structure of the two groups. Principal coordinate analysis and unweighted pair group method with arithmetic mean (UPGMA) clustering analysis showed separation between the HT and JS clusters. Meanwhile, permutational multivariate analysis of variance (PERMANOVA) revealed that their microbial structures are significantly different (p<0.0001). LEfSe biomarker analysis was performed to discover the differenc microbial features between the two groups. We found that several microbes, such as Firmicutes, Bacilli, Moraxellaceae and Pseudomonadales account for most of the difference in intestinal microbial community structure between the two groups.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1635-1650
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• 2023

Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m^-3, and primary production of 580.96-1574.13 mg C m^-2 day^-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.235-257
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• 2010

Contemporary belief is that the creative talented can create new knowledge and lead national development, so lots of countries in the world have interest in Gifted Education. As we well know, U.S.A., England, Russia, Germany, Australia, Israel, and Singapore enforce related laws in Gifted Education to offer Gifted Classes, and our government has also created an Improvement Act in January, 2000 and Enforcement Ordinance for Gifted Improvement Act was also announced in April, 2002. Through this initiation Gifted Education can be possible. Enforcement Ordinance was revised in October, 2008. The main purpose of this revision was to expand the opportunity of Gifted Education to students with special education needs. One of these programs is, the opportunity of Gifted Education to be offered to lots of the Gifted by establishing Special Classes at each school. Also, it is important that the quality of Gifted Education should be combined with the expansion of opportunity for the Gifted. Social opinion is that it will be reckless only to expand the opportunity for the Gifted Education, therefore, assessment on the Teaching and Learning Program for the Gifted is indispensible. In this study, 3 middle schools were selected for the Teaching and Learning Programs in mathematics. Each 1st Grade was reviewed and analyzed through comparative tables between Regular and Gifted Education Programs. Also reviewed was the content of what should be taught, and programs were evaluated on assessment standards which were revised and modified from the present teaching and learning programs in mathematics. Below, research issues were set up to assess the formation of content areas and appropriateness for Teaching and Learning Programs for the Gifted in mathematics. A. Is the formation of special class content areas complying with the 7th national curriculum? 1. Which content areas of regular curriculum is applied in this program? 2. Among Enrichment and Selection in Curriculum for the Gifted, which one is applied in this programs? 3. Are the content areas organized and performed properly? B. Are the Programs for the Gifted appropriate? 1. Are the Educational goals of the Programs aligned with that of Gifted Education in mathematics? 2. Does the content of each program reflect characteristics of mathematical Gifted students and express their mathematical talents? 3. Are Teaching and Learning models and methods diverse enough to express their talents? 4. Can the assessment on each program reflect the Learning goals and content, and enhance Gifted students' thinking ability? The conclusions are as follows: First, the best contents to be taught to the mathematical Gifted were found to be the Numeration, Arithmetic, Geometry, Measurement, Probability, Statistics, Letter and Expression. Also, Enrichment area and Selection area within the curriculum for the Gifted were offered in many ways so that their Giftedness could be fully enhanced. Second, the educational goals of Teaching and Learning Programs for the mathematical Gifted students were in accordance with the directions of mathematical education and philosophy. Also, it reflected that their research ability was successful in reaching the educational goals of improving creativity, thinking ability, problem-solving ability, all of which are required in the set curriculum. In order to accomplish the goals, visualization, symbolization, phasing and exploring strategies were used effectively. Many different of lecturing types, cooperative learning, discovery learning were applied to accomplish the Teaching and Learning model goals. For Teaching and Learning activities, various strategies and models were used to express the students' talents. These activities included experiments, exploration, application, estimation, guess, discussion (conjecture and refutation) reconsideration and so on. There were no mention to the students about evaluation and paper exams. While the program activities were being performed, educational goals and assessment methods were reflected, that is, products, performance assessment, and portfolio were mainly used rather than just paper assessment.