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An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

Computer Modeling in Engineering & Sciences 2024年第2期138卷 1051-1075页

作者： Shazia Shamas Surya Narayan Panda Ishu Sharma kalpna Guleria Aman singh Ahmad Ali AlZubi Mallak Ahmad AlZubi Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Higher Polytechnic School Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Engineering Universidad Internacional IberoamericanaAreciboPR00613USA Uttaranchal Institute of Technology Uttaranchal UniversityDehradunUttarakhand248007India Computer Science Department King Saud UniversityRiyadhSaudi Arabia Faculty of Medicine Jordan University of Science and TechnologyIrbidJordan

The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis andplanning intervention. This research work addresses the major issues pertaining to the field of medical imageprocessing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposesan improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. Thebetter resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In thisprocess, the visual challenges of the k-means are addressed with the integration of four nature-inspired swarmintelligent techniques. The techniques experimented in this paper are k-means with Artificial Bee Colony (ABC),k-means with Cuckoo Search Algorithm (CSA), k-means with Particle Swarm Optimization (PSO), and kmeanswith Firefly Algorithm (FFA). The testing and evaluation are performed on Early Lung Cancer ActionProgram (ELCAP) database. The simulation analysis is performed using lung cancer images set against metrics:precision, sensitivity, specificity, f-measure, accuracy,Matthews Correlation Coefficient (MCC), Jaccard, and *** detailed evaluation shows that the k-means with Cuckoo Search Algorithm (CSA) significantly improved thequality of lung cancer segmentation in comparison to the other optimization approaches utilized for lung cancerimages. The results exhibit that the proposed approach (k-means with CSA) achieves precision, sensitivity, and Fmeasureof 0.942, 0.964, and 0.953, respectively, and an average accuracy of 93%. The experimental results prove thatk-meanswithABC,k-meanswith PSO,k-meanswith FFA, andk-meanswithCSAhave achieved an improvementof 10.8%, 13.38%, 13.93%, and 15.7%, respectively, for accuracy measure in comparison to k-means segmentationfor lung cancer images. Further, it is highlighted that the proposed k-means with CSA have achieved a significantimprovement in accuracy, hence can be utilized by resea

关键词： Lesion lung cancer segmentation medical imaging meta-heuristic Artificial Bee Colony(ABC) Cuckoo Search Algorithm(CSA) Particle Swarm Optimization(PSO) Firefly Algorithm(FFA) segmentation

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Cancer chemotherapy and beyond:Current status,drug candidates,associated risks and progress in targeted therapeutics

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Genes & Diseases 2023年第4期10卷 1367-1401页

作者： Uttpal Anand Abhijit Dey a.vind k.singh cha.del Rupa Sanyal Amarnath Mishra Devendra kumar Pandey Valentina De Falco Arun Upadhyay Ramesh kandimalla Anupama chaudhary Jaspreet kaur Dhanjal Saikat Dewanjee Jayalakshmi Vallamkondu José M.Pérez de la Lastra Department of Life Sciences Ben-Gurion University of the NegevBeer-Sheva 84105Israel Department of Life Sciences Presidency UniversityKolkataWest Bengal 700073India Center for Disease Biology and Integrative Medicine Faculty of MedicineThe University of TokyoTokyo 113-0033Japan Department of Botany Bhairab Ganguly College(affiliated to West Bengal State University)KolkataWest Bengal 700056India Faculty of Science and Technology Amity Institute of Forensic SciencesAmity University Uttar PradeshNoida 201313India Department of Biotechnology School of Bioengineering and BiosciencesLovely Professional UniversityPhagwaraPunjab 144411India Institute of Endocrinology and Experimental Oncology(IEOS) National Research Council(CNR)Department of Molecular Medicine and Medical Biotechnology(DMMBM)University of Naples Federico IINaples 80131Italy Department of Biochemistry School of Life SciencesCentral University of RajasthanBandar SindariKishangarh AjmerRajasthan 305817India CSIR-Indian Institute of Chemical Technology HyderabadTelangana 500007India Department of Biochemistry Kakatiya Medical CollegeWarangalTelangana 506007India Orinin-BioSystems LE-52Lotus Road 4CHD CityKarnalHaryana 132001India Department of Computational Biology Indraprastha Institute of Information Technology Delhi(IIIT-D)Okhla Industrial EstatePhase IIINew Delhi 110020India Advanced Pharmacognosy Research Laboratory Department of Pharmaceutical TechnologyJadavpur UniversityKolkata 700032India Department of Physics National Institute of Technology-WarangalWarangalTelangana 506004India Biotechnology of Macromolecules Research Group Instituto de Productos Naturales y AgrobiologíaIPNA-CSICSan Cristóbal de La Laguna 38206TenerifeSpain

