检索结果-南通市图书馆

Networking Controller Based Real time traffic Prediction in Clustered Vehicular Adhoc Networks

Intelligent Automation & soft Computing 2023年第2期35卷 2189-2203页

作者： t.s.balaji s.srinivasan saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electronics and Communication Engineering College of Engineering and TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Department of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India

the vehicular ad hoc network(VANEt)is an emerging network tech-nology that has gained popularity because to its low cost,ﬂexibility,and seamless *** deﬁned networking(sDN)technology plays a critical role in network administration in the future generation of VANEt withﬁfth generation(5G)*** of the beneﬁts of VANEt,energy economy and trafﬁc control are signiﬁcant architectural *** and real-time trafﬁcﬂow prediction(tFP)becomes critical for managing trafﬁc effectively in the *** controllers are a critical issue in VANEt,which has garnered much interest in recent *** this objective,this study develops the sDNtFP-C technique,a revolutionary sDN controller-based real-time trafﬁcﬂow forecasting technique for clustered *** proposed sDNtFP-C technique combines the sDN controller’s scalability,ﬂexibility,and adaptability with deep learning(DL)***,a novel arithmetic optimization-based clustering technique(AOCA)is developed to cluster automobiles in a *** tFP procedure is then performed using a hybrid convolutional neural network model with atten-tion-based bidirectional long short-term memory(HCNN-ABLstM).to optimise the performance of the HCNN-ABLstM model,the dingo optimization techni-que was used to tune the hyperparameters(DOA).the experimental results ana-lysis reveals that the suggested method outperforms other current techniques on a variety of evaluation metrics.

关键词： VANEt trafﬁcﬂow prediction clustering metaheuristics sDN controller deep learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Fuzzy-Based secure Clustering with Routing technique for VANEts

引用

Computer systems science & Engineering 2022年第10期43卷 291-304页

作者： t.s.balaji s.srinivasan s.Prasanna Bharathi B.Ramesh saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Electronics and Communication Engineering College of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Electronics and Communication Engineering SRM Institute of Science and Technology600026ChennaiIndia Department of Civil Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India

Due to the advanced developments in communication technologies,Internet of vehicles and vehicular adhoc networks(VANEt)offers numerous opportunities for effectively managing transportation *** the other,the cloud environment needs to disseminate the emergency message to the vehicles which are consistently distributed on the roadway so that every vehicle gets the messages from closer vehicles in a straightforward *** resolve this issue,clustering and routing techniques can be designed using computational intelligence *** this motivation,this paper presents a new type-2 fuzzy sets based clustering with metaheuristic optimization based routing(t2FsCMOR)technique for secure communication in *** t2FsC-MOR technique aims to elect CHs and optimal routes for secure intercluster data transmission in *** proposed model involves t2FsC technique for the selection of CHs and construction of *** t2FsC technique uses different parameters namely traveling speed(ts),link quality(LQ),trust factor(tF),inter-vehicle distance(IVD),and neighboring node count(NCC).the inclusion of trust factor helps to select the proper cluster heads(CHs)for secure data dissemination ***,trust aware seagull optimization based routing(tAsGOR)approach was derived for the optimal selection of routes in *** order to validate the enhanced performance of proposed technique,the set of simulations take place and the outcomes are examined interms of different *** experimental outcomes highlighted the improved performance of the proposed model over the other state of art techniques with a higher throughput of 98%.

关键词： VANEt security clustering routing fuzzy logic systems metaheuristic algorithms

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Deep Learning Based Multi-Retinal Disease Diagnosis and Classification Framework

引用

Computers, Materials & Continua 2022年第12期73卷 5543-5557页

作者： thavavel Vaiyapuri s.srinivasan Mohamed Yacin sikkandar t.s.balaji seifedine Kadry Maytham N.Meqdad Yunyoung Nam College of Computer Engineering and sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105India Department of Medical Equipment technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesChennai602105India Department of Electronics and Communication Engineering College of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Department of Applied Data science Noroff University CollegeKristiansand4608Norway Department of Computer techniques Engineering Al-Mustaqbal University CollegeHillahBabil51001Iraq Department of Computer science and Engineering Soonchunhyang UniversityAsan31538Korea

In past decades,retinal diseases have become more common and affect people of all age grounds over the *** examining retinal eye disease,an artificial intelligence(AI)based multilabel classification model is needed for automated *** analyze the retinal malady,the system proposes a multiclass and multi-label arrangement ***,the classification frameworks based on features are explicitly described by ophthalmologists under the application of domain knowledge,which tends to be time-consuming,vulnerable generalization ability,and unfeasible in massive ***,the automated diagnosis of multi-retinal diseases becomes essential,which can be solved by the deep learning(DL)*** this motivation,this paper presents an intelligent deep learningbased multi-retinal disease diagnosis(IDL-MRDD)framework using fundus *** proposed model aims to classify the color fundus images into different classes namely AMD,DR,Glaucoma,Hypertensive Retinopathy,Normal,Others,and Pathological ***,the artificial flora algorithm with shannon’s function(AFA-sF)basedmulti-level thresholding technique is employed for image segmentation and thereby the infected regions can be properly *** addition,squeezeNet based feature extractor is employed to generate a collection of feature ***,the stacked sparse Autoencoder(ssAE)model is applied as a classifier to distinguish the input images into distinct retinal *** efficacy of the IDL-MRDD technique is carried out on a benchmark multi-retinal disease dataset,comprising data instances from different *** experimental values pointed out the superior outcome over the existing techniques with the maximum accuracy of 0.963.

