An Investigation on The Role of In-between Spaces in Iranian Traditional Houses as an Architectural Heritage: The Case of Kashan Houses

In-between spaces have the duty of separating other space by putting a distance between them, facilitating spatial identification and specification along with creating consequent spaces which gradually lead passers from public environment to more private sections. Designing such spaces was considered a necessity with significant importance in the architecture of Iranian Traditional Housing. Therefore, regarding the importance of the issue under study, the goal is to discover strategies applied in Iranian Traditional Houses by benefiting from the data gathered through a survey carried out on 50 respondents and technicians in the field of Iranian Traditional Architecture. To do so, EFA was utilized to specify factors creating by in between spaces in traditional houses. The result revealed that elements of continuity, hierarchy and spatial organization are the most evident factors in the architect of Iranian Traditional Houses and as the statistic showed that the highest level variance belonged to spatial organization.

Spatial identification of component-based relative risks

This article aims at identifying the high risk provinces in Iraq using a finite Poisson mixture. Through this methodology, the levels of relative risk is determined through identifying the number of components. In this article we do not investigate spatial correlation among regions and assume that the levels of risk observed in different regions are independent each other. The estimation of the model parameters and the model selection are performed using the Bayesian approach which allow to allocate each province to an identified risk level. We consider the data of the Coronavirus disease (COVID-19) infections in 18 provinces in Iraq and determining the levels of relative risks of this pandemic. The results are spatially shown in map which illustrates that the best Bayesian model fitted the data is 3 components model (high, medium and low risk).

Interactive Scenario-Based Assessment Approach of Urban Street Lighting and Its Application to Estimating Energy Saving Benefits

If excessive and misdirected, street lighting (SL) causes energy waste and might pose significant risks to humans and natural ecosystems. Based on data collected by an interactive user-oriented method, we developed a novel empirical approach that enables the spatial identification of over-illuminated areas in residential neighborhoods and calculation of potential energy savings that can be achieved there, by reducing excessive illumination. We applied the estimated model to a densely populated residential neighborhood in the City of Tel Aviv-Yafo in Israel, to test the proposed approach’s performance. According to our estimates, illumination levels can be lowered by up to 50% in approximately 60% of the neighborhood’s area, which is currently over-illuminated, thus leading to significant energy savings, while preserving a reasonable level of visual comfort associated with SL.