@article { author = {Monir, Mohamad and Nassar, M. and El-Fishawy, Adel and Zein El-Din, Mohamad and Dessouky, Moawad and El-Rabaie, El-sayed and El-Samie, Fathi}, title = {Study for Speaker Identification Under Reverberation Effect}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {1-7}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64932}, abstract = {Speech is the way people interact with each other. With the development of computer technology, some researchers have sought to find techniques that allow the computer to understand natural speech. Smart systems are now trying to imitate the functions of the human brain by using neural networks. Reverberation represents interference noise on the original speech signal. The aim of the research is investigate of reverberation effect on speech signal and whether it affects the identification of the speaker or not to determine the best scenario for identifying the speaker in the presence of reverberation. This study is done using feature extraction with Mel-Frequency Capstral coefficients (MFCCs) and neural networks.}, keywords = {speaker recognition system,Mel Frequency Cepstral Coefficients,Registration Mode,Identification Mode,reverberation,artificial neural network}, url = {https://mjeer.journals.ekb.eg/article_64932.html}, eprint = {} } @article { author = {Ghazi, A. and Zainud-Deen, Saber and Malhat, Hend}, title = {Beam-Switching High Gain CP Graphene ME-Dipole Antenna for 5G MIMO Communications}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {8-13}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64937}, abstract = {A wideband circularly polarized (CP) graphene-based magneto-electric (ME) antenna with reconfigurable radiation characteristics for 5G MIMO communications is presented in this paper. It consists of graphene patches deposited on silicon oxide substrate arranged horizontally and vertically to act as a ME-antenna. The reconfigurable conductivity of graphene is used to control the operating bandwidth of the antenna. The single element has an impedance matching bandwidth of 78.3 % with the circular polarized band of 61.2% for applying chemical potential, µc=2 eV. The effect of changing the graphene reconfigurable conductivity on the radiation characteristics of the ME-antenna is investigated. The operating bandwidth is controlled by proper biasing the graphene sheet. The peak gain and the antenna efficiency are increased with increasing the chemical potential value due to the increase in graphene conductivity. The mutual coupling between ME-antenna elements is investigated for linear and circular arrangement. Octagonal array consists of 8-similar elements are constructed to produce electronic beam switching in different directions. Single beam, dual-beams, and omni-directional beam is achieved by controlling the graphene conductivity of single, two, and all the ME-elements in the array. Three ring array are designed to switch the beam in different angles for highest coverage area.}, keywords = {Graphene,Beam switching,Magnetio-Electric antenna}, url = {https://mjeer.journals.ekb.eg/article_64937.html}, eprint = {} } @article { author = {Arafa, Nancy and Abd El-atty, Saied and Abou Elazm, Atef}, title = {Performance Analysis of Channel Capacity for Flow based-Diffusive Molecular Communication System}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {14-18}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64451}, abstract = {The main application of molecular communication (MC) technology is the medical field wherein the communication medium is the blood vessel. This medium is flow-based diffusion MC and the channel capacity plays an important role. Unlike previous literature, we present the performance analysis of the channel capacity for flow based-diffusive molecular communication system. The molecular diffusion process in the flow-based medium is represented by advection diffusion equation wherein the velocity of flow is considered while the receiver is based on the ligand-receptor mechanism. The performance evaluation of proposed channel capacity is evaluated in terms flow   medium velocity, receiver's sensing area and physical size. The numerical results reveal that the proposed approach is useful in the application of drug delivery system (DSS).}, keywords = {Molecular Communication,Nanomachine,Diffusion,Channel Capacity}, url = {https://mjeer.journals.ekb.eg/article_64451.html}, eprint = {} } @article { author = {El-Refaey, Amir and Shouman, Marwa and Hemdan, Ezz El-din and EL-Fishawy, Adel and Abd El-Samie, Fathi}, title = {Triple C: A New Algorithm for ECG Cancelable Biometric System}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {43-50}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67376}, abstract = {This paper investigates the possibility of biometric human identification based on the electrocardiogram (ECG) using a new algorithm called CCC or Triple C.  The ECG, being a record of electrical currents generated by the beating heart, is potentially a distinctively human characteristic, since ECG waveforms and other properties of the ECG depend on the anatomic features of the human heart and body. The experimental studies involved 46 volunteers. For usability, each signal was shifted and encrypted by Cepstrum algorithm, the output is convoluted with the original signal then stored as an authorized database. Any new signal is processed as mentioned before then compared with the stored authorized database. AROC metric value is used to measure the performance of the proposed technique. Comparing results with traditional techniques showed that the recognition rate is better than other techniques and reach 99%. The findings support using the ECG as a new biometric characteristic in various biometric access control applications.}, keywords = {eCG,Cancelable Biometrics,Cepstrum,Convolution,AROC}, url = {https://mjeer.journals.ekb.eg/article_67376.html}, eprint = {} } @article { author = {Nabil, Essam and zaki, Gomaa and Abdulaziz, Sally}, title = {Maximum Power Point Tracking of Photovoltaic System Using Perturb and Observe and Fuzzy Logic Controller Techniques}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {236-241}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64407}, abstract = {Nowadays, there is trending toward utilizing renewable resources of energy, due to the massive shortage in fossil fuels, in addition to the environmental pollution caused by burning such fuels which in turn releases carbon dioxide. Photovoltaic systems are regarded as one of the most significant renewable energy resources, so it is required to enhance the performance of such systems. The performance of photovoltaic system can be enhanced by utilizing Maximum Power Point Tracking (MPPT) techniques by continuously tracking the maximum power point under changeable atmospheric conditions, as the characteristics of the photovoltaic systems depend nonlinearly on both solar radiance and ambient temperature. In this paper two MPPT techniques, Perturb and Observe algorithm (P&O) and fuzzy logic controller (FLC), are used to control the photovoltaic systems to reach to the maximum power point. Using the MATLAB program A simulation of a 250-watt photovoltaic module is done to justify that the proposed FLC design accomplishes better performance than P&O technique under various atmospheric conditions.}, keywords = {Renewable energy sources,Photovoltaic systems,Maximum power point trackers,Fuzzy control,DC‐DC power converters}, url = {https://mjeer.journals.ekb.eg/article_64407.html}, eprint = {} } @article { author = {Amer, Shaymaa and El-Nagar, Ahmed and El-Bardini, Mohammad}, title = {PID-like Neural Network for Maximum Power Point Tracking of a Photovoltaic System}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {242-247}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64929}, abstract = {In this study, the PID–like neural network (PIDNN) controller is proposed for maximum power point tracking (MPPT) of the photovoltaic (PV) systems. The proposed neural network (NN) structure works as a nonlinear PID controller. The proposed controller combines the advantages of the PID controller such as easy to implement and the advantages of the NN. The parameters of the proposed PIDNN are learned and tuned on-line based on the gradient descent method. This scheme creates a nonlinear PID controller, which improves the system performance. The results show the robustness of the PIDNN under different levels of the environmental changes such as PV cell temperature and solar irradiance. The simulation results for the proposed PIDNN are compared with other schemes in order to show the robustness of the proposed structure.}, keywords = {Photovoltaic System,Maximum Power Point Tracking,PID controller,Neural Networks}, url = {https://mjeer.journals.ekb.eg/article_64929.html}, eprint = {} } @article { author = {Essa, Youssef and Al-Mahalawy, Ahmed and Attiya, Gamal and El-Sayed, Ayman}, title = {Feature Engineering For Readmission Prediction Model of Real-Time Patient Streaming Data}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {286-291}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64926}, abstract = {Providing healthcare services without emergency waiting is the one of important challenges for healthcare organizations. The poor patient readmission management increasing the emergency waiting and maybe cause a risk on the patient life. The current prediction models working on batching processing model, and not provides real time tracking of patient status. However, the patient profile growth every second by new records or new attributes and the accuracy of analysis is insufficient when the quality of health data is incomplete, old, or not clean. Indeed, all patient data need to analyze using big data technologies in real time to extract important features from the data. So, this paper tackles most problems that hinder extracting features for readmission prediction models in real time. The new model called High-Risk Readmission Prediction model (HR2P). This model based on machine learning and big data technology to be able streaming patient data from Internet of Things (IoT) and electronic health records (EHR) storage. The new approach allows healthcare organizations to minimize waiting time for patients and emergency cases.}, keywords = {Powerset,Distributed Systems,Hadoop,Spark,Big Data}, url = {https://mjeer.journals.ekb.eg/article_64926.html}, eprint = {} } @article { author = {Shoka, Athar and Dessouky, Mohamed and El-Sherbeny, Ahmed and El-Sayed, Ayman}, title = {Literature Review on EEG Preprocessing, Feature Extraction, and Classifications Techniques}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {292-299}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64927}, abstract = {Classification is one of the main applications of machine learning, which can group and classify the cases based on learning and development using the available data and experience knowledge. Classification is used widely in biological and medical aspects. This paper presents the problem of electroencephalogram (EEG) signal classification. Classification is the step of identifying groups or classes based on similarities between them. This step is essential to differentiate between seizure and normal periods. EEG is a monitoring tool to determine the electrical activity of the brain. The nature of EEG is quite long, so it consumes time and very difficult in processing. Epilepsy is an illness that affects people of all ages, both cases males and females. Epilepsy is a neurological disorder that makes the activities of the brain abnormal and generates seizures. Seizure symptoms vary from one people to another; it depends on the location of epileptic discharge in the cortex. To speed up the classification process and make it efficient, EEG signal needs to be preprocessed. This paper reviews the epilepsy mentality disorder and the types of seizure, preprocessing operations that performed on EEG data, a common extracted feature from the signal, and detailed view on classification techniques that can be used in this problem.