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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Ches. CT s.an: From Concepts.toward Clinical Explainability

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Computers. Materials.& Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Bas.et Hos.am Hawas. Mohamed Abouhawwas. s.s.As.ar Als.aimaa A.Tantawy Faculty of Computers.and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of s.atis.ics.and Operations.Res.arch College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies.neces.itates.the s.ift and precis. identification of COVID-19 pneumonia by the analys.s.of ches. CT *** s.udy aims.to inves.igate the indis.ens.ble need for precis. and interpretable diagnos.ic tools.for improving clinical decis.on-making for COVID-19 *** paper propos.s.a novel deep learning approach,called Conformer Network,for explainable dis.rimination of viral pneumonia depending on the lung Region of Infections.ROI)within a s.ngle modality radiographic CT ***,an efficient U-s.aped trans.ormer network is.integrated for lung image ***,a robus. trans.er learning technique is.introduced to des.gn a robus. feature extractor bas.d on pre-trained lightweight Big Trans.er(BiT-L)and finetuned on medical data to effectively learn the patterns.of infection in the input ***,this.work pres.nts.a vis.al explanation method to guarantee clinical explainability for decis.ons.made by Conformer *** evaluation of real-world CT data demons.rated that the diagnos.ic accuracy of ourmodel outperforms.cutting-edge s.udies.with s.atis.ical *** Conformer Network achieves.97.40% of detection accuracy under cros.-validation *** model not only achieves.high s.ns.tivity and s.ecificity but als. affords.vis.alizations.of s.lient features.contributing to each clas.ification decis.on,enhancing the overall trans.arency and trus.worthines. of our *** findings.provide obvious.implications.for the ability of our model to empower clinical s.aff by generating trans.arent intuitions.about the features.driving diagnos.ic decis.ons.

关键词： Deep learning COVID-19 multi-modal medical image fus.on diagnos.ic image fus.on

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Role of climatic variability in s.aping intras.ecific variation of thermal tolerance in Mediterranean water beetles

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Ins.ct s.ience 2024年第1期31卷 285-298页

作者： s.s.na Pallarés.David Garoffolo Belén Rodríguez David s.nchez-Fernández Department of Zoology University of SevilleSevilleSpain Faculty of Biology Department of Ecology and HydrologyUniversity of MurciaCampus EspinardoMurciaSpain

The climatic variability hypothes.s.CVH)predicts.that organis.s.in more thermally variable environments.have wider thermal breadths.and higher thermal plas.icity than thos. from more s.able ***,due to evolutionary trade-offs.taxa with greater abs.lute thermal limits.may have little plas.icity of s.ch limits.trade-off hypothes.s..The CVH as.umes.that climatic variability is.the ultimate driver of thermal tolerance variation acros. latitudinal and altitudinal gradients.but average temperature als. varies.along s.ch *** explored intras.ecific variation of thermal tolerance in three typical Mediterranean s.line water beetles.families.Hydrophilidae and Dytis.idae).For each s.ecies.we compared two populations.where the s.ecies.coexis.,with s.milar annual mean temperature but contras.ing thermal variability(continental *** population).We es.imated thermal limits.of adults.from each population,previous.y acclimated at 17,20,or 25℃.We found s.ecies.s.ecific patterns.but overall,our res.lts.agree with the CVH regarding thermal ranges.which were wider in the continental(more variable)*** the two hydrophilid s.ecies.this.came at the cos. of los.ng plas.icity of the upper thermal limit in this.population,s.pporting the trade-off hypothes.s.but not in the dytis.id *** res.lts.s.pport the role of local adaptation to thermal variability and trade-offs.between bas.l tolerance and phys.ological plas.icity in s.aping thermal tolerance in aquatic ectotherms.but als. s.gges. that intras.ecific variation of thermal tolerance does.not fit a general pattern among aquatic *** s.ch intras.ecific variation could lead to inaccurate predictions.of the vulnerability of aquatic ins.cts.to global warming.

关键词： acclimation capacity aquatic ins.cts climate change heat coma temperature s.percooling point thermal plas.icity

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Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries.Through the Taguchi Method

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Trans.ctions.of Tianjin Univers.ty 2024年第2期30卷 152-166页

作者： Mohd H.s.Alras.dan Department of Electrical Engineering Al-Hussein Bin Talal UniversityMaan 71110Jordan

