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Laser-induced etching parameters impact on optical properties of the silicon nanostructures

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Science China(Technological Sciences) 2011年第1期54卷 58-62页

作者： Asmiet RAMIZY Z.HASSAN Khalid omar Nano-Optoelectronics Research and Technology Laboratory School of PhysicsUniversiti Sains Malaysia

Porous silicon (PS) was fabricated by laser-induced etching (LIE) process. The objective of this study is to investigate the selected LIE parameters to control size and shape of nanostructures,which are considered important factors in semiconductor device applications. Photoluminescence output intensity becomes stronger due to the increase in the number of emitted photons on the porous surface. There is a dramatic increase in photoluminescence intensity due to the increase of porosity as a function of laser power density. The increase in electrolyte concentration is an important parameter to accelerate the dissolution reaction on the interface layer between the electrolyte solution and wafer surface. PS spectra displayed a stronger Raman intensity than crystalline bulk Si;also the PS spectrum was shifted and broadened as a function of LIE parameters.

关键词： porous Si laser-induced etching nanostructure optical properties

Vibrating Particles System Algorithm for Solving Classification Problems

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Computer Systems Science & Engineering 2022年第12期43卷 1189-1206页

作者： Mohammad Wedyan omar Elshaweesh Enas Ramadan Ryan Alturki Department of Autonomous Systems Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan Department of Software Engineering Information Technology CollegeAL-Hussein bin Talal UniversityMa’an71111Jordan Department of Computer Science Prince Abdullah Bin Ghazi Faculty of Communication and Information TechnologyAl-Balqa Applied UniversityAl-Salt19117Jordan Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21961Saudi Arabia

Big data is a term that refers to a set of data that,due to its largeness or complexity,cannot be stored or processed with one of the usual tools or applications for data management,and it has become a prominent word in recent years for the massive development of *** immediately thereafter,the term“big data mining”emerged,i.e.,mining from big data even as an emerging and interconnected field of *** is an important stage in data mining since it helps people make better decisions in a variety of situations,including scientific endeavors,biomedical research,and industrial *** probabilistic neural network(PNN)is a commonly used and successful method for handling classification and pattern recognition *** this study,the authors proposed to combine the probabilistic neural network(PPN),which is one of the data mining techniques,with the vibrating particles system(VPS),which is one of the metaheuristic algorithms named“VPS-PNN”,to solve classi-fication problems more *** data set is eleven common benchmark medical datasets from the machine-learning library,the suggested method was *** suggested VPS-PNN mechanism outperforms the PNN,biogeography-based optimization,enhanced-water cycle algorithm(E-WCA)and the firefly algorithm(FA)in terms of convergence speed and classification accuracy.

关键词： Vibrating particles system(VPS) probabilistic neural network(PNN) classification problem data mining

Eigenproblem for p-Laplacian and Nonlinear Elliptic Equation with Nonlinear Boundary Conditions

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Acta Mathematica Sinica,English Series 2015年第4期31卷 659-674页

作者： Berrajaa MOHAMMED Chakrone omar Diyer FATIHA Diyer OKACHA Department of Mathematics Faculty of sciences University Mohamed I

In this article, we study the solvability of nonlinear problem for p-Laplacian with nonlinear boundary conditions. We give some characterization of the first eigenvalue of an intermediary eigenvalne problem as simplicity, isolation and its strict monotonicity. Afterward, we character also the second eigenvalue and its strictly partial monotony. On the other hand, in some sense, we establish the non-resonance below the first and furthermore between the first and second eigenvalues of nonlinear Steklov-Robin.

关键词： Eigenproblem p-Laplacian operator variational method non-resonance problems

Developed Fall Detection of Elderly Patients in Internet of Healthcare Things

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Computers, Materials & Continua 2023年第8期76卷 1689-1700页

作者： omar Reyad Hazem Ibrahim Shehata Mohamed Esmail Karar College of Computing and Information Technology Shaqra UniversityP.O.Box 33Shaqra11961Saudi Arabia Faculty of Computers and Artificial Intelligence Sohag UniversitySohag82524Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt

Falling is among the most harmful events older adults may *** the continuous growth of the aging population in many societies,developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes *** paper presents a new healthcare Internet of Health Things(IoHT)architecture built around an ensemble machine learning-based fall detection system(FDS)for older *** to deep neural networks,the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal *** number of cascaded random forest stages is automatically *** study uses a public dataset of fall detection samples called SmartFall to validate the developed fall detection *** SmartFall dataset is collected based on the acquired measurements of the three-axis accelerometer in a *** scenario in this dataset is classified and labeled as a fall or a *** comparison to the three machine learning models—K-nearest neighbors(KNN),decision tree(DT),and standard random forest(SRF),the proposed ensemble classifier outperformed the other models and achieved 98.4%*** developed healthcare IoHT framework can be realized for detecting fall accidents of older people by taking security and privacy concerns into account in future work.

