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Journal of Wuhan University of Technology(Materials Science) 2023年第5期38卷 1077-1085页

作者： premkumar r ramesh Babu Chokkalingam Meyyappan PL Shanmugasundaram M Kalasalingam Academy of research and Education Krishnan KoilTamil Nadu626126 India Vellore Institute of Technology-Chennai Tamilnadu600127 India

This study aims to investigate the behavior of alkali activated mortar,which is made of naturally available magnesium silicate as source *** magnesium silicate,ultrafine natural steatite powder(UFNSP)is used as the primary source of binder,and the activation is initiated through the alkali liquid which is proportioned in various combinations of silicate to hydroxide ratio(Na_(2)SiO_(3)/Na OH)ratio,and this ratio in this study varies from 1 to *** UFNSP is calcined at two difierent temperatures,700 and 1000℃.The mortar mix is proportioned as 1:3 between powder and the fine aggregate,and the mortar is prepared with hydroxide molarity(M)of 10 *** mortar is cured for 48 hours at 60℃and the compressive strength was *** the mix were studied for its microstructural behavior along with compressive *** mix proportion of the mortar,and the results obtained through microstructural characterization were combinedly formed as input for artificial neural network(ANN)predictive *** model is designed to predict the compressive strength,which is trained through Bayesian regularization algorithm with varying hidden neurons of 7 to *** experimental and predictive study shows that the strength is influenced by both Na_(2)SiO_(3)/Na OH ratio and calcination *** the ANN is influenced by mainly calcination temperature and uncorrelation occurs in selected samples of 1000℃calcined UFNSP mix.

关键词： magnesium silicate silicate alkali activation geopolymer UFNSP prediction

Cytokine Storm of COVID-19 and Its Impact on Patients with and without Chronic Liver Disease

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Journal of Clinical and Translational Hepatology 2021年第2期9卷 256-264页

作者： Madhumita premkumar Chandan Kumar Kedarisetty Departments of Hepatology Postgraduate Institute of Medical Education and ResearchChandigarhIndia Department of Hepatology and Liver transplantation Gleneagles Global HospitalHyderabadIndia

The coronavirus pandemic has resulted in increased rates of hepatic decompensation,morbidity and mortality in patients suffering from existing liver disease,and deranged liver biochemistries in those without liver *** patients with cirrhosis with coronavirus disease 2019(COVID-19),new onset organ failures manifesting as acute-onchronic liver failure have also been *** severe acute respiratory syndrome-coronavirus-2(SArS-CoV-2)also directly binds to enterocytes and cholangiocytes via the angiotensin converting enzyme receptor 2,although the lung remains the portal of *** with the COVID-19 related bystander hepatitis,a systemic inflammatory response is noted due to unregulated macrophage activation syndrome and cytokine ***,the exact definition and diagnostic criteria of the‘cytokine storm’in COVID-19 are yet *** addition,inflammatory markers like C-reactive protein,ferritin,D-dimer and procalcitonin are frequently *** in turn leads to disease progression,activation of the coagulation cascade,vascular microthrombi and immune-mediated injury in different organ *** liver chemistries are also noted due to the cytokine storm,and synergistic hypoxic or ischemic liver injury,drug-induced liver injury,and use of hepatotoxic antiviral agents all contribute to deranged liver *** of an unregulated cytokine storm at an early stage may avert disease morbidity and *** immunomodulator drugs and repurposed immunosuppressive agents have been used in COVID-19 with varying degrees of success.

关键词： Chronic liver disease COVID-19 Cytokines Hepatitis Gut-liver axis

A New Metaheuristic Optimization Algorithms for Brushless Direct Current Wheel Motor Design Problem

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Computers, Materials & Continua 2021年第5期67卷 2227-2242页

作者： M.premkumar r.Sowmya Pradeep Jangir Kottakkaran Sooppy Nisar Mujahed Aldhaifallah Department of Electrical and Electronics Engineering GMR Institute of TechnologyRajam532127India Department of Electrical and Electronics Engineering National Institute of TechnologyTiruchirappalli620015India rajasthan rajya Vidyut Prasaran Nigam Sikar305001India Department of Mathematics College of Arts and SciencesPrince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia Systems Engineering Department King Fahd University of Petroleum&MineralsDhahranSaudi Arabia

