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CSEE Journal of Power and Energy Systems 2022年第3期8卷 682-695页

作者： praveen kumar bonthagorla Suresh Mikkili Department of Electrical and Electronics Engineering National Institute of TechnologyGoaIndia

Currently,the critical challenge in solar photovoltaic(PV)systems is to make them energy efficient.One of the key factors that can reduce the PV system power output is partial shading conditions(PSCs).The reduction in power output not only depends on a shaded region but also depends on the pattern of shading and physical position of shaded modules in the array.Due to PSCs,mismatch losses are induced between the shaded modules which can cause several peaks in the output power-voltage(P-V)characteristics.The series-parallel(SP),total-cross-tied(TCT),bridge-link(BL),honey-comb(HC),and triple-tied(TT)configurations are considered as conventional configurations,which are severely affected by PSCs and generate more mismatch power losses along with a greater number of local peaks.To reduce the effect of PSCs,hybrid PV array configurations,such as series-parallel:total-cross-tied(SP-TCT),bridge-link:total-cross-tied(BL-TCT),honey-comb:total-cross-tied(HC-TCT)and bridge-link:honey-comb(BL-HC)are proposed.This paper briefly discusses the modeling,simulation and performance evaluation of hybrid and conventional 7×7 PV array configurations during different PSCs in a Matlab/Simulink environment.The performance of hybrid and conventional PV configurations are evaluated and compared in terms of global maximum power(GMP),voltage and currents at GMP,open and short circuit voltage and currents,mismatch power loss(MPL),fill factor,efficiency,and a number of local maximum power peaks(LMPPs).

关键词： Fill factor global maximum power(GMP) hybrid PV array configuration maximum power point(MPP) mismatch power loss(MPL) partial shading triple-tied(TT)

Optimal PV Array Configuration for Extracting Maximum Power Under Partial Shading Conditions by Mitigating Mismatching Power Losses

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CSEE Journal of Power and Energy Systems 2022年第2期8卷 499-510页

作者： praveen kumar bonthagorla Suresh Mikkili the Electrical and Electronics Engineering Department National Institute of Technology Goa403401India

The grid-connected or standalone PV central inverter architecture is comprised of several PV modules which are connected in different ways to form the PV array.The power generation capability of the PV array is primarily affected by partial shading conditions(PSC).Due to PSCs,the power output of the PV array is dramatically reduced,and mismatching losses are induced in the PV modules.Based on the extent of these problems,multiple peaks also appear in the power-voltage(P-V)curve,which makes it very difficult to track the global maximum power point(GMPP).The main objective of this research paper is to model and simulate the series(S),series-parallel(SP),bridge-link(BL),honey-comb(HC),total-cross-tied(TCT)and proposed triple-tied(TT)solar PV array configurations under various partial shading scenarios.The performance of all PV configurations is evaluated under a uniform approach,considering eight different shading scenarios.The performance of the considered PV configurations is analyzed in terms of their mismatching power losses,fill factors,efficiency,global maximum power points(GMPPs),local maximum power points(LMPPs),voltages and currents at GMPPs,open circuit voltage and short circuit currents.The above-mentioned PV configurations are modeled and simulated in a Matlab/Simulink environment by considering the KC-200GT module parameters.

关键词： Photo voltaic(PV) PV array configurations triple-tied(TT) maximum power point(MPP) partial shading mismatching power losses fill factor efficiency

Hybrid, Optimal, Intelligent and Classical PV MPPT Techniques: A Review

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CSEE Journal of Power and Energy Systems 2021年第1期7卷 9-33页

作者： Ratnakar Babu Bollipo Suresh Mikkili praveen kumar bonthagorla Department of Electrical and Electronics Engineering National Institute of Technology GoaFARMAGUDIPondaGoa 403401India

Renewable energy-based solar photovoltaic(PV)generation is the best alternative for conventional energy sources because of its natural abundance and environment friendly characteristics.Maximum power extraction from the PV system plays a critical role in increasing the efficiency of the solar power generation during partial shading conditions(PSCs).Therefore,a suitable maximum power point tracking(MPPT)technique to track the maximum power point(MPP)is of high need,even under PSCs.This paper presents an organized and concise review of MPPT techniques implemented for the PV systems in literature along with recent publications on various hardware design methodologies.Their classification is done into four categories,i.***.classical,intelligent,optimal,and hybrid depending on the tracking algorithm utilized to track MPP under PSCs.During uniform insolation,classical methods are highly preferred as there is only one peak in the P-V curve.However,under PSCs,the F-V curve exhibits multiple peaks,one global maximum power point(GMPP)and remaining are local maximum power points(LMPP’s).Under the PSCs,classical methods fail to operate at GMPP and hence there is a need for more advanced MPPT techniques.Every MPPT technique has its advantages and limits,but a streamlined MPPT is drafted in numerous parameters like sensors required,hardware implementation,cost viability,tracking speed and tracking efficiency.This study provides the advancement in this area since some parameter comparison is made at the end of every classification,which might be a prominent base-rule for picking the most gainful sort of MPPT for further research.

