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LBP–Bilateral Based Feature Fusion for Breast Cancer Diagnosis

Computers, Materials & Continua 2022年第11期73卷 4103-4121页

作者： Yassir Edrees Almalki Maida khalid Sharifa khalid alduraibi Qudsia Yousaf Maryam Zaffar Shoayea Mohessen Almutiri Muhammad Irfan Mohammad Abd Alkhalik Basha alaa khalid alduraibi Abdulrahman Manaa Alamri Khalaf Alshamrani Hassan A.Alshamrani Division of Radiology Department of MedicineMedical CollegeNajran UniversityNajran 61441Saudi Arabia Department of Computer Science and Information Technology Ibadat International UniversityIslamabad44000Pakistan Department of Radiology College of MedicineQassim UniversityBuraidah 52571Saudi Arabia Department of Radiology King Fahad Specialist HospitalBuraydah 52571Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran 61441Saudi Arabia Radiology Department Human Medicine CollegeZagazig UniversityZagazig 44631Egypt Department of Surgery College of MedicineNajran UniversityNajran 61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran 61441Saudi Arabia

Since reporting cases of breast cancer are on the rise all over the *** in regions such as Pakistan,Saudi Arabia,and the United *** methods for the early detection and diagnosis of breast cancer are *** usual diagnosis procedures followed by physicians has been updated with modern diagnostic approaches that include computer-aided support for better *** learning based practices has increased the accuracy and efficiency of medical diagnosis,which has helped save lives of many *** is much research in the field of medical imaging diagnostics that can be applied to the variety of data such as magnetic resonance images(MRIs),mammograms,X-rays,ultrasounds,and histopathological images,but magnetic resonance(MR)and mammogram imaging have proved to present the promising *** proposed paper has presented the results of classification algorithms over Breast Cancer(BC)mammograms from a novel dataset taken from hospitals in the Qassim health cluster of Saudi *** paper has developed a novel approach called the novel spectral extraction algorithm(NSEA)that uses feature extraction and fusion by using local binary pattern(LBP)and bilateral algorithms,as well as a support vector machine(SVM)as a *** NSEA with the SVM classifier demonstrated a promising accuracy of 94%and an elapsed time of 0.68 milliseconds,which were significantly better results than those of comparative experiments from classifiers named Naïve Bayes,logistic regression,K-Nearest Neighbor(KNN),Gaussian Discriminant Analysis(GDA),AdaBoost and Extreme Learning Machine(ELM).ELM produced the comparative accuracy of 94%however has a lower elapsed time of 1.35 as compared to *** has produced a fairly well accuracy of 82%,KNN has a low accuracy of 66%.However Logistic Regression,GDA and Naïve Bayes have produced the lowest accuracies of 47%,43%and 42%.

关键词： Artificial intelligence machine learning breast cancer mammograms supervised learning classification feature fusion

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Breast Cancer Detection in Saudi Arabian Women Using Hybrid Machine Learning on Mammographic Images

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Computers, Materials & Continua 2022年第9期72卷 4833-4851页

作者： Yassir Edrees Almalki Ahmad Shaf Tariq Ali Muhammad Aamir Sharifa khalid alduraibi Shoayea Mohessen Almutiri Muhammad Irfan Mohammad Abd Alkhalik Basha alaa khalid alduraibi Abdulrahman Manaa Alamri Muhammad Zeeshan Azam Khalaf Alshamrani Hassan A.Alshamrani Division of Radiology Department of MedicineMedical CollegeNajran UniversityNajran61441Kingdom of Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Radiology College of MedicineQassim UniversityBuraidah52571Kingdom of Saudi Arabia Department of Radiology King Fahad Specialist HospitalBuraydah52571Kingdom of Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Kingdom of Saudi Arabia Radiology Department Human Medicine CollegeZagazig UniversityZagazig44631Egypt Department of Surgery College of MedicineNajran UniversityNajran61441Kingdom of Saudi Arabia Department of Computer Science Bahauddin Zakariya UniversityMultan66000Pakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Kingdom of Saudi Arabia