The Equilibrium Optimizer(EO),Grey Wolf Optimizer(GWO),and Whale Optimizer(WO)algorithms are being recently developed for engineering optimization *** this paper,the EO,GWO,and WO algorithms are applied individually for a brushless direct current(BLDC)design optimization *** EO algorithm is inspired by the models utilized to find the system’s dynamic state and equilibrium *** GWO and WO algorithms are inspired by the hunting behavior of the wolf and the whale,*** primary purpose of any optimization technique is to find the optimal configuration by maximizing motor efficiency and/or minimizing the total ***,two objective functions are being used to achieve these *** first refers to a design with high power output and *** second is a constraint imposed by the reality that the motor is built into the wheel of the vehicle and,therefore,a lightweight is *** EO,GWO,and WOA algorithms are then utilized to optimize the BLDC motor’s design variables to minimize the motor’s total mass or maximize the motor efficiency by simultaneously satisfying the six inequality *** simulation is carried out using MATLAB simulation software,and the simulation results prove the dominance of the proposed *** paper also suggests an efficient method from the proposed three methods for the BLDC motor design optimization problem.

关键词： BLDC motor constrained equilibrium optimizer singleobjective optimization

Kombucha SCOBY-based carbon and graphene oxide wrapped sulfur/polyacrylonitrile as a high-capacity cathode in lithium-sulfur batteries

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Frontiers of Chemical Science and Engineering 2020年第6期14卷 976-987页

作者： Krishnaveni Kalaiappan Subadevi rengapillai Sivakumar Marimuthu raja Murugan premkumar Thiru Energy Materials Lab Department of PhysicsScience BlockAlagappa UniversityKaraikudi630003 Tamil NaduIndia Electrochemical Power Systems Division CSIR-Central Electrochemical Research InstituteKaraikudi630003 Tamil NaduIndia

Hierarchically-porous carbon nano sheets were prepared as a conductive additive for sulfur/polyacrylonitrile(S/PAN)composite cathodes using a simple heat *** this study,kombucha(that was derived from symbiotic culture of bacteria and yeast)carbon(KC)and graphene oxide(GO)were used as a carbon host *** rational-designed S/PAN/KC/GO hybrid composites greatly suppress the diffusion of polysulfides by providing strong physical and chemical *** cathode delivered an initial discharge capacity of 1652 mAh·g^-1 at a 0.1 C rate and a 100th cycle capacity of 1193 mAh·g^-*** nano sheets with embedded hierarchical pores create a conductive network that provide effective electron transfer and fast electrochemical ***,the nitrogen component of PAN can raise the affinity/interaction of the carbon host with lithium polysulfides,supporting the cyclic *** results exploit the cumulative contribution of both the conductive carbon matrix and PAN in the enhanced performance of the positive electrode.

关键词： sulfur cathode kombucha SCOBY graphene oxide polyacrylonitrile lithium-sulfur battery

Cytokinin induced shoot regeneration and flowering of Scoparia dulcis L.(Scrophulariaceae)-an ethnomedicinal herb

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Asian Pacific Journal of Tropical Biomedicine 2011年第3期1卷 169-172页

作者： premkumar G Sankaranarayanan r Jeeva S rajarathinam K Department of Botany Virudhunagar Hindu Nadars' Senthikumara Nadar College Department of Floriculture and Medicinal Crops Horticulture College and Research Institute Centre for Biodiversity and Biotechnology Department of BotanyN.M.Christian College

Objective:To develop an improved protocol for micropropagation of ethnomedicinally important Scoparia dulcis(***) ***:Explants were inoculated on MS basal medium supplemented with kinelin and 6-benzylaminopurine for shoot bud *** enhance the shoot induction,various auxins like 3-indoleacetic acid or 3-indolebutyric acid or a-naphthylacetic acid were tested along with 2.32 M KI and 4.44 μ M *** regenerated shoots were rooted in half strength MS medium supplemented with various concentrations of IAA,IBA or *** roots were developed,the plantlets were transplanted to pots filled with vermiculate and sand and kept in growth chamber with 70%-80%humidity under 16 h *** acclimatization,the plantlets were transferred to the garden and survival percentage was *** were statistically analyzed and means were compared using Duncan's multiple range test(Presults:An in vitro method was developed to induce high frequency shoots regeneration from stem,mature leaf and young leaf explants of *** induction on young leaf explants was most successful in MS medium supplemented with combination of two cytokinins(2.32 μ M KI and 4.44 μ M BAP) 2.85 μ M IAA,10%CM and 1 483.79 μM adenine sulfate.A single young leaf explant was capable of producing 59 shoots after 13 days of culture. Flower was induced in medium supplemented with combination of KI and ***: Cytokinins are the key factor to induce the direct shoot regeneration and flowering of ***.

