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Cervical Cancer Prediction Empowered with Federated Machine Learning

Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.khan khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

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Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq khan Muhammad Ramzan Mudassar Raza Muhammad Attique khan Khalid Iqbal Taerang Kim Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

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Thermal analysis of the Rindler-Schwarzschild black hole via corrected entropy

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Communications in Theoretical Physics 2024年第9期76卷 95-106页

作者： Allah Ditta Xia Tiecheng Riasat ali aliÖvgün Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai200444China Physics Department Eastern Mediterranean UniversityFamagusta99628 North Cyprus via Mersin 10Turkiye

In this study,we investigate the thermodynamic characteristics of the Rindler–Schwarzschild black hole *** analysis encompasses the examination of energy emission,Gibbs free energy,and thermal *** calculate various quantities such as the Hawking temperature,geometric mass,and heat capacity to assess the local and global thermodynamic *** temperature of the black hole is determined using the first law of thermodynamics,while the energy emission rate is evaluated as *** computing the Gibbs free energy,we explore the phase transition behavior exhibited by Rindler–Schwarzschild black hole,specifically examining the swallowing ***,we derive the corrected entropy to investigate the influence of thermal fluctuations on small and large black ***,we compare the impact of correction terms on the thermodynamic system by comparing the results obtained for large black holes and small black holes.

关键词： black holes thermodynamics thermal fluctuations heat capacity Gibbs free energy energy emission Rindler–Schwarzschild black hole

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Adipose-derived regenerative therapies for the treatment of knee osteoarthritis

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World Journal of Stem Cells 2024年第4期16卷 324-333页

作者： Ilias E Epanomeritakis Wasim S khan Division of Trauma and Orthopaedic Surgery Addenbrooke’s HospitalCambridge University Hospitals NHS Foundation TrustCambridge CB20QQUnited Kingdom Division of Trauma and Orthopaedic Surgery Department of SurgeryUniversity of CambridgeCambridge CB20QQUnited Kingdom

Knee osteoarthritis is a degenerative condition with a significant disease burden and no disease-modifying *** treatment ultimately requires joint *** capable of regenerating cartilage could significantly reduce financial and clinical *** regenerative potential of mesenchymal stromal cells(MSCs)has been extensively studied in the context of knee *** has yielded promising results in human studies,and is likely a product of immunomodulatory and chondroprotective biomolecules produced by MSCs in response to ***-derived MSCs(ASCs)are becoming increasingly popular owing to their relative ease of isolation and high proliferative *** vascular fraction(SVF)and micro-fragmented adipose tissue(MFAT)are produced by the enzymatic and mechanical disruption of adipose tissue,*** avoids expansion of isolated ASCs ex vivo and their composition of heterogeneous cell populations,including immune cells,may potentiate the reparative function of *** this editorial,we comment on a multicenter randomized trial regarding the efficacy of MFAT in treating knee *** discuss the study’s findings in the context of emerging evidence regarding adipose-derived regenerative *** underlying mechanism of action of ASCs is proposed while drawing important distinctions between the properties of isolated ASCs,SVF,and MFAT.

关键词： Knee osteoarthritis Mesenchymal stromal cells Adipose tissue Stromal vascular fraction Micro-fragmented adipose tissue Regeneration

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CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

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New insights into the therapeutic approaches for the treatment of tauopathies

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Neural Regeneration Research 2024年第5期19卷 1020-1026页

作者： Himanshi Singh Asmita Das Mohammad Moshahid khan Tayebeh Pourmotabbed Department of Microbiology Immunology and BiochemistryUniversity of Tennessee Health Science CenterMemphisTNUSA Department of Biotechnology Delhi Technological UniversityShahbad DaulatpurDelhiIndia Department of Neurology College of MedicineUniversity of Tennessee Health Science CenterMemphisTNUSA Neuroscience Institute University of Tennessee Health Science CenterMemphisTNUSA Center for Muscle Metabolism and NeuropathologyDivision of Regenerative and Rehabilitation Sciences and Department of Physical TherapyCollege of Health ProfessionsUniversity of Tennessee Health Science CenterMemphisTNUSA