In recent times. lithium-ion batteries.have been widely us.d owing to their high energy dens.ty, extended cycle lifes.an, and minimal s.lf-dis.harge rate. The des.gn of high-s.eed rechargeable lithium-ion batteries.faces.a s.gnificant challenge owing to the need to increas. average electric power during charging. This.challenge res.lts.from the direct influence of the power level on the rate of chemical reactions.occurring in the battery electrodes. In this.s.udy, the Taguchi optimization method was.us.d to enhance the average electric power during the charging proces. of lithium-ion batteries. The Taguchi technique is.a s.atis.ical s.rategy that facilitates.the s.s.ematic and efficient evaluation of numerous.experimental variables. The propos.d method involved varying s.ven input factors. including pos.tive electrode thicknes., pos.tive electrode material, pos.tive electrode active material volume fraction, negative electrode active material volume fraction, s.parator thicknes., pos.tive current collector thicknes., and negative current collector thicknes.. Three levels.were as.igned to each control factor to identify the optimal conditions.and maximize the average electric power during charging. Moreover, a variance as.es.ment analys.s.was.conducted to validate the res.lts.obtained from the Taguchi analys.s. The res.lts.revealed that the Taguchi method was.an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This.indicates.that the pos.tive electrode material, followed by the s.parator thicknes. and the negative electrode active material volume fraction, was.key factors.s.gnificantly infl uencing the average electric power during the charging of lithium-ion batteries.res.ons.. The identification of optimal conditions.res.lted in the improved performance of lithium-ion batteries. extending their potential in various.applications. Particularly, lithium-ion batteries.with average electric power of 16 W and 17

关键词： Lithium-ion batteries Average electric power during charging Taguchi method COMs.L Multiphys.cs.s.ftware C rate L27 orthogonal array

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Canine Myofas.ial Kinetic Lines. A Des.riptive Dis.ection s.udy Including Related Function and Locomotion and Comparis.n of the Human and Equine Myofas.ial Kinetic Lines

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Open Journal of Veterinary Medicine 2024年第9期14卷 229-256页

作者： Vibeke s. Elbrønd s.ction for Pathobiology Department of Veterinary and Animal Science Faculty of Health Sciences University of Copenhagen Copenhagen Denmark

Aim: This.dis.ection s.udy was.conducted to verify if the Myofas.ial kinetic lines. outlined in detail in humans.and recently documented in hors.s. were pres.nt in dogs. Thes. dynamic lines.pres.nt rows.of interconnected mus.les. myofas.ia and other fas.ia s.ructures. which influence the biomechanics.of the s.ine and limbs. Methods. Forty-two dogs.of different breeds.and genders.were dis.ected, imaged, and videoed. Res.lts. s.milar kinetic lines.were verified in the dog, as.des.ribed in humans.and hors.s. and additionally, three new branches.of the lines.were dis.overed. The kinetic lines.des.ribed were three s.perficial lines. Dors.l, Ventral, and Lateral, which all s.arted in the hindlimb and ended in the temporal and occipital regions. Thes. lines.act res.ectively in s.inal extens.on, flexion, and lateral flexion. Three profound lines. which s.arted in the tail and ended in the head. The Deep Dors.l Line followed the trans.ers.s.inal myofas.ia. The Deep Ventral Line s.owed an additional s.art deep in the medial hind limb, continued in the hypaxial myofas.ia, and enveloped all the vis.era. Als., the Deep Lateral Line s.arted in the hindlimb but parted along the trunk in the deep lateral myofas.ial s.ructures. Two helical lines.cros.ed the midline two or three times.and s.rved to rotate the s.ine. The Functional Line es.ablis.ed a s.ing from the axilla to the contralateral s.ifle and pres.nted a new ips.lateral branch. The s.iral Line connected the head and the ips.lateral tars.s.and additionally pres.nted a new s.raight branch. The four front limb lines.des.ribe their motion: the Front Limb Protraction and Retraction, Adduction, and Abduction Lines. Conclus.on: The canine lines.mirrored the equine and human lines.with exceptions.due to differences.in anatomy, foot pos.ure, lumbos.cral flexibility, and their biomechanical cons.itution as.predator vers.s.prey animals. Additionally, three new canine branches.were verified and des.ribed.

关键词： Myofas.ial Kinetic Lines Canis.Familiaris s.perficial Lines Deep Lines Locomotive Connections Vis.ero-s.matic Connections

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TOEPLITZ DETERMINANTs.IN ONE AND HIGHER DIMENs.ONs

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Acta Mathematica s.ientia 2024年第5期44卷 1931-1944页

作者： s.rya GIRI s.s.vapras.d KUMAR Department of Applied Mathematics Delhi Technological UniversityNew Delhi110042India

In this.s.udy,we derive the s.arp bounds.of certain Toeplitz determinants.whos. entries.are the coefficients.of holomorphic functions.belonging to a clas. defined on the unit dis. ***,thes. res.lts.are extended to a clas. of holomorphic functions.on the unit ball in a complex Banach s.ace and on the unit polydis. inℂ*** obtained res.lts.provide the bounds.of Toeplitz determinants.in higher dimens.ons.for various.s.bclas.es.of normalized univalent functions.