关键词： Ethnomedicinal herb Scoparia dulcis Shoot induction regeneration Cytokinin Micropropagation Explant Flowering Auxin Survival percentage Bud induction

IrKO:An Improved runge-Kutta Optimization Algorithm for Global Optimization Problems

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Computers, Materials & Continua 2022年第3期70卷 4803-4827页

作者： r.Manjula Devi M.premkumar Pradeep Jangir Mohamed Abdelghany Elkotb rajvikram Madurai Elavarasan Kottakkaran Sooppy Nisar Department of Computer Science and Engineering Kongu Engineering CollegePerundurai638060Tamil NaduIndia Department of Electrical&Electronics Engineering Dayananda Sagar College of EngineeringBengaluru560078KarnatakaIndia rajasthan rajya Vidyut Prasaran Nigam Sikar332025RajasthanIndia Mechanical Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Mechanical Engineering Department Faculty of EngineeringKafrelsheikh UniversityEgypt Clean and resilient Energy Systems(CArES)Laboratory Texas A&MUniversityGalveston77553TXUSA College of Arts and Sciences Prince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost,gains,energy,mass,and so *** order to solve optimization problems,metaheuristic algorithms are *** of these techniques are influenced by collective knowledge and natural *** is no such thing as the best or worst algorithm;instead,there are more effective algorithms for certain ***,in this paper,a new improved variant of a recently proposed metaphorless runge-Kutta Optimization(rKO)algorithm,called Improved runge-Kutta Optimization(IrKO)algorithm,is suggested for solving optimization *** IrKO is formulated using the basic rKO and local escaping operator to enhance the diversification and intensification capability of the basic rKO *** performance of the proposed IrKO algorithm is validated on 23 standard benchmark functions and three engineering constrained optimization *** outcomes of IrKO are compared with seven state-of-the-art algorithms,including the basic rKO *** to other algorithms,the recommended IrKO algorithm is superior in discovering the optimal results for all selected optimization *** runtime of IrKO is less than 0.5 s for most of the 23 benchmark problems and stands first for most of the selected problems,including real-world optimization problems.

关键词： Engineering design global optimization local escaping operator metaheuristics runge-Kutta optimization algorithm

BHGSO:Binary Hunger Games Search Optimization Algorithm for Feature Selection Problem

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Computers, Materials & Continua 2022年第1期70卷 557-579页

作者： r.Manjula Devi M.premkumar Pradeep Jangir B.Santhosh Kumar Dalal Alrowaili Kottakkaran Sooppy Nisar Department of Computer Science and Engineering Kongu Engineering CollegePerundurai638060Tamil NaduIndia Department of Electrical and Electronics Engineering Dayananda Sagar College of EngineeringBengaluru560078KarnatakaIndia rajasthan rajya Vidyut Prasaran Nigam Sikar332025RajasthanIndia Department of Computer Science and Engineering Guru Nanak Institute of TechnologyHyderabad501506TelanganaIndia Mathematics Department College of ScienceJouf UniversitySakakaP.O.Box:2014Saudi Arabia Department of Mathematics College of Arts and SciencesPrince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

In machine learning and data mining,feature selection(FS)is a traditional and complicated optimization *** the run time increases exponentially,FS is treated as an NP-hard *** researcher’s effort to build a new FS solution was inspired by the ongoing need for an efficient FS framework and the success rates of swarming outcomes in different optimization *** paper presents two binary variants of a Hunger Games Search Optimization(HGSO)algorithm based on V-and S-shaped transfer functions within a wrapper FS model for choosing the best features from a large *** proposed technique transforms the continuous HGSO into a binary variant using V-and S-shaped transfer functions(BHGSO-V and BHGSO-S).To validate the accuracy,16 famous UCI datasets are considered and compared with different state-of-the-art metaheuristic binary *** findings demonstrate that BHGSO-V achieves better performance in terms of the selected number of features,classification accuracy,run time,and fitness values than other state-of-the-art *** results demonstrate that the BHGSO-V algorithm can reduce dimensionality and choose the most helpful features for classification *** proposed BHGSO-V achieves 95%average classification accuracy for most of the datasets,and run time is less than 5 *** low and medium dimensional datasets and less than 10 sec for high dimensional datasets.

