• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.338-347
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• 2019

The purpose of this study is to provide policy and adaptive interventions for quality of life of the elderly and evidence-based data. For this, meta-analysis was performed using CMA program, and the final 65 researches were used for analysis. The results, (1)The risk factors(depression, solitude, anxiety, suicidal Ideation, stress) showed the effect size which is suitable for quality of life. The effect size of depression was the highest. (2)The protective factors(self-esteem, self-efficacy) showed medium effect size and large effect size. Among them, self-esteem showed the greatest effect size of quality of life. However, self - control appeared to have a low effect size.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.95-103
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• 2008

Knowledge of expected losses in terms of physical, economic, and social damages due to a potential earthquake will be helpful in the effort to mitigate seismic hazards. In this study, losses due to a magnitude 6.7 scenario earthquake in the Gyeongju area have been estimated using the deterministic method in HAZUS. The attenuation relation proposed by Sadigh et al.(1997) for site classes B, C, and D, which are assumed to represent the characteristics of the strong-motion attenuation in the Korean Peninsula, has been applied. Losses due to the hypothetical earthquake have been also calculated using other attenuation relationships to examine their roles in the loss estimation. The findings indicate differences among the estimates based on various attenuation relationships. Estimated losses of the Gyeongju area by a scenario earthquake using HAZUS should be seriously considered in the planning of disaster response and hazard mitigation.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.2
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• pp.205-237
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• 2014

Last 50 years there were a lot of space subjects launched by space activities of many states and these activities also had created tremendous, significant space debris contaminating the environment of outer space. The large number of space debris which are surrounding the earth have the serious possibilities of destroying a satellite or causing huge threat to the space vehicles. For example, Chinese anti-satellite missile test was conducted by China on January 11, 2007. As a consequence a Chinese weather satellite was destroyed by a kinetic kill vehicle traveling with a speed of 8 km/s in the opposite direction. Anti-satellite missile tests like this,contribute to the formation of enormous orbital space debris which can remain in orbit for many years and could interfere with future space activity (Kessler Syndrome). The test is the largest recorded creation of space debris in history with at least 2,317 pieces of trackable size (golf ball size and larger) and an estimated 150,000 debris particles and more. Several nations responded negatively to the test and highlighted the serious consequences of engaging in the militarization of space. The timing and occasion aroused the suspicion of its demonstration of anti-satellite (ASAT) capabilities following the Chinese test of an ASAT system in 2007 destroying a satellite but creating significant space debris. Therefore this breakup seemed to serve as a momentum of the UN Space Debris Mitigation Guidelines and the background of the EU initiatives for the International Code of Conduct for Outer Space Activities. The UN Space Debris Mitigation Guidelines thus adopted contain many technical elements that all the States involved in the outer space activities are expected to observe to produce least space debris from the moment of design of their launchers and satellites until the end of satellite life. Although the norms are on the voluntary basis which is normal in the current international space law environment where any attempt to formulate binding international rules has to face opposition and sometimes unnecessary screening from many corners of numerous countries. Nevertheless, because of common concerns of space-faring countries, the Guidelines could be adopted smoothly and are believed faithfully followed by most countries. It is a rare success story of international cooperation in the area of outer space. The EU has proposed an International Code of Conduct for Outer Space Activities as a transparency and confidence-building measure. It is designed to enhance the safety, security and sustainability of activities in outer space. The purpose of the Code to reduce the space debris, to allow exchange of the information on the space activities, and to protect the space objects through safety and security. Of the space issues, the space debris reduction and the space traffic management require some urgent attention. But the current legal instruments of the outer space do not have any binding rules to be applied thereto despite the incresing activities on the outer space. We need to start somewhere sometime soon before it's too late with the chaotic situation. In this article, with a view point of this problem, focused on the the Chinese test of an ASAT system in 2007 destroying a satellite but creating significant space debris and tried to analyse the issues of space debris reduction.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.613-613
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• 2015

최근 전 지구적인 온난화로 인한 이상기후에 따라 강수량이 증가하고, 특정지역에만 국한되어 집중적으로 비가 내리는 국지성 집중호우의 발생 빈도가 증가하여 이로 인한 극한 홍수나 강우로 인한 산사태 등의 재해가 반복적으로 발생하고 있다. 홍수는 재산 및 인명에 이르기까지 막대한 피해를 야기한다는 점에서 이를 대비하기 위한 방안이 필수적이므로 국가적인 차원에서 홍수피해를 경감시키기 위한 여러 가지 구조적 또는 비구조적 대책들을 제시하고 있지만, 정확한 기상 변화의 예측이 어렵고 다양한 유발 원인들로부터 비롯된 홍수에 모두 대응할 수 있는 통합 대책 마련이 어려운 실정이다. 즉, 사전예방보다는 피해 복구에만 중점을 두고 있기 때문에 홍수 발생 유역의 지역적인 홍수피해 특성을 반영하지 못할 뿐만 아니라 어느 지역이 상대적으로 홍수피해의 위험성이 높은 지역인지도 파악하기 어렵다. 따라서, 본 연구에서는 도시홍수피해 유형인 내수침수피해와 외수침수피해의 유형에 따라 사례들을 조사하고 관련문헌들로부터 도시 홍수 취약성 평가를 위한 대표적 인자들을 도출하였다. 도출된 인자들을 각각 IPCC의 취약성 평가 프레임에 따라 기후노출, 민감도 그리고 적응능력으로 구분하고 도시 상습침수지역인 도림천 유역을 시범 지역으로 하여 도시홍수 취약성 평가를 위한 지수를 개발하고자 한다. 본 연구를 통하여 향후 도시홍수피해의 잠재적 위험성이 높을 것으로 판단되는 유역에 대한 활용방안을 제시하고 유역의 특성 및 중요도에 따른 치수사업의 우선순위를 결정하는 등 유역의 특성을 반영한 구체적 적응정책의 방향성을 세우는데 기초자료로 제공될 수 있으며, 도시홍수로 인한 인명 및 재산의 피해를 최소화 하는 것에 목적이 있다.

