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Automated Deep Learning Based Cardiovascular Disease Diagnosis Using ECG signals

Computer systems science & Engineering 2022年第7期42卷 183-199页

作者： s.Karthik m.santhosh m.s.kavitha A.Christopher Paul Department of Computer science&Engineering SNS College of TechnologyCoimbatore641035India Department of Information Technology Karpagam Institute of TechnologyCoimbatore641105India

Automated biomedical signal processing becomes an essential process to determine the indicators of diseased *** the same time,latest develop-ments of artiﬁcial intelligence(AI)techniques have the ability to manage and ana-lyzing massive amounts of biomedical datasets results in clinical decisions and real time *** can be employed for medical imaging;however,the 1D biomedical signal recognition process is still needing to be ***(ECG)is one of the widely used 1-dimensional biomedical sig-nals,which is used to diagnose cardiovascular *** assisted diag-nostic modelsﬁnd it difﬁcult to automatically classify the 1D ECG signals owing to time-varying dynamics and diverse proﬁles of ECG *** resolve these issues,this study designs automated deep learning based 1D biomedical ECG sig-nal recognition for cardiovascular disease diagnosis(DLECG-CVD)*** DLECG-CVD model involves different stages of operations such as pre-proces-sing,feature extraction,hyperparameter tuning,and classiﬁ*** the initial stage,data pre-processing takes place to convert the ECG report to valuable data and transform it into a compatible format for further *** addition,deep belief network(DBN)model is applied to derive a set of feature ***,improved swallow swarm optimization(IssO)algorithm is used for the hyper-parameter tuning of the DBN ***,extreme gradient boosting(XGBoost)classiﬁer is employed to allocate proper class labels to the test ECG *** order to verify the improved diagnostic performance of the DLECG-CVD model,a set of simulations is carried out on the benchmark PTB-XL dataset.A detailed comparative study highlighted the betterment of the DLECG-CVD model interms of accuracy,sensitivity,speciﬁcity,kappa,mathew correlation coefﬁcient,and Hamming loss.

关键词： Biomedical signals 1-dimensional signal electrocardiogram artiﬁcial intelligence deep learning cardiovascular disease decision making

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Cost Effective Optimal Task scheduling model in Hybrid Cloud Environment

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Computer systems science & Engineering 2022年第9期42卷 935-948页

作者： m.manikandan R.subramanian m.s.kavitha s.Karthik Department of Computer science&Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatore641035India Department of Computer science&Engineering SNS College of TechnologyCoimbatore641035India

In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task scheduling model(CEOTs). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.

关键词： Cost effectiveness hybrid cloud optimal task scheduling virtual machine resource allocation make span

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Oppositional Red Fox Optimization Based Task scheduling scheme for Cloud Environment

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Computer systems science & Engineering 2023年第4期45卷 483-495页

作者： B.Chellapraba D.manohari K.Periyakaruppan m.s.kavitha Department of Information Technology Karpagam Institute of TechnologyCoimbatore641032TamilnaduIndia Department of Computer science and Engineering St.Joseph’s Institute of TechnologyChennai600119India Department of Computer science&Engineering SNS College of EngineeringCoimbatore641107India Department of Computer science&Engineering SNS College of TechnologyCoimbatore641035India

Owing to massive technological developments in Internet of Things(IoT)and cloud environment,cloud computing(CC)offers a highly flexible heterogeneous resource pool over the network,and clients could exploit various resources on *** IoT-enabled models are restricted to resources and require crisp response,minimum latency,and maximum bandwidth,which are outside the *** was handled as a resource-rich solution to aforementioned *** high delay reduces the performance of the IoT enabled cloud platform,efficient utilization of task scheduling(Ts)reduces the energy usage of the cloud infrastructure and increases the income of service provider via minimizing processing time of user ***,this article concentration on the design of an oppositional red fox optimization based task scheduling scheme(ORFOTss)for IoT enabled cloud *** presented ORFO-Tss model resolves the problem of allocating resources from the IoT based cloud *** achieves the makespan by performing optimum Ts procedures with various aspects of incoming *** designing of ORFO-Tss method includes the idea of oppositional based learning(OBL)as to traditional RFO approach in enhancing their efficiency.A wide-ranging experimental analysis was applied on the Cloudsim *** experimental outcome highlighted the efficacy of the ORFO-Tss technique over existing approaches.

