Misunderstanding of technology transfer and lack of a scientific viewpoint in this area are among the fundamental problems of some industries. A novel Delphi-decision-making trial and evaluation laboratory (DEMATEL)-elimination and choice expressing reality (ELECTRE) decision-making method, which benefited from both qualitative and quantitative methods, is introduced on gray numbers to solve the selection problem of technology providers systematically. The technology provider evaluation criteria are developed according to a literature review and experts’ opinions. Next, the Delphi method is used to evaluate the criteria. Gray DEMATEL is used to investigate the cause and effect relationship between the selected criteria, based on which the criteria were ranked. Finally, using the gray ELECTRE method, the priority of companies is determined. Based on the results of the illustrative case study, the two most robust causal criteria are management/executive capability and cost. Moreover, cost and support through organization policies played a leading role in the system. Also, out of nine technology providers, company 4 is superior to other companies, whereas most companies were of greater advantage to company 5. According to the comparison of weights by Spearman's correlation coefficients, the proposed method is as efficient as the available methods. This novel method can be used in uncertain conditions to select the most reliable company.

Breast cancer is the most common invasive cancer and the second leading cause of cancer death in women. and regrettably, this rate is increasing every year. One of the aspects of all cancers, including breast cancer, is the recurrence of the disease, which causes painful consequences to the patients. Moreover, the practical application of data mining in the field of breast cancer can help to provide some necessary information and knowledge required by physicians for accurate prediction of breast cancer recurrence and better decision-making. The main objective of this study is to compare different data mining algorithms to select the most accurate model for predicting breast cancer recurrence. This study is cross-sectional and data gathering of this research performed from June 2018 to June 2019 from the official statistics of Ministry of Health and Medical Education and the Iran Cancer Research Center for patients with breast cancer who had been followed for a minimum of 5 years from February 2014 to April 2019, including 5471 independent records. After initial pre-processing in dataset and variables, seven new and conventional data mining algorithms have been applied that each one represents one kind of data mining approach. Results show that the C5.0 algorithm possibly could be a helpful tool for the prediction of breast cancer recurrence at the stage of distant recurrence and nonrecurrence, especially in the first to third years. also, LN involvement rate, Her2 value, Tumor size, free or closed tumor margin were found to be the most important features in our dataset to predict breast cancer recurrence.

The welding tool parameters play a critical role in obtaining weld strength during friction stir welding. In this investigation, the effect of welding tool parameters such as pin and shoulder diameter and pin height on the axial and traverse forces and also temperature of welding of AA5083 alloy was investigated. A specially designed dynamometer was used to measure the welding tool forces. Then, the mechanical properties of the welds were characterized using tensile tests. Moreover, macrostructure of welds was investigated in order to analyze weld quality. Finally, optimum values for shoulder diameter, pin height and pin diameter were determined.