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Energy Efficient Cluster-Based Optimal Resource Management in IoT Environment

Computers, Materials & Continua 2022年第1期70卷 1247-1261页

作者： J.V.Anchitaalagammai T.Jayasankar P.Selvaraj Mohamed Yacin Sikkandar M.Zakarya Mohamed Elhoseny k.shankar Department of Computer Science and Engineering Velammal College of Engineering and TechnologyMadurai625009India Department of Electronics and Communication Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India Department of Information Technology SRMInstitute of Science and TechnologyKattankulathur603203Tamil NaduIndia Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAlMajmaah11952Saudi Arabia Department of Mathematics College of ScienceKing Khalid UniversityP.O.Box 9004Abha61413Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityAssiut71524Egypt College of Computer Information Technology American University in the EmiratesDubai503000United Arab Emirates Department of Computer Applications Alagappa UniversityKaraikudiIndia

Internet of Things(IoT)is a technological revolution that redefined communication and computation of modern *** generally refers to a network of gadgets linked via wireless network and communicates via *** management,especially energy management,is a critical issue when designing IoT *** studies reported that clustering and routing are energy efficient solutions for optimal management of resources in IoT *** this point of view,the current study devises a new Energy-Efficient Clustering-based Routing technique for Resource Management i.e.,EECBRM in IoT *** proposed EECBRM model has three stages namely,fuzzy logic-based clustering,Lion Whale Optimization with Tumbling(LWOT)-based routing and cluster maintenance *** proposed EECBRMmodel was validated through a series of experiments and the results were verified under several *** model was compared with existing methods in terms of energy efficiency,delay,number of data transmission,and network *** simulated,in comparison with other methods,EECBRM model yielded excellent results in a significant ***,the efficiency of the proposed model is established.

关键词： IoT environment clustering routing resource management energy efficiency

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Hyperparameter Tuning Bidirectional Gated Recurrent Unit Model for Oral Cancer Classification

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Computers, Materials & Continua 2022年第12期73卷 4541-4557页

作者： k.shankar E.Laxmi Lydia Sachin kumar Ali S.Abosinne Ahmed alkhayyat A.H.Abbas Sarmad Nozad Mahmood Department of Computer Science South Ural State UniversityChelyabinsk454080Russia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Computer Technical Engineering Department College of Technical Engineeringthe Islamic UniversityNajaf54001Iraq College of Technical Engineering the Islamic UniversityNajafIraq College of Information Technology Imam Ja’afar Al-Sadiq UniversityAl-Muthanna66002Iraq Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityIraq

Oral Squamous Cell Carcinoma(OSCC)is a type of Head and Neck Squamous Cell Carcinoma(HNSCC)and it should be diagnosed at early stages to accomplish efficient treatment,increase the survival rate,and reduce death *** imaging is a wide-spread standard used for OSCC ***,it is a cumbersome process and demands expert’s ***,there is a need exists for automated detection ofOSCC using Artificial Intelligence(AI)and Computer Vision(CV)*** this background,the current research article introduces Improved Slime Mould Algorithm with Artificial Intelligence Driven Oral Cancer Classification(ISMA-AIOCC)model on Histopathological images(HIs).The presented ISMA-AIOCC model is aimed at identification and categorization of oral cancer using *** the initial stage,linear smoothing filter is applied to eradicate the noise from ***,MobileNet model is employed to generate a useful set of feature ***,Bidirectional Gated Recurrent Unit(BGRU)model is exploited for classification *** the end,ISMA algorithm is utilized to fine tune the parameters involved in BGRU ***,ISMA algorithm is created by integrating traditional SMA and ChaoticOppositional Based Learning(COBL).The proposed ISMA-AIOCC model was validated for performance using benchmark dataset and the results pointed out the supremacy of ISMA-AIOCC model over other recent approaches.

关键词： Computer aided diagnosis deep learning BGRU biomedical imaging oral cancer histopathological images

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RGB Based Multiple Share Creation in Visual Cryptography with Aid of Elliptic Curve Cryptography

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China Communications 2017年第2期14卷 118-130页

作者： k.shankar P.Eswaran Department of Computer Science and Engineering Alagappa UniversityKaraikudi-630003Tamil NaduIndia Department of Computer Science and Engineering Alagappa UniversityKaraikudi-630003Tamil NaduIndia

In visual cryptography, many shares are generated which are illogical containing certain message within themselves. When all shares are piled jointly, they tend to expose the secret of the image. The notion of visual secret sharing scheme is to encrypt a secret image into n illogical share images. It is unable to reveal any data on the original image if at least one of the shares is not achieved. The original image, in fact, is realized by overlapping the entire shares directly, in order that the human visual system is competent to identify the collective secret image without employing any complicated computational tools. Therefore, they are communicated steadily as number of shares. The elliptic curve cryptography approach, in turn, is employed to augment the privacy and safety of the image. The *** technique is utilized to generate the multiple shares which are subjected to encryption and decryption by means of the elliptic curve cryptography technique. The test outcomes have revealed the fact that the peak signal to noise ratio is 58.0025, Mean square error value is 0.1164 and the correlation coefficient is 1 for the decrypted image without any sort of distortion of the original image.