}, keywords = {Epilepsy,EEG,preprocessing,features extraction,classification}, url = {https://mjeer.journals.ekb.eg/article_64927.html}, eprint = {} } @article { author = {Yassin, Yassin and Murtada, Wael and El Mahallawy, Ahmed}, title = {Fault Detection and Avoidance for Spacecraft Failure using PSO Algorithm}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {300-305}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64936}, abstract = {Fault detection algorithm design of satellite inflight control is important for most remote sensing satellites. The responsibility of a satellite attitude control system always keeps the satellite in a stable mode. A satellite control mode contains standby, imaging and detumbling modes. Before we start imaging, we used to prepare an attitude control system to change satellite angles according to payload camera planning schedule to shoot a specific area of interest. After imaging is complete, the attitude control changes satellite angles back to nadir (zero tilting angels). Some control problems may cause failures which put the satellite in a detumbling mode due to accumulated torque on reaction wheel of the satellite. Artificial intelligent design algorithm of particle swarm optimization (PSO) is proposed to control the satellite in real-time mode, which decreases the angular velocity received from the satellite. This approach calculates the difference between the real-time measurement and the designed angular velocity (∆θ) within the satellite communication session time. The Matlab customization function implements PSO controller. The mathematical model of satellite attitude control system has been designed according to the satellite dynamics and kinematics laws. The approached mathematical model is implemented using Simulink Matlab tools.}, keywords = {Fault diagnosis algorithm,particle swarm optimization (PSO),satellite control,and Euler’s moment equations}, url = {https://mjeer.journals.ekb.eg/article_64936.html}, eprint = {} } @article { author = {Abd El-Naby, Aya and Hemdan, Ezz El-din and EL-SAYED, Ayman}, title = {An Efficient Credit Card Fraud Detection Model}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {332-336}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67377}, abstract = {online transaction is the most popular mode of payment over the internet. Financial institutes such as banking organization provides various online services for customers such as e-commerce and e-cash. Credit card is one of the supreme conventional methods of online transaction. In recent times, criminal can use illegal ways to carry out fraud transaction by credit card over e-services. Due to the growing volume of electronic payments, the monetary strain of credit-card fraud is turning into a substantial challenge for financial institutions and service providers, thus forcing them to continuously improve their fraud detection systems. Therefore, there is a serious need to develop efficient credit card fraud detection for mortgage companies, financial institutes, credit card enterprises, and banking system.  One of the most common problems in with building credit card detection model is imbalanced data sets. The data set can be imbalanced when the examples of one class significantly outnumber the examples of the other one, i.e., classification becomes very tough as the result may get biased by the dominating class values. In this paper, we will apply two techniques to get rid of this problem for credit card data. Then, the imbalanced dataset used in developing an efficient credit card fraud detection model. In the proposed model, different machine learning algorithms are used such as K-Nearest Neighbor (KNN), Logistic Regression (REG), Latent Dirichlet Allocation (LDA), Classification And Regression Tree (CART), and Naïve Bayes (NB). The results show that LDA gives 99.9543 which is best accuracy results while CART algorithm gives 99.9797 which is the higher accuracy in case of up-sampling, and finally, in down-sampling, LDA gives 94.9238 which is the higher accuracy result.}, keywords = {}, url = {https://mjeer.journals.ekb.eg/article_67377.html}, eprint = {} } @article { author = {Emad El-Din, Aml and Hemdan, Ezz El-Din and El-Sayed, Ayman}, title = {Malicious Website Detection using Machine Learning on Apache Spark}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {337-342}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.64449}, abstract = {Malicious websites considered as critical threats to the users’ systems that access these websites as hackers use these websites to steal users’ personal information or account information or even harms the users’ systems. Many solutions have been developed to detect and prevent these malicious websites, but these solutions are not fully effective as these websites are changed continuously. This paper evaluates various classification algorithms to predict malicious and non- malicious web sites, based on various feature selection scenarios. Reasonable results are reached with 100% accuracy, recall, and precision when applying Logistic Regression and Decision Tree algorithms while 95% when applying Naïve Bayes algorithm with good timing.}, keywords = {}, url = {https://mjeer.journals.ekb.eg/article_64449.html}, eprint = {} } @article { author = {Moursi, Ahmed Samy Abd El Aziz and Shouman, Marwa and Hemdan, Ezz El-din and El-Fishawy, Nawal}, title = {PM2.5 Concentration Prediction for Air Pollution using Machine Learning Algorithms}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {349-354}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67375}, abstract = {Air pollution is a phenomenon harmful to both human being existence as well as the ecological system. It is caused by the excess of some substances above a particular concentration in the atmosphere. Atmospheric particulate matter (APM) – or PM for short – threatens life because of its tiny size – diameter is up to 10 micrometers. Their danger comes from their ability to penetrate deeper inside the human respiratory system. (PM2.5) particulates are less than 2.5 micrometers and are more hazardous when compared to (PM10) coarse particles–10 micrometers in size. Hence, environmental agencies and governments seek to explore new methods to predict future air pollution. These endeavors mainly focus on mitigating environmental pollution and predicting pollutants concentrations to take enough precautions for citizens protection.  This paper presents various machine learning algorithms that predict PM2.5 concentration for the next hour. These algorithms are Support Vector Regression (SVR), Long Short-Term Memory (LSTM), Random Forest, and Extra Trees. Their performance is measured in Root Mean Square Error (RMSE), coefficient of determination R2, and duration in seconds. Extra Trees shows the least RMSE and the highest coefficient of determination R2.}, keywords = {Air pollution forecast,Atmospheric particulate matter,PM2.5,Machine Learning,SVR,LSTM,Random Forest and Extra Trees}, url = {https://mjeer.journals.ekb.eg/article_67375.html}, eprint = {} } @article { author = {Ibrahim, Elhossiny and Shouman, Marwa and Torkey, Hanaa and Hendan, Ezz El-din and EL-SAYED, Ayman}, title = {Big Data Analytics for Diabetes Prediction on Apache Spark}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {355-360}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67374}, abstract = {Dangerous diseases like diabetes, in which blood glucose levels are too high, some machine learning models have been used to classify or predict the patient state. Currently, the collected dataset size increases dramatically. Therefore, big data analytics technology is an essential factor in building an efficient healthcare system that can fit for the future. This paper discusses the effect of using big data analytics with different dataset sizes by usinga  different number of processing cores over apache spark. The system has been evaluated using several performance evaluation metrics like accuracy, recall, precision, time, etc. A comparative study made among various algorithms such as Support Vector Machine (SVM), Naive Bayes (NB), Decision Tree (DT), and Random Forest (RF). The experimental result shows that the most accurate models were when using RF, and SVM, and the minimum time model was when using NB algorithm.}, keywords = {diabetes,Big Data Analytics,Machine Learning,Decision Tree,Random Forest,Naïve,SVM,and Apache Spark}, url = {https://mjeer.journals.ekb.eg/article_67374.html}, eprint = {} } @article { author = {Abshosha, Bassam and Dessouky, Mohamed and Ramdan, Rabie and EL-SAYED, Ayman}, title = {Design and Analysis of Substitution Boxes in GOST Lightweight Security Algorithm}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {361-368}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67378}, abstract = {Recently, lightweight symmetric cryptography became one of the most vital topics for researchers in cryptology. It is introduced as a smart solution to protect the data communication in constraint resources environments. S-boxes play a very vital role in the security of the modern block ciphers. They form the only non-linear element of a block cipher. ‎Therefore, S-boxes have to be chosen carefully to make the ‎cipher rigid against all kinds of attacks. Specially, the compact S-boxes that have been selected to be used in limited resources devices. ‎So, it is essential to understand some of the design criteria that the S-box must satisfy. In lightweight designs, 4-bit S-boxes are preferred to save the area (Gate Equivalents). In this paper, we in our primary analysis, we consider two versions of the GOST algorithm S-Boxes to be tested and evaluated. The Central Bank of the Russian ‎Federation Version and the Most Recent Version are ‎introduced. ‎GOST is one of the most famous modern symmetric ‎block ciphers. The paper looks into the design details of both GOST versions and considers different analysis criteria to their S-Boxes. Our design guarantees that the resulting S-boxes will be ‎bijective and nonlinear and will exhibit the strict avalanche ‎criterion and the output bit independence criterion. ‎In addition, the paper evaluates GOST high resistivity against both linear and differential cryptanalysis.}, keywords = {Lightweight Cryptography,S-boxes,Non linearity,SAC,BIC,Bijective,Linear and Differential Cryptanalysis}, url = {https://mjeer.journals.ekb.eg/article_67378.html}, eprint = {} } @article { author = {Aboshosha, Bassam and Dessouky, Mohamed and Ramadan, Rabie and EL-SAYED, Ayman}, title = {LCA- Lightweight Cryptographic Algorithm for IoT Constraint Resources}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {374-380}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67379}, abstract = {Recently, constraint resources devices applications are growing very fast. Such devices are connected together to serve ‎billions of users. A well-known example of these structures is ‎the Internet of Things (IoT). Saving energy is one of the most challenging aspects in IoT environments. IoT devices operate on unattended mode in hostile environments. Therefore, sensitive data communication should be protected using some sort of cryptography. Due to the limited computing power of wireless devices, it is impossible to apply one of the traditional advanced encryption algorithms for the data encryption. A ‎lightweight cryptographic algorithm is one of the most ‎suitable solutions to save information in such environments. Therefore, a novel light weight cryptography algorithm is proposed in this paper, called LCA.  LCA fits IoT ‎systems due to its low energy consumption, simple hardware requirements, and its level of security. A new strong substitution box is suggested considering   the algorithm immunity against the various types of ‎attacks such as linear, differential, and side channel cryptanalysis. LCA has a simple bit slice implementation and it relies its design on a new approach of Feistel structure.