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Electrochemical Study of Diffusion Bonded Joints between Micro-duplex Stainless Steel and Ti6A14V Alloy

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Journal of Materials Science & Technology 2014年第2期30卷 163-171页

作者： Shaily M.Bhola sukumar Kundu Rahul Bhola Brajendra Mishra Subrata Chatterjee Department of Metallurgical and Materials Engineering Colorado School of Mines Department of Metallurgy and Materials Engineering Bengal Engineering and Science University

In the present study, corrosion behavior of diffusion bonded joints formed between micro-duplex stainless steel （MDSS） and Ti6AI4V alloy （TiA）（at 900 ~C for 60 min under 4 MPa uniaxial pressure in vacuum） was investigated in 1 mol/L HCI and 1 mol/L NaOH solutions using various electrochemical measurements such as open circuit potential （OCP）, electrochemical impedance spectroscopy （EIS） and potentiodynamic polarization （PD）. For comparison, corrosion behavior of base metals （MDSS and TiA） was also evaluated. Bonded joint was characterized by light optical microscopy and scanning electron microscopy using backscattered electron mode. The layer wise σ phase and λ ＋ FeTi phase mixture has been observed at the bond interface and the bond tensile strength and shear strength were - 556.4 MPa and -420.2 MPa, respectively.

关键词： Diffusion bonding Micro-duplex stainless steel Titanium ahoy Corrosion EIS

Methane hydrate formation and dissociation in synthetic seawater

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Journal of Natural Gas Chemistry 2012年第6期21卷 625-632页

作者： Vikash Kumar Saw Iqbal Ahmad Ajay Mandal G.Udayabhanu sukumar Laik Gas Hydrate Laboratory Department of Petroleum Engineering Department of Applied Chemistry Indian School of Mines

The formation and dissociation of methane gas hydrate at an interface between synthetic seawater （SSW） and methane gas have been experimentally investigated in the present work. The amount of gas consumed during hydrate formation has been calculated using the real gas equation. Induction time for the formation of hydrate is found to depend on the degree of subcooling. All the experiments were conducted in quiescent system with initial cell pressure of 11.14 MPa. Salinity effects on the onset pressure and temperature of hydrate formation are also observed. The dissociation enthalpies of methane hydrate in synthetic seawater were determined by Clausius-Clapeyron equation based on the measured phase equilibrium data. The dissociation data have been analyzed by existing models and compared with the reported data.

关键词： methane hydrate formation and dissociation total dissolved salt induction time subcooling

CONVERGENCE ANALYSIS OF A LOCALLY ACCELERATED PRECONDITIONED STEEPEST DESCENT METHOD FOR HERMITIAN-DEFINITE GENERALIZED EIGENVALUE PROBLEMS

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Journal of Computational Mathematics 2018年第5期36卷 739-760页

作者： Yunfeng Cai Zhaojun Bai John E. Pask N. sukumar LMAM & School of Mathematical Sciences Peking University Beijing 100871 China Department of Computer Science and Department of Mathematics University of California Davis CA 95616 USA Physics Division Lawrence Livermore National Laboratory Livermore CA 94550 USA Department of Civil and Environmental Engineering University of California Davis CA 95616 USA

By extending the classical analysis techniques due to Samokish, Faddeev and Faddee- va, and Longsine and McCormick among others, we prove the convergence of the precon- ditioned steepest descent with implicit deflation （PSD-id） method for solving Hermitian- definite generalized eigenvalue problems. Furthermore, we derive a nonasymptotie estimate of the rate of convergence of the PSD-id method. We show that with a proper choice of the shift, the indefinite shift-and-invert preconditioner is a locally accelerated preconditioner, and is asymptotically optimal which leads to superlinear convergence Numerical examples are presented to verify the theoretical results on the convergence behavior of the PSD- id method for solving ill-conditioned Hermitian-definite generalized eigenvalue problems arising from electronic structure calculations. While rigorous and full-scale convergence proofs of preconditioned block steepest descent methods in practical use still largely eludes us, we believe the theoretical results presented in this paper shed light on an improved understanding of the convergence behavior of these block methods.

关键词： Eigenvalue problem Steepest descent method Preconditioning Superlinear convergence.

