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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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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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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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Model Agnostic Meta-Learning(MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks

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Computers, Materials & Continua 2024年第5期79卷 2795-2811页

作者： Yasir Maqsood Syed Muhammad Usman Musaed Alhussein Khursheed Aurangzeb Shehzad khalid Muhammad Zubair Department of Creative Technologies Faculty of Computing and Artificial IntelligenceAir UniversityIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Engineering Bahria School of Engineering and Applied SciencesBahria UniversityIslamabad44000Pakistan Laboratory for Neuro&Psychophysiology KU LeuvenLeuven3000Belgium

Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating *** presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease *** advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a *** challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease *** this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data *** study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural *** paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate *** proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens *** future,more diseases can be included for detection along with some other modalities like pests and weed.

关键词： Wheat disease detection deep learning vision transformer graph neural network model agnostic meta learning

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Quantitative and Qualitative Responses of Hydroponic Tomato Production to Different Levels of Salinity

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1311-1323页

作者： khalid A.Al-Gaadi Ahmed M.Zeyada ElKamil Tola Abdullah M.Alhamdan khalid A.M.Ahmed Rangaswamy Madugundu Mohamed K.Edrris Department of Agricultural Engineering College of Food and Agriculture SciencesKing Saud UniversityRiyadh11451Saudi Arabia Precision Agriculture Research Chair Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Chair of Dates Industry&Technology Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Agricultural Research Centre Agricultural Engineering Research Institute(AEnRI)Giza12619Egypt

From economic and nutritional points of view,tomato is,historically,considered one of the most important *** signiﬁcant yield reduction,most commercial cultivars of tomato crops are sensitive to moderate levels of ***,high levels of salt stress can negatively affect the yield and quality of tomato ***,this study was conducted to evaluate the yield and fruit quality of three tomato cultivars(Forester,Ghandowra-F1,and Feisty-Red)cultivated hydroponically,under three different levels of nutrient solution *** of tomato fruits was performed based on quantity(number and weight of fruits,and total fruit yield),physical quality(color andﬁrmness),and chemical quality(refractometric index“Brix”,pH,EC,K^(+),Na^(+),and NO_(3)-).Experiments were conducted using three salinity levels of the nutrient solution with electrical conductivity values(dSm^(-1))of 2.5(control),6.0,and *** showed that the studied tomato cultivars were signiﬁcantly inﬂuenced by high salinity(9.5 dSm^(-1))in comparison to the low(2.5 dSm^(-1))and medium(6.0 dSm^(-1))levels of *** average,the highest fruit weight per plant of 1944.84 g and total fruit yield of 4.42 kgm^(-2) were observed at the low salinity level;however,no signiﬁcant differences were obtained in the two yield factors(single fruit weight and total fruit yield)for the low and medium salinity *** the other hand,a signiﬁcant reduction in tomato yield(31%)was associated with the high salinity level compared to the yield at low and medium salinity *** of physical quality parameters showed highly signiﬁcant differences among all salinity *** average,the maximum value of color change(1.72)was associated with the medium salinity level,and the maximum value ofﬁrmness(9.61 Ncm^(-1))was recorded at the high salinity *** levels and tomato cultivars introduced signiﬁcant differences in chemical quality parameters;however,no signiﬁcant differences in these

关键词： Quality cultivars yield color ﬁrmness brix

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Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 633-659页

作者： Nadeem Ahmed khalid Mohammadani Ali Kashif Bashir Marwan Omar Angel Jones Fayaz Hassan School of Electronic Science Beijing University of Post and TelecommunicationBeijing100086China Department of Computer Science Huanggang Normal UniversityHuanggangChina Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabad502345India Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Information Technology and Management Illinois Institute of TechnologyChicagoUSA College of Computing Capital Technology UniversityLaurelUSA

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes *** the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against *** additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network *** testing of our solution has revealed its remarkable ability to enhance communication in ***,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and *** results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

关键词： Black hole attack IoV vehicular ad hoc network AODV routing protocol

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Video Summarization Approach Based on Binary Robust Invariant Scalable Keypoints and Bisecting K-Means

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Computers, Materials & Continua 2024年第3期78卷 3565-3583页

作者： Sameh Zarif Eman Morad khalid Amin Abdullah Alharbi Wail S.Elkilani Shouze Tang Department of Information Technology Faculty of Computers and InformationMenoufia UniversityMenoufia32511Egypt Department of Artificial Intelligence Faculty of Artificial IntelligenceEgyptian Russian UniversityBader11829Egypt Department of Computer Science Community CollegeKing Saud UniversityRiyadh11362Saudi Arabia College of Applied Computer Science King Saud UniversityAl-Muzahmiya19676Saudi Arabia School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

Due to the exponential growth of video data,aided by rapid advancements in multimedia *** became difficult for the user to obtain information from a large video *** process of providing an abstract of the entire video that includes the most representative frames is known as static video *** method resulted in rapid exploration,indexing,and retrieval of massive video *** propose a framework for static video summary based on a Binary Robust Invariant Scalable Keypoint(BRISK)and bisecting K-means clustering *** current method effectively recognizes relevant frames using BRISK by extracting keypoints and the descriptors from video *** video frames’BRISK features are clustered using a bisecting K-means,and the keyframe is determined by selecting the frame that is most near the cluster *** applying any clustering parameters,the appropriate clusters number is determined using the silhouette *** were carried out on a publicly available open video project(OVP)dataset that contained videos of different *** proposed method’s effectiveness is compared to existing methods using a variety of evaluation metrics,and the proposed method achieves a trade-off between computational cost and quality.

关键词： BRISK bisecting K-mean video summarization keyframe extraction shot detection

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