}, keywords = {Wireless networks,IOT,Cryptography,LCA,Bit- slice implementation,Feistel structure}, url = {https://mjeer.journals.ekb.eg/article_67379.html}, eprint = {} } @article { author = {Aboshsha, Bassam and Dessouky, Mohamed and Ramadan, Rabie and EL-SAYED, Ayman}, title = {Immunity of Lightweight DES Algorithm (DESL) Against Linear Cryptanalysis Attack}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {381-387}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67380}, abstract = {Lightweight DES Algorithm (DESL) was introduced by Axel Poschmann et.al as a strong, compact and efficient encryption algorithm suitable for constraint resource like WSNs, RFID and IOT devices. This paper discusses the security of the DESL against Linear Cryptanalysis which is a known plaintext attack in which a large number of plaintext-ciphertext pairs are used to determine the value of key bits. Linear cryptanalysis works on the principle of finding “high probability occurrences of linear expressions involving plaintext bits, ciphertext bits, and subkey bits”. Furthermore, we show that DESL is more resistant against the linear cryptanalysis attack than classical DES.}, keywords = {Cryptography,DESL,Linear cryptanalysis,RFID}, url = {https://mjeer.journals.ekb.eg/article_67380.html}, eprint = {} } @article { author = {Elkousy, Ahmed and Younis, ola and Abdelrahman, Salah and EL-SAYED, Ayman}, title = {Performance Enhancement of Wireless Sensor Networks Using Fixed Clustering/Event-Driven Concept}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {395-402}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67381}, abstract = {Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. In this paper, we develop and analyze a new concept in the Optimal Energy LEACH Protocol (OELP), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve excellent performance in terms of system lifetime. The new approach is studying and analyzing the effect of fixed clustering and event-driven on the network lifetime. Fixed clustering OELP (FCOELP) includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to distribute the energy load among all the nodes evenly. The results show that fixed-clustering OELP increases network lifetime by a factor of 50% approximately compared with previous related work researches.}, keywords = {Data Driven,Fixed Clustering,Low power Consumption,Wireless Sensor Network}, url = {https://mjeer.journals.ekb.eg/article_67381.html}, eprint = {} } @article { author = {Abu Khadra, Shaimaa and Abdulrahman, Salah Eldin and Ismail, Nabil}, title = {A Novel Approch for Binary Elliptic Curve Cryptosystem Implementation Over GF(2^409)}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {387-394}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.67631}, abstract = {Security in embedded systems are presented in this work based on Elliptic Curve crypto-processor (ECCP). Comparison with state-of-the-art algorithms that have been used to implement ECCP are also presented. It proves that Montgomery ladder algorithm is preferred one when the speed is needed. Optimization problem for general ECCP architecture are started from the selected algorithm and ends with liveness analysis and forward path. The inversion operation based on Itoh-Tsujii GF(2409) is discussed in this work. The proposed ECCP is implemented for GF(2163) and GF(2409) where the execution time are 8 μs and 61.2 μs respectively in sequentially design.  The design and  results are implemented using Xilinx ISE Virtex6.}, keywords = {finite field arithmetic,elliptic curve scalar multiplication,Itoh-Tsujii inversion}, url = {https://mjeer.journals.ekb.eg/article_67631.html}, eprint = {} } @article { author = {A. El-Booz, Sheren and A. Radad, Marwa and El-Fishawy, Nawal A and Attiya, Gamal}, title = {A Review of the Methods for Detecting and Characterizing DNA Methylation as a Cancer Biomark}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {311-318}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.69025}, abstract = {DNA methylation is a covalent alteration in the DNA genome that modifies the expression of gene. DNA methylation occurs by adding methyl group to DNA molecule at fifth carbon of Cytosine ring. This process alters DNA activities but doesn’t change the sequence. This modification may cause tumorigenesis and cancer progression. Therefore, there is an urgently need to detect the methylated sites in DNA sequences and their regulation mechanisms which effect the epigenetics transformation. Predominantly, these epigenetic changes are in small regions in DNA called CpG islands, which exist with various frequencies in DNA sequences but mostly detected in promoter regions. Recently, a lot of efforts have been dedicated to computationally detect CpG islands, build large-scaled databases with visualization tools and develop analysis methods for DNA methylation data. Here, we provide a review on CpG islands detectors and classifier algorithms. We focus on genome-wide methylation databases of human cancers. We present an overview of methodologies available for DNA deferential methylation analysis. We aimed to summarize the recent efforts in DNA methylation changes and their significance in human cancers to open the door for more development in mechanisms and treatment perspectives.}, keywords = {Epigenetics,DNA Methylation,hypo-methylation,hyper-methylation,Mutation,carcinogenesis}, url = {https://mjeer.journals.ekb.eg/article_69025.html}, eprint = {} } @article { author = {I. Selim, Gamal Eldin and Hemdan, EZZ El-Din and M. Shehata, Ahmed and A. El-Fishawy, Nawal}, title = {Anomaly Activities Detection System in Critical Water SCADA Infrastructure Using Machine Learning Techniques}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {343-384}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.69027}, abstract = {Industrial Control System (ICS) plays important role to reduce the human interact to operate the industrial system process. Cyber Physical Systems (CPSs) exist in critical infrastructure such as nuclear power generation, transportation networks, gas and water distribution networks, Unmanned Aerial Vehicle Systems (UASs) and electric power distribution networks. In this paper, we present a system to detect anomalies and malicious activities in critical water infrastructure. This system helps the industrial operator and administrator when an anomaly occurs and acts on the infrastructure.  The system is built using various machine learning techniques such as Logistic Regression (LR), Linear Discriminant Analysis (LDA), Classification and Regression Tree (CART) and Support Vector Machine (SVM). The model was evaluated using a real-world dataset covering 15 anomaly scenarios including normal system behavior. The presented scenarios covered a wide range of events, ranging from hardware failure to sabotage in the water critical infrastructure. The overall evaluation showed that CART is the best classification technique because it has the highest results in all performance evaluation metrics such as accuracy, precision. There is a comparative study between the results after applying normalization on the dataset. The results after applying normalization are better than the results before applying it.}, keywords = {Industrial Control System,Cyber Physical Systems,Machine Learning,Critical Infrastructure}, url = {https://mjeer.journals.ekb.eg/article_69027.html}, eprint = {} } @article { author = {Elshrief, Yasser Ahmed and Helmi, Dalal Hussein and Asham, Amin Danial and abozalam, Belal Ahmed}, title = {ROCOF for detecting Islanding of Photovoltaic system}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {255-258}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.70897}, abstract = {Power industry has been emphasizing more importance on a distributed generation because there is new technology like Photovoltaic (PV), fuel cell, wind turbine, and power electronic use for advancement of the power system has been evolved so much which cannot be possible without distributed generation. The majority of small scale PV systems are domestic roof-top type installations and are generally single-phase systems. Rebates and concession schemes that were introduced by the government for installing small scale PV systems along with price reductions in PV panels are the main reasons for the increased number of grid-connected small scale PV systems in the power distribution grid. Hence Distributed Generation (DG) has become an inseparable part in power system and gained so much importance because of economic and environmental purpose. Islanding is a situation where a part of the distributed generation system containing a distributed generator gets electrically isolated from the remainder of the power system continues to energize the network where the situation has occurred. Thus it has become important that the portion where islanding has occurred must detect this situation immediately for safety purpose. If tripping doesn’t occur in time, there can be a various and critical problem. Currently, in industry practice, we disconnect all distributed generators after islanding has occurred. Generally, a distributed generator should be disconnected within 0.1s to 0.3s after the loss of grid/main supply. This paper gives a simulation model to achieve this, each distributed generator must be supplied with an anti-islanding device which detects islanding like UOF and ROCOF relays.}, keywords = {— islanding detection,Distributed generation,integrated power distribution network,non-detection zone,islanding detection method,ROCOF}, url = {https://mjeer.journals.ekb.eg/article_70897.html}, eprint = {} } @article { author = {Elshrief, Yasser Ahmed and Helmi, Dalal Hussein and Asham, Amin Danial and abozalam, Belal Ahmed}, title = {Merits and Demerits of the Distributed Generations Connected to the Utility Grid}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {259-262}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.70907}, abstract = {The necessity for smart electrical systems having a minimum technical loss and environmental impact is providing impetus to go for Distributed Generations (DGs) which may offer several other advantages such as reduced transmission and distribution system resources, increased reliability, better power quality, etc. However, depending on the system configuration and management, these advantages may not be true. Moreover, due to structural and managerial changes in the electricity supply industry motivated with the introduction of completion, the role of small generations distributed in the low/medium voltage network has gained importance. This paper presents a complete discussion of the advantages and disadvantages of the distributed generations and their types. This paper also highlights the key issues in the DG integration in power systems.  }, keywords = {Distributed generation,stability,connected to the grid}, url = {https://mjeer.journals.ekb.eg/article_70907.html}, eprint = {} } @article { author = {Shoukralla, E. S. and Ahmed, B. M.}, title = {Numerical Solutions of Volterra Integral Equations of the Second Kind Using Barycentric Lagrange with Chebyshev Interpolation}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {275-279}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76664}, abstract = {The Barycentric Lagrange interpolation with non-uniformly spaced Chebyshev interpolation nodes has been modified and re-configured in a new formula to solve Volterra integral equations of the second kind. To avoid the application of the collocation methods necessary to transform the solution into an equivalent linear system, the unknown function is interpolated using the given modified Barycentric Lagrange polynomials and is substituted twice into the integral equation, while the given data function is expanded into Maclaurin polynomial of the same degree as the interpolant unknown function. Thus, the presented technique yields substantially higher accuracy and faster convergence of the solutions. The obtained results of the five illustrated examples show that the numerical solutions converge to the exact solutions, particularly for unknown analytic functions, and strongly converge to the exact ones for all values of  including the endpoints of the integration domain regardless of whether the kernel and data functions are algebraic or not. }, keywords = {Volterra integral equations,second kind,Chebyshev nodes,interpolation,Barycentric Lagrange,Numerical methods}, url = {https://mjeer.journals.ekb.eg/article_76664.html}, eprint = {} } @article { author = {Said, Mervat and El-Saghir, Zeiad and EL-Fishawy, Nawal}, title = {A Comparative Study of Single-Iteration Scheduling Algorithms for Input-Queued ATM Switches}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {306-310}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76665}, abstract = {Most high-speed switches use input queued architectures. These architectures generally utilize iterative scheduling algorithms for their operation. Iterative schedulers require high time complexity, so their efficiency is low, especially under heavy load conditions. To overcome this drawback, a new trend has emerged in the field of scheduling algorithms, by introducing so-called non-iterative scheduling algorithms. These algorithms achieve a maximum matching of I/O mapping in a single iteration, so they achieve high throughput and reduce the switch delay as they require less time complexity. This paper is a comparative study of the most efficient single-iteration algorithms used for scheduling cells in high-bandwidth input-queued ATM switches. Five algorithms were evaluated in terms of the throughput and the switch latency, including PIM-1, iSLIP-1, SSRR, SRRR, and CHRF algorithms.