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Improved Integrated Deep Model for Pap-Smear Cell Analysis

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Journal of Systems Science and Information 2024年第1期12卷 113-124页

作者： somasundaram DEVARAJ Nirmala MADIAN Gnanasaravanan SUBRAMANIAM Rithaniya CHELLAMUTHU Muralitharan KRISHANAN School of Electronics Engineering Vellore Institute of TechnologyVellore 632014India Department of Biomedical Engineering Dr.N.G.P Institute of TechnologyCoimbatore 641045India Karunya Institute of Technology and Sciences Coimbatore 641114India Department of Computer Science Institute of Mathematical ScienceSungkyunkwan UniversitySuwon 16419South Korea

Cervical cancer is the fourth most common malignancy to strike a woman *** discovered early enough,it can be effectively *** there is a chance of error owing to human error,the Pap smear is a good tool for first screening for cervical *** also takes a lot of time and effort to *** aim of this study was to reduce the possibility of error by automating the process of classifying cervical cancer using Pap smear *** the purpose of this study,dual convolution neural networks with LstM were employed to classify images due to deep learning approaches inspire distinct features and powerful classifiers for many computer vision *** proposed deep learning model based on convolution neural networks(CNN)with the long short-term memory(LstM)network is to learn features which give better recognition *** overall model is known as *** which‘smear’indicates‘pap-smear cancer cells’and‘net’refers to neural *** parameters such as,Accuracy,Precision,Recall,Accuracy,Sensitivity,and Specificity are used to validate the *** proposed method provides the improved accuracy of 99.57 percentage for classification of the pap-smear *** proposed approaches demonstrate the effectiveness of our contributions by testing and comparing with the state-of-the-art techniques.

关键词： pap-smear deep learning convolution neural network smear-net

Mesenchymal stem cell-based TRAIL delivery inhibits the metastatic state of clinical therapy-resistant progressive neuroblastoma

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World Journal of Pediatrics 2024年第3期20卷 287-293页

作者： Dinesh Babu somasundaram Andrew Maher Sheeja Aravindan Zhongxin Yu Brian MBesch Natarajan Aravindan Department of Radiation Oncology University of Oklahoma Health Sciences CenterOklahoma CityOKUSA stephenson Cancer Center Oklahoma CityOKUSA Department of Pathology University of Oklahoma Health Sciences CenterOklahoma CityOKUSA Radiation Biology Laboratory University of Oklahoma Health Sciences CenterBSEB 302F941 Stanton L.Young BoulevardOklahoma CityOK 73104USA

Progressive neuroblastomas(pNBs)that defy current intensive multimodal clinical therapy(IMCT)are a significant contributor to overall childhood cancer deaths[l].Neuroblastomas(NBs)that survive first-line IMCT actively evolve to acquire genetic and molecular rearrangements and display unparalleled plasticity and evolution,which causes frequent relapses in a rapidly accelerating timeline[2-4].

关键词： neuroblastoma clinical evolve

An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems

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Big Data Mining and Analytics 2024年第2期7卷 399-418页

作者： Sankaramoorthy Muthubalaji Naresh Kumar Muniyaraj Sarvade Pedda Venkata Subba Rao Kavitha Thandapani Pasupuleti Rama Mohan Thangam somasundaram Yousef Farhaoui Department of Electrical and Electronics Engineering CMR College of Engineering&TechnologyHyderabad 501401India Department of Electronics and Communication Engineering Vardhaman College of Engineering KacharamShamshabad 501218India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and TechnologyHyderabad 501301India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India Department of Electrical and Electronics Engineering Bharat Institute of Engineering and TechnologyHyderabad 501510India Department of Computer Science and Engineering Amrita School of ComputingAmrita Vishwa VidhyapeethamBengaluru 560035India T-IDMS Department of Computer ScienceFaculty of Sciences and TechniquesMoulay Ismail UniversityErrachidia 52000Morocco

Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of heterogeneous big data as a consequence of the growth of power grid technologies,along with data processing and advanced *** main obstacles in turning the heterogeneous large dataset into useful results are computational burden and information *** original contribution of this paper is to develop a new big data framework for detecting various intrusions from the smart grid systems with the use of AI ***,an AdaBelief Exponential Feature Selection(AEFS)technique is used to efficiently handle the input huge datasets from the smart grid for boosting ***,a Kernel based Extreme Neural Network(KENN)technique is used to anticipate security vulnerabilities more *** Polar Bear Optimization(PBO)algorithm is used to efficiently determine the parameters for the estimate of radial basis ***,several types of smart grid network datasets are employed during analysis in order to examine the outcomes and efficiency of the proposed AdaBelief Exponential Feature Selection-Kernel based Extreme Neural Network(AEFS-KENN)big data security *** results reveal that the accuracy of proposed AEFS-KENN is increased up to 99.5%with precision and AUC of 99%for all smart grid big datasets used in this study.

