abbas alimohammadi

The challenges of food production in the 21st century make the employment of modern agricultural technologies increasingly vital due to population growth. The Internet of Things (IoT( is critical in changing traditional technology into modern technology, and it could help smart agriculture reduce waste and increase output. The integrated use of this technology in large metropolitan or national areas is problematic since data producers employ various formats and standards to implement the IoT. One of the most challenging aspects of utilizing the IoT in agriculture is gathering the collected data and displaying it online and in a standard format. This research has examined a method for receiving information from sensors, storing it, and presenting it in a standard context utilizing IoT technology. The result of this research shows that the sensor's data and their observations can be recorded in a standard format using the standard sensor observation service from the Open Geospatial Consortium. An integrated platform is built using spatial data infrastructure. In fact, using a standard format reduces the number of services requested and the parameters associated with the sensor name, retrieval time, and sensor position. Therefore, the output of sensor observations in the spatial portal of spatial data infrastructure will be more easily accessible than methods that use only web services. The use of spatial data infrastructure makes it possible to display sensor data alongside other spatial layers. Using this method, agricultural environmental data collected using sensors are more easily provided to farmers and decision-makers instantly and online.

The increasing shortage of the renewable water resources in the country has made the farm water needs estimation to become as one of the important priorities in agricultural water management. Farm water needs are normally controlled by climatologic factors. It equals to the reference evapotranspiration which is corrected by a scaling factor associated to the crop kind and to local characteristics. In this research, using Landsat satellite imagery, we estimated and compared the crop coefficients for main agricultural crops in the Moghan cultivation industry, from two procedures: the first based on evapotranspiration measuring, and the second based on NDVI measuring. The comparisons in the case of the five main crops showed that the Root Mean Square Errors are within an acceptable range, leass than 0.28. In the following, the evapotranspiration based crop coefficient has been used in order to estimate farm water needs. Farm's water needs are indeed estimated by six methods a combination of two actual evapotranspiration and three reference evapotranspiration ways. Among the six methods, the Metric/PenmanMonteith method was selected for final step, i.e. farm irrigation needs. The farm irrigation needs is equivalent to farm water need minus effective rain. We compared four different ways for estimating the effective rains but preferred the FAO method assigned for low slopes. Based on our results, farm irrigation needs in the Moghan cultivation industry range from 270 mm (for rainfed barley) to 1500 mm (olive groves). Statistical investigation in three years data revealed a dependency between yield performance and evapotranspiration rate. In addition, it showed that yield performance is correlated with crop spectral indices such as NDVI, LAI and SAVI. The primary goal of this research is to estimate local agricultural crop coefficient in the Moghan cultivation industry. The second goal is to investigate of relationships between crop coefficient and crop spectral indices in order to make the crop coefficient estimable directly from spectral indices.

Security is one of the most basic needs of any country and progress and prosperity are achieved by security. On the other hand, power and defense of the country against violation and malice is necessary for the security. This power and defense is achieved through the development of defense and security researches. Without defense research, security is dependent on foreign equipment, which itself challenges security. On the other hand, defense and security research and its development requires financial resources while government budgets are limited. So, identifying new sources of funding for defense and security research is essential. One of these options is the capacity of the charitable society. Accordingly, the present study seeks to identify and prioritize the factors affecting the attitudes and incentives of the benefactors to finance defense and security research. For this purpose, after reviewing the literature, for identifying the indicators that affect the supportive behavior of the benefactors, semi-structured interviews were conducted with the benefactors, Organization of Endowment and Charity experts and researchers. Then the factors were prioritized using the Hierarchical Analysis Process based on the opinion of 30 experts (consisting of the charitable foundations of the country and charity institutes). The results of the research showed that among the 25 main indicators affecting the behavior of the benevolent, the indices of one’s history, patriotism and durability of one’s name are the most important indicators and excitement of feelings, lack of concern about confiscation of property and tax incentives are the low priority.

