درخت حوزه‌های تخصصی

Nowadays Iran’s position on the international corridors, the loss of Iran's roads accidents and the emergence of environmental and energy issues, have made the development of transportation in Iran a prerequisite. The purpose of this research is to identify the effective factors on the he high speed train technology transfer and provide t its framework. Data collection has been done with library and field studies. After these stages, from 73 extracted indicators, 54 main indicators were selected by the experts of the rail transportation technology field. According to these indices, the research questionnaire was designed and distributed. Finally, after completion of the questionnaires by 37 experts in the technology transfer field, the collected data were analysed using structural equations and PLS Smart software and the research model was fitted. The 49 indicators were accepted in 3 factors and 8 dimensions for the designed model. Also the results indicate that in the selecting and acquiring technology factor,the technology selection ranked first, the technology acquisition ranked second and technology recognition ranked third and in the Deployment factor, the technology adaptation and localization,the technology absorption and analysis and technology exploitation dimensions were ranked first to third respectively and in the maintaining factor, the technology development and improvement and technology diffusion dimensions ranked first and second respectively.

Opportunistic networks in the Internet of Things (IoT) scenario, also known as OppIoT, espouse IoT devices interactions opportunistically in order to improve connectivity, the lifetime of the network, and network reliability. An increase in opportunistic utilization is fostered by IoT applications to find communication opportunities whenever possible to route and deliver data efficiently. In this opportunistic scenario, devising an efficient path for data delivery is a challenging work due to uncertainty in the connection between the nodes and the selection of intermediate forwarder nodes for data delivery towards the destination. Considering the scenario of uncertainty in device location and exploiting IoT devices opportunistically, this paper propounds a routing algorithm for OppIoT called Hybrid Multi-Copy Routing Algorithm (HMCRA). The proposed algorithm finds potential forwarder nodes by using fuzzy logic wherein residual energy, distance, and speed of the nodes are considered as input values while preparing fuzzy rules. Genetic Algorithm (GA) is considered along with fuzzy logic to select an efficient path for data delivery. In GA, the delay is taken as the fitness function to select a reliable path for data delivery. Simulation results of the proposed algorithm perform well in contrast with relative existing routing algorithms with respect to latency, overhead ratio, delivery probability, and hop count. The work uniqueness lies in the selection of potential nodes and finding path having less hop count in an opportunistic IoT network scenario.