关键词： smart grid Machine Learning(ML) big data analytics AdaBelief Exponential Feature Selection(AEFS) Polar Bear Optimization(PBO) Kernel Extreme Neural Network(KENN)

Exploring the impact of high density planting system and deficit irrigation in cotton(Gossypium hirsutum L.):a comprehensive review

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Journal of Cotton Research 2024年第3期7卷 302-317页

作者： MANIBHARATHI Sekar somasundaram Selvaraj PARASURAMAN Panneerselvam SUBRAMANIAN Alagesan RAVICHANDRAN Veerasamy MANIKANDA BOOPATHI Narayanan Department of Agronomy Tamil Nadu Agricultural UniversityCoimbatoreTamil Nadu 641003India Cotton Research station Tamil Nadu Agricultural UniversityPerambalurTamil Nadu621116India Department of Cotton Tamil Nadu Agricultural UniversityCoimbatoreTamil Nadu 641003India Department of Crop Physiology Tamil Nadu Agricultural UniversityCoimbatoreTamil Nadu 641003India Department of Plant Biotechnology Centre for Plant Molecular Biology and BiotechnologyTamil Nadu Agricultural UniversityCoimbatoreTamil Nadu 641003India

Lessons learned from past experiences push for an alternate way of crop *** India,adopting high density planting system(HDPS)to boost cotton yield is becoming a growing *** has recently been considered a replacement for the current Indian production *** is also suitable for mechanical harvesting,which reducing labour costs,increasing input use efficiency,timely harvesting timely,maintaining cotton quality,and offering the potential to increase productivity and *** technology has become widespread in globally cotton growing *** management is critical for the success of high density cotton *** to the problem of freshwater availability,more crops should be produced per drop of *** the high-density planting system,optimum water application is essential to control excessive vegetative growth and improve the translocation of photoassimilates to reproductive *** irrigation is a tool to save water without compromising *** the same time,it consumes less water than the normal evapotranspiration of *** review comprehensively documents the importance of growing cotton under a high-density planting system with deficit *** on the current research and combined with cotton production reality,this review discusses the application and future development of deficit irrigation,which may provide theoretical guidance for the sustainable advancement of cotton planting systems.

关键词： Deficit irrigation High density planting system Ultra narrow row Cost saving Mechanical harvesting Yield optimization

Adaptive Marine Predator Optimization Algorithm(AOMA)-Deep Supervised Learning Classification(DSLC)based IDS framework for MANET security

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Intelligent and Converged Networks 2024年第1期5卷 1-18页

作者： M.Sahaya Sheela A.Gnana Soundari Aditya Mudigonda C.Kalpana K.Suresh K.somasundaram Yousef Farhaoui Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600069India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai 602105India JNIAS School of Planning and Architecture Hyderabad 500034India Department of Computer Science and Engineering NPR College of Engineering and TechnologyNatham Dindigul 624401India Department of Computer Science and Engineering PSNA College of Engineering and TechnologyPoolangulathupatti 620009India Department of Computer Science and Engineering Sri Muthukumaran Institute of TechnologyChennai 600069India Department of Computer Science Moulay Ismail UniversityMeknes 5003Morocco

Due to the dynamic nature and node mobility,assuring the security of Mobile Ad-hoc Networks(MANET)is one of the difficult and challenging tasks *** MANET,the Intrusion Detection System(IDS)is crucial because it aids in the identification and detection of malicious attacks that impair the network’s regular *** machine learning and deep learning methodologies are used for this purpose in the conventional works to ensure increased security of ***,it still has significant flaws,including increased algorithmic complexity,lower system performance,and a higher rate of ***,the goal of this paper is to create an intelligent IDS framework for significantly enhancing MANET security through the use of deep learning ***,the min-max normalization model is applied to preprocess the given cyber-attack datasets for normalizing the attributes or fields,which increases the overall intrusion detection performance of ***,a novel Adaptive Marine Predator Optimization Algorithm(AOMA)is implemented to choose the optimal features for improving the speed and intrusion detection performance of ***,the Deep Supervise Learning Classification(DSLC)mechanism is utilized to predict and categorize the type of intrusion based on proper learning and training *** evaluation,the performance and results of the proposed AOMA-DSLC based IDS methodology is validated and compared using various performance measures and benchmarking datasets.

