• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.59-67
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• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• Journal of The Korean Association For Science Education
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• v.16 no.3
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• pp.314-328
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• 1996

This study investigated the literature about science process skills' evaluation to analyse transition of evaluation objectives before and after a Scholastic Ability Test for College Entrance. In the literature survey the researcher established a 3 dimensional science assessment framework with X axis as science concept, Y axis as science process skills and Z axis as problem context. In order to analysis and compare each items the researcher selected 210 items from the 1st to the 7th trials and 138 items from the 1st to 4th Scholastic Ability Test for College Entrance and sampled 2873 science achievement test items from 10 high schools. In accordance with this taxonomy the researcher analysed and compared science process skills item forms. The following results were drawn : The items were evenly distributed in all the four areas(Earth Science, Biology, Physics and Chemistry) of the science concept domain, but they were heavily concentrated on data analysis and drawing a conclusion in science process domain. In the domain of problem context school context was the majority. In spite of distribution like this the ratio on science process skills measurement items and science achievement test items was increased after the Scholastic Ability Test for College Entrance was given. Also the ratio on item expression type was increased. Item form was almost 5 options selection type in the national level test. Although there were 4 options selection type, 5 options selection type, short answer type, essay type in school level test, rising from 33.1% to 65.5% on 5 options selection type is exhibited. This study showed that the school level item form was better various than the nation level. This point like this is the evidence for the improvement toward the science process skills test and influenced by Scholastic Ability Test for College Entrance. The ratio on the item which joined with the 3 axes had a mean of 99.3% in nation level test and mean 44.9% in school achievement test level. But the ratio in the school achievement test level increased after the Scholastic Ability Test for College Entrance was given. In view of this study we must furthermore study the item types which can evaluate valjdately science process skill's five stage each and evaluation method by the high school students' problem solving patterns and features in scientific inquiry on all science process skills elements.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.57-73
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• 2006

This paper describes a methodology for automating the material handling equipment (MHE) evaluation and selection processes by combining knowledge-based rules and fuzzy multi-criteria decision making approach. The methodology is proposed to solve the MHE selection problems under fuzzy environment. At the primary stage, the most appropriate MHE type among the alternatives for each material flow link is searched. Knowledge-based rules are employed to retrieve the alternatives for each material flow link. To consider and compare the alternatives, multiple design factors are considered. These factors include both quantitative and qualitative measures. The qualitative measures are converted to numerical measures using fuzzy logic. The concept of fuzzy logic is applied to evaluation matrices used for the selection of the most suitable MHE through a fuzzy linguistic approach. Thus, this paper demonstrates the potential applicability of fuzzy theory in the MHE applications and provides a systemic guidance in the decision-making process.

• Knowledge Management Research
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• v.13 no.3
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• pp.55-77
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• 2012

Selecting promising technology is becoming more and more difficult due to the increased number and complexity. In this study, we propose hybrid AHP/DEA-AR method and hybrid AHP/DEA-AR-G method to evaluate efficiency of technology alternatives based on ordinal rating data collected through survey to technology experts in a certain field and select efficient technology alternative as promising technology. The proposed method normalizes rating data and uses AHP to derive weights to improve the credibility of analysis, then in order to avoid basic DEA models' problems, use DEA-AR and DEA-AR-G to evaluate efficiency of technology alternatives. In this study, we applied the proposed methods to clean technology and compared with the basic DEA models. According to the result of the comparison, we can find that the both proposed methods are excellent in confirming most efficient technology, and hybrid AHP/DEA-AR method is much easier to use in the process of technology selection.

• Journal of Life Science
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• v.32 no.4
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• pp.279-284
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• 2022

This study was conducted to establish a genetic evaluation system applicable to general farms for improving cows raised on farms. The analysis used Best Linear Unbiased Prediction (BLUP) and Genomic Best Linear Unbiased Prediction (GBLUP) for 619 cows raised in Gyeonggi-do Province and compared and analyzed the accuracy of the estimated breeding value according to four traits (carcass weight, loineye muscle area, back fat thickness, and marbling). In the case of the GBLUP method, the size of the reference population was divided into different four groups and analyzed. The analysis results confirmed that the accuracy of the breeding value of each trait increased as the size of the GBLUP reference population increased. Comparing the accuracy of the breeding values estimated using the BLUP and GBLUP methods, it was confirmed that when the breeding values were estimated using the GBLUP method, they increased by 0.10, 0.09, 0.09, and 0.11 for carcass weight, eye muscle area, back fat thickness, and marbling scores, respectively. Applying the GBLUP method to the evaluation and selection of cows can enable precise and accurate individual selection, while increasing the size of the reference population can make even more accurate individual selection possible, thus increasing selection efficiency.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.4
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• pp.248-256
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• 2023

