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Extended Deep Learning Algorithm for Improved Brain Tumor Diagnosis System

Intelligent Automation & Soft Computing 2024年第1期39卷 33-55页

作者： M.Adimoolam k.maithili N.M.Balamurugan R.Rajkumar S.Leelavathy Raju kannadasan Mohd Anul Haq Ilyas khan ElSayed M.Tag El Din Arfat Ahmad khan Department of Computer Engineering Government Polytechnic CollegeSevvapetTiruvallurTamil Nadu602025India Department of Computer Science and Engineering KG Reddy College of Engineering and TechnologyHyderabadTelangana500075India Department of Computer Science and Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Computer Science and Engineering Annamalai UniversityChidambaramTamil Nadu608002India Department of Computer Science and Engineering Aarupadai Veedu Institute of TechnologyVinayaka Mission Research FoundationPaiyanurTamil Nadu603104India Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLA algorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of dataset records is enormous,then themethod’s computation power has to be updated.

关键词： Brain tumor extended deep learning algorithm convolution neural network tumor detection deep learning

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Stage-Wise Categorization and Prediction of Diabetic Retinopathy Using Ensemble Learning and 2D-CNN

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Intelligent Automation & Soft Computing 2023年第4期36卷 499-514页

作者： N.M.Balamurugan k.maithili T.k.S.Rathish Babu M.Adimoolam Department of Computer Science and Engineering Sri Venkateswara College of EngineeringSriperumbudurChennaiIndia Department of Computer Science and Engineering KG Reddy College of Engineering and Technology(Autonomous)HyderabadTelanganaIndia Department of Computer Science and Engineering Sridevi Women’s Engineering CollegeHyderabadTelanganaIndia Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesThandalamChennaiIndia

Diabetic Eye Disease(DED)is a fundamental cause of blindness in human beings in the medical *** techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy(DR).The Machine Learning(ML)and the Deep Learning(DL)algorithms are the predomi-nant techniques to project and explore the images of *** though some solu-tions were adapted to challenge the cause of DR disease,still there should be an efﬁcient and accurate DR prediction to be adapted to reﬁne its *** this work,a hybrid technique was proposed for classiﬁcation and prediction of *** proposed hybrid technique consists of Ensemble Learning(EL),2 Dimensional-Conventional Neural Network(2D-CNN),Transfer Learning(TL)and Correlation ***,the Stochastic Gradient Boosting(SGB)EL method was used to predict the ***,the boosting based EL method was used to predict the DR of *** 2D-CNN was applied to categorize the various stages of DR ***,the TL was adopted to transfer the clas-siﬁcation prediction to training *** this TL was applied,a new predic-tion feature was *** the experiment,the proposed technique has achieved 97.8%of accuracy in prophecies of DR images and 98%accuracy in grading of *** experiment was also extended to measure the sensitivity(99.6%)and speciﬁcity(97.3%)*** predicted accuracy rate was com-pared with existing methods.

关键词： Diabetic retinopathy prediction and classiﬁcation ensemble learning conventional neural network diabetic eye disease

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Aqueous-phase reforming of hydroxyacetone solution to bio-based H_(2)over supported Pt catalysts

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Green Energy & Environment 2024年第4期9卷 777-788页

作者： A.k.k.Vikla k.koichumanova Songbo He k.Seshan Joint International Research Laboratory of Circular Carbon Nanjing Tech UniversityNanjing211816China Faculty of Science and Technology University of Twente7500 AE EnschedeThe Netherlands CoRe Pro 9723 BL GroningenThe Netherlands

Aqueous-phase reforming(APR)is an attractive process to produce bio-based hydrogen from waste biomass streams,during which the catalyst stability is often challenged due to the harsh reaction *** this work,three Pt-based catalysts supported on C,AlO(OH),and ZrO_(2)were investigated for the APR of hydroxyacetone solution in afixed bed reactor at 225℃and 35 *** them,the Pt/C catalyst showed the highest turnover frequency for H_(2)production(TOF of 8.9 molH_(2)molPt^(-1)min^(-1))and the longest catalyst *** the AlO(OH)and ZrO_(2)supported Pt catalysts,the side reactions consuming H_(2),formation of coke,and Pt sintering result in a low H_(2)production and the fast catalyst *** proposed reaction pathways suggest that a promising APR catalyst should reform all oxygenates in the aqueous phase,minimize the hydrogenation of the oxygenates,maximize the WGS reaction,and inhibit the condensation and coking reactions for maximizing the hydrogen yield and a stable catalytic performance.

