• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.1-7
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• 2020

Recently 5G technology is one of the technologies that has been receiving much positive responses from users as it is integrated with virtual technology. However, 5G's security issues have not been fully resolved and more security is soon required. In this paper, an approach technique is proposed as a probability-based hierarchy to provide personal privacy for 5G-based IoT users more safely. The proposed technique is aimed at not exposing the privacy of IoT users to third parties by using two random keys created personally by IoT users. In order to satisfy both safety and efficiency, the proposed technology divides the privacy of IoT users into two layers. In the first stage, IoT users will control access to intermediate media using anonymous keys generated by IoT users, and in the second stage, information of IoT users registered with servers will be darkened and replicated. The proposed technique has improved the accuracy of the privacy protection of IoT users as they assign weights to layered information after layering users' privacy information on a probabilistic basis.

• Journal of Korean Society of Forest Science
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• v.99 no.1
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• pp.111-124
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• 2010

This study has intended to develop an evaluation model to select suitable locations of recreation forests in accordance with their types, and to apply the models to the feasibility study of selecting suitable recreation forest locations of candidate sites. To reach this goal, this study employed a Delphi expert survey method and Analytic Hierarchy Process (AHP) for the whole process of model building. And the followings are what this study has found during model building and application process. First, the assessment criteria for classifying recreation forests and selecting suitable locations were initially identified through justification process with two rounds of expert review, after broken down into 2 categories, and then further divided into 6 items and 12 indicators accompanying with hierarchical structure. Second, in the third phase of Delphi expert survey, the relative weights of the assessment criteria were derived by employing AHP. Through overlaying two evaluation categories including resource and usability, 4 types of recreation forest were presented. In the forth phase of the Delphi survey, this study has developed an evaluation model to select suitable locations of recreation forests in accordance with their types using relative weights of the selected indicators through. This study has applied the models to the feasibility study of selecting suitable recreation forest locations of candidate sites, and found that the usability of recreation forest was severely affected by the distance from the capital region, that the closer the locations of natural recreation forests from the capital region, the more advantageous. The developed model can be used to designate recreation forests in accordance with their types.

• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.307-331
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• 2014

The purpose of the present study was to explore latent trajectory classes in the longitudinal change of depression measured using CES-D. The study data was extracted from the Korea Welfare Panel Study Data collected from 2006 to 2010. It consisted of 8,900 adults with aged over 19. Growth Mixture Modeling(GMM) was used to explore possible latent trajectory classes in the change of depression over time. The major findings of the present study were as follows. First, there were five latent trajectory classes in the longitudinal change of depression. Second, there were 4 latent trajectory classes of depression for people in a non-poverty group, while there were 3 latent trajectory classes of depression for people in a poverty group. These findings lead to three conclusions. First, 12.1% of the sample shows that their depression level increases over time. Second, the previous research findings of decreased depression over time might be caused by the combination of two latent trajectory classes(a low level depression sustain group and a depression decrease group). Lastly, the latent trajectory classes in the longitudinal change of depression, which are found in the present study, might be caused by interactions among depression, age, and poverty status.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.70-80
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• 1999

In this paper, a new hierarchical image segmentation algorithm based on human visual system(HVS) characteristic is proposed which can efficiently reduce and control transmission information quantity without the degradation of the subjective and objective image quality. It consists of image segmentation based on mathematical morphology and region merging considering HVS characteristic for the pairs of two adjacent regions at each level of the hierarchy. Image segmentation is composed of 3-level hierarchical structure. In the region merging structure of each level, we extract the pairs of two adjacent regions which human vision can't discriminate, and then merge them. The proposed region merging method extracts pairs of two neighbor regions to be merged and performs region merging according to merging priority based on HVS characteristics. The merging priority for each adjacent pair is determined by the proposed merging priority function(MPF). First of all, the highest priority pair is merged. The information control factor is used to regulate the transmission information at each level. The proposed segmentation algorithm can efficiently improve bottleneck problem caused by excessive contour information at region-based very low bit rate coding. And it shows that it is more flexible structure than that of conventional method. In experimental results, though PSNR and the subjective image quality by the proposed algorithm is similar to that of conventional method, the contour information quantity to be transmitted is reduced considerably. Therefore it is an efficient image segmentation algorithm for region-based very low bit rate coding.

• Korean Journal of Social Welfare Studies
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• v.49 no.2
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• pp.159-180
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• 2018

The purpose of this study is to identify the trajectories in the use time of children from community children centers and to examine the predictive factors and developmental factors related to each trajectory. The data were derived from the second stage of the Community Children Center Panel Survey using from the first wave (2014) to the third wave (2016). A total of 606 samples were selected from the forth to sixth grades of elementary school. Latent class growth model was employed to identify the trajectories, and the multinominal logistic regression and the logistic regression analysis were used to examine predictive factors and developmental factors. Main results indicated that three types of trajectory were identified: high using group, low using group, and high initial using-rapid declining group. Sex, parental supervision, and use duration were found to be significant predictors. Regarding developmental factors, children who constantly use the community children centers were more likely to increase academic performance and school adaptation. However, no significant results were found for aggression and delinquent behaviors. Based on these findings, this study have suggested the future direction of the community children center.