}, keywords = {Input queued switches,Iterative scheduling algorithms,time complexity,maximum matching,Single-iteration algorithms}, url = {https://mjeer.journals.ekb.eg/article_76665.html}, eprint = {} } @article { author = {Abd El-Moneim, Samia and Hassan, Shaimaa E. A. Aziz and Sedik, Ahmed and Nassar, M. A. and Dessouky, Moawd I. and Ismail, Nabil A. and El-Fishawy, Adel S. and El-Banby, Ghada M. and Khalaf, Ashraf A. M. and Abd El-Samie, Fathi I.}, title = {Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {19-23}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76669}, abstract = {Speaker recognition is one of many biometric authentications, due to its high importance in many applications of security considerations and telecommunications. The main aspiration of speaker recognition system is to know who is speaking depending on voice characteristics. Many current researches focuses on text-dependent speaker recognition which has a pre-knowledge of what utterance the speaker will say. In this paper text-independent speaker recognition system is used, where no prior knowledge is accessible in the context of the speakers’ utterances for all stages. A Convolutional Neural Network (CNN) based feature extraction is extended to a text-independent Speaker recognition task. Also the effect of reverberation on speaker recognition is addressed. All the speech signals are converted into images by obtaining their spectrograms. A proposed CNN model is presented to enhance the performance of the system in case of a reverberant signal. It depends on image processing concepts, and hence spectrograms of signals are used. The proposed model is compared with a conventional benchmark model. The performance of the recognition system is measured by the recognition rate in the case of clean and reverberant data.}, keywords = {Speaker recognition,CNN,reverberation,spectrogram,recognition rate}, url = {https://mjeer.journals.ekb.eg/article_76669.html}, eprint = {} } @article { author = {Abedellatif, Heba and selim, Abdelrahman and Taha, Taha E. and El-Shanawany, Ramadan and Zahran, Osama F. and Abd El-Samie, Fathi E.}, title = {Comparative Study of Wavelet Transform Based Fractal Image Compression}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {24-28}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76677}, abstract = {Fractal image compression has been studying during the last years for compressing images by using their self-similarity. The main advantages of fractal compression are, achieves a higher compression ratio and preserves the image resolution, but it lacks expensive computational cost searching the domain pool. To overcome this limitation and keeping better image quality, we propose a combination of a discrete wavelet transform and fractal coding to implement an encoder based on a flexible domain pool constructed from the neighborhoods of each range block.  A comparison between recent encoding algorithms and the proposed fractal image compression introduced.}, keywords = {Fractal Image Compression,Discrete Wavelet Transform (DWT),Compression Ratio}, url = {https://mjeer.journals.ekb.eg/article_76677.html}, eprint = {} } @article { author = {El-Shamy, Ahmed and El-Fishawy, Nawal and Attiya, Gamal and Ahmed, Mokhtar}, title = {Dynamic Load Balancing of Cloud Data Center Traffic Based on Software-Defined Networking}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {319-325}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76682}, abstract = {Cloud computing has grown rapidly in the last decade, where many tenants are using various cloud applications. Cloud computing users expect and demand to run their applications with the highest performance, reliability, and best quality of service. So, load balancing techniques are essential components and widely used in the cloud data center network to manage users’ requests and distribute applications traffic among available data center resources. Software-defined networking is a highly flexible network architecture that automates network configuration using a centralized controller to overcome the traditional network limitations and manual configuration for every network device. This paper proposes a dynamic load balancing technique using software-defined networking for the cloud data center that can handle different application types in real-time based on traffic type and the required quality of service. The proposed method aims to bridge the gap between application requirements and the resources in the cloud data center by choosing the best path for data transmission and selecting the best performance server to process the users' requests according to traffic type for efficient resources’ utilization, minimizing response time, and maximizing throughput. The simulation results show that the proposed method enhances the performance of the running applications’ and utilizes the data center resources efficiently compared with the current load balancing techniques.}, keywords = {Cloud Computing,Data Center network,Dynamic Load Balancing,OpenFlow Protocol,Software-Defined Networking}, url = {https://mjeer.journals.ekb.eg/article_76682.html}, eprint = {} } @article { author = {E. S., Shoukralla, and S. A., EL-Serafi, and H., Elgohary, and M., Morgan,}, title = {A Computational Method for Solving Fredholm Integral Equations of the Second Kind}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {280-285}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76689}, abstract = {this paper presents a new double­-approximate computational method for solving Fredholm integral equations of the second kind. The method is based on the approximation of the given data function, and the unknown function by utilizing Legendre polynomials in matrix form, while the approximate function of Legendre coefficients of the first approximation of the kernel is expanded once again using Legendre polynomials. In addition, the double substitution of the unknown function into the considered integral equation provides access to a linear system of an algebraic equation, which is equivalent to the required solution. Convergence in the mean of the unknown function is proved. Finally, five illustrative examples are presented. It turns out that the obtained approximate solutions converge to the exact solutions that demonstrate the authenticity and the efficiency of the new method. }, keywords = {Fredholm integral equations, Legendre polynomials,approximate solution, second kind}, url = {https://mjeer.journals.ekb.eg/article_76689.html}, eprint = {} } @article { author = {Ramadan, Mohamed M. and Koutb, Prof. Dr. Magdy A.}, title = {Determination of Optimal Q-V Droop Controller Parameters for Three-Phase Modular UPS System Based on Genetic Algorithm (GA)}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {248-255}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76703}, abstract = { This paper presents an optimized reactive power-voltage (Q-V) droop controller parameters for three-phase modular uninterruptible power supply (UPS) based on genetic algorithm (GA). The main objective of this paper is to minimize the voltage regulation error when there are changes in loads. In addition to select the control parameters carefully to promote the performance of the system against disturbances.  This is substantial to attain power sharing between different UPS units to balance sudden disturbances that happen when there are changes in loads. We propose a discrete proportional-integral controller which compares the output voltage with the reference value given by the droop control loops then generates suitable voltage vector signal to pulse-width modulation (PWM) inverter.  The fitness function for the optimization problem is formulated by considering the sum of square errors in voltage. This fitness function converges to local minima during the iterative operation of the genetic algorithm. Thus, the optimal parameters of the voltage droop control can be discovered with great probability. Simulation of two parallel-connected three-phase UPS units are carried out using MATLAB/SIMULINK R2018a. Comparison between the conventional trial and error tuning methods and GA optimization is performed. The results show that GA succeeded to minimize the output voltage root mean square error (RMSE) and to enhance the power sharing capability when there is variation in loads.}, keywords = {Genetic Algorithm,Uninterruptible Power Supply,Power Sharing,Parallel Operation,Droop Control}, url = {https://mjeer.journals.ekb.eg/article_76703.html}, eprint = {} } @article { author = {Siam, Ali I. and Abou Elazm, Atef and El-Bahnasawy, Nirmeen A. and El Banby, Ghada and Abd El-Samie, Fathi}, title = {Smart Health Monitoring System based on IoT and Cloud Computing}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {37-42}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76711}, abstract = {This paper presents a secure IoT-based health monitoring system that shortens the distance between a patient and the relevant medical organization. Vital signals captured from sensors are processed and encrypted using AES (Advanced Encryption Standard) algorithm before sending to the cloud for storage. A Node MCU microcontroller is utilized to carry out the processing and encryption functions, and for providing connectivity to the cloud over WiFi. In addition, a medical specialist can visualize the private health data in real-time only after providing decryption credentials. Moreover, the proposed system provides an alert by sending an email to some patient relatives or coordinating specialist if vital signs are outside the normal rates. The proposed system provides privacy, security, and real-time connectivity for private health data records.}, keywords = {Secure Health Monitoring,Internet-of-Things (IoT),Cloud Computing,AES Encryption}, url = {https://mjeer.journals.ekb.eg/article_76711.html}, eprint = {} } @article { author = {Eldesokey, Heba M. and Amoon, Mohamad and Abd Elaaty, Said and Abd El-Samie, Fathi E.