A segmentation approach for file broadcast scheduling

We study the broadcast scheduling problem in which clients send their requests to a server in order to receive some files available on the server. The server may be scheduled in a way that several requests are satisfied in one broadcast. When files are transmitted over computer networks, broadcasting the files by fragmenting them provides flexibility in broadcast scheduling that allows the optimization of per user response time. The broadcast scheduling algorithm, then, is in charge of determining the number of segments of each file and their order of transmission in each round of transmission. In this paper, we obtain a closed form approximation formula which approximates the optimal number of segments for each file, aiming at minimizing the total response time of requests. The obtained formula is a function of different parameters including those of underlying network as well as those of requests arrived at the server. Based on the obtained approximation formula we propose an algorithm for file broadcast scheduling which leads to total response time which closely conforms to the optimum one. We use extensive simulation and numerical study in order to evaluate the proposed algorithm which reveals high accuracy of obtained analytical approximation. We also investigate the impact of various headers that different network protocols add to each file segment. Our segmentation approach is examined for scenarios with different file sizes at the range of 100 KB to 1 GB. Our results show that for this range of file sizes the segmentation approach shows on average 13% tolerance from that of optimum in terms of total response time and the accuracy of the proposed approach is growing by increasing file size. Besides, using proposed segmentation in this work leads to a high Goodput of the scheduling algorithm.     

A model validation approach to texture recognition and inpainting

A new approach to texture recognition and inpainting problems is proposed. The approach is based on the robust model validation and state estimation techniques. The proposed solutions require the modeling of textures by using uncertain dynamical systems. We propose a new modeling method which is efficient in terms of computational and memory requirements. The main aspects of the modeling method include system identification and order reduction of marginally stable uncertain discrete-time systems. To demonstrate the results, both static-image textures and video textures (also known as dynamic textures) are considered.     

Two-stage Fabry-Perot filters as demultiplexers in optical FDMALANs

A high-finesse optical filter can be constructed by cascading two moderate-finesse Fabry-Perot filters of different free spectral ranges. Methods for controlling the undesirable interactions within the interfilter cavity are studied. In particular, the use of an isolator, an attenuator, or a length of fiber longer than the coherence length of the light sources used is considered. The use of a three-mirror filter, which avoids the offending cavity altogether, is also considered. The implications on the number of potential users of optical frequency-division multiple-access (FDMA), local-area networks (LANs) are also addressed     

MATRIX AND CEMENT EFFECTS ON RESIDUAL OIL SATURATION IN SANDSTONE FORMATIONS: A NEURAL NETWORK APPROACH

Abstract

Residual oil in sandstone is affected by mineral composition, clay matrix and cementing material. Matrix minerals affect the affinity of a fluid to spread on a rock surface significantly and in turn controls the fluid distribution within the pore spaces. At the interface between the rock surface and the contacting fluid, electrical charges are in the origin of the extent of phase wetness. Available framework grains, a dominant component of rock matrix, affect porosity and, hence, amounts of rock preferential wetness. Cement, clay matrix and quartz overgrowth, which make up for the rest of the grain population in a rock, influence wetness and, therefore, amounts of residual oil. In this paper, spectro-electromicroscopy (SEM) point-count technique in conjunction with neural network analysis were used to determine the effect of certains rock parameters on the amounts of residual oil following waterflooding operations. Using artifcial neural network, the intent was then to predict the extent of residual oil in sandstone rocks given limited information about rock matrix, cementing material and primary porosity.     

Compressive sensing based high-resolution passive bistatic radar

Passive bistatic radar (PBR) systems using different communication signals can only offer low-resolution target detection due to their inherent low bandwidth. In this paper, compressive sensing (CS) is applied to multichannel FM and GSM PBR to achieve improved range-Doppler resolutions and avoid some limitations of classical multiband PBR processing. In CS context, block-structured time-domain dictionary which is formed from multichannel signals suffers from coherence when fine range resolution is employed. To overcome such a pitfall, this work first transforms the dictionary to spectral domain where only the most important spectral components are retained. Principle component analysis followed by a whitening method are then applied to this spectrally transformed data in order to reduce the dimensionality of problem, thereby reducing the dictionary size and most importantly fulfilling the required condition of dictionary incoherence for better CS-based recovery. Two different block-structured dictionary formations are tested. The performance of the recovery of spatially close targets, in both FM and GSM PBR setups, are reported.     

