دکتر سید احمد حسینی

In most of the old cities of Iran, the tissues with historical value are seen in abundance, which are recognized by various characteristics such as smallness, access problems and instability. Taking into account problems such as negative population growth, lack of access within the necessary neighborhoods, and the ever-increasing expansion of space is therefore important. In ruined and abandoned tissues, not having the necessary facilities, action should be taken to solve these problems. This research was conducted with the aim of analyzing the effects of social, economic and physical factors on the regeneration of the neighborhoods of the central fabric of Kashan city (including seven neighborhoods) and the descriptive, analytical research method and the desired information was collected in the form of a survey. There were about 44,000 people in the area. The size of the research sample was estimated to be 385 people using Cochran's formula. SPSS and AMOS software were used to analyze the research data. The findings of the research showed that access to services and facilities, identity and social capital, housing ownership, and income were factors influencing the regeneration of dilapidated structures, and in the neighborhoods of Soltan Mirahamd and Darb of Esfahan, which enjoyed the mentioned privileges, residents were more inclined to re-create dilapidated structures.

IntroductionAs a land use specially designed for physical activity, recreation and leisure, sports facilities are considered to be a public space vital for the society, improving health and well-being of the community. Therefore, special attention should be paid to the pattern of distribution, easy access to these land uses, and spatial organization of these facilities in accordance with the pattern of road networks. Accordingly, the pattern in which sport facilities are distributed across urban areas can have a direct impact on the desired operational efficiency of the city. Therefore, optimal site selection and easy access to sports facilities are of great importance for a healthy city and a healthy community. A huge difference between per capita sports areas and the standard per capita or imbalanced distribution of sports facilities in the region may result in reduced interest in physical activities and threaten the health of individual and society. Accordingly, the present study has evaluated per capita sports spaces in Kashan, and the spatial distribution of these facilities. The average time required for accessing these spaces has also been measured in accordance with the local road network and the total area each facility serves. Finally, an optimal model has been proposed for sports related land use in Kashan. Materials & MethodsThe present descriptive-analytical study is applied in nature and uses ArcGIS and SuperDecisions software to analyze its descriptive and spatial data. To provide an optimal model, 11 indicators including area each land use serves, its quality, urban land use, population density, health centers, educational centers, distance from faults, distance from urban waterways, fuel centers, distance from industries, parks and green spaces were identified based on expert opinions. The importance of each indicator was also determined based on expert opinions using the ANP model, and weighted linear combination was used to combine the previously mentioned indicators in GIS. A brief summary of the models used are presented in the following section.  Results and discussionThe nearest neighbor algorithm is used to evaluate the spatial distribution regardless of the total area of each sports facility. Results indicate the presence of a completely clustered distribution (P = 0.000 and Z = -3.368) at the level of 99%. Finally, the relative weight of each criteria is combined with the relative weight of each option obtained from ANP model using the weighted combination in GIS to reach an optimal model for site selection. The resulting value actually indicates the necessity of new sports facilities. In other words, higher values show higher priority and as it is shown, about 40% of the total area of Kashan is potentially appropriate for new sports facilities while about 60% of the city area is not suitable for such facilities. ConclusionOptimal site selection maximizes the efficiency of sports facilities and improves the quality of services for those using the areas. Therefore, the present study aims to evaluate the area each sports center is serving and provide an optimal model for site selection in Kashan. In 2016, Kashan had a population of about 304 thousand people and about 202 thousand meters of sports related land use. Thus, there was a 0.67 square meters per capita sports related land use in Kashan. Finally, 11 indicators were combined using the weighted combination to reach an optimal model. Results showed that about 40% of the total area of Kashan is potentially appropriate (relatively appropriate and completely appropriate) for new sports centers while about 60% of this urban area is not suitable for construction of such facilities. Moreover, results proves the efficiency of spatial statistics used to evaluate spatial distribution of land uses. As it is shown in the present study, GIS can provide an optimal model for site selection using practical indicators and appropriate data analysis methods. In general, results indicate that sports facilities in Kashan are not generally in a good condition in terms of per capita and distribution pattern which confirms the fact that these issues were not considered important in the process of site selection.

