Imbaby I. Mahmoud

Modeling and automatic control of nuclear reactors

This paper presents a developed real time simulator for MPR (multi purpose reactor), on which the Egyptian 2/sup nd/ research reactor is based. A VisSim S/W environment with real-time add-on is employed to achieve this put-pose. VisSim S/W supports a variety of standard and industrial grade I/O cards and uses the block diagram programming technique, which keeps use of specialized code to minimum. All necessary reactivity feedback is taken into consideration and modeled by sufficiently accurate equations. A control rod withdrawal algorithm, which represents the actual one of the MPR, is stated and modeled. Application of traditional control algorithms are implemented and discussed. Advanced control algorithms such as fuzzy, neural network, and genetic are investigated to substitute the moving control rod selection logic and core parameter prediction. The simulator can be distributed with VisSim viewer or through generated C code from VisSim block diagram. The results of the proposed simulator in the power state agree well with the published experimental and analytical results.

Performance improvement of quantum well infrared photodetectors through modeling

We study the performance of quantum well infrared photodetectors (QWIPs) in the case of infrared irradiation. This type of photodetector is interesting from the point of view that QWIPs have numerous advantages over photodetectors based on HgCdTe in terms of large array size, high uniformity, high yield, radiation hardness and lower cost of the systems. Therefore, it is important to evaluate their characteristics theoretically. We develop a simple modeling for this interesting type of photodetector. This model describes a nontrivial evaluation of the most important characteristics. The potential distribution of the developed model is obtained by self-consistently solving the Poisson equation. On the other hand, it is used to calculate the dark current, responsivity and detectivity as a function of the structural parameters. These parameters are the spacing between the wells, the number of quantum wells and the operating temperature. Also, the optimization of the characteristics of QWIPs is of primary concern. The effect of uniformity of the dopant density in the QWIP is studied theoretically. We find that the uniformity of the dopant distribution in the plane of QW decreases the dark current.

Statistical representation for iris anti-spoofing using wavelet-based feature extraction and selection algorithms

The development of fake iris detection systems, which is one of the most important topics in the biometric field, is growing rapidly. In this paper, discriminative statistical features are used for differing between real and fake iris images. The multilevel 2-D wavelet decomposition is employed to obtain approximation and detail wavelet channels. For feature classification, Euclidean distance and suitable fusion rules are applied. Problems with numerous features require the use of feature selection. Thus, to reduce the computational cost and enhance the system performance, an effective feature selection algorithm is proposed. CASIA-Iris-Syn database, which consists of about 10000 synthesized images, is used. Results show that the variance measure is efficient for detecting deceived attacks with 100% classification accuracy. The kurtosis measure gives 90.4648 %, which is the lowest accuracy obtained. Other feature selection algorithms are applied for a comparison purpose. Results prove the high explanatory capability of the prediction method. The proposed feature selection/classifier ensemble not only achieves dimensionality reduction, but also carefully investigates the dependence between the statistical features, and does not neglect features with complementary information. A poor choice of features may lead to significant deterioration in system performance. The proposed system has the advantage of working with large size database, and thus ensures the generalization ability of the proposed algorithms. Results also show that working with original non-segmented images not only reduces the processing time, but also enhances the classification accuracy, noticeably.

An accurate model of worst case signal to interference ratio for frequency reuse cellular systems

In cellular networks, fractional frequency reuse (FFR) is an efficient inter-cell interference (ICI) mitigation scheme. Although many related research papers are published in this area. Formulas to handle this scheme in more accurate manner are still required. In this paper, closed-form formulas for worst case signal to interference ratio (SIR) in frequency reuse three, four, soft frequency reuse (SFR), and sectored FFR are derived. Also, an accurate closed-form formulas for inner radius for all these cases are driven based on worst SIR case taking into account the interference effect only and the impact of interference combined with path loss effect. Analytical models are validated using Long Term Evolution (LTE) simulator. Simulation results show that the proposed analytical models are in good agreement with those obtained through simulations and they are more accurate than previously published analytical treatments as they consider the practical scenarios.

Development of coincidence summing and resolution enhancement algorithms for digital gamma ray spectroscopy

This paper discusses the correction of some of the main problems of digital gamma ray spectroscopy. These problems are the coincidence summing and energy resolution. The coincidence summing effects are evaluated using analytical techniques. Correction is made at different energies for both 137Cs and 60Co radioisotopes. A simple relation is derived between the coincidence summing correction factor and the energies under the conditions of the system configuration. This relation is deduced using the least square approximation method. Consequently, correction can be done at different energies of radiation sources under the constraints of the measured conditions. Furthermore, the coincidence summing algorithm is validated through comparison with published experimental results in the literature and good agreement is found. Coincidence summing correction factors are used to correct the values of the Full Energy Peak (FEP) efficiencies. Correction factors were calculated for predominant gamma emissions significantly affected by coincidence summing effects for both 137Cs and 60Co point sources. Also, a correction algorithm for the resolution–degradation in scintillation (NaI (TI)) gamma ray detectors using derivative methodology is presented. The derivative methodology is implemented by weighted sum of the original signal, the negative of its second derivative and the positive of its fourth derivative. We noticed that using both derivatives in combination improves the energy resolution, which is enhanced by 24.03%. From the obtained results, the FEP efficiency was enhanced by 1.58% due to coincidence summing correction. Consequently, accurate determination for the source activity can be achieved.

