• Industrial Engineering and Management Systems
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• 제16권1호
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• pp.129-140
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• 2017

This research was conducted in order to solve the problem of selecting an operational strategy for projects in project-based organizations by designing a fuzzy expert system. In the current research, we first determined the contributing parameters in operational strategy of project-based organizations based on existing research literature and experts' opinion. Next, we divided them into two groups of model inputs and outputs and the rules governing them were determined by referring to research literature and educational instances. In order to integrate rules, the revised Ternary Grid (revised TG) and expert opinions were applied according to a hybrid algorithm. The Ultimate rules were provided in Fuzzy Inference System format (FIS). In this FIS, proper manufacturing decisions are recommended to the user based on selected competitive priority and also project properties. This paper is the first study in which rules and relations governing the parameters contributing operational strategy in project-based organizations are acquired in a guided integrated process and in the shape of an expert system. Using the decision support system presented in this research, managers of project-based organizations can easily become informed of proper manufacturing decisions in proportion with selected competitive priority and project properties; and also be ensured that theoretical background and past experiences are considered.

• Structural Engineering and Mechanics
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• 제25권3호
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• pp.331-345
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• 2007

Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.52-58
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• 2021

Questionnaires and surveys are increasingly being used to collect information from participants of empirical software engineering studies. Usually, such data is analyzed using statistical methods to show an overall picture of participants' agreement or disagreement. In general, the whole survey population is considered as one group with some methods to extract varieties. Sometimes, there are different opinions in the same group, but they are not well discovered. In some cases of the analysis, the population may be divided into subgroups according to some data. The opinions of different segments of the population may be the same. Even though the existing approach can capture the general trends, there is a risk that the opinions of different sub-groups are lost. The problem becomes more complex in longitudinal studies where minority opinions might fade over time. Longitudinal survey data may include several interesting patterns that can be extracted using a clustering process. It can discover new information and give attention to different opinions. We suggest using a data mining approach to finding the diversity among the different groups in longitudinal studies. Our study shows that diversity can be revealed and tracked over time using the clustering approach, and the minorities have an opportunity to be heard.

• 한국중재학회지:중재연구
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• 제26권3호
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• pp.121-147
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• 2016

Factual issues in most patent litigation are related to very complicated techniques. Thus, the courts has emphasised that the technology in dispute has to be read and understood through the eyes of a person to whom it is directed. Therefore, among the various processes in federal litigation, most litigation in the field of patent infringement relies on at least some expert evidence. This paper focuses on issues regarding patent dispute evidence, and explore whether there are unresolved issues in evidential rules and procedures of patent proceedings. Further, this paper seeks to demonstrate that both the parties and the courts in patent disputes generally benefit from the current evidence system. However, in a number of Australian cases, the scope of expert evidence in patent cases has been strictly limited. Australian Government identified uncertain issues associated with the present patent enforcement system, due to factors such as a low level of knowledge about what patent rights entail, the high degree of uncertainty of outcome in legal proceedings, etc. Arbitration shall be reviewed and suggested as an alternative to tackling the ongoing problems in the trial system.

• 환경영향평가
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• 제20권2호
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• pp.123-131
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• 2011

The objective of this study is to prepare the effective management plan of environmental noise with a noise map, and the guideline on the management plan of environmental noise was suggested through the review of existing application examples. The management plan of environmental noise with a noise map includes the practical contents in the stages of subdivision of management areas, establishment of reduction measures, opinion collection, post investigation, and reformulation of management plan. First, the classification of management regions is performed considering the excess degree of noise standard and the facility type in the phase of subdivision of management areas. Second, the optimal management plan is established through the investigation of regional characteristics and various noise reduction measures in the phase of establishment of reduction measures, which includes the examination of noise reduction effects with a noise map and the budget planning with the costing of noise reduction measures. Third, the opinion survey with a local resident and a expert is carried out in order to prove the validity of the management plan in the phase of opinion collection, and the management plan is modified with gathered opinions. Fourth, the post examination plan with noise measurement is performed in order to verify the real effect of noise reduction measures according to the management plan in the phase of post investigation. Finally, the amendment of the management plan as well as the improvement of a noise map is carried out at a regular cycle in the phase of reformulation of management plan.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.201-210
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• 2024

In empirical software engineering research, there is an increased use of questionnaires and surveys to collect information from practitioners. Typically, such data is then analyzed based on overall, descriptive statistics. Overall, they consider the whole survey population as a single group with some sampling techniques to extract varieties. In some cases, the population is also partitioned into sub-groups based on some background information. However, this does not reveal opinion diversity properly as similar opinions can exist in different segments of the population, whereas people within the same group might have different opinions. Even though existing approach can capture the general trends there is a risk that the opinions of different sub-groups are lost. The problem becomes more complex in case of longitudinal studies where minority opinions might fade or resolute over time. Survey based longitudinal data may have some potential patterns which can be extracted through a clustering process. It may reveal new information and attract attention to alternative perspectives. We suggest using a data mining approach to finding the diversity among the different groups in longitudinal studies (agile skeptics). In our study, we show that diversity can be revealed and tracked over time with the use of clustering approach, and the minorities have an opportunity to be heard.

• Asian Journal of Innovation and Policy
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• 제8권3호
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• pp.417-427
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• 2019

This article puts forward the opinion of a policy expert, who had been involved in Korea's science and technology policy for 30 years, about technology policy for SMEs. This article first explains why technology policies for SMEs are needed, and from what point of view. The next section looks at the current problems facing Korean SMEs, followed by the introduction of past and current polices to support SMEs. The comparison between current issues facing SMEs and past and current policies leads to lessons that can be learned. There are four lessons for the policy itself and three for the implementation of these policies. As for policy, the first four are about stages of development, concentration, R&D and diffusion, and policy mix. The latter three are policymakers, institutional building, and cooperation between ministries. This article makesfour suggestions for future policy: the importance of startups' culture, cooperation with others, infrastructure to reduce uncertainty, and policy monitoring and evaluation.

• 대한한의학원전학회지
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• 제36권2호
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• pp.23-34
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• 2023

Objectives : We propose a method to disassemble Traditional East Asian Medicine herbal formulas using machine learning. Methods : After creating a model using Byte Pair Encoding(BPE) and G-Score, the model was trained with training data. Afterwards, the learned model was applied to the test data, of which the results were compared with expert opinion. Results : The results acquired through the model were not significantly different from those of modern expert opinions. However, there were cases where the meaning was partially unclear, while there were cases where new knowledge could be obtained through the disassembling process. Conclusions : It is expected that disassembling herbal formulas through the proposed method in this study will help save resources required to understand complex ones.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.178-182
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• 1995

The technique of neural networks is applied to cold forging design system. A user can select more desirable plans in cold forging design by being advised with expert's opinion from neural networks. The neural networks are learned with 3 parts which are most important in cold forging design-undercut, narrow hole, sharp corner. Using the neural networks, the cold forging design system built in this study determines forming possibility about variable shapes in product. We can get available result using the system.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2002년도 추계공동학술대회
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• pp.433-439
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• 2002

In this paper, we implemented technology assessment on the public R＆D activities in IT field in order to select the promising technologies, so called "star technology," making for national industry development. Technology assessment frame in this study included qualitative factors. IT technologies are classified five sector - network, wireless/broadcasting, SW/application/computer/terminal equipment, semiconductor/component. Expert opinion interviews on each field are carried out. Assessment factors consist of technology usefulness and technology competitiveness. In the final analysis, 23 technology items selected as a promising technologies and the results can be used public R＆D planning and If industry policy.