关键词： Multi-retinal disease computer aided diagnosis fundus images deep learning segmentation intelligent models

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Improving Power Quality by DstAtCOM Based DQ theory with soft Computing techniques

引用

Intelligent Automation & soft Computing 2023年第5期36卷 1315-1329页

作者： V.Nandagopal t.s.balaji Damodhar P.Vijayapriya A.thamilmaran Department of Electrical and Electronics Engineering Adhi College of Engineering and TechnologyKanchipuramTamil NaduIndia Department of Electrical&Electronics Engineering Madanapalle Institute of Technology and ScienceMadanapalleAndhra PradeshIndia school of Electrical Engineering Vellore Institute of TechnologyVelloreTamil NaduIndia

the development of non-linear loads at consumers has signiﬁcantly impacted power supply ***,the poor power quality has been found in the three-phase distribution system due to unbalanced loads,harmonic current,undesired voltage regulation,and extreme reactive power *** overcome this issue,Distributed stAticCOMpensator(DstAtCOM)is *** is a shunt-connected Voltage source Converter(VsC)that has been utilized in distribution networks to balance the bus voltage in terms of enhancing reactive power control and power *** can provide both rapid and continuous capacitive and inductive mode compensation.A rectiﬁed resistive and inductive load eliminates current harmonics in a three-phase power *** synchronous fundamental DQ frame is a time-domain approach developed from three-phase system space vector transformations has been designed using MAtLAB/*** DQ theory is used to produce the reference signal for the Pulse Width Modulation(PWM)*** addition,a traditional Propor-tional Integral Derivative(PID)controller is designed and compared with pro-posed soft computing approaches such as Fuzzy–PID and Artiﬁcial Neural Network(ANN-PID)and compared accurate reference current determination for Direct Current(DC)bus through DC *** Analytical explores the pro-posed control strategies given to establish superior ***,total harmo-nic distortion analysis should be taken for performance analysis of the proposed system with IEEE standards.

关键词： DstAtCOM synchronous reference frame fuzzy-PID artiﬁcial neural network-PID power quality issues

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Optimal Deep Learning Enabled statistical Analysis Model for traffic Prediction

引用

Computers, Materials & Continua 2022年第9期72卷 5563-5576页

作者： Ashit Kumar Dutta s.srinivasan s.N.Kumar t.s.balaji Won Il Lee Gyanendra Prasad Joshi sung Won Kim Department of Computer science and Information systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electrical&Electronics Engineering Amal Jyothi College of EngineeringKanjirappallyKerala686518India saveetha school of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electronics and Communication Engineering College of Engineering and TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Department of Business Administration Hanbat National National UniversityDaejeon34158Korea Department of Computer science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Due to the advances of intelligent transportation system(Itss),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different Itss namely traffic signal control,navigation,route mapping,*** traffic prediction model aims to predict the traffic conditions based on the past traffic *** more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis *** study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALstM)model for traffic *** proposed OCNN-ALstM technique primarily preprocesses the traffic data by the use of min-max normalization ***,OCNN-ALstM technique was executed for classifying and predicting the traffic data in real time *** enhancing the predictive outcomes of the OCNN-ALstM technique,the bird swarm algorithm(BsA)is employed to it and thereby overall efficacy of the network gets *** design of BsA for optimal hyperparameter tuning of the CNN-ALstM model shows the novelty of the *** experimental validation of the OCNNALstM technique is performed using benchmark datasets and the results are examined under several *** simulation results reported the enhanced outcomes of the OCNN-ALstM model over the recent methods under several dimensions.

