• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.767-779
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• 2013

A field of privacy protection lacks statistical information about the current status, compared to other fields. On top of that, since it has not been classified as a concrete separate field, the related survey is only conducted as a part of such concrete areas. Furthermore, this trend of being regarded as a part of fields such as informatization, information protection and law will continue in the near future. In this paper, a novel and practical way for collecting and storing a big amout of data from 110,000 privacy policies by data controller is proposed and the real analysis results is also shown. The proposed method can save time and cost compared with the traditional survey-based method while maintaining or even advancing the accuracy of results and speediness of process. The collected big personal data can be used to set up various kinds of statistical models and they will play an important role as a breakthrough of observing the present status of privacy information protection policy. The big data concept is incorporated into the privacy protection and we can observe the method and some results throughout the paper.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.153-158
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• 2020

The study aims to identify the factors affecting employee loyalty in the case of small and medium enterprises (SMEs) in Tra Vinh province, Viet Nam and to find out critical factors affecting the loyalty of employees in SMEs. This is implemented with the method of collecting primary data of 320 employees working at SMEs in 5 districts including: Cau Ngang, Tra Cu, Chau Thanh, Cang Long, Tieu Can) and Tra Vinh City, Viet Nam. Using the multivariate regression method, the researchers have found 6 factors affecting employee loyalty: colleagues, leaders, job characteristics, remuneration policies, organizational culture, and working environment. Particularly, learning opportunities may not be not statistically significant for employees' loyalty towards small and medium-sized enterprises in Tra Vinh province. From the above research results, the authors have proposed implicational piolicies such as: focusing on colleague relationships, improving leadership of business owners, attaching importance to appropriate work arrangement, having appropriate remuneration policies for laborers, building effective organizational culture and working environment to improve employee loyalty at SMEs. From the above policy implications, helping business owners realize the aspirations of workers in small and medium-sized enterprises more closely in the future, in order to sustainably develop the business system in Vietnam.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2009.04a
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• pp.149-154
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• 2009

For the past few decades, residential improvement projects have been mainly carried out after demolition of the original dwelling place. So far, interests and opinions of the existing residents have largely been ignored during the projects. However, citizen participation in local redevelopment has recently been regarded as essential part as progress in democracy and diversified public interests have offered more importance to citizen participation in the implementation of public policies. While the importance of resident participation has been increasingly emphasized in principle, there still has been more to do in its application in reality. We should develop the experience of collecting community opinion to make them reflected in public policy, if we are to achieve the resident and citizen-centered society. The purpose of this study is to develop an image map tool that can be applied to "Maul-Mandulgi" projects as a visualized method to facilitate the exchange of opinions and work toward agreements. The tool is supposed to assist the public discussion by visualizing the policies and reducing the possibility of misunderstanding, so that residents can properly respond to them. In addition, this study will verify the effectiveness of the tool in the application to local community workshops.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.167-180
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• 2021

The "sharing economy" describes a type of business built on the sharing of resources - allowing customers to access goods when needed. While sharing goods has always been a common practice among friends, family, and neighbors, in recent years, the concept of sharing has moved from a community practice into a profitable business model. This study explores gaps between customers' actual usages and current policies on accommodation sharing by analyzing what needs to be done for the better establishment of sharing economy in society. The purpose of this study is to investigate perceptions of accommodation sharing by analyzing reviews and negative aspects that help resolve complaints and improve better services through policy establishment. This study investigates key attributes that influence business performance to improve citizens' decision-making for the usage of accommodation sharing. This study applies qualitative research by collecting demand- and supply-side reviews from selected registered accommodations using a random sampling procedure. This study finds that guests prefer entire house sharing with instrumental attributes related to properties. Entire house sharing of multiple dwellings shows business impacts in terms of high occupancy rate on the platform, while there are policy concerns with entire house sharing. The results provide policy and managerial implications by suggesting proper policies and considering relationships with citizens.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.203-214
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• 2024

This study seeks to provide implications for domestic-related policies through exploratory analysis research to support AI-based policy decision-making. The following should be considered when establishing an AI-based decision-making model in Korea. First, we need to understand the impact that the use of AI will have on policy and the service sector. The positive and negative impacts of AI use need to be better understood, guided by a public value perspective, and take into account the existence of different levels of governance and interests across public policy and service sectors. Second, reliability is essential for implementing innovative AI systems. In most organizations today, comprehensive AI model frameworks to enable and operationalize trust, accountability, and transparency are often insufficient or absent, with limited access to effective guidance, key practices, or government regulations. Third, the AI system is accountable. The OECD AI Principles set out five value-based principles for responsible management of trustworthy AI: inclusive growth, sustainable development and wellbeing, human-centered values and fairness values and fairness, transparency and explainability, robustness, security and safety, and accountability. Based on this, we need to build an AI-based decision-making system in Korea, and efforts should be made to build a system that can support policies by reflecting this. The limiting factor of this study is that it is an exploratory study of existing research data, and we would like to suggest future research plans by collecting opinions from experts in related fields. The expected effect of this study is analytical research on artificial intelligence-based decision-making systems, which will contribute to policy establishment and research in related fields.

• The Journal of Korean Association of Computer Education
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• v.22 no.3
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• pp.135-146
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• 2019

Big data analysis is actively used for collecting and analyzing direct information on related topics in each field of society. Applying big data analysis technology in education field is increasingly interested in Korea, because applying this technology helps to identify the effectiveness of education methods and policies and applying them for policy formulation. In this paper, we propose our approach of utilizing big data analysis technology in education field. We focus on free semester program, one of the current core education policies, and we analyze the main points of interests and differences in the free semester through analysis and visualization of texts that are written on the operation reports prepared by each school. We compare regional differences in key characteristics and interests based on the free semester operation reports from middle schools particularly at Seoul and Gangwon-do regions. In conclusion, applying and utilizing big data analysis technology according to the needs and requirements of education field is a great significance.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.31-39
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• 1995

Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.73-81
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• 2017

In this paper, we propose an analysis framework to capture the trends of information security incidents and evaluate the security policy based on the incident analysis. We build a big data from news media collecting security incidents news and policy news, identify key trends in information security from this, and present an analytical method for evaluating policies from the point of view of incidents. In more specific, we propose a network-based analysis model that allows us to easily identify the trends of information security incidents and policy at a glance, and a cosine similarity measure to find important events from incidents and policy announcements.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.19-27
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• 2010

Historical archived traffic data management system enables a long term time-series analysis and provides data necessary to acquire the constantly changing traffic conditions and to evaluate and analyze various traffic related strategies and policies. Such features are provided by maintaining highly reliable traffic data through scientific and systematic management. Now, the management systems for massive traffic data have a several problems such as, the storing and management methods of a large volume of archive data. In this paper, we describe how to storing and management for the massive traffic data and, we propose methodology for logical and physical architecture, collecting and storing, database design and implementation, process design of massive traffic data.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.10-18
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• 2002

A more comprehensive analytical framework for examining the relative merits of alternative dispatching process policies for nurseries is developed in this paper. The efficiency of the dispatch process of plants in a nursery is analysed using a vehicle routing model. The problem then involves determining in what order each vehicle should visit its locations. The problem is NP-hard. Several heuristic techniques are used to solve a real life nursery sequencing problem. The results obtained by these heuristic techniques are compared with each other and the current sequencing of orders. The model with some minor alterations can be also used to minimise the dispatching and collecting process in different agricultural plants.