فهرست مطالب مسلم درویشی

Greenhouse refers to a limited space that has the ability to control the appropriate environmental conditions for the growth of plants in different areas during different seasons of the year. Rapid economic and cultural growth, population growth, soil and water constraints, the community's need for food, the existence of large consumer markets and the interest in producing off-season crops in recent years have led to the development of greenhouse crops. But choosing the wrong place to build a greenhouse leads to a waste of capital and the failure of these goals. The purpose of this study is to find the optimal location of the greenhouse in Asadabad plain with a sustainable development approach.

Due to the existence of numerous and effective parameters –for the performance of greenhouses, the technique of multi-criteria analysis has been used to find a suitable location. Also, due to the uncertainty in the behavior of natural parameters, fuzzy logic has been used to model the effect of the parameters.

The results show that of the total area of Asadabad plain, 10% are in a very good condition, 39% are in a good condition (suitable with restrictions) and 51% are in a bad condition in terms of greenhouse construction.

Relying on spatial analysis can reduce the investment risk for greenhouses and lead to environmental sustainability.

With the expansion of the urban limits, some of the lands that were used for gardening years ago have been located within the urban limits. The difference between the value of garden land use and urban land use, such as residential and commercial, encourages gardeners to change their land use. Urban managers try to prevent this change of use by enforcing strict rules.Assessing the success of such plans requires examining land-use change in the urban over a long periodof time. The main purpose of this study is to detect abandoned urban gardens using Landsat satellite imagery. The second goal is to determine the extent of changes in urban gardens in the study area over the past 30 years. In this study, based on Landsat satellite images in 2018 and 1988 for the northern slope of Alvand Mountain in Hamadan province and the city of Hamadan, the normalized differential index of vegetation (NDVI) along with land surface temperature (LST) in 9 time periods per year was extracted. The results indicated a 4/75 ° C increase in LSTfor the region over 30 years. Also, the inverse relationship of LST with NDVI is confirmed. Based on the separation of urban gardens, a comparison was made between 2018 and 1988, which showed a decrease of 175 hectares of urban gardens in the study area, which is equivalent to a 49% reduction in urban gardens. In the main part of the research, based on the behavioral evaluation of urban gardens, in these two characteristics, a differentiation index for active and abandoned gardens is presented. Examination of the results based on ground truth data including 25 active gardens and 25 abandoned gardens suggested that the proposed method had an overall accuracy of 82% and a Kappa coefficient of 0/64.

The study area includes a part of the northern slope of Alvand Mountain, which is limited to the southern part of Hamedan and has a latitude of 34 degrees and 45 minutes to 34 degrees and 48 minutes north and a longitude of 48 degrees and 27 minutes to 48 degrees and 31 minutes east. Ground truth data including 25 active gardens and 25 abandoned gardens were collected as field visits using a Garmin GPSMAP 62s handheld navigator so that coordinates were collected by attending the location of abandoned and active gardens. The satellite data used in this study concern the time series data of Landsat 8 satellite OLI and TIRS sensors for 2018 and Landsat 5 satellite TM sensor for 1988.To achieve the first objective and separate active and abandoned gardens in 2018, the land surface temperature (LST) and the normalized difference vegetation index (NDVI) are calculated and the behavior pattern of these two components is examined during the year for active and abandoned gardens in nine periods according to the proposed method, a final index for separating active and abandoned gardens is presented based on the NDVI behavior pattern throughout the year. The time series of NDVI for each year is evaluated in 9 periods and garden maps are extracted in 1988 and 2018 to achieve the second objective and prepare the maps of 30-year changes in active gardens in the study area. The rate of change of area and the percentage of changes in the class of gardens are obtained by comparing the maps.

Since this study is conducted mainly to identify abandoned gardens in urban space, two criteria for assessing user accuracy and errors of commission in the abandoned garden class are very important. In other words, in this problem, the number of gardens that are properly divided into the abandoned garden class is important, and the proposed method provides an accuracy of 86%. The most important issue is the number of abandoned gardens that the proposed method has mistakenly labeled as active gardens, which is 14% in this method. Both accuracies provided are evaluated as acceptable. The overall accuracy of the proposed method is estimated at 82%, which is acceptable, indicating the efficiency of the proposed method.