Cancer is an abnormal state of cells where they undergo uncontrolled proliferation and produce aggressive malignancies that causes millions of deaths every *** the new understanding of the molecular mechanism(s)of disease progression,our knowledge about the disease is snowballing,leading to the evolution of many new therapeutic regimes and their successive *** the past few decades,various combinations of therapies have been pro-posed and are presently employed in the treatment of diverse *** drug therapy,immunotherapy,and personalized medicines are now largely being employed,which were not common a few years *** field of cancer discoveries and therapeutics are evolving fast as cancer type-specific biomarkers are progressively being identified and several types of cancers are nowadays undergoing systematic therapies,extending patients’disease-free survival *** growing evidence shows that a systematic and targeted approach could be the future of cancer medicine,chemotherapy remains a largely opted therapeutic option despite its known side effects on the patient’s physical and psychological ***-apeutic agents/pharmaceuticals served a great purpose over the past few decades and have remained the frontline choice for advanced-stage malignancies where surgery and/or radiation therapy cannot be prescribed due to specific *** present report succinctly reviews the existing and contemporary advancements in chemotherapy and assesses the status of the enrolled drugs/pharmaceuticals;it also comprehensively discusses the emerging role of specific/targeted therapeutic strategies that are presently being employed to achieve better clinical success/survival rate in cancer patients.

关键词： Antimicrobial peptides Cancer therapies Clinical trials Combination therapy Immunotherapy Patient survival Personalized medicine Targeted drug delivery

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Radioisotope production using lasers:From basic science to applications

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Matter and Radiation at Extremes 2024年第3期9卷 31-44页

作者： M.R.D.Rodrigues A.Bonasera M.Scisciò J.A.Pérez-Hernández M.Ehret F.Filippi P.L.Andreoli M.Huault H.Larreur D.Singappuli D.Molloy D.Raffestin M.Alonzo G.G.Rapisarda D.Lattuada G.L.Guardo C.Verona Fe.Consoli G.Petringa A.McNamee M.La Cognata S.Palmerini T.Carriere M.Cipriani G.Di Giorgio G.Cristofari R.De Angelis G.A.P.Cirrone D.Margarone L.Giuffrida D.Batani P.Nicolai k.Batani R.Lera L.Volpe D.Giulietti S.Agarwal M.krupka S.singh Fa.Consoli Cyclotron Institute Texas A&M UniversityCollege StationTexas 77840USA Laboratori Nazionali del Sud Istituto Nazionale di Fisica Nucleare(LNS-INFN)CataniaItaly ENEA Fusion and Technologies for Nuclear Safety and Security Department-CFrascatiItaly Centro de Láseres Pulsados(clpu) VillamayorSpain Universidad de Salamanca SalamancaSpain Centre Lasers Intenses et Applications(CELIA) Universitéde BordeauxCNRSCEATalenceFrance HB11 Energy Holdings Pty FreshwaterNew South WalesAustralia School of Mathematics and Physics Queen’s University BelfastBelfastUnited Kingdom Dipartimento di Fisica e Astronomia“E.Majorana ”Università di CataniaCataniaItaly Facoltàdi Ingegneria e Architettura Universitàdegli Studi di Enna“Kore”EnnaItaly Dipartimento di Ingegneria Industriale Universitàdi Roma“Tor Vergata”RomaItaly Dipartimento di Fisica e Geologia Universitàdegli Studi di PerugiaPerugiaItaly Istituto Nazionale di Fisica Nucleare Sezione di PerugiaPerugiaItaly ELI Beamlines Facility the Extreme Light Infrastructure ERICDolni BrezanyCzech Republic ETSIA Universidad Politécnica de MadridMadridSpain Dipartimento Fisica “E.Fermi”Universitàdi Pisa and INFNPisaItaly FZU–Institute of Physics of Czech Academy of Sciences PragueCzech Republic Institute of Plasma Physics of Czech Academy of Sciences PragueCzech Republic