Tauopathies are a group of neurological disorders,including Alzheimer’s disease and frontotemporal dementia,which involve progressive neurodegeneration,cognitive deficits,and aberrant tau protein *** development of tauopathies cannot currently be stopped or slowed down by treatment *** the significant contribution of tau burden in primary tauopathies and the strong association between pathogenic tau accumulation and cognitive deficits,there has been a lot of interest in creating therapies that can alleviate tau pathology and render neuroprotective ***,small molecules,immunotherapies,and gene therapy have been used to reduce the pathological tau burden and prevent neurodegeneration in animal models of ***,the major pitfall of the current therapeutic approach is the difficulty of drugs and gene-targeting modalities to cross the blood-brain barrier and their unintended side *** this review,the current therapeutic strategies used for tauopathies including the use of oligonucleotide-based gene therapy approaches that have shown a promising result for the treatment of tauopathies and Alzheimer’s disease in preclinical animal models,have been discussed.

关键词： dementia gene therapies immunotherapy neurodegeneration oligonucleotides tau tauopathies therapies

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Determination of uncertainties of geomechanical parameters of metamorphic rocks using petrographic analyses

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第2期16卷 345-364页

作者： Behzad Dastjerdy ali Saeidi Shahriyar Heidarzadeh Department of Applied Sciences University of Quebec at ChicoutimiSaguenayQCCanada SNC-Lavalin MontrealCanada

Geomechanical parameters of intact metamorphic rocks determined from laboratory testing remain highly uncertain because of the great intrinsic variability associated with the degrees of *** aim of this paper is to develop a proper methodology to analyze the uncertainties of geomechanical characteristics by focusing on three domains,*** treatment process,schistosity angle,and ***,the variabilities of the geomechanical laboratory data of Westwood Mine(Quebec,Canada)were examined statistically by applying different data treatment techniques,through which the most suitable outlier methods were selected for each parameter using multiple decision-making criteria and engineering *** indicated that some methods exhibited better performance in identifying the possible outliers,although several others were unsuccessful because of their limitation in large sample *** well-known boxplot method might not be the best outlier method for most geomechanical parameters because its calculated confidence range was not acceptable according to engineering ***,several approaches,including adjusted boxplot,2MADe,and 2SD,worked very well in the detection of true ***,the statistical tests indicate that the best-fitting probability distribution function for geomechanical intact parameters might not be the normal distribution,unlike what is assumed in most geomechanical ***,the negative effects of schistosity angle on the uniaxial compressive strength(UCS)variabilities were reduced by excluding the samples within a specific angle range where the UCS data present the highest ***,a petrographic analysis was conducted to assess the associated uncertainties such that a logical link was found between the dispersion and the variabilities of hard and soft minerals.

关键词： Intact rock parameters Natural variabilities Outlier detection methods Uncertainties Westwood mine Mineralogy

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A new class of generalized quasi-variational inequalities with applications to Oseen problems under nonsmooth boundary conditions

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Science China Mathematics 2024年第2期67卷 315-338页

作者： Shengda Zeng Akhtar A.khan Stanislaw Migórski Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal UniversityYulin 537000China Faculty of Mathematics and Computer Science Jagiellonian University in Krak´owKrak´ow 30348Poland Center for Applied and Computational Mathematics School of Mathematical SciencesRochester Institute of TechnologyRochesterNY 14623USA College of Sciences Beibu Gulf UniversityQinzhou 535000China

In this paper, we study a generalized quasi-variational inequality (GQVI for short) with twomultivalued operators and two bifunctions in a Banach space setting. A coupling of the Tychonov fixedpoint principle and the Katutani-Ky Fan theorem for multivalued maps is employed to prove a new existencetheorem for the GQVI. We also study a nonlinear optimal control problem driven by the GQVI and givesufficient conditions ensuring the existence of an optimal control. Finally, we illustrate the applicability of thetheoretical results in the study of a complicated Oseen problem for non-Newtonian fluids with a nonmonotone andmultivalued slip boundary condition (i.e., a generalized friction constitutive law), a generalized leak boundarycondition, a unilateral contact condition of Signorini’s type and an implicit obstacle effect, in which themultivalued slip boundary condition is described by the generalized Clarke subgradient, and the leak boundarycondition is formulated by the convex subdifferential operator for a convex superpotential.

