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International Journal of Mining Science and technology 2013年第5期23卷 725-731页

作者： t.laxmi Satya Sai Srikant D.S.Rao R.Bhima Rao Mineral Processing Department CSIR-Institute of Minerals and Materials Technology Department of Electronics and Communication Engineering SRM University Aryan College of Engineering and technology

this paper deals with the recovery of ilmenite mineral from red sediments of badlands topography and suggested flowsheet with material *** results of these investigations reveal that the red sediment samples contain 33.2%total heavy mineral,in which ilmenite mineral concentrate is 28.71%(by weight).the ilmenite concentrate recovered from red sediment sample by physical benefciation process,which included scrubbing,desliming,gravity concentration,magnetic and electrostatic separation,contains 99.41%grade with 97.3%*** ilmenite mineral concentrate recovered from red sediments is also suitable for industrial *** characterization studies on ilmenite reveal that the tiO2percentage is marginally increasing from 46.69%to 47.86%with increasing magnetic intensity from0.46 to 1.55 t.

关键词： Red sediments Badlands topography Ilmenite Benefciation Characterization

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Flotation tree analysis for recovery of sillimanite from red sediments

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International Journal of Mining Science and technology 2015年第5期25卷 843-848页

作者： laxmi t. Rao R.Bhima Advanced Materials technology Department Institute of Minerals & Materials Technology Aryan Institute of Engineering and technology Bijupatnaik University of Technology

In this paper an attempt is made to recover sillimanite by flotation tree analysis process and conventional flotation process from non magnetic fraction of red *** experimental results of both the processes are *** data reveal that the deslimed sample contains 33.2%(by weight) total heavy minerals and out of which the sillimanite mineral content is 3.6%(by weight).It is observed that flotation tree analysis needs 10 cells to get five output products and where as conventional flotation process needs 15 cells to recover similar grade of five output ***,flotation tree analysis is not only economic process but also efficient process(to say efficient process,the tree analysis product should be higher grade).

关键词： tree analysis Flotation Red sediment Sillimanite

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Recovery of total Heavy Minerals from Badlands of Basanputti Village,Odisha

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Journal of Earth Science 2012年第6期23卷 892-899页

作者： t.laxmi Rajalaxmi Mohapatra R Bhima Rao Institute of Minerals and Materials technology Council of Scientific and Industrial ResearchBhubaneswar 751013India Aryan Institute of Engineering and technology Bijupatnaik UniversityBhubaneswarIndia

the badland topography of Basanputti Village, Ganjam District, Odisha, possesses red sediments. the typical red sediment deposit, on average, consists of 71.8% total heavy minerals （tHM）, out of which 62.1% are ilmenite. the other heavy minerals sillimanite, zircon, garnet, monazite, and pyriboles are in the order of abundance identified. In this present study, Mozley mineral separator has been used to recover tHM from red sediment. Mineral separator results indicate that a product ob- tained contains 72.2% by weight with 94.4% tHM and 95% recovery. the ilmenite concentrate recov- ered using dry low-intensity magnetic separator from the tHM concentrate can be used in pigment in- dustries after suitable pyrometallurgical/chemical processing methods.

关键词： red sediment total heavy mineral (tHM) Mozley mineral separator Perm roll mag-netic separator ilmenite zircon.

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Coot Optimization with Deep Learning-Based False Data Injection Attack Recognition

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Computer Systems Science & Engineering 2023年第7期46卷 255-271页

作者： t.Satyanarayana Murthy P.Udayakumar Fayadh Alenezi E.laxmi Lydia Mohamad Khairi Ishak Department of Information technology Chaitanya Bharathi Institute of TechnologyHyderabadTelanganaIndia Department of Computer Science and Engineering Aditya Engineering CollegeSurampalemAndhra PradeshIndia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia

the recent developments in smart cities pose major security issues for the Internet of things(Iot)*** security issues directly result from inappropriate security management protocols and their implementation by Iot gadget ***-attackers take advantage of such gadgets’vulnerabilities through various attacks such as injection and Distributed Denial of Service(DDoS)*** this background,Intrusion Detection(ID)is the only way to identify the attacks and mitigate their *** recent advancements in Machine Learning(ML)and Deep Learning(DL)models are useful in effectively classifying *** current research paper introduces a new Coot Optimization Algorithm with a Deep Learning-based False Data Injection Attack Recognition(COADL-FDIAR)model for the Iot *** presented COADL-FDIAR technique aims to identify false data injection attacks in the Iot *** accomplish this,the COADL-FDIAR model initially preprocesses the input data and selects the features with the help of the Chi-square *** detect and classify false data injection attacks,the Stacked Long Short-term Memory(SLStM)model is exploited in this ***,the COA algorithm effectively adjusts the SLtSM model’s hyperparameters effectively and accomplishes a superior recognition *** proposed COADL-FDIAR model was experimentally validated using a standard dataset,and the outcomes were scrutinized under distinct *** comparative analysis results assured the superior performance of the proposed COADL-FDIAR model over other recent approaches with a maximum accuracy of 98.84%.

