• 제목/요약/키워드: effective evaluation

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Supplier Evaluation in Green Supply Chain: An Adaptive Weight D-S Theory Model Based on Fuzzy-Rough-Sets-AHP Method

  • Li, Lianhui;Xu, Guanying;Wang, Hongguang
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.655-669
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    • 2019
  • Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

Dynamic evaluation of water source safety based on fuzzy extension model

  • Ou, Bin;Gong, Aimin;He, Chunxiang;Fu, Shuyan
    • Membrane and Water Treatment
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    • v.10 no.2
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    • pp.149-154
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    • 2019
  • The information matter-element system was built to assess safety of water source. Based on the thought of multiindex fusion, fuzzy matter-element model evaluating water source behavior was constructed by matter-element transform. This model can process comprehensively hydrogeological data, ecological environment, water pollution, surface disturbance, and so on. Water source safety behavior can be described by the qualitative and quantitative manners. According to the development trend of quantitative results, water source safety behavior can be expressed dynamically. As an example, the proposed method was used to assess safety status of 7 water sources in the region. The numerical example shows that the proposed method is feasible and effective, and the evaluation results are reasonable.

Proposing a Method for Robustness Index Evaluation of the Structures Based on the Risk Analysis of Main Shock and Aftershock

  • Abdollahzadeh, Gholamreza;Faghihmaleki, Hadi
    • International journal of steel structures
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    • v.18 no.5
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    • pp.1710-1722
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    • 2018
  • Investigating remained damages from terrible earthquakes, it could be concluded that some events including explosion because of defect and failure in the building mechanical facilities or caused by gas leak, firing, aftershocks, etc., which are occurred during or a few time after the earthquake, will increase the effects of damages. In this paper, by introducing a complete risk analysis which included direct and indirect risks for earthquake (the main shock) and aftershock, the corresponding robustness index was created that called as "robustness index sequential critical events risk-based". One of the main properties of the intended robustness index is using progressive collapse percentage in its evaluation. Then, in a numerical example for a 4-storey moment resisting steel frame structure, a method is presented for obtaining all effective parameters in robustness index evaluation based on the intended risk and at last its results were reported.

Evaluation of Similarity Analysis of Newspaper Article Using Natural Language Processing

  • Ayako Ohshiro;Takeo Okazaki;Takashi Kano;Shinichiro Ueda
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.1-7
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    • 2024
  • Comparing text features involves evaluating the "similarity" between texts. It is crucial to use appropriate similarity measures when comparing similarities. This study utilized various techniques to assess the similarities between newspaper articles, including deep learning and a previously proposed method: a combination of Pointwise Mutual Information (PMI) and Word Pair Matching (WPM), denoted as PMI+WPM. For performance comparison, law data from medical research in Japan were utilized as validation data in evaluating the PMI+WPM method. The distribution of similarities in text data varies depending on the evaluation technique and genre, as revealed by the comparative analysis. For newspaper data, non-deep learning methods demonstrated better similarity evaluation accuracy than deep learning methods. Additionally, evaluating similarities in law data is more challenging than in newspaper articles. Despite deep learning being the prevalent method for evaluating textual similarities, this study demonstrates that non-deep learning methods can be effective regarding Japanese-based texts.

A Utility Evaluation Framework of Blockchain Services using a MCDM (다중의사결정모델을 이용한 블록체인 서비스 효용 평가 프레임워크)

  • Kwang-Kyu Seo
    • Journal of the Semiconductor & Display Technology
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    • v.23 no.2
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    • pp.45-49
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    • 2024
  • Blockchain has gone beyond the proof-of-concept level and is converging with various industries and fields, moving toward the service development and commercialization stage. However, although various blockchain technologies and services are emerging, their development is quite slow and their widespread application to various industries is difficult. Accordingly, it is necessary to identify areas with high introduction utility when applying blockchain services in actual industries and to develop a method to evaluate the utility of blockchain services for this purpose. This paper proposes a framework for evaluating the utility of blockchain services using a multi-criteria decision-making model. Through a case study on the utility evaluation of blockchain services, the proposed framework was applied to domestic and foreign blockchain services to evaluate its utility and verify its applicability. It is expected that the proposed framework will be able to identify industrial and functional characteristics where actual blockchain services can be introduced and demonstrate effective utility and can be used to develop blockchain services in various industrial fields.

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Development of a chatbot for school violence prevention among elementary school students in South Korea: a methodological study

  • Kyung-Ah Kang;Shin-Jeong Kim;Byoung-doo Oh;Yu-Hyeon Kim
    • Child Health Nursing Research
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    • v.30 no.1
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    • pp.45-53
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    • 2024
  • Purpose: This study develops a chatbot for school violence prevention (C-SVP) among elementary school students. Methods: Among the analysis, design, development, implementation, and evaluation (ADDIE) models, ADD phases were applied to develop a C-SVP. Students' learning needs were identified by constructing content with a design that attracted their attention. Subsequently, a formative evaluation was conducted on the developed C-SVP to test its applicability by ten elementary school students targeting the 5th and 6th grades. Results: The chatbot was designed using KakaoTalk and named "School Guardian Angel." The formative evaluation revealed that the developed C-SVP was easily accessible and useful for elementary school students. Conclusion: The developed C-SVP is expected to be effective in preventing violence among elementary school students. However, further research involving children of various age groups is required.