• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Journal of the Korean Chemical Society
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• v.58 no.5
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• pp.463-477
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• 2014

The purpose of this study is to investigate the teaching-learning effects in the experimental classes for the 'Redox' unit of science textbook of 11th grade using self-regulated learning strategy. Simultaneously, the effects of teaching-learning through the student's characteristics of the scientific high school were also included. The experimental and the controlled groups were selected by the teaching-learning method established on self-regulated learning strategy and regular laboratory activity based on the teacher' instruction, respectively. The questionaries of the scientific inquiry and scientific attitude were examined by the student. For their achievement, the total score which was obtained from the formative evaluation and performance assessment was utilized. After the laboratory activity for the unit grounded on the self-regulated learning strategy, the mean values of the scientific inquiry, scientific attitude, and achievement by the experimental group were higher than those of the controlled group. There was significant difference between the two groups in the post-test. By the results of the post-test for the experimental group, there has been somewhat relationship between the self-regulated learning strategy and the scientific inquiry, the scientific attitude, and the scientific achievement.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of Preventive Medicine and Public Health
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• v.32 no.3
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• pp.361-373
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• 1999

Objectives: Receive Operating Characteristic(ROC) curve with the area under the ROC curve(AUC) is one of the most popular indicator to evaluate the criterion validity of the measurement tool. This study was conducted to develop a standardized questionnaire to discriminate workers at high-risk of work-related musculoskeletal disorders using ROC analysis. Methods: The diagnostic results determined by rehabilitation medicine specialists in 370 persons(89 shipyard CAD workers, 113 telephone directory assistant operators, 79 women with occupation, and 89 housewives) were compared with participant's own replies to 'the questionnair on the worker's subjective physical symptoms'(Kwon, 1996). The AUC's from four models with different methods in item selection and weighting were compared with each other. These 4 models were applied to 225 persons, working in an assembly line of motor vehicle, for the purpose of AUC reliability test. Results: In a weighted model with 11 items, the AUC was 0.8155 in the primary study population, and 0.8026 in the secondary study population(p=0.3780). It was superior in the aspects of discriminability, reliability and convenience. A new questionnaire of musculoskeletal disorder could be constructed by this model. Conclusion: A more valid questionnaire with a small number of items and the quantitative weight scores useful for the relative comparisons are the main results of this study. While the absolute reference value applicable to the wide range of populations was not estimated, the basic intent of this study, developing a surveillance fool through quantitative validation of the measures, would serve for the systematic disease prevention activities.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.2
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• pp.339-348
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• 2004

This study was peformed to assess the relationships among bone mineral density (BMD), Physiological characteristics and lifestyle factors in 61 premenopausal working women aged 30∼49 y in Busan. The BMDs of the lumbar spines (Ll∼L4), femoral necks (FN), ward's triangles (WT) and trochanters (TC) were measured by dual energy X-ray absorptiometry. Data for physiological characteristics and physical activity was assessed by questionnaire and usual intakes of coffee, green tea, alcohol, Coca cola by food frequency questionnaire. The BMDs of L14, FN, WT and TC were 1.02 g/$\textrm{cm}^2$, 0.76 g/$\textrm{cm}^2$,0.69 g/$\textrm{cm}^2$ and 0.66 g/$\textrm{cm}^2$respectively The BMD of FN was assessed as osteopenia by T-score. The BMD of WT was positively correlated with age of monarch (p<0.05) and the BMD of Ll4 was positively correlated with delivery number (p<0.05). The BMD of Ll4 was positively correlated with hours of outdoor activity per weekend and week (p<0.05, p<0.05). The BMDs of FN and WT (p<0.05, p<0.05) were positively correlated with intake of green tea per month and the BMD of FN (p<0.05) was positively correlated with intake of wine per month. But the BMD of Ll (p<0.05) was negatively correlated with intake of Coca cola per month. So nutritional education for increasing hours of outdoor activity and decreasing intake frequency of beverage contributing to diminishment of bone mineral density is needed for premenopausal working women to prevent osteoporosis.