One of the problems facing human societies today is the reduction of forests and gardens. Given the important role that trees play in improving the quality of human life, protecting them is one of the inherent duties of rulers. Various factors cause the destruction of trees, one of which is the development of urban areas in the vicinity of forests and gardens. Traditional methods of conserving natural resources and monitoring their changes have failed in practice. For example, in the study area, 49% of the tree-covered areas have declined over the past 30 years. However, the ban on construction in the area has always been emphasized by city managers in the years under study, and the inefficiency of the methods used has been proven by the statistics provided. New methods of monitoring changes based on satellite image processing can be alternatives to traditional methods due to their high accuracy and speed and significant cost reduction. The proposed index is recommended to be evaluated to separate active and abandoned gardens in other areas facing this problem using images with higher spatial resolution. In different cases of threshold limit, the overall accuracy of the proposed method is examined based on the ground truth data of the evaluator. At best, the separation of active and abandoned gardens is associated with an overall accuracy of 82%.

Due todecreased rainfall and increased groundwater harvesting, our country faces drought. With drastic decline of water levelin lakes and hydroelectric reservoirs, water scarcity is deeply felt. Thus, managers and officials shall find new ways of decreasing waterconsumption and overcome this crisis. Due to the rising global temperatures and reportsof the World Wildlife Fund, water scarcitycrisis will dominate most countries of the world, especially in Europe and Asia in the next ten years (Sengupta, 2018). Therefore, advanced water management principles shall be applied to decrease water consumption in the agricultural sector and maintain water security. Iran is among the top five countries of the world in terms of having vast irrigated land (Bruinsma, 2017), which shows that in many parts of the country agricultural lands are irrigated. Thus, the country’s water resources reach a critical stage, and because of limited resources, no more water can be provided for agriculture. The present study primarily seeks to optimize crop cultivation using two approaches: first, reduce water consumption and increase farmers’ income and second, reduce water consumption and meet domestic demand. In order to achieve this goal, first, the type of crops and area under cultivation were determined using remote sensing and satellite imagery. Then,spatial information system was used for data analysisand optimization of crop cultivation.  

Remotely sensed images were used to collect data about the area under cultivationin agricultural patches and crop type. Those images were then analyzed using remote sensing techniques.According to pixel-based classification ofmultitemporal satellite images using training data, a croplabel is assigned to each pixelin this method. Moreover, borders of each agricultural land are extracted from pan-chromatic images of the region with higher spatial resolution. Finally, fitting the results of pixel-based classification with the extracted bordersof each agricultural land,a final croplabel is determinedfor the total area of the agricultural landbased on the majority labels. In order to optimize the problem, two objective functions (relationships 1 and 2) are defined in which income maximization and water consumption minimization are considered. Typically, location and allocation problems include objective and constraints functionswhich are maximized or minimized based on the goal of the problem. Linear programming is used to solve the problem. Linear programming is a classical optimization method whichdevelop a deterministic algorithm tosolve the problem. This method can only be used when the relationships between variables are linear. In other words, the relationship between variables shall be perfectly proportional and directin this method. (1) (1)  (2) 

The study area consists of 198 hectares of agricultural land in vicinity of GolangTapeh village of Asadabad city. The city covers an area of ​​1195 km2 and constitutes 6.1% of Hamadan province. It is located between 34° 37› to34°50 ‹northern latitude and 47°9› to 47°51›eastern latitude. Its average height is 1607 meters above sea level. The city is bounded in northwest with the province of Kordestan,in west with the province of Kermanshah, in southeast with Tuyserkancity and in the northeast withBaharcity. Assad Abad consists of three plains and a mountainside, but since it mostly consists of fertile plains, it can be considered as a flat area (Fig. 1). Fig1: Case study area   Figure 2 shows the results of pixel-basedclassificationusing neural network method. In this method, network is trained using ground data. After training the network on the basis of ground truth estimator data, the estimation accuracy is about 88%.   Fig. 2: The results ofclassification using neural network Following the calculation of the area under cultivation in agricultural lands and the type of crops, optimization is investigated using two scenarios (Figure 3). In the first scenario, reduction of water consumption and increased farmers’ income and in the second scenario,meeting domestic demandsto prevent capital outflow is considered.     Fig3: Crop type and boundaries of agricultural lands   In the first scenario, our priority is to reduce water consumption and increase farmers’ income. In this scenario, the goal is to select the type of crops according to the modeling constraints so that the crop type and water consumption are optimized. Figure 4 shows the proposed crop type.   Fig4: The results of thefirst scenario  