Route Towards Road Freight Electrification in India:Examining Battery Electric Truck Powertrain and Energy Consumption

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Chinese Journal of Electrical Engineering 2022年第3期8卷 57-75页

作者： Sreedhar Madichetty Avram John Neroth sukumar Mishra B.Chitti Babu Department of Electrical and Electronics Engineering Mahindra University Ecole CentraleHyderabad 500043India Department of Electrical Engineering Indian Institute of TechnologyDelhi 110016India Department of Electronics and Communication Engineering Indian Institute of Information TechnologyDesign and ManufacturingKanchipuram 600127India

Medium-duty/heavy-duty trucks(MD/HDTs)are yet to be included in India’s electric mobility *** the improvement of electric vehicle(EV)technologies,there is a growing interest in battery-electric trucks(BETs)from original equipment manufacturers(OEMs).The time is opportune to consider electrification as a future direction for road freight in ***,this article presents the results of an energy consumption simulation study of a BET under Indian *** study specifically considered an MDBET over a domestic drive *** energy consumption figures can facilitate future studies that analyze the technical and practical feasibility of BETs in the *** addition,the article provides the requisite groundwork for BET modeling for a simulation study by reviewing available EV powertrain systems and *** powertrain considerations are thereby obtained for a typical medium-duty/heavy-duty battery-electric truck(MD/HDBET)in the Indian context.

关键词： Electric truck heavy-duty battery electric truck medium-duty battery electric truck energy consumption vehicle powertrain

Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI

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Computers, Materials & Continua 2023年第8期76卷 2551-2570页

作者： Umair Muneer Butt Rimsha Arif sukumar Letchmunan Babur Hayat Malik Muhammad Adil Butt School of Computer Sciences Universiti Sains MalaysiaPenang1180Malaysia Department of Computer Science and IT The University of ChenabGujrat50700Pakistan

The detection of brain disease is an essential issue in medical and research *** learning techniques have shown promising results in detecting and diagnosing brain diseases using magnetic resonance imaging(MRI)*** techniques involve training neural networks on large datasets of MRI images,allowing the networks to learn patterns and features indicative of different brain ***,several challenges and limitations still need to be addressed further to improve the accuracy and effectiveness of these *** paper implements a Feature Enhanced Stacked Auto Encoder(FESAE)model to detect brain *** standard stack auto encoder’s results are trivial and not robust enough to boost the system’s ***,the standard Stack Auto Encoder(SAE)is replaced with a Stacked Feature Enhanced Auto Encoder with a feature enhancement function to efficiently and effectively get non-trivial features with less activation energy froman *** proposed model consists of four ***,pre-processing is performed to remove noise,and the greyscale image is converted to Red,Green,and Blue(RGB)to enhance feature details for discriminative feature ***,feature Extraction is performed to extract significant features for classification using DiscreteWavelet Transform(DWT)and ***,classification is performed to classify MRI images into four major classes:Normal,Tumor,Brain Stroke,and Alzheimer’***,the FESAE model outperforms the state-of-theart,machine learning,and deep learning methods such as Artificial Neural Network(ANN),SAE,Random Forest(RF),and Logistic Regression(LR)by achieving a high accuracy of 98.61% on a dataset of 2000 MRI *** proposed model has significant potential for assisting radiologists in diagnosing brain diseases more accurately and improving patient outcomes.

关键词： Brain diseases deep learning feature enhanced stacked auto encoder stack auto encoder

Electrospinning of curcumin loaded chitosan/poly （lactic acid） nanofilm and evaluation of its medicinal characteristics

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Frontiers of Materials Science 2013年第4期7卷 350-361页

作者： Bhaarathi DHURAI Nachimuthu SARASWATHY Ramasamy MAHESWARAN Ponnusamy SETHUPATHI Palanisamy VANITHA sukumar VIGNESHWARAN~, and Venugopal RAMESHBABU Department of Textile Technology Kumaraguru College of Technology Coimbatore 641049 Tamilnadu India Department of Biotechnology Kumaraguru College of Technology Coimbatore 641049 Tamilnadu India

The curcumin loaded chitosanlpoly （lactic acid）（PLA） nanoflbers were produced using electrospinning. Box-Behnken experimental design was used for the optimization of variables （-1, 0, ＋ 1 coded level） like chitosan/PLA strength （% w/v）, curcumin strength （% w/v） and applied voltage （kV） to obtain uniform fiber diameter. The morphology of nanofibers was shown by SEM. Molecular interactions and the presence of each chemical compound of curcumin loaded chitosanlPLA fibers were characterized by FTIR and EDX analysis. Antioxidant, drug release and in vitro cytotoxicity tests were performed to evaluate the suitability of nanofibers that would be used for wound healing. In vivo wound healing studies on excision and incision wounds created on rat model showed significant reduction of wound area when compared to untreated. The better healing efficiency can be attributed to the presence of curcumin and chitosan.