• The korean journal of orthodontics
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• v.30 no.2 s.79
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• pp.175-183
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• 2000

The purpose of this study was to identify the compensatory adaptation of dentoalveolar structure according to the various skeletal relation through the statistical correlation between the anteroposterior, vertical skeletal and dentoalveolar relation. For this study, the sample were consisted of 101 adult subjects (51male and 50 female, mean age; male 23.6 years, female 21.5 years) who had good occlusion with the range of normal overjet and overbite and acceptable Angle's class I molar relationship which had not been related orthodontically The results were as follows : 1. Even though acceptable normal occlusion, the range of measurements which represent anteroposterior, vertical skeletal relation and dentoalveolar relation were very wide. 2. Upper and lower incisor axis were significantly correlated with anteroposterior skeletal relation, which means the mote lingual inclination of upper anterior teeth and the more labial inclination of lower anterior teeth according to the more anterior position of mandible to the maxilla (P<0.01). 3. Upper and 1ower anterior alveolar bone height was statistically correlated with the lower anterior vertical skeletal height. 4. Upper and 1ower alveolar bone height were not correlated with anteroposterior skeletal relation (P>0.05). 5. The correlation between the incisor axis and vertical skeletal was more closely related in upper anterior teeth than the lower anterior teeth. To summarize the above results, even though acceptable normal occlusion, skeletal and dentoalveolar relation was very widely ranged, and there were close relationship between the anteroposterior skeletal relation and the inclination of upper and lower anterior teeth and between the vertical skeletal relation and upper and lower anterior alveolar bone height. These finding can be concluded as compensatory adaptation to the different skeletal relationship.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.49-63
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• 2003

Recently, two international standard organizations, ISO and OGC, have done the work of standardization for GIS. Current standardization work for providing interoperability among GIS DB focuses on the design of open interfaces. But, this work has not considered procedures and methods for designing GIS DB. Eventually, GIS DB has its own model. When we share the data by open interface among heterogeneous GIS DB, differences between models result in the loss of information. Our aim in this paper is to revise the design guidelines for geographic information databases in order to make consistent spatial data models, logical structures, and semantic structure of populated geographical databases. In details, we propose standard guidelines which convert ISO abstract schema into relation model, object-relation model, object-centered model, and geometry-centered model. Furthermore, we provide sample models for applying these guidelines in commercial GIS S/Ws. Building GIS DB based on design guidelines proposed in the paper has the following advantages: the interoperability among databases, the standardization of schema definitions, and the catalogue of GIS databases through.

• Korean Journal of Biological Psychiatry
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• v.6 no.2
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• pp.153-160
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• 1999

Animal models can provide a useful tool for the study of some aspects of psychiatric disorders and their treatment. The four criteria for the evaluation of animal models of psychiatric disorders are as following : 1) similarity of inducing conditions 2) similarity of behavioral state 3) common underlying neurobiological mechanisms 4) reversal by clinically effective treatment techniques. Several animal models have been proposed for schizophrenia : phenylethylamine model, L-dopa model, hallucinogen model, cocaine model, amphetamine model, phencyclidine model, noradrenergic reward system lesion model, reticular stimulation model, social isolation model, conditioned avoidance reaction, catalepsy test, paw test, self-stimulation paradigms, latent inhibition paradigms, blocking paradigms, prepulse inhibition of the startle reflex, rodent interaction, social behavior in monkeys, hippocampal damage, high ambient pressure, and models using selective breeding. Among them, animals with bilateral lesion of the hippocampus may provide an adequate animal model for several symptoms of schizophrenia, and ketamine model can reproduce negative symptoms and cognitive deficits as well as positive symptoms of schizophrenia. In conclusion, no model of schizophrenia is entirely representative of the disease, and findings gleaned from model systems must be cautiously interpreted. Furthermore, the process of developing and validating animal models must work in concert with the process to identify reliable measures of human phenomenology.

• Journal of the Korean Arthroscopy Society
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• v.8 no.1
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• pp.14-18
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• 2004

Purpose: To compare the mid-term follow-up results of anterior cruciate ligament(ACL) reconstruction with the bone-patellar tendon- bone(BTB) autograft to those with the BTB allograft. Materials and Methods: Retrospective study was performed in 59 cases with BTB autograft and 42 cases with BTB allograft. Evaluations include Lysholm score, 2000 IKDC subjective knee score, Shelbourne patello-femoral pain score , Lachman test, pivot shift test, KT-1000 arthrometer test and 2000 IKDC knee examination. Results: There were no significant statistic differences between two groups in Lysholm score and 2000 IKDC subjective knee score of more than 70 (p<0.05). Five cases(8.5%) showed the patello-femoral pain score less than 80 according to Shelboume with autograft group and two cases(4.8%) with allograft group (p<0.05). Lachman test, pivot shift test and KT-1000 arthrometer test showed no significant statistic differences between two groups(P<0.05). Fifty-four cases(91.5%) were normal or nearly normal according to the 2000 IKDC knee examination with autograft group and thirty-eight cases(90.4%) with allograft group(p<0.05).Conclusion: BTB allograft as well as BTB autograft is considered to be an acceptable choice for ACL reconstruction.