The discovery of chirped pulse amplification has led to great improvements in laser technology,enabling energetic laser beams to be compressed to pulse durations of tens of femtoseconds and focused to a few *** with energies of tens of MeV can be accelerated using,for instance,target normal sheath acceleration and focused on secondary *** such conditions,nuclear reactions can occur,with the production of radioisotopes suitable for medical *** use of high-repetition lasers to produce such isotopes is competitive with conventional methods mostly based on *** this paper,we study the production of^(67)Cu,^(63)Zn,^(18)F,and^(11)C,which are currently used in positron emission tomography and other *** the same time,we study the reactions^(10)B(p,α)^(7)Be and^(70)Zn(p,4n)^(67)Ga to put further constraints on the proton distributions at different angles,as well as the reaction^(11)B(p,α)^(8)Be relevant for energy *** experiment was performed at the 1 PW laser facility at VegaⅢin Salamanca,*** distributions of radioisotopes in the forward(with respect to the laser direction)and backward directions were measured using a high purity germanium *** results are in reasonable agreement with numerical estimates obtained following the approach of kimura and Bonasera[*** ***.,Sect.A 637,164–170(2011)].

关键词： purity estimates backward

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Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第11期15卷 3010-3038页

作者： Jitendra khatti kamaldeep singh Grover Department of Civil Engineering Rajasthan Technical UniversityKota324010RajasthanIndia

A comparison between deep learning and standalone models in predicting the compaction parameters of soil is presented in this *** hundred and ninety and fifty-three soil samples were randomly picked up from two hundred and forty-three soil samples to create training and validation datasets,*** performance and accuracy of the models were measured by root mean square error(RMSE),coefficient of determination(R2),Pearson product-moment correlation coefficient(r),mean absolute error(MAE),variance accounted for(VAF),mean absolute percentage error(MAPE),weighted mean absolute percentage error(WMAPE),a20-index,index of scatter(IOS),and index of agreement(IOA).Comparisons between standalone models demonstrate that the model MD 29 in Gaussian process regression(GPR)and model MD 101 in support vector machine(SVM)can achieve over 96%of accuracy in predicting the optimum moisture content(OMC)and maximum dry density(MDD)of soil,and outperformed other standalone *** comparison between deep learning models shows that the models MD 46 and MD 146 in long short-term memory(LSTM)predict OMC and MDD with higher accuracy than ANN ***,the LSTM models outperformed the GPR models in predicting the compaction *** sensitivity analysis illustrates that fine content(FC),specific gravity(SG),and liquid limit(LL)highly influence the prediction of compaction parameters.

