• The Journal of Korean Philosophical History
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• no.28
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• pp.183-212
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• 2010

The purpose of this study is to provide a theoretical base for making a character education program and to develop a school violence prevention program and analysis the effects of the program in elementary schools. The prevention program was designed to target students, teachers, parents and community residents and utilized the above groups as participants. This study is developed on the basis of Social Emotional Learning as well as Emotional Intelligence which put on the importance on the role of emotion in the problem solving. In concrete, school violence prevention program based on the social and emotional learning, development of integrative programs articulating three key domains directly and indirectly influencing students' character formation, maximum use of the educational institutes' moral education curriculums and potential curriculums in the surrounding environment. To do so, bibliographical study and analysis of the research materials are carried out, and also the professionals' advice is received. The study object is 113 elementary school students of 2 elementary schools in Seoul. For them, the preparatory program is carried out from September 2009 to November 2009. And then, the analysis for the satisfaction degree of participation in the program and for the descriptive results of the school violence prevention education is carried out.

• The Mathematical Education
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• v.63 no.2
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• pp.255-272
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• 2024

This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.

• Journal of the Korean association of regional geographers
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• v.6 no.2
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• pp.1-19
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• 2000

This study is to investigate and analyze regional patterns of aging in Taejeon Metropolitan city-the overpopulated area of Choong-Cheong Province-by cohort analysis method. According to the population structure transition caused by rapid social and economic changes, Korea has made a rapid progress in population aging since 1970. This trend is so rapid that we should prepare for and cope with aging society. It is not only slow to cope with it in our society, but also there are few studies on population aging of the geographical field in Korea. The data of this study are the reports of Population and Housing Censuses in 1975 and 1985 and General Population and Housing Censuses with 10% sample survey in 1995 taken by National Statistical Office. The research method is to sample as the aging district the area with high aged population rate where the populations over 60 reside among total population during the years of 1975, 1985, 1995 and to sample the special districts of decreasing population where the population decreases very much and the special districts of increasing population in which the population increases greatly, presuming that the reason why aged population rate increases is that non-elderly population high in mobility moves out. It is then verified and ascertained whether it is true or not with cohort analysis method by age. Finally regional patterns in the city are found through the classification and modeling by type based on the aging district, the special districts of decreasing population, and the special districts of increasing population. The characteristics of the regional patterns show that there is social population transition and that non-elderly population moves out. The aging district with the high aged population rate is divided into high-level keeping-up type, relative falling type below the average of Taejeon city in aging progress, and relative rising type above the average of the city. This district can be found at both the central area of the city and the suburbs because Taejeon city has the characteristic of over-bounded city. But it cannot be found at the new built-up area with the in-migration of large population. The special districts of decreasing population where the population continues to decrease can be said to be the population doughnuts found at the CBD and its neighboring inner area. On the other hand, the special districts of increasing population where the population continues to increase are located at the new built-up area of the northern part in Taejeon city. The special districts of decreasing population are overlapping with the aging district and higher in aged population rate by the out-migration of non-elderly population. The special districts of increasing population are not overlapping with the aging district and lower in aged population rate by the in-migration of non-elderly population. To clarify the distribution map of the aging district, the special districts of decreasing and increasing population and the aging district are divided into four groups such as the special districts of decreasing population group-the same one as the aging district, the special districts of decreasing population group, the special districts of increasing population group, and the other district. With the cohort analysis method by age used to investigate the definite increase and decrease of aging population through population transition of each group, it is found that the progress of population aging is closely related to the social population fluctuation, especially that aged population rate is higher with the out-migration of non-elderly population. This is to explain each model of CBD, inner area, and the suburbs after modeling the aging district, the special districts of decreasing population, and the special districts of increasing population in Taejeon city. On the assumption that the city area is a concentric circle, it is possible to divide it into three areas such as CBD(A), the inner area(B), and the suburbs(C). The special districts of increasing and decreasing population in the city are divided into three districts-the special districts of decreasing population(a), the special districts of increasing population(b), and the others(c). The aging district of this city is divided into the aging district($\alpha$) and the others($\beta$). And then modeling these districts, it is probable to find regional patterns in the city. $Aa{\alpha}$ and $Ac{\beta}$ patterns are found in the CBD, in which $Aa{\alpha}$ is the special district of decreasing population and is higher in aged population rate because of aged population low in mobility staying behind and out-migration of non-elderly population. $Ba{\alpha}$, $Ba{\beta}$, $Bb{\beta}$, and $Bc{\beta}$ patterns are found in the inner area, in which neighboring area $Ba{\alpha}$ pattern is located. $Bb{\beta}$ pattern is located at the new developing area of newly built apartment complex. $Cb{\beta}$, $Cc{\alpha}$, and $Cc{\beta}$ patterns are found in the suburbs, among which $Cc{\alpha}$ pattern is highest in population aging. It is likely that the $Cc{\beta}$ under housing land readjustment on a large scale will be the $Cb{\beta}$ pattern. As analyzed above, marriage and out-migration of new family, non-elderly population, with house purchase are main factors in accelerating population aging in the central area of the city. Population aging is responsible for the great increase of aged population with longer life expectancy by the low death rate, the out-migration of non-elderly population, and the age group of new aged population in the suburbs. It is necessary to investigate and analyze the regional patterns of population aging at the time when population problems caused by aging as well as longer life expectancy are now on the increase. I hope that this will help the future study on population aging of the geographical field in Korea. As in the future population aging will be a major problem in our society, local autonomy should make a plan for the problem to the extent that population aging progresses by regional groups and inevitably prepare for it.