关键词： APR Hydroxyacetone TOF Bio-based H_(2) Support effect

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Direct scaling of residual displacements for bilinear and pinching oscillators

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Earthquake Engineering and Engineering Vibration 2024年第1期23卷 129-149页

作者： Mohammad Saifullah Vinay k.Gupta Department of Civil Engineering Indian Institute of Technology KanpurKanpur 208016India

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the *** attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model *** of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not *** statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model *** proposed scaling model is applicable to horizontal ground motions in the western *** earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

关键词： residual displacement spectrum bilinear hysteresis model pinching hysteresis model nonlinear analysis scaling model

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Analysis of the Oscillatory Flows of Multiple Shock Waves in a Constant Area Duct

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Journal of Thermal Science 2024年第3期33卷 794-806页

作者： k JAMES Jintu kIM Heuy Dong Department of Mechanical Engineering Andong National UniversityAndong36729Republic of Korea CAD-IT korea Co. Ltd.Seoul08591Republic of Korea

The oscillatory response of multiple shock waves to downstream perturbations in a supersonic flow is studied numerically in a rectangular *** shock waves are formed inside the duct at a shock Mach number of *** duct has an exit height of H,and the effect of duct resonance on multiple shock oscillations is investigated by attaching exit ducts of lengths 0H,50H,and *** downstream disturbance frequency varied from 10 Hz to 200 Hz to explore the oscillation characteristics of the multiple shock *** oscillatory response of shock waves under self-excited and forced oscillation conditions are analyzed in terms of wall static pressure,shock train leading-edge location,shock train length,and the size of the separation *** extent of the initial shock location increases with an increase in exit duct length for the self-excited oscillation *** analysis of the shock train leading edge and the spectral analysis of wall static pressure variations are *** variation in the shock train length is analyzed using the pressure ratio method for self-excited as well as forced *** RMS amplitude of the normalized shock train length(ζ_(ST))increases with an increase in the exit duct length for the self-excited oscillation *** the downstream perturbation frequency is increased,ζ_(ST)is decreased for exit duct *** all exit duct designs and downstream forcing frequencies,the size of the separation bubble grows and shrinks during the shock oscillations,demonstrating the dependence on duct resonance and forced oscillations.

关键词： shock train downstream disturbance supersonic flow shock wave boundary layer interaction duct resonance flow separation

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Impact of Fin Arrangement on Heat Transfer and Melting Characteristics of Phase Change Material

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Journal of Thermal Science 2024年第2期33卷 435-456页

作者： Arun UNIYAL Yogesh k.PRAJAPATI Department of Mechanical Engineering National Institute of Technology UttarakhandSrinagar(Garhwal)246174India Department of Mechanical Engineering BIT SindriDhanbadJharkhand828123India

Present work investigates the heat transfer and melting behaviour of phase change material(PCM) in six enclosures(enclosure-1 to 6) filled with paraffin *** enclosures are equipped with distinct arrangements of the fins while keeping the fin's surface area equal in each *** analysis has been presented to recognize the suitable fin arrangements that facilitate improved heat transfer and melting rate of the *** wall of the enclosure is maintained isothermal for the temperature values 335 k,350 k and 365 *** length of the enclosure including fins is ranging between 0 and *** have been illustrated through the estimation of important performance parameters such as energy absorbing capacity,melting rate,enhancement ratio,and Nusselt *** has been found that melting time(to melt 100% of the PCM) is 60.5%less in enclosure-2(with two fins of equal length) as compared to the enclosure-1,having no *** the fin surface area equal,if the longer fin is placed below the shorter fin(enclosure-3),melting time is further decreased by 14.1% as compared to ***,among all the configurations,enclosure-6 with wire-mesh fin structure exhibits minimum melting time which is 68.4% less as compared to the *** on the findings,it may be concluded that fins are the main driving agent in the enclosure to transfer the heat from heated wall to the *** design and positioning of the fins improve the heat transfer rate followed by melting of the PCM in the entire area of the *** of the favourable vortices and natural convection current in the enclosure accelerate the melting phenomenon and help to reduce charging time.