Landforms represent influential processes affecting features on the earth’s surface both in the past and in the present while providing important information about the characteristics and potentials of the earth. The shape of the terrain and features such as landforms affect the flow in water bodies, sediment transport, soil production, and climate at a local and regional scale. Identification and classification of landforms are among the most important purposes of geomorphological maps and also a fundamental step in the process of producing such maps. Geomorphologists have always been interested in achieving a proper and accurate classification of landforms in which their morphometric properties and construction processes are clearly indicated. The present study has attempted to develop a new method and identify the relationship between morphometry of landforms and surface processes using a multi-scale and object-based analysis. Extraction and classification of landforms are especially important in mountainous areas, which are considered to be dynamic due to their special physical and climatic conditions. These areas are often remote and sometimes unknown. Mountainous topography has also made them difficult to access. However, they are of great importance due to their impact on the macro-regional system. Because of this significant importance, Maku County was selected as the study area.

Maku County is located in northwestern Iran (West Azerbaijan Province) which borders Qarasu River and Turkey in the north, Aras River and the Republic of Azerbaijan in the east, Turkey in the west, and Shut County in the south. This County is located between 44° 17' and 44° 52' east longitude and 39° 8' and 39° 46' north latitude. The present study takes advantage of satellite images (sentinel-2A) with a spatial resolution of 10 m, derivatives of DEM layer (slope, maximum curvature, and minimum curvature, profile and plan curvature) and object-based methods to identify and extract landforms of the study area precisely. 

The present study applies various functions and capabilities of OBIA techniques to extract landforms precisely. These functions include texture features (GLCM), average bands in the image, geometric information (shape, compression, density, and asymmetry), brightness index, terrain roughness index (TRI), maximum and minimum curvature, texture, and etc. The image segmentation scale was first optimized in the present study using ESP tools and objects of the image were created on three levels (9, 17, and 27 scales). In the next step, sample landforms were introduced, membership weights were calculated and defined for the classes in accordance with the fuzzy functions, and finally, 14 types of landforms were extracted using object-oriented analysis.

Fuzzy method includes boundary conditions, defines membership function, and constantly considers landform changes in class definition. Thus, it seems to be ideal for the purpose of the present study. The present study used two types of data (data derived from satellite imagery and DEM layer) along with OBIA approach to extract landforms. Classification of landforms based on fuzzy theory makes it possible to collect more comprehensive information from the earth's surface. Results indicate that fuzzy object-based method has classified landforms with an accuracy of 87% and a kappa index of 85%. Considering the resolution of the images applied in the present study, all features were extracted with an acceptable accuracy except for debris. This can be attributed to the fact that debris is usually accumulated in a small area on steep mountainsides, and thus remains hidden from satellites in nadir images. OBIA approach shows a high efficiency because it can combine spectral characteristics of various types of data (i.e. images and DEM data) and their derivatives while analyzing the shape of the segment, and size, texture and spatial distribution of segments based on their class and other neighboring segments.

Physical status and body composition are affected by various parameters such as ecological, nutritional, and racial as well as age and sex factors. Therefore, identification of most effectiveness factors for health and sport performance can be useful to develop a formulation during sports programs. Therefore, this study aimed to determine the relationship between somatotype profile, environmental potential and socio-economic indicators in some provinces of Iran.

 This research is a descriptive-analytic type. The somatotype and body mass indices (boys 9-13 years old) are used as anthropometric indicators as well as the height, latitude and human development indices are used as environmental and economic indicators. The Human Development Index, are considerd as average of the three indicators of life expectancy, education and per capita GDP in terms of equal purchasing power with the same weight. The statistical methods were used as spatial statistics in ArcGIS and SPSS softwares.

Regression analysis showed that there is a linear relationship between somatotype and topographic features (R2=0.39, p=0.02). Also, according to regression test, there was a significant relationship between body mass index and latitude (R2=0.42, p=0.0001), height (R2=0.39, p=0.008) and human development index (R2=0.377, p=0.005) respectively.

