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Precise segmentation of tumors in the breast is one of the most significant steps for MRIs and diagnosis tools using computers. Segmentation of the breast tumor is a demanding task due to some factors including partial volume effect, the similarity of the brightness of tumor texture with other surrounding non-tumor textures, variety in shape size and location of the tumor in different patients. Due to its vitality, the process of segmentation is carried out manually by specialists and its disadvantages are long computation time, and high cost. To overcome these issues, algorithms are required to segment images with high accuracy and no need for user intervention. This study presents a new method based on fuzzy connectedness algorithm and super pixels for tumor segmentation in magnetic resonance imaging (MRI). The proposed method is applied to a dataset built by the respected researchers on Matlab. The suggested method has been compared using two commonly used methods of clustering and morphological operators in tumor segmentation in magnetic resonance imaging (MRI). Mean average precision of 98.33 and the Dice similarity coefficient of 98.06 signifies the prominence of the suggested method in comparison with other methods compared using clustering algorithm 90.33 and morphological algorithm 91.83. [ABSTRACT FROM AUTHOR]

The preparation and characterization of binary spinel nickel cobaltite, NiCo2O4 are presented by two methods. The prepared NiCo2O4 nanocomposites were tested for 1,3-dipolar cycloaddition reaction of different benzyl halides with phenylacetylene. The heterogeneity of the NiCo2O4 catalytic system was investigated using a hot filtration test, indicating that there is virtually no catalyst leaching into the reaction solution under the applied reaction conditions. Furthermore, our results show that the catalytic system can be reused four times without significant loss of stability or any additional treatment. [ABSTRACT FROM AUTHOR]

In order to prevent accidents and occupational diseases in workplaces, it is necessary to ensure the control of risks. Training has always been a fundamental pillar of health safety and environment management systems. This study was carried out to find the interventional role of training in promotion of HSE culture in wood industries. The Behsazan Wood Industry in Eslamshahr County, central Iran, was selected as a case study. Initially two pre-test and post-test sessions were held for the supervisors and workers in the company to assess the level of their HSE culture. The analysis of the training needs was done in accordance with ISO 10015 after administration of the specified training programs. The outcomes were analyzed using pre and post test statistical analysis. Finally, the relationship between training structures and HSE culture was investigated using structural equation modeling (SEM). After codification and implementation of six training courses, the results of the second part showed a significant difference in the three sub-factors, including "HSE awareness and attitude"," staff capability", and "HSE reporting". The noticeable changes in the sub-factor of "HSE awareness and attitude", as the most valuable result of this study, obviously indicated that the training programs were tailored and conducted to the training needs of the organization. Although the intervention seems to be effective from various aspects, however, it is often comprehensive and resource demanding. Thus, it is highly recommended to improve learning outcomes in all domains (cognitive, affective, and psychomotor) for planning promotion programs can be more effective in this industry. [ABSTRACT FROM AUTHOR]