Scheduling vehicles’ runtime and dwell time is one important phase of designing and developing public transportation systems. Apart from trains’ headway time in subway systems, parameters such as time and rate of acceleration when trains startup or brake and also their dwell time at stations influence scheduling design criteria including passengers travel time, economic efficiency of the service and the amount of energy consumed. Since these criteria are not positively correlated, Tehran subway line no. 1 service schedule has been optimized using NSGA-II in this study. To achieve this goal, the problem was modelled first and objective functions of optimization procedure were formulated based on scheduling criteria. Then, by performing the multi-objection algorithm, solutions occurred on the Pareto Front was obtained. Since the number of solutions obtained by NSGA-II are numerous, K-Means analysis was used to cluster solutions. Centroids of each cluster could be considered as candidate solutions that one of them will be chosen by decision makers as the preferred solution. Results of the study show that using the suggested approach would output a wide variety of solutions and provide possibility of choosing the final solution based on decision preferences for the decision maker. Calculated objective functions for candidate solutions were compared with those for current subway schedule that resulted in the preferred solution to be chosen which leads to passengers travel time and economy loss of the system decreasing by 7.16 and 5.13 percent respectively.

Defense industry is one of the most important users of new technologies in the country that plays an active role in the innovation process. In recent years the importance of science and innovation cooperation networks in the areas of defense is well understood and to networking capabilities of the elite, universities, research centers and knowledge – based companies “Center of scientific cooperation and the elite affiers” was established to creation and development of scientific network of Defense industry. So far, the mission of the Center of scientific cooperation and the elite affairs has not yet fully achieved and there are many barriers along the way. The study focused on the offices of mediator in the network, by using of a qualitative approach major obstacles to the formation of effective networks in the field of defense industry were identified. To this end After reviewing the literature and concepts of scientific collaboration and innovation’s network, interviews with 10 officials of the offices of a mediator in one of the main networks in the Defense industry by thematical analysis method was analysed and ultimately in the form of major and minor themes were defined. The results show that barriers to staff, environmental condition and managerial and structural elements decreases the effectiveness of the mediator's offices to play their role in the network.

The ever-increasing population leads to establishing new educational centers. One of the important stages in school establishing, is selecting the optimal locations for them according to different objectives and criteria. The objectives are defined to determine well-distributed schools with balanced capacity and minimize the incompatibility of land-uses in the area. Increasing the related factors and criteria makes the location-allocation problem more complicated. Therefore, it is necessary to use efficient methods to solve it. In this paper, GIS, Multi-criteria decision making methods and multi-objective evolutionary algorithm were used to location-allocation of multiple girls’ primary schools in region 17 of Tehran urban area. Equity in geographic access and balance of schools capacity were considered in optimization process. Furthermore, suitability of the selected sites was determined considering the distance from the compatible and incompatible land-uses of the area. Because of using a multi-objective evolutionary algorithm, multiple solutions are presented in results instead of only one solution. In this research, five solutions were selected and investigated. In the best solution according to the first objective function, although the suitability of sites is adequate, the capacities of schools are imbalanced. In the best solution according to the second objective function (equity in geographic access), the chosen sites are well-distributed, but the compatibility of the land-uses and suitability of the sites are not satisfactory. Similarly, in the best solution according to the third objective function (balance of schools capacity), compatibility of the land-uses and suitability of the sites are inappropriate. Anyway, decision-makers can compare different optimal solutions and choose one of them to implementation according to different relative importance of objective functions.

In this paper, has been tried to discriminate wheat_cultivated fields from those crops that have similar characteristics to this class, spectrally and phonologically, in bahar_hamedan region. So based on cultivation calendar of study region, decided to apply bitemporal or dual_season multispectral spot5 images for this aim. Both images divided to discrete objects(polygpns) using multiresoluion segmentation algorithm. The zonal attributes of segments entered to discriminant analysis as variables. After the stepwise discrimination analysis, all the segments were classified using outputted discrimination functions. ‘’discrimination accuracy’’ and ‘’ classification accuracy’’ were defined as discrete concepts. Also, with assuming the DNs of each band pixels as variables “pixel based” discriminant analysis was applied. Comparison of both methods results indicated that generally, accuracy of pixel_based classification is upper than other method.

All phenomena in the universe are undergoing change and transformation. Certainly, we can say that there is no phenomenon on the planet that does not undergo metamorphosis. The difference between the phenomena in terms of change is the difference in the rate of change. In studies on land and natural resources, phenomena in general can be classified in terms of the rate of change into three categories: high speed (flood, earthquake, storm, climate change), average speed (land use, urban development) and slow (topographic changes, etc.) phenomena. Remote sensing has made it possible to study average and high speed changes. With the availability of images for two different times, changes can be assessed. In this regard, using images of the years 1988 and 1998 from the city of Tehran, changes in land use in this city have been retrieved and determined.