The physical condition and especially the somatotype, depends on geographical areas and also different socioeconomic conditions. Therefore, it can be used extensively in talent identification, sports polarization and health promotion. type profile and environmental potential and socio-economic indicators in the provinces of Iran. Present investigation methodology is a descriptive-analytic type. The somatotype and body mass index data are used as anthropometric indicators and height, latitude and human development index data are used as environmental and economic indicators. The Human Development Index results from the average of three indicators of life expectancy, training and education, and GDP per capita is in terms of equal purchasing power with the same weight. For this purpose, analyses are done through using statistical methods and statistical techniques and spatial statistics in ArcGIS and SPSS softwares.

Regression analysis showed that there is a linear relationship between somatotype and and topographic features (R2 = 0/386, p= 0.023).Also, according to regression test, there is a significant relationship between body mass index and latitude, height and human development index respectively; (R2=0/423, p = 0/0001), (R2 = 0/398, p = 0/008), (R2 = 0/377, p = 0/005).

The physical condition, and in particular the somatotype, depends on geographical areas and different socioeconomic conditions, and this can be widely used in the identification and designation of sports poles.

Today, the smart city is emerging as a new urban development strategy that has different dimensions.Smart city management is considered as the most important smart city dimension.The purpose of the present research is to create more and common insight into smart city management and specific processes that can improve this goal.Regarding the nature of the subject, the prevailing approach to this research is descriptive-explanatory.In this regard, library and field methods including text-editing, phishing, reading, tabling, interviewing, panel questionnaire (Delphi) and Micmac software have been used.The results indicate that according to the prioritization made for successful implementation of smart city management, out of thirty-three indicators, first of all, the conditions of nine (9) indicators (including the availability of software and hardware infrastructure, base formation Data, The continued use of innovation in relevant organizations and institutions, the exchange of data and information among all stakeholders & ...) Then, according to the results of the research, we have determined the type and level of relationship between city management and citizens.. In the end, while presenting a conceptual model-executive for intelligent management, two suggestions have been made in the direction of more efficient city intelligent management.

A review of current global developments suggests that the city and urbanization have fundamentally experienced some qualitative and quantitative changes. One of the most important consequences of such changes during the recent decades is the disturbance of service system’s distribution and their concentration in a particular location. The proper management of the growing need for sport will never be possible without having enough information, tools, and modern methods in different levels of neighborhood, district, region and city. Easy and quick access to sport services, cost saving and optimal allocation of resources require scientific methods and related criteria to support the management of cities. Accordingly, the present study evaluates the spatial pattern and presents an optimal model for locating sports centers in Tehran. The research method is a combination of descriptive and analytical methods and its type is applicable. To analyze the data ArcGIS and Super Decisions software are applied. Also, Average Nearest Neighbors index, ANP model and fuzzy logic are used for analyzing the data related to locating sport spaces. The results of this study showed that according to the cluster pattern of the distribution of sports spaces in Tehran and also the lower per capita sport spaces of this city than the minimum number of inhabitants, access to these centers is not suitable in the current situation. The results of the fuzzy model showed that the situation in the central regions of Tehran is more inferior in this regard.

