routing

Ease of routing is one of the most important principles in the design of public spaces. Such spaces can provide higher desirability when they can communicate with numerous users. This study aims to find the components affecting the mental image, to investigate the compliance of the mental map of passengers from the terminal, and the effect of the variables of gender, education, and the number of trips on the mental map. The results in the theoretical part reached four main components: body, readability, meaning, and attractiveness, each of which includes six subsets. Then, by studying these components, a questionnaire was developed and distributed among the passengers. Software analyses were performed by SPSS. The results of the one-sample Chi-square test to check the compliance rate of the mind map showed that the mind map of passengers in terms of the body, meaning, and attractiveness is undesirable. However, the readability of the airport is desirable. The effectiveness of gender, education, and the number of trips on the mind map was reported to be 0.34, 0.14, and 0.27, with a coefficient of determination of 25%, respectively, indicating that the above variables explain 25% of the variance of the mind map. According to the t-tests of independent female samples, there was a clearer mind map in all components, and the analysis of the variance test shows that the higher the number of trips and the level of education, the clearer the mind map.

Wireless Sensor Networks (WSNs) have been employed in various real-time applications and addressed fundamental issues, such as limited power resources and network life. Several sensor nodes in a WSN monitor the actual world and relay discovered data to base stations. The biggest issue with WSN is that the sensors have a limited lifetime and use much electricity to relay data to the base station. This paper proposes an improved PSO-based Enhanced Distributed Energy Efficient Clustering (EDEEC) algorithm to extend the network's life and reduce power consumption. Clustering is the process of forming groups of sensor nodes. The cluster aims to improve the network's scalability, energy efficiency, and other characteristics. The particle swarm optimization algorithm is modified to obtain energy-efficient WSNs. The assessment is based on the essential WSN characteristics, including network lifetime and energy efficiency (power consumption). Compared to LEACH, HEED, and DEEC, our proposed IPSO-EDEEC uses less energy.