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Hyper-Parameter Optimization of Semi-Supervised GANs Based-Sine Cosine algorithm for Multimedia Datasets

Computers, Materials & Continua 2022年第10期73卷 2169-2186页

作者： Anas al-Ragehi Said Jadid Abdulkadir Amgad Muneer Safwan Sadeq qasem al-tashi Computer and Information Sciences Department Universiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Centre for Research in Data Science(CERDAS) Universiti Teknologi PETRONASSeri Iskandar32610Malaysia Mechanical Engineering Department Universiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Department of Imaging Physics The University of Texas MD Anderson Cancer CenterHoustonTXUSA University of albaydha AlbaydhaYemen

Generative Adversarial Networks(GANs)are neural networks that allow models to learn deep representations without requiring a large amount of training ***-Supervised GAN Classifiers are a recent innovation in GANs,where GANs are used to classify generated images into real and fake and multiple classes,similar to a general multi-class ***,GANs have a sophisticated design that can be challenging to *** is because obtaining the proper set of parameters for all models-generator,discriminator,and classifier is *** a result,training a single GAN model for different datasets may not produce satisfactory ***,this study proposes an SGAN model(Semi-Supervised GAN Classifier).First,a baseline model was *** model was then enhanced by leveraging the Sine-Cosine algorithm and Synthetic Minority Oversampling Technique(SMOTE).SMOTE was used to address class imbalances in the dataset,while Sine Cosine algorithm(SCA)was used to optimize the weights of the classifier *** optimal set of hyperparameters(learning rate and batch size)were obtained using grid manual *** well-known benchmark datasets and a set of evaluation measures were used to validate the proposed *** proposed method was then compared against existing models,and the results on each dataset were recorded and demonstrated the effectiveness of the proposed *** proposed model successfully showed improved test accuracy scores of 1%,2%,15%,and 5%on benchmarking multimedia datasets;Modified National Institute of Standards and Technology(MNIST)digits,Fashion MNIST,Pneumonia Chest X-ray,and Facial Emotion Detection Dataset,respectively.

关键词： Generative adversarial networks semi-supervised generative adversarial network sine-cosine algorithm SMOTE principal component analysis grid search

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Type 2 Diabetes Risk Prediction Using Deep Convolutional Neural Network Based-Bayesian Optimization

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Computers, Materials & Continua 2023年第5期75卷 3223-3238页

作者： alawi alqushaibi Mohd Hilmi Hasan Said Jadid Abdulkadir Amgad Muneer Mohammed Gamal qasem al-tashi Shakirah Mohd Taib Hitham alhussian Computer&Information Sciences Universiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Centre for Research in Data Science(CERDAS) Universiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Department of Imaging Physics University of Texas MD Anderson CancerHoustonTXUSA

Diabetes mellitus is a long-term condition characterized by *** could lead to plenty of *** to rising morbidity in recent years,the world’s diabetic patients will exceed 642 million by 2040,implying that one out of every ten persons will be *** is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’*** to its rapid development,deep learning(DL)was used to predict numerous ***,DLmethods still suffer from their limited prediction performance due to the hyperparameters selection and parameters ***,the selection of hyper-parameters is critical in improving classification *** study presents Convolutional Neural Network(CNN)that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm(BOA)has been employed for hyperparameters selection and parameters *** issues have been investigated and solved during the experiment to enhance the *** first is the dataset class imbalance,which is solved using Synthetic Minority Oversampling Technique(SMOTE)*** second issue is the model’s poor performance,which has been solved using the Bayesian optimization *** findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%,F1-score of 0.88.6,andMatthews Correlation Coefficient(MCC)of 0.88.6.