1- Introduction Twentieth century began with a billion people with 10 percent urban dwellers. It has ended with 6 billion people and 50 percent urban dwellers. Therefore, urban planning is more important than ever before. As a result, attention to the optimal distribution of applications and service centers is needed and thus most programmers are working with this issue. Accordingly, one of the most preliminary needs of disaster victims in the initial hours proceeding man-made disasters is health utilities. Supplying and equipping health care systems and their proper distribution among urban regions is one of biggest challenges for crisis managers. Extracted maps by network analyst model shows that hospital centers distribution in Tehran 3rd district do not comply with the principle of equitable distribution and adequate access for all citizens. A Lack of equitable distribution and lack of proper servicing in case of man-made crises in the region under study is one of the main reasons of this study. In this paper the allocation of hospital centers in Tehran 3rd district is done by colonial competitive algorithm. 2- Methodology The research method in this paper is based on a combination of descriptive and analytical procedures. The case study area included Tehran 3rd District in northern Tehran, with six regional and 11 neighborhoods and a population of 290,726 people in 2006, with an area of 29.38 hectares. Required information for this research has been collected from housing and population census data, 1:2000 maps and comprehensive and master plans of Tehran in addition to magazines and books related to the research topic. The results were analyzed using Arc/GIS, Super Decisions and Matlab software with network analysis was used for the evaluation of hospital service span and ANP model and ICA algorithm were used for hospital centers allocation. 3-Discussion The internal flexibility of urban systems, the potential utilization of internal rules and regulations conforming to the expectations of external passive defense system are important factors that help planners and urban designers while creating a healthy and safe urban demand. According to analysis, it is revealed that the pattern of hospitals centers distribution is inappropriate in the study area and has many deficiencies. Accordingly, allocating the correct and optimal hospitals centers were based on the principles of passive defense. The allocation of hospital in this research was based on three principals: safety, consistency and efficiency. Moreover, population factors, population density, passage confinement, pathway access, suitability, and neighborhood service area were defined as sub criteria in this case study. The results are been shown in fig 1. After converting the layers to measurable criteria, the final Weights were calculated by Network Analysis Model (ANP). Then the relative weight of each factor relative to the weight of each item obtained were incorporated in the Weighted Overlay function. The resulting number indicates the region which has the highest priority is to establish hospitals.Finally, after optimizing the algorithm based on colonial competitiveness, hospitals center has been allocated in the case study area. Accordingly, each of the proposed sites is listed for the applications of weighted priorities in Table 3, and the final results are shown in Figure 2. Table 3: Preference weights for the Tehran 3 district hospitals Centers Numbers 1 2 3 4 5 6 weights 6.3 5.79 5.54 5.83 5.36 5.79 Map 2: Optimal sites for medical centers in Tehran 3 District 4- Conclusion and Suggestions In this study, medical centers have been allocated with an emphasis on the principles of passive defense. This new approach to site selection for urban applications uses a heuristic algorithm colonial competition. Furthermore, network analysis model were used to examine the distribution of and access to hospital facilities. The results of network analysis showed that these centers cannot provide appropriate services in man-made crises in the region and do not follow the same distribution in the region. In order to optimize site selection and basic principles of passive defense, network analysis models, ANP model and algorithm of ICA were used for selecting of the best sites for medical centers. The results of this study showed that colonial competitive algorithm can be used as a suitable model for urban land use site selection and help urban planners to understand and prioritize and find best solutions for urban issues.

One of the main factors for human gathering equivalence and stability is dwelling place. So the dwelling is a fundament requirement for family which is necessary provide human demands and all social life system is forming in a one dwelling place will be obstacle for forming, safe growth and become a place for pleasing family and these element has been causing the dwelling place converting to one of the main human requirements. The main object of the main human requirement of urban dwelling an approach to access social democracy in the urban region of razavi khorasan. In this research dwelling place index in the points including congestion, facilities percapita, microlitihic, endurance and materials. The required data has been obtained from 1385 demographic censuses and residence place which is the required data are un scaleby fuzzy model and then components weights related to each domain extracted by hierarchy model and applied for ranking urban points from TOPSIS model. Ultimately only %22/05 from all points in this index including desirable quality and %11/4 from area including mean quality but total 19 urban situated 8 urban in the unsuitable position.

One of the objectives defined in the facility location problem is the maximum dispersing facility location. In these issues، the goal is maximizing the distance between the facilities according to the available constraints. In some cases these issues use the location of radio stations، schools، sales representatives and general location with sensitive facilities which have much application in passive defense principles. On the other hand، the facilities operating one principle of passive defense should be dispersed. Therefore، they should be established in a place where they can gain their mission correctly. As a result، the coefficient errors are reduced. Considering this issue (coefficient of performance and reduced error of candidate points)، we suggest Data Envelopment Analysis with the criteria to choosing locations with efficient distribution model. So، in this paper a new multi-objective model for locating critical and important facilities considering passive defense principles is presented.