}, title = {Earlier Deadline Algorithm for Virtual Machine Allocation}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {326-331}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76744}, abstract = {The problem of allocating the virtual machines to the jobs in cloud computing systems is a complex one. The key challenge inferred is attaining better power consumption, time and cost. To allocate a job, set of power-aware dynamic allocators for Virtual Machines are presented. It takes the benefit of software Defined Networking (SDN) paradigm. Integrating Ant colony algorithm augments the power consumption with its uncertain time convergence. These approaches escalated preemptive mechanism that assists better decision in scheduling. In order to overcome all those shortcomings, the Earliest Deadline First (EDF) algorithm has been implemented which tends to solve the inefficient allocation of virtual machines. The segmentation of the dataset is done to enhance the performance of the VM which is firstly realized in this VM allocation approach. In this paper, we introduce 10 virtual machines with different allocation strategies, and compare them with a baseline that consists of using the first available server (First Fit). The allocators differ in terms of allocation policy (Best Fit/Worst Fit), allocation strategy (Single/Multi objective optimization), and joint/disjoint selection of IT and network resources. The EDF algorithm is preferred here to achieve better power consumption and it is accomplished beyond the expectations. Moreover, the experimental results highlight that joint approaches outperform disjoint ones}, keywords = {— software Defined Networking,virtual machine,Ant colony algorithm,allocation strategy,Single/Multi objective optimization}, url = {https://mjeer.journals.ekb.eg/article_76744.html}, eprint = {} } @article { author = {Maher, Mohammad M. and Abd El-Samie, Fathi E. and Zahran, O.}, title = {A Novel Dynamic Bandwidth Allocation for the Integrated EPON and WiMAX Based on Auction Process}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {51-57}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76749}, abstract = {Integration of Ethernet passive optical network (EPON) and WiMAX technologies is regarded as a promising solution for next-generation broadband access networks. In implementing such networks, efficient bandwidth allocation schemes are essential to satisfy quality of service (QoS) and fairness requirements of various traffic classes. Existing proposals for solving the bandwidth allocation problem in EPON/WiMAX networks neglect interactions between the self-interested EPON and WiMAX service providers (WSPs). Accordingly, this study proposes a novel EPON-based DBA method that shows advantages over currently available methods in integration process. In the proposed algorithm, that based on the auction theory, optical line terminal runs an auction-based process to effectively register optical network unit’s bandwidth that requests and allocates the highest bidders based on the amount of available bandwidth. Simulation results indicate significant improvements comparing to fair sharing using dual-service-level agreements, ‘limited service’ interleaved polling with adaptive cycle time methods, bandwidthalllocation strategy using Stackelberg game and bandwidth allocation strategy using coalition game regarding quality of service parameters such as throughput and the time delay of running method.}, keywords = {EPON,WiMAX,DBA,QOS,throughput,time delay}, url = {https://mjeer.journals.ekb.eg/article_76749.html}, eprint = {} } @article { author = {Elshiekh, Aya G and Naeem, Ensherah A. and Abou Elazm, Atef and El-Shafai, Walid and El-Banby, Ghada M. and Abd El-Samie, Fathi E.}, title = {A New Application of MACE Filter for Cancelable Fingerprint Recognition}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {58-62}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76753}, abstract = {Now a days there is a widespread use of biometric authentication system, biometric templates cannot be replaced if lost or compromised. To deal with the issue of the compromised biometric template, template protection schemes evolved to make it possible to replace the biometric template. Cancelable biometric is such a template protection scheme that replaces a biometric template when the stored template is stolen or lost. Fingerprints are a good choice as they are unique to a person. Fingerprint recognition is a complex pattern recognition problem. This paper proposes fingerprint verification based on correlation filters because of their properties like shift invariance, ability to accommodate in-class image variability and closed form expressions. The performance of a specific type of correlation filter called the minimum average correlation energy (MACE) filter}, keywords = {Cancelable biometric system,correlation filter,Fingerprint Recognition,Minimum average correlation energy (MACE)}, url = {https://mjeer.journals.ekb.eg/article_76753.html}, eprint = {} } @article { author = {Mesrega, Ahmed K. and El-Shafai, Walid and Ahmed, Hossam Eldin H. and El-Bahnasawy, Nirmeen A. and Abd El-Samie, Fathi E. and Elfiqi, Abdulaziz E.}, title = {A Hybrid Modified Advanced Encryption Standard and Chaos Encryption Algorithm for Securing Compressed Multimedia Data}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {63-70}, year = {2020}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2020.76761}, abstract = {Multimedia data is being used more widely in the field of Internet communication technology. Over wireless networks, extensive use of multimedia applications can easily be intercepted. The widespread use of multimedia data makes media content security and protection increasingly urgent and necessary. In order to fully protect or maintain security and privacy of multimedia data, it must be secured through encryption before transmission. Multimedia encryption is the core enabling technology that provides confidentiality and end-to-end security preventing unauthorized access of the information. In this paper, an encryption algorithm is proposed to achieve the desired integrity. Compressed video frames usingH.264 with multi-view video coding MVC are encrypted using a hybrid algorithm based on modified advanced encryption standard AES with 1D, and 2D chaotic maps. The encryption process replaces add round key and S-box operations of AES encryption by XOR operation and chaotic map generators on different blocks of input data frames. The results of our simulation using MATLAB show that the proposed algorithm is suitable for multimedia encryption applications.}, keywords = {Multimedia application,Encryption,3DV Compression,wireless communication,Information Security}, url = {https://mjeer.journals.ekb.eg/article_76761.html}, eprint = {} } @article { author = {Mahmoud Ahmed, Mohamad Essam and and Fathi E. Abd El-Samie, E. S. Shoukralla, Saied M. Abd El-atty and}, title = {Quaternion Based On Cancelable Biometrics}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {71-77}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76767}, abstract = {The current paper presents a novel cancelable face recognition scheme based on quaternion mathematics. The main idea of the proposed model is to mask the nature of faces prior to use in the face recognition process. The objective of this process is to keep the privacy of users during the initiation biometric data and the biometric verification process in case of data base compromising wherein it is possible to change the saved biometric templates while the color face image is used to compose a quaternion. Subsequently, a mask image is used in another quaternion. Quaternion multiplication and thus quaternion inverse are applied to generate the cancelable templates. The performance analysis of the proposed approach reveals that low EER and large area under ROC curve which are the required high index templates}, keywords = {— cancelable biometrics,image encryption,quaternion mathematics}, url = {https://mjeer.journals.ekb.eg/article_76767.html}, eprint = {} } @article { author = {Haweel, Mohammad T. and Abd El-Samie, Fathi E. and Zahran, O.}, title = {Polynomial Series FLANN for Nonlinear Equalization}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {78-82}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76768}, abstract = {Efficient equalization for nonlinear communication channels with Additive White Gaussian Noise (AWGN) is presented. The proposed equalization is based on a Functional Link Artificial Neural Network (FLANN) structure in which the original input is nonlinearly expanded. The proposed nonlinear expansion follows a polynomial series. The nonlinearity incorporated at the output of the conventional FLANN is omitted in the proposed Polynomial Series Equalizer (PSE). Consequently, the convergence of the PSE is fast and its computational complexity is low. Moreover, explicit mathematical formula for the optimum PSE is obtained. The PSE is adapted using the fast gradient based signed Least Mean Squared (LMS). Simulations demonstrate that, the PSE vastly outperforms other FLANN based equalizers employing the Bit Error Rate (BER) metric at different nonlinear channel models and different Signal to Noise Ratios (SNR). }, keywords = {nonlinear channel equalization,functional link artificial neural network,polynomial series,signed LMS adaptive algorithm,bit error rate}, url = {https://mjeer.journals.ekb.eg/article_76768.html}, eprint = {} } @article { author = {Hassan, Neven and El-Shafai, Walid and Soliman, Naglaa and EL-Fishawy, Adel and Abd El-Samie, Fathi E.}, title = {Cancelable Speaker Recognition System based on Chaotic Encryption Approach}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {83-88}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76772}, abstract = {Biometric-based authentication system can provide strong safety guarantee of user identity, but it creates other concerns pertaining to template security. There is an urgent issue of preventing the original templates from being abused, and protecting the users' privacy efficiently. This paper introduces a cancellable speaker identification system based on chaotic encryption process to produce cancelable templates instead of original templates. The resulted transformed version of the voice biometrics is stored in the server instead of the original biometrics. So, the users' privacy can be protected well. In the experimental results, we calculate the EER, FRR, FAR, and AROC values for the proposed work. Also, we estimate the score for genuine and impostor and the ROC curve .}, keywords = {Cancelable Biometrics,Chaotic maps,voice recognition}, url = {https://mjeer.journals.ekb.eg/article_76772.html}, eprint = {} } @article { author = {Abd Al Rahim, Mohamed and El-Shafai, Walid and El-Rabaie, El-Sayed M. and Zahran, Osama and Abd El-Samie, Fathi E.}, title = {Comb Filter Approach for Cancelable Face and Fingerprints Recognition}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {89-94}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76776}, abstract = {Now many security systems depend on biometrics, these systems have suffered from hacking trials. If the biometric databases have been hacked and stolen, the biometrics saved in these databases will be lost forever. Thus, there is a desperate need to develop new cancelable biometric systems. The main concept of cancelable biometrics is to use another version of the original biometric template created through a one-way transform or an encryption scheme to keep the original biometrics safe and away from utilization in the system. In this paper, a comb filter algorithm is utilized for cancelable face and fingerprint recognition systems. The comb filter performs encryption process for faces and fingerprints to produce their cancelable patterns and compare them with any random attacked encrypted biometric. We notice that there is no any correlation between the stored biometrics and the attacked biometric at different filter order (L) values of the employed comb filter where L is tested in the cases of 6, 8, 10, and 12. Also, we calculate the  evaluation matrices of the Equal Error Rate (EER), False Accept Rate (FAR), False Reject Rate (FRR), and the Area under Receiver Operating Characteristic (ROC) curves for the proposed framework.}, keywords = {Cancelable Biometrics,Face and fingerprint,Comb filter,FAR,EER,AROC,FRR}, url = {https://mjeer.journals.ekb.eg/article_76776.html}, eprint = {} } @article { author = {Omran, Eman M. and Soliman, Randa F. and Eisa, Ayman A. and Ismail, Nabil A. and Abd El-Samie, Fathi E.