• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.1-17
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• 2011

The performance of DHCS depends on the algorithm which schedules input DAG. However, as the task scheduling problem in DHCS is an NP-complete problem, heuristic approach has to be made. Task scheduling algorithm consists of task prioritizing phase and processor allocation phase, and most of studies are considering both phases together. In this paper, we focus on task prioritizing phase and propose a WPD algorithm which is optimized for task duplication based processor allocation method. For an evaluation of the proposed WPD algorithm, we combined WPD algorithm with processor allocation phase of HMPID, HCPFD, HCT algorithms, which are using task duplication based processor allocation method. The results show that WPD algorithm makes a better use of task duplication than conventional task prioritizing methods and provides 9.58% better performance than HCPFD algorithm, 1.31% than HCT algorithm.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.21-54
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• 2012

As we know every software development process is pretty large and consists of different modules. This raises the idea of prioritizing different software modules so that important modules can be tested by preference. In the software testing process, it is not possible to test each and every module regressively, which is due to time and cost constraints. To deal with these constraints, this paper proposes an approach that is based on the fuzzy multi-criteria approach for prioritizing several software modules and calculates optimal time and cost for software testing by using fuzzy logic and the fault tolerance approach.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.2
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• pp.76-89
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• 2010

The performance of Distributed Heterogeneous Computing System depends on the algorithm which schedules input DAG graph. Among various scheduling algorithms, list scheduling algorithm provides superior performance with low complexity. List scheduling consists of task prioritizing phase and processor allocation phase, but most studies only focus on task prioritizing phase. In this paper, we propose LIP policy which has the same complexity with traditional allocation policies but has superior performance. The performance of LIP has been observed by applying them to task prioritizing phase of traditional list scheduling algorithms, HCPT, HEFT, GCA, and PETS. The results show that LIP has better performance than insertion-based policy and non-insertion-based policy, which are traditional processor allocation policies.

• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.264-275
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• 2015

While the method of prioritization has been practicing in the community needs-based programs to improve the effectiveness and efficiency of community health planning, it has not been systematically used. This study aims to suggest more sophisticated method of prioritizing. Based on the analysis of 81 community health plans which adopt prioritizing method, this study tried to examine their methods and criteria and evaluate their adequacy. In the prioritization process, projects themselves, rather than health problems, were commonly adopted for the subject of the analysis. The most used was the Basic priority rating, followed by the Prioritization matrix. Looking at the size of health problem among the prioritization criteria, the prevalence for chronic diseases and the proportion of people with health problems for health behaviors, mainly were used as indicators. Along with the size of health problem, other factors such as the degree of seriousness of health problem, and the effectiveness of intervention have been used as the criteria of prioritizing, not fully supported by objective data base and the clear standard of scoring. In the prioritization, the analysis need to be limited only to health problems, and the scoring criteria for each health problem area be presented.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.10-16
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• 2021

As the implementation of smart factories spreads widely, the need for research to improve data efficiency is raised by prioritizing massive amounts of big data using IoT devices in terms of relevance and quality. The purpose of this study is to investigate whether prioritizing big data in management accounting decisions such as cost volatility estimation and recipe optimization can improve smart solution performance and decision-making effectiveness. Based on the survey answers of 84 decision makers at domestic small and medium-sized manufacturers who operate smart solutions such as ERP and MES that link manufacturing data in real time, empirical research was conducted. As a result, it was analyzed that setting prioritization of big data has a positive effect on decision-making in management accounting. became In addition, it was found that big data prioritization has a mediating effect that indirectly affects smart solution performance by using big data in management accounting decision making. Through the research results, it will be possible to contribute as a prior research to develop a scale to evaluate the correlation between big data in the process of business decision making.

