Ashraf A. M. Khalaf

1 V supply second generation current conveyor in standard CMOS technology for low voltage low power analog circuits applications

Second generation current conveyor (CCII) in standard CMOS technology for low voltage, low power analog circuits applications are presented. The main features of the proposed CMOS CCII are, it can operate at low voltage supply (1V), consume low power (383 muW), low input resistance at X-terminal (Rx = 6.9ohm), at low biasing current (16muA), low offset voltage (1.3mV), wide band width (F-3dB = 82MHz), and is very simple in its structure. As applications for proposed CCII, a four quadrant analog multiplier was built. PSPICE is used to verify the performance of the circuits

Design and implementation of a computer-aided diagnosis system for brain tumor classification

Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.

Classification of Brain Tumor MRIs Using a Kernel Support Vector Machine

The use of medical images has been continuously increasing, which makes manual investigations of every image a difficult task. This study focuses on classifying brain magnetic resonance images (MRIs) as normal, where a brain tumor is absent, or as abnormal, where a brain tumor is present. A hybrid intelligent system for automatic brain tumor detection and MRI classification is proposed. This system assists radiologists in interpreting the MRIs, improves the brain tumor diagnostic accuracy, and directs the focus toward the abnormal images only. The proposed computer-aided diagnosis (CAD) system consists of five steps: MRI preprocessing to remove the background noise, image segmentation by combining Otsu binarization and K-means clustering, feature extraction using the discrete wavelet transform (DWT) approach, and dimensionality reduction of the features by applying the principal component analysis (PCA) method. The major features were submitted to a kernel support vector machine (KSVM) for performing the MRI classification. The performance evaluation of the proposed system measured a maximum classification accuracy of 100 % using an available MRIs database. The processing time for all processes was recorded as 1.23 seconds. The obtained results have demonstrated the superiority of the proposed system.

Different adaptive beamforming algorithms for performance investigation of smart antenna system

Smart antenna systems are of great importance in wireless communication and radar applications. They effectively enhance the system capacity and reduce the co-channel interference. Smart antenna is an array antenna that uses adaptive beamforming algorithms to steer the main beam toward the desired signal direction and reject the interfering signals of the same frequency from other directions without moving the antenna. This is achieved by continuously updating the weights of each radiating element (antenna). An algorithm with low complexity, low computation costs, high speed convergence rates and better performance is usually preferred. This paper introduces a new performance investigation and comparison between five different beamforming algorithms: Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Sample Matrix Inversion (SMI), Recursive Least Square (RLS) and Hybrid Least Mean Square / Sample Matrix Inversion (LMS/SMI). In this investigation, the number of array elements and the displacement among them are changed in each algorithm. Simulation experiments are carried out, and the results are compared to verify the effectiveness of this investigation. The performance of each algorithm is optimized and demonstrated using MATLAB software package.

Differential voltage current conveyor and fully differential current conveyor in standard CMOS technology for low voltage analog circuits applications

A CMOS differential voltage second generation current conveyor (DVCCII), and fully differential current conveyor (FDCCII) are presented. They have advantages of a wide bandwidth, low input impedance at X-terminal, low offset voltage at X-terminal and low voltage operation. They are useful building blocks for analog circuits, especially for applications demanding differential input. They can be directly used with MOS transistors operating in ohmic region to implement require analogue functions. PSPICE simulations indicate the very good performance of the proposed DVCCII and FDCCII.

Investigation of different ethernet wiring and different frame size to enhance the performance of LAN

A computer network that covers only a small area networks abbreviated Local Area Network LAN, is used in campus computer networks, buildings, offices, in homes, schools or smaller. Currently, most LANs based on the IEEE 802.3 Ethernet technology using devices such as hubs and switches, which have a data transfer speed of 10, 100, or 1000 Mega bit /s (Mbps). In this paper, we are investigating the different Ethernet wiring standard and different frame size.

Performance of smart antenna system under different SNR

Many significant sources of error take place in the smart antenna system like mismatching between the supposed steering vectors and the real vectors, insufficient calibration of array antenna, etc. These errors correspond to adding spatially white noise to each element of the array antenna, therefore the performance of the smart antenna falls and the desired output signal is destroyed. This paper presents a performance study of a smart antenna system at different noise levels using five adaptive beamforming algorithms and compares between them. The investigated algorithms are Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Sample Matrix Inversion (SMI), Recursive Least Square (RLS) and Hybrid Least Mean Square / Sample Matrix Inversion (LMS/SMI). MATLAB simulation results are illustrated to investigate the performance of these algorithms.

Effects of ZigBee component failure on the WSN performance with different topologies

The IEEE 802.15.4 and ZigBee protocol stack offers a practical application solution for low cost, low data rate, and low energy consumption characteristics for Wireless Sensor Networks (WSN). In this paper, there are two scenarios studied. First, the three possible topologies (Star, Cluster tree and Mesh) are compared with each other at the case of various nodes failure as ZC, ZR and ZED to certify the reliability of this networks. There is just one ZigBee coordinator in each topology. The comparison includes the statistics: Data Traffic Sent, Data Traffic Received, Throughput and Delay. These statistics are performed taking into account the specific features and recommendations of the IEEE 802.15.4/ZigBee standard. Second, the Cluster Tree Topology with a single ZC is chosen and compared with a similar network that has an additional ZC. The network will two ZCs forms two PANs. The comparison includes the statistics: Data Traffic Received, Data Traffic Sent, Throughput and Delay. The simulations will be performed using Riverbed Modeler Academic Edition 17.5 Simulation.

Raman Amplifier Performance under New Wavelength Ranges

Abstract Due to the benefits of Raman amplifier (RA) for long-haul Ultra Wideband (UW)-WDM optical communications systems, we are studying and investigating how to widen the bandwidth and flatten the gain of RA by testing it in a new wider range of wavelengths (1.4 μm≤λsignal≤1.7 μm) instead of the benchmark range (1.45 μm≤λsignal≤1.65 μm). Four different ranges of signal wavelengths are used in this paper with the aim of testing the performance of RA model proposed in [13–15]: 1. 1.4 μm≤λsignal≤1.45 μm 2. 1.45 μm≤λsignal≤1.65 μm 3. 1.65 μm≤λsignal≤1.75 μm 4. 1.43 μm≤λsignal≤1.7 μm Different model sizes are used and analyzed to get wider bandwidth and more flat gain.

Proposed triple hill cipher algorithm for increasing the security level of encrypted binary data and its implementation using FPGA

Nowadays security becomes an important feature with the growth of electronic communication systems. In this paper, we study the security problem and present a proposed triple hill cipher algorithm and its implementation on FPGA to encrypt any binary data such as images, audio, video... etc. This proposed algorithm uses three stages of a modified hill cipher to make the algorithm more robust, each stage is considered a block cipher with a block length of 128 bits and key length of 256 bits. The message to be encrypted is processed by this block cipher in three stages to increase the security. The keys are taken from random number generator. The proposed algorithm is promising to give better security.