关键词： Artificial intelligence(AI) Anderson-darling(AD)test Compaction parameters Fine-grained soil Soft computing Score analysis

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Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices

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Computers, Materials & Continua 2022年第7期72卷 999-1015页

作者： Anita Gehlot Rajesh singh Sweety Siwach Shaik Vaseem Akram khalid Alsubhi Aman singh Irene delgado Noya Sushabhan Choudhury School of Electronics&Electrical Engineering Lovely Professional UniversityPunjab144411India Department of Electronics&Communication Engineering University of Petroleum and Energy StudiesDehradun248001India Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah37848Saudi Arabia Higher Polytechnic School Universidad Europea del AtlánticoC/Isabel Torres 2139011 SantanderSpain Universidad Internacional Iberoamericana CampecheMexico

Wearable monitoring devices are in demand in recent times for monitoring daily activities including ***,it is widely utilizing for preventing injuries of athletes during a practice session and in few cases,it leads to muscle *** present,emerging technology like the internet of things(IoT)and sensors is empowering to monitor and visualize the physical data from any remote location through internet *** this study,an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram(sEMG)***,the EMG signal is utilized to display muscle *** controller,Wi-Fi module,and EMG sensor are utilized in developing the wearable *** Time-frequency domain spectrum technique is employed for classifying the threemuscle fatigue conditions including meanRMS,mean frequency,etc.A real-time experiment is realized on six different individuals with developed wearable devices and the average RMS value assists to determine the average threshold of recorded *** threshold level is analyzed by calculating the mean RMS value and concluded three fatigue conditions as>2V:Extensive);1–2V:Moderate,and<1V:*** warning alarm system was designed in LabVIEW with three color LEDs to indicate the different states of muscle ***,the device is interfaced with the cloud through the internet provided with a Wi-Fi module embedded in wearable *** data available in the cloud server can be utilized for forecasting the frequency of an individual to muscle fatigue.

关键词： LabVIEW muscle fatigue sEMG wearable sensor IoT cloud server

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A review on synthesis of graphene,h-BN and MoS2 for energy storage applications:Recent progress and perspectives

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Nano Research 2019年第11期12卷 2655-2694页

作者： Rajesh kumar Sumanta Sahoo Ednan Joanni Rajesh kumar singh Ram Manohar Yadav Rajiv kumar Verma Dinesh Pratap singh Wai kian Tan Angel Perez del Pino Stanislav A.Moshkalev Atsunori Matsuda Department of Eletrical and Electronic Information Engineering Toyohashi University of Technologys1-1 HibarigaokaTempaku-chaToyohashiAichi 441-8580Japan Department of Applied Chemistry Indian Institute of Technology(ISM) Dhanbad826004JharkhandIndia Centre for Information Technology Renato Archer(CTI) Campinas 13069-901Brazil School of Physical and Material Sciences Central University of Himachal Pradesh(CUHP)KangraDharamshala 176215HR India Department of Plhysics VSSD CollegeKanpur 208002India International College Osaka University1-2 MachikaneyamachoToyonaka shiOsaka 560-0043Japan Department of Physics and Milermium Institute for Research in Optics(MIRO) University of SantiagoAvenida Ecuador 3493Estacion CentralSantiago 9170124Chile Institute of Liberal Arts and Sciences Toyohashi University of Technology1-1 HibarigaokaTempaku choToyohashiAichi 441-8580 Japan Instituto de Ciencia de Materiales de Barcelona Consejo Superior de Irvestigaciones Cientificas(ICMAB-CSIC)Campus UABBllaterra08193 BarcelonaSpain Centre for Semiconductor Components and Nanotechnology(CCS Nano) Uniersity of Campinas(UNICAMP)Campinas 13083-870Brazil

The significance of graphene and its two-dimensional(2D)analogous inorganic layered materials especially as hexagonal boron nitride(h-BN)and molybdenum disulphide(MoS2)for“clean energy”applications became apparent over the last few years due to their extraordinary *** this review article we study the current progress and selected challenges in the syntheses of graphene,h-BN and MoS2 including energy storage applications as supercapacitors and *** substrates/catalysts(metals/insulator/semiconducting)have been used to obtain graphene,h-BN and MoS2 using different kinds of *** most widespread methods for synthesis of graphene,h-BN and MoS2 layers are chemical vapor deposition(CVD),plasma-enhanced CVD,hydro/solvothermal methods,liquid phase exfoliation,physical methods *** research has shown that graphene,h-BN and MoS2 layered materials modified with metal oxide can have an insightful influence on the performance of energy storage devices as supercapacitors and *** review article also contains the discussion on the opportunities and perspectives of these materials(graphene,h-BN and MoS2)in the energy storage *** expect that this witen review article including recent research on energy storage will help in generating new insights for further development and practical applications of graphene,h-BN and MoS2 layers based materials.

