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Optimization Techniques in University Timetabling Problem:Constraints,Methodologies,Benchmarks,and Open Issues

Computers, Materials & Continua 2023年第3期74卷 6461-6484页

作者： Abeer Bashab Ashraf Osman ibrahim ibrahim Abakar Tarigo Hashem Karan Aggarwal Fadhil Mukhlif Fuad A.Ghaleb Abdelzahir Abdelmaboud Faculty of Computer Science&Information Technology Alzaiem Alazhari University13311KhartoumSudan Faculty Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400SabahMalaysia Department of Computer Science University of SharjahSharjah27272United Arab Emirates Electronic and Communication Engineering Department Maharishi Markandeshwar Deemed to be UniversityMullanaAmbala133207HaryanaIndia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi Malaysia81310JohorMalaysia Department of Information Systems King Khaled UniversityMuhayel61913AseerSaudi Arabia

University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal *** techniques have been used to solve university timetabling problems,and most of them use optimization *** paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling *** comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the *** is noted that meta-heuristic methodologies are widely used in the ***,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling ***,trends and future directions in university timetabling problems are *** paper provides good information for students,researchers,and specialists interested in this area of *** challenges and possibilities for future research prospects are also explored.

关键词： University timetabling timetabling approaches meta-heuristics combinatorial optimization

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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

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Proposed Framework for Detection of Breast Tumors

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Computers, Materials & Continua 2023年第2期74卷 2927-2944页

作者： Mostafa Elbaz Haitham Elwahsh ibrahim Mahmoud El-Henawy Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt

Computer vision is one of the significant trends in computer *** plays as a vital role in many applications,especially in the medical *** detection and segmentation of different tumors is a big challenge in the medical *** proposed framework uses ultrasound images from Kaggle,applying five diverse models to denoise the images,using the best possible noise-free image as input to the U-Net model for segmentation of the tumor,and then using the Convolution Neural Network(CNN)model to classify whether the tumor is benign,malignant,or *** main challenge faced by the framework in the segmentation is the speckle ***’s is a multiplicative and negative issue in breast ultrasound imaging,because of this noise,the image resolution and contrast become reduced,which affects the diagnostic value of this imaging *** result,speckle noise reduction is very vital for the segmentation *** framework uses five models such as Generative Adversarial Denoising Network(DGAN-Net),Denoising U-Shaped Net(D-U-NET),Batch Renormalization U-Net(Br-UNET),Generative Adversarial Network(GAN),and Nonlocal Neutrosophic ofWiener Filtering(NLNWF)for reducing the speckle noise from the breast ultrasound images then choose the best image according to peak signal to noise ratio(PSNR)for each level of *** five used methods have been compared with classical filters such as Bilateral,Frost,Kuan,and Lee and they proved their efficiency according to PSNR in different levels of *** five diverse models are achieved PSNR results for speckle noise at level(0.1,0.25,0.5,0.75),(33.354,29.415,27.218,24.115),(31.424,28.353,27.246,24.244),(32.243,28.42,27.744,24.893),(31.234,28.212,26.983,23.234)and(33.013,29.491,28.556,25.011)forDGAN,Br-U-NET,D-U-NET,GANand NLNWF *** to the value of PSNR and level of speckle noise,the best image passed for segmentation using U-Net and classification usingCNNto detect tumor *** experiments proved

关键词： Breast tumor speckle noise GAN model U-Net model neutrosophic

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Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

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Computers, Materials & Continua 2022年第5期71卷 2599-2616页

作者： Muhammad ibrahim Faisal Jamil YunJung Lee DoHyeun Kim Big Data Research Center Department of Computer Science and StatisticsJeju National UniversityKoreaJeju-si63243Korea Department of Computer Engineering(and Advanced Technology Research Institute) Jeju National UniversityJeju 63243Korea

In recent times,the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security *** IoT has shown wide adoption in various applications including smart cities,healthcare,trade,business,*** these applications,fitness applications have been widely considered for smart fitness *** users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness ***,scheduling such a huge number of requests for fitness exercise is a big ***,the user fitness data is critical thus securing the user fitness data from unauthorized access is also *** overcome these issues,this work proposed a blockchain-based load-balanced task scheduling approach.A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling *** proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’requests and improve resource *** performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection *** obtained results confirm the efficiency of the proposed scheduling *** investigating the performance of the blockchain,various experiments are performed using the Hyperledger Caliper concerning latency,throughput,resource *** Solo approach has shown an improvement of 32%and 26%in throughput as compared to Raft and Solo-Raft approaches *** obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.

