• Journal of Environmental Policy
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• v.3 no.1
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• pp.31-54
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• 2004

This paper aims at analyzing the issues on how to improve UNEP's roles in international environmental governance context. Although UNEP has been presumed to play a leading role in addressing global environment problems, several problems (such as collective action problem, fragmentation, lack of authority and insufficient legitimacy) in its governance have led to losing its leadership to other entities such as the World Bank, OECD and CSD. While a position of changing UNEP's status to an independent international organization has not been developed enough, several efforts, which might not be sufficient to respond to the changing environment of international environmental governance, have been made to strengthen UNEP's roles in the short run. These include universal membership, strengthening the financing of UNEP, and issues concerning MEAs. Whether current efforts for enhancing UNEP's roles in international environmental governance will be successful or not, would rely on to what extent interested parties hold political wills for its reforms and how to draw a compromise on critical issues among those parties.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.410-413
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• 2008

Existing Outlier detections have been widely studied in geosensor networks. Recently, machine learning and data mining have been applied the outlier detection method to build a model that distinguishes outliers based on anchored criterion. However, it is difficult for the existing methods to detect outliers against incoming time-variant data, because outlier detection needs to monitor incoming data and classify irregular attacks. Therefore, in order to solve the problem, we propose a time-variant outlier detection using 2-dimensional grid method based on unanchored criterion. In the paper, outliers using geosensor data was performed to classify efficiently. The proposed method can be utilized applications such as network intrusion detection, stock market analysis, and error data detection in bank account.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.357-366
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• 2010

Many tree algorithms have been developed for regression problems. Although they are regarded as good algorithms, most of them suffer from loss of prediction accuracy when there are many noise variables. To handle this problem, we propose the multi-step GUIDE, which is a regression tree algorithm with a variable selection process. The multi-step GUIDE performs better than some of the well-known algorithms such as Random Forest and MARS. The results based on simulation study shows that the multi-step GUIDE outperforms other algorithms in terms of variable selection and prediction accuracy. It generally selects the important variables correctly with relatively few noise variables and eventually gives good prediction accuracy.

• Journal of Family Resource Management and Policy Review
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• v.6 no.2
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• pp.1-14
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• 2002

The purpose of this study was examine and clarify the recognition according to gender of sexual harassment in the office. The samples were consisted of 250 employees in a seoul headquarter and 13 branches of S bank. the data were analyzed using percentage, frequency, mean, 1-test, F-test and ANOVA. The results of this study were as follows; 1) female workers recognized sexual harassment as severe problem, but male workers as minor and trivial things. 2) workers recognized the cause of sexual harassment as female low position in the office and sexual distinction 3) workers recognized sexual harassment type as visual, verbal and physical harassment. 4) workers recognized the main assaulters of sexual harassment as male senior workers and co-workers. 5) worker recognized place of harassment as times of workers' dining together. 6) worker recognized the victim of sexual harassment was apt to experience anger, hurt of self-respect, shame and embarrassment. 7) female workers recognized necessity of sexual education but male workers none of it.

• KCID journal
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• v.17 no.2
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• pp.28-34
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• 2010

This study re-exams hydrologic stability on spillway outlet capacity of agricultural reservoirs using hydrologic data with current rainfall condition instead of project hydrologic data applied at design on Backgok reservoir located in Chungbuk province. It is concluded that Backgok reservoir is not hydrologically stable and therefore structural measures including the extension of spillway and non structural measures should be taken. Continuous basic plan for river maintenance including additional bank reinforcement to bottom river shall be carried out. Due to high peak flood with more than 290% compared to 200 year frequency probability flood which was design standard of the past in view of the results of calculating PMF according to revised design standard for reservoirs, there could a problem for securing rationality in case of applying PMF with design flood. Therefore, hydrological stability, construction, and maintenance cost shall be synthetically studied and reasonal application shall be made if the decision is made on applying PMF with design flood.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.325-329
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• 2003

This paper discuss the method of the system's efficient control using a Intelligent hybrid algorithm in nonlinear dynamics systems. Existing neural network and genetic algorithm for the control of non-linear systems work well in static states. but it be not particularly good in changeable states and must re-learn for the control of the system in the changed state. This time spend a lot of time. For the solution of this problem we suggest the intelligent hybrid self-tuning controller. it includes neural network, genetic algorithm and immune system. it is based on neural network, and immune system and genetic algorithm are added against a changed factor. We will call a change factor an antigen. When an antigen broke out, immune system come into action and genetic algorithm search an antibody. So the system is controled more stably and rapidly. Moreover, The Genetic algorithm use the memory address of the immune bank as a genetic factor. So it brings an advantage which the realization of a hardware easy.

• Journal of the Korean Professional Engineers Association
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• v.42 no.3
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• pp.22-26
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• 2009

As Korea's water resources are dominated by intense summer rainfall and steep mountainous territory, it is inevitable for most of the rainfall in Korea to flow into sea immediately and directly. It cannot help having severe conditions which droughts and floods occur repeatedly due to the seasonal and geological conditions in Korea. Those kinds of disasters will be expected more frequently and seriously in the future because of the unexpected climate changes in the world. Therefore, Korean government will plan to develop small and medium-size dams environmentally friendly, multi-regional water supply system continuously and alternative water resources such as river bank filtrations, rainwater storages and underground dams, in order to prevent floods as well as to secure stable water supply.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2143-2148
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• 2011

In general, existed kiosk using touch-screen based kiosk system has been used by only single user, so that multiple users to access this kiosk need to provide a lot of waiting time and maintenance costs. To solve this problem, the framework design based on Bluetooth profile for kiosk servers is presented. The proposed kiosk system can be more efficiently used in theater, train station, bank, government, and public offices by using Bluetooth module and AP in mobile system such as smart phone.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.179-188
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• 2004

Bankruptcy prediction is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. Recently, support vector machine (SVM) has been applied to the problem of bankruptcy prediction. The SVM-based method has been compared with other methods such as neural network, logistic regression and has shown good results. Genetic algorithm (GA) has been increasingly applied in conjunction with other AI techniques such as neural network, CBR. However, few studies have dealt with integration of GA and SVM, though there is a great potential for useful applications in this area. This study proposes the methods for improving SVM performance in two aspects: feature subset selection and parameter optimization. GA is used to optimize both feature subset and parameters of SVM simultaneously for bankruptcy prediction.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.300-304
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• 2016

본 논문에서는 한국어 의미역 결정을 순차열 분류 문제(Sequence Labeling Problem)가 아닌 순차열 변환 문제(Sequence-to-Sequence Learning)로 접근하였고, 구문 분석 단계와 자질 설계가 필요 없는 End-to-end 방식으로 연구를 진행하였다. 음절 단위의 RNN Search 모델을 사용하여 음절 단위로 입력된 문장을 의미역이 달린 어절들로 변환하였다. 또한 순차열 변환 문제의 성능을 높이기 위해 연구된 인풋-피딩(Input-feeding) 기술과 카피넷(CopyNet) 기술을 한국어 의미역 결정에 적용하였다. 실험 결과, Korean PropBank 데이터에서 79.42%의 레이블 단위 f1-score, 71.58%의 어절 단위 f1-score를 보였다.