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Protecting Data Mobility in Cloud Networks Using Metadata Security

Computer Systems Science & Engineering 2022年第7期42卷 105-120页

作者： r.punithavathi M.Kowsigan r.Shanthakumari Miodrag Zivkovic Nebojsa Bacanin Marko Sarac Department of Information Technology M.Kumarasamy College of EngineeringKarur639113India Department of Computer Science and Engineering School of ComputingSRM Institute of TechnologyKattankulathur CampusChennai603203India Department of Information Technology Kongu Engineering CollegeErode638060India Singidunum University Belgrade11000Serbia

At present,health care applications,government services,and banking applications use big data with cloud storage to process and implement data.Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data.Sometimes,data may have highly sensitive information,lead-ing users to consider using big data and cloud processing regardless of whether they are secured are not.Threats to sensitive data in cloud systems produce high risks,and existing security methods do not provide enough security to sensitive user data in cloud and big data environments.At present,several security solu-tions support cloud systems.Some of them include Hadoop Distributed File Sys-tem(HDFS)baseline Kerberos security,socket layer-based HDFS security,and hybrid security systems,which have time complexity in providing security inter-actions.Thus,mobile data security algorithms are necessary in cloud environ-ments to avoid time risks in providing security.In our study,we propose a data mobility and security(DMoS)algorithm to provide security of data mobility in cloud environments.By analyzing metadata,data are classiﬁed as secured and open data based on their importance.Secured data are sensitive user data,whereas open data are open to the public.On the basis of data classiﬁcation,secured data are applied to the DMoS algorithm to achieve high security in HDFS.The pro-posed approach is compared with the time complexity of three existing algo-rithms,and results are evaluated.

关键词： Data mobility data security cloud computing big data DMoS algorithm

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Suicide Ideation Detection of Covid Patients Using Machine Learning Algorithm

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Computer Systems Science & Engineering 2023年第4期45卷 247-261页

作者： r.punithavathi S.Thenmozhi r.Jothilakshmi V.Ellappan Islam Md Tahzib Ul M Kumarasamy College of Engineering KarucrTamil NaduIndia Dayananda Sagar College of Engineering BangaloreKarnatakaIndia r.M.D Engineering College KavaraipettaiTamil NaduIndia Adama Science and Technology University AdamaEthiopia Dhaka International University DhakaBangaladesh

During Covid pandemic,many individuals are suffering from suicidal ideation in the world.Social distancing and quarantining,affects the patient emotionally.Affective computing is the study of recognizing human feelings and emotions.This technology can be used effectively during pandemic for facial expression recognition which automatically extracts the features from the human face.Monitoring system plays a very important role to detect the patient condition and to recognize the patterns of expression from the safest distance.In this paper,a new method is proposed for emotion recognition and suicide ideation detection in COVID patients.This helps to alert the nurse,when patient emotion is fear,cry or sad.The research presented in this paper has introduced Image Processing technology for emotional analysis of patients using Machine learning algorithm.The proposed Convolution Neural Networks(CNN)architecture with DnCNN preprocessing enhances the performance of recognition.The system can analyze the mood of patients either in real time or in the form of video files from CCTV cameras.The proposed method accuracy is more when compared to other methods.It detects the chances of suicide attempt based on stress level and emotional recognition.

关键词： HOG ACO-CS optimizedKNN PCA emotion detection covid face recognition

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Computer Vision and Deep Learning-enabled Weed Detection Model for Precision Agriculture

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Computer Systems Science & Engineering 2023年第3期44卷 2759-2774页

作者： r.punithavathi A.Delphin Carolina rani K.r.Sughashinir Chinnarao Kurangit M.Nirmala Hasmath Farhana Thariq Ahmed S.P.Balamurugan Department of Information Technology M.Kumarasamy College of EngineeringKarur6391 I3India Department of Computer Science and Engineering K.Ramakrishnan College of TechnologyTiruchirapalli621112India Department of Electronics and Instrumentation Easwani Engineering CollegeTamil Nadu600089India Pondichery University Puducherry605014India Department of computer science and engineering The Oxford college of EngineeringBangalore560068India Department of Computer Science Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Computer and Information Science Faculty of ScienceAnnamalai University Chidambaram608002India

