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Dr Alireza Shahraki, Mrs Vajiheh Bahrami,
Volume 0, Issue 0 (5-2022)

Background and Purpose: The IoT is recognized as one of the most efficient and pervasive technologies that is constantly evolving. In order to use it effectively, it is necessary to get acquainted with the capabilities of this technology and the importance of each of them. Therefore, this study was conducted with the aim of identifying and ranking the capabilities of the Internet of Things in the industrial sector using multi-criteria decision-making techniques. And quantitative-qualitative research in terms of data analysis.
Materials and methods: In this study, IoT capabilities were identified in three categories of capabilities, benefits and challenges using library resources and Delphi method through a survey of experts. Data collection was done through questionnaires. Expert Choice software was performed.
Findings: The results of data analysis in this study showed that among the three main criteria, obstacles and challenges, advantages and capabilities are the most important, respectively. Also, among the sub-criteria of obstacles and challenges, security and operating system were the most important and compatibility was the least important. Among the sub-criteria of capabilities, artificial intelligence and communication had the highest and sensors the lowest and weighted rank. Also, among the benefits, saving time and reducing costs were the most important, and process improvement was the least important.
Conclusion: The results of this study showed that in order to use technologies such as the Internet of Things in the manufacturing sector, including the industrial sector, in order to use them more effectively and efficiently, it is necessary to identify the capabilities, advantages and obstacles of this technology. By determining the degree of importance and effectiveness of each of these criteria, selecting and prioritizing that aspect of technology for implementation is determined. Therefore, the results of this study, in addition to identifying the capabilities, advantages and obstacles of using this technology, also identified the priority of each criterion in terms of their importance.
Dr Hossein Vakilimofrad, Razieh Bahramian, Liyla Masuomi, Alireza Soltanian,
Volume 5, Issue 4 (3-2019)

Background and Aim: Relative generality and precision are two important criteria for measuring the efficiency and performance of information retrieval systems. The aim of this study was to compare the integrity and location of evidence-based bases in the digital library of Hamedan University of Medical Sciences in data retrieval of diabetes.   
Methods: The design of this research is cross-sectional, survey, descriptive and is an applied type. Preparing a list on clinical questions here was done as referring to the Diabetes Center in Semirom for 5 months. The following keywords were searched on databases: Up To Date, Clinical Key, Embase, Cochrane, Ovid, and PubMed Tool. The data were analyzed using the descriptive and inferential statistics in terms of tables, diagrams, chi-square test.
Results: The findings showed that both Ovid and Clinical Key databases recovered more relevant documents in contrast to other databases Based on the most relevant documents. According to the relevant and relatively relevant documents, Clinical Key, Embase, Ovid and Up To Date databases had the highest recall in contrast to the PubMed and Cochrane databases which possessed the lowest recall. According to the most relevant documents, the Ovid Database has the highest precision while the PubMed Database had the lowest precision. Among the databases, up to date had retrieved the relevant documents.
Conclusion: Ovid possesses more recall and precision among the databases analyzed, but evidence-based resources are generally well-suited to clinical questions in the field of diabetes

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