关键词： Load balancing resource scheduling task scheduling Internet of things blockchain fitness applications

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Vertex-Edge Degree Based Indices of Honey Comb Derived Network

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Computer Systems Science & Engineering 2022年第1期40卷 247-258页

作者： Muhammad ibrahim Sadia Husain Nida Zahra Ali Ahmad Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya UniversityMultanPakistan College of Computer Sciences and Information Technology Jazan UniversityJazanSaudi Arabia

Chemical graph theory is a branch of mathematics which combines graph theory and *** reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound *** pulled the research community due to its applications in theoretical and organic chemistry since ***,it also increases the interest the mathematicians due to the interesting mathematical structures and problems are *** structure of an interconnection network can be represented by a *** the network,vertices represent the processor nodes and edges represent the links between the processor *** invariants play a vital feature in graph theory and distinguish the structural properties of graphs and *** this paper,we determined the newly introduced topological indices namely,first ve-degree Zagreb?index,first ve-degree Zagreb?index,second ve-degree Zagreb index,ve-degree Randic index,ve-degree atom-bond connectivity index,ve-degree geometric-arithmetic index,ve-degree harmonic index and ve-degree sum-connectivity index for honey comb derived *** the analysis of the quantitative structure property relationships(QSPRs)and the quantitative structure-activity relationships(QSARs),graph invariants are important tools to approximate and predicate the properties of the biological and chemical ***,we give the numerical and graphical representation of our outcomes.

关键词： Honey comb derived network ev-degree topological indices

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Improving Date Fruit Classification Using Cycle GAN-Generated Dataset

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Computer Modeling in Engineering & Sciences 2022年第4期131卷 331-348页

作者： Dina M.ibrahim Nada M.Elshennawy Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computers and Control Engineering Department Faculty of EngineeringTanta UniversityTanta37133Egypt

Dates are an important part of human *** are high in essential nutrients and provide a number of health *** fruits are also known to protect against a number of diseases,including cancer and heart *** fruits have several sizes,colors,tastes,and *** are a lot of challenges facing the date *** of the most significant challenges is the classification and sorting of *** there is no public dataset for date fruits,which is a major limitation in order to improve the performance of convolutional neural networks(CNN)models and avoid the overfitting *** this paper,an augmented date fruits dataset was developed using Deep Convolutional Generative Adversarial Networks(DCGAN)and CycleGAN approach to augment our collected date fruit *** augmentation is required to address the issue of a restricted number of images in our datasets,as well as to establish a balanced *** are three types of dates in our proposed dataset:Sukkari,Ajwa,and *** dataset augmentation,we train our created dataset using ResNet152V2 and CNN models to assess the classification process for our three categories in the *** train these two models,we start with the original ***,the models were trained using the DCGAN-generated dataset,followed by the CycleGAN-generated *** resulting results demonstrated that when using the ResNet152V2model,the CycleGAN-generated dataset had the highest classification performance with 96.8%accuracy,followed by the CNN model with 94.3%accuracy.

关键词： Dates fruits data augmentation DCGAN CycleGAN,deep learning convolution neural networks

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Attribute Weighted Naïve Bayes Classifier

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Computers, Materials & Continua 2022年第4期71卷 1945-1957页

作者： Lee-Kien Foo Sook-Ling Chua Neveen ibrahim Multimedia University Cyberjaya63100Malaysia

The naïve Bayes classifier is one of the commonly used data mining methods for *** its simplicity,naïve Bayes is effective and computationally *** the strong attribute independence assumption in the naïve Bayes classifier makes it a tractable method for learning,this assumption may not hold in real-world *** enhancements to the basic algorithm have been proposed in order to alleviate the violation of attribute independence *** these methods improve the classification performance,they do not necessarily retain the mathematical structure of the naïve Bayes model and some at the expense of computational *** approach to reduce the naïvetéof the classifier is to incorporate attribute weights in the conditional *** this paper,we proposed a method to incorporate attribute weights to naïve *** evaluate the performance of our method,we used the public benchmark *** compared our method with the standard naïve Bayes and baseline attribute weighting *** results show that our method to incorporate attribute weights improves the classification performance compared to both standard naïve Bayes and baseline attribute weighting methods in terms of classification accuracy and F1,especially when the independence assumption is strongly violated,which was validated using the Chi-square test of independence.

关键词： Attribute weighting naïve Bayes Kullback-Leibler information gain classification

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Zinc carnosine-based modified bismuth quadruple therapy vs standard triple therapy for Helicobacter pylori eradication: A randomized controlled study

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World Journal of Clinical Cases 2022年第1期10卷 227-235页

作者： Nour ibrahim Hassan El Said Ali Choukair Faculty of Medical Sciences Lebanese UniversityBeirut 0000Lebanon Department of Biological and Chemical Sciences School of Arts and SciencesLebanese International UniversityBeirut 0000Lebanon Department of Gastroenterology Clemenceau Medical CenterDubai 00000United Arab Emirates

