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Tehrān, Iran

Momen A.R.,ICT Research Institute | Azmi P.,Tarbiat Modares University | Bazazan F.,Iran Telecommunication Research Center | Hassani A.S.,Iran Telecommunication Research Center
IET Intelligent Transport Systems | Year: 2011

Providing proper coverage is one of the main applications of wireless sensor networks. In many working environments, it is necessary to take advantage of mobile sensor networks (MSNs), with the capability of having cooperation between sensor nodes and moving into appropriate positions, to provide the required coverage. However, in some applications such as intelligent transport system (ITS), where sensors are applied in complex dense urban environments, traditional MSN cannot properly cover the defined area. In this study, the authors study the use of a few unreserved selected cars as a vehicular sensor network (VSN) to cover a defined area and in this scenario, the sensors movements are assumed to be random from the network viewpoint. In the proposed random structure VSN, the coverage property is managed and controlled by introducing a suggested method for resource allocation and coverage control based on the real vehicle mobility model. Major advantages of this VSN are considering the real car mobility model, compatibility with the deployed infrastructure and processing simplicity and efficiency. The implementation results of suggested method verify the analytical results that are mentioned in the simulation section. © 2011 The Institution of Engineering and Technology. Source

Moin M.-S.,ICT Research Institute | Sepas-Moghaddam A.,Islamic Azad University at Qazvin
Signal, Image and Video Processing | Year: 2013

JPEG compression standard is widely used for reducing the volume of images that are stored or transmitted via networks. In biometrics datasets, facial images are usually stored in JPEG compressed format and should be fully decompressed to be used in a face recognition system. Recently, in order to reduce the computational complexity of JPEG decompression step, face recognition in compressed domain is considered as an emerging topic in face recognition systems. In this paper, a novel coefficient selection method based on face segmentation has been proposed for selecting a limited number of zigzag scanned quantized coefficients in JPEG compressed domain, which led to an improvement in recognition accuracy and a reduction in computational complexity of the face recognition system. In the proposed method, different low frequency coefficients based on the importance of the regions of a face have been selected for recognition process. The experiments were conducted on FERET and FEI face databases, and PCA and ICA methods have been utilized to extract the features of the selected coefficients. Different criteria including recognition accuracy and time complexity metrics were employed in order to evaluate the performance of the proposed method, and the results have been compared with those of the state-of-the art methods. The results show the superiority of the proposed approach, in terms of recognition ranks, discriminatory power and time complexity aspects. © 2013, Springer-Verlag London. Source

Nazari S.,Islamic Azad University at Qazvin | Eftekhari-Moghadam A.-M.,Islamic Azad University at Qazvin | Moin M.-S.,ICT Research Institute
Security and Communication Networks | Year: 2015

Steganography is the art and science of hiding a message in a carrier, in such a manner that no one, except the sender and intended recipient, can guess the existence of the message it is a form of security through obscurity. Often, steganography algorithms using discrete cosine transform are detectable through steganalysis attacks. To reduce detectability of the stego, we propose an image steganography algorithm in transform domain based on morphological associative memory, permutation approach, and matrix encoding. In our proposed algorithm, in order to insert a secret message in the cover image, first, we map the cover image to a morphological representation containing morphological coefficients, and then bits of secret message are inserted into the image by permutation approach and matrix encoding. Permutation approach leads to unique distribution of secret message in the carrier, and the use of matrix encoding minimizes the number of coefficients needed to be changed because of inserting secret message. In our experiments, we compared the quality of stego, time complexity, and robustness of our method with state-of-art image steganography algorithms (F5 and morphological steganography) with an equal payload. The experimental results showed that the proposed method is able to produce insignificant visual distortion compared with other traditional approaches. To test the robustness of our proposed algorithm, we used wavelet-based and block-based steganalysis methods. The obtained results showed a high level of robustness of our algorithm against steganalysis attacks. © 2014 John Wiley & Sons, Ltd. Source

Zarei M.,Islamic Azad University at Tehran | Rahmani A.M.,Islamic Azad University at Tehran | Samimi H.,ICT Research Institute
Wireless Networks | Year: 2016

Speed variation is one of the main challenges in deriving the connectivity related predictions in mobile ad-hoc networks, especially in vehicular ad hoc networks (VANETs). In such a dynamic network, a piece of information can be rapidly propagated through dedicated short-range communication, or can be carried by vehicles when multihop connectivity is unavailable. This paper proposes a novel analytical model that carefully computes the connectivity distance for a single direction of a free-flow highway. The proposed model adopts a time-varying vehicular speed assumption and mathematically models the mobility of vehicles inside connectivity. According to the dynamic movability scenario, a novel and accurate closed form formula is proposed for probability density function of connectivity. Moreover, using vehicular spatial distribution, joint Poisson distribution of vehicles in a multilane highway and tail probability of the expected number of vehicles inside single lane in a multilane highway are mathematically investigated. The accuracy of analytical results is verified by simulation. The concluded results provide helpful insights towards designing new applications and improving performance of existing applications on VANETs. © 2016 Springer Science+Business Media New York Source

Hasanzadeh M.,Amirkabir University of Technology | Hasanzadeh M.,ICT Research Institute | Sadeghi S.,Payame Noor University | Rezvanian A.,Amirkabir University of Technology | And 2 more authors.
Journal of Experimental and Theoretical Artificial Intelligence | Year: 2016

The group search optimiser (GSO) algorithm is a newly found evolutionary algorithm that is inspired by animal-searching behaviour and group living theory. The GSO algorithm follows the producer-scrounger framework that consists of producer, scrounger and ranger members. There are multiple key parameters in the GSO algorithm that directly affect the performance of the algorithm. Among these parameters, the maximum pursuit distance parameter plays an important role because it determines the step length of the producer and rangers of the GSO algorithm. In this paper, we develop a modified GSO algorithm by using the success rate model to adjust the maximum pursuit distance parameter of the algorithm. We test the proposed algorithm on a rich set of benchmark functions including 30-and 300-dimensional problems and compare the results with popular evolutionary and swarm algorithms. The experimental results demonstrate that the scanning mechanism of the proposed algorithm quickly optimises not only the 30-dimensional problems but also the high-dimensional (300D) problems. © 2014 Taylor and Francis. Source

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