This paper reports a.c., d.c. conductivity and dielectric behavior of Ep-hybrid composite with12 Vol.% Kevlar-Carbon hybrid . D.C. conductivity measurements are conducted on the graded composites by using an electrometer over the temperature range from (293-413) K. It was shown then that conductivity increases by increasing number of Kevlar –Carbon fiber layers (Ep1, Ep2, Ep3), due to the high electrical conductivity of Carbon fiber. To identify the mechanism governing the conduction, the activation energies at low temperature region (LTR) and at high temperature region (HTR) have been calculated. The activation energy values for hybrid composite decrease with increasing number of fiber layers. The a.c. conductivity was measured over fr

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

The standard formulation of Wave Intensity Analysis (WIA) assumes that the flow velocity (U) in the conduit is <;<; the velocity of propagation of waves (c) in the system, and Mach number, M=U/c, is negligible. However, in the large conduit arteries, U is relatively high due to ventricular contraction and c is relatively low due to the large compliance; thus M is > 0, and may not be ignored. Therefore, the aim of this study is to identify experimentally the relationship between M and the reflection coefficient in vitro. Combinations of flexible tubes, of 2 m in length with isotropic and uniform circular cross sectional area along their longitudinal axes, were used to present mother and daughter tubes to produce a range of reflection coeffic

: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o

    The search included a comparison between two etchands for etch CR-39 nuclear track detector, by the calculation of bulk etch rate (Vb) which is one of the track etching parameters, by two measuring methods (thichness and change mass). The first type, is the solution prepared  from solving NaOH in Ethanol (NaOH/Ethanol) by varied normalities  under temperature(55ËšC)and etching time (30 min) then comparated with the second type the solution prepared from solving NaOH in water (NaOH/Water) by varied normalities with (70ËšC) and etching time (60 min) . All detectors were irradiated with (5.48 Mev) α-Particles from an 241Am source in during (10 min). The results that Vb would increase with the increase of

Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

      In many areas, such as simulation, numerical analysis, computer programming, decision-making, entertainment, and coding, a random number input is required. The pseudo-random number uses its seed value. In this paper, a hybrid method for pseudo number generation is proposed using Linear Feedback Shift Registers (LFSR) and Linear Congruential Generator (LCG). The hybrid method for generating keys is proposed by merging technologies. In each method, a new large in key-space group of numbers were generated separately. Also, a higher level of secrecy is gained such that the internal numbers generated from LFSR are combined with LCG (The adoption of roots in non-linear iteration loops). LCG and LFSR are linear structures and outputs

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In