• Journal of Korean Society for Quality Management
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• v.43 no.2
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• pp.127-140
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• 2015

Purpose: To obtain the area for improvement, the Importance-Performance analysis(IPA) uses relatively simple questions, that is, satisfaction and importance at attribute level. However, no attempt has been made to consider the gap between own company's performance and those of competitors in IPA, in the field of quality management. This study is aimed to suggest a new prioritizing method for improvement and to test for validity of the proposed technique. Methods: This study used data collected from Song and Lim(2015), which is satisfaction of employees, customers and competitors as well as importance data for 7 quality attributes of K animal hospital. A correlation comparison with other priority methods such as Bacon(2003)'s model and Matzler and Hinterhuber(1998)'s QI index is conducted. Results: The priority results by the proposed method shows better in correlation coefficient with customer perceived priority for improvement than other methods. Conclusion: From the result of the current study, it can be concluded that the result of the proposed method is valid, while it is relatively easy to understand and analyze, and therefore no additional survey is necessary for improvement priority.

• Journal of the Korean Society of Systems Engineering
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• v.9 no.2
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• pp.1-6
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• 2013

Developing Build-Own (or Operate)-Transfer (BOT) nuclear power project carrying large capital in the long term requires initially well-made multi-decision which it prevents sorts of risks from unexpected situation of target countries. In order to analyze the feasibility of project country, the Analytic Hierarchy Process is adopted. Firstly, the factors influencing the success of BOT nuclear power project in overseas countries were investigated through the literature survey for the country risk and were evaluated by expert interview for estimating comparative weight through pairwise comparison between such factors. Finally, it is developed comparative database of alternate countries with respect to each factor. This analytic method enables the developer to select and focus on the country which has preferable circumstance so that it enhances the efficiency of the project promotion. Also, it enables the developer to quantify the qualitative factors so that it diversifies the project success strategy and policy for the target country.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.101-112
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• 2015

The objective of this study was to investigate non-point sources (NPS) pollution and prioritize management areas affected by NPS pollution in the Saemangeum Watershed. AHP (Analytical Hierarchy Process) technique was selected to prioritize sub-watersheds for effectively managing NPS pollution in this study areas. Generation properties of NPS pollution, discharge properties of NPS pollution, and runoff properties of NPS pollution were selected and set for AHP. Weighted descriptors including indicators like numbers of livestock, land- and livestock-system loads, rainfall, and impervious area ratio were generalized from 0 to 1 and multiply each index based on screened 17 survey data. The results were visualized as maps which enable resource managers to identify sub-watersheds for effective improving water quality. The sub-watersheds located in Gongdeok-Myeon, Yongji-Myeon, Hwangsan-Myeon of Gimje-Si were selected for managing NPS pollution control areas. This result presented that these sub-watershed are more affected by the pollution from livestock-system than from land-system. The finding from this study can be used to screen sub-watersheds that need further assessment by managers and decision-makers within the study area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.3
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• pp.75-86
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• 2014

An urban ecosystem is a complex system that includes social, economic and ecosystems. Therefore, it is important to consider its environmental capacity while developing a city plan. Most of the plans, however, consider only the social aspects, which fragments the green spaces and disturbs the movement of species. Sungnam has approximately 100 parks with unexecuted development plans and with great potential to contribute towards urban ecosystem enhancement. Therefore, this study applied network analysis to prioritize the development of city parks and contribute towards improving the green network, with Parus spp. as the target species. To compensate for the drawbacks of binary and possibility-based network analysis, this study included two indices, namely $BC^{PC}_K$, $BC^{IIC}_K$, $dPCconnector_k$ and $dIICconnector_k$. These indices make it possible to find patches that could play an important role in green network enhancement. The urban park with greater value gets a higher priority to be transformed into a park. Thus, our methodology could prove to be very useful in prioritizing the undeveloped parks, thereby supporting decision-making.

• Journal of Energy Engineering
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• v.2 no.1
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• pp.45-53
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• 1993

This study was directed to an inquiry into a methodology for prioritizing and evaluating R & D alternatives for fuel cell technology, that can provide information for use in future decisions under the current uncertainty. A case study was performed for three cases of fuel cell development under the assumption that basic input data are same. The three cases are the case considering sequential R & D schedule only(Case 1), the case considering equivalent and excluding subprojects(Case 2), and the case allowing parallel efforts for each phase(Case 3). The following results were obtained; the probabilities of success for R & D phases in parallel projects are correlated, the probability of success for each project increases through Case 1, Case 2 and Case 3 successively and the expected dates of commercialization were notably shortened in Case 3.