关键词： generalized quasi-variational inequality existence theorem optimal control Kakutani-Ky Fan theorem Oseen problem non-Newtonian fluid nonmonotone slip boundary condition

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Identifying flow regime in the aquifer of fractured rock system in Germi Chai Basin,Iran

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Journal of Mountain Science 2024年第2期21卷 574-589页

作者： VAEZIHIR Abdorreza SEPEHRIPOUR ali TABARMAYEH Mehri Department of Earth Sciences University of TabrizTabriz ***Iran

Considering the importance of fractured rock aquifers in the hydrogeologic process,this research aimed to analyze the flow regime,internal degree of karstification,and estimate storage volume in fractured rock aquifers of the Germi Chai Basin in northwest Iran,which is attributed to its active tectonics,erosion,and the lithological *** the geological setting,the hypothesis is that this basin is characterized by a high degree of karstification and diffuse or intermediate flow regime leading to variation in discharge flow *** hydrodynamic and hadrochemical analysis was conducted on 9 well distributed springs across the basin from 2019 to *** maximum flow rate in most of the springs appeared in the early wet season despite their different levels of fluctuations on the monthly discharge time *** the spring recession curve form revealed an aquifer containing multiple micro-regimes withαrecession coefficients and a degree of karstification ranging between 0.001 to 0.06 and 0.55 to 2.61,*** findings indicated a dominant diffuse and intermediate flow system resulting from the development of a high density of fractures in this *** electrical conductivity of the spring changes inversely proportional to the change in flow discharge,indicating the reasonable hydrological response of the aquifer to rainfall *** analysis revealed that the delay time of spring discharge after rainfall events mostly varies between 10 to 30 *** total dynamic storage volume of the spring for a given period(2019-2020)was estimated to be approximately 1324 million cubic meters reflecting the long-term drainage potential and high perdurability of dynamic *** the maximum and minimum ratio revealed that the springs recharging system in Germi Chai Basin comes under the slow aquifers *** finding provides valuable insight into the hydrogeological properties of fractured rock aquifers contributing to effective w

关键词： Fractured rock aquifer Hydrodynamic and hadrochemical analysis Germi Chai Basin Recession coefficient

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An SDN-Based Algorithm for Caching,Routing,and Load Balancing in ICN

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China Communications 2024年第5期21卷 64-76页

作者： MohammadBagher Tavasoli Hossein Saidi ali Ghiasian Department of Electrical and Computer Engineering Isfahan University of TechnologyIsfahanIran Department of Technology and Engineering Shahrekord UniversityShahrekordIran

One of the challenges of Informationcentric Networking(ICN)is finding the optimal location for caching content and processing users’*** this paper,we address this challenge by leveraging Software-defined Networking(SDN)for efficient ICN *** achieve this,we formulate the problem as a mixed-integer nonlinear programming(MINLP)model,incorporating caching,routing,and load balancing *** explore two distinct scenarios to tackle the ***,we solve the problem in an offline mode using the GAMS environment,assuming a stable network state to demonstrate the superior performance of the cacheenabled network compared to non-cache ***,we investigate the problem in an online mode where the network state dynamically changes over *** the computational complexity associated with MINLP,we propose the software-defined caching,routing,and load balancing(SDCRL)algorithm as an efficient and scalable *** evaluation demonstrates that the SDCRL algorithm significantly reduces computational time while maintaining results that closely resemble those achieved by GAMS.

关键词： in-network caching information-centric network power efficiency routing software-defined networking

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