关键词： Binary optimization feature selection machine learning hunger games search optimization

State-of-Charge Estimation of Lithium-Ion Battery for Electric Vehicles Using Deep Neural Network

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Computers, Materials & Continua 2022年第12期73卷 6289-6306页

作者： M.premkumar r.Sowmya S.Sridhar C.Kumar Mohamed Abbas Malak S.Alqahtani Kottakkaran Sooppy Nisar Department of Electrical and Electronics Engineering Dayananda Sagar College of EngineeringBengaluru560078KarnatakaIndia Department of Electrical and Electronics Engineering National Institute of TechnologyTiruchirapalli620015Tamil NaduIndia Department of Electrical and Electronics Engineering M S Ramaiah Institute of TechnologyBengaluru560054KarnatakaIndia Department of Electrical and Electronics Engineering M.Kumarasamy College of EngineeringKarur639113Tamil NaduIndia Electrical Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Computers and Communications Department College of EngineeringDelta University for Science and TechnologyGamasa35712Egypt Faculty of Technology The GatewayDe Montfort UniversityLeicesterLE19BHUnited Kingdom Department of Mathematics College of Arts and SciencesPrince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

It is critical to have precise data about Lithium-ion batteries,such as the State-of-Charge(SoC),to maintain a safe and consistent functioning of battery packs in energy storage systems of electric *** strategies for estimating battery SoC,such as by including the coulomb counting and Kalman filter,have been *** a result of the differences in parameter values between each cell,when these methods are applied to highcapacity battery packs,it has difficulties sustaining the prediction accuracy of overall *** a result of aging,the variation in the parameters of each cell is higher as more time is spent in *** is suggested in this study to establish an SoC estimate model for a Lithium-ion battery by employing an enhanced Deep Neural Network(DNN)*** is because the proposed DNN has a substantial hidden layer,which can accurately predict the SoC of an unknown driving cycle during training,making it ideal for SoC *** evaluate the nonlinearities between voltage and current at various SoCs and temperatures,the proposed DNN is *** current and voltage data measured at various temperatures throughout discharge/charge cycles is necessary for training and testing *** the method has been thoroughly trained with the data collected,it is used for additional cells cycle tests to predict their *** simulation has been conducted for two different Li-ion battery *** to the experimental data,the suggested DNN-based SoC estimate approach produces a low mean absolute error and root-mean-square-error values,say less than 5%errors.

关键词： Artificial intelligence deep neural network Li-ion battery parameter variation SoC estimation

DArTS-Drone and Artificial Intelligence reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline resilience

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International Journal of Disaster risk Science 2022年第5期13卷 810-821页

作者： premkumar ravishankar Seokyon Hwang Jing Zhang Ibrahim X.Khalilullah Berna Eren-Tokgoz Department of Industrial and Systems Engineering Lamar UniversityBeaumontTX 77710USA Construction Management Program Lamar UniversityBeaumontTX 77710USA Department of Computer Science Lamar UniversityBeaumontTX 77710USA

The need for safe operation and effective maintenance of pipelines grows as oil and gas demand ***,it is increasingly imperative to monitor and inspect the pipeline system,detect causes contributing to developing pipeline damage,and perform preventive maintenance in a timely ***,pipeline inspection is performed at pre-determined intervals of several months,which is not sufficiently robust in terms of *** research proposes a drone and artificial intelligence reconsolidated technological solution(DArTS) by integrating drone technology and deep learning *** solution is aimed to detect the targeted potential root problems-pipes out of alignment and deterioration of pipe support system-that can cause critical pipeline failures and predict the progress of the detected problems by collecting and analyzing image data *** test results show that DArTS can be effectively used to support decision making for preventive pipeline maintenance to increase pipeline system s afety and resilience.

关键词： Artifcial intelligence Asset management Drone application Midstream industry Pipeline resilience Predictive maintenance

Carvacrol attenuates N-nitrosodiethylamine induced liver injury in experimental Wistar rats

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Food Science and Human Wellness 2015年第2期4卷 66-74页

作者： Balan rajan rajendran ravikumar Thandavamoorthy premkumar Thiruvengadam Devaki Department of Biochemistry Guindy CampusUniversity of MadrasChennai 600025TNIndia

Carvacrol is a main constituent in the essential oils of countless aromatic plants including Origanum Vulgare and Thymus vulgari,which has been assessed for substantial pharmacological *** recent years,notable research has been embarked on to establish the biological actions of Carvacrol for its promising use in clinical *** present study is an attempt to reveal the protective role of Carvacrol against NNitrosodiethylamine(DEN)induced hepatic injury in male Wistar albino *** is an egregious toxin,present in numerous environmental factors,which enhances chemical driven liver damage by inducing oxidative stress and cellular *** of DEN(200 mg/kg bodyweight,I.P)to rats results in elevated marker enzymes(in both serum and tissue).Carvacrol(15 mg/kg body weight)suppressed the elevation of marker enzymes(in both serum and tissue)and augmented the antioxidants *** hoisted activities of Phase I enzymes and inferior activities of Phase II enzymes were observed in DEN-administered animals,whereas Carvacrol treated animals showed improved near normal *** observations also support the protective role of Carvacrol against DEN induced liver *** outcome from our findings intimate that Carvacrol might be beneficial in attenuating toxin induced liver damage.

关键词： protective damage rats