• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.591-598
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• 2020

Since COVID-19's 1st pandemic came in February 2020, the demand for telemedicine grew greatly that in most countries the deregulation for telemedicine policy have been implemented in more countries. Also in Korea, with the name of 'Non-face-to-face Treatment' telemedicine began to be approved. Telemedicine having strength in chronic disease management has been effective in more and more specialties along with the recent development of ICT that it is expected to contribute to the improvement of the quality of healthcare service and creation of new treatment model. On the contrary it may also exacerbate the distortion in the hospital healthcare service industry in Korea, which is the excessive tipping toward large hospitals. So the dual promotion policy approach in which the settlement of family doctors system extensively utilizing telemedicine for chronic disease management and the support for tertiary hospitals and hospitals focusing on treating foreign patients to provide quality service using telemedicine technology are pursued simultaneously are recommended.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.1-11
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• 2009

TCS Data imply characteristics of traffic conditions. However, there are outliers in TCS data, which can not represent the travel time of the pertinent section, if these outliers are not eliminated, travel time may be distorted owing to these outliers. Various travel time can be distributed under the same section and time because the variation of the travel time is increase as the section distance is increase, which make difficult to calculate the representative of travel time. Accordingly, it is important to grasp travel time characteristics in order to compute the representative of travel time using TCS Data. In this study, after analyzing the variation ratio of the travel time according to the link distance and the level of congestion, the outlier elimination model and the smoothing model for TCS data were proposed. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variation of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.90-97
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• 2009

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, and lower multi-path distortion. To further utilize vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subchannel and bit allocation among users. In this paper, we propose an 0-1 integer programming model formulating the optimal subchannel and bit allocation problem of the multiuser OFDM. We employ a dual-decomposition method that provides a tight linear programming (LP) relaxation bound. Simulation results are provided to show the effectiveness of the 0-1 integer programming model. MATLAB simulation on a system employing M-ary quardarature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multi-paths are carried with the optimal subchannel and bit allocation solution generated by 0-1 integer programming model.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.3069-3085
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• 2018

In this study, we examined the effect of non-cognitive factors on job tenure and tenure using KLIPS. We examine the internal consistency of the big5 personality trait and of the locus of control, and use the parameterized proportional hazards model. As a result, we confirmed that non-cognitive skill such as personality traits and locus of control affect individual labor market performance. Conscientiousness has shown that the job seeking period of adult job seekers is lengthened, thereby lowering the unemployment rate. It can be understood that high attentiveness under uncertainty can misinterpret information, and that lack of decision restricts escape from unemployment. In the tenure analysis, people with internal locus of control tendency were less likely to leave the job due to longer tenure. Those who have internal control can not only be preferred by the organization but also the internal control tendency seems to be the factor that maintains the long-term job because of the motivation and self-control of their actions.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.462-462
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• 2021

최근 도시화 및 불투수면의 증가와 지하수의 과다한 사용으로 직접유출이 증가하고, 침투량이 감소하며, 하천의 건천화가 발생하고 있다. 이에 환경부에서는 이러한 물순환의 왜곡을 막기위해 물환경보전법상의 물순환율을 정의하고 물순환 관리목표를 설정하였다. 하지만 지역 별 물순환 특성을 반영한 관리계획이 부족하고, 현재 제한된 재원의 효율적 활용을 위해서는 물순환 관리지역에 대한 우선순위 결정도 필요하다. 본 연구에서는 PSR framework를 통해 유역 물순환 평가방법론을 만들고 이를 활용한 지역별 관리계획 및 우선순위를 결정하고자하였다. PSR framework는 지속가능성을 위해 OECD가 개발한 개념 모형이며, Pressure, State, Response 세 가지 요소로 구분해 평가하게된다. PSR framework의 기본 개념은 인간의 활동들이 환경에 압력 (P)를 주고, 이로 인해 자연의 질과 영향 (S)을 미치며, 이에대한 회복을 위해 인식과 행동을 통해 정책과 제도 등을 통해 반응 (R)한다는 것이다. 유역 물순환을 4가지 그룹 (기후, 수문학적, 사회경제학적, 환경적)으로 구분하고 각 그룹 별 평가요소에 대하여 도출하였다. 기후그룹은 강우, 수문학적 그룹은 증발산, 토지이용, 유출특성을, 사회경제학적 그룹은 재정, 사회구조, 기반시설, 정책을, 환경적 그룹은 수질, 수생태계를 선정하였다. 이후 각 요소 별 평가를 위해 다양한 지표를 고려하여 선정하였으며, 각 지표를 PSR framework에 맞춰 재분류하였다. 각 지표를 하나의 점수로 통합하기 위해 지표 별 가중치를 산정하였으며, 이때 연구자의 주관이 반영되지않는 엔트로피 기법을 이용하여 산정하였다. 구한 식을 통해 우리나라 소유역구분을 기준으로 모든 지표를 계산하였으며, 각 지표에 가중치를 적용해 유역 종합점수를 산정하고 유역 별 취약지역 및 취약요소를 평가하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.143-143
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• 2020