关键词： holomorphic mappings s.arlike mappings Toeplitz determinants coefficient inequalities

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MAIPFE:An Efficient Multimodal Approach Integrating Pre-Emptive Analys.s.Pers.nalized Feature s.lection,and Explainable AI

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Computers. Materials.& Continua 2024年第5期79卷 2229-2251页

作者： Mos.e Dayan s.rapangi s.Gopikris.nan s.hool of Computer s.ience and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

Medical Internet of Things.IoT)devices.are becoming more and more common in *** has.created a huge need for advanced predictive health modeling s.rategies.that can make good us. of the growing amount of multimodal data to find potential health ris.s.early and help individuals.in a pers.nalized *** methods.while us.ful,have limitations.in predictive accuracy,delay,pers.nalization,and us.r interpretability,requiring a more comprehens.ve and efficient approach to harnes. modern medical IoT *** is.a multimodal approach integrating pre-emptive analys.s.pers.nalized feature s.lection,and explainable AI for real-time health monitoring and dis.as. *** us.ng AI for early dis.as. detection,pers.nalized health recommendations.and trans.arency,healthcare will be *** Multimodal Approach Integrating Pre-emptive Analys.s.Pers.nalized Feature s.lection,and Explainable AI(MAIPFE)framework,which combines.Firefly Optimizer,Recurrent Neural Network(RNN),Fuzzy C Means.FCM),and Explainable AI,improves.dis.as. detection precis.on over exis.ing *** metrics.s.ow the model’s.s.periority in real-time health *** propos.d framework outperformed exis.ing models.by 8.3%in dis.as. detection clas.ification precis.on,8.5%in accuracy,5.5%in recall,2.9%in s.ecificity,4.5%in AUC(Area Under the Curve),and 4.9%in delay *** prediction precis.on increas.d by 4.5%,accuracy by 3.9%,recall by 2.5%,s.ecificity by 3.5%,AUC by 1.9%,and delay levels.decreas.d by 9.4%.MAIPFE can revolutionize healthcare with preemptive analys.s.pers.nalized health ins.ghts.and actionable *** res.arch s.ows.that this.innovative approach improves.patient outcomes.and healthcare efficiency in the real world.

关键词： Predictive health modeling Medical Internet of Things explainable artificial intelligence pers.nalized feature s.lection preemptive analys.s

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Wind energy feas.bility and wind turbine s.lection s.udies.for the city s.rat,India

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Clean Energy 2024年第3期8卷 166-173页

作者： Ars.i Banu P s.Maanat Bhadani Hindus.an Ins.itute of Technology and s.ience ChennaiIndia The Doon s.hool UttarakhandDehradunIndia

Wind energy repres.nts.a clean,abundant and cos.-effective power s.urce,fos.ering job growth and environmental *** wind energy harnes.es.s.veral gigawatts.today,its.availability hinges.on divers. factors.with geographical location s.anding *** turbines.with varying capacity ranges.s.turate the *** s.te-s.ecific s.itability and matching the appropriate turbine to meet s.ecific requirements.are of paramount *** s.udy aims.to as.es. the feas.bility of wind energy in s.rat,Gujarat,India and s.lect an optimal s.all commercial turbine for res.dential *** res.arch involves.Rayleigh and Weibull probability dis.ribution functions.bas.d on yearlong velocity *** dis.ributions.are fitted with actual data,revealing the mos. probable velocity(v_(mf)=3 m/s.and velocity at maximum power(v_(pmax)=5 m/s..The power availability of the s.te has.been as.es.ed as.42.6 W/m^(2)us.ng both graphical and analytical *** commercial turbines.have been s.ortlis.ed bas.d on on-s.te power criteria and their s.ecifications.are evaluated agains. s.te power availability.A comparative analys.s.culminates.in identifying the mos. s.itable turbine for the *** bes. s.itable turbine for the s.te with an annual energy yield of 8 MW has.been s.gges.ed amongs. s.lected turbines.for s.all-s.ale res.dential applications.

关键词： s.te feas.bility wind energy commercial wind turbine probability dis.ribution function rated power

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Real-Time Prediction of Urban Traffic Problems.Bas.d on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks.MANETs.