关键词： Type 2 diabetes diabetes mellitus convolutional neural network Bayesian optimization SMOTE

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Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection

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Computer Systems Science & Engineering 2023年第11期47卷 1937-1966页

作者： qasem al-tashi Tareq M Shami Said Jadid Abdulkadir Emelia Akashah Patah Akhir Ayed alwadain Hitham alhussain alawi alqushaibi Helmi MD Rais Amgad Muneer Maliazurina B.Saad Jia Wu Seyedali Mirjalili Department of Imaging Physics The University of Texas MD Anderson Cancer CenterHoustonTXUSA Department of Electronic Engineering University of YorkYorkYO105DDUK Computer and Information Sciences Department Universiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Computer Science Department Community CollegeKing Saud UniversityRiyadhP.O.Box 145111Saudi Arabia Torrens University Australia BrisbaneQLDAustralia Yonsei Frontier Lab Yonsei UniversitySeoulKorea University Research and Innovation Center Obuda UniversityBudapest1034Hungary

The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be *** it is a multi-objective problem,current methods tend to treat feature selection as a single-objective optimization *** paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase(LMuMOGWO)for tackling feature selection *** proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer(MOGWO):a Lévy flight and a mutation *** Lévy flight,a type of random walk with jump size determined by the Lévy distribution,enhances the global search capability of MOGWO,with the objective of maximizing classification accuracy while minimizing the number of selected *** mutation operator is integrated to add more informative features that can assist in enhancing classification *** feature selection is a binary problem,the continuous search space is converted into a binary space using the sigmoid *** evaluate the classification performance of the selected feature subset,the proposed approach employs a wrapper-based Artificial Neural Network(ANN).The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO,BMOGWO-S(based sigmoid),BMOGWO-V(based tanh)as well as Non-dominated Sorting Genetic algorithm II(NSGA-II)and Multi-objective Particle Swarm Optimization(BMOPSO).The results demonstrate that the proposed LMuMOGWO approach is capable of successfully evolving and improving a set of randomly generated solutions for a given optimization ***,the proposed approach outperforms existing approaches in most cases in terms of classification error rate,feature reduction,and computational cost.

关键词： Feature selection multi-objective optimization grey wolf optimizer Lévy flight mutation classification

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Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

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Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah Md.Siraj Bander ali Saleh al-rimy Sultan Noman qasem Tawfik al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** security solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection Systems(CIDS).Existing adaptive CIDS solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall security *** address these challenges,we propose ACIDS(Adaptive Cloud Intrusion Detection System)-*** novel Adaptive CIDS framework leverages the Pruned Exact Linear Time(PELT)algorithm and a Support Vector Machine(SVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature Selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HSO-SU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)Surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential security threats with improved precision compared to existing approaches.(3)Training Set:Labeled network traffic data forms the training set used to train the SVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing Set:The testing set evaluates ACIDS-PELT’s performance by measuring its accuracy,precision,and recall in detecting security threats within the cloud *** evaluate the performance of ACIDS-PELT using the NSL-KDD benchmark *** results demonstrate that ACIDS-PELT outperf

关键词： Adaptive cloud IDS harmony search distributed denial of service(DDoS) PELT machine learning SVM ISOTCID NSL-KDD

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An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

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Computers, Materials & Continua 2022年第1期70卷 1721-1747页

作者： Sultan Noman qasem Mohammed al-Sarem Faisal Saeed Computer Science Department College of Computer and Information SciencesAl Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Computer Science Department Faculty of Applied ScienceTaiz UniversityTaiz6803Yemen College of Computer Science and Engineering Taibah UniversityMedinaSaudi Arabia Information System Department Saba’a Region UniversityMareebYemen