关键词： Intrusion Detection System(IDS) Security Mobile Ad-hoc Network(MANET) min-max normalization Adaptive Marine Predator Optimization Algorithm(AOMA) Deep Supervise Learning Classification(DSLC)

Effect of process parameters on microstructural and mechanical properties of *** 304L explosive cladding

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Journal of Central South University 2017年第6期24卷 1245-1251页

作者： Saravanan somasundaram Raghukandan Krishnamurthy Hokamoto Kazuyuki Department of Mechanical Engineering Annamalai UniversityAnnamalai NagarTamilnadu 608002India Department of Manufacturing Engineering Annamalai UniversityAnnamalai NagarTamilnadu 608002India Institute of Pulsed Power Science Kumamoto UniversityKurokamiKumamotoJapan

The present work pertains to the study of microstructure and mechanical properties of explosively cladded commercially pure titanium(cpTi) with austenitic stainless steel(SS 304L) subjected to varied process parameters, viz., loading ratios(mass of explosive or mass of flyer plate) and preset angles. The microstructural study reveals the transformation from straight to wavy interface while increasing loading ratios. Vickers hardness increases with loading ratios, and the maximum hardness is witnessed in the closer proximity of collision interface. Ram tensile and shear strength of explosive claddings are higher than that of parent plates. While the base plate fails in impact test, the flyer plate is deformed, indicating good impact strength. Increased mass of claddings, due to oxide formation, is witnessed in corrosion tests, which confirms the superiority of explosive claddings in corrosive environment. Triaxial weldability window, an analytical estimation for Ti-SS 304L explosive claddings, is developed and correlated.

关键词： explosive cladding titanium stainless steel microstructure strength corrosion

Kautz Function Based Continuous-Time Model Predictive Controller for Load Frequency Control in a Multi-Area Power System

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Computer Modeling in Engineering & Sciences 2018年第11期117卷 169-187页

作者： A.Parassuram P.somasundaram Department of Electrical and Electronics Engineering College of EngineeringAnna UniversityGuindyChennaiTamilnaduIndia.

A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model Predictive Controller(MPC)*** predicts the future trajectory of the dynamic model by calculating the optimal closed loop feedback gain *** this paper,the optimal closed loop feedback gain matrix was calculated using Kautz *** an Orthonormal Basis Function(OBF),Kautz function has an advantage of solving complex pole-based nonlinear *** Algorithm(GA)was applied to optimally tune the Kautz function-based MPC.A constraint based on phase plane analysis was implemented with the cost function in order to improve the robustness of the Kautz function-based *** proposed method was simulated with three area interconnected power system and the efficiency of the proposed method was measured and exhibited by comparing with conventional Proportional and Integral(PI)controller and Linear Quadratic Regulation(LQR).

关键词： Load frequency control model predictive controller orthonormal basis function kautz function phase plane analysis linear quadratic regulator proportional and integral controller genetic algorithm.

Modeling and Analysis of Novel Multilevel Inverter Topology with Minimum Number of Switching Components

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Computer Modeling in Engineering & Sciences 2017年第4期113卷 461-473页

作者： V.Thiyagarajan P.somasundaram Department of EEE SSN College of EngineeringKalavakkamTamilnadu603110India Department of EEE CEGAnna UniversityChennaiTamilnadu600025India

This paper proposes a novel single phase symmetrical and asymmetrical type extendable multilevel inverter topology with minimum number of *** basic circuit of the proposed inverter topology consist of four dc voltage sources and 10 main switches which synthesize 9-level output voltage during symmetrical operation and 17-level output voltage during asymmetrical *** comparison between the proposed topology with conventional and other existing inverter topologies is presented in this *** advantages of the proposed inverter topology include minimum switches,less harmonic distortion and minimum switching *** performance of the proposed multilevel inverter topology has been analyzed in both symmetrical and asymmetrical *** simulation model is developed using MATLAB/SIMULINK software to verify the performance of the proposed inverter.

关键词： Multilevel inverter symmetric asymmetric THD on state switches

Effect of Bio-filler on Hybrid Sisal-Banana-Kenaf-Flax Based Epoxy Composites:A statistical Correlation on Flexural strength

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Journal of Bionic Engineering 2020年第6期17卷 1263-1271页

作者： somasundaram Vivek Karuppusamy Kanthave Arun Torris Vijayananth Kavimani Department of Mechanical Engineering Anna University Regional CampusCoimbatore 641046Tamil NaduIndia Polymer Science and Engineering Division CSIR-National Chemical LaboratoryDr.Homi Bhabha RoadPune411008MaharashtraIndia Department of Mechanical Engineering Karpagam Academy of Higher EducationCoimbatore 641021Tamil NaduIndia

This work deals with the investigation of the synergistic effect of bagasse ash with sisal-banana-kenaf-flax fibers reinforced epoxy composite for their flexural *** composites with three combinations of hybrid fibers ***/kenaf(HSK),banana/kenaf(HBK),and banana/flax(HBF)with bagasse ash(BGA)as filler material are fabricated using vacuum bag assisted resin transfer *** were conducted based on L27 orthogonal array to understand the influence of control factor *** volume,alkali concentration&BGA over output response.A'-ray micro computed tomography analysis was conducted over the developed sample to infer the uniform dispersion of fiber and filler *** experimental results reveal that the addition of fiber up to 30 vol%depicts better strength and further addition results in a negative *** in order of BGA decreases the flexural strength of the developed composites.

关键词： bagasse ash natural fiber flexural strength X-ray micro computed tomography vacuum bag assisted resin transfer molding