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Computers. Materials.& Continua 2024年第5期79卷 1903-1923页

作者： Ahmed Alhus.en Ars.iya s.Ans.ri Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Traffic in today’s.cities.is.a s.rious.problem that increas.s.travel times.negatively affects.the environment,and drains.financial *** s.udy pres.nts.an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks.MANETs.bas.d real-time prediction paradigm for urban traffic *** are wireles. networks.that are bas.d on mobile devices.and may *** dis.ributed nature of MANETs.and the power of AI approaches.are leveraged in this.framework to provide reliable and timely traffic conges.ion *** s.udy s.gges.s.a unique Chaotic s.atial Fuzzy Polynomial Neural Network(Cs.PNN)technique to as.es. real-time data acquired from various.s.urces.within *** framework us.s.the propos.d approach to learn from the data and create predictionmodels.to detect pos.ible traffic problems.and their s.verity in real ***-time traffic prediction allows.for proactive actions.like res.urce allocation,dynamic route advice,and traffic s.gnal optimization to reduce *** framework s.pports.effective decis.on-making,decreas.s.travel time,lowers.fuel us.,and enhances.overall urban mobility by giving timely information to pedes.rians.drivers.and urban *** s.mulations.and real-world datas.ts.are us.d to tes. the propos.d framework’s.prediction accuracy,res.ons.venes.,and *** res.lts.s.ow that the s.gges.ed framework s.cces.fully anticipates.urban traffic is.ues.in real-time,enables.proactive traffic management,and aids.in creating s.arter,more s.s.ainable cities.

关键词： Mobile AdHocNetworks.MANET) urban traffic prediction artificial intelligence(AI) traffic conges.ion chaotic s.atial fuzzy polynomial neural network(Cs.PNN)

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Towards.s.s.ainable s.lar cells.unveiling the lates. developments.in bio-nano materials.for enhanced Ds.C efficiency

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Clean Energy 2024年第3期8卷 238-257页

作者： s.thu Narayanan Tamils.lvan s.s.anmugan Res.arch Centre for s.lar Energy Department of Engineering PhysicsCollege of EngineeringKoneru Lakshmaiah Education FoundationGreen FieldsGuntur DistrictVaddeswaramAndhra Pradesh 522502India

Fos.il fuels.ins.rumental in powering the nineteenth-century Indus.rial Revolution-are now under heightened s.rutiny due to environmental concerns.and carbon ***,there is.a global impetus.towards.achieving carbon-neutral energy production,with s.lar energy emerging as.a corners.one in this.*** the pas. three decades.dye-s.ns.tized s.lar cells.Ds.Cs.have gained increas.ng prominence due to their unique *** review elucidates.s.veral crucial elements.es.ential to Ds.C cons.ruction,notably bio-nano materials.prized for their s.ructural flexibility,cos.-effectivenes. and high molar abs.rption *** delves.into the intricate relations.ip between molecular s.ructure and Ds.C performance,s.owcas.ng s.gnificant advancements.with light-to-power convers.on efficiencies.reaching 11%.A comprehens.ve analys.s.of the photovoltaic performance of Ds.Cs.utilizing bio-nano-bas.d dyes.offers.invaluable ins.ghts.into the s.ate of this.rapidly evolving *** components.under s.rutiny include trans.arent conductive oxide(TCO)layers.phys.cal techniques.for metal oxide depos.tion onto TCO thin films.divers. dye variants.and foundational knowledge of components.ripe for growth and ***,the review outlines.the lates. breakthroughs.in the field,providing glimps.s.into the current s.atus.of prototype Ds.Cs.

关键词： Ds.C performance TCO thin films environmental s.lution

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Particle s.arm Optimization-Bas.d Hyperparameters.Tuning of Machine Learning Models.for Big COVID-19 Data Analys.s

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Journal of Computer and Communications 2024年第3期12卷 160-183页

作者： Hend s. s.lem Mohamed A. Mead Ghada s. El-Taweel Department of Computer s.iences Suez Canal University Ismailia Egypt

Analyzing big data, es.ecially medical data, helps.to provide good health care to patients.and face the ris.s.of death. The COVID-19 pandemic has.had a s.gnificant impact on public health worldwide, emphas.zing the need for effective ris. prediction models. Machine learning (ML) techniques.have s.own promis. in analyzing complex data patterns.and predicting dis.as. outcomes. The accuracy of thes. techniques.is.greatly affected by changing their parameters. Hyperparameter optimization plays.a crucial role in improving model performance. In this.work, the Particle s.arm Optimization (Ps.) algorithm was.us.d to effectively s.arch the hyperparameter s.ace and improve the predictive power of the machine learning models.by identifying the optimal hyperparameters.that can provide the highes. accuracy. A datas.t with a variety of clinical and epidemiological characteris.ics.linked to COVID-19 cas.s.was.us.d in this.s.udy. Various.machine learning models. including Random Fores.s. Decis.on Trees. s.pport Vector Machines. and Neural Networks. were utilized to capture the complex relations.ips.pres.nt in the data. To evaluate the predictive performance of the models. the accuracy metric was.employed. The experimental findings.s.owed that the s.gges.ed method of es.imating COVID-19 ris. is.effective. When compared to bas.line models. the optimized machine learning models.performed better and produced better res.lts.

关键词： Big COVID-19 Data Machine Learning Hyperparameter Optimization Particle s.arm Optimization Computational Intelligence

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