Breast cancer(BC)is the most common cause of women’s deaths *** mammography technique is the most important modality for the detection of *** detect abnormalities in mammographic images,the Breast Imaging Reporting and Data System(BI-RADs)is used as a *** correct allocation of BI-RADs categories for mammographic images is always an interesting task,even for *** this work,to detect and classify the mammogram images in BI-RADs,a novel hybrid model is presented using a convolutional neural network(CNN)with the integration of a support vector machine(SVM).The dataset used in this research was collected from different hospitals in the Qassim health cluster of Saudi *** collection of all categories of BI-RADs is one of the major contributions of this *** significant contribution is the development of a hybrid approach through the integration of CNN and *** proposed hybrid approach uses three CNN models to obtain ensemble CNN model *** ensemble model saves the values to integrate them with *** proposed system achieved a classification accuracy,sensitivity,specificity,precision,and F1-score of 93.6%,94.8%,96.9%,96.6%,and 95.7%,*** proposed model achieved better performance compared to previously available methods.

关键词： Breast cancer CNN SVM BIRADS classification

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An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

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Computers, Materials & Continua 2024年第9期80卷 4643-4662页

作者： Zinah khalid Jasim Jasim Sefer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)*** steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least *** contemporary methods of steganography are at best a compromise between these *** this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic *** approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret *** approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale *** ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual *** evaporation is introduced through iterations to avoid stagnation in solution *** levels of pheromone are modified to reinforce successful pixel *** results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of *** approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.

关键词： Steganography steganalysis capacity optimization ant colony algorithm

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Photochemical reactions as synthetic tool for pharmaceutical industries

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Chinese Chemical Letters 2024年第9期35卷 9-31页

作者： Shehla khalid Muhammad Bilal Nasir Rasool Muhammad Imran Department of Chemistry Government College UniversityFaisalabad 38000Pakistan School of Chemistry and Chemical Engineering Shandong UniversityJi’nan 250100China Department of Chemistry Faculty of ScienceKing Khalid UniversityAbha 61413Saudi Arabia

In the quest for new agrochemicals and pharmaceuticals,chemists seek access to reliable and mild synthetic techniques to allow for the systematic modification of chemical structures,exploration of unexplored chemical space,and facilitation of practical synthesis in their search for novel agrochemicals and *** this regard,photocatalytic reactions enabled the synthesis of intricate and more functionalized *** review overviews the developed synthetic methodologies and their utility in the chemical synthesis of *** review also offers in-depth insights into contemporary photoredox reactions such as allylic additions,cyclization,reductive cross-coupling,C–H activation,ring opening,oxidative cross-coupling,dehydrogenation,desulphonation,and *** provides a positive outlook for the promising future of this field.

关键词： Photocatalyst Photochemical reactions Drugs Natural products Late-stage functionalization

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Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

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Computers, Materials & Continua 2024年第7期80卷 61-103页

作者： Ahmed khalid Rana Asif Rehman Byung-Seo Kim Department of Computer Science FAST School of ComputingNational University of Computer and Emerging SciencesLahore54000Pakistan Department of Software and Communications Engineering Hongik UniversitySejong City30016Republic of Korea

Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

关键词： Content centric network Internet of Things mobile ad hoc network named data network vehicular ad hoc network

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Hydrometallurgy two stage process for preparation of (Nd,La,Ce)_(2)O_(3) from end-of-life NiMH batteries

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Journal of Rare Earths 2024年第2期42卷 415-423,I0007页

作者： Karim Tanji khalid Ouzaouit Mohamed Belghiti Isam Lamsayety Hakim Faqir Intissar Benzakour Centre de recherche REMINEX-Groupe MANAGEM MarrakechMorocco