关键词： graphene norganic layered materials hierarchical structures energy storage supercapacitor battery

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Real-Time Multi-Class Infection Classification for Respiratory Diseases

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Computers, Materials & Continua 2022年第11期73卷 4157-4177页

作者： Ahmed El.Shafee Walid El-Shafai Abdulaziz Alarifi Mohammed Amoon Aman singh Moustafa H.Aly Department of Electrical Engineering Faculty of EngineeringAhram Canadian UniversityGizaEgypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Science Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Higher Polytechnic School Universidad Europea del AtlánticoSantander39011Spain Electronics and Communications Engineering Department College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt

Real-time disease prediction has emerged as the main focus of study in the field of computerized *** disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable,consistent,and timely,successfully lowering mortality rates,particularly during endemics and *** prevent this pandemic’s rapid and widespread,it is vital to quickly identify,confine,and treat affected *** need for auxiliary computer-aided diagnostic(CAD)systems has *** recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 *** advanced convolutional neural network(CNN)architectures in conjunction with radiological imaging makes it possible to provide rapid,accurate,and extremely useful susceptible *** research work proposes a methodology for real-time detection of COVID-19 infections caused by the Corona *** purpose of this study is to offer a two-way COVID-19(2WCD)diagnosis prediction deep learning system that is built on Transfer Learning Methodologies(TLM)and features customized fine-tuning on top of fully connected layered pre-trained CNN architectures.2WCD has applied modifications to pre-trained models for better *** is designed and implemented to improve the generalization ability of the classifier for binary and multi-class *** with the ability to differentiate COVID-19 and No-Patient in the binary class model and COVID-19,No-Patient,and Pneumonia in the multi-class model,our framework is augmented with a critical add-on for visually demonstrating infection in any tested radiological image by highlighting the affected region in the patient’s lung in a recognizable color *** proposed system is shown to be extremely robust and reliable for real-time COVID-19 diagnostic *** can also be used to forecast other lung-related *** the system can assist medical practitioner

关键词： COVID-19 real-time computerized disease prediction intelligent disease identification framework CAD systems X-rays CT-scans CNN real-time detection of COVID-19 infections

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Stress Detector Supported Galvanic Skin Response System with IoT and LabVIEW GUI

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Computers, Materials & Continua 2023年第1期74卷 1217-1233页

作者： Rajesh singh Anita Gehlot Ritika Saxena khalid Alsubhi Divya Anand Irene delgado Noya Shaik Vaseem Akram Sushabhan Choudhury Lovely Professional University Punjab144411India Department of Electronics&Communication Engineering University of Petroleum and Energy Studies248001India Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah37848Saudi Arabia Universidad Europea del Atlántico Santander39011Spain Universidad Internacional Iberoamericana CampecheC.PMexico

Stress is now a serious disease that exists due to changes in working life and food ecosystems around the *** general,it is difficult for a person to know if they are under *** to previous research,temperature,heart rate variability(HRV),humidity,and blood pressure are used to assess stress levels with the use of *** the development of sensor technology and wireless connectivity,people around the world are adopting and using smart *** this study,a bio signal detection device with Internet of Things(IoT)capability with a galvanic skin reaction(GSR)sensor is proposed and built for real-time stress *** proposed device is based on an Arduino controller and Bluetooth *** evaluate the performance of the system,physical stress is created on 10 different participants with three distinct tasks namely reading,visualizing the timer clock,and watching *** analysis is performed for identifying the three different levels of stress and obtaining the threshold values as if the person GSR voltage i.e.,relaxed for1.44 *** addition,LabVIEW is used as a data acquisition system,and a Blueterm mobile application is also used to view the sensor reading received from the device through Bluetooth communication.

