Sharif Digital Repository

Purpose: The purpose of this research is to propose a framework for developing business intelligence systems (BIS). Design/methodology/approach: Following a qualitative research method, a comprehensive framework at organizational and individual level, as well as team level, was developed. Findings: The findings revealed that team-level influential factors play a more significant role in BIS development success. The results also indicate that BIS development relies on suppliers, customers and their relationships, whereas the supplier side has a more significant impact on determining successful development. Drawing on these findings, embedded knowledge, knowledge management process capability... 

Diurnal volume changes is one of the main factors influencing socket fit in trans-tibial prosthesis and causing pressure problem issues. Embedded bladder liners have been recently a potential approach to deal with this problem. The aim of this technical note was to introduce a new transtibial silicone liner designed based on hybrid socket theory. To make expandability in the liner, an integrated wax structure was constructed over the selected areas of the positive model and then removed after lamination process. In addition, a mechanical system with manual control was designed to fit the liner with the residual limb volume by pumping the water in or out of the liner through connec-tive... 

In this paper, an efficient approach for ultrasonic object segmentation with special application for left ventricle segmentation in echocardiography images is proposed. At first, an efficient hybrid trend for ultrasonic image edge detection is suggested. Then, a modified level set approach is introduced based on the extracted edges and the computed probabilistic map as the stopping criteria for the contour evolution. Both synthetic and clinical images are utilized as validation measures with respect to the prior techniques which indicate outperform results quantitatively and qualitatively. Left ventricle segmentation using proposed method illustrates expert-approved performance, providing a... 

Disease prediction is a well-known classification problem in medical applications. Graph Convolutional Networks (GCNs) provide a powerful tool for analyzing the patients’ features relative to each other. This can be achieved by modeling the problem as a graph node classification task, where each node is a patient. Due to the nature of such medical datasets, class imbalance is a prevalent issue in the field of disease prediction, where the distribution of classes is skewed. When the class imbalance is present in the data, the existing graph-based classifiers tend to be biased towards the major class(es) and neglect the samples in the minor class(es). On the other hand, the correct diagnosis...