关键词： statistical analysis predictive models deep learning traffic prediction bird swarm algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Beyond statistical significance:Embracing minimal clinically important difference for better patient care

引用

World Journal of Methodology 2025年第1期15卷 33-41页

作者： Naveen Jeyaraman Madhan Jeyaraman swaminathan Ramasubramanian sangeetha balaji sathish Muthu Department of Orthopaedics ACS Medical College and HospitalDr MGR Educational and Research InstituteChennai 600077Tamil NaduIndia Department of Research Methods Orthopaedic Research GroupCoimbatore 641045Tamil NaduIndia Department of Orthopaedics Government Medical CollegeOmandurar Government EstateChennai 600002Tamil NaduIndia Department of Biotechnology Faculty of EngineeringKarpagam Academy of Higher EducationCoimbatore 641021Tamil NaduIndia Department of Orthopaedics Government Medical CollegeKarur 639004Tamil NaduIndia

the minimal clinically important difference(MCID)represents a pivotal metric in bridging the gap between statistical significance and clinical relevance,addressing the direct impact of medical interventions from the patient's *** comprehensive review analyzes the evolution,applications,and challenges of MCID across medical specialties,emphasizing its necessity in ensuring that clinical outcomes not only demonstrate statistical significance but also offer genuine clinical utility that aligns with patient expectations and *** discuss the evolution of MCID since its inception in the 1980s,its current applications across various medical specialties,and the methodologies used in its calculation,highlighting both anchor-based and distribution-based ***,the paper delves into the challenges associated with the application of MCID,such as methodological variability and the interpretation difficulties that arise in clinical *** for the future include standardizing MCID calculation methods,enhancing patient involvement in setting MCID thresholds,and extending research to incorporate diverse global *** steps are critical to refining the role of MCID in patient-centered healthcare,addressing existing gaps in methodology and interpretation,and ensuring that medical interventions lead to significant,patient-perceived improvements.

关键词： Minimal clinically important difference Patient-centered care Clinical relevance Global health

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Free vibration and transient response of double curved beams connected by intermediate straight beams

引用

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 37-62页

作者： R.A.JAFARI-tALOOKOLAEI H.GHANDVAR E.JUMAEV s.KHAtIR t.CUONG-LE school of Mechanical Engineering Babol Noshirvani University of Technology Department of Mechanical Engineering Faculty of Engineering New Uzbekistan University University of Business and science Center for Engineering Application and technology solutions Ho Chi Minh City Open University

this paper investigates the free vibration and transient response of interconnected structures including double curved beams and intermediate straight beams,which are all constructed from functionally graded porous(FGP) materials. the strain potential and kinetic energies of each beam along with the work done by the external force are calculated. Additionally, a higher-order beam element is introduced to derive stiffness and mass matrices, along with the force vector. the curved and straight beams are discretized, and their assembled stiffness, mass matrices, and force vectors, are *** conditions at the joints are used to derive the total matrices of the entire structure. subsequently, the natural frequencies and transient response of the system are determined. the accuracy of the mathematical model and the self-developed computer program is validated through the comparison of the obtained results with those of the existing literature and commercial software ANsYs, demonstrating excellent ***, a comprehensive study is conducted to investigate the effects of various parameters on the free vibration and transient response of the considered structure.

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Acute pancreatitis in pregnancy

引用

World Journal of Gastroenterology 2009年第45期15卷 5641-5646页

作者： Capecomorin s Pitchumoni balaji Yegneswaran Drexel University College of Medicine and Robert Wood Johnson Medical school New BrunswickNJ 08901 United States Department of Gastroenterology Saint Peter's University Hospital New BrunswickNJ 08901 United States Drexel University College of Medicine saint Peter's University Hospital New BrunswickNJ 08901 United States

Acute pancreatitis (AP) is a rare event in pregnancy, occurring in approximately 3 in 10 000 pregnancies. the spectrum of AP in pregnancy ranges from mild pancreatitis to serious pancreatitis associated with necrosis, abscesses, pseudocysts and multiple organ dysfunction syndromes. Pregnancy related hematological and biochemical alterations infl uence the interpretation of diagnostic tests and assessment of severity of AP. As in any other disease associated with pregnancy, AP is associated with greater concerns as it deals with two lives rather than just one as in the non-pregnant population. the recent advances in clinical gastroenterology have improved the early diagnosis and effective management of biliary pancreatitis. Diagnostic studies such as endoscopic ultrasound, magnetic resonance cholangiopancreatography and endoscopic retrograde cholangiopancreatography and therapeutic modalities that include endoscopic sphincterotomy, biliary stenting, common bile duct stone extraction and laparoscopic cholecystectomy are major milestones in gastroenterology. When properly managed AP in pregnancy does not carry a dismal prognosis as in the past.

关键词： Acute pancreatitis Pregnancy Pancreatitis in pregnancy

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy Prediction in Iot systems Using Machine Learning Models

引用

Computers, Materials & Continua 2023年第4期75卷 443-459页

作者： s.balaji s.Karthik Department of ECE SRM Institute of Science and TechnologyVadapalani CampusNo1 Jawaharlal Nehru RoadVadapalani600026TNIndia

the Internet of things (Iot) technology has been developed fordirecting and maintaining the atmosphere in smart buildings in real time. Inorder to optimise the power generation sector and schedule routine maintenance,it is crucial to predict future energy demand. Electricity demandforecasting is difficult because of the complexity of the available demandpatterns. Establishing a perfect prediction of energy consumption at thebuilding’s level is vital and significant to efficiently managing the consumedenergy by utilising a strong predictