• Computers and Concrete
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• 제33권4호
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• pp.425-443
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• 2024

Floods are among the most common natural hazards in urban areas. To mitigate the problems caused by flooding, unstructured data such as images and videos collected from closed circuit televisions (CCTVs) or unmanned aerial vehicles (UAVs) have been examined for flood management (FM). Many computer vision (CV) techniques have been widely adopted to analyze imagery data. Although some papers have reviewed recent CV approaches that utilize UAV images or remote sensing data, less effort has been devoted to studies that have focused on CCTV data. In addition, few studies have distinguished between the main research objectives of CV techniques (e.g., flood depth and flooded area) for a comprehensive understanding of the current status and trends of CV applications for each FM research topic. Thus, this paper provides a comprehensive review of the literature that proposes CV techniques for aspects of FM using ground camera (e.g., CCTV) data. Research topics are classified into four categories: flood depth, flood detection, flooded area, and surface water velocity. These application areas are subdivided into three types: urban, river and stream, and experimental. The adopted CV techniques are summarized for each research topic and application area. The primary goal of this review is to provide guidance for researchers who plan to design a CV model for specific purposes such as flood-depth estimation. Researchers should be able to draw on this review to construct an appropriate CV model for any FM purpose.

• 한국콘텐츠학회지
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• 제15권1호
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• pp.21-28
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• 2017

• 한국콘텐츠학회지
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• 제13권1호
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• pp.43-47
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• 2015

• Human Ecology Research
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• 제52권6호
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• pp.573-586
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• 2014

The purpose of this study was to review the conceptual framework of social constructionism and critical social constructionism in the research area of multi-cultural family homes, using a literature review. Fopp argued that social constructionism had an objectivation problem that only considered the actor side as a policy object; therefore he suggested a weaker social constructionist perspective with moderate relativism and the application of feminist epistemology to marginal life for maximizing objectivity. This article explores a conceptual framework for studying the reality of housing of multi-cultural families in Korea in the light of constructionist ideas and presents a review of empirical positivist data to support the framework. Based on results, using the social constructionist framework, five contexts (structural, institutional, organizational, operational, and intersubjective) were reviewed and ideas were suggested to develop an appropriate future situation for multi-cultural family homes. For a weaker social constructionist framework, three National Survey of Multi-Cultural Family Homes data sets were reviewed to determine the real condition of multi-cultural family homes. Further, from a feminist perspective, the empirical data of marginalized multi-cultural family homes were reviewed from the perspectives of gender inequality of decision making, cultural adaptation, and differentiation in housing related areas. In conclusion, two perspectives were useful for understanding multi-cultural family housing in Korea but must be compensated with substantial empirical data for a holistic approach.

• Journal of the Korean Data and Information Science Society
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• 제13권1호
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• pp.79-86
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• 2002

Recently, it is shown that the unrelated quest ion randomized response models proposed by Moors (1971), Folsom et al.(1973), Greenberg et al.(1971) are in capable of protecting the privacy of the respondent. Thus, in this paper, we review recent days research tendency. Also modification model of Mahmood et al.(1998) is proposed, and we show th at this model is more efficient than Greenberg et al.(1969). Furthermore we treat the privacy protection based on Lanke's (1975) risk of suspicion measure.

• 한국병원경영학회지
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• 제7권3호
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• pp.121-136
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• 2002

The main purpose of this study is to examine the overall procedure of hospital's internal review of health insurance reimbursement, to present the case of protest against reimbursement cut, and hence to provide some information on hospital's management of medical revenue. The object of the case study is 'P' university medical center, possessing 5 different hospitals under its system. Presentation of the case of protest against reimbursement cut has following meanings: Firstly, to the hospitals that already have internal review departments, information on the details of the protest process and results can be exchanged. Secondly, to the Government and National Health Insurance Corporation, useful data are provided for the improvement of the rules and procedures of health insurance reimbursement. Thirdly, to the hospitals without internal review departments, fundamental materials on the internal review process are provided for the effective management of medical revenue.

• 한국벤처창업학회:학술대회논문집
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• 한국벤처창업학회 2022년도 춘계학술대회
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• pp.123-126
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two important aspects of online reviews are first, the topics consumers choose to address and second, the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre-and post-pandemic periods. After performing topic modeling on Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. Also, the order and magnitude of topics' impact on review sentiment change between pre-and post-pandemic periods for both countries. This study can help businesses to understand how topics and sentiments associated with their products and services changed after pandemic, and also help them identify areas of improvement.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.514-536
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two crucial aspects of online reviews are the topics consumers choose to address, and the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we employ the Expectation-Confirmation Theory (ECT) to examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre- and post-pandemic periods. After applying a topic modeling to Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. In addition, the order and magnitude of topics' impact on review sentiment change between pre- and post-pandemic periods for both countries. This study can help businesses understand how topics and sentiments associated with their products and services changed after the pandemic and thus identify areas of improvement.

• Journal of the Korean Data and Information Science Society
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• 제24권5호
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• pp.1077-1088
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• 2013

High-dimensional data analysis arises from almost all scientific areas, evolving with development of computing skills, and has encouraged penalized estimations that play important roles in statistical learning. For the past years, various penalized estimations have been developed, and the least absolute shrinkage and selection operator (LASSO) proposed by Tibshirani (1996) has shown outstanding ability, earning the first place on the development of penalized estimation. In this paper, we first introduce a number of recent advances in high-dimensional data analysis using the LASSO. The topics include various statistical problems such as variable selection and grouped or structured variable selection under sparse high-dimensional linear regression models. Several unsupervised learning methods including inverse covariance matrix estimation are presented. In addition, we address further studies on new applications which may establish a guideline on how to use the LASSO for statistical challenges of high-dimensional data analysis.

• Journal of Computing Science and Engineering
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• 제7권4호
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• pp.220-230
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• 2013

In recent years, progress in hardware technology has resulted in the possibility of monitoring many events in real time. The volume of incoming data may be so large, that monitoring all individual data might be intractable. Revisiting any particular record can also be impossible in this environment. Therefore, many database schemes, such as aggregation, join, frequent pattern mining, and indexing, become more challenging in this context. This paper surveys the previous efforts to resolve these issues in processing data streams. The emphasis is on specifying and processing sliding window queries, which are supported in many stream processing engines. We also review the related work on stream query processing, including synopsis structures, plan sharing, operator scheduling, load shedding, and disorder control.