수도권에 용수를 공급하는 팔당유역은 경제, 사회, 환경적으로 매우 중요한 공공의 자산이며, 이러한 자산을 누리는 데에 이어 국민 모두가 공평한 혜택을 받을 필요가 있다. 수량과 수질의 만족도는 곧 지역민들의 복지이며, 복지는 삶의 질을 높여주는 것을 의미한다. 팔당유역에서는 인간의 개발행위로 인해 하천과 생태계의 지속적인 훼손과 방치가 발생하며, 팔당유역에 대한 수도권과 지역주민들의 사회적, 문화적 요구가 증가함에 따라 수자원의 안정적인 확보와 하천의 자연성 회복을 위해 유역 건전성 평가가 필요하다. 따라서 본 연구에서는 팔당유역 수량과 수질의 평가지표에 대한 과거 10년 동안의 기초자료를 수집하여 SPSS를 통해 통계분석을 실시하였다. 통계분석을 통해 도출된 결과를 이용해 가중치를 산정한 후 각 하천에 대한 유역 건전성 지수산정과 등급평가를 하여 표준유역 규모의 하천 변화 정도에 대한 상세평가를 통해 지역별 현황을 쉽게 파악할 수 있도록 하였다. 수량에 대한 기초자료는 TANK모형을 통해 자연유출량을 산정 후 관측유량과의 차이를 이용하여 산출하였으며, 수질에 대한 기초자료는 물환경정보시스템을 통해 수집하였다. 기초자료를 기반으로 왜곡된 자료의 정규성 확보 및 표준화를 수행하고, SPSS 프로그램을 이용하여 요인분석을 실시한 후 적합성 검토를 통해 최종지표를 산정하였다. 산정된 지표를 주성분 분석에 의한 가중치, 엔트로피에 의한 가중치를 산정하여 비교 후 최종 가중치를 선정하였다. 유역 건전성의 최종평가를 위해 가중치와 지표를 이용하여 지수산정 및 등급화를 실시하였다. 유역 건전성의 등급화를 통해 연도별 하천환경의 변화를 모니터링 함으로써 하천의 가치 보전과 개발에 따른 영향을 최소화할 수 있으며, 하천기본계획 수립 시 기초정보로 이용될 수 있을 것이다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.

