• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.188-200
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• 2014

The IPCC 5th Assessment Report (Climate Change 2013: The Physical Science Basis) was accepted at the 36th Session of the IPCC on 26 September 2013 in Stockholm, Sweden. It consists of the full scientific and technical assessment undertaken by Working Group I. This comprehensive assessment of the physical aspects of climate change puts a focus on those elements that are relevant to understand past, document current, and project future of climate change. The assessment builds on the IPCC Fourth Assessment Report and the recent Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. The assessment covers the current knowledge of various processes within, and interactions among, climate system components, which determine the sensitivity and response of the system to changes in forcing, and they quantify the link between the changes in atmospheric constituents, and hence radiative forcing, and the consequent detection and attribution of climate change. Projections of changes in all climate system components are based on model simulations forced by a new set of scenarios. The report also provides a comprehensive assessment of past and future sea level change in a dedicated chapter. The primary purpose of this Technical Summary is to provide the link between the complete assessment of the multiple lines of independent evidence presented in the main report and the highly condensed summary prepared as Policy makers Summary. The Technical Summary thus serves as a starting point for those readers who seek the full information on more specific topics covered by this assessment. Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased. Total radiative forcing is positive, and has led to an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of $CO_2$ since 1750. Human influence on the climate system is clear. This is evident from the increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and understanding of the climate system. Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. The in-depth review for past, present and future of climate change is carried out on the basis of the IPCC 5th Assessment Report.

• Geophysics and Geophysical Exploration
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• v.20 no.3
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• pp.185-192
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• 2017

A sequence of earthquakes with the main shock $M_L$ 5.8 occurred on September 12 2016 in the Gyeongju area. The main shock was the largest earthquakes in the southern part of the Korean peninsula since the instrumental seismic observation began in the peninsula in 1905 and clearly demonstrated that the Yangsan fault is seismically active. The mean focal depth of the foreshock, main shock, and aftershock of the Gyeongju earthquakes estimated by the crustal model of single layer of the Korean peninsula without the Conrad discontinuity turns out to be 12.9 km, which is 2.8 km lower than that estimated based on the IASP91 reference model with the Conrad discontinuity. The distribution of the historical and instrumental earthquakes in the Gyeongju area indicates that the Yangsan fault system comprising the main Yangsan fault and its subsidiary faults is a large fracture zone. The epicenters of the Gyeongju earthquakes show that a few faults of the Yangsan fault system are involved in the release of the strain energy accumulated in the area. That the major earthquakes of Gyeongju earthquakes occurred not on the surface but below 10 km depth suggests the necessity of the study of the distribution of deep active faults of the Yangsan fault system. The magnitude of maximum earthquake of the Gyeongju area estimated based on the earthquake data of the area turns out to be 7.3. The recurrence intervals of the earthquakes over magnitudes 5.0, 6.0 and 7.0 based on the earthquake data since 1978, which is the most complete data in the peninsula, are estimated as 80, 670, and 5,900 years, respectively. The September 2016 Gyeongju earthquakes are basically intraplate earthquakes not related to the Great East Japan earthquake of March 11 2011 which is interplate earthquake.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.15-30
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• 2000

The important considerations in the design of fiber-optic networks are reliability and survivability preparing against a failure. The SDH(Synchronous Digital Hierarchy), the international standard of optical transmission, offers several network reconfiguration methods that enable network to be automatically restored from failure. One of the methods is the SHR(Self Healing Ring), which is a ring topology system. Most network providers have constructed their backbone networks with SHR architecture since it can provide survivability economically. The network architecture has eventually evolved into a multi-ring network comprised of interconnected rings. This paper addresses multi-ring network design problems is to minimize ring-construction cost. This problem can be formulated with MIP(mixed integer programming) model. However, it is difficult to solve the model within reasonable computing time on a large scale network because the model is NP-complete. Furthermore, in practice we should consider the problem of routing demands on rings to minimize total cost. This routing problem involves multiplex bundling at the intermediate nodes. A family of heuristic algorithms is presented for this problem. These algorithms include gateway selection and routing of inter-ring demands as well as load balancing on single rings. The developed heuristic algorithms are applied to some network provider's regional and long-distance transmission networks. We show an example of ring design and compare it with another ring topology design. Finally, we analysis the effect bundling.

• Convergence Security Journal
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• v.20 no.2
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• pp.101-110
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• 2020

Since the third inter-Korean summit, the inter-Korean summit in Pyongyang and the U.S.-North Korea summit in Singapore and Hanoi, denuclearization negotiations are under way that will determine the fate of the Korean Peninsula. However, the negotiations are stalled and some skepticism is expected due to the conflicting U.S.-North Korea stance over the terms of denuclearization. The reason why it is difficult to realize the complete denuclearization of North Korea is that there are a variety of variables such as the traditional security dilemma in Northeast Asia, the hegemonic competition between the U.S. and China, and the formation of a new cold-war system. At a turning point when three inter-Korean summits and three U.S.-North Korea summits were held in the wake of the 2018 PyeongChang Winter Olympics, North Korea's complete denuclearization has become a must-do historical task for Northeast Asia and world peace beyond the Korean Peninsula. In this sense, the inter-Korean summit in Pyongyang is seen as a historic occasion for presenting a new milestone for the denuclearization of North Korea and the development of inter-Korean relations through the 9.19 Pyongyang Joint Declaration and the Military Agreement. Meanwhile, Constructivism, which has become the main paradigm of international political theory, presents the view that ideological variables such as ideology, history and culture define material factors, identity and interests of state actors, and that the structure of international relations can be changed through interaction. In this study, the historical meaning of the 9.19 Pyongyang Declaration, which is now past its first anniversary, was considered from a constructivist perspective. To this end, the development process of constructivism theory and analysis model and the development process of inter-Korean relations were briefly reviewed, and the military implications of the 9.19 Military Agreement were presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.870-877
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• 2020