关键词： Elderly population fall detection wireless sensor networks Internet of health things ensemble machine learning

Machine Learning-based Optimal Framework for Internet of Things Networks

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Computers, Materials & Continua 2022年第6期71卷 5355-5380页

作者： Moath Alsafasfeh Zaid A.Arida omar A.Saraereh Department of Computer Engineering College of EngineeringAl-Hussein Bin Talal UniversityMa’anJordan Abdul Aziz Ghurair School of Advanced Computing(ASAC) LTUCAmmanP11118Jordan Department of Electrical Engineering Engineering FacultyThe Hashemite UniversityZarqa13133Jordan

Deep neural networks(DNN)are widely employed in a wide range of intelligent applications,including image and video ***,due to the enormous amount of computations required by ***,performing DNN inference tasks locally is problematic for resourceconstrained Internet of Things(IoT)*** cloud approaches are sensitive to problems like erratic communication delays and unreliable remote server *** utilization of IoT device collaboration to create distributed and scalable DNN task inference is a very promising *** existing research,on the other hand,exclusively looks at the static split method in the scenario of homogeneous IoT *** a result,there is a pressing need to investigate how to divide DNN tasks adaptively among IoT devices with varying capabilities and resource constraints,and execute the task inference *** major obstacles confront the aforementioned research problems:1)In a heterogeneous dynamic multi-device environment,it is difficult to estimate the multi-layer inference delay of DNN tasks;2)It is difficult to intelligently adapt the collaborative inference approach in real *** a result,a multi-layer delay prediction model with fine-grained interpretability is proposed ***,for DNN inference tasks,evolutionary reinforcement learning(ERL)is employed to adaptively discover the approximate best split *** show that,in a heterogeneous dynamic environment,the proposed framework can provide considerable DNN inference *** the number of devices is 2,3,and 4,the delay acceleration of the proposed algorithm is 1.81 times,1.98 times and 5.28 times that of the EE algorithm,respectively.

关键词： IoT distributed computing neural networks reinforcement learning

Secure Inverted Index Based Search over Encrypted Cloud Data with User Access Rights Management

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Journal of Computer Science & Technology 2019年第1期34卷 133-154页

作者： Fateh Boucenna omar Nouali Samir Kechid M.Tahar Kechadi Security Division Research Center for Scientific and Technical InformationAlgiers 16028Algeria Laboratory of Research in Artificial Intelligence Department of Computer ScienceUniversity of Sciences and Technology H Suari B oumedieneAlgiers 16111Algeria The Insight Centre Unversity College DublinDublinDO4 VIW8Ireland

Cloud computing is a technology that provides users with a large storage space and an enormous computing ***,the outsourced data are often sensitive and confidential,and hence must be encrypted before being ***,classical search approaches have become obsolete and new approaches that are compatible with encrypted data have become a *** privacy reasons,most of these approaches are based on the vector model which is a time consuming process since the entire index must be loaded and exploited during the search process given that the query vector must be compared with each document *** solve this problem,we propose a new method for constructing a secure inverted index using two key techniques,homomorphic encryption and the dummy documents ***,1)homomorphic encryption generates very large ciphertexts which are thousands of times larger than their corresponding plaintexts,and 2)the dummy documents technique that enhances the index security produces lots of false positives in the search *** proposed approach exploits the advantages of these two techniques by proposing two methods called the compressed table of encrypted scores and the double score ***,we exploit a second secure inverted index in order to manage the users'access rights to the ***,in order to validate our approach,we performed an experimental study using a data collection of one million *** experiments show that our approach is many times faster than any other approach based on the vector model.

