Machine-learning algorithms aid predictions for complex systems with multiple influencing variables. However, many neural-network related algorithms behave as black boxes in terms of revealing how the prediction of each data record is performed. This drawback limits their ability to provide detailed insights concerning the workings of the underlying system, or to relate predictions to specific ...

Damage of the urban gas network due to an earthquake can cause much loss including fire-induced loss to infrastructure and loss due to interruption of gas service and repairing or replacing of network elements. In this paper, a new fire ignition model is proposed and applied to a conventional semi-probabilistic model for estimating various losses due to damage of an urban gas network in an eart...

water resources local governance can is one of the most influential collaborative approach in the water resources management. social monitoring of local stakeholders plays an important role in planning, resources management and water efficient governance. therefore to achieve this goal, social network analysis has been considered as an approach of analysis of the relationship among local stakeh...

objective: this paper tries to analyse and visualize the co-authorship network of institutions in 1351 papers published in 7 knowledge and information science journals in iran from 1387 through 1391.methodology: in this paper, we use scientometric and social network analysis to study the collaboration network of institutions. overall structure of the network was investigated using a few macro-l...

The connectivity of wireless network is critical for effective and efficient communications. Yet, it is challenged by mobility, transmission range and density. In terms of increasing node density, there is a transition phase of connectivity when a network starts transforming from partition to connected state. In this paper, we study the upperand lowerbounds of critical density for the transitio...

Abstract Currently, single-stage point-based 3D object detection network remains underexplored. Many approaches worked on point cloud space without optimization and failed to capture the relationships among neighboring sets. In this paper, we propose DCGNN, a novel based density clustering graph neural networks. DCGNN utilizes ball query partition exploits local global by Density optimizes part...

Social network researchers have long sought measures of network cohesion. Density has often been used for this purpose, despite its generally admitted deficiencies. An approach to network cohesion is proposed that is based on minimum degree and which produces a sequence of subgraphs of gradually increasing cohesion. The approach also associates with any network measures of local density which p...

Background and Objectives: While social network analysis has left a remarkable practical impact in the healthcare field, the potential implication of this methodology in the primary health domain is poorly researched. Hence, this study aimed to explore the use and usefulness social network analysis in the context of primary health care. Methods: The health volunteers of Imam Ali Health Center...