Presently,precision agriculture processes like plant disease,crop yield prediction,species recognition,weed detection,and irrigation can be accom-plished by the use of computer vision(CV)approaches.Weed plays a vital role in influencing crop productivity.The wastage and pollution of farmland's natural atmosphere instigated by full coverage chemical herbicide spraying are increased.Since the proper identification of weeds from crops helps to reduce the usage of herbicide and improve productivity,this study presents a novel computer vision and deep learning based weed detection and classification(CVDL-WDC)model for precision agriculture.The proposed CVDL-WDC technique intends to prop-erly discriminate the plants as well as weeds.The proposed CVDL-WDC technique involves two processes namely multiscale Faster rCNN based object detection and optimal extreme learning machine(ELM)based weed classification.The parameters of the ELM model are optimally adjusted by the use of farmland fertility optimization(FFO)algorithm.A comprehensive simulation analysis of the CVDL-WDC technique against benchmark dataset reported the enhanced out-comes over its recent approaches interms of several measures.

关键词： Precision agriculture smart farming weed detection computer vision deep learning

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Hybrid BWO-IACO Algorithm for Cluster Based routing in Wireless Sensor Networks

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Computers, Materials & Continua 2021年第10期69卷 433-449页

作者： r.punithavathi Chinnarao Kurangi S.P.Balamurugan Irina V.Pustokhina Denis A.Pustokhin K.Shankar Department of Information Technology M.Kumarasamy College of EngineeringKarur639113India Department of Computer Science Pondicherry UniversityPuducherry605014India Department of Computer and Information Science Faculty of ScienceAnnamalai UniversityChidambaram608002India 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 Network(WSN)comprises a massive number of arbitrarily placed sensor nodes that are linked wirelessly to monitor the physical parameters from the target region.As the nodes in WSN operate on inbuilt batteries,the energy depletion occurs after certain rounds of operation and thereby results in reduced network lifetime.To enhance energy efficiency and network longevity,clustering and routing techniques are commonly employed in WSN.This paper presents a novel black widow optimization(BWO)with improved ant colony optimization(IACO)algorithm(BWO-IACO)for cluster based routing in WSN.The proposed BWO-IACO algorithm involves BWO based clustering process to elect an optimal set of cluster heads(CHs).The BWO algorithm derives a fitness function(FF)using five input parameters like residual energy(rE),inter-cluster distance,intra-cluster distance,node degree(ND),and node centrality.In addition,IACO based routing process is involved for route selection in inter-cluster communication.The IACO algorithm incorporates the concepts of traditional ACO algorithm with krill herd algorithm(KHA).The IACO algorithm utilizes the energy factor to elect an optimal set of routes to BS in the network.The integration of BWO based clustering and IACO based routing techniques considerably helps to improve energy efficiency and network lifetime.The presented BWO-IACO algorithm has been simulated using MATLAB and the results are examined under varying aspects.A wide range of comparative analysis makes sure the betterment of the BWO-IACO algorithm over all the other compared techniques.

关键词： Clustering routing wireless sensor network energy efficiency black widow optimization

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Metaheuristic Clustering Protocol for Healthcare DataCollection in MobileWireless Multimedia Sensor Networks

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Computers, Materials & Continua 2021年第3期66卷 3215-3231页

作者： G G.Kadiravan P.Sujatha T.Asvany r.punithavathi Mohamed Elhoseny Irina V.Pustokhina Denis A.Pustokhin K.Shankar Department of Computer Science Pondicherry UniversityPuducherry605014India Department of Information Technology M.Kumarasamy College of EngineeringKarur639113India Faculty of Computers and Information Mansoura UniversityEgypt Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Applications Alagappa UniversityKaraikudiIndia

