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Extended Deep Learning Algorithm for Improved Brain Tumor Diagnosis System

Intelligent Automation & Soft Computing 2024年第1期39卷 33-55页

作者： M.Adimoolam K.Maithili N.M.Balamurugan R.Rajkumar S.Leelavathy raju kannadasan Mohd Anul Haq Ilyas Khan ElSayed M.Tag El Din Arfat Ahmad Khan Department of Computer Engineering Government Polytechnic CollegeSevvapetTiruvallurTamil Nadu602025India Department of Computer Science and Engineering KG Reddy College of Engineering and TechnologyHyderabadTelangana500075India Department of Computer Science and Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Computer Science and Engineering Annamalai UniversityChidambaramTamil Nadu608002India Department of Computer Science and Engineering Aarupadai Veedu Institute of TechnologyVinayaka Mission Research FoundationPaiyanurTamil Nadu603104India Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLA algorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of dataset records is enormous,then themethod’s computation power has to be updated.

关键词： Brain tumor extended deep learning algorithm convolution neural network tumor detection deep learning

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Modelling and validation of metal oxide surge arrester for very fast transients

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High Voltage 2018年第2期3卷 147-153页

作者： kannadasan raju Valsalal Prasad Department of Electrical and Electronics Engineering College of Engineering Guindy CampusAnna UniversityChennai 600025India

Metal oxide surge arrester models that are currently on rounds suffer from certain deficiencies and as a consequence,they are not in position to portray accurately the arrester residual *** drawback is mainly attributed to their inherent *** prevailing pressing need demands accurate performance assessment of zinc oxide arrester under all types of overvoltages including very fast transient overvoltages(VFTOs).So immediate corrective measures like the formation of a new arrester model or rejig of the existing one are urgently *** issue constitutes the centre piece/core of this *** consideration of its various merits,which includes its capacity to bring out the virtual representation of arrester activities,electromagnetic transient programme software has been chosen for this *** its aid,the arrester model recommended by IEEE Working Group has been aptly reshaped to suit the needs of VFTOs *** end results of the simulations thus carried out have clearly established its suitability for the studies involving nanosecond waves;additionally,it got its validation and endorsement from the test data obtained from different arrester *** commendable endorsements got from these studies shed clear light on *** these aspects are dealt with this work.

关键词： oxide transient prevailing

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Effect of capacitance on ZnO-Bi_2O_3-Yb_2O_3 based varistor for nanosecond transients

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Journal of Central South University 2018年第10期25卷 2332-2338页

作者： kannadasan raju Valsalal PRASAD Department of Electrical & Electronics Engineering CEG Campus Anna University

The microstructure and electrical properties of ZnO-Bi2O3-Yb2O3 based varistor ceramics were investigated with various temperature effects from 900°C to 1050°*** the results,it was observed that the increase of sintering temperature offers a reduced capacitive effect from 0.460 nF to 0.321 ***,the grain sizes of varistors were varied from 6.8μm to 9.8μ*** consequence of such smaller grain sizes provided a better voltage gradient of about 895 V/mm for the disc sintered at 900°C and fallen drastically to 410 V/mm for the sample sintered at 1050°*** addition,there was an increase of non-linearity index to a maximum value of 36.0 and reduced leakage current of 0.026 mA/***,the density of the varistor decreased with an increase of temperature from 5.41 g/cm3 to 5.24 g/*** this base,the influence of varistor capacitance and high voltage gradient were scrutinized and it led an improved transition speed of the varistor assembly from non-conduction to conduction mode during intruding nanosecond transients.

