Advanced Defense Science and Technology
Year:2016 | Volume:6 | Issue:4|Papers Count:7

As source and channel coding are performed independently from each other without any feedback, source coding tries to remove redundancy of the information whereas channel coding tries to increase reliability of transmitted data. As known, channel capacity restricts volume of the transmitted data and so depending to conditions, it is required to have a tradeoff between source and channel coding. The aim of this paper is to improve the quality of the synthesized video by increasing the robustness against channel errors in fixed transmission rate. In other words, the robustness of the transmitted video frames increases without any increment in bit rate. This results in improvement in the quality of the synthesized video. In the proposed method, the transmitted information is considerably compressed using neural network with Huffman coding in H.264. Then a secondary channel coding whose rate depends on the amount of the compression is applied on the compressed information. This causes that the proposed method is able to increase channel coding rate and therefore provides higher protection for the transmitted information and more robustness against channel errors. The obtained results by the proposed method are compared to the other methods for different source coding rates and SNRs.

Bridges are important structures in a transportation system which may be one of the targets of terrorist attacks. Given the complexity of bridges against the blast, the purpose of this research is determining a suitable equivalent static load pattern for nonlinear analysis of composite steel deck bridges under the load of the blast. For this purpose, at first, the simulation of blast and modeling of bridges with composite decks have been performed and the accuracy of the proposed modeling method is evaluated. Then several samples of bridges with the composite deck under the load of the blast have been modeled with different intensities and nonlinear dynamic analysis is carried out on them. By proposing a suitable load pattern and after the nonlinear static analysis on all samples using displacement control, the equivalent static load factor to correct the desired pattern in each sample is calculated. Based on the results of the nonlinear analysis of the samples, a correlation for the equivalent static load factor is extracted and evaluated.

Considering the importance of power networks in national security, power system stability under critical conditions such as occurrence of contingencies is the most important concern of power system engineers and government. In this area, employing Distributed Artificial Intelligence (DAI) theory and also Wide Area Monitoring, Protection And Control (WAMPAC) infrastructures may help to create a flexible organization where provides a robust system against contingency occurrence. This study proposes an adaptive structure on the basis of Multi Agent System (MAS). In this context, an algorithm has been proposed which helps the control system to save power system from collapse after detection of wide area voltage violation. Also, in order to verify the proposed algorithm, Dig SILENT software has been employed to simulate and the results are compared with conventional structures such as central control system and also unsupervised control structure.

Electromagnetic bombs use a powerful electromagnetic pulse to destroy the target. When using this kind of bombs, due to presence of strong magnetic flux, high voltages and currents appear on the transmission lines, which are harmful and destructive for all kinds of electrical and electronic equipment. In this paper a new algorithm is introduced with which robustness of electrical network and its electrical components are preserved in a possible electromagnetic attack.In this work, that used from Time-Based Improved Equal Area Criterion (TBIEAC) idea, it is assumed that protective relays of transmission lines are able to detect the over currents and send commands to circuit breakers for disconnecting related lines. Here, with the use of presented algorithm, fast power swings are scrutinized. Based on the results obtained, a decision is made to identify if the specified generator is subjected to a loss of synchronism or not.The simulation results show that the proposed method has higher response and precision compared with the previous methods.

For critical and sensitive facility location, finding an adequate coverage can reduce the amount of damages which are caused by disaster or military attacks; and also, locating the critical facilities far from each other can decrease the probability of identification and destruction of them. In this paper, a bi-objective mathematical model is derived for the critical facility location problem, in which the principals of passive defenses have been taken into account via the objective functions of minimizing the uncovered demand amount and maximizing the minimum distance between facilities. In the proposed model, it is assumed that each facility is identified and destructed based on a specific and known probability. Furthermore, it is supposed that injuries (customers) can be served by those facilities located within a predefined coverage distance. Since the proposed problem is NP-hard, a bi-objective genetic algorithm is presented in order to solve the large sized problems.

The advances in hyperspectral remote sensing technology, have become these images the specific information source for target identification. "spectral anomaly detection" Processing domain, which determine the location of unusual objects on the image identifying anomalies in hyperspectral images, is a threat in camouflage designs. the subject of this article is success evaluation of camouflage designs deal with this threat. The assessment process should be comprehensive and to be done on the basis of efficient measures. In this paper, the type of algorithm, the background specifications and the target specifications, were considered as the efficient parameters in the anomaly detection process, and on the basis of it, were presented measures for effectiveness evaluation of camouflage designs in terms of Spectral anomaly features. In the software implementations on two hyperspectral images, was created a variety of real and synthetic targerts with different camouflage levels. effectiveness Evaluation of simulated camouflage levels using the proposed measures and Comparison and analysis of the received results, shows the The effectiveness of the proposed measures.

In recent years, terrorist groups have become a major Threats for the world. These terrorist groups attack critical infrastructures and cause substantial damages. One of the most critical infrastructures is power system which is an attractive target to terrorists. The experience of terrorist attacks shows the crippling effects of such attacks which could lead to public discontent. Vulnerability evaluation and identification the weak points of power system due to such threats are necessary in order to make appropriate decisions to defend against them. The aim of this article is to review common methods of vulnerability evaluation and present a new index for vulnerability evaluation of power system based on combination of expected energy not supplied index and other indices. The simulation results show using the new index leads to favorable outputs for determining the vulnerability of power system.