Rumors regarding epidemic diseases such as COVID 19,medicines and treatments,diagnostic methods and public emergencies can have harmful impacts on health and political,social and other aspects of people’s lives,especially during emergency situations and health *** huge amounts of content being posted to social media every second during these situations,it becomes very difficult to detect fake news(rumors)that poses threats to the stability and sustainability of the healthcare sector.A rumor is defined as a statement for which truthfulness has not been *** COVID 19,people found difficulty in obtaining the most truthful news easily because of the huge amount of unverified information on social *** methods have been applied for detecting rumors and tracking their sources for COVID 19-related ***,very few studies have been conducted for this purpose for the Arabic language,which has unique ***,this paper proposes a comprehensive approach which includes two phases:detection and *** the detection phase of the study carried out,several standalone and ensemble machine learning methods were applied on the Arcov-19 dataset.A new detection model was used which combined two models:The Genetic algorithm Based Support Vector Machine(that works on users’and tweets’features)and the stacking ensemble method(that works on tweets’texts).In the tracking phase,several similarity-based techniques were used to obtain the top 1%of similar tweets to a target tweet/post,which helped to find the source of the *** experiments showed interesting results in terms of accuracy,precision,recall and F1-Score for rumor detection(the accuracy reached 92.63%),and showed interesting findings in the tracking phase,in terms of ROUGE L precision,recall and F1-Score for similarity techniques.

关键词： Rumor detection rumor tracking similarity techniques COVID-19 social media analytics

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On Nonlinear Conformable Fractional Order Dynamical System via Differential Transform Method

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1457-1472页

作者： Kamal Shah Thabet Abdeljawad Fahd Jarad qasem al-Mdallal Department of Mathematics and Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Mathematics University of MalakandChakdara Dir(L)Khyber Pakhtunkhwa18000Pakistan Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Mathematics Faculty of Arts and Sciences莂nkaya UniversityAnkara06790Turkey Department of Mathematical Sciences UAE UniversityAl-Ain15551United Arab Emirates

This article studies a nonlinear fractional order Lotka-Volterra prey-predator type dynamical *** the proposed study,we consider the model under the conformable fractional order derivative(CFOD).We investigate the mentioned dynamical system for the existence and uniqueness of at least one ***,Schauder and Banach fixed point theorems are utilized to prove our ***,an algorithm for the approximate analytical solution to the proposed problem has been *** this regard,the conformable fractional differential transform(CFDT)technique is used to compute the required results in the form of a *** Matlab-16,we simulate the series solution to illustrate our results ***,a comparison of our solution to that obtained for the Caputo fractional order derivative via the perturbation method is given.

关键词： Prey predator model existence results conformable fractional differential transform

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A systematic review:Detecting phishing websites using data mining models

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Intelligent and Converged Networks 2023年第4期4卷 326-341页

作者： Dina Jibat Sarah Jamjoom qasem Abu al-Haija Abdallah Qusef the Department of Business Intelligence Technology Princess Sumaya University for TechnologyAmman 11941Jordan the Department of Cybersecurity Princess Sumaya University for TechnologyAmman 11941Jordan the Department of Software Engineering Princess Sumaya University for TechnologyAmman 11941Jordan

As internet technology use is on the rise globally,phishing constitutes a considerable share of the threats that may attack individuals and organizations,leading to significant losses from personal and confidential information to substantial financial ***,much research has been dedicated in recent years to developing effective and robust mechanisms to enhance the ability to trace illegitimate web pages and to distinguish them from non-phishing sites as accurately as *** to conclude whether a universally accepted model can detect phishing attempts with 100%accuracy,we conduct a systematic review of research carried out in 2018-2021 published in well-known journals published by Elsevier,IEEE,Springer,and *** researchers studied different Data Mining(DM)algorithms,some of which created a whole new model,while others compared the performance of several *** studies combined two or more algorithms to enhance the detection *** reveal that while most algorithms achieve accuracies higher than 90%,only some specific models can achieve 100%accurate results.

关键词： phishing data mining machine learning algorithm classification

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Cooperative Relay Networks Based on the OAM Technique for 5G Applications

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Computer Systems Science & Engineering 2023年第3期44卷 1911-1919页

作者： Mohammad alkhawatrah Ahmad alamayreh Nidal qasem Department of Electronics and Communications Engineering Al-Ahliyya Amman UniversityAmmanJordan