Nowadays,healthcare applications necessitate maximum volume of medical data to be fed to help the physicians,academicians,pathologists,doctors and other healthcare professionals.Advancements in the domain of Wireless Sensor Networks(WSN)andMultimediaWireless Sensor Networks(MWSN)are tremendous.M-WMSN is an advanced form of conventional Wireless Sensor Networks(WSN)to networks that use multimedia devices.When compared with traditional WSN,the quantity of data transmission in M-WMSN is significantly high due to the presence of multimedia content.Hence,clustering techniques are deployed to achieve low amount of energy utilization.The current research work aims at introducing a new Density Based Clustering(DBC)technique to achieve energy efficiency inWMSN.The DBC technique is mainly employed for data collection in healthcare environment which primarily depends on three input parameters namely remaining energy level,distance,and node centrality.In addition,two static data collector points called Super Cluster Head(SCH)are placed,which collects the data from normal CHs and forwards it to the Base Station(BS)directly.SCH supports multi-hop data transmission that assists in effectively balancing the available energy.Adetailed simulation analysiswas conducted to showcase the superior performance of DBC technique and the results were examined under diverse aspects.The simulation outcomes concluded that the proposed DBC technique improved the network lifetime to a maximum of 16,500 rounds,which is significantly higher compared to existing methods.

关键词： Smart sensor environment healthcare data multimedia big data processing clustering mobility energy efficiency

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Analysis and Optimization of Operational and Pollutant Attributes of Diesel Engine with CNT-Infused Orange Peel Biodiesel-Diesel Blend Fuel

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Journal of Thermal Science 2024年第2期33卷 761-778页

作者： ranjeet rAI r.r.SAHOO Mechanical Engineering Department GLA UniversityMathura281406India Mechanical Engineering Department IIT(BHU)Varanasi221005India

The current study is performed to find sustainable solutions for the future of transportation and environmental well-being.Both conventional methods and experimental design table(L16 Orthogonal Array)techniques have been employed to examine and optimize a diesel-powered engine's operational and pollutant parameters.The L16 Orthogonal Array is obtained through Taguchi's experimental design approach using Minitab 16 software.The experimental design incorporated three control variables,namely engine speed,fuel type,and engine load,each with four levels.The operational parameters,namely brake thermal efficiency(BTE)and brake specific fuel consumption(BSFC),as well as the emission characteristics,including hydrocarbon(HC),carbon monoxide(CO),nitrogen oxide(NO),and smoke emissions,were acquired using the L16 orthogonal array(OA) and subsequently examined.The utilization of methodologies such as signal-to-noise(S/N) ratio and grey analysis was employed to determine the optimal operational state of the engine to achieve maximum performance while minimizing emissions.The engine's ideal state of operation,in terms of BTE and BSFC,was determined to be at 75% engine load,1000 r/min engine speed,and using 10^(-4)(in vol) carbon nanotube incorporated 20% orange peel biodiesel(OPB20CNT100) blended fuel(A3-B1-C4).The study indicated that engine load significantly influenced BTE and BSFC,with 84.05% and 87.79% contribution factors,respectively.At 25% engine load,1000 r/min,and OPB20CNT100 fuel(A1-B1-C4) CO,smoke,NO,and HC emissions were the lowest.Engine load affects emissions the most.Engine BSFC increased 3.10% and NO emissions 1.77%.BTE,CO,smoke,and HC emissions decreased by 1.9%,12.29%,47.05%,and 47.22%,respectively,at optimal operating conditions concerning diesel fuel.This study shows that Taguchi-Grey's experimental design optimizes diesel engine operational and pollutant attributes.The outcomes revealed that orange peel biodiesel infused with CNT can replace diesel fuel in an environmentally friendly way.This alternative

关键词： Taguchi-Grey method OPB20CNT100 transesterification S/N ratio GrG HC CO and NO

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Treat to target in Crohn’s disease:A practical guide for clinicians

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World Journal of Gastroenterology 2024年第1期30卷 50-69页

