In this work we present a detailed study on anisotype nGe-pSi heterojunction (HJ) used as photodetector in the wavelength range (500-1100 nm). I-V characteristics in the dark and under illumination, C-V characteristics, minority carriers lifetime (MCLT), spectral responsivity, field of view, and linearity were investigated at 300K. The results showed that the detector has maximum spectral responsivity at λ=950 nm. The photo-induced open circuit voltage decay results revealed that the MCLT of HJ was around 14.4 μs

 Neuroimaging is a description, whether in two-dimensions (2D) or three-dimensions (3D), of the structure and functions of the brain. Neuroimaging provides a valuable diagnostic tool, in which a limited approach is used to create images of the focal sensory system by medicine professionals. For the clinical diagnosis of patients with Alzheimer's Disease (AD) or Mild Cognitive Impairs (MCI), the accurate identification of patients from normal control persons (NCs) is critical. Recently, numerous researches have been undertaken on the identification of AD based on neuroimaging data, including images with radiographs and algorithms for master learning. In the previous decade, these techniques were also used slowly to differentiate AD a

In the present work, an image compression method have been modified by combining The Absolute Moment Block Truncation Coding algorithm (AMBTC) with a VQ-based image coding. At the beginning, the AMBTC algorithm based on Weber's law condition have been used to distinguish low and high detail blocks in the original image. The coder will transmit only mean of low detailed block (i.e. uniform blocks like background) on the channel instate of transmit the two reconstruction mean values and bit map for this block. While the high detail block is coded by the proposed fast encoding algorithm for vector quantized method based on the Triangular Inequality Theorem (TIE), then the coder will transmit the two reconstruction mean values (i.e. H&L)

Most tubes are made from butyl rubbers, but certain types, such as giant tubes, are based on natural rubber because very high green strength is required when handling the uncured compound. By using blends of natural rubber (NR) and brominated butyl rubber (BIIR), it is possible to maintain high green strength in the uncured compound and improve impermeability and heat resistance of the cured tube.  The best formulations are obtained in the presence of 50 phr of (BIIR) to achieve desired mechanical properties. Improved impermeability was obtained by using 50 and 75 phr of (BIIR) rubber in compounds. Blending of brominated butyl rubber (BIIR) with natural rubber (NR) enhances air retention with acceptable sacrifices in green strength.

In this paper, an adaptive polynomial compression technique is introduced of hard and soft thresholding of transformed residual image that efficiently exploited both the spatial and frequency domains, where the technique starts by applying the polynomial coding in the spatial domain and then followed by the frequency domain of discrete wavelet transform (DWT) that utilized to decompose the residual image of hard and soft thresholding base. The results showed the improvement of adaptive techniques compared to the traditional polynomial coding technique.

A principal problem of any internet user is the increasing number of spam, which became a great problem today. Therefore, spam filtering has become a research fo-cus that attracts the attention of several security researchers and practitioners. Spam filtering can be viewed as a two-class classification problem. To this end, this paper proposes a spam filtering approach based on Possibilistic c-Means (PCM) algorithm and weighted distance coined as (WFCM) that can efficiently distinguish between spam and legitimate email messages. The objective of the formulated fuzzy problem is to construct two fuzzy clusters: spam and email clusters. The weight assignment is set by information gain algorithm. Experimental results on spam based benchmark

        The secure data transmission over internet is achieved using Steganography. It is the art and science of concealing information in unremarkable cover media so as not to arouse an observer’s suspicion. In this paper the color cover image is divided into equally four parts, for each part select one channel from each part( Red, or Green, or  Blue), choosing one of these channel depending on the high color ratio in that part. The chosen part is decomposing into four parts {LL, HL, LH, HH} by using discrete wavelet transform. The hiding image is divided into four part n*n then apply DCT on each part. Finally the four DCT coefficient parts embedding in four high frequency sub-bands {HH} in

     Many cryptosystems and security techniques use substitution boxes to ensure the data’s secure communication. A new technique is presented for generating a robust S-box to fulfill security requirements. The AES algorithm represents a block cipher cryptographic algorithm. It was selected by the National Institute of Science and Technology as the optimal cryptographic algorithm in 2011. Through the study of the properties of original S-BOX, this algorithm has been subjected to a number of attacks (linear, differential, statistical, and interpolation), and original S-BOX has been static, which makes the attack strong and shows a weakness in the algorithm.  It is necessary to make this algorithm more efficient and powerful through

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or