• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.78-94
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• 2000

The ever increasing demands for enhanced competitiveness of engineered products require a "designing-in-quality" strategy that can effectively and efficiently incorporate concepts of uncertainty, quality, and robustness into design. Engineered design optimization approaches that are typically carried out with respect to a single objective become inadequate to address these multiple set of requirements. This paper presents a design metric for a multi-attribute robust design problem with designer′s preferences on the performance accuracy and the performance precision. The use of this design metric as the robust optimal design criterion in multi-stage experimentation and modeling technique is presented. The effectiveness of the overall design procedure and the performance of the proposed design metric are tested with the aid of IC design and the results are discussed.

• International Journal of High-Rise Buildings
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• v.3 no.4
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• pp.273-278
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• 2014

Green roof's performance in reducing stormwater runoff has been reported by numerous studies. Nonetheless, the roles of low growing vegetation in influencing stormwater runoff reduction on green roofs have been greatly overlooked. This paper describes an experiment investigating the influence of low growing vegetation in the reduction of tropical stormwater runoff on extensive green roofs. Three types of locally occurring native vegetation and one non-native Sedum species were selected (fern, herb, grass and succulent) for the experiment. Stormwater runoff reduction performance from different low growing species was done by measuring excess water runoff from the simulated green roof modules. The results show significant differences in stormwater runoff reduction from different types of vegetation. Fern was the most effective in reducing stormwater runoff, followed by herb, Sedum and grass. Vegetative characters that are found to attribute towards the performance of stormwater runoff are rooting density, structure, density, leaf type, and vegetation biomass.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Journal of Information Technology Services
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• v.5 no.2
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• pp.59-78
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• 2006

This research is to suggest the factor which is effecting on the information system audit fidelity in the perspective of audit procurer, to develop the measure to evaluate it, to investigate the audit performance and project performance for comparison the audit fidelity between the audit teams. As the analysis results, we found that the audit service factors can be divided to the expert knowledge of auditor and the project attributes itself. It means these factors are the major measures for the audit fidelity. In this research, the hypothesis of this study model is verified throughout the factor and corelation analysis, and the structured equation model is applied. Analysis results show that all relations between the factors are significant statistically. The audit service factors has an effect on audit fidelity. Also the information system audit fidelity can be affect on the project performance, audit performance and customer satisfaction. So, in conclusion, we need to judge closely the audit service factors affecting the audit fidelity for the enhancement of the project performance, audit performance and customer satisfaction.

• The Journal of Korean Association of Computer Education
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• v.21 no.1
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• pp.51-58
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• 2018

Recently artificial neural networks have shown excellent performance in various fields. However, there is a problem that it is difficult for a person to understand what is the knowledge that artificial neural network trained. One of the methods to solve these problems is an algorithm for extracting rules from trained neural network. In this paper, we extracted rules from artificial neural networks using ordered-attribute search(OAS) algorithm, which is one of the methods of extracting rules, and analyzed result to improve extracted rules. As a result, we have found that the distribution of output values of the hidden layer unit affects the accuracy of rules extracted by using OAS algorithm, and it is suggested that efficient rules can be extracted by binarizing hidden layer output values using hidden unit clarification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1315-1329
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• 2018

Ciphertext-policy attribute-based encryption (CP-ABE) associates ciphertext with access policies. Only when the user's attributes satisfy the ciphertext's policy, they can be capable to decrypt the ciphertext. Expressivity and security are the two directions for the research of CP-ABE. Most of the existing schemes only consider monotonic access structures are selectively secure, resulting in lower expressivity and lower security. Therefore, fully secure CP-ABE schemes with non-monotonic access structure are desired. In the existing fully secure non-monotonic access structure CP-ABE schemes, the attributes that are set is bounded and a one-use constraint is required by these projects on attributes, and efficiency will be lost. In this paper, to overcome the flaw referred to above, we propose a new fully secure non-monotonic access structure CP-ABE. Our proposition enforces no constraints on the scale of the attributes that are set and permits attributes' unrestricted utilization. Furthermore, the scheme's public parameters are composed of a constant number of group elements. We further compare the performance of our scheme with former non-monotonic access structure ABE schemes. It is shown that our scheme has relatively lower computation cost and stronger security.

• The Journal of Information Systems
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• v.27 no.1
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• pp.89-110
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• 2018

Purpose There is much information in customer reviews, but finding key information in many texts is not easy. Business decision makers need a model to solve this problem. In this study we propose a multi-topic sentiment analysis approach using Latent Dirichlet Allocation (LDA) for user-generated contents (UGC). Design/methodology/approach In this paper, we collected a total of 104,039 hotel reviews in seven of the world's top tourist destinations from TripAdvisor (www.tripadvisor.com) and extracted 30 topics related to the hotel from all customer reviews using the LDA model. Six major dimensions (value, cleanliness, rooms, service, location, and sleep quality) were selected from the 30 extracted topics. To analyze data, we employed R language. Findings This study contributes to propose a lexicon-based sentiment analysis approach for the keywords-embedded sentences related to the six dimensions within a review. The performance of the proposed model was evaluated by comparing the sentiment analysis results of each topic with the real attribute ratings provided by the platform. The results show its outperformance, with a high ratio of accuracy and recall. Through our proposed model, it is expected to analyze the customers' sentiments over different topics for those reviews with an absence of the detailed attribute ratings.

• Journal of the Korea Safety Management & Science
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• v.19 no.3
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• pp.137-150
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• 2017

Logistic enterprises want to be competitive enterprises in fierce logistic market and worry about the securement of discriminative competitiveness for it. The standards for the judgement of logistic industry's maintenance of competitiveness are not only economic feasibility of logistic costs but also the satisfaction of users because well-established service system for variety and enhancement of logistic needs. Some of the quality attributes sufficiently satisfy expectation of customers, but not guarantee high-quality satisfaction. Therefore, it's difficult to grasp quality attributes with the existing approach of perceived service quality. Quality attribute model suggested by Kano is widely used as the concept is accurate, there is high possibility to be used at the stage of product/service planning, and it can be easily applied. Kano model has a limitation that quality attributes are classified with mode and the differences between strong property of the quality attribute and week property in quality attributes were ignored. Therefore, Timko calculated customer satisfaction coefficient with the result of Kano's survey and effects of customer satisfaction and unsatisfaction through relations between satisfaction coefficient and unsatisfaction coefficient. The purposes of this study are to use ASC, the average of satisfaction coefficient and unsatisfaction, as the satisfaction of quality characteristics, decide the importance of quality characteristics with TOPSIS, a representative multi-standard decision-making method, and calculate strategy improvement propriety of logistic service quality.

• 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.

• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.15-24
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• 2021

Purpose: This study measured the consumer-perceived importance and satisfaction of eco-friendly food selection factors and performed the IPA to derive the factors that need to be maintained, reinforced, improved and selectively improved or where investment need to be minimized, and thus provide some clues for eco-friendly food companies' sales growth. Research design, data and methodology: To this end, efficient questionnaires of a total of 312 respondents who answered the questions about the importance of and the satisfaction with 20 selection attribute factors of eco-friendly foods were returned, and then, paired-samples t-test and IPA by all respondents, gender, age and incomes were conducted. Results: The analysis showed that a maintenance/reinforcement strategies planned by companies are required for some factors including 'safety' and 'product quality' at the first quadrant, while active improvement strategies are required for others including 'price' and 'flavor' at the second quadrant. Conclusions: The findings show that different marketing strategies should be established for each consumer who often purchase eco-friendly foods, and that more effective and efficient performance of eco-friendly food companies may be acquired by establishing and operating active improvement strategies.