Hybrid features of spatial domain and frequency domain for person identification through ear biometrics

Biometrics proved to be very efficient, more natural and easier for users than traditional methods of human identification. This paper presents an accurate biometric system based on human ear. Many features have been extracted in the spatial domain such as area of the ear, ear edge points, and widths of ear in different places. Those features have been extracted in the enrollment stages and stored as templates. Using a comparing technique such as Euclidean distance for each feature or for the whole features gives different correct recognition rates, which reaches 88.2%. Using spatial domain features as well as frequency domain features such as FFT and DCT coefficients raises our recognition rate to 92% of success. 100% of correct recognition can be achieved by using the average values of five samples instead of three samples for each person. The article is published in the original. Farid Saleh. Graduated from Telecommunications and Electronics Department, Faculty of Engineering of Helwan University, Egypt in 2001. He is presently a M.Sc. student at the same university. His current research interests include image processing and pattern recognition. Alaa Hamdy. Was born in Giza in Egypt, on August 17, 1966. He graduated from the Telecommunications and Electronics Department, Faculty of Engineering and Technology of Helwan University, Cairo, Egypt in 1989. He received the M.Sc. degree in computer engineering from the same university in 1996 and the Ph.D. degree from the Faculty of Electrical Engineering, Poznan University of Technology, Poland in 2004. Currently he is working as a lecturer in the Faculty of Engineering of Helwan University. His special fields of interest include image processing, pattern analysis, and machine vision. Fathy Zaki. Is an associate professor of Microelectronics, Electronics Department, Faculty of Engineering of Helwan University.     

Notes on integral performance indices in fractional-order control systems

Integral performance indices as quantitative measures of the performance of a system are commonly used to evaluate the performance of designed control systems. In this paper, it is pointed out that due to existence of non-exponential modes in the step response of a fractional-order control system having zero steady state error, integral performance indices of such a system may be infinite. According to this point, some simple conditions are derived to guarantee the finiteness of different integral performance indices in a class of fractional-order control systems. Finally, some numerical examples are presented to show the applicability of the analytical achievements of the paper.     

Optical equalization to combat the effects of laser chirp and fiberdispersion

Optical equalizers capable of combating the effects of laser chirp and fiber chromatic dispersion on high-speed long-haul fiber-optic communication links at 1.5 μm are described. They consist of both reflective and transmissive cavity structures. The equalizers are adaptive in the sense that the position of their periodic frequency responses are optimally adjusted in real time. The equalizers are evaluated by using computer simulation routines based on the rate equations for intensity-modulated lasers. It is shown that, by using equalizers of the type proposed, the receiver data eyes remain open well beyond where they would close without equalization     

Optical equalization for high-bit-rate fiber-optic communications

An optical equalizer consisting of a reflective cavity structure, which gives an all-pass amplitude response and a frequency-selective delay response, is described. Equalizer performance is evaluated for links using external modulation with chirp absent. It is also shown that, by using equalizers of the type described, the receiver data eye can remain open for distances more than twice those where the unequalized system becomes inoperable     

On the Computational Cutoff Rate, R0for the Peak-Power-Limited Gaussian Channel

The "computational cutoff rate," R0, represents a practical measure of the maximum reliable data rate that can be achieved by coding over a given communication channel using a given modulation format, in contrast with the "channel capacity,"C, which represents an idealized theoretical limit on the achievable data rate. Moreover, designing signal sets with good error probabilities using the R0criterion results in a mathematical problem that is much more tractable than that obtained by using the probability of error itself as a criterion. Both of the above reasons establish the importance of R0in communications theory. This paper starts with a brief tutorial background, which reveals the origin and the significance of R0. Next, the problem of achieving R0over the additive white Gaussian noise (AWGN) dispersive or nondispersive channel, using quadrature-amplitude modulation (QAM) with a peakpower constraint, is addressed. The major result is that, for both cases, the optimum transmission signal set is chosen from a discrete distribution. The solution is derived in detail for the peak-power-limited nondispersive channel, where it is shown that the optimum QAM symbols are selected independently from a probability distribution that is uniform in the phase and discrete in the radius. The solution for the corresponding peak-power-limited dispersive channel is obtained only asymptotically, for large signal-to-noise ratio (SNR), where it is shown that the QAM symbols are selected independently from a uniform distribution within a disk in the complex signal space.