关键词： GMPP MPPT classification MPPT techniques partial shading conditions(PSCs) photovoltaic system

Genes linked to obesity-related infertility: bridging the knowledge gap

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生殖与发育医学(英文) 2024年第2期8卷 121-129页

作者： Sekar praveen kumar Chandra Veerabathiran Ramakrishnan Human Cytogenetics and Genomics Laboratory Faculty of Allied Health Sciences Chettinad Academy of Research and Education Kelambakkam Tamil Nadu India

Genetic factors play a pivotal role in the complex relationship between obesity and infertility. This article delves into the genetics of obesity-related infertility, focusing on the essential genes and mechanisms in both sexes. We explored infertility factors in obese females, focusing on polycystic ovary syndrome (PCOS) and the influence of genes like insulin receptor (INSR), androgen receptor (AR), and follicle-stimulating hormone receptor (FSHR). Epigenetic changes are believed to contribute to PCOS-related infertility. The impact of adipokines and inflammation on obesity-related infertility has been discussed, with genes such as fat mass and obesity (FTO) and melanocortin-4-receptor (MC4R) playing significant roles. Genetic factors affecting sperm quality and function, including nuclear receptor subfamily 3 group C member 1 (NR3C1) and methylenetetrahydrofolate reductase (MTHFR), have been investigated in obesity-related infertility in males. Hormonal dysregulation influenced by genetic markers, such as leptin receptor (LEPR), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6), was also examined. Genetic factors play a vital role in obesity-related infertility in both sexes. Genes involved in metabolism, hormonal regulation, and inflammation contribute to the complex association between obesity and infertility. Epigenetic changes further complicate the relationship. Understanding these genetic mechanisms is essential to address obesity-related infertility and develop personalized interventions.

关键词： Obesity Infertility PCOS DNA methylation Epigenetics

Deep Learning-Based Speech Emotion Recognition: Leveraging Diverse Datasets and Augmentation Techniques for Robust Modeling

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Journal of Harbin Institute of Technology(New series) 2024年

作者： Ayush Porwal praveen kumar Tyagi Ajay Sharma Dheeraj kumar Agarwal Department of Electronics and Instrumentation Engineering Shri G.S.Institute of Technology and Science Department of Electronics and Communication Engineering Maulana Azad National Institute of Technology School of Computing Science and Engineering VIT Bhopal University

In recent years， Speech Emotion Recognition (SER) has developed into an essential instrument for interpreting human emotions from auditory data. The proposed research focused on the development of a SER system employing deep learning and multiple datasets containing samples of emotive speech. The primary objective of this research endeavor is to investigate the utilization of Convolutional Neural Networks (CNNs) in the process of sound feature extraction. Stretching， pitch manipulation， and noise injection are a few of the techniques utilized in this study to improve the data quality. The investigation includes coverage of these methods. Feature extraction methods including Zero Crossing Rate， Chroma＿stft， MFCC， RMS， and MelSpectogram are used to train a model. By using these techniques， audio signals can be transformed into recognized features that can be utilized to train the model. Ultimately， the study will produce a thorough evaluation of the model’s performance. When this method was applied， the model achieved an impressive accuracy of 94.57% on the test dataset. Proposed work also validated on EMO-BD and IEMOCAP dataset. These consist of further data augmentation， feature engineering， and hyperparameter optimization. By following these development paths， SER systems will be able to be implemented in real-world scenarios with greater accuracy and resilience.