关键词： capacitance metal oxide varistor nanosecond transient rare earth oxide transition delay ytterbium oxide

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Adaptive Cell Zooming Strategy Toward Next-Generation Cellular Networks with Joint Transmission

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Computers, Materials & Continua 2021年第10期69卷 81-98页

作者： Abu Jahid Mohammed H.Alsharif raju kannadasan Mahmoud A.Albreem Peerapong Uthansakul Jamel Nebhen Ayman A.Aly Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia

The Internet subscribers are expected to increase up to 69.7%(6 billion)from 45.3%and 25 billion Internet-of-things connections by ***,the ubiquitous availability of data-hungry smart multimedia devices urges research attention to reduce the energy consumption in the fifthgeneration cloud radio access network to meet the future traffic demand of high data *** propose a new cell zooming paradigm based on joint transmission(JT)coordinated multipoint to optimize user connection by controlling the cell coverage in the downlink communications with a hybrid power *** endeavoring cell zooming technique adjusts the coverage area in a given cluster based on five different JT schemes,which will help in reducing the overall power consumption with minimum inter-cell *** provide heuristic solutions to assess wireless network performances in terms of aggregate throughput,energy efficiency index(EEI),and energy consumption gain under a different scale of network *** suggested algorithm allows efficient allocation of resource block and increases energy and spectral efficiency over the conventional location-centric cell zooming *** system-level simulations show that the proposed framework reduces energy consumption yielding up to 17.5%and increases EEI by 14%.Subsequently,a thorough comparison among different JT-based load shifting schemes is pledged for further validation of varying system bandwidths.

关键词： Wireless networks green communications C-RAN coordinated multipoint energy efficiency

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Optimal Cost-Aware Paradigm for Off-Grid Green Cellular Networks in Oman

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Computers, Materials & Continua 2021年第8期68卷 2665-2680页

作者： Mohammed H.Alsharif kannadasan raju Abu Jahid Mahmoud A.Albreem Peerapong Uthansakul Jamel Nebhen Venkatesan Chandrasekaran Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand Prince Sattam bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia

Green wireless networks or energy-efficient wireless networks have gained popularity as a research topic due to the ecological and economic concerns of cellular *** specific power supply requirements for the cellular base station,such as cost-effectiveness,efficiency,sustainability,and reliability,can be met by utilizing the technological advances in renewable *** are numerous drivers for the deployment of renewable energy technologies and the transition towards green *** energy is free,clean,and abundant in most locations throughout the ***,this work proposes a novel framework for energy-efficient solar-powered base stations for the Oman site,specifically for off-grid locations where fuel transportation for diesel generator(DG)is a serious *** demonstrate the effectiveness of the proposed system for off-grid sites,the Hybrid Optimization Model for Electric Renewables optimization software is adapted by considering real-time conditions and its technical *** cost factors such as capital cost,salvage cost,replacement cost,operational,and maintenance cost of PV panels,inverters,and batteries also undergo extensive *** the observed results,the total net present cost(NPC)of the proposed system is$27,887,while the net NPC of the DG is estimated at$32,***,the proposed scheme can potentially achieve considerable savings in the operational expenditure at approximately 15.24%.Indeed,these outcomes can provide profound economic,technical,and ecological benefits to the cellular operators of *** also ensures a sizeable reduction in greenhouse gas that supports sustainable green wireless network deployment in remote areas.

关键词： Wireless networks green wireless networks green communications sustainability OPEX

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Design of a Low-Cost Air Quality Monitoring System Using Arduino and ThingSpeak

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Computers, Materials & Continua 2022年第1期70卷 151-169页

作者： Anabi Hilary Kelechi Mohammed H.Alsharif Chidumebi Agbaetuo Osichinaka UbadikeAlex Aligbe Peerapong Uthansakul raju kannadasan Ayman A.Aly Department of Aerospace Engineering College of EngineeringAirForce Institute of TechnologyKadunaNigeria Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversitySeoul05006Korea Department of Electrical Engineering and Information Engineering College of EngineeringCovenant UniversityCanaanlandOtaP.M.B 1023OgunNigeria School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringChennai602117India Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia

The impact of daily emissions of gaseous and particulate pollutants of machines and industries on human health and the environment has attracted increasing *** impact has significantly led to a notable increase in mortality in the highly industrialized ***,monitoring air quality and creating public awareness are important for a safer future,which led the governments globally to investmulti-billion in policymaking and solution stratification to address the *** study aims to design a realtime Internet of Things low-cost air quality monitoring *** system utilizes air quality and carbon monoxide sensors for monitoring gaseous ***,the system utilizes an Arduino Nano development board equipped with a WiFi module to effectively send readings to a ThingSpeak online channel platformfor instantaneous and real-time display of air *** ThingSpeak uses HTTP protocols to send emails in raising awareness of poor air *** level of concentration is monitored graphically through channels with the help of ThingSpeak to aid remote *** value is ***,when pollutants have become unhealthy and harmful,the system trips off an alarm,and e-mail notifications are sent to the *** results have shown that the work was successfully implemented a design of a low-cost air quality monitoring system using Arduino and ThingSpeak,showing that an air quality system can be implemented using a low-cost technology,Arduino and ThingSpeak.