The present study used a combination of remote sensing and spatial information system to find a solution for optimization ofcultivation pattern through two different scenarios. First, land boundaries and types of crops were determinedusing pan-chromatic images and artificial intelligence. Then, two objective functions were developed to minimize water consumption and maximize income. Also, constraints such as crop type, periodicity constraints and domestic demand were modeled. Considering two objective functions, an algorithm was presented to optimize the cultivation pattern and the results were implemented in this algorithm. Results indicated that the difference between the first scenario which seeks to minimize water consumption and maximize farmers’ income and the second scenario which seeks tominimize water consumption and maximizedomestically demanded crops is relatively small. In both scenarios, the water use rate inAsadabad plain have decreased by about 1000 m3. In other words, in both scenarios there was a 50% reduction in water consumption. Moreover, if priority is given to meeting domestic demand, water consumption increase by about 3% and income decrease by about 3%. In future studies, owners of each agricultural land can be determined and each farmer’s incomecan be considered to further optimize crop cultivation.

The effectiveness of the research to measure the achievement of the goal has always been emphasized by managers. Hence, the purpose of this research is to investigate the effectiveness of the Iran Police maintenance center from the viewpoints of experts and managers of the organization. To measure the effectiveness of the maintenance center, 5 variables, namely the planning process, acceptance process, inspection process, parts supply process and maintenance process were explored. The method of this study is based on the purpose of the applied research, based on the time of data collection, sampling and in terms of data collection, it was a descriptive research. The statistical population of the present study is managers and maintenance experts of Iran Police maintenance center. According to Cochran's formula, the sample size was 92 and the questionnaires were distributed among them. The sampling method is simple random. A researcher-made questionnaire was used to collect data and was used by the faculty members and relevant experts to evaluate their validity. Also, Cronbach's alpha for the 963 questionnaires was obtained which indicates a high reliability of the instrumentation. Data were analyzed using SPSS software. In analyzing the data, the planning process, the acceptance process, the inspection process, the process of supplying parts, and the maintenance process were evaluated by experts and effective managers.

Introduction and Background: The growth of cities and the increase in the population and the diverse use of urban lands have caused problems for urban communities. One of these is the phenomenon of heat islands, which is the result of an unusual temperature increase of the city relative to the surrounding countryside. This research tries to achieve a general view on the heat island mechanism, air temperature changes and urban temperature changes in parts of Hamadan city by using TIRS (Landsat 8 satellite images) and comparing it with actual ground level data by statistical methods. The temperature difference of different points from satellite images based on the spectral radiance method and the degree of gray value of pixels in the thermal bond was made using the photo of the Planck equation. Based on the relationship between real data on ground surface temperature at the meteorological station and data extracted from satellite images, according to different regression models, the highest determination coefficient was obtained for three linear, quadratic and cubic correlation methods. Among them, the cubic regression method with the least error was meaningful at 95% confidence level. The high explanatory factor (70% and above) indicates that there is an acceptable coordination between satellite image information and weather station information. The maximum difference between the data taken with the actual ground station data is related to the blanket and minimum temperature of 5.5 and the minimum difference of the green area is 0.5°C. The difference in temperature in different parts of the city is more closely related to the minimum temperature. While the temperature difference in areas covered by green space in Hamadan city with real data is higher at maximum temperature. The results showed that the Hamadan heat islands have a direct relationship with the construction and land use. The temperature changes in different parts of the city of Hamedan are indicative of the creation of heat islands in the non-used building and ground areas. The results of this research can be applied in the management and urban planning and land use of Hamedan.