关键词： visual cryptography pixel shares elliptic curve cryptography encryption PSNR mean square error

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Optimal Confidential Mechanisms in Smart City Healthcare

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Computers, Materials & Continua 2022年第3期70卷 4883-4896页

作者： R.Gopi P.Muthusamy P.Suresh C.G.Gabriel Santhosh kumar Irina V.Pustokhina Denis A.Pustokhin k.shankar Department of Computing Science and Engineering Dhanalakshmi Srinivasan Engineering CollegePerambalur621212India School of Computing Science and Engineering Galgotias UniversityNCRDelhi203201India Department of Computer Science and Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Applications Alagappa UniversityKaraikudi630001India

Smart City Healthcare(SHC2)system is applied in monitoring the patient at home while it is also expected to react to their needs in a timely *** system also concedes the freedom of a *** is a part of this system and it helps in providing care to the *** healthcare devices are trustworthy since it almost certainly recognizes the potential intensifications at very early stage and alerts the patients and medical experts to such an extent that they are provided with immediate *** methodologies exhibit few shortcomings in terms of computational complexity,cost and data ***,the current research article examines SHC2 security through LightWeight Cipher(LWC)with Optimal S-Box model in PRESENT *** procedure aims at changing the sub bytes in which a single function is connected with several bytes’information to upgrade the security level through Swam *** key contribution of this research article is the development of a secure healthcare model for smart city using SHC2 security via LWC and Optimal S-Box *** study used a nonlinear layer and single 4-bit S box for round configuration after verifying SHC2 information,constrained by Mutual Authentication(MA).The security challenges,in healthcare information systems,emphasize the need for a methodology that immovably concretes the *** methodology should act practically,be an effective healthcare framework that depends on solidarity and adapts to the developing *** service providers integrated the IoT applications and medical services to offer individuals,a seamless technology-supported healthcare *** proposed SHC^(2) was implemented to demonstrate its security levels in terms of time and access *** model was tested under different parameters such as encryption time,decryption time,access time and response time inminimum ***,the level of the model and throughput were analyzed by maximum value i.e.,50Mbp

关键词： Smart city healthcare security block cipher LWC

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Improved hybrid Strength Pareto Evolutionary Algorithms for multi-objective optimization

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International Journal of Intelligent Computing and Cybernetics 2018年第1期11卷 20-46页

作者： k.shankar Akshay S.Baviskar Department of mechanical engineering indian institute of technology madraschennaiindia

Purpose–The purpose of this paper is to design an improved multi-objective algorithm with better spread and convergence than some current *** proposed application is for engineering design ***/methodology/approach–This study proposes two novel approaches which focus on faster convergence to the Pareto front(PF)while adopting the advantages of Strength Pareto Evolutionary Algorithm-2(SPEA2)for better *** first method,decision variables corresponding to the optima of individual objective functions(Utopia Point)are strategically used to guide the search toward *** second method,boundary points of the PF are calculated and their decision variables are seeded to the initial ***–The proposed methods are tested with a wide range of constrained and unconstrained multi-objective test functions using standard performance *** evaluation demonstrates the superiority of proposed algorithms over well-known existing algorithms(such as NSGA-II and SPEA2)and recent ones such as NSLS and E-NSGA-II in most of the benchmark *** is also tested on an engineering design problem and compared with a currently used *** implications–The algorithms are intended to be used for practical engineering design problems which have many variables and conflicting objectives.A complex example of Welded Beam has been shown at the end of the *** implications–The algorithm would be useful for many design problems and social/industrial problems with conflicting ***/value–This paper presents two novel hybrid algorithms involving SPEA2 based on:local search;and Utopia point directed search *** concept has not been investigated before.