关键词： phase change material enclosure fin melting fraction energy storage heat transfer

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Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition:application of the clique polynomial method and physics-informed neural networks

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Applied Mathematics and Mechanics(English Edition) 2024年第9期45卷 1613-1632页

作者： k.CHANDAN k.kARTHIk k.V.NAGARAJA B.C.PRASANNAkUMARA R.S.VARUN kUMAR T.MUHAMMAD Amrita School of Artificial Intelligence Amrita Vishwa VidyapeethamBengaluru 560035KarnatakaIndia Department of Studies in Mathematics Davangere UniversityDavangere 577002KarnatakaIndia Computational Science Lab Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru 560035KarnatakaIndia Department of Pure and Applied Mathematics School of Mathematical SciencesSunway UniversityPetaling Jaya 47500Malaysia Department of Mathematics College of ScienceKing Khalid UniversityAbha 61413Saudi Arabia

The heat transfer through a concave permeable fin is analyzed by the local thermal non-equilibrium(LTNE)*** governing dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled,and then are nondimensionalized by suitable dimensionless ***,the obtained nondimensional equations are solved by the clique polynomial method(CPM).The effects of several dimensionless parameters on the fin's thermal profiles are shown by graphical ***,the current study implements deep neural structures to solve physics-governed coupled equations,and the best-suited hyperparameters are attained by comparison with various network *** results of the CPM and physicsinformed neural network(PINN)exhibit good agreement,signifying that both methods effectively solve the thermal modeling problem.

关键词： heat transfer fin porous fin local thermal non-equilibrium(LTNE)model physics-informed neural network(PINN)

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MDCN:Modified Dense Convolution Network Based Disease Classification in Mango Leaves

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Computers, Materials & Continua 2024年第2期78卷 2511-2533页

作者： Chirag Chandrashekar k.P.Vijayakumar k.Pradeep A.Balasundaram School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)ChennaiIndia

The most widely farmed fruit in the world is *** the production and quality of the mangoes are hampered by many *** diseases need to be effectively controlled and ***,a quick and accurate diagnosis of the disorders is *** convolutional neural networks,renowned for their independence in feature extraction,have established their value in numerous detection and classification ***,it requires large training datasets and several parameters that need careful *** proposed Modified Dense Convolutional Network(MDCN)provides a successful classification scheme for plant diseases affecting mango *** model employs the strength of pre-trained networks and modifies them for the particular context of mango leaf diseases by incorporating transfer learning *** data loader also builds mini-batches for training the models to reduce training ***,optimization approaches help increase the overall model’s efficiency and lower computing *** employed on the MangoLeafBD Dataset consists of a total of 4,000 *** the experimental results,the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

关键词： Leaf disease detection deep convolutional neural networks transfer learning optimization MangoLeafBD Dataset

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Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

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Journal of Magnesium and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan Sekar S.k.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnesium Research Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till *** corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical *** intrinsic high electrochemical nature of Mg limits their utilization in diverse *** scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion *** present review enlightens the influence of grain size(GS),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg ***,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are ***,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are ***,the individual role of GS,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and *** challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is *** review is presented from basic concrete background to advanced corrosion mechanisms with an aim of creating interest among the readers like students,researchers and industry experts from various research ***,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of knowledge,(ii)foster research and development,(iii)make breakthrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

关键词： Corrosion Bio corrosion Magnesium alloys Magnesium composites Magnesium implants.

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Long Term X-Ray Spectral Variations of the Seyfert-1 Galaxy Mrk 279

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Research in Astronomy and Astrophysics 2024年第6期24卷 307-314页

作者： k.Akhila Ranjeev Misra Savithri H.Ezhikode k.Jeena Department of Physics Providence Women’s CollegeUniversity of CalicutKerala 673009India Inter-University Centre for Astronomy and Astrophysics(IUCAA) PB No.4GaneshkhindPune 411007India Department of Physics and Electronics CHRIST(Deemed to be University)Hosur Main RoadBangalore 560029India

We present the results from a long term X-ray analysis of Mrk 279 during the period 2018–*** use data from multiple missions–AstroSat,NuSTAR and XMM-Newton,for the *** X-ray spectrum can be modeled as a double Comptonization along with the presence of neutral Fe kαline emission,at all *** determined the source’s X-ray flux and luminosity at these different *** find significant variations in the source’s flux *** also investigate the variations in the source’s spectral components during the observation *** find that the photon index and hence the spectral shape follow the variations only over longer time *** probe the correlations between fluxes of different bands and their photon indices,and found no significant correlations between the parameters.

关键词： galaxies:Seyfert galaxies:individual(Mrk 335) X-rays:galaxies

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