A NOVEL HYBRID APPROACH FOR SIMPLIFIED NEUTROSOPHIC DECISION-MAKING WITH COMPLETELY UNKNOWN WEIGHT INFORMATION

Author(s):  
Gökçe Dilek Küçük ◽  
Ridvan Şahin
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 135770-135783
Author(s):  
Alka Agrawal ◽  
Abhishek Kumar Pandey ◽  
Abdullah Baz ◽  
Hosam Alhakami ◽  
Wajdi Alhakami ◽  
...  

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1290
Author(s):  
Zheng-Yun Zhuang ◽  
Chi-Kit Ho ◽  
Paul Juinn Bing Tan ◽  
Jia-Ming Ying ◽  
Jin-Hua Chen

The administration of A/B exams usually involves the use of items. Issues arise when the pre-establishment of a question bank is necessary and the inconsistency in the knowledge points to be tested (in the two exams) reduces the exams ‘fairness’. These are critical for a large multi-teacher course wherein the teachers are changed such that the course and examination content are altered every few years. However, a fair test with randomly participating students should still be a guaranteed subject with no item pool. Through data-driven decision-making, this study collected data related to a term test for a compulsory general course for empirical assessments, pre-processed the data and used item response theory to statistically estimate the difficulty, discrimination and lower asymptotic for each item in the two exam papers. Binary goal programing was finally used to analyze and balance the fairness of A/B exams without an item pool. As a result, pairs of associated questions in the two exam papers were optimized in terms of their overall balance in three dimensions (as the goals) through the paired exchanges of items. These exam papers guarantee their consistency (in the tested knowledge points) and also ensure the fairness of the term test (a key psychological factor that motivates continued studies). Such an application is novel as the teacher(s) did not have a pre-set question bank and could formulate the fairest strategy for the A/B exam papers. The model can be employed to address similar teaching practice issues.


2020 ◽  
Vol 38 (3) ◽  
pp. 3371-3388 ◽  
Author(s):  
Jiashuang Fan ◽  
Suihuai Yu ◽  
Mingjiu Yu ◽  
Jianjie Chu ◽  
Baozhen Tian ◽  
...  

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1370
Author(s):  
Chin-Tsai Lin ◽  
Ching-Chiang Yeh ◽  
Fan Ye

This study proposes a novel evaluation model for lawyer selection incorporating the lawyer’s backbone leadership attitude employing the hybrid multi-criteria decision-making (MCDM) approach. In the proposed approach, the lawyer’s backbone leadership attitude is employed as an evaluation factor in the evaluation model for lawyer selection from law firms’ perspective. In this paper, a hybrid approach based on the Delphi technique and analytic hierarchy process (AHP) is proposed to manage qualitative and quantitative criteria for selecting the best alternative lawyer for law firms in China. Finally, a law firm in China is carried out to verify the feasibility of the proposed approach. Based on the result, the backbone leadership does provide valuable information in the evaluation model for lawyer selection. The results also revealed that the proposed approach would help law firms and human resource managers to understand and develop strategies to hire a lawyer.


Author(s):  
Ozan Çaldıran ◽  
Engin Baglayici ◽  
Morteza Dousti ◽  
Eren Mungan ◽  
Enes Bulut ◽  
...  

10.2196/27472 ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. e27472
Author(s):  
Leonardo W Heyerdahl ◽  
Benedetta Lana ◽  
Tamara Giles-Vernick

Background The COVID-19 pandemic has been widely described as an infodemic, an excess of rapidly circulating information in social and traditional media in which some information may be erroneous, contradictory, or inaccurate. One key theme cutting across many infodemic analyses is that it stymies users’ capacities to identify appropriate information and guidelines, encourages them to take inappropriate or even harmful actions, and should be managed through multiple transdisciplinary approaches. Yet, investigations demonstrating how the COVID-19 information ecosystem influences complex public decision making and behavior offline are relatively few. Objective The aim of this study was to investigate whether information reported through the social media channel Twitter, linked articles and websites, and selected traditional media affected the risk perception, engagement in field activities, and protective behaviors of French Red Cross (FRC) volunteers and health workers in the Paris region of France from June to October 2020. Methods We used a hybrid approach that blended online and offline data. We tracked daily Twitter discussions and selected traditional media in France for 7 months, qualitatively evaluating COVID-19 claims and debates about nonpharmaceutical protective measures. We conducted 24 semistructured interviews with FRC workers and volunteers. Results Social and traditional media debates about viral risks and nonpharmaceutical interventions fanned anxieties among FRC volunteers and workers. Decisions to continue conducting FRC field activities and daily protective practices were also influenced by other factors unrelated to the infodemic: familial and social obligations, gender expectations, financial pressures, FRC rules and communications, state regulations, and relationships with coworkers. Some respondents developed strategies for “tuning out” social and traditional media. Conclusions This study suggests that during the COVID-19 pandemic, the information ecosystem may be just one among multiple influences on one group’s offline perceptions and behavior. Measures to address users who have disengaged from online sources of health information and who rely on social relationships to obtain information are needed. Tuning out can potentially lead to less informed decision making, leading to worse health outcomes.


Author(s):  
Derya Deliktaş ◽  
◽  
Büşra Günhan ◽  

This study proposes a hybrid approach for the selection of students employed part-time at the various departments of a university. There are both qualitative and quantitative criteria for the selection of students. Thus, to handle the subjective assessment in the decision-making process, this study considers developing DEMATEL-modified ANP and MULTIMOORA. An empirical case study applied at Metallurgical and Materials Engineering Department in Turkey is exhibited to test the effectiveness of the proposed decision-making method, which provides a fair selection considering three main and seven sub-criteria. These criteria are determined in accordance with the previous experience of the commission members and the principles which are listed in the Administration Guideline of the university. One among five candidates is selected by a novel hybrid approach. The obtained results and all scenarios in sensitivity analysis based on the changing of the decision makers’ weights and the changing of the dimension weights indicate that the S3 student remains the most preferred alternative, and the S4 student mostly is the most suitable alternative, respectively.


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