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Innovative Hetero-Associative Memory Encoder(HAMTE)for Palmprint Template Protection

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Computer Systems Science & Engineering 2023年第7期46卷 619-636页

作者： eslam Hamouda Mohamed Ezz Ayman Mohamed mostafa Murtada K.Elbashir Meshrif Alruily Mayada Tarek College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia College of Computers and Informatics Mansoura University35516Egypt

Many types of research focus on utilizing Palmprint recognition in user identification and *** Palmprint is one of biometric authentication(something you are)invariable during a person’s life and needs careful protection during enrollment into different biometric authentication *** and irreversibility are critical requirements for securing the Palmprint template during enrollment and *** paper proposes an innovative HAMTE neural network model that contains Hetero-Associative Memory for Palmprint template translation and projection using matrix multiplication and dot product multiplication.A HAMTE-Siamese network is constructed,which accepts two Palmprint templates and predicts whether these two templates belong to the same user or different *** HAMTE is generated for each user during the enrollment phase,which is responsible for generating a secure template for the enrolled *** proposed network secures the person’s Palmprint template by translating it into an irreversible template(different features space).It can be stored safely in a trusted/untrusted third-party authentication system that protects the original person’s template from being *** results are conducted on the CASIA database,where the proposed network achieved accuracy close to the original accuracy for the unprotected Palmprint *** recognition accuracy deviated by around 3%,and the equal error rate(EER)by approximately 0.02 compared to the original data,with appropriate performance(approximately 13 ms)while preserving the irreversibility property of the secure ***,the brute-force attack has been analyzed under the new Palmprint protection scheme.

关键词： Palmprint recognition hetero-associative memory neural network and Siamese network

Improved Siamese Palmprint Authentication Using Pre-Trained VGG16-Palmprint and Element-Wise Absolute Difference

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Computer Systems Science & Engineering 2023年第8期46卷 2299-2317页

作者： Mohamed Ezz Waad Alanazi Ayman Mohamed mostafa eslam Hamouda Murtada K.Elbashir Meshrif Alruily College of Computers and Information Sciences Jouf UniversitySakaka72314Saudi Arabia

Palmprint identification has been conducted over the last two decades in many biometric ***-dimensional data with many uncorrelated and duplicated features remains difficult due to several computational complexity *** paper presents an interactive authentication approach based on deep learning and feature selection that supports Palmprint *** proposed model has two stages of learning;the first stage is to transfer pre-trained VGG-16 of ImageNet to specific features based on the extraction *** second stage involves the VGG-16 Palmprint feature extraction in the Siamese network to learn Palmprint *** proposed model achieves robust and reliable end-to-end Palmprint authentication by extracting the convolutional features using VGG-16 Palmprint and the similarity of two input Palmprint using the Siamese *** second stage uses the CASIA dataset to train and test the Siamese *** suggested model outperforms comparable studies based on the deep learning approach achieving accuracy and EER of 91.8%and 0.082%,respectively,on the CASIA left-hand images and accuracy and EER of 91.7%and 0.084,respectively,on the CASIA right-hand images.

关键词： Palmprint authentication transfer learning feature extraction classification VGG-16 and Siamese network

A Transfer Learning Approach Based on Ultrasound Images for Liver Cancer Detection

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Computers, Materials & Continua 2023年第6期75卷 5105-5121页

作者： Murtada K.Elbashir Alshimaa Mahmoud Ayman Mohamed mostafa eslam Hamouda Meshrif Alruily Sadeem M.Alotaibi Hosameldeen Shabana Mohamed Ezz College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia Department of Information Systems MCI AcademyCairoEgypt College of Medicine Shaqra UniversityShaqraKSA Faculty of Medicine Al Azhar UniversityCairoEgypt

The convolutional neural network(CNN)is one of the main algorithms that is applied to deep transfer learning for classifying two essential types of liver lesions;Hemangioma and hepatocellular carcinoma(HCC).Ultrasound images,which are commonly available and have low cost and low risk compared to computerized tomography(CT)scan images,will be used as input for the model.A total of 350 ultrasound images belonging to 59 patients are *** number of images with HCC is 202 and 148,*** images were collected from ultrasound ***(28 Hemangiomas patients and 11 HCC patients),the department of radiology,the University of Washington(7 HCC patients),the Atlas of ultrasound Germany(3 HCC patients),and Radiopedia and others(10 HCC patients).The ultrasound images are divided into 225,52,and 73 for training,validation,and testing.A data augmentation technique is used to enhance the validation *** proposed an approach based on ensembles of the best-selected deep transfer models from the on-the-shelf models:VGG16,VGG19,DenseNet,Inception,InceptionResNet,ResNet,and *** tuning both the feature extraction and the classification layers,the best models are *** accuracy is used for model tuning and *** accuracy,sensitivity,specificity and AUROC are used to evaluate the *** experiments are concluded in five *** first stage aims to evaluate the base model performance by training the on-the-shelf *** best accu-racy obtained in the first stage is 83.5%.In the second stage,we augmented the data and retrained the on-the-shelf models with the augmented *** best accuracy we obtained in the second stage was 86.3%.In the third stage,we tuned the feature extraction layers of the on-the-shelf *** best accuracy obtained in the third stage is 89%.In the fourth stage,we fine-tuned the classification layer and obtained an accuracy of 93%as the best *** the fifth stage,we applied the en