• Korean Journal of Forensic Psychology
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• v.13 no.1
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• pp.53-74
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• 2022

This article aims to explore the possibility of forgiving among serious juvenile offenders placed in correctional facilities, as an alternative to current correctional approaches. The definition, characteristics, and misconceptions of forgiveness were outlined, and the two major models of forgiveness were introduced. The differences between the two concepts of forgiveness in psychological literature and in restorative justice were addressed. Based on the prior studies on the prevalence of adverse childhood experiences in serious juvenile delinquents and a recent forgiveness project conducted in a maximum-security prison, it was argued that it would be possible for a small number of serious juvenile offenders in correctional facilities to forgive someone who did injustice in the past, which would result in an improvement in the outcomes of correctional education and treatment. Some limitations of this article and the need of further studies were pointed out as well.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.217-239
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• 2009

As gas hydrate is recently emerging as a new energy source to solve environmental and exhaustion problems caused by fossil energy, Korea is working on a gas hydrate development project under a 10-year plan from 2005 to 2014. Gas hydrate is expected to have a big effect on the economy and society of Korea, which is largely depending on energy imports besides water energy and atomic energy. However, it is uncertain whether the project will produce successful results. Thus, it is very important to improve its validity and to propose effective execution strategies by evaluating the value of the project in advance. Thus, this study intended to include new information, which had not been evaluated in existing methods, and to reduce biases or errors in value evaluation results by applying a fuzzy risk analysis to the real option model in order to evaluate the value of a gas hydrate development project. It is advantageous that the real option model based on the fuzzy risk analysis modelizes the vagueness and inexactness of intangible element judgment into an appropriate language scale so as to evaluate these elements clearly and integrate them with estimated financial performance results. The application of the fuzzy risk analysis makes it possible to conduct an analysis by dissolving a decision-making issue with complicated and various attributes into several simplified problems. With the continuing high oil prices and today's demand of clean energy, the necessity of energy resources and technology development projects keeps growing. Amid this situation, it is expected that these study results will contribute to proposing a guideline not only for gas hydrate projects but also for policy decision-making related to future energy industries.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.610-621
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• 2021

The soil creep, primarily caused by earthquakes and torrential rainfall events, has widely occurred across the country. The Korea Forest Service attempted to quantify the soil creep susceptible areas using a discriminant value table to prevent or mitigate casualties and/or property damages in advance. With the advent of advanced computer technologies, machine learning-based classification models have been employed for managing mountainous disasters, such as landslides and debris flows. This study aims to quantify the soil creep susceptibility using several classifiers, namely the k-Nearest Neighbor (k-NN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) models. To develop the classification models, we downscaled 292 data from 4,618 field survey data. About 70% of the selected data were used for training, with the remaining 30% used for model testing. The developed models have the classification accuracy of 0.727 for k-NN, 0.750 for NB, 0.807 for RF, and 0.750 for SVM against test datasets representing 30% of the total data. Furthermore, we estimated Cohen's Kappa index as 0.534, 0.580, 0.673, and 0.585, with AUC values of 0.872, 0.912, 0.943, and 0.834, respectively. The machine learning-based classifications for soil creep susceptibility were RF, NB, SVM, and k-NN in that order. Our findings indicate that the machine learning classifiers can provide valuable information in establishing and implementing natural disaster management plans in mountainous areas.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Korea Water Resources Association
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• v.39 no.5 s.166
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• pp.441-452
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• 2006

Recently the natural damage associated with flood disaster has been dramatically increased. Especially, inundation in the urban area causes serious damage to people and assets because of the concentration of infrastructure and population growth. The purpose of this study is to develop a new urban inundation model combining a storm sewer system model and a 2D overland-flow model for the estimation inundation depth In urban area caused by the surcharge of storm sewers. The movement of water in the studied urban watershed is characterized by two components, namely, the storm sewer flow component and the surcharge-induced inundation component. The model was applied to Goonja and Jangan catchments. Inundated depths were presented to demonstrate model simulation results. The simulation results can help the authority decide preventing flood damages by redesigning and enlarging the capacities of storm sewer systems in the inundation-prone areas. The model can also be applied to make the potential inundation area map and establish flood-mitigation measures as a part of the decision support system for flood control authority.

• Spatial Information Research
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• v.22 no.3
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• pp.71-77
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• 2014

There are numbers of unpredictable risk factors in the disaster scenes such as fire, explosion and fail to early life-saving or holding the flames which can lead to massive damage. In particular, fire-fighters who arrive on the scene within 5 minutes after dispatching, have a limitation to get aware to the situation of scene fully, because of immediate deploy to disaster scene with limited information. This situation may lead to disturbance that fire-fighters perform effective fire-fighting activities, to put fire-fighter's life at risk by misjudge the situation. Previous domestic and International studies focused vulnerability for spatial area or features which can damage to life and property in the event of anticipated. In this study, we have been developed fire-fighting vulnerable zone model that can analyze comprehensively hindrance factors for fire-fighting activities targeting whole life cycle of fire-fighting activities from dispatch to fire suppression or life-saving. In addition, we have been given shape to finality and applicability for our model by defining the new concept of fire-fighting vulnerable zone which can be distinguished from the concept of fire vulnerable area in previous studies. The results of this study can be used to analysis fire-fighting vulnerable zone type analysis, establish fire-fighting policies and improve the performance of decision-making process.