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Cost Optimized Switching of Routing Protocol Scheme for IoT Applications

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Computer Systems Science & Engineering 2022年第4期41卷 67-82页

作者： Karunanithi praveen kumar Perumal Sivanesan School of Computing SASTRA UniversityThanjavur613401TamilnaduIndia

In this work,we propose a context-aware switching of routing protocol scheme for speciﬁc application requirements of IoT in real-time using a software-deﬁned networking controller in wireless sensor networks.The work planned has two stages i)Selection of suitable routing protocol(RP)for given IoT applications using higher cognitive process and ii)Deployment of the corresponding routing protocol.We use the supervised learning-regression method for classiﬁcation of the routing protocol while considering the network parameters like stability,path delay,energy utilization,and throughput.The chosen routing protocol will be set in the sensor network using a software-deﬁned networking controller in an exceedinglyﬂexible manner during the second stage.Extensive simulation has been done and results are evaluated to point out the strength of the proposed work,while dynamically varying the speciﬁc requirements of IoT applications.We observe that the work proposed is path-breaking the prevailing methods,where a speciﬁc routing protocol is employed throughout the period of time.It’s clearly shown that the proposed,Low-cost Context-Aware Protocol Switching(LCAPS)scheme is efﬁcient in improving the performance of the sensor network and also meets the speciﬁc application requirements of IoT by using Software-Deﬁned Wireless Sensor Networks SDWSNs.

关键词： Internet of things sensor network efﬁciency software-deﬁned networking wireless sensor networks supervised learning cost optimization

Mix design,development,production and policies of recycled hot mix asphalt:A review

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Journal of Traffic and Transportation Engineering(English Edition) 2022年第5期9卷 765-794页

作者： Ankit Sharma Gondaimei Ransinchung Rongmei Naga praveen kumar Priti Rai Department of Civil Engineering Indian Institute of Technology RoorkeeRoorkee 247667India

Worldwide,flexible pavements are the paramount type of pavements.These national assets can be recycled to serve the next design life without the need to dispose of them in landfill.The old/distressed,flexible pavement material is called,reclaimed asphalt pavement(RAP)material.In view of the sustainable development practice,100%RAP should be recycled.However,the practical range of RAP incorporation in a drum mix plant ranges from 10%to 50%whereas in a batch mix plant,it is 10%-35%.In a batch mix plant,incorporation of the hot dried RAP(instead of cold RAP feeding)can increase the RAP incorporation level by 20%.Studies recommended that the rejuvenator should be added over the RAP material instead adding with the base binder.The addition of rejuvenator on the RAP conveyor belt(to the pug mill),provided sufficient time for rejuvenating the aged binder coating over RAP aggregates.Further,a thorough knowledge of the mix design process of recycled hot mix asphalt(RAP-HMA)is essential to produce a durable mix.For high RAP content(>20%),the RAP binder properties are important for the mix design process.However,very limited studies discussed(in detail)the recovery process of the RAP binder.The review article through light on the binder recovery process,method of RAP gradation,specific gravity determination for RAP material,minimum desirable properties of the RAP material etc.This review paper also provides a narrative review of the historical development of RAP-HMA technology,technical aspects related to the procurement of RAP material,mix design and production of the recycled mix.Moreover,the international&national policies/laws for construction and demolition waste are discussed.

关键词： Reclaimed asphalt pavement Hot mix asphalt Recycled mix Blending chart Rejuvenator dose Batch and drum asphalt plant

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Isospin dependent properties of the isotopic chains of Scandium and Titanium nuclei within the relativistic mean-field formalism

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Chinese Physics C 2022年第8期46卷 155-169页

作者： praveen K.Yadav Raj kumar M.Bhuyan School of Physics and Materials Science Thapar Institute of Engineering and TechnologyPatiala-147004PunjabIndia Center for Theoretical and Computational Physics Department of PhysicsFaculty of ScienceUniversity of MalayaKuala Lumpur 50603Malaysia Institute of Research and Development Duy Tan UniversityDa Nang 550000Vietnam