关键词： GSR LabVIEW stress detection MATLAB IoT bluetooth

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Intelligent Approach for Clustering Mutations’ Nature of COVID-19 Genome

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Computers, Materials & Continua 2022年第9期72卷 4453-4466页

作者： Ankur Dumka Parag Verma Rajesh singh Anuj Bhardwaj khalid Alsubhi Divya Anand Irene delgado Noya Silvia Aparicio Obregon Computer Science and Engineering Women Institute of TechnologyUttarakhand248007India Chitkara University Institute of Engineering and Technology Chitkara University PunjabPunjab140401India Division of Innovation&Entrepreneurship Lovely Professional UniversityPunjab144411India Computer Science and Engineering Chandigarh UniversityPunjab140413India Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah37848Saudi Arabia Computer Science and Engineering Lovely Professional UniversityPunjab144411India Higher Polytechnic School Universidad Europea del AtlánticoSantander39011Spain Universidad Internacional Iberoamericana Campeche24560MexicoC.P Universidade Internacional do Cuanza Bairro kaluanda BiéAngola

In December 2019,a group of people in Wuhan city of Hubei province of China were found to be affected by an infection called dark etiology *** outbreak of this pneumonia infection was declared a deadly disease by the China Center for Disease Control and Prevention on January 9,2020,named Novel Coronavirus 2019(nCoV-2019).This nCoV-2019 is now known as *** is a big list of infections of this coronavirus which is present in the form of a big *** virus can cause several diseases that usually develop with a serious *** to the World Health Organization(WHO),2019-nCoV has been placed as the modern generation of Severe Acute Respiratory Syndrome(SARS)and Middle East Respiratory Syndrome(MERS)coronaviruses,so COVID-19 can repeatedly change its internal genome structure to extend its *** and accurately predicting the mutational properties of the genome structure of COVID-19 can form a good leadership role in preventing and fighting against *** this research paper,an analytical approach has been presented which is based on the k-means cluster technique of machine learning to find the clusters over the mutational properties of the COVID-19 viruses’complete *** method would be able to act as a promising tool to monitor and track pathogenic infections in their stable and local genetics/hereditary *** paper identifies five main clusters of mutations with k=5 as best in most cases in the coronavirus that could help scientists and researchers develop disease control vaccines for the transformation of coronaviruses.

关键词： nCoV-2019 SARS-CoV-2 COVID-19 genome structure etiology COVID-19 mutations COVID-19 genomes

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Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

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Computers, Materials & Continua 2022年第7期72卷 1799-1814页

作者： Mudita Uppal Deepali Gupta Divya Anand Fahd S.Alharithi Jasem Almotiri Arturo Mansilla Dinesh singh Nitin Goyal Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Computer Science&Engineering Department Lovely Professional UniversityJalandharPunjabIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Higher Polytechnic School/Industrial Organization Engineering Universidad Europea del AtlánticoIsabel Torres 2139011SantanderSpain Department of Project Management Universidad Internacional IberoamericanaCampeche24560Mexico Computer Science and Engineering Department Deenbandhu Chhotu Ram University of Science and TechnologyMurthalSonipatHaryanaIndia

The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and *** applications depend upon the accuracy of sensor ***,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor *** technique identifies the faulty sensor and determines the correct working of the *** sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular *** prediction in digital and analog sensors along with methods of sensor fault prediction are *** are several advantages and disadvantages of sensor fault prediction methods and the fall curve ***,some solutions are provided to overcome the limitations of the fall curve *** this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five *** novelty is to predict a fault before its occurrence by looking at the fall *** sensing of current flow in devices is important to prevent a major ***,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty *** analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to *** evaluation metrics for fault prediction are also described in this *** last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.

关键词： Fault identification fault classification IoT sensor nodes analog sensors digital sensors fall curve

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