• Korean Journal of Social Welfare Studies
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• v.48 no.4
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• pp.157-185
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• 2017

This study aimed to explore the trajectories of economic preparations for the aging among people with physical disabilities and to identify the determinants according to the Andersen model. For this study, data were drawn from Panel Survey of Employment for the Disabled (PSED). A total of 1,847 samples were used from the second to the eighth wave. Latent class growth model was conducted to explore the longitudinal change classes for the disabled, and the multinominal logistic regression analysis was conducted to examine the influence of the determinants. As a result, four classes were identified: preparation decrease group, continuous non-preparation group, preparation increase group, and continuous preparation group. Each group was found to be associated deferentially with education level, family income, socioeconomic status, employment, home ownership, national basic livelihood security recipient status, and ADL. These findings proposed the practical and political implications for the strategies concerned with facilitating the economic preparations for the aging among the disabled.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.346-353
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• 2020

The purpose of this study was to explore types of longitudinal changes in interactions between mothers and 4-year-old children in primary school as well as the effects on media device addiction. To explore interaction types between mothers and children, latent class growth modeling (LCGM) and BCH were used in a three-step approach. Data from the 6-10th wave of the Panel Study of Korea Children were used. First, the trajectory of the mother-child interactions was linear and decreased across time. This linear decrease was classified into the following three trajectories: high-decreasing, average-deceasing, and low-decreasing. Second, BCH was performed to examine media device addiction in each trajectory, and the findings show that children who had low initial mother-child interactions over time were more likely to experience daily disturbances in adaptive functions such as withdraw or tolerance than other groups of children. The results indicate that maximizing the quality of mother-child interactions in childhood through primary school can lower media device addiction in children.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.175-181
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• 2022

The condition of infrastructure deteriorates as the service life increases. Since most infrastructure in South Korea were intensively built during the period of economic growth, the proportion of outdated infrastructure is rapidly increasing now. Aging of such infrastructure can lead to safety accidents and even human casualties. To prevent these issues in advance, periodic and accurate inspection is essential. For this reason, the need for research to detect various types of damage using computer vision and deep learning is increasingly required in the field of remotely controlled or autonomous inspection. To this end, this study proposed a neural network structure that can detect concrete damage by classifying it into three types. In particular, the proposed neural network can detect them more accurately through a hierarchical learning technique. This neural network was trained with 2,026 damage images and tested with 508 damage images. As a result, we completed an algorithm with average mean intersection over union of 67.04% and F1 score of 52.65%. It is expected that the proposed damage detection algorithm could apply to accurate facility condition diagnosis in the near future.

• Journal of Family Resource Management and Policy Review
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• v.27 no.3
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• pp.67-75
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• 2023

This study will examine the changing nature of housework by analyzing participation in domestic work among 30-somethings according to generational and life cycle characteristics. To this end, 2,687 men and women in their 30s were taken from the 2020 Family Status Survey data, and a latent class analysis was conducted to categorize their participation in housework. The subjects were categorized into three groups: overall non-participation (18.05%), overall participation (59.96%), and intensive cleaning participation (21.99%). Gender, employment status, family life cycle, and attitudes about gender roles were significantly related to participation in housework. Men were more likely to be in the overall non-participation group, while women were more likely to be in the overall participation group. Individuals in the pre-formative period of the family life cycle were more likely to be in the overall non-participation group, while those in the formative and expanding periods were more likely to be in the overall participation group. The results of this study suggest that gender inequality in housework is common in the younger generation; the results also show that, in the same generation, individual participation in housework differs according to family life cycle.

• Journal of The Korean Association For Science Education
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• v.6 no.2
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• pp.53-62
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• 1986

본 연구의 목적은 한국 중 고등학교 학생들의 지적 발달의 특성을 조사 분석함으로써 교과서 및 교육과정의 개발에 필요한 기초자료를 얻으려는 것이다. 지역, 학년, 연령, 성 및 가정의 사회 경제적 지위에 따른 인지 발달 특성을 조사하였다. 연구의 대상은 전국을 대도시, 중 소도시, 농촌으로 유층화한 유층군집 표집방법에 의해 표집한 중학교 1학년부터 고등학교 2학년까지의 남 녀 학생이었다. 표집학생 수는 중학교가 18개교 54학급 3,164명이었고, 고등학교가 18개교 36학급 1,981명이었다. 가정의 사회 경제적 지위는 가정의 경제적 형편, 부의 직업, 부의 학력, 가정의 수입 정도를 고려하여 4계층으로 구분하였다. 사용된 도구는 지적 영역의 조사에 Piaget의 인지발달이론에 따른 논리발달 검사를 이용했다. 분석된 결과를 요약하면 다음과 같다. 첫째, 명제논리, 확률논리, 조합논리, 변인조작개념은 연령과 학년이 높아질수록, 대도시로 갈수록, 사회 경제적 지위가 높을수록 더욱 발달하는 경향이다. 둘째, 개념의 발달경향에 있어서 이원추리와 조합논리개념의 발달이 확률논리와 명제논리 개념의 발달보다 빠른 경향이다. 셋째, 한국의 중등학생 중에서 12세의 64.6%, 13세의 58.1%, 14세의 43.8%, 15세의 30.1%, 16세의 22.6%가 구체적 조작 후기에 도달해 있다. 넷째, 중등학생의 학년별 인지발달경향을 보면 중1의 69.8%, 중2의 51.1%, 중3의 47.4%, 고1의 21.6%, 고2의 21.7%가 구체적 후기의 발달수준이다.