Sharif Digital Repository

Thermal neutron analysis (TNA) technology has been used for the non-destructive detection of explosives. The system uses a relatively weak 252Cf neutron source (1.03.107 n/s) and two 3″3×″ NaI(Tl) detectors. The presence of explosives is confirmed via detection of the 10.83 MeV prompt gamma-ray associated with nitrogen decay. The MCNP4A code was used to simulate the neutron and gamma transport through the system. The thermal neutron flux in the activation position was measured using gold and indium foils. The measured thermal neutron flux was lower, by not more than 9.5%, than that of simulation. In this report the results of the preliminary tests on the system are described  

Iran is a country with numerous traffic accidents, offenses, and disruptions. According to the deterrence theory, increased detection of traffic offenses would decrease violations. Detection of traffic offenses is insufficient in Iran due to the limited operational capacity of the police. Reducing traffic violations would reduce accidents, disorders, and socio-economic costs. In this paper, a scheme for detecting and reporting speeding and parking violations to infringement processing through a crowdsourcing platform is proposed as a solution considering Iran's economic and social context. Two scenarios for detecting and reporting speeding and parking violations were considered: public... 

In this paper, we have proposed a quasi-static model of a multi-agent system as police agents with and without non-holonomic constraints for agents' motion. We also consider an active thief agent which has stochastic dynamic equation of motion. Our control purpose is that these police agents pursue the thief agent and the geometrical center of them aims the thief agent current position. Also in the motion of the police agents for surrounding the thief, the unity of the swarm should be preserved and collision between them should be avoided. Police agents do not have all of the dynamic states of the thief agent's motion andalso those that are available and observable for the police agents are... 

We study the interdiction of illegal product distribution in a network with multiple sources (origins) and sinks (destinations). This work contributes to the literature of dynamic maximum flow interdiction problems by addressing multiple commodities in a network of relationships. The related distribution network consists of (1) criminals, who are hierarchically connected, and seeking to maximize the total profit flow from origins to destinations, and (2) enforcement officers aiming to minimize criminals’ long-term success by monitoring and arresting them, using the limited resources at their disposal. Considering several real-world operational details, we first propose a mixed-integer... 

We study the interdiction of illegal product distribution in a network with multiple sources (origins) and sinks (destinations). This work contributes to the literature of dynamic maximum flow interdiction problems by addressing multiple commodities in a network of relationships. The related distribution network consists of (1) criminals, who are hierarchically connected, and seeking to maximize the total profit flow from origins to destinations, and (2) enforcement officers aiming to minimize criminals’ long-term success by monitoring and arresting them, using the limited resources at their disposal. Considering several real-world operational details, we first propose a mixed-integer... 

We study the interdiction of illegal product distribution in a network with multiple sources (origins) and sinks (destinations). This work contributes to the literature of dynamic maximum flow interdiction problems by addressing multiple commodities in a network of relationships. The related distribution network consists of (1) criminals, who are hierarchically connected, and seeking to maximize the total profit flow from origins to destinations, and (2) enforcement officers aiming to minimize criminals’ long-term success by monitoring and arresting them, using the limited resources at their disposal. Considering several real-world operational details, we first propose a mixed-integer... 

This paper investigated the headway distribution of platooning vehicles in work zones with and without automated Speed Photo Enforcement (SPE). Data from two work zones were collected and analyzed. The portion of vehicles traveling with a very short headway (less than 0.7 sec) was also examined. In addition, the behavior of vehicles near the law enforcement vehicles was analyzed in terms of applying brakes and changing lane in one of the work zones. The results indicated that the mean headway of cars in the median lane significantly increased in both work zones when the SPE van was present compared to the base condition. For trucks, the mean headway increase was significant only in the... 

Systems based on machine vision are used more and more these days. Machine vision is used widely in different industries for increasing efficiency and automating processes, and one of the reasons which makes these techniques so popular is the speed of producing more powerful hardware which in recent times became more accessible, so real time using of many algorithms is possible Our group is designing and producing a stereo vision based system for detection, tracking, and accurate speed measurement of multi vehicles in, both mobile and stationary status, different weather condition, day and night, urban streets and highways, which is now used by police for law enforcement. The system offers... 

