In the last few decades, structural health monitoring has gained relevance in context of civil engineering, and much effort been made to automate process data acquisition analysis through use data-driven methods. Currently, main issues arising automated processing regard establishment a robust approach that covers all intermediate steps from output production interpretation. To overcome this li...

Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimiz...

  Background: Because of the importance of community health and the growing need for health care Health organizations have expanded their scope and with an entrepreneurial approach seeking to upgrade their performance. Knowledge is the most important capital of organizations and key factor in economics. The purpose of this study was to investigate the effect of knowledge management on organizat...

Learning 3-D scene structure from a single still image has become a hot research topic recently, during which edges played a very important role as they provided critical information about the structures. While not all the intensity edges are useful, existing 3-D reconstruction methods suffered heavily when not differentiating structural edges with non-structural ones. In this report, we consid...

Automatic extraction of structural models interferes with the deductive research method in information systems research. Nonetheless it is tempting to use a statistical learning method for assessing meaningful relations between structural variables given the underlying measurement model. In this paper, we discuss the epistemological background for this method and describe its general structure....