• Journal of the Economic Geographical Society of Korea
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• v.22 no.3
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• pp.237-245
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• 2019

The aim of this article is to introduce articles of the special issue on 'Revitalization Conditions on Crisis on Industrial Regions: Experience from Europe and the Republic of Korea, and to explore policy alternatives to crisis on industrial regions on the basis of policy diagnoses and prescriptions. In the existing research, diagnoses of such Korean regions are quantitatively focused upon industry, employment, plant, consumption, investment, real estate, and labour market, and are qualitatively based upon external environment and functional, structural and spatial characteristics. Prescriptions of such regions emphasize the establishment of a law and an institutional fix, financial supports, jobs' creation, industrial diversification, the intensification of urban foundation throughout the urban revitalizaion. In the policy development for these regions, it is required to link the industrial sector to social, educational, political and welfare sectors, and furthermore the collaboration of inter- and intra-ministry and the active participation of provincial and local governments are needed.

• Korean Journal of Social Welfare Studies
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• v.47 no.1
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• pp.57-92
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• 2016

The Correlations Between the Labour Market Structure and Poverty of the Regions The main objectives of this study are to make an investigation into the spatial characteristics of poverty and to analyze the effects of regional labour market structure. Most previous studies on poverty were more likely to examine internal factors like the characteristics of poor households or family structures than external factors in terms of the regional environments. In order to achieve these goals, this study used the Small Area Estimation designed to estimate the income of each household and then calculate the poverty rate of each local area in order to examine the spatial characteristics of poverty. The poverty distribution in Korea showed the local labour market structures effect on the region poverty rate. The Korean economy now exhibits a big gap between the haves and the have-nots and between urban areas and rural areas. The poverty rate of particular regions will increase and those in the areas will face deteriorated circumstances falling into poverty traps. This study reflects this stern reality and empirically proved the strong need for consideration of regional characteristics in conducting studies on poverty and related policy amendments.

• 한국노년학
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• v.29 no.3
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• pp.1159-1182
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• 2009

The purpose of this study is to examine everyday emotional experience of urban elderly in Korea. Specifically, this study explores gender differences in the effect of place/location of activity and companionship on the daily emotional experience. Data were collected from 148 urban elderly (men=76, women=72) in Seoul, using Experience Sampling Method(ESM). The unit of analysis was the self-report and in total 5,530 self-reports were provided. The statistical methods used for the data analyses were descriptive statistics, t-test, χ² verification, and ANOVA. The major findings are as follows. First, the elderly in Korea spend a quite substantial portion of their time at home, and they spend the largest share of their time in company with their spouse. Second, women report higher intensity of stress and irritation than men in terms of overall emotional experience. Third, the effect of activity location and companionship on emotional experience turned out to be different depending on gender. Emotional experience of daily lives and overall quality of life are shown to be inter-related. Based on these findings, this study provides a significant implication that situational contexts of experience should be considered in order to understand the daily emotional experience of the contemporary Korean elderly.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.

• Cartoon and Animation Studies
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• s.14
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• pp.129-150
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• 2008

The article concerns the relationship between the animation festival and the regional cultural industries. In particular, the article studies the WAF(Web Animation Festival) case, in which has hold since 2004 by the Gwangju Information & Culture industry Promotion Agency in the city of Gwangju. The WAF case will be examined in terms of the promotion of the selected web cartoons and animations in the festival competition. As a result, the competion festival has been managed in connection with the support programs for the promotion of the regional cultural industries. In the process, the Gwangju Information & Culture industry Promotion Agency has sought to connect the selected arts works with the CEOs in the field of content business and media business. The article concludes the WAF need to be reestablished in the context of the development of the Gwangu cultural industries cluster and the reinforcement of the international exchange and networking through the grand project of Asian Cultural Capital Gwangu.

• Proceedings of the KOR-KST Conference
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• 2002.02a
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• pp.17-42
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• 2002