关键词： metaheuristics task scheduling cloud computing internet of things makespan red fox optimizer

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Improved soil Quality Prediction model Using Deep Learning for smart Agriculture systems

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Computer systems science & Engineering 2023年第5期45卷 1545-1559页

作者： P.sumathi V.V.Karthikeyan m.s.kavitha s.Karthik Department of Information Technology SNS College of EngineeringCoimbatoreTamilnaduIndia Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia Department of Computer science&Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia

soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all ***,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper *** present decade,the application of deep learning models in many fields of research has created greater *** increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil *** that concern,this paper proposes a novel model called Improved soil Quality Prediction model using Deep Learning(IsQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil ***,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)***,soil nutrient data has been given as second input to the DNNR *** utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been *** training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the *** results show that the proposed model is effective for sQP(soil Quality Prediction model)with efficient good fitting and generality is enhanced with input features with higher rate of classification *** results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

关键词： soil quality classification accuracy deep learning neural network soil features training and testing

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Cooperative Channel and Optimized Route selection in Adhoc Network

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Intelligent Automation & soft Computing 2023年第5期36卷 1547-1560页

作者： D.manohari m.s.kavitha K.Periyakaruppan B.Chellapraba Department of Computer science and Engineering St.Joseph’s Institute of TechnologyChennai600119TamilnaduIndia Department of Computer science&Engineering SNS College of TechnologyCoimbatore641035TamilnaduIndia Department of Computer science&Engineering SNS College of EngineeringCoimbatore641107TamilnaduIndia Department of Information Technology Karpagam Institute of TechnologyCoimbatore641032TamilnaduIndia

Over the last decade,mobile Adhoc networks have expanded dramati-cally in popularity,and their impact on the communication sector on a variety of levels is *** uses have expanded in lockstep with its *** to its instability in usage and the fact that numerous nodes communicate data concur-rently,adequate channel and forwarder selection is *** this proposed design for a Cognitive Radio Cognitive Network(CRCN),we gain the conﬁdence of each forwarding node by contacting one-hop and second level nodes,obtaining reports from them,and selecting the forwarder appropriately with the use of an optimization *** that point,we concentrate our efforts on their channel,selection,and lastly,the transmission of data packets via the designated *** simulation work is validated in this section using the mATLAB ***,steps show how the node acts as a conﬁdent forwarder and shares the channel in a compatible method to communicate,allowing for more packet bits to be transmitted by conveniently picking the channel between *** cal-culate the conﬁdence of the node at the start of the network by combining the reliability report for theﬁrst hop and the reliability report for the secondary *** then refer to the same node as the conﬁdent node in order to operate as a *** a result,we witness an increase in the leftover energy in the *** percentage of data packets delivered has also increased.

关键词： Adhoc Network conﬁdent forwarder one-hop optimized route selection secondary report channel selection

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Automated Red Deer Algorithm with Deep Learning Enabled Hyperspectral Image Classification

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Intelligent Automation & soft Computing 2023年第2期35卷 2353-2366页

Hyperspectral(Hs)image classiﬁcation is a hot research area due to challenging issues such as existence of high dimensionality,restricted training data,*** recognition of features from the Hs images is important for effective classiﬁcation ***,the recent advancements of deep learning(DL)models make it possible in several application *** addition,the performance of the DL models is mainly based on the hyperparameter setting which can be resolved by the design of *** this view,this article develops an automated red deer algorithm with deep learning enabled hyperspec-tral image(HsI)classiﬁcation(RDADL-HIC)*** proposed RDADL-HIC technique aims to effectively determine the HsI *** addition,the RDADL-HIC technique comprises a NAsNetLarge model with Adagrad ***,RDA with gated recurrent unit(GRU)approach is used for the identiﬁcation and classiﬁcation of *** design of Adagrad optimizer with RDA helps to optimally tune the hyperparameters of the NAsNetLarge and GRU models *** experimental results stated the supremacy of the RDADL-HIC model and the results are inspected interms of different *** comparison study of the RDADL-HIC model demonstrated the enhanced per-formance over its recent state of art approaches.

关键词： Hyperspectral images image classiﬁcation deep learning adagrad optimizer nasnetlarge model red deer algorithm

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Impact of Zika virus non-structural protein mutations on hippocampal damage

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Neural Regeneration Research 2025年第8期20卷 2307-2308页

作者： Larissa m.G.Cassiano Roney s.Coimbra Neurogenômica/Imunopatologia Instituto RenéRachouFiocruzBelo HorizonteBrazil Departamento de Bioquímica e Imunologia Instituto de Ciências BiológicasUniversidade Federal de Minas GeraisBelo HorizonteBrazil

The Zika virus(ZIKV),a member of the Flaviviridae family,attracted worldwide attention for its connection to severe neurological effects,notably microcephaly in newborns,first reported during the 2015 epidemic in ***,its impact goes beyond fetal and neonatal abnormalities,also affecting the central nervous system(CNs)in both children and adults,leading to enduring cognitive and behavioral impairments.