A suction bucket foundation, especially useful at depths of more than 20m, is a method of construction. The method first places an empty upturned bucket at the target site. Then, the bucket is installed by sucking water or air into it to create negative pressure. For stability, it is crucial to secure the verticality of the bucket. However, inclination by the bucket may occur due to sea-bottom conditions. In general, a repeated intrusion-pulling method is used for securing verticality. However, it takes a long time to complete the job. In this paper, we propose a real-time suction bucket verticality monitoring system. Specifically, the system consists of a sensor unit that collects raw verticality data, a controller that processes the data and wirelessly transmits the information, and a display unit that shows verticality information of a circular steel pipe. The system is implemented using an inclination sensor and an embedded controller. Experimental results show that the proposed system can efficiently measure roll/pitch information with a 0.028% margin of error. Furthermore, we show that the system properly operates in a suction bucket-based model experiment.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.429-435
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• 2020

North Korea declared itself complete with nuclear force after its sixth nuclear test in 2017. Despite efforts at home and abroad to denuclearize the Korean Peninsula, the prospects for the denuclearization are not bright. Along with political and diplomatic efforts to deter NK's WMD threats, the government is required to strengthen its consequence management capabilities against 'catastrophic situations' expected in case of emergency. Accordingly, this study was conducted to present measures to strengthen follow-up management against CBRN threats. The research model was partially supplemented and utilized by the THIRA process adopted and utilized by the U.S. Department of Homeland Security among national-level disaster management plan development models. Korea's consequence management (CM) system encompasses risk and crisis management on disaster condition. The system has been carried out in the form of a civil, government and military integrated defense operations for the purpose of curbing the spread or use of CBRNs, responding to threats, and minimizing expected damages. The preventive stage call for the incorporation of CBRN concept and CM procedures into the national management system, supplementing the integrated alarm systems, preparation of evacuation facilities, and establishment of the integrated training systems. In the preparation phase, readjustment of relevant laws and manuals, maintenance of government organizations, developing performance procedures, establishing the on-site support systems, and regular training are essential. In the response phase, normal operations of the medical support system for first aid and relief, installation and operation of facilities for decontamination, and development of regional damage assessment and control guidelines are important. In the recovery phase, development of stabilization evaluation criteria and procedures, securing and operation of resources needed for damage recovery, and strengthening of regional damage recovery capabilities linked to local defense forces, reserve forces and civil defense committees are required.

• The Journal of Engineering Geology
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• v.8 no.2
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• pp.99-114
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• 1998

The Yangsan fault system of Kyungsang Basin in the southeastern part of Korean peninsula is one of the most important structures in the peninsula. A number of strong earthquakes occurred in the vicinity of the fault. It was suggested that this fault can be divided into three segments: northern, central and southern ones. Earthquake data around the Yangsan fault were classified into two groups as incomplete and complete ones; the former is the data before the Choseon Dynasty and the latter is those since the dynasty. The maximum likelihood method was applied to compute seismicity parameters such as earthquake occurrence rates, b-values of frequency-magnitude relation and maximum possible magnitudes for each segment and the entire fault. These parameters show considerably different values from segment to segment. The b-value for the entire fault turned out to be 0.85 and maximum possible magnitudes for the northern, central and southern segments are 5.2, 6.8 and 6.0, respectively. The mean return periods for the maximum possible magnitudes for each segments are greater than 1000 years. In addition, according to the analysis of the frequency-magnitude relation, the occurrence pattern of earthquakes around the Yangsan fault show more similarity to the characteristic earthquake model than the Gutenberg-Richter model. The data for each segments are, however, too scarce to obtain any physically meaningful results.

• Journal of Information Technology and Architecture
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• v.9 no.2
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• pp.177-186
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• 2012

Navy establishes the Naval Task Forces (TF) for many kinds of maritime operations. Then the TF in the maritime environment performs simultaneous component operations such as ASUW (Anti-Surface Warfare), ASW (Anti-Submarine Warfare), AAW (Anti-Aircraft Warfare), and assault operations. The TF consists of many tactical systems for the completion of missions C4I, VOIP (Voice Over Internet Protocol), DMHS (Digital Massage Handling System), and TDLs (Tactical Data Links) such as LINK-11, 16, ISDL (Inter Site Data Link). When the TF executes naval operations to complete a mission, we are interested in the kill chain for the maritime operations in the TF. The kill chain is a standard procedure for the naval operations to crush enemy defenses. Although each ship has a procedure about a manual for 'how to fight', it leave something to be desired for the TF detailed kill chain currently. Therefore, in this paper, we propose the naval TF's kill chain to perform the naval operations. Then, the operational effectiveness of the TF in the kill chain environment is determined through operation scenarios of TDL system implementation. It is to see the operational information sharing effect to a data link model based on MND-AF OV 6c (statement of tracking operational status) in the maritime operations applied to TDL and is to identify improvements in information dissemination process. We made the kill chain of maritime TF for the effective naval operations.