}, title = {Cancelable Iris Recognition System with Pre-trained Convolutional Neural Networks}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {95-101}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76778}, abstract = {Iris recognition is one of the automated processes of verifying individuals’ identity based on their iris characteristics. Apparently, the random nature of the iris texture, which is unique for each individual, makes it an exclusive trait for biometric recognition even for the case of identical twins’ authentication. Recently, the improvement in deep learning and computer vision indicated that the extracted features using convolutional neural networks (CNNs) are suitable to describe the complex image patterns. But, how to protect the biometric data and provide users’ privacy is a main concern, nowadays. In this paper, we study the performance of pre-trained CNNs to successfully classify cancelable iris features when taking the feature vector from each fully connected layer. We show that these pre-trained CNNs, while originally learned for classifying generic objects, are also extremely good for representing iris images for recognition. The performance metrics are evaluated on three datasets: CASIA-IrisV3, IITD and Palacky iris databases. The obtained results achieve promising cancelable iris recognition and also ensure the robustness and effectiveness of the proposed approach.}, keywords = {Deep learning,Convolutional Neural Networks,Cancelable Biometrics,Iris recognition}, url = {https://mjeer.journals.ekb.eg/article_76778.html}, eprint = {} } @article { author = {Abd-Elgawad, Lamiaa A. and Hussein,, Gamal A. and Shalaby, Abdel Aziz T. and Abd-Elazim, Yara and Osama Oraby, Ibrahim M. Eldokany, Gaber Alabyad, and El-Rabaie,, El-Sayed M. and Hamad, Randa and Abd El-Samie, Fathi E. and Dessouky, Moawad I.}, title = {Enhanced Finite Impulse Response Equalizer with Activity Detection Guidance and Tap Decoupling Techniques}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {102-106}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76781}, abstract = {this paper deals with the physical impairments in Free Space (FS) channel of wireless Optical Communication System (OWC) considering different equalization schemes performance. Study of different adaptive equalizers is presented. The convergence process of these equalizers is considered and compared. Results show that the equalizer based on adopting Activity Detection Guidance ADG and Tap Decoupling TD techniques with standard LMS algorithm could provide better performance.}, keywords = {Adaptive Equalizer,activity detection guidance,tap decoupling}, url = {https://mjeer.journals.ekb.eg/article_76781.html}, eprint = {} } @article { author = {Monir, Mohamad and Kareem, Mona and Nassar, M. M. and El-Fishawy, Adel S. and Zain El-Din, M. A. and El-Dolil, Sami M. and Saleeb, Adel and El-Rabaie, EL-Sayed M. and Abd El-Samie, Fathi E.}, title = {Optimized Digital Filters Based on Zero Cancelation for Speech Security Applications}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {107-114}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76785}, abstract = {The secured biometric templates play an important role in real applications of recognition system             to generate revocable biometric templates. This paper introduces a proposed technique in cancelable biometrics that is used for speaker recognition. In this technique, zero cancelation digital filters are used to decode the extracted user features, intentionally. The objective of this work is to generate protected templates of speech signals. Simulation results  reveal the possibility of recognizing speakers in spite of feature deterioration due to the digital filtering effect which based on zero cancelation. Consequently, the robustness of the proposed speaker recognition system is guaranteed.  }, keywords = {digital comb filter,zero cancelation,Cancelable Biometric,speaker recognition system}, url = {https://mjeer.journals.ekb.eg/article_76785.html}, eprint = {} } @article { author = {Amr, Samer and Hussein, Hossam El din and Ramadan, Noha and El-Shafai, Walid and El-Hanafy, Waleed and Abd El-Samie, Fathi E.}, title = {Chaotic Encryption of ECG Signals with a Random Kernel Approach}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {115-121}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76786}, abstract = {Security of biometric data is very important in the healthcare domain. Due to uniqueness of electrocardiogram (ECG) is very high even in identical twins, so it can be used as biometric signature.This paper introduces a simple efficient ECG encryption technique based on random kernel approach. As ECG signals contain sensitive confidential information with details for patient identification, it needs to be encrypted before transmission through public network to avoid the data being breached and hacked. The security of the proposed system will depend on random kernel coefficients, substitution process and length of kernel filter. Simulation results show that the proposed system is capable of encrypting ECG signals for secure communication efficiently.}, keywords = {Encryption,ECG signals,Secure communication}, url = {https://mjeer.journals.ekb.eg/article_76786.html}, eprint = {} } @article { author = {Sallam, Youssef F. and Sedik, Ahmed and Ghazy, Rania and Abdelwahab, Nirmeen and Ahmed, HossamEl-din H. and Saleeb, Adel and El Banby, Ghada M. and Khalaf, Ashraf A. M. and Abd El-Samie, Fathi E.}, title = {Intrusion Detection Based on Deep Learning}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {369-373}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76787}, abstract = {Information and Communication Technology (ICT) plays an important role in our life. ICT is engaged with the business and individual patterns of human life. The ICT security is one of the normal ICT fields, which attracts researchers’ attention. The objective of security is to discover attacks represented in control and data planes. These attacks include Denial of Service (DoS), and probing attacks. Intrusion Detection System (IDS) is one of the best solutions for observing, and distinguishing these attacks. In this paper, an IDS dependent on Deep Learning (DL) is proposed. This system achieves an accuracy detection level of 100%.}, keywords = {Intrusion Detection System (IDS),Deep Learning (DL) and Convolutional Neural Network (CNN)}, url = {https://mjeer.journals.ekb.eg/article_76787.html}, eprint = {} } @article { author = {El-Ashkar, Alaa M. and Sedik, Ahmed and Shendy, H. and Taha, Taha El Sayed and El-Fishawy, Adel S. and Abd El-Nabi, Mohamed and . Khalaf, Ashraf A. M and El-Banby, GH. M. and Abd El-Samie, Fathi E.}, title = {Classification of Reconstructed SAR Images Based on Convolutional Neural Network}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {122-125}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76897}, abstract = {Synthetic aperture radar (SAR) is a very important radar imaging type in which the utilization of antenna movement with respect to the target to be detected is considered. Detecting of target existence through noisy received images is a very critical and challenging point. Classification through deep learning presented in the form of Convolutional Neural Network (CNN) is a very good choice to enhance the decision performance reducing the error rate and false alarms. The main aim of this paper is to use a reliable classification technique in order to detect target existence through noisy received SAR images. Training data set for CNN is collected through a simulation in which realistic SAR images can be generated and used for SAR Automatic Target Recognition (ATR). CNNs are performed on images to classify the existence of targets. The accuracy of this approach is 100%.  }, keywords = {Convolutional neural network (CNN),Radar imaging,SAR imaging,range Doppler algorithm (RDA),Image Reconstruction,Image classification,Automatic Target Recognition (ATR)}, url = {https://mjeer.journals.ekb.eg/article_76897.html}, eprint = {} } @article { author = {Khalil, Hager and El-Hag, Noha and Sedik, Ahmed and El-Shafie, Walid and Mohamed, Abd El-Naser and Khalaf, Ashraf A. M. and El-Banby, Ghada M. and Abd El-Samie, Fathi I. and El-Fishawy, Adel S.}, title = {Classification of Diabetic Retinopathy types based on Convolution Neural Network (CNN)}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {126-153}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76962}, abstract = {- Diabetes mellitus have an eye disease called diabetic retinopathy. The early discovery of the disease is a great achievement in management of diabetic retinopathy. We use Fundus images are used for identification of the nature of an illness or other problem through examination of the symptoms to check for any abnormalities or any change in the retina. In this paper, Convolutional Neural Networks (CNN) is performed to classify the retinal fundus images to normal, background and pre-proliferative retinopathy. The proposed model consists of 5 convolutional layers followed by 5 max pooling layers. Finally, a global average pooling is used. In this work we achieve accuracy reached 95.23%.}, keywords = {diabetic retinopathy,Convolutional Neural Networks,fundus images}, url = {https://mjeer.journals.ekb.eg/article_76962.html}, eprint = {} } @article { author = {Elsayed, Marwa and El-Shafai, Walid and Rashwan, Mohsen A. and Dessouky, Moawad I. and El-Fishawy, Adel S. and Abd El-Samie, Fathi E.}, title = {Cancelable Speaker Identification Based on Inverse Filter}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {133-137}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76969}, abstract = { Nowadays, biometric systems have replaced the password or token based authentication systems in many fields to improve the security level. Biometric authentication systems automatically identify or verify a person using physical, biological, and behavioral characteristics. Unfortunately, these systems have suffered from hacking trials. This paper presents masking techniques for cancelable speaker identification. The basic concept is to use another version of the original speaker signal created through a masking techniques to keep the original signals safe and away from utilization in the system. The basic idea is adding some sort of noise to the speech signal and magnification of this noise by the proposed techniques. The proposed techniques are discrete wavelet transform (DWT), wavelet thresholding, Linear Minimum Mean Square Error (LMMSE) technique and invers filter. A comparison between these techniques is established using objective quality measures of speaker identification. Simulation results show good performance of the technique based on invers filter.}, keywords = {Speaker identification,biometric systems,Cancelable Biometric,LMMSE,invers filter}, url = {https://mjeer.journals.ekb.eg/article_76969.html}, eprint = {} } @article { author = {Sayed, Khairy and Kassem, Ahmed M. and Aboelhassan, Ismail and Aly, Abdelmaged M. and Abo-Khalil, Ahmed G.}, title = {Role of Supercapacitor Energy Storage in DC Microgrid}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {263-268}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76978}, abstract = {Recently, energy storage technologies are not only protruded as sources of energy rather; these technologies provide a great contribution to improve the stability, power quality and reliability in the electrical system. The high utilizing of renewable energy sources can be harnessed by using these energy storage systems. This paper shows the role of supercapacitor in DC Microgrid to be stable under partial shading issue. For studying the effect of adding supercapacitor, the microgrid system is simulated with and even without supercapacitor. The fluctuations of the DC link bus voltage of the microgrid is reduced as a result of integration with   supercapacitor unit. The simulation results approve that supercapacitor improve the DC microgrid stability. }, keywords = {Renewable Energy Sources (RESs),Energy Storage System (ESS),DC Microgrid}, url = {https://mjeer.journals.ekb.eg/article_76978.html}, eprint = {} } @article { author = {El-Beheiry, S. S. and El-Fiqi, A. E. and El-Mahlaway, A. and El-Banby, Gh. and Abd EL-Samie, Fathi E. and El-Rabaie, S.