Orbital Angular Momentum(OAM)is an intrinsic property of electro-magnetic *** research has been witnessed in the last decades aiming at exploiting the OAM wave property in different areas in radio and *** pro-mising area of particular interest is to enhance the efficiency of the available communications ***,adopting OAM-based solutions is not priceless as these suffer from wave divergence especially when the OAM order is *** shall limit the practical communications distance,especially in the radio *** this paper,we propose a cooperative OAM relaying system consisting of a source,relay,and *** help the source to transmit packets to the destination by providing an alternative connection between source and *** cooperative solution aims on the one hand,through best-path selection,on increasing the communications *** the other hand,through the parallel transmission orders allowed by OAM carrying waves,the system could raise its total transmission *** results show that combining a cooperative relay with OAM improves the system throughput compared to using each element *** addition,the proposed cooperative relaying OAM out-performs the cooperative relaying non-orthogonal multiple access scheme,which is a key spectrally efficient technique used in 5G technology.

关键词： 5G cooperative network OAM relay throughput

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Improved Beam Steering Method Using OAM Waves

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Computer Systems Science & Engineering 2023年第7期46卷 417-431页

作者： Nidal qasem Ahmad alamayreh Department of Electronics and Communications Engineering Al-Ahliyya Amman UniversityAmmanJordan

Orbital Angular Momentum(OAM)is an intrinsic feature of electromagnetic waves which has recently found many applications in several areas in radio and *** this paper,we use OAM wave characteristics to present a simple method for beam steering over both elevation and azimuth *** design overcomes some limitations of traditional steering methods,such as limited dynamic range of steering,the design complexity,bulky size of the steering structure,the limited bandwidth of operation,and low *** on OAM wave characteristics,the proposed steering method avoids design complexities by adopting a simple method for generating the OAM-carrying *** waves are generated by an array of Planar Circular Dipole(PCD)*** elements are designed to cover a wide bandwidth range between 3 and 30 *** transmitting array shows an enhanced gain value from 8.5 dBi to almost 11.5 dBi at the broadside *** the enhanced PCD-based OAM generation,the novelty of the design lies in a new method of beam *** steering is then performed by controlling the electrical feeding of the PCD elements;the beam azimuthal location is managed by turning off some of the PCD elements,while the elevation is determined by changing the gradient phase of excitation for the turned-on PCD *** analysis of the steering method is carried out by finding the mathematical model of the system and the generated *** performance has been verified through numerical simulators.

关键词： Antenna array bandwidth beam steering orbital angular momentum

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Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

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Computers, Materials & Continua 2023年第2期74卷 2415-2430页

作者： Narongsak Yotha Qusain Hiader Zulqurnain Sabir Muhammad Asif Zahoor Raja Salem Ben Said qasem al-Mdallal Thongchai Botmart Wajaree Weera Department of Applied Mathematics and Statistics Rajamangala University of Technology IsanNakhon Ratchasima30000Thailand Department of Mathematics University of GujratGujrat50700Pakistan Department of Mathematics Hazara UniversityMansehra21120Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliouYunlin64002Taiwan Department of Mathematical Science College of ScienceUnited Arab Emirates UniversityAl AinAbu DhabiUAE Department of Mathematics Faculty of ScienceKhon Kaen UniversityKhon Kaen40002Thailand

This study aims to solve the nonlinear fractional-order mathematical model(FOMM)by using the normal and dysregulated bone remodeling of themyeloma bone disease(MBD).For themore precise performance of the model,fractional-order derivatives have been used to solve the disease model *** FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts(OC)and bone formation or osteoblasts(OB).The connections of OC and OB are represented by a nonlinear differential system based on the cellular components,which depict stable fluctuation in the usual bone case and unstable fluctuation through the *** myeloma causes by increasing the OC and reducing the osteoblasts,resulting in net bone waste the tumor *** solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation(LVMBP)neural networks(NN),i.e.,*** mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the *** static structural performances are 82%for investigation and 9%for both learning and *** performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton *** accomplish the capability,steadiness,accuracy,and ability of the LVMBPNN,the performances of the error histograms(EHs),mean square error(MSE),recurrence,and state transitions(STs)will be provided.

关键词： Bone remodeling fractional-order myeloma disease artificial neural networks levenberg-marquardt backpropagation population cell dynamics

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