Investigating the main implementation factors of M-commerce: A case study in Saderat Bank, Iran

Nowadays, M-Commerce influences on organizational and social activities cause to change the nature of performance styles. This research explores how organizations are influenced to adopt the M-commerce. The research employed the Technology Acceptance Model (TAM) to examine factors affecting organization attitudes toward this emerging mobile technology and applications. In present research the sample size consisted of 79 employees that were selected at random from 42 branches of employees from Saderat Bank in Tabriz-Iran in 2012. Data analyses were carried out by using Factor Analysis, Structural Equation and Freidman Mean Ranking Test. The results of present study illustrated that there was a significant relationship between factors together, and also considering the Ranking Analyses it can be said that the Compatibility of performance factors is more important factor than others for improving M-Commerce in studied place

Investigating the main implementation factors of M-commerce: A case study in Saderat Bank, Iran

Nowadays, M-Commerce influences on organizational and social activities cause to change the nature of performance styles. This research explores how organizations are influenced to adopt the M-commerce. The research employed the Technology Acceptance Model (TAM) to examine factors affecting organization attitudes toward this emerging mobile technology and applications. In present research the sample size consisted of 79 employees that were selected at random from 42 branches of employees from Saderat Bank in Tabriz-Iran in 2012. Data analyses were carried out by using Factor Analysis, Structural Equation and Freidman Mean Ranking Test. The results of present study illustrated that there was a significant relationship between factors together, and also considering the Ranking Analyses it can be said that the Compatibility of performance factors is more important factor than others for improving M-Commerce in studied place

Investigating the main implementation factors of M-commerce: A case study in Saderat Bank, Iran

Nowadays, M-Commerce influences on organizational and social activities cause to change the nature of performance styles. This research explores how organizations are influenced to adopt the M-commerce. The research employed the Technology Acceptance Model (TAM) to examine factors affecting organization attitudes toward this emerging mobile technology and applications. In present research the sample size consisted of 79 employees that were selected at random from 42 branches of employees from Saderat Bank in Tabriz-Iran in 2012. Data analyses were carried out by using Factor Analysis, Structural Equation and Freidman Mean Ranking Test. The results of present study illustrated that there was a significant relationship between factors together, and also considering the Ranking Analyses it can be said that the Compatibility of performance factors is more important factor than others for improving M-Commerce in studied place

Medical image registration using unsupervised deep neural network: A scoping literature review

In medicine, image registration is vital in image-guided interventions and other clinical applications. However, it is a difficult subject to be addressed which by the advent of machine learning, there have been considerable progress in algorithmic performance has recently been achieved for medical image registration in this area. The implementation of deep neural networks provides an opportunity for some medical applications such as conducting image registration in less time with high accuracy, playing a key role in countering tumors during the operation. The current study presents a comprehensive scoping review on the state-of-the-art literature of medical image registration studies based on unsupervised deep neural networks is conducted, encompassing all the related studies published in this field to this date. Here, we have tried to summarize the latest developments and applications of unsupervised deep learning-based registration methods in the medical field. Fundamental and main concepts, techniques, statistical analysis from different viewpoints, novelties, and future directions are elaborately discussed and conveyed in the current comprehensive scoping review. Besides, this review hopes to help those active readers, who are riveted by this field, achieve deep insight into this exciting field