关键词： Evolutionary algorithms Boundary points Multi-objective optimization problems Strength Pareto Evolutionary Algorithm 2(SPEA2)

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An IoT-Cloud Based Intelligent Computer-Aided Diagnosis of Diabetic Retinopathy Stage Classification Using Deep Learning Approach

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Computers, Materials & Continua 2021年第2期66卷 1665-1680页

作者： k.shankar Eswaran Perumal Mohamed Elhoseny Phong Thanh Nguyen Department of Computer Applications Alagappa UniversityKaraikudi630001India Faculty of Computers and Information Mansoura UniversityMansoura35516Egypt Department of Project Management Ho Chi Minh City Open UniversityHo Chi Minh City7000000Vietnam

Diabetic retinopathy(DR)is a disease with an increasing prevalence and the major reason for blindness among working-age *** possibility of severe vision loss can be extensively reduced by timely diagnosis and *** automated screening for DR has been identified as an effective method for early DR detection,which can decrease the workload associated to manual grading as well as save diagnosis costs and *** studies have been carried out to develop automated detection and classification models for *** paper presents a new IoT and cloud-based deep learning for healthcare diagnosis of Diabetic Retinopathy(DR).The proposed model incorporates different processes namely data collection,preprocessing,segmentation,feature extraction and *** first,the IoT-based data collection process takes place where the patient wears a head mounted camera to capture the retinal fundus image and send to cloud ***,the contrast level of the input DR image gets increased in the preprocessing stage using Contrast Limited Adaptive Histogram Equalization(CLAHE)***,the preprocessed image is segmented using Adaptive Spatial kernel distance measure-based Fuzzy C-Means clustering(ASkFCM)***,deep Convolution Neural Network(CNN)based Inception v4 model is applied as a feature extractor and the resulting feature vectors undergo classification in line with the Gaussian Naive Bayes(GNB)*** proposed model was tested using a benchmark DR MESSIDOR image dataset and the obtained results showcased superior performance of the proposed model over other such models compared in the study.

关键词： Deep learning classification GaussianNaive Bayes feature extraction diabetic retinopathy

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Damage modeling of ballistic penetration and impact behavior of concrete panel under low and high velocities

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Defence Technology（防务技术） 2021年第1期17卷 202-211页

作者： Chahmi Oucif J.S.kalyana Rama k.shankar Ram Farid Abed Institute of Structural Mechanics(ISM) Bauhaus-Universitat WeimarMarienstraße 15D-99423WeimarGermany Department of Civil Engineering BITS Pilani-Hyderabad CampusHyderabad500072India Department of Civil Engineering Vignana Bharathi Institute of TechnologyHyderabad501301India Department of Civil Engineering University of CaliforniaBerkeleyBerkeleyCAUnited States Department of Civil Engineering American University of SharjahP.O.Box 26666United Arab Emirates

This work presents a numerical simulation of ballistic penetration and high velocity impact behavior of plain and reinforced concrete *** paper is divided into two *** first part consists of numerical modeling of reinforced concrete panel penetrated with a spherical projectile using concrete damage plasticity(CDP)model,while the second part focuses on the comparison of CDP model and Johnson-Holmquist-2(JH-2)damage model and their ability to describe the behavior of concrete panel under impact *** first and second concrete panels have dimensions of 1500 mm1500 mm150 mm and 675 mm675 mm200 mm,respectively,and are meshed using 8-node hexahedron solid *** impact object used in the first part is a spherical projectile of 150 mm diameter,while in the second part steel projectile of a length of 152 mm is modeled as rigid *** and scabbing characteristics are studied in the first *** the second part,the comparison results are presented as damage contours,kinetic energy of projectile and internal energy of the *** results revealed a severe fracture of the panel and high kinetic energy of the projectile using CDP model comparing to the JH-2 *** addition,the internal energy of concrete using CDP model was found to be less comparing to the JH-2 model.

关键词： Johnson-Holmquist-2 Concrete damage plasticity Concrete panel Damage Impact loads

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Secure Localization Based Authentication (SLA) Strategy for Data Integrity in WNS

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Computers, Materials & Continua 2021年第6期67卷 4005-4018页

作者： V.Manikandan M.Sivaram Amin Salih Mohammed V.Porkodi k.shankar Assistant Professor Research Research CenterLebanese French UniversityErbil44001Iraq Vice President Lebanese French UniversityErbil44001Iraq Department of Information Technology College of Engineering and Computer ScienceLebanese French UniversityErbil44001Iraq Department of Computer Applications Alagappa UniversityKaraikudi630003India

