Wael MohamedBenha University · Department of Electrical Engineering (Benha)
Wael Mohamed
bu.edu.eg/staff/waelahmed5
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26
Publications
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147
Citations
Introduction
Additional affiliations
June 1999 - present
Publications
Publications (26)
In wireless sensor networks, it is crucial to support the collected data of sensor nodes with position information. One of the promising ways to acquire the position of unknown nodes is using a mobile anchor node that traverses throughout the network, stops at determined points, and sends its position to aid in obtaining the location of other unkno...
The continuous growth of smart communities and ever-increasing demand of sending or storing videos, have led to consumption of huge amount of data. The video compression techniques are solving this emerging challenge. However, H.264 standard can be considered most notable, and it has proven to meet problematic requirements. The authors present (BPM...
Due to the gigantic power quality (PQ) demands for modern systems, power systems fault detection and diagnosis have become a significant issue. For this aim, it's very important to detect the fault at early time and determine its location through any signal. Several methods and techniques are applied to solve this problem such as discrete wavelet t...
This study presents a new technique for fast detecting and diagnosing of power grids faults. Discrete Wavelet transform (DWT) has a major disadvantage of noise sensitivity. The proposed technique solves the problems of DWT, where a high-precision classification of noisy and faulty signals could be obtained. Fusion between voltage and power readings...
In the last few years, a great attention was paid to the deep learning Techniques used for image analysis because of their ability to use machine learning techniques to transform input data into high level presentation. For the sake of accurate diagnosis, the medical field has a steadily growing interest in such technology especially in the diagnos...
Due to the development in the digital image
processing, its wide use in many applications such as medical,
security, and others, the need for more accurate techniques that
are reliable, fast and robust is vehemently demanded. Face
recognition technology is very important for the security that
provides intelligence services. Recently, a new trend ha...
In recent years, the use of Convolution Neural Network (CNN) with a huge amount of images in databases, has made
the deep learning technique very beneficial. Our objective is to improve the Face Recognition system using Deep Neural Network
because of the importance of this system in many applications such as security systems, mobile authentication,...
The video compression techniques began to impose themselves on the ground in recent years, as it can provide sending the vide os using less transmission bandwidth or stored in less storage space. One of these innovative compression techniques is the H.264 standard which has huge significance in terms of technology. Thus attracted our interest as re...
Nowadays, there are millions of people around the world suffer from the disability caused by big stroke. In recent years we have seen a rising interest in brain computer interface (BCI) systems that help those patients to practice their normal lives. Therefore, this work presents a GUI application based on an offline BCI system to test their mental...
Classification of EEG signals is one of the biggest problems in Brain Computer Interface (BCI) systems. This paper presents a BCI system based on using the EEG signals associated with five mental tasks (baseline, math, mental letter composing, geometric figure rotation and visual counting). EEG data for these five cognitive tasks from one subject w...
DC photovoltaic pumping system is presented in this paper. Solar DC pump needs less solar panels to run than the AC pump. The system is divided into three parts; photovoltaic (PV) array, boost converter and permanent magnet (PM) dc motor-pump set. Solar cells have nonlinear I-V characteristics, efficiency of PV module is low and output power depend...
The maximum power point tracking (MPPT) technique in the photovoltaic (PV) system is used to achieve maximum power from the solar PV system. In this context, three MPPT techniques, artificial neural network (ANN), fuzzy logic control (FLC) and adaptive neuro-fuzzy inference system (ANFIS), are implemented and their performance is investigated in te...
The maximum power point tracking (MPPT) technique in the photovoltaic (PV) system is used to achieve maximum power from the solar PV system. In this context, three MPPT techniques, artificial neural network (ANN), fuzzy logic control (FLC) and adaptive neuro-fuzzy inference system (ANFIS), are implemented and their performance is investigated in te...
This paper presents a comparison between the performance of Kalman filter and particle filter in the single object tracking system. The performance parameters of interest are the processing time of the algorithm and the accuracy of the tracking system. The algorithms are implemented using MATLAB and tested using two video sequences, and the results...
Nowadays, it has been a developing consideration towards utilization of photovoltaic (PV) system. This paper proposes an intelligent control method using Adaptive Neuro-Fuzzy Inference System (ANFIS) and an integrated offline Genetic Algorithm (GA) for maximum power point tracking (MPPT). The method is verified under different irradiance and temper...
This paper provides a new technique of multi-sensor data fusion to achieve an optimal spatial design and power operation of integrated Renewable Energy Grids (REG). This new approach depends on making a sensor data fusion system depending on the spatial concepts for measuring the important climate parameters, which have a great effect on the perfor...
Iris recognition is one of the most reliable biometric
technologies. In order to improve the accuracy of iris recognition
systems, and according to the variations in iris data, due to
noises of the eyelids and eyelashes or inappropriate image
acquisition environment, multiple iris images per person are
enrolled. Therefore, these systems suffer from...
A new methodology for computer aided diagnosis in digital mammography using unsupervised classification and class-dependent feature selection is presented. This technique considers unlabeled data and provides unsupervised classes that give a better insight into classes and their interrelationships, thus improving the overall effectiveness of the di...
This paper presents a computer-aided diagnosis (CAD) system based on combined support vector machine (SVM) and linear discriminant analysis (LDA) classifier for detection and classification breast cancer in digital mammograms. The proposed system has been implemented in four stages: (a) Region of interest (ROI) selection of 32Ã32 pixels size which...
Clusters of microcalcifications in mammograms are an important early sign of breast cancer in women. Comparing with microcalcifications, the breast background tissues have high local self-similarity, which is the basic property of fractal objects. A fast fractal modeling method of mammograms for detecting the presence of microcalcifications is prop...
In this paper an approach is proposed to develop a computer-aided diagnosis (CAD) system that can be very helpful for radiologist in diagnosing microcalcifications' patterns in digitized mammograms earlier and faster than typical screening programs and showed the efficiency of feature selection on the CAD system. The proposed method has been implem...
Mammogram - breast X-ray imaging - is considered the most effective, low cost, and reliable method in early detection of breast cancer. Clustered microcalcifications are an important early sign of breast cancer. In this paper, we are introducing, as an aid to radiologists, a computer-aided diagnosis (CAD) system, which could be helpful in detecting...
The high incidence of breast cancer in women has increased significantly in the recent years. Mammogram -breast x-ray imaging -is considered the most effective, low cost, and reliable method in early detection of breast cancer. Although general rules for the differentiation between benign and malignant breast lesion exist, only 15 to 30% of masses...