전통적인 OD조사에 의한 OD추정의 여러 문제점들로 인해 링크관측교통량과 기존OD를 결합해 OD를 추정하고자 하는 연구들이 제시되고 있다. Yang(1995)은 일반화최소자승법을 풀기 위한 IEA와 SAB 알고리즘을 제시하였다. 그러나 두 알고리즘의 문제점은 첫째 실제 OD를 알기가 어렵기 때문에 기존 OD를 중요한 추정기준으로 설정한다는 것으로, 이러한 추정의 종속성으로 인해, 기존 OD와 실제 OD의 차이가 큰 경우 정확한 해를 도출하지 못한다. 두 번째 문제는 통행패턴 추정시 선형근사화를 가정하기 때문에 게임이론적 측면에서 전제로 설정한 완전한 Stackelberg 상황을 구현하지 못한다는 것이다. 이러한 문제점을 피하기 위해서는 기존 OD나 관측교통량의 오차에 일관적인 해도출 기법이 필요하다. OD추정 문제는 본질적으로 비선형이고 비볼록하여 전역해 탐색기법이 필요하기 때문에 전역최적화가 가능한 유전알고리즘을 이용한 OD추정모형(GAM)을 개발하였다. 사례네트워크 분석결과, GAM은 기존 OD의 오차에 대해 크게 종속적이지 않으며 OD구조가 변하는 경우에도 추정이 가능하여, 일반적으로 실제 OD를 알 수 없는(기존OD의 오차가 어느 정도인지를 알 수 없는) 도시부 네트워크에서 신뢰성있는 추정력을 보였다. 또한 기존 OD 추정모형은 비교적 용이하게 차종별로 관측할 수 있는 링크교통량을 차종구분 없이 단일차종으로 이용함으로써, 정보의 손실을 초래하여 결과적으로 모형의 추정력을 저하시켰다. 그렇지만 다차종 링크관측교통량으로부터 다차종 OD 추정연구는 거의 없었으며, 그 결과가 단일차종에 대한 추정결과와 어떻게 다른지에 대한 연구도 전무하였다. 본 연구에서는 유전알고리즘을 이용한 OD 추정모형을 다수단 OD 추정모형(GAMUC)으로 확대하였다. 사례 분석 결과 단일차종 OD추정기법은 심각한 추정오류를 범할 수 있으며, 그 적용성도 낮다는 것을 보였다. 다차종 OD 추정기법이 단일차종 OD 추정기법보다 양호한 추정력을 보였으며, 다차종 기법 중에서는 GAMUC가 IEAMUC보다 우수한 추정력을 보였다.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.167-186
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• 2008

This study is to investigate, from the perspective of implicit theory, what elements influence children's motivation to learn and how their configurations are different according to different sexes. One analysis was based on answers to a motivation questionnaire by fourth to sixth graders from four different cities in South Korea. The subjects children were most highly motivated to learn were math and science for boys, and math and English for girls, respectively. Factors influencing the motivation were near 30 in number, including later happier life, joy of learning, parental rewards, pleasure of being informed, and meeting parental expectations, among others. Another analysis was an exploratory and confirmative factor analysis on motivation to learn among 856 fourth to sixth graders randomly sampled from 7 different cities all over South Korea. Factors revealed to contribute to the motivated learning here were five factors of utility, interest, recognition, knowledge acquisition(being informed), and expectancy sufficiency. There were some differences in the structure of factors between sexes; importance was given to five factors of utility, interest, recognition, knowledge acquisition, and expectancy sufficiency in descending order for boys, and six factors of interest, utility, rewards, recognition, expectancy sufficiency, and competition for girls.

• Journal of Korean Society of Transportation
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• v.18 no.6
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• pp.89-99
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• 2000

To cope with the limits of conventional O-D trip matrix collecting methods, several approaches have been developed. One of them is bilevel Programming method Proposed by Yang(1995), which uses Sensitivity Analysis Based(SAB) algorithm to solve Generalized Least Square(GLS) problem. However, the SAB a1gorithm has revealed two critical short-comings. The first is that when there exists a significant difference between target O-D matrix and true O-D matrix, SAB algorithm may not produce correct solution. This stems from the heavy dependance on the historical O-D information, in special when gravel Patterns are dramatically changed. The second is the assumption of iterative linear approximation to original Problem. Because of the approximation, SAB algorithm has difficulty in converging to Perfect Stackelberg game condition. So as to avoid the Problems. we need a more robust and stable solution method. The main purpose of this Paper is to show the problem of the dependency of Previous models and to Propose an alternative solution method to handle it. The Problem of O-D matrix estimation is intrinsically nonlinear and nonconvex. thus it has multiple solutions. Therefore it is necessary to require a method for searching globa1 solution. In this paper, we develop a solution algorithm combined with genetic algorithm(GA) , which is widely used as probabilistic global searching method To compare the efficiency of the algorithm, SAB algorithm suggested by Yang et al. (1992,1995) is used. From the results of numerical example, the Proposed algorithm is superior to SAB algorithm irrespective of travel patterns.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.89-101
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• 2017

Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.915-929
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• 2023

Improvements in people's quality of life, diversification of leisure activities, and changes in population structure have led to an increase in the demand for tourism and an expansion of the diversification of tourism activities. In particular, for coastal cities where land and marine tourism elements coexist, various factors influence their tourism demands. Tourism requires the construction of infrastructure and content development according to the demand at the tourist destination. This study aims to improve the prediction accuracy and explore influencing factors through time series analysis of tourism scale using agent-based data. Basic local governments in the Busan area were examined, and the data used were the number of tourists and the amount of tourism consumption on a monthly basis. The univariate time series analysis, which is a deterministic model, was used along with the SARIMAX analysis to identify the influencing factor. The tourism consumption propensity, focusing on the consumption amount according to business types and the amount of mentions on SNS, was set as the influencing factor. The difference in accuracy (RMSE standard) between the time series models that did and did not consider COVID-19 was found to be very wide, ranging from 1.8 times to 32.7 times by region. Additionally, considering the influencing factor, the tourism consumption business type and SNS trends were found to significantly impact the number of tourists and the amount of tourism consumption. Therefore, to predict future demand, external influences as well as the tourists' consumption tendencies and interests in terms of local tourism must be considered. This study aimed to predict future tourism demand in a coastal city such as Busan and identify factors affecting tourism scale, thereby contributing to policy decision-making to prepare tourism demand in consideration of government tourism policies and tourism trends.