关键词： damage fetal neonatal

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Predicting maximum Lifespan Limits at mean menopausal Age

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Journal of mathematical Research with Applications 2025年第1期 133-142页

作者： m.sUmATHI s.ANTONY CARLA Department of mathematics N.M.S.S.Vellaichamy Nadar College Research scholar (Part-time) Madurai Kamaraj University

The age at which a woman enters natural menopause has also been associated to death from any cause. menopause is a natural component of aging that happens between the ages of 45 and 55, with the average menopausal age being 51. Previous research has revealed the age at which women reach menopause, but there is no evidence to support the link between menopause and longevity. We made a study in assessing the limits of maximum lifespan at menopausal age in our previous article. In this paper, we aim to predict the maximum lifespan of women at mean menopausal age.

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Brain-derived neurotrophic factor signaling in the neuromuscular junction during developmental axonal competition and synapse elimination

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Neural Regeneration Research 2025年第2期20卷 394-401页

作者： Josep Tomàs Víctor Cilleros-mañé Laia Just-Borràs marta Balanyà-segura Aleksandra Polishchuk Laura Nadal marta Tomàs Carolina silvera-simón manel m.santafé maria A.Lanuza Unitat d’Histologia i Neurobiologia(UHNeurob) Facultat de Medicina i Ciències de la SalutUniversitat Rovira i VirgiliReusSpain

During the development of the nervous system,there is an overproduction of neurons and *** competition between neighboring nerve endings and synapses performing different activity levels leads to their elimination or *** have extensively studied the involvement of the brain-derived neurotrophic factor-Tropomyosin-related kinase B receptor neurotrophic retrograde pathway,at the neuromuscular junction,in the axonal development and synapse elimination process versus the synapse *** purpose of this review is to describe the neurotrophic influence on developmental synapse elimination,in relation to other molecular pathways that we and others have found to regulate this *** particular,we summarize our published results based on transmitter release analysis and axonal counts to show the different involvement of the presynaptic acetylcholine muscarinic autoreceptors,coupled to downstream serine-threonine protein kinases A and C(PKA and PKC)and voltage-gated calcium channels,at different nerve endings in developmental *** dynamic changes that occur simultaneously in several nerve terminals and synapses converge across a postsynaptic site,influence each other,and require careful studies to individualize the mechanisms of specific *** describe an activity-dependent balance(related to the extent of transmitter release)between the presynaptic muscarinic subtypes and the neurotrophin-mediated TrkB/p75NTR pathways that can influence the timing and fate of the competitive interactions between the different axon *** downstream displacement of the PKA/PKC activity ratio to lower values,both in competing nerve terminals and at postsynaptic sites,plays a relevant role in controlling the elimination of supernumerary ***,calcium entry through L-and P/Q-subtypes of voltage-gated calcium channels(both channels are present,together with the N-type channel in developing nerve terminals)contributes to red

关键词： acetylcholine release adenosine receptors axonal competition brain-derived neurotrophic factor calcium channels motor end-plate muscarinic acetylcholine receptors postnatal synapse elimination serine kinases tropomyosin-related kinase receptorB

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solution‑Processed Thin Film Transparent Photovoltaics:Present Challenges and Future Development

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Nano-micro Letters 2025年第2期17卷 566-600页

作者： Tianle Liu munerah m.s.Almutairi Jie ma Aisling stewart Zhaohui Xing mengxia Liu Bo Hou Yuljae Cho Um-sJTU Joint Institute Shanghai Jiao Tong UniversityShanghai 200240People’s Republic of China school of Physics and Astronomy Cardiff UniversityCardiff CF243AAWalesUK Department of Electrical and Computer Engineering Yale UniversityNew HavenCT 06511USA Energy sciences Institute Yale UniversityWest HavenCT 06516USA Future Photovoltaics Research Center Global Institute of Future TechnologyShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Electrical energy is essential for modern society to sustain economic *** soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar ***,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban *** overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric *** TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar *** this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve *** of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV *** we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic *** applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and ***,current challenges and future opportunities in TPV research are pointed out.

关键词： Transparent semiconductors solution-processable transparent solar cell Emerging solar cell materials Buildingintegrated photovoltaics

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