作者： Ashish r Srinivasan Department of Gastroenterology Austin HealthVictoriaMelbourne 3083Australia Department of Gastroenterology Eastern HealthVictoriaMelbourne 3128Australia Department of Medicine University of MelbourneVictoriaMelbourne 3052Australia

A treat-to-target(T2T)approach applies the principles of early intervention and tight disease control to optimise long-term outcomes in Crohn's disease.The Selecting Therapeutic Targets in Inflammatory Bowel Disease(STrIDE)-II guidelines specify short,intermediate,and long-term treatment goals,documenting specific treatment targets to be achieved at each of these timepoints.Scheduled appraisal of Crohn’s disease activity against pre-defined treatment targets at these timepoints remains central to determining whether current therapy should be continued or modified.Consensus treatment targets in Crohn’s disease comprise combination clinical and patient-reported outcome remission,in conjunction with biomarker normalisation and endoscopic healing.Although the STrIDE-II guidelines endorse the pursuit of endoscopic healing,clinicians must consider that this may not always be appropriate,acceptable,or achievable in all patients.This underscores the need to engage patients at the outset in an effort to personalise care and individualise treatment targets.The use of non-invasive biomarkers such as faecal calprotectin in conjunction with cross-sectional imaging techniques,particularly intestinal ultrasound,holds great promise;as do emerging treatment targets such as transmural healing.Two randomised clinical trials,namely,CALM and STArDUST,have evaluated the efficacy of a T2T approach in achieving endoscopic endpoints in patients with Crohn’s disease.Findings from these studies reflect that patient subgroups and Crohn’s disease characteristics likely to benefit most from a T2T approach,remain to be clarified.Moreover,outside of clinical trials,data pertaining to the real-world effectiveness of a T2T approach remains scare,highlighting the need for pragmatic real-world studies.Despite the obvious promise of a T2T approach,a lack of guidance to support its integration into real-world clinical practice has the potential to limit its uptake.This highlights the need to describe strategies,processes,and models of care capable of

关键词： Treat to target Inflammatory bowel disease Crohn’s disease Treatment targets Endoscopic remission Transmural healing Time to response Intestinal ultrasound

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Kinematic analysis of flexible bipedal robotic systems

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 795-818页

作者： r.FAZEL A.M.SHAFEI S.r.NEKOO Department of Mechanical Engineering Shahid Bahonar University of KermanKerman ***Iran Departamento de Ingenieria de Sistemas y Automatica Escuela Técnica Superior de IngenieriaUniversidad de SevillaSeville 41092Spain

In spite of its intrinsic complexities,the passive gait of bipedal robots on a sloping ramp is a subject of interest for numerous researchers.What distinguishes the present research from similar works is the consideration of flexibility in the constituent links of this type of robotic systems.This is not a far-fetched assumption because in the transient(impact)phase,due to the impulsive forces which are applied to the system,the likelihood of exciting the vibration modes increases considerably.Moreover,the human leg bones that are involved in walking are supported by viscoelastic muscles and ligaments.Therefore,for achieving more exact results,it is essential to model the robot links with viscoelastic properties.To this end,the Gibbs-Appell formulation and Newton's kinematic impact law are used to derive the most general form of the system's dynamic equations in the swing and transient phases of motion.The most important issue in the passive walking motion of bipedal robots is the determination of the initial robot configuration with which the system could accomplish a periodic and stable gait solely under the effect of gravitational force.The extremely unstable nature of the system studied in this paper and the vibrations caused by the impulsive forces induced by the impact of robot feet with the inclined surface are some of the very serious challenges encountered for achieving the above-mentioned goal.To overcome such challenges,an innovative method that uses a combination of the linearized equations of motion in the swing phase and the algebraic motion equations in the transition phase is presented in this paper to obtain an eigenvalue problem.By solving this problem,the suitable initial conditions that are necessary for the passive gait of this bipedal robot on a sloping surface are determined.The effects of the characteristic parameters of elastic links including the modulus of elasticity and the Kelvin-Voigt coefficient on the walking stability of this type of robotic systems are also studied.The findings o