• 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 Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.646-680
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• 2000

In this paper, we discuss the design and implementation of a concurrency control manager for a main memory DBMS(MMDBMS). Since an MMDBMS, unlike a disk-based DBMS, performs all of data update or retrieval operations by accessing main memory only, the portion of the cost for concurrency control in the total cost for a data update or retrieval is fairly high. Thus, the development of an efficient concurrency control manager highly accelerates the performance of the entire system. Our concurrency control manager employs the 2-phase locking protocol, and has the following characteristics. First, it adapts the partition, an allocation unit of main memory, as a locking granule, and thus, effectively adjusts the trade-off between the system concurrency and locking cost through the analysis of applications. Second, it enjoys low locking costs by maintaining the lock information directly in the partition itself. Third, it provides the latch as a mechanism for physical consistency of system data. Our latch supports both of the shared and exclusive modes, and maximizes the CPU utilization by combining the Bakery algorithm and Unix semaphore facility. Fourth, for solving the deadlock problem, it periodically examines whether a system is in a deadlock state using lock waiting information. In addition, we discuss various issues arising in development such as mutual exclusion of a transaction table, mutual exclusion of indexes and system catalogs, and realtime application supports.

• International Journal of Quality Innovation
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• v.8 no.3
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• pp.156-172
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• 2007

The high-tech industry is the economic lifeline for Taiwan. Its characteristics are short product life cycle, rapid changes in the market, and a high obsolescence rate for new products. Under globalization, the high-tech industry has adopted Information Technology (IT) to shorten the manufacturing process, reduce costs and conduct product research and development (R&D) to increase the core competence of enterprises and achieve the goal of sustainable operations. Enterprises should actively strengthen their integration with internal and external resources and lead in R&D management to increase industrial operating performance. Effectively managing operations and R&D management evaluation in Taiwan's High-tech Industry has become a critical subject. This study adopted 4 major Balanced Scorecard (BSC) perspectives to establish the Total Performance Evaluation Indicators for the R&D management department in Taiwan's High-tech Industry. The Analytic Network Process (ANP) was applied to evaluate the overall performance of the R&D management department. The research framework is divided into 2 phases. The first phase is combined with the 4 major perspectives, Financial, Customer, Internal Business Process and Learning and Growth, as the related indicators for each measurement perspective. The Key Performance Indicators (KPI) were selected using Factor Analysis to identify the key factor from the complicated indicators. The relationship between the characteristics of each BSC's evaluation perspective is dependence and feedback. This study applied ANP to conduct the calculation and adjustment of correlation between each KPI, and determine on their relative weights for the objective KPI. The "Financial Perspective" for R&D management department in Taiwan's High-tech Industry focused on the budget achievement rate of R&D management. The weight indicator value is (0.05863). The "Customer Perspective" focused on problem-solving satisfaction. The weight value of this indicator is (0.17549). The "Internal Business Process Perspective" focused on the quantity and quality of R&D. The weight value of this indicator is (0.13506). The "Learning and Growth Perspective" focused on improving competence in the research personnel's professional techniques. The weight value of this indicator is (0.02789). From the total weighting indicators, the order of the Performance Indicators for the R&D management department in Taiwan's High-tech Industry is: (1) Customer Perspective; (2) Internal Business Process Perspective; (3) Financial Perspective; and (4) Learning and Growth Perspective.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.379-385
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• 2014