关键词： Transfer learning liver lesions ultrasound images and convolutional neural network

Microalgae-based wastewater treatment:Mechanisms,challenges,recent advances,and future prospects

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Environmental Science and Ecotechnology 2023年第1期13卷 5-22页

作者： Abdallah Abdelfattah Sameh Samir Ali Hassan Ramadan eslam Ibrahim El-Aswar Reham Eltawab Shih-Hsin Ho Tamer Elsamahy Shengnan Li mostafa M.El-Sheekh Michael Schagerl Michael Kornaros Jianzhong Sun School of Environment and Safety Engineering Jiangsu UniversityZhenjiang212013PR China Department of Public Works Engineering Faculty of EngineeringTanta UniversityTanta31511Egypt Biofuels Institute School of the Environment and Safety EngineeringJiangsu UniversityZhenjiang212013PR China Botany Department Faculty of ScienceTanta UniversityTanta31527Egypt Central Laboratories for Environmental Quality Monitoring(CLEQM) National Water Research Center(NWRC)El-Kanater13621QalyubiyahEgypt State Key Laboratory of Urban Water Resource and Environment School of EnvironmentHarbin Institute of TechnologyHarbin150090PR China Department of Functional and Evolutionary Ecology University of ViennaDjerassiplatz 1A-1030 ViennaAustria Laboratory of Biochemical Engineering&Environmental Technology(LBEET) Department of Chemical EngineeringUniversity of Patras1 Karatheodori Str.University Campus26504PatrasGreece

The rapid expansion of both the global economy and the human population has led to a shortage of water resources suitable for direct human *** a result,water remediation will inexorably become the primary focus on a global *** can be grown in various types of wastewaters(WW).They have a high potential to remove contaminants from the effluents of industries and urban *** review focuses on recent advances on WW remediation through microalgae *** has already been paid to microalgae-based wastewater treatment(WWT)due to its low energy requirements,the strong ability of microalgae to thrive under diverse environmental conditions,and the potential to transform WW nutrients into high-value *** turned out that microalgae-based WWT is an economical and sustainable ***,different types of toxins are removed by microalgae through biosorption,bioaccumulation,and biodegradation *** are toxins from agricultural runoffs and textile and pharmaceutical industrial *** have the potential to mitigate carbon dioxide and make use of the micronutrients that are present in the *** review paper highlights the application of microalgae in WW remediation and the remediation of diverse types of pollutants commonly present in WW through different mechanisms,simultaneous resource recovery,and efficient microalgae-based co-culturing systems along with bottlenecks and prospects.

关键词： Bioremediation Wastewater treatment Environmental applications Microalgae Co-culturing

Multi-Node Fault-Tolerant Two-Cell Real-Time S2A Network

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Intelligent Control and Automation 2016年第2期7卷 25-38页

作者： Merna N. Abou Eita mostafa W. Hussein Ahmed A. Ibrahim Shereen S. Abouelazayem Mennatallah A. Morsi eslam A. Moustafa Hassan H. Halawa Ramez M. Daoud Hassanein H. Amer Hany M. ElSayed Electronics and Communications Engineering Department The American University in Cairo New Cairo Egypt Electronics and Communications Engineering Department Cairo University Giza Egypt

This paper presents a novel fault-tolerant networked control system architecture consisting of two cells working in-line. This architecture is fault-tolerant at the level of the controllers as well as the sensors. Each cell is based on the sensor-to-actuator approach and has an additional supervisor node. It is proven, via analysis as well as OMNeT++ simulations that the production line succeeds in meeting all control system requirements with no dropped or over-delayed packets. A reliability analysis is then undertaken to quantitatively estimate the increase in reliability due to the introduction of fault-tolerance.

关键词： Fault-Tolerance NCS S2A In-Line TMR Ethernet OMNeT++ Reliability