}, title = {Proposed Cancelable Face Recognition System Based on Histogram of Oriented Gradients}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {138-144}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76987}, abstract = {nowadays have seen exponential growth in the usage of various biometric technologies in authenticated automatic recognition of humans. With the fast adaptation of biometric systems, there is a vital concern that biometric technologies may compromise the privacy and anonymity of individuals. To restrain the theft of biometric templates, it is desirable to alter them through noninvertible and revocable transformations to produce a cancelable biometric pattern. In this paper, we propose cancelable face pattern generation technique based on component Histogram of Oriented Gradients (HOG) and The Optical Double Random Phase Encoding (DRPE) algorithm. The proposed is evaluated by the security degree and receiver operating characteristic (ROC) Experiments carried out on diverse face databases assure the efficiency of the proposed approach. The proposed template succeeds to hide the details of the images and enhances ROC compared to the traditional standard.}, keywords = {Biometric,Face Recognition,Cancelable Biometric,Random Projection,Bio Hashing}, url = {https://mjeer.journals.ekb.eg/article_76987.html}, eprint = {} } @article { author = {Hsaneen, Abd El-aziz Ebrahim and El-Rabaei, EL-Sayed M. and Dessouky, Moawad I. and El-bamby, Ghada and Abd El-Samie, Fathi E. and Mohamed, Abd El-hamid}, title = {Cancelable Biometric System for face Based on linear minimum mean square error Model.}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {145-152}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76994}, abstract = {Now-a-days biometric systems have replaced the password or token based authentication system in many fields to improve the security level. However, biometric system is also vulnerable to security threats. Unlike password based system, biometric templates cannot be replaced if lost or compromised. To deal with the issue of the compromised biometric template, template protection schemes evolved to make it possible to replace the biometric template. Cancelable biometric is such a template protection scheme that replaces a biometric template when the stored template is stolen or lost. It is a feature domain transformation where a distorted version of a biometric templates generated and matched in the transformed domain .This paper presents a scheme for cancelable face recognition based on linear minimum mean square error This scheme begins with add noise to the original face and applied LMMSE to the face image to obtain face image with magnified fixed noise pattern.}, keywords = {}, url = {https://mjeer.journals.ekb.eg/article_76994.html}, eprint = {} } @article { author = {HASSANIN, Abdel-Aziz Ibrahim Mahmoud and Shaaban, Amr Saadeldien Elsayed and Abd El-Samie, Fathi E.}, title = {Tomographic Image and the Inverse Scattering Problem Using Multiple Incidence on Biological Object in Terahertz}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {153-157}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76996}, abstract = {Tomographic image and the inverse scattering problem using multiple incidence of biological object in Terahertz has been presented.The feasibility of a three-dimensional terahertz imaging using an electromagnetic exploration that has been proven, it remains to be determined in what conditions may be could obtain a good resolution in all directions. The recipe of conditions that will make collaboration engineering and economy comes together has been taken into account.Numerical results are given to demonstrate the capability to solve of inverse scattering problem algorithm for biological object of smooth cells which make up the intestine.  Also, the biological object of laceration in the tissue or puncture. The scattered field distribution is measured in a plane situated behind the object. They show that this field distribution depends on the object shape. The results of scattered electromagnetic field measurements carried out on different material objects are given. Good reconstruction is obtain from measured data even the results of scattered electromagnetic field measurements carried out on different material objects are given.}, keywords = {}, url = {https://mjeer.journals.ekb.eg/article_76996.html}, eprint = {} } @article { author = {Haggag, Nehad T. and Sedik, Ahmed and Elbanby, Ghada M. and El-Fishawy, Adel S. and Dessouky, Moawad I- and Khalaf, Ashraf A. M.}, title = {Classification of Corneal Pattern Based on Convolutional LSTM Neural Network}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {158-162}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76998}, abstract = {The development of the image classification techniques using deep learning has become one of the interesting research fields. It can be used in several fields such as the diagnosis of the corneal diseases. This paper proposes a Convolutional neural network – Long short-term memory (CNN-LSTM) model that can classifies the corneal images into normal and abnormal cases. The experimental results reveal that the CNN-LSTM neural network model provides a high performance. This model combines convolutional neural network (CNN) and long short-term memory (LSTM). The target of this combination is to extract complex features from the corneal images with a few number of layers rather than Convolutional neural networks. The proposed technique is carried out on a set of corneal images. These images are collected from patients via confocal microscopy.  The CNN-LSTM classification results on corneal fundus images achieved an accuracy of 100 %.  }, keywords = {Deep learning,Convolutional neural network (CNN),Long short Term Memory (LSTM),Normal and abnormal corneal images and model accuracy}, url = {https://mjeer.journals.ekb.eg/article_76998.html}, eprint = {} } @article { author = {Zahran, E. G. and Arafa, A. A. and Saleh, H. I. and Dessouky, M. I.}, title = {Development of RFID-Based Tracking System for Nuclear Material Via GPS Service: A Prototype Study}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {163-168}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.76999}, abstract = {A prototype RFID-based system has been developed for tracking and monitoring of nuclear materials and waste packages during transport and storage. The system is designed to allow persistent monitoring at all stages, including waste disposal. The system consists of RFID tags attached to the packages with on-board collection of sensors and radiation detectors, a reader network, application software, a database server and web pages. The tags monitor and record critical parameters, including the movement of objects, and environmental conditions of the nuclear material packages in real time. They also provide instant warnings or alarms when pre-set thresholds for the sensors are exceeded. The information collected by the readers is transmitted to a dedicated central database server that can be accessed by authorized users via a secured network. After the data is received, authorized operators can analyze the status of the packages and take the suitable actions for each case including emergencies via a secured website. The on-board memory of the tags allows the materials list and event history data to be associated with the packages throughout their life cycles in storage, transportation, and disposal. The software provides easy-to-use graphical interface.}, keywords = {GPS,Tracking,Raspberry Pi,RFID and 3S standards}, url = {https://mjeer.journals.ekb.eg/article_76999.html}, eprint = {} } @article { author = {Hussein, Ahmad and El-Rabaie, El-SayedM. and El-Mashed, Mohamed G.}, title = {A Scalable Security Communication System Based on ElGamal and RSA Schemes}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {169-176}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77002}, abstract = {Enhancing the security schemes in a communication system is very important, where data is transmitted through the channels and can’t be secured by physical hardware. A security schemes (i.e., cryptographic schemes) can guarantee the data integrity, confidentiality and authentication. The optimum choice of security scheme is a challenge task for communication system to be more accuracy, efficiency and safety. In this paper, we propose scalable roulette security scheme under ElGamal’s and Rivest–Shamir–Adleman’s (RSA’s) key generators. The performance of the proposed scheme is analyzed and compared with the advanced encryption standard-128 (AES-128) scheme, blowfish scheme and international data encryption (IDE) scheme. We analyze the proposed scheme with time variable and random number synchronization. Results demonstrate that throughput performance of the proposed scheme that adopts ElGamal’s and RSA’s key generators outperforms the other schemes.}, keywords = {security,Key generators,ElGamal,RSA and Throughput}, url = {https://mjeer.journals.ekb.eg/article_77002.html}, eprint = {} } @article { author = {Mohamed, Samia. and AbdEl-atty, Saied M. and El-Mashed, Mohmed}, title = {Performance Enhancement for Device-to-Device Communication Using Cooperative Techniques}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {177-182}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77005}, abstract = {We propose a network model for a relay assisted device-to-device (D2D) cellular system to enhance the system performance. An effective power control scheme is of great importance to suppress interference between D2D and cellular communications, which can improve the total system signal to noise ratios (SNRs). Therefore, we propose an open loop and closed loop power control schemes for the system. The comparison between D2D mode and cellular mode is made under different scenarios. The received signal-to-noise ratio is derived. Results showed that the performance of D2D mode under applying power control can give better performance compared to other cases. Large amount of data can be transferred using massive MIMO at mobile devices.}, keywords = {D2D communication,Relay technique,Power control}, url = {https://mjeer.journals.ekb.eg/article_77005.html}, eprint = {} } @article { author = {Abd-Alhalem, Samia M. and Soliman, Naglaa F. and Abd Elrahman, Salah Eldin, S. E. and Ismail, Nabil A. and El-Rabaie, El-Sayed M. and Abd El-Samie, Fathi E.}, title = {Spectral Features Based on Bidirectional Long Short-Term Memory for DNA Classification}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {183-188}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77008}, abstract = {the analyzing hidden features of DNA sequence is main challenge in bioinformatics. Since learning from DNA sequences based on analytical approaches to identify the hidden patterns provides a vital role in various genomic applications. In classification tasks, Re-current neural network with Bidirectional Long Short-Term Memory (BLSTM) is usually used for sequential data that is strongly dependent on the feature's extraction stage. Recently, digital signal processing (DSP) techniques such as spectral transformations has been used in genomic data for extracting the hidden features and periodicities within the DNA fragments. The objective of this paper is comparing different spectral transformations of DNA sequences such as Discrete Cosine Transform (DCT), Discrete Fourier Transform (DFT) and Discrete Wavelet Transform (DWT) based on BLSTM to achieve high performance in the taxonomic classification of bacteria. The reason for applying these transformations emerges from its wide and effective use for extracting features, decorrelation, ordering and dimensionality reduction purposes in the fields of speech and image processing. Evaluation metrics such as F1 score and accuracy show that DWT features give surpassing performance compared with other features. }, keywords = {Bidirectional Long Short-Term Memory (BLSTM),Discrete Cosine Transform (DCT),Discrete Fourier Transform (DFT) and Discrete Wavelet Transform (DWT)}, url = {https://mjeer.journals.ekb.eg/article_77008.html}, eprint = {} } @article { author = {Khattab, Ramy Mohammad and Shalaby, Abdel-Aziz Taha}, title = {Wideband Two-Section Branch-Line Coupler Using Microstrip Technique}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {189-193}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77011}, abstract = {This paper introduces a compact quadrature hybrid coupler for wideband applications. Using the conventional technique of cascading two sections in a quadrature hybrid we designed a broadband coupler at a central frequency of 1.8 GHz. To improve the performance of this coupler and to reduce its size we used the artificial transmission line concept, microstrip line loaded with shunt open ended stubs, and meandering lines. A size reduction of about 31% was achieved compared to the conventional one. The proposed design has a relative bandwidth of 33.3 %, and return loss and isolation loss are both better than 18 dB on the entire band. The proposed coupler has been simulated using the CST Studio suite, fabricated, and measured. A good agreement has been obtained between the simulated and measured results.