关键词： Box-Behnken chitosan curcumin electrospinning poly (lactic acid) (PLA)

Imbalanced Classification in Diabetics Using Ensembled Machine Learning

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Computers, Materials & Continua 2022年第9期72卷 4397-4409页

作者： M.Sandeep Kumar Mohammad Zubair Khan sukumar Rajendran Ayman Noor A.Stephen Dass J.Prabhu School of Information Technology and Engineering Vellore Institute of TechnologyVelloreTamil Nadu632014India Department of Computer Science and Information Taibah UniversityMedinaSaudi Arabia College of Computer Science and Engineering Taibah UniversityMedinaSaudi Arabia

Diabetics is one of the world’s most common diseases which are caused by continued high levels of blood *** risk of diabetics can be lowered if the diabetic is found at the early *** recent days,several machine learning models were developed to predict the diabetic presence at an early *** this paper,we propose an embedded-based machine learning model that combines the split-vote method and instance duplication to leverage an imbalanced dataset called PIMA Indian to increase the prediction of *** proposed method uses both the concept of over-sampling and under-sampling along with model weighting to increase the performance of *** measures such as Accuracy,Precision,Recall,and F1-Score are used to evaluate the *** results we obtained using K-Nearest Neighbor(kNN),Naïve Bayes(NB),Support Vector Machines(SVM),Random Forest(RF),Logistic Regression(LR),and Decision Trees(DT)were 89.32%,91.44%,95.78%,89.3%,81.76%,and 80.38%*** SVM model is more efficient than other models which are 21.38%more than exiting machine learning-based works.

关键词： Diabetics classification imbalanced data split-vote instance duplication

Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences

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Computers, Materials & Continua 2023年第3期74卷 5017-5033页

作者： Umair Muneer Butt Hadiqa Aman Ullah sukumar Letchmunan Iqra Tariq Fadratul Hafinaz Hassan Tieng Wei Koh School of Computer Sciences Universiti Sains MalaysiaPenang1180Malaysia Department of Computer Science The University of ChenabGujrat50700Pakistan Department of Software Engineering and Information System Universiti Putra MalaysiaSelangor43400Malaysia

Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social ***,dynamic environments and anthropometric differences between individuals make it harder to recognize *** study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world *** uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural ***,the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification *** state-of-the-art pre-trained models are exploited to find the best model for spatial feature *** temporal sequence,this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short TermMemory(BiLSTM)to capture *** state-of-the-art datasets,UCF101 and HMDB51,are used for evaluation *** addition,seven state-of-the-art optimizers are used to fine-tune the proposed network ***,this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network(CNN),where two streams use RGB *** contrast,the other uses optical flow ***,the proposed ensemble approach using max hard voting outperforms state-ofthe-art methods with 96.30%and 90.07%accuracies on the UCF101 and HMDB51 datasets.

关键词： Human activity recognition deep learning transfer learning neural network ensemble learning spatio-temporal

Human Exposure Assessment of Element Pollution for Environmental Health Implications: Teeth as a Biomonitoring Tool

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Journal of Geoscience and Environment Protection 2018年第3期6卷 37-53页

作者： Athimoolam sukumar Department of Education in Science and Mathematics Regional Institute of Education (RIE) National Council of Educational Research and Training (NCERT) Mysore India

Reference values reflecting the findings of natural concentrations of teeth in a well-defined group of individuals, are indispensable, if one is to interpret results generated for clinical utility. Hence, a comprehensive compilation of literature survey is attempted to make available as a reference guideline for tooth element concentrations. Presently, the reference values are proposed for 19 elements. Several factors that are found influencing element levels, are common to any biosample and are broadly grouped under four categories namely, the factors of teeth, donor, environment and analytical methods. How best the influencing factors to be considered during analysis, are discussed. It is elucidated that standardized method of analysis with quality assurance and precision will reduce the ambiguity of comparison of inter-laboratory measurement. When the merits and demerits of element measurements are evaluated, it is recognized that except a hurdle of difficult specific sampling, many advantages make teeth an attractive material for environmental health monitoring of population and for assessment of element status of deficiency and excess due to differential exposure. The available data of tooth elements are lesser in comparison to data of blood and hair;further studies are required for reference values of others elements and for distribution pattern in different conditions, parts and types of teeth.

关键词： Environmental Health Monitoring Elements Human Teeth Reference Values Element Exposure