Density-dependent nuclear symmetry energy is directly related to iso spin asymmetry for finite and infinite nuclear systems.It is critical to determine the coefficients of symmetry energy and their related observables because they hold great importance in different areas of nuclear physics,such as the analysis of the structure of ground state exotic nuclei and neutron star studies.The ground state bulk properties of Scandium(Z=21) and Titanium(Z=22) nuclei are calculated,such as their nuclear binding energy(B.E.),quadrupole deformation(β_2),two-neutron separation energy(S_(2 n)),differential variation in the two-neutron separation energy(dS_(2 n)),and root-mean-square charge radius(r_(ch)).The iso spin properties,namely the coefficient of nuclear symmetry energy and its components,such as the surface and volume symmetry energy of a finite isotopic chain,from the corresponding quantities of infinite nuclear matter,are also estimated.Finally,we correlate the neutron-skin thickness with the coefficient of symmetry energy and the related observables corresponding to the isotopic chains of these nuclei.The coherent density fluctuation model(CDFM) is used to estimate the iso spin-dependent properties of finite nuclei,such as symmetry energy,surface symmetry energy,and volume symmetry energy,from their corresponding component in infinite nuclear matter.The relativistic mean-field(RMF) formalism with non-linear NL3 and relativistic-Hartree-Bogoliubov theory with density-dependent DD-ME2 interaction parameters are employed in the analysis.The weight function |F(x)|^(2) is estimated using the total density of each nucleus,which in turn is used with the nuclear matter quantities to obtain the effective symmetry energy and its components in finite nuclei.We calculate the ground state bulk properties,such as nuclear binding energy,quadrupole deformation,two-neutron separation energy,differential variation in the two-neutron separation energy,and root-mean-square charge radius,for the Sc-and Ti-isotopic chains using the non-li

关键词： relativistic energy density functional symmetry energy weight function isospin asymmetry

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Survey on recent advances in IoT application layer protocols and machine learning scope for research directions

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Digital Communications and Networks 2022年第5期8卷 727-744页

作者： praveen kumar Donta Satish Narayana Srirama Tarachand Amgoth Chandra Sekhara Rao Annavarapu Department of Computer Science and Engineering Indian Institute of Technology(Indian School of Mines)Dhanbad826004India School of Computer and Information Sciences University of HyderabadHyderabad500046India Mobile&Cloud Lab Institute of Computer ScienceFaculty of Science and TechnologyUniversity of Tartu50090Estonia

The Internet of Things(IoT)has been growing over the past few years due to its flexibility and ease of use in real-time applications.The IoT's foremost task is ensuring that there is proper communication among different types of applications and devices,and that the application layer protocols fulfill this necessity.However,as the number of applications grows,it is necessary to modify or enhance the application layer protocols according to specific IoT applications,allowing specific issues to be addressed,such as dynamic adaption to network conditions and interoperability.Recently,several IoT application layer protocols have been enhanced and modified according to application requirements.However,no existing survey articles focus on these protocols.In this article,we survey traditional and recent advances in IoT application layer protocols,as well as relevant real-time applications and their adapted application layer protocols for improving performance.As changing the nature of protocols for each application is unrealistic,machine learning offers means of making protocols intelligent and is able to adapt dynamically.In this context,we focus on providing open challenges to drive IoT application layer protocols in such a direction.

关键词： Internet of things Machine learning Application layer Request-response protocols Publish-subscribe protocols

The effect of pH on stability and thermal performance of graphene oxide and copper oxide hybrid nanofluids for heat transfer applications:Application of novel machine learning technique

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Journal of Energy Chemistry 2023年第7期82卷 359-374,I0009页

作者： praveen kumar Kanti Prabhakar Sharma K.V.Sharma M.P.Maiya Department of Mechanical Engineering Indian Institute of Technology MadrasChennai 600036India Department of Mechanical Engineering Delhi Skill and Entrepreneurship UniversityDelhi 110089India Center for Energy Studies Department of Mechanical EngineeringJNTUH College of EngineeringKukatpallyHyderabad 500085Telangan1India

This paper investigates the effects of pH on stability and thermal properties of copper oxide(CuO),graphene oxide(GO),and their hybrid nanofluid(HNF)at different mixing ratios.Initially,sol-gel and Hummer’s method was employed for the synthesis of CuO and GO nanoparticles(NPs),and they are characterized with various techniques.The effects of two different surfactants were analyzed on nanofluid’s(NF’s)stability at different pH values.The properties like thermal conductivity(TC)and viscosity(VST)of NFs were measured at different volume concentration(0.1 vol%to 1.0 vol%)and temperature range of 30-60℃,respectively.The TC and VST of GO/CuO(50:50)HNF are higher than that of GO/CuO(20:80).The figure of merit(FOM)is determined for the studied HNFs.The correlations were presented to calculate the TC as well as VST of HNFs.Two modern novel machine learning-based ensemble approaches were employed for predictive model development for TC and VST of considered HNFs.The comparison of prognostic models with Taylor’s diagram revealed that Bayesian optimized support vector machine(BoASVM)was superior to Bayesian optimized boosted regression trees(BoA-BRT)for both TC and VST models.

关键词： CuO Figure of merit Graphene oxide Machine learning pH Stability

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