The present work aims to investigate the recovery of light rare earth elements(LREEs) oxides from end-oflife NiMH batteries using a hydro metallurgical process followed by effective *** operational leaching parameters such as phosphoric acid concentration,temperature,and the solid-liquid ratio were first optimized by Box-Behnken *** results reveal that under optimum conditions([H_(3)PO_(4)]=2 mol/L,T=80℃,and S/L=1:10 g/mL) the leaching efficiencies of Ni,Co reach 98.1% and99.3%.While La,Ce,and Nd elements remain in the leaching residue as(La,Ce,Nd)PO_(4) with yields of 98.2%,98.6%,and 99.6% for La,Ce,and Nd,***,the(La,Ce,Nd)PO_(4) is leached with HCl acid,then the rare earth oxalate was precipitated using oxalic acid at a pH of 1.8 and then the product was calcined at 800℃ for 2 h in order to synthesize the(Nd,La,Ce)_(2)O_(3).The analysis using scanning electron microscopy(SEM) coupled with energy dispersive X-ray spectroscopy(EDX) confirms the homogeneity of(Nd,La,Ce)_(2)O_(3) particles that have two morphologies,i.e.,flower and sticks with a particle size between 3and 6 μ*** unit cell parameters of(Nd,La,Ce)_(2)O_(3) were calculated after Rietveld refinement of the XRD patterns,in the space group of Fm-3m are a=b=c=0.57921 nm and the volume equal to 0.194322 nm^(3).

关键词： NiMH batteries Hydrometallurgical process Leaching Phosphoric acid Box-Behnken Light rare earth oxides

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An extensive analytical and numerical study of the generalized q-deformed Sinh-Gordon equation

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Journal of Ocean Engineering and Science 2024年第3期9卷 232-239页

作者： khalid K.Ali Abdel-Haleem Abdel-Aty Mathematics Department Faculty of ScienceAl-Azhar UniversityNasr-CityCairoEgypt Department of Physics College of SciencesUniversity of BishaPO Box 344Bisha 61922Saudi Arabia Physics Department Faculty of ScienceAl-Azhar UniversityAssiut 71524Egypt

In this paper,the q-deformed Sinh-Gordon equation is solved analytically using a new general form based on the extended tanh *** numerical solutions of the equation is obtained using a b-spline finite element ***,we present numerous figures to demonstrate the various solitons propagation *** type of equation has not been previously dealt with in such ways,whether analytical or *** study is very useful in studying several physical systems that have lost their symmetry.

关键词： q-Deformed equation Solitos solutions The extended tanh method Finite element method q-Calculus

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Mixed plastics waste valorization to high-added value products via thermally induced phase separation and spin-casting

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Green Energy & Environment 2024年第10期9卷 1627-1640页

作者： Junaid Saleem Moghal Zubair khalid Baig Usman Bin Shahid Rafael Luque Gordon McKay Division of Sustainable Development College of Science and EngineeringHamad Bin Khalifa University Center for Advanced Materials Qatar University Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Universidad ECOTEC

Plastic waste is an underutilized resource that has the potential to be transformed into value-added ***,its chemical diversity leads to cost-intensive sorting techniques,limiting recycling and upcycling ***,we report an open-loop recycling method to produce graded feedstock from mixed polyolefins waste,which makes up 60%of total plastic *** method uses heat flow scanning to quantify the composition of plastic waste and resolves its compatibility through controlled *** resulting feedstock is then used to synthesize blended pellets,porous sorbents,and superhydrophobic coatings via thermally induced phase separation and *** hybrid approach broadens the opportunities for reusing plastic waste,which is a step towards creating a more circular economy and better waste management practices.

关键词： Plastic waste Valorization Superhydrophobic coatings Blended pellets Porous materials Sorbents

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Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma Mohammad khalid Imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

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Deep Learning Approach for Hand Gesture Recognition:Applications in Deaf Communication and Healthcare

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Computers, Materials & Continua 2024年第1期78卷 127-144页

作者： Khursheed Aurangzeb khalid Javeed Musaed Alhussein Imad Rida Syed Irtaza Haider Anubha Parashar Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Kingdom of Saudi Arabia Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Laboratory Biomechanics and Bioengineering University of Technology of CompiegneCompiegne60200France Department of Computer Science and Engineering Manipal University JaipurJaipur303007India

Hand gestures have been used as a significant mode of communication since the advent of human *** facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free *** technology is pivotal in healthcare and communication for the deaf *** significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature ***,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and ***,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer *** proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,*** results demonstrate the effectiveness of CNN as a promising HGRoc *** findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.

关键词： Computer vision deep learning gait recognition sign language recognition machine learning

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