关键词： IoT air quality MQ 135 sensor MQ-7 sensor air pollution

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Powering Mobile Networks with Optimal Green Energy for Sustainable Development

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Computers, Materials & Continua 2021年第10期69卷 661-677页

作者： Mohammed H.Alsharif Mahmoud A.Albreem Abu Jahid kannadasan raju Peerapong Uthansakul Jamel Nebhen Venkatesan Chandrasekaran Ayman A.Aly Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversityGwangjin-guSeoul05006Korea Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia

Green wireless networking is an emerging area for many societies,especially academia and industry,in light of economic and ecological *** wireless infrastructures exploiting green power sources can enhance sustainability due to the adverse effects of conventional power sources and atmospheric ***,the specific power supply requirements for a base station(BS),such as cost effectiveness,efficiency,sustainability,and reliability,can be met by utilizing technological advances in renewable *** drivers and motivators are involved in the deployment of renewable energy technologies and the transition toward green *** energy is free,clean,and abundant in most locations throughout the *** this work,a sustainable optimal stand-alone solarpowered model envisioning green cellular BSs for urban locations in Oman is *** model can extend 24 h uninterrupted power supply support to a cellular BS that fully utilizes an integrated storage *** system analysis is conducted using a hybrid optimization model for electric renewables(HOMER)based on actual prevailing conditions of the regions and their technical *** results showed can be achieved operational expenditure savings up to 16%.These outcomes provide a huge benefit to the cellular operators of Oman economically,technically,and ecologically.

关键词： Wireless networks green wireless networks green communications sustainability OPEX

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Crop Yield Prediction Using Machine Learning Approaches on a Wide Spectrum

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Computers, Materials & Continua 2022年第9期72卷 5663-5679页

作者： SVinson Joshua ASelwin Mich Priyadharson raju kannadasan Arfat Ahmad Khan Worawat Lawanont Faizan Ahmed Khan Ateeq Ur Rehman Muhammad Junaid Ali Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Suranaree University of Technology Nakhon Ratchasima30000Thailand University of Central Punjab Lahore54000Pakistan Government College University Lahore54000Pakistan Virtual University of Pakistan Islamabad Campus45550Pakistan

The exponential growth of population in developing countries likeIndia should focus on innovative technologies in the Agricultural processto meet the future crisis. One of the vital tasks is the crop yield predictionat its early stage;because it forms one of the most challenging tasks inprecision agriculture as it demands a deep understanding of the growth patternwith the highly nonlinear parameters. Environmental parameters like rainfall,temperature, humidity, and management practices like fertilizers, pesticides,irrigation are very dynamic in approach and vary from field to field. In theproposed work, the data were collected from paddy fields of 28 districts in widespectrum of Tamilnadu over a period of 18 years. The Statistical model MultiLinear Regression was used as a benchmark for crop yield prediction, whichyielded an accuracy of 82% owing to its wide ranging input data. Therefore,machine learning models are developed to obtain improved accuracy, namelyBack Propagation Neural Network (BPNN), Support Vector Machine, andGeneral Regression Neural Networks with the given data set. Results showthat GRNN has greater accuracy of 97% (R2 = 0.97) with a normalizedmean square error (NMSE) of 0.03. Hence GRNN can be used for crop yieldprediction in diversified geographical fields.

