A novel sorting method topsis-sort: an applicaiton for tehran environmental quality evaluation

Many real-life problems are multi-objective by nature that requires evaluation of more than one criterion, therefore MCDM has become an important issue. In recent years, many MCDM methods have been developed; the existing approaches have been improved and extended. Multi criteria decision analysis has been regarded as a suitable set of methods to perform sustainability evaluations. Among numerous MCDM methods developed to solve real-life decision problems, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily in diverse application areas. In this paper, a novel sorting method (TOPSIS-Sort) based on the classic TOPSIS method is presented. In the TOPSIS-Sort approach an outranking relation is used for sorting purposes. The proposed approach uses characteristic profiles for defining the classes and outranking relation as the preference model. Application of the proposed approach is demonstrated by classifying 22 districts of Tehran into five classes (but none of the districts fits into Classes 4 and 5), representing areas with different levels of environmental quality. An analysis and assessment of the environmental conditions in Tehran helps to identify the districts with the poor environmental quality. Priority should be given to these areas to maintain and improve the quality of environment. The results obtained by the TOPSIS-Sort give credence to its success, because the results of sorting con firm our and specialists’ evaluation of the districts. This research provides appropriate results with respect to the development of sorting models in the form of outranking relations. The model, proposed by this study, is applicable to the other outranking methods such as ELECTRE, PROMETHEE, etc

Risk assessment in tourism system using a fuzzy set and dominance-based rough set

The purpose of this study is to identify risks, discover rule base structure and the impact of risks by knowledge base system design in one of the Iran tourism destination. Based on tourism system approach, the factors of risks are divided in two dimensions: internal risks and external risks and seven criteria: political, economic, cultural-social, technological, environmental-health, functional and safe-security. Data were analyzed by fuzzy inference system and Dominance-based Rough Set Approach (DRSA) synthesizing to construction of forecasting risk assessment system. Tourists’ perspectives towards the possibilities of risks were first assessed within seven risk factors and converted into a systematic structure within the structure of rough sets. Designing of a fuzzy expert system was dealt with using the created knowledge database. Then, the system’s sensitivity analysis was examined. The results indicate that the system can be a good way to estimate the risks and their fluctuation rates and impacts on the development of tourism destinations. The technological, social, functional and safety-security risks had the highest values in the system designed for minimum travel repeatability. The research suggests that it is important impact of risks and their interaction with each other on the future development of tourism destination

Indicators Affecting the Urban Resilience with a Scenario Approach in Tehran Metropolis

Urban resilience refers to the capacity of an urban system to fully recover from unforeseen calamities. This study aims to assess the physical resilience indicators used to measure urban resilience in Tehran, the political and economic capital of Iran, and to pinpoint the most significant direct and indirect influences on urban resilience. The research process divided into two parts. The environmental scanning approach (reviewing papers and published sources, interviewing specialists, and monitoring conferences) and the literature review were employed in the first part to compile a database of the key information on the elements impacting physical resilience. The most significant factors impacting physical resilience over the next ten years were requested to be identified by specialists and intellectuals in the second part. Finally, the MicMac program was used to analyze the data after 29 variables were specified in Delphi. In light of the trace-analysis-dependence diagram, which depicts the instability of the influential factors and the persistence of their impact on other variables, the results demonstrate that Tehran’s physical resilience is in an unstable condition. According to the results, the factors that have the maximum impact on other variables are granularity drivers, emergency evacuation capacity, rescue and security spaces (emergency, fire station, and police station), impermeability, rate of the amendment and retrofitting measures in the buildings of each zone, building age, and the compatibility of land uses. The variables that are most susceptible to change from other variables include the distribution status of dangerous land uses, the quality of the buildings, the rate of historically vulnerable buildings, the vulnerability of internal and external roads, the rate of improvements and retrofitting measures in buildings in each zone, as well as historically vulnerable historical buildings

Spatial Analysis of the Distribution of Small Businesses in the Eastern Villages of Gilan Province with Emphasis on the Tourism Sector in Mountainous Regions

The development of small businesses in rural areas as a key strategy for sustaining the population and improving the quality of life of villagers has always been a concern for many developed and developing countries. Some rural areas provide their villagers with favorable conditions for the development of businesses in order to enjoy the potential in the field of tourism. Sustainable development in these areas can be achieved with systematic attention and planning. In the present work, the spatial analysis of the distribution of small businesses in the eastern parts of Gilan Province was studied with an emphasis on tourism in mountainous regions. The study population consisted of all villages in the east part of Gilan Province, and the sample included all businesses officially supported by the Omid Entrepreneurship Fund. The research method was a descriptive analytic in which GIS software and the G statistic were used for the analysis of spatial correlation, clustering, hot and cold spots analysis and buffer zones. Finally, the results of the study showed that the spatial distribution of businesses in different economic sectors (agriculture, industry, services and tourism) were different between 2011 and 2016 in the way the cluster pattern was formed in agricultural and service activities. A cluster pattern cannot be considered in the tourism and industrial activities, but there is a random (point) pattern; in this regard, the results indicate the importance of the factor of distance between the village and the city center in the distribution of tourism businesses. In addition, the highest levels of support for businesses were in the agricultural and services sectors, while the lowest support was in industry and tourism. Finally, the results showed that the distribution of businesses in all activities was much higher in the plains and valleys as compared to the mountainous and hill areas

Role of Air Pollution and rs10830963 Polymorphism on the Incidence of Type 2 Diabetes: Tehran Cardiometabolic Genetic Study

Diabetes mellitus (DM) is considered one of the leading health issues that are egregiously threatening human life throughout the world. Several epidemiological studies have examined the relationship of a particular matter<10 μm (PM10) exposure and with type 2 diabetes mellitus (T2DM) prevalence and incidence. Accordingly, the current study is a study investigating the independent influence of air pollution (AP) and rs10830963 on the incidence of T2DM. A total number of 2428 adults over 20 years of age participated in a prospective cohort (TCGS) during a 9-year follow-up phase. The concentration of AP was measured, and the obtained values were considered the mean level in three previous years since the exposure concentration took the people living in that location. The COX regression model was employed to determine the influence of AP and rs10830963 on the incidence of T2DM in adjustment with covariate factors. Among the 392 T2DM, 230 cases (58.7%) were female diabetics, and 162 (41.3%) were male diabetics. According to the multivariable-adjusted model, exposure to PM10 (per 10 μm/m3), associated with the risk of T2DM, although just a borderline (p=0.07) was found in the multivariable model (HR; 1.50, 95% CI; 1-2.32). The rs10830963 was directly associated with the incidence of diabetes, and the GG genotype increased the T2DM rate by 113% (more than two times) (HR; 2.134, 95% CI; 1.42-3.21, p≤0.001) and GC increased it by 65% (HR; 1.65, 95% CI; 1.24-2.21, p≤0.001). Long-term exposure to PM10 was associated with an increased risk of diabetes. Thus, it is suggested that the individuals with variant rs10830963 genotypes fall within a group susceptible to an increased risk of T2DM arising from AP