As a means to activate eco pastoral system in alpine grassland, the government can consider public pastures, which are currently unused, to scale them up into public ranches. Depending on ownership and operation, four management models proposed as follows: 1) Government-Owned and Operated with Balanced Profit and Loss 2) Government-Owned and Operated with Revenue Generation 3) Government-Owned but Privately Operated by Outsourced to Professional Manager 4) Full Privatization (Ownership and Operation by Private Individuals). The study outlined above proposes four management models for the activation of eco pastoral system in alpine grassland. It also suggests methods for the selection and performance evaluation of manager to establish a profitable structure. Additionally, the research provides management methods for the conservation of grazing ecology in pastoral ecosystems. Particularly, the adaptation of tools commonly used in South Korean business sector for the selection and performance evaluation of manager within the system of the proposed management models. This aspect is deemed valuable as it aligns these tools with the specific characteristics of eco pastoral system in alpine grassland, contributing not only to the effective implementation of the models but also to the enhancement of the revenue structure.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.29-42
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• 2014

Extensive research has been conducted on supplier evaluation and selection as a strategic and crucial component of supply chain management in recent years. However, few articles in the previous literature have been dedicated to the use of fuzzy inference systems as an aid in decision-making. Therefore, this essay attempts to demonstrate the application of this method in evaluating suppliers, based on a comprehensive framework of qualitative and quantitative factors besides the effect of gradual coverage distance. The purpose of this study is to investigate the applicability of the numerous measures and metrics in a multi-objective optimization problem of the supply chain network design with the aim of managing the allocation of orders by coordinating the production lines to satisfy customers' demand. This work presents a dynamic non-linear programming model that examines the important aspects of the strategic planning of the manufacturing in supply chain. The effectiveness of the configured network is illustrated using a sample, following which an exact method is used to solve this multi-objective problem and confirm the validity of the model, and finally the results will be discussed and analyzed.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.488-493
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• 2005

Railload line design of the railroad construction project should be planed considering the variety of quantitative and qualitative factors, and needs to be selected the optimum altinative weighing from VE/LCC analysis of the planned design. The purpose of this research is for showing selecting plan of the optimum railload line and railway bridge applying VE/LCC analysis in selecting the optimum altinative of railroad construction based on quantitative and qualitative factors, such as initial construction cost, maintenance cost, owner and user's requirements. In this research showed the application plan by each stage using data analysis, function analysis, and alternative evaluation of VE/LCC analysis with AHP and LCC analysis program for the selection. This research is proved the rationality and application of the course of selecting the optimum alternative through case application

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7A
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• pp.523-529
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• 2009

This paper provides closed form expressions for the evaluation of the end-to-end outage probability, symbol error rate, bit error rate and average capacity of the partial-based Decode-and-Forward (DF) relay selection scheme with an arbitrary number of relays. In a comparison with the performance of systems that exploit Amplify-and-Forward (AF), it can be seen that the performance of our proposed protocol converges to that of partial-based AF relay selection in high SNR regime. We also perform Monte-Carlo simulations to validate the analysis.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.7-11
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• 2024

In the era of the 4th Industrial Revolution, new technologies such as artificial intelligence, big data, cloud, Internet of Things, and blockchain are being developed and applied to new industries. Blockchain has the characteristics of decentralization, security, and transparency, so it can serve as a core technology for developing new growth industries. Blockchain is provided as BaaS (Blockchain as a Service), but it is not easy for users who are introducing or building blockchain to choose BaaS. In this study, we identify evaluation factors and develop a decision-making model using fuzzy theory and AHP for BaaS selection. Eventually we aim to help companies choose the best BaaS and develop and commercialize blockchain-based services by developing a new decision-making model for BaaS selection.