• The Journal of Korean Philosophical History
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• no.28
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• pp.363-386
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• 2010

The purpose of this study is to examine the relationship between theory of Confucian moral cultivation and meditation. Recently our community is more interested in 'a disease of mind'. A view of world, life, values which derived from the distorted perception of 'a disease of mind' can not be treated by psychiatric methods. In this sense, 'a disease of mind' is different from psychiatric illness. In this reason, alternative therapies applying philosophy, literature, arts, and humanities are attracting attention. Meditation is also one of them. In general, Meditation has been developed in Buddhism, but its method is closely related with Confucianism. Buddhist meditation has a pessimistic view of the reality in human life, but that of Confucian philosophy has laid stress on the reality and ego in human life. At this point, the Confucian meditation could provide a clue of solution for us in treatment of a disease of human mind. So Confucian moral cultivation and meditation have a great significance for the treatment of this disease as a methodology. In general, mental healing or psychotherapy has been proceeded by way of dialogue. 'Talking Cure' was conceived to let clients themselves recognize their current situation and find out the problem: "what happened and what's wrong" in their minds. But it does not have a high possibility of successful cure for subjects who are in the state of frustration, confusion, and lost of value. And also it is very difficult to apply to special institutions such as correctional institutions and military soldier who are targeted by current application of Humanities therapy. On this sense, it seems to be valuable to apply Confucian cultivation of mind and meditation which have emphasized the importance of mind-control for this. This study tries to examine theoretically how to relate the Confucian cultivation of mind with meditation, and to suggest a model of Humanities therapy that could be applied by Toe-gye's 『The Method on Preservation of Human mind(活人心方)』. Although Confucian cultivation of mind could present a meaningful theory for curing the disease of mind, it is very difficult to put the theory into practice. It is because Confucian cultivation of mind in itself is a kind of instruction that you need to do in all of your life, and essentially it is difficult to expect a temporary effect by performance or practice. So a cure model of Confucian cultivation of mind will be suggested on this assumption and limitations. This model is attempted on the main purpose of Humanities therapy in accordance with the development of a Korean model.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.1-15
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• 2015

Urban flooding threatens human beings and facilities with chemical and physical hazards since the beginning of human civilization. Recent studies have emphasized the integration of data and models for effective urban flood inundation modeling. However, the model set-up process is tend to be time consuming and to require a high level of data processing skill. Furthermore, in spite of the use of high resolution grid data, inundation depth and velocity are varied with building treatment methods in 2-D inundation model, because undesirable grids are generated and resulted in the reliability decline of the simulation results. Thus, it requires building generalization process or enhancing building orthogonality to minimize the distortion of building before converting building footprint into grid data. This study aims to develop building generalization method for 2-dimensional inundation analysis to enhance the model reliability, and to investigate the effect of building generalization method on urban inundation in terms of geographical engineering and hydraulic engineering. As a result to improve the reliability of 2-dimensional inundation analysis, the building generalization method developed in this study should be adapted using Digital Building Model(DBM) before model implementation in urban area. The proposed building generalization sequence was aggregation-simplification, and the threshold of the each method should be determined by considering spatial characteristics, which should not exceed the summation of building gap average and standard deviation.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.525-535
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• 2018

If the frequency of a particular class is excessively higher than the frequency of other classes in the classification problem, data imbalance problems occur, which make machine learning distorted. Corporate bankruptcy prediction often suffers from data imbalance problems since the ratio of insolvent companies is generally very low, whereas the ratio of solvent companies is very high. To mitigate these problems, it is required to apply a proper sampling technique. Until now, oversampling techniques which adjust the class distribution of a data set by sampling minor class with replacement have popularly been used. However, they are a risk of overfitting. Under this background, this study proposes ROSE(Random Over Sampling Examples) technique which is proposed by Menardi and Torelli in 2014 for the effective corporate bankruptcy prediction. The ROSE technique creates new learning samples by synthesizing the samples for learning, so it leads to better prediction accuracy of the classifiers while avoiding the risk of overfitting. Specifically, our study proposes to combine the ROSE method with SVM(support vector machine), which is known as the best binary classifier. We applied the proposed method to a real-world bankruptcy prediction case of a Korean major bank, and compared its performance with other sampling techniques. Experimental results showed that ROSE contributed to the improvement of the prediction accuracy of SVM in bankruptcy prediction compared to other techniques, with statistical significance. These results shed a light on the fact that ROSE can be a good alternative for resolving data imbalance problems of the prediction problems in social science area other than bankruptcy prediction.