关键词： Machine learning crop yield prediction computer simulation and modelling

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Optimization Analysis of Sustainable Solar Power System for Mobile Communication Systems

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Computers, Materials & Continua 2022年第5期71卷 3243-3255页

作者： Mohammed H.Alsharif raju kannadasan Amir Y.Hassan Wael Z.Tawfik Mun-Kyeom Kim Muhammad Asghar Khan Ahmad A.A.Solyman Department of Electrical Engineering College of Electronics and Information EngineeringSejong University209 Neungdong-roGwangjin-guSeoul05006Korea Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriprumbudurChennai602117India Department of Power Electronics and Energy Conversion Electronics Research InstituteGiza12622Egypt Department of Physics Faculty of ScienceBeni-Suef UniversityBeni-Suef62511Egypt Department of Energy System Engineering Chung-Ang University84 Heukseok-roDongjak-guSeoul156-756Korea Department of Electrical Engineering Hamdard University Islamabad44000Pakistan Department of Electrical and Electronics Engineering Istanbul Gelisim UniversityAvcılar34310Turkey

Cellular mobile technology has witnessed tremendous growth in recent *** of the challenges facing the operators to extend the coverage of the networks to meet the rising demand for cellular mobile services is the power sources used to supply cellular towers with energy,especially in ***,switch from the conventional sources of energy to a greener and sustainable power model became a target of the academic and industrial sectors in many fields;one of these important fields is the telecommunication ***,this study aims to find the optimum sizing and technoeconomic investigation of a solar photovoltaic scheme to deploy cellular mobile technology infrastructure cleanly and *** optimal solarpowered system is designed by employing the energy-balance procedures of the HOMER software *** problem objective is considered in terms of cost,but the energy system is constrained to meet the power demand *** simulations were performed to determine the optimum sizing,performance and monetary cost of the power system,using long-term meteorological datasets for a case study site with defined longitude(31◦25E)and latitude(30◦06N).From the observed results,the total net present cost(NPC)of the proposed system is$28,***,these outcomes can provide profound economic,technical,and ecological benefits to cellular *** also ensures a sizeable reduction in greenhouse gas that supports sustainable green wireless network(WN)deployment in remote areas.

关键词： Wireless networks green wireless networks green communications sustainability OPEX

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Brain Tumor Identification Using Data Augmentation and Transfer Learning Approach

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Computer Systems Science & Engineering 2023年第8期46卷 1845-1861页

作者： K.Kavin Kumar P.M.Dinesh P.Rayavel L.Vijayaraja R.Dhanasekar Rupa Kesavan kannadasan raju Arfat Ahmad Khan Chitapong Wechtaisong Mohd Anul Haq Zamil S.Alzamil Ahmed Alhussen Department of Electronics and Communication Engineering Kongu Engineering College638060Tamil NaduIndia Department of Electronics and Communication Engineering Sona College of Technology636005Tamil NaduIndia Department of Computer Science and Engineering Sri Sairam Institute of TechnologyChennai600044Tamil NaduIndia Department of Electrical and Electronics Engineering Sri Sairam Institute of TechnologyChennai600044Tamil NaduIndia Department of Computer Science and Engineering Sri Venkateswara College of EngineeringSriperumbudur602117Tamil NaduIndia Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117Tamil NaduIndia Department of Computer Science College of ComputingKhon Kaen UniversityKhonKaen40002Thailand School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

A brain tumor is a lethal neurological disease that affects the average performance of the brain and can be *** India,around 15 million cases are diagnosed *** mitigate the seriousness of the tumor it is essential to diagnose at the ***,the manual evaluation process utilizing Magnetic Resonance Imaging(MRI)causes a few worries,remarkably inefficient and inaccurate brain tumor ***,the examination process of brain tumors is intricate as they display high unbalance in nature like shape,size,appearance,and ***,a precise and expeditious prognosis of brain tumors is essential for implementing the of an implicit *** computer models adapted to diagnose the tumor,but the accuracy of the model needs to be *** all the above mentioned things,this work aims to identify the best classification system by considering the prediction accuracy out of Alex-Net,ResNet 50,and Inception *** augmentation is performed on the database and fed into the three convolutions neural network(CNN)models.A comparison line is drawn between the three models based on accuracy and *** accuracy of 96.2%is obtained for AlexNet with augmentation and performed better than ResNet 50 and Inception V3 for the 120th *** the suggested model with higher accuracy,it is highly reliable if brain tumors are diagnosed with available datasets.

关键词： AlexNet brain tumor data augmentation inception V3 ResNet 50

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