Global warming has profoundly changed the climatic regions of the earth and the time and the place of snowfall, which has caused a lot of damage to humans, especially in recent decades. Indeed, depending on the nature of the climatic regions, these changes are diverse and varied. Mountains and valleys play different roles in the uneven distribution of the temperature and snow. The effects of different directions can be very important in snow coverage on the northern and southern slopes. In this research, using statistical models and satellite images in the Alvand, the role of the elevation, the direction of the slope, and the effect of temperature changes on snow cover in the recent decade (2015-2006) have been investigated. In this research, based on Landsat satellite 5, 7, and 8 imagery, the data from the visible and infrared bands were used to extract snow data based on the NDSI index. The NDSI index was applied using relationship (1) to produce snow maps on images. Indeed, the use of relative indices such as NDSI reduces the effect of the topography on the result.
(1)
To investigate the role of the Alvand in snowfall in both of its northern and southern slopes and the snowfall regime changes in its windward slope and windsurf, the harmonic analysis was used. For this purpose, to analyze the snowfall co-ordinates and periodic behaviors and time variations, the monthly mean snowfall per cm with harmonic analysis was used. This analysis is given as a substring using a time series. Resultsand Discussion: According to the findings of the NDSI index, Tuyserkan area receives less snow (62%) than Hamadan (69%). The moist air mass ascending the western slopes of the Alvand's heights causes more rainfall than its eastern slopes. However, the temperature of Hamadan station is lower than that of Tuyserkan due to its northern slopes in the Alvand and the less energy it receives from the sun, which has made the snowfall on the northern slopes be more visible than it is on the southern slopes. The minimum and maximum temperatures have increased in the winter. This steep trend of increase in the winter temperatures along with lower snowfall indicates the effects of climate change and global warming on Hamadan and Tuyserkan regions. The value of the variance in the second harmonic reflects the effect of elevations on the region's climate. The value of the second harmonic variance in the northern slope which is 28% and significant shows the impact of topography on snowfall in the area. Indeed, the snowfall up to 28 % is related to the height and topography of the northern slopes of the Alvand.
While at Tuyserkan Station, this amount is reduced to 20%, meaning that the northern altitude of the Alvand is more effective in the snowfall. The Alvand is a branch of the Zagros mountain range that passes through Hamedan province and has high peaks. The climatic phenomena of this mountain range are abundantly observed in the province. Severe winds and snowfall of the Alvand altitudes are among these phenomena. The mountainous cities of the province, including Hamadan and Tuyserkan, are among the most affected by the Alvand. This study by examining the hidden features of the climatic data by harmonic analysis and satellite images showed that the northern slope shared more than the southern slope in snowfall which was a significant amount in the second harmonic and a relative decrease in the temperature and snowfall. The northern slope was colder in the northern hemisphere and the sunrise of southern slope got more heat than those that were not exposed to the direct sunlight. The percentage of snow in the NDSI index on both sides of the Alvand confirmed this geographic reality. In general, the results showed a hidden feature of the rise in temperature and snow loss in the data and satellite imagery also recognized this fact. Considering the fact that the Alvand is a climatic region of the country's cold and mountainous regions and the sustainability of the natural environment depends on the relative stability of the climate, in order to achieve sustainable development and land use in the region, it seems that regional climate change should be considered in the context of climate change and the reduction of snowfall in the long time.

All people are entitled and eager to be aware of their daily performance results.This has another aspect for employees and that is employees are interested to be aware of the organization’s comments about themand on the other hand, the organization is entitled to express his opinions about the organization's human resources that are a major capital of the organization and inform them.The study aimed to identify and rank the effective factors in evaluating the performance of NAJA employees.Choosing appropriate indicators in the evaluation of staff performance is the most important part of implementing performance evaluation management in organizations. The present study used Fuzzy Delphi method to identify factors effective in evaluating the performance of NAJA personnel and in this study, experts’ opinion was used to evaluate the performance. First, to identify effective factors through interaction with experts and using Fuzzy Delphi method, eight factorswere eventually identified. Identified factors include: the satisfaction of managers and supervisors, staff performance skills, effectiveness and efficiency of staff, internal and external customer satisfaction,coworkers’ satisfaction, commitment and responsibility to the duties, the revolutionary spirit and religious beliefs of staff and creativity and innovation in doing tasks. Then, in order to determine the effect of indices, fuzzyDEMATEL method was used.Fuzzy DEMATELresults introduced the satisfaction of managers and supervisors as the most important indicator in evaluating the performance of staff.