关键词： bipedal robot flexible link swing phase transient phase eigenvalue problem Kelvin-Voigt coefficient

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Neurogenic potential of NG2 in neurotrauma:a systematic review

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Neural regeneration research 2024年第12期19卷 2673-2683页

作者： Yuri r.rigo radharani Benvenutti Luis V.Portela Nathan r.Strogulski Departamento de Bioquímica Instituto de Ciências Básicas da SaúdeUniversidade Federal do Rio Grande do Sul(UFRGS)Porto AlegreBrazil School of Pharmacy and Biomolecular Sciences RCSI University of Medicine and Health SciencesDublinIreland School of Biochemistry and Immunology Trinity Biomedical Sciences InstituteTrinity College DublinUniversity of DublinDublinIreland

regenerative approaches towards neuronal loss following traumatic brain or spinal cord injury have long been considered a dogma in neuroscience and remain a cutting-edge area of research.This is reflected in a large disparity between the number of studies investigating primary and secondary injury as therapeutic to rgets in spinal co rd and traumatic brain injuries.Significant advances in biotechnology may have the potential to reshape the current state-of-the-art and bring focus to primary injury neurotrauma research.recent studies using neural-glial factor/antigen 2(NG2)cells indicate that they may differentiate into neurons even in the developed brain.As these cells show great potential to play a regenerative role,studies have been conducted to test various manipulations in neurotrauma models aimed at eliciting a neurogenic response from them.In the present study,we systematically reviewed the experimental protocols and findings described in the scientific literature,which were peer-reviewed original research articles(1)describing preclinical experimental studies,(2)investigating NG2 cells,(3)associated with neurogenesis and neurotrauma,and(4)in vitro and/or in vivo,available in PubMed/MEDLINE,Web of Science or SCOPUS,from 1998 to 2022.Here,we have reviewed a total of 1504 papers,and summarized findings that ultimately suggest that NG2 cells possess an inducible neurogenic potential in animal models and in vitro.We also discriminate findings of NG2 neurogenesis promoted by different pharmacological and genetic approaches over functional and biochemical outcomes of traumatic brain injury and spinal co rd injury models,and provide mounting evidence for the potential benefits of manipulated NG2 cell ex vivo transplantation in primary injury treatment.These findings indicate the feasibility of NG2 cell neurogenesis strategies and add new players in the development of therapeutic alternatives for neurotrauma.

关键词： neural-glial antigen 2 neural-glial factor 2 neuron differentiation NG2 cell regeneration spinal cord injury(SCI) traumatic brain injury(TBI)

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Transcranial photobiomodulation for the brain: a wide range of clinical applications

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Neural regeneration research 2024年第3期19卷 483-484页

作者： Michael r.Hamblin Laser research Centre Faculty of Health ScienceUniversity of Johannesburg-Doornfontein CampusDoornfonteinSouth Africa

Photobiomodulation therapy(PBMT)is a rapidly growing approach to the healing,stimulation,protection,and regeneration of many human organs and tissue types.PBMT started in the 1960s as low-level laser therapy for wound healing,but since then the introduction of light-emitting diodes(LEDs)has dramatically increased the number of applications and reports of positive results.PBMT generally uses red(620-700 nm)and/or near-infrared(780-1270 nm)wavelengths of light at an intensity that causes no tissue heating,and its activity is based on well-established biological and cellular mechanisms(de Freitas and Hamblin,2016).While laser therapists continue to use various types of laser in their office practice,LEDs are ideally suited for home use devices because they are completely safe and without any known significant adverse effects.Among the various body parts on which PBMT has been shown to exert beneficial effects,the brain stands out as perhaps the most promising overall.PBMT has been shown to reduce neuroinflammation,while increasing mitochondrial function,oxygen consumption,and blood flow within the brain(Hamblin,2016).Moreover,PBMT can stimulate the processes of synaptogenesis,neurogenesis,and neuroplasticity thus helping the brain to heal itself.

关键词： healing stimulation wound

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