关键词： False data injection attack security internet of things deep learning coot optimization algorithm

Deep Learning Enabled Predictive Model for P2P Energy trading in tEM

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Computers, Materials & Continua 2022年第4期71卷 1473-1487页

作者： Pudi Sekhar t.J.Benedict Jose Velmurugan Subbiah Parvathy E.laxmi Lydia Seifedine Kadry Kuntha Pin Yunyoung Nam Department of Electrical and Electronics Engineering Vignan’s Institute of Information Technology(Autonomous)Visakhapatnam530049India Department of Computer Applications Government Arts&Science CollegeKanyakumari629401India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626126India Department of Computer Science and Engineering Vignan’s Institute of Information Technology(Autonomous)Visakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Department of ICt Convergence Soonchunhyang UniversityKorea Department of Computer Science and Engineering Soonchunhyang UniversityKorea

With the incorporation of distributed energy systems in the electric grid,transactive energy market(tEM)has become popular in balancing the demand as well as supply adaptively over the *** classical grid can be updated to the smart grid by the integration of Information and Communication technology(ICt)over the *** tEM allows the Peerto-Peer(P2P)energy trading in the grid that effectually connects the consumer and prosumer to trade energy among *** the same time,there is a need to predict the load for effectual P2P energy trading and can be accomplished by the use of machine learning(DML)*** some of the short term load prediction techniques have existed in the literature,there is still essential to consider the intrinsic features,parameter optimization,*** *** this aspect,this study devises new deep learning enabled short term load forecasting model for P2P energy trading(DLStLF-P2P)in *** proposed model involves the design of oppositional coyote optimization algorithm(OCOA)based feature selection technique in which the OCOA is derived by the integration of oppositional based learning(OBL)concept with COA for improved convergence ***,deep belief networks(DBN)are employed for the prediction of load in the P2P energy trading *** order to additional improve the predictive performance of the DBN model,a hyperparameter optimizer is introduced using chicken swarm optimization(CSO)algorithm is applied for the optimal choice of DBN parameters to improve the predictive *** simulation analysis of the proposed DLStLF-P2P is validated using the UK Smart Meter dataset and the obtained outcomes demonstrate the superiority of the DLStLF-P2P technique with the maximum training,testing,and validation accuracy of 90.17%,87.39%,and 87.86%.

关键词： Energy trading distributed systems power generation load forecasting deep learning peer-to-peer

Enhanced Archimedes Optimization Algorithm for Clustered Wireless Sensor Networks

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Computers, Materials & Continua 2022年第10期73卷 477-492页

作者： E.laxmi Lydia t.M.Nithya K.Vijayalakshmi Jeya Prakash Kadambaajan Gyanendra Prasad Joshi Sung Won Kim Computer Science and Engineering Vignan’s Institute of Information Technology(Autonomous)Andhra Pradesh530049India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Electronics&Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai600025India Department of Electronics&Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Wireless sensor networks(WSN)encompass a set of inexpensive and battery powered sensor nodes,commonly employed for data gathering and tracking *** energy utilization of the nodes in WSN is essential to capture data effectively and transmit them to *** latest developments of energy efficient clustering techniques can be widely applied to accomplish energy efficiency in the *** this aspect,this paper presents an enhanced Archimedes optimization based cluster head selection(EAOA-CHS)approach for *** goal of the EAOA-CHS method is to optimally choose the CHs from the available nodes in WSN and then organize the nodes into a set of ***,the EAOA is derived by the incorporation of the chaotic map and pseudo-random ***,the EAOA-CHS technique determines a fitness function involving total energy consumption and lifetime of *** design of EAOA for CH election in the WSN depicts the novelty of *** order to exhibit the enhanced efficiency of EAOA-CHS technique,a set of simulations are applied on 3 distinct conditions dependent upon the place of base station(BS).the simulation results pointed out the better outcomes of the EAOA-CHS technique over the recent methods under all scenarios.

关键词： Wireless sensor network CH selection energy efficiency clustering lifetime

Harris Hawks Optimizer with Graph Convolutional Network Based Weed Detection in Precision Agriculture

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Computer Systems Science & Engineering 2023年第8期46卷 1533-1547页

作者： Saud Yonbawi Sultan Alahmari t.Satyanarayana Murthy Padmakar Maddala E.laxmi Lydia Seifedine Kadry Jungeun Kim Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and technology RiyadhKingdom of Saudi Arabia Chaitanya Bharathi Institute of technology HyderabadTelanganaIndia Department of Civil Engineering Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop *** agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental *** control has become one of the significant problems in the agricultural *** traditional weed control,the entire field is treated uniformly by spraying the soil,a single herbicide dose,weed,and crops in the same *** more precise farming,robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the weed *** may lessen by large margin utilization of agrochemicals on agricultural fields and favour sustainable *** study presents a Harris Hawks Optimizer with Graph Convolutional Network based Weed Detection(HHOGCN-WD)technique for Precision *** HHOGCN-WD technique mainly focuses on identifying and classifying weeds for precision *** image pre-processing,the HHOGCN-WD model utilizes a bilateral normal filter(BNF)for noise *** addition,coupled convolutional neural network(CCNet)model is utilized to derive a set of feature *** detect and classify weed,the GCN model is utilized with the HHO algorithm as a hyperparameter optimizer to improve the detection *** experimental results of the HHOGCN-WD technique are investigated under the benchmark *** results indicate the promising performance of the presented HHOGCN-WD model over other recent approaches,with increased accuracy of 99.13%.