}, keywords = {Broadband coupler,CST Studio suite,open ended stubs,compact quadrature hybrid}, url = {https://mjeer.journals.ekb.eg/article_77011.html}, eprint = {} } @article { author = {El.Abasy, Mohamed.M. and Taha, Taha E. and El-fishawy, Adel S. and Dessoky, Moawad. I. and Abd El-Samie, Fathi E.}, title = {Efficient Utilization of Compression Techniques on Seismic Signals}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {194-200}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77013}, abstract = {This paper presents a framework for compressing seismic signals. These signals move through the layers of the earth as a result of either natural sources such as earthquakes, volcanoes or landslides or by artificial sources like explosions. The compression can be defined as the process of compressing a signal to reduce its size for easy transmission. The seismic signal is coded by Linear Predictive Coding (LPC) technique. Also, the seismic signal is compressed using two techniques. The first technique depends on decimation process to compress the signal. On the other hand, the signal can be recovered using inverse techniques. The inverse techniques include maximum entropy and regularized. The second technique is called Compressive Sensing (CS) and the seismic signal can be reconstructed using linear programming. The performance of coding and compression techniques is evaluated using Dynamic Time Warping (DTW).}, keywords = {LPC,Decimation process,Maximum entropy technique,Regularized technique,CS and DTW}, url = {https://mjeer.journals.ekb.eg/article_77013.html}, eprint = {} } @article { author = {AbdelZaher, Hesham M. and El-Dokany, Ibrahim M. and El-Dolil, Sami A. and Oraby, Osama A. and Dessouky, Moawad I. and El-fishawy, Adel and El_Rabaie, El_Sayed M. and Abd-El-Samie, Fathi. E.}, title = {Efficient Noise Reduction in Optical Gyroscope Signals}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {201-208}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77016}, abstract = { Gyroscopes are sensors that are used for motion measurement. They are generally used to measure rotation rate of moving equipment. Gyroscope signals suffer from two types of noise. There is external noise due to environmental disturbances and internal noise due to internal device operation. Different filtering techniques can be employed to reduce this noise. Kalman filtering is one of these techniques that have been used. This paper presents a study of wavelet-based filtering technique and compares its results with Kalman filtering results. Results show the superiority of using the wavelet-based filtering technique over the Kalman filtering technique. }, keywords = {Gyroscope,Kalman filter,Wavelet denoising}, url = {https://mjeer.journals.ekb.eg/article_77016.html}, eprint = {} } @article { author = {Elsherbieny, Zeinab and Messiha, Nagy and El-Fisawy, Adel S. and Rihan, Mohamed and Abd El-Samie, Fathi E.}, title = {Efficient Denoising Schemes of EEG Signals}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {209-213}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77020}, abstract = {This paper presents a class of noise reduction techniques for EEG signals. The noise reduction is very important for subsequent EEG processing tasks. The suggested techniques are extended from application in speech processing to application in EEG signals due to the common nature of low frequency of both types of signals. These techniques are spectral subtraction, Wiener filtering, adaptive Wiener filtering, and Discrete Wavelet Transform (DWT). A comparison between different techniques is presented. Simulation results are used to compare between the different denoising techniques.  Four metrics are used to evaluate the different denoising techniques: signal -to-noise ratio (SNR), segmental signal-to-noise ratio (SNRseg), spectral distortion (SD), and log likelihood ratio (LLR).}, keywords = {EEG,denoising,Spectral Subtraction,Wiener filter,Adaptive Wiener filter,Discrete Wavelet Transform}, url = {https://mjeer.journals.ekb.eg/article_77020.html}, eprint = {} } @article { author = {Safan, Mohamed and El-Shafai, Walid and Mohamed, Abd Naser and Rashed, Ahmed and Desouky, Moawad I. and El-Rabaie, El-Sayed and Abd El-Samie, Fathi E.}, title = {Cancelable Face Recognition System Based on Optical Scanning Holography}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {2-7}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77024}, abstract = {Recently, biometrics has emerged joined of the foremost necessary methods of template preservation and most modern security systems rely on biometrics. Unfortunately, these systems have experienced for quite a while hacking endeavors. If biometric databases are compromised and stolen, biometrics spared in these databases will be lost until the end of time. Consequently, there is an immediate need to grow new upgrade biometric systems. The concept behind cancelable biometrics is to convert biometric data or extracted feature to an alternative template, which can't be easily used by the impostor or intruder and can be eliminated if it is breached. In this paper, the optical scanning holography (OSH) algorithm is utilized as cancelable face recognition system. In the proposed cancelable face recognition technique, the encrypted images are generated by OSH technique. Simulation results using evaluation metrics False Positive Rate (FPR), False Negative Rate (FNR), Equal Error Rate (EER), Receiver Operating Characteristic (ROC) and Area under ROC (AROC) prove that the the proposed cancelable biometric technique is good.}, keywords = {Biometrics,Enrollment and presentation,Optical scanning holography,EER,AROC}, url = {https://mjeer.journals.ekb.eg/article_77024.html}, eprint = {} } @article { author = {Ibrahim, Fatma E. and Eldokany, Ibrahim M. and Abd El-Samie, Fathi E.}, title = {EEG Seizure Prediction with Less Samples}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {220-5}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77026}, abstract = {In this paper, a new proposed approach using wavelet domain statistical analysis is presented to predict epilepsy seizures. In addition, in seizure prediction systems of wearable devices, while using wireless communication technologies such as Bluetooth, the challenge encountered is the amount of data acquired. Compressive sensing has been investigated as a tool to reduce data rates needed to be transferred and processing time as well. Histograms for segments of various signal states were studied in wavelet domain utilizing different signal processing tools such as differentiator, median filtering, local mean, and local variance estimators after the compressive sensing is applied. Simulation results revealed the possibility to use compressive sensing in epileptic seizure prediction systems. This opens the door for more compact seizure prediction algorithms.}, keywords = {EEG,Seizure Prediction,Compressive Sensing,Wavelet Transform}, url = {https://mjeer.journals.ekb.eg/article_77026.html}, eprint = {} } @article { author = {Hammad, Randa S. and El_Rabaie, El_Sayed M. and Abd-El-Samie, Fathi. E. and El-Dokany, Ibrahim M.}, title = {Efficient Adaptive Equalization for Wireless Optical Communication Systems}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {224-231}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77028}, abstract = {Optical Wireless Communication (OWC) system is used in many applications to transmit and receive light waves via free space. It is a perfect solution when it is difficult to use optical fibers system due to its cost or constructing difficulty.  On the other hand, FSO systems suffer from the physical impairments in free space channel such as clouds, fog, snow and rain that may degrade the transmission quality. This paper presents an efficient adaptive equalization scheme for OWC systems to mitigate the effect of ISI due to atmospheric impairments. It is based on using the Recursive Least Squares (RLS) equalizer with Activity Detection Guidance (ADG) and Tap Decoupling (TD).  The simulation results prove that the proposed scheme gives a very good performance to mitigate the problem of ISI in OWC systems. In addition, the results prove that the RLS algorithm has a fast convergence rate, which recommends it for nonstationary channel models (wireless communication environments).}, keywords = {Free Space Optics (FSO),Optical Wireless Communication (OWC),Adaptive Equalizer,Recursive Least Squares. (RLS) Equalizer,ADG (Activity Detection Guidance),TD (Tap Decoupling)}, url = {https://mjeer.journals.ekb.eg/article_77028.html}, eprint = {} } @article { author = {gamal, Aya M. and Ashiba, H. I. and ElBanby, Ghada and Elfishawy, Adel S. and Ismail, Nabil A. and Abd El-Samie, Fathi E.}, title = {Infrared Video Enhancement Using Contrast Limited Adaptive Histogram Equalization and Fuzzy Logic}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {231-236}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77373}, abstract = {Infrared image enhancement is a challenging task due to several factors such as low dynamic range, noise and non-uniformity effect. The non-uniformity is a time-dependent noise that appears owing to the lack of sensor equalization. This paper presents two proposed approaches for infrared video enhancement. The first proposed approach depends on histogram matching. The second one depends on contrast limited adaptive histogram equalization (CLAHE) and fuzzy logic. The performance metrics of average gradient, entropy, contrast improvement factor and Sobel edge magnitude are used for evaluating the obtained results.}, keywords = {IR video enhancement,Histogram matching,Fuzzy Logic,and CLAHE}, url = {https://mjeer.journals.ekb.eg/article_77373.html}, eprint = {} } @article { author = {El Kareh, Zeinab Z. and Essam Emadbouly, Ghada M. El Banby,}, title = {Efficient Fusion Scheme for Multi-Modality Images}, journal = {Menoufia Journal of Electronic Engineering Research}, volume = {28}, number = {ICEEM2019-Special Issue}, pages = {269-274}, year = {2019}, publisher = {Menoufia University, Faculty of Electronic Engineering}, issn = {1687-1189}, eissn = {2682-3535}, doi = {10.21608/mjeer.2019.77377}, abstract = {this paper presents an optimum approach for medical wavelet based Principa1 Component Ana1ysis (PCA) to modify central fusion using different wavelet families and force optimization (MCFO) technique. The proposed MCFO optimized wavelet based fusion algorithm provides the optimum gain parameters values for fusion that achieves the highest image quality and best visualization. The modalities adopted are Magnetic Resonance imaging (MRI), Positron Emission Tomography (PET) as a type of Computed Tomography (CT) modalities. A comparative study is held between the proposed algorithms and the traditional (DWT) fusion rule then evaluated subjectively and objectively with different Evaluation metrics such as entropy, edge intensity, contrast, standard deviation, (PSNR), and average gradient have been adopted for performance evaluation of the proposed method. The obtained results confirm that the proposed method is superior in performance to the DWT and PCA methods individually.}, keywords = {Modified central force optimization,Principa1 Component Ana1ysis, Discrete Wavelet Transform, average gradient}, url = {https://mjeer.journals.ekb.eg/article_77377.html}, eprint = {} }