关键词： searchable encryption cloud computing homomorphic encryption attributeqbased encryption inverted index

An Effective Memory Analysis for Malware Detection and Classification

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Computers, Materials & Continua 2021年第5期67卷 2301-2320页

作者： Rami Sihwail Khairuddin omar Khairul Akram Zainol Ariffin Department of Information Science&Technology Universiti Kebangsaan MalaysiaSelangor43600Malaysia

The study of malware behaviors,over the last years,has received tremendous attention from researchers for the purpose of reducing malware *** of the investigating experiments are performed using either static analysis or behavior ***,recent studies have shown that both analyses are vulnerable to modern malware files that use several techniques to avoid analysis and ***,extracted features could be meaningless and a distraction for malware ***,the volatile memory can expose useful information about malware behaviors and *** addition,memory analysis is capable of detecting unconventional malware,such as in-memory and fileless ***,memory features have not been fully utilized ***,this work aims to present a new malware detection and classification approach that extracts memory-based features from memory images using memory forensic *** extracted features can expose the malware’s real behaviors,such as interacting with the operating system,DLL and process injection,communicating with command and control site,and requesting higher privileges to perform specific *** also applied feature engineering and converted the features to binary vectors before training and testing the *** experiments show that the proposed approach has a high classification accuracy rate of 98.5%and a false positive rate as low as 1.24%using the SVM *** efficiency of the approach has been evaluated by comparing it with other related ***,a new memory-based dataset consisting of 2502 malware files and 966 benign samples forming 8898 features and belonging to six memory types has been created and published online for research purposes.

关键词： Cybersecurity feature selection machine learning malware dataset malware detection memory analysis memory features

STABILITY ANALYSIS OF CAUSAL INTEGRAL EVOLUTION IMPULSIVE SYSTEMS ON TIME SCALES

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Acta Mathematica Scientia 2021年第3期41卷 781-800页

作者： Jiafa XU Bakhtawar PERVAIZ Akbar ZADA Syed omar SHAH School of Mathematical Sciences Chongqing Normal UniversityChongqing 401331China Department of Mathematics University of PeshawarPeshawar 25000Pakistan Department of Physical and Numerical Sciences Qurtuba University of Science and Information Technology PeshawarDera Ismail KhanPakistan

In this article,we present the existence,uniqueness,Ulam-Hyers stability and Ulam-Hyers-Rassias stability of semilinear nonautonomous integral causal evolution impulsive integro-delay dynamic systems on time scales,with the help of a fixed point *** use Gronwall’s inequality on time scales,an abstract Growall’s lemma and a Picard operator as basic tools to develop our main *** overcome some difficulties,we make a variety of *** the end an example is given to demonstrate the validity of our main theoretical results.

关键词： Time scale Ulam-Hyers stability impulses semilinear nonautonomous system Gr?nwall’s inequality dynamic system

From plasma to plasmonics:toward sustainable and clean water production through membranes

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Frontiers of Chemical Science and Engineering 2023年第12期17卷 1809-1836页

作者： Farah Abuhatab omar Khalifa Husam Al Araj Shadi W.Hasan Center for Membranes and Advanced Water Technology(CMAT) Khalifa University of Science and Technology127788 Abu DhabiUnited Arab Emirates Department of Chemical Engineering Khalifa University of Science and Technology127788 Abu DhabiUnited Arab Emirates Department of Chemical and Environmental Engineering Yale UniversityNew HavenCT 06520USA

The increasing demand for potable water is *** resources are scarce and stress is accumulating on other ***,new technologies and novel optimization methods are developed for the existing ***-based processes are among the most efficient methods for water ***,membranes suffer from severe operational problems,namely fouling and temperature *** effects can harm the membrane’s permeability,permeate recovery,and *** mitigate such effects,membranes can be treated through two techniques:plasma treatment(a surface modification technique),and treatment through the use of plasmonic materials(surface and bulk modification).This article showcases plasma-and plasmonic-based treatments in the context of water desalination/*** aims to offer a comprehensive review of the current developments in membrane-based water treatment technologies along with suggested directions to enhance its overall efficiency through careful selection of material and system ***,basic guidelines and strategies are outlined on the different membrane modification techniques to evaluate its ***,we discuss the challenges and future developments about these membrane modification methods.

关键词： water treatment membrane-based process plasma treatment plasma polymerization plasmonic light-to-heat conversion