关键词： Weed detection precision agriculture graph convolutional network harris hawks optimizer hyperparameter tuning

transport mechanism in chemically reactive hybrid nanofluid flow containing gyrotactic micro-organisms over a curved oscillatory surface

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 177-192页

作者： M.NAVEED M.IMRAN t.ASGHAR Z.ABBAS Department of Mathematics Division of Science and TechnologyUniversity of Education Department of Mathematics The Islamia University of Bahawalpur

this paper examines the transport analysis, including both heat transfer and mass transfer, in hybrid nanofluid flow containing gyrotactic microorganisms towards a curved oscillatory surface. the influence of magnetic fields is also inspected in terms of their physical characteristics. to depict the phenomena of transport, modified versions of both Fick's and Fourier's laws are used. Additionally, the characteristics of both heterogeneous and homogeneous chemical reactions are also incorporated. Utilizing a curvilinear coordinate system, the flow problem is formulated as partial differential equations(PDEs)for momentum, concentration, microorganism field, and energy. An analytical solution to the obtained flow equations is achieved utilizing the homotopy analysis method(HAM).the effects of significant flow parameters on the pressure and microorganism fields, velocity, oscillation velocity, concentration, and temperature distributions are shown via graphs. Furthermore, the variations in skin friction, mass transfer rate, heat transfer rate, and local motile number due to different involved parameters are presented in tables and are analyzed in detail. Graphical results indicate that the curves of velocity and temperature fields are enhanced as the values of the solid volume fraction variables *** is also verified that the concentration rate field decreases as the values of the homogeneous reaction strength parameter and the radius of curvature parameter increase, and it increases with the Schmidt number and the heterogeneous reaction strength *** outcomes show a favorable response of the motile number to advanced values of the Peclet number, the Schmidt number, the microorganism difference parameter, and the bio-convective Lewis number.

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Deep Learning Based License Plate Number Recognition for Smart Cities

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Computers, Materials & Continua 2022年第1期70卷 2049-2064页

作者： t.Vetriselvi E.laxmi Lydia Sachi Nandan Mohanty Eatedal Alabdulkreem Shaha Al-Otaibi Amal Al-Rasheed Romany F.Mansour Department of Computer Science and Engineering K.Ramakrishnan College of TechnologyTrichy620002India Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science&Engineering Vardhaman College of Engineering(Autonomous)Hyderabad501218India Department of Informatics and Computing Singidunum UniversitySerbia Computer Science Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Information Systems Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Smart city-aspiring urban areas should have a number of necessary elements in place to achieve the intended *** controlling and management of traffic conditions,increased safety and surveillance,and enhanced incident avoidance and management should be top priorities in smart city *** the same time,Vehicle License Plate Number Recognition(VLPNR)has become a hot research topic,owing to several real-time applications like automated toll fee processing,traffic law enforcement,private space access control,and road traffic *** VLPNR is a computer vision-based technique which is employed in the recognition of automobiles based on vehicle number *** current research paper presents an effective Deep Learning(DL)-based VLPNR called DLVLPNR model to identify and recognize the alphanumeric characters present in license *** proposed model involves two main stages namely,license plate detection and tesseract-based character *** detection of alphanumeric characters present in license plate takes place with the help of fast RCNN with Inception V2 ***,the characters in the detected number plate are extracted using tesseract Optical Character Recognition(OCR)*** performance of DL-VLPNR model was tested in this paper using two benchmark databases,and the experimental outcome established the superior performance of the model compared to other methods.

关键词： Deep learning smart city tesseract computer vision vehicle license plate recognition

Effect of Nonlinear thermal Radiation on Boundary Layer Flow of Viscous Fluid over Nonlinear Stretching Sheet with Injection/Suction

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Journal of Applied Mathematics and Physics 2016年第2期4卷 307-319页

作者： t. Vijaya laxmi Bandari Shankar Department of Mathematics Osmania University Hyderabad India Department of Mathematics M.V.S. Govt. Arts & Science College Mahabubnagar India

the present study reveals the effect of nonlinear thermal radiation and magnetic field on a boundary layer flow of a viscous fluid over a nonlinear stretching sheet with suction or an injection. Using suitable similarity transformations, governing partial differential equations were reduced to higher order ordinary differential equations and further these are solved numerically using of Keller-Box method. Effect of flow controlling parameter on velocity, temperature and nanoparticle fluid concentration, local skin friction coefficient, local Nusselt number and local Sherwood numbers are discussed. It is found that the dimensionless velocity decreases and temperature, concentration are increased with the increasing of magnetic parameter. the temperature profile is an increasing function of thermal radiation when it is increasing.

关键词： Nonlinear thermal Radiation Stretching Sheet Boundary Layer Keller-Box Method Suction/Injection