Pileup recovery algorithms for digital gamma ray spectroscopy

This paper presents algorithms for overcoming a common problem of gamma ray spectroscopy, namely the peak pileup recovery problem. Three different approaches are studied and evaluated within a spectroscopy system. The algorithms are evaluated by the means of parameters error and fitting error calculations. The first approach is a direct search based on Nelder-Mead technique without any derivatives in order to find the local minimum points. A Gaussian shape in conjunction with the peak height and its position of each pulse are used to construct the pulse. So, the main pulse parameters such as peak amplitude, position and width can be determined. The second algorithm is based on the nonlinear least square method. In this paper another technique is tried. This technique which is proposed as third algorithm is based on a maximum peak search method combined with the first derivative method to determine peak position of each pulse. Comparison among these approaches is conducted in terms of parameters errors. The pulse parameters have been calculated and compared with the actual one. The second approach shows the best accuracy, for determining peak height and position, but the width parameter scored the highest error.

Piecewise linear model for haze level estimation and an efficient image restoration technique

Abstract In this paper, a piecewise linear predication model that relates light extinction coefficient (bext) to log of image contrast/transmission is proposed. The objective is to calculate more accurate bext values compared with previous treatments which used linear model of contrast relationship only. A multivariate linear regression model is learned for each linear portion of the model. Results show superior behavior of the proposed model in terms of error calculated between estimated values and ground truth values. Moreover, an effective approach to dehaze and enhance outdoor images captured under adverse weather conditions is introduced. A raw transmission map is estimated using a dark channel prior, then guided image filtering is used in two stages; first for transmission map refinement, second for details enhancement. Guided filtering not only exhibits the edge-preserving smoothing, but also a structure transferring property. Details enhancement results in improved visibility with minimum information loss.

Effective visibility restoration and enhancement of air polluted images with high information fidelity

In this paper, an effective approach for dehazing and enhancing outdoor images is proposed. The dark channel prior is used to estimate a raw transmission map. This transmission map is then refined using guided image filtering under the guidance of the hazy image. For colors and details enhancement, the adaptive manifolds high-dimensional filtering is applied to the recovered scene radiance. The proposed approach is compared with other enhancement techniques and effective quality assessment methods are used for objective evaluation. The visual information fidelity (VIF) metric is used to quantify the loss of image information, since contrast overcompensation may cause information loss. The structural similarity index (SSIM) is used to quantify the degradation of structural information between the enhanced and recovered image. Other metrics including the ratio between the gradient of visible edges before and after enhancement are also computed. Experimental results show that combining guided image filtering for refining the raw transmission map, with adaptive manifolds filtering for image enhancement, produces images with improved colors, high contrast and minimum information loss.

Analysis of Downlink sectored Frequency Reuse cellular systems combined with different beamforming techniques

Although Fractional Frequency Reuse (FFR) is a good solution for Inter-Cell Interference (ICI) problem, combined FFR and beamforming can be utilized for more improved cellular system performance. In this paper, we consider a hexagonal cellular network, where we derive the Downlink (DL) worst case Signal to Interference Ratio (SIR) closed form formula for three different beamforming techniques (horizontal, vertical, and 3D) combined with sectored FFR. Furthermore, the derived SIRs formulas are used to get Spectral Efficiency (SE) as well as channel capacity in terms of several parameters. Also, we derive an accurate closed form formula for inner radius based on the proposed analytical model including a correction factor. Simulation results show that the proposed analytical method is in good agreement with those obtained through simulations and more accurate than previously published analytical treatments. The same treatment can be applied for other FFR techniques.

Comparison of Routing Protocols in Wireless Sensor Networks for Monitoring Applications

recent years, evaluation and development of the routing protocols in wireless sensor networks (WSNs) are very important and attractive research topic especially for monitoring applications. Because of, the difficulties of studying WSNs routing protocols in real implementation which takes a lot of time and it can be very expensive, using a suitable simulator become a common trend in such evaluation. This paper presents a systematic performance study of three routing protocols, Ad hoc On Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Optimized Link State Routing (OLSR) protocols for WSNs by proposing a simulation model that targeted to the sensor networks with mobile sensor nodes and single sink as it is often seen in many monitoring applications such as military, agriculture, medical, transport, industry, etc to monitor physical environments. The performance study of WSNs routing protocols is analyzed by comparing important metrics like the end-to-end delay, total packets dropped, load, routing overhead, route discovery time, and number of hops per route in the Network under the same random waypoint mobility model for the three protocols. These routing protocols are implemented and simulated using OPNET Modeler simulator. Theoretical analysis and simulation results show that both AODV and DSR protocols have identical on demand behavior but with performance differentials resulted from the differences in protocol mechanics. In addition to, they are suffering from higher end to end delay compared to the Optimized Link State Routing (OLSR) protocol. The results obtained may be useful for implementation of wireless sensor networks for many monitoring and control applications.