Transaction cost theory is largely used to investigate the formal domain of land and housing. In the informal domain, however, this perspective has been employed largely as a supplement in addressing the other fundamental notion in new institutional economics—property rights—despite the possibility that informality in land development can emerge regardless of the informality or formality of such rights. To cover this gap, this study developed a theoretical framework based on transaction cost theory to explain the formal–informal dichotomy in land development. The proposed framework maintains that land development depends on engaging in transactions that involve total or partial ownership of... 

An improved vorticity-based gridding technique is presented and applied to create optimal non-uniform Cartesian coarse grid for numerical simulation of two-phase flow. The optimal coarse grid distribution (OCGD) is obtained in a manner to capture variations in both permeability and fluid velocity of the fine grid using a single physical quantity called "vorticity". Only single-phase flow simulation on the fine grid is required to extract the vorticity. Based on the fine-scale vorticity information, several coarse grid models are generated for a given fine grid model. Then the vorticity map preservation error is used to predict how well each coarse grid model reproduces the fine-scale... 

Iran, having two separate coastlines at its north and south of about 3000 km length, with very different characteristics, suffers from various coastal problems. While its northern coastal area is over-populated and its sensitive and unique habitats must be protected from destruction, most of its southern coastal areas are undeveloped and deserted. Intense oil and gas exploitation activities in the Caspian Sea region and occurrence of two wars in the Persian Gulf during the last two decades have rendered hydrocarbon pollution a major issue for this country's marine and coastal environment. Biodiversity is under threat in some areas and natural resources are deteriorating. To overcome the... 

The human impact on the coastal ecosystems is a global environmental concern. Due to the growing urbanization, industrialization, and transportation, this impact on the living and non-living components of the coastal area is expected to further increase in the coming years. Artificial intelligence based automation of the coastal monitoring, including data collection, analysis and decision making, provides real-time insights and opportunities for large-scale coastal management and governance. In this paper, a framework for autonomous litter surveying and human activity monitoring for governance intelligence in coastal eco-cyber-physical systems (ecoCystem) is presented. A large dataset of... 

Road speed cameras are usually used in photovoltaic power plants, especially in the areas with limited or no access to grid power. However, there are many areas in Iran where wind power is more accessible than solar energy. So, in this study, a small permanent magnet vernier generator is designed to meet power concussion requirements of traffic enforcement camera. The designed generator is optimized to achieve lower harmonic content of no-load induced voltage and lower cogging torque. In this regard, the effect of geometrical dimensions and the configuration of permanent magnets are investigated using three-dimensional time stepping finite element method. Both no-load and full-load... 

This paper is focused on video event recognition based on frame level CNN descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited computational resources. After fine-tuning of the existing Convolutional Neural Network (CNN) concept score extractors, pre-trained on ImageNet, the output descriptors of the different fully connected layers are employed as frame descriptors. The resulting descriptors are hierarchically post-processed and combined with novel and efficient pooling and normalization methods. As major contributions of this work to the video event recognition, we present a... 

This paper is focused on video event recognition based on frame level convolutional neural network (CNN) descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited computational resources. After fine-tuning of the existing CNN concept score extractors, pretrained on ImageNet, the output descriptors of the different fully connected layers are employed as frame descriptors. The resulting descriptors are hierarchically postprocessed and combined with novel and efficient pooling and normalization methods. As major contributions of this paper to the video event recognition, we present a... 

This paper is focused on video event recognition based on frame level convolutional neural network (CNN) descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited computational resources. After fine-tuning of the existing CNN concept score extractors, pretrained on ImageNet, the output descriptors of the different fully connected layers are employed as frame descriptors. The resulting descriptors are hierarchically postprocessed and combined with novel and efficient pooling and normalization methods. As major contributions of this paper to the video event recognition, we present a...