BACKGROUND Helicobacter pylori(***)infection is a worldwide problem with increasing burden on the health sector due to its increasing rate of *** conventional triple therapy(TT)is becoming obsolete with a high failure rate of eradication,necessitating the need for better alternatives or *** To investigate *** eradication rate of TT vs modified bismuth quadruple *** Ninety-two patients with dyspepsia symptoms and positive ^(13)C-urea breath test were randomly assigned to two *** first group(control group)was treated for 14 d using standard TT protocol:Esomeprazole(40 mg twice daily),amoxicillin(1 g twice daily)and clarithromycin(500 mg twice daily).On the other hand,the second group was prescribed a 10-d course of modified bismuth quadruple therapy fortified with zinc carnosine:TT in addition to bismuth subcitrate(240 mg twice daily)and zinc carnosine(75 mg twice daily).A repeated 13C-urea breath test was done 4 wk after the completion of the eradication *** Among the 92 subjects,67.4%were males and 32.6%were *** were no differences in demographic characteristics(age,body mass index,smoking history,previous antibiotics use and ethnicity)between the modified bismuth quadruple therapy group and TT *** eradication rate was higher[93.5%(43/46)]in the modified bismuth quadruple therapy group compared to 69.6%(32/46)in the standard TT group(P=0.003).Of the tested predictor variables,only nationality,smoking and therapy type were statistically *** dizziness,which was recorded in modified bismuth quadruple therapy group,there were no significant differences in side effects between the two *** Ten days of modified bismuth quadruple therapy fortified with zinc carnosine is superior to 14 d of conventional TT in eradicating *** infection,with no additional significant adverse events.

关键词： Helicobacter pylori Polaprezinc Bismuth Peptic ulcer Gastritis Drug Resistance Microbial

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Cluster Representation of the Structural Description of Images for Effective Classification

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Computers, Materials & Continua 2022年第12期73卷 6069-6084页

作者： Yousef ibrahim Daradkeh Volodymyr Gorokhovatskyi Iryna Tvoroshenko Medien Zeghid Department of Computer Engineering and Networks College of Engineering at Wadi AddawasirPrince Sattam Bin Abdulaziz UniversityWadi Addawasir11991Saudi Arabia Department of Informatics Kharkiv National University of Radio ElectronicsKharkiv61166Ukraine Electrical Engineering Department College of Engineering at Wadi AddawasirPrince Sattam Bin Abdulaziz UniversityWadi Addawasir11991Saudi Arabia Electronics and Micro-Electronics Laboratory Faculty of SciencesUniversity of MonastirMonastir5000Tunisia

The problem of image recognition in the computer vision systems is being *** results of the development of efficient classification methods,given the figure of processing speed,based on the analysis of the segment representation of the structural description in the form of a set of descriptors are *** propose three versions of the classifier according to the following principles:“object-etalon”,“object descriptor-etalon”and“vector description of the object-etalon”,which are not similar in level of integration of researched data *** options for constructing clusters over the whole set of descriptions of the etalon database,separately for each of the etalons,as well as the optimal method to compare sets of segment centers for the etalons and object,are *** experimental rating of the efficiency of the created classifiers in terms of productivity,processing time,and classification quality has been realized of the *** proposed methods classify the set of etalons without *** have formed the inference about the efficiency of classification approaches based on segment *** time of image processing according to the developedmethods is hundreds of times less than according to the traditional one,without reducing the accuracy.

关键词： Cluster representation computer vision description relevance descriptor image classification keypoint processing speed vector space

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Price Prediction of Seasonal Items Using Machine Learning and Statistical Methods

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Computers, Materials & Continua 2022年第2期70卷 3473-3489页

作者： Mohamed Ali Mohamed ibrahim Mahmoud El-Henawy Ahmad Salah Faculty of Computers and Informatics Zagazig UniversityZagazigEgypt

Price prediction of goods is a vital point of research due to how common e-commerce platforms *** are several efforts conducted to forecast the price of items using classicmachine learning algorithms and *** models can predict prices of various financial instruments,e.g.,gold,oil,cryptocurrencies,stocks,and second-hand *** these efforts,the literature has no model for predicting the prices of seasonal goods(e.g.,Christmas gifts).In this context,we framed the task of seasonal goods price prediction as a regression ***,we utilized a real online trailer dataset of Christmas gifts and then we proposed several machine learningbased models and one statistical-based model to predict the prices of these seasonal ***,we utilized a real-life dataset of Christmas gifts for the prediction ***,we proposed support vector regressor(SVR),linear regression,random forest,and ridgemodels as machine learningmodels for price ***,we proposed an autoregressive-integrated-movingaverage(ARIMA)model for the same purpose as a statistical-based ***,we evaluated the performance of the proposed models;the comparison shows that the best performing model was the random forest model,followed by the ARIMA model.

关键词： ARIMA machine learning price prediction random forest ridge support vector regressor

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