Wireless Sensor Networks(WSN)has been extensively utilized as a communication model in Internet of Things(IoT).As well,to offer service,numerous IoT based applications need effective transmission over unstable *** ensure reliability,prevailing investigations exploit multiple candidate forwarders over geographic opportunistic routing in ***,these models are affected by crucial denial of service(DoS)attacks,where huge amount of invalid data are delivered intentionally to the receivers to disturb the functionality of ***,secure localization based authentication(SLA)is presented to fight against DoS attack,and to fulfil the need of reliability and *** examining state information,SLA projects a trust model to enhance efficacy of data ***,of the prevailing opportunistic protocols,SLA guarantees data integrity by modelling a trust based authentication,providing protection against DoS attackers and diminishing computational ***,this model acts as a verification strategy to accelerate?attackers and to handle *** strategy helps SLA in eliminating duplicate transmission and by continuous verification that results from conventional opportunistic *** is performed in a MATLAB environment that offers authentic and reliable delivery by consuming approximately 50%of the cost in contrast to other *** anticipated model shows better trade off in comparison to the prevailing ones.

关键词： Wireless sensor networks opportunistic routing secure localization based authentication denial of service computational cost

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Hybrid Swarm Intelligence Based QoS Aware Clustering with Routing Protocol for WSN

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Computers, Materials & Continua 2021年第9期68卷 2995-3013页

作者： M.S.Maharajan T.Abirami Irina V.Pustokhina Denis A.Pustokhin k.shankar Department of Computer Science and Engineering GRT Institute of Engineering and TechnologyTiruttani631209India Department of Information Technology Kongu Engineering CollegeErode638060India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Applications Alagappa UniversityKaraikudi630001India

Wireless Sensor Networks(WSN)started gaining attention due to its wide application in the fields of data collection and information *** recent advancements in multimedia sensors demand the Quality of Service(QoS)be maintained up to certain *** restrictions and requirements in QoS management completely depend upon the nature of target *** of the major QoS parameters in WSN are energy efficiency,network lifetime,delay and *** this scenario,clustering and routing are considered as the most effective techniques to meet the demands of *** they are treated as NP(Non-deterministic Polynomial-time)hard problem,Swarm Intelligence(SI)techniques can be *** current research work introduces a new QoS aware Clustering and Routing-based technique using Swarm Intelligence(QoSCRSI)*** proposed QoSCRSI technique performs two-level clustering and proficient ***,the fuzzy is hybridized with Glowworm Swarm Optimization(GSO)-based clustering(HFGSOC)technique for optimal selection of Cluster Heads(CHs).Here,Quantum Salp Swarm optimization Algorithm(QSSA)-based routing technique(QSSAR)is utilized to select the possible routes in the *** order to evaluate the performance of the proposed QoSCRSI technique,the authors conducted extensive simulation analysis with varying node *** experimental outcomes,obtained from the proposed QoSCRSI technique,apparently proved that the technique is better compared to other state-of-the-art techniques in terms of energy efficiency,network lifetime,overhead,throughput,and delay.

关键词： Quality of service clustering routing energy efficiency wireless sensor networks swarm intelligence

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Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model

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Computers, Materials & Continua 2021年第5期67卷 1881-1897页

作者： Thavavel Vaiyapuri Sachi Nandan Mohanty M.Sivaram Irina V.Pustokhina Denis A.Pustokhin k.shankar College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science&Engineering IcfaiTechICFAI Foundation for Higher EducationHyderabadIndia Assistant professor Research Research CenterLebanese French UniversityErbil44001Iraq Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Applications Alagappa UniversityKaraikudiIndia

The latest advancements in highway research domain and increase in the number of vehicles everyday led to wider exposure and attention towards the development of efficient Intelligent Transportation System(ITS).One of the popular research areas i.e.,Vehicle License Plate Recognition(VLPR)aims at determining the characters that exist in the license plate of the *** VLPR process is a difficult one due to the differences in viewpoint,shapes,colors,patterns,and non-uniform illumination at the time of capturing *** current study develops a robust Deep Learning(DL)-based VLPR model using Squirrel Search Algorithm(SSA)-based Convolutional Neural Network(CNN),called the SSA-CNN *** presented technique has a total of four major processes namely preprocessing,License Plate(LP)localization and detection,character segmentation,and *** Transform(HT)is applied as a feature extractor and SSA-CNN algorithm is applied for character recognition in *** SSA-CNN method effectively recognizes the characters that exist in the segmented image by optimal tuning of CNN *** HT-SSA-CNN model was experimentally validated using the Stanford Car,FZU Car,and HumAIn 2019 Challenge *** experimentation outcome verified that the presented method was better under several *** projected HT-SSA-CNN model implied the best performance with optimal overall accuracy of 0.983%.

关键词： Deep learning license plate recognition intelligent transportation segmentation

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