N-Screen era is held due to the cloud computing technology which access to contents anytime, anywhere without any persistent. In the broadcast industry, this broadcast contents is rapidly serviced by variety of media devices such as PC, Smart phone, Tablet, App, IPTV. To Increase the usefulness and usability of the platform, same brand identity have to be maintain by devices and integrated guide which can encompass a variety of media are needed. This study tries to figure out the need of New Media Style Guide to keep brand identity in a variety of new media beyond previously Web style guide which limited in the Web pages. First, Integrated Guide GEL of BBC's and Web style guide of KBS was analyzed. Through the analysis it was found that the limitations and problem of the current web style guide and then suggested the improvement direction. In addition, this study tried to find which design elements should be made for new media style guides through in-depth interview with practitioners who work in broadcast media industry for more than three years. Through the research it was understood the current status of integrated brand identity and found a way to improve forward to new media platforms of KBS.

• Korean Journal of Social Welfare
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• v.60 no.2
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• pp.131-153
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• 2008

Based upon the first national sample of adult men and women, the study aims to examine the prevalence of chid sexual abuse in Korea and factors related to the incidence of child sexual abuse. The results of the study show that 20.8% of the sample experienced one or more types of sexual abuse in their childhood, which indicates that Korean society is not any longer immune to child sexual abuse. With regard to how to cope with sexual abuse, "not informed to anyone and did not get any help at all" is the most major one for all types of sexual abuse. Even those who got help were reported to depend heavily upon private routes such as parents, relatives, or friends, indicating the urgency of establishing systematic intervention schemes for the problem. The results of a logistic regression analysis show that gender of the child, involvement in delinquent behaviors, economic status of the family, number of siblings, and residence in high-crime region are significantly related to the incidence of child sexual abuse. These results of the study would be expected to provide a useful guideline for developing policies or intervention programs aimed to prevent or address child sexual abuse.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.37-45
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• 2008

It is expected that conditions of water resources will be changed in Korea in accordance with world wide climate change. In order to deal with this problem and find a way of minimizing the effect of future climate change, the usefulness of climate model simulation information is examined in this study. The objective of this study is to assess the applicability of GCM (General Circulation Model) information for Korean water resources management through uncertainty analysis. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. An estimator that accounts for climate model simulation and spatial association between the GCM data and observed data is used. Atmospheric general circulation model (AGCM) simulations done by ECMWF (European Centre for Medium-Range Weather Forecasts) with a resolution of $2^{\circ}{\times}2^{\circ}$, and METRI (Meteorological Research Institute, Korea) with resolutions of $2^{\circ}{\times}2^{\circ}$ and $4^{\circ}{\times}5^{\circ}$, were used for indicator variables, while observed mean areal precipitation (MAP) data, discharge data and mean areal temperature data on the seven major river basins in Korea were used for target variables. The results show that GCM simulations are useful in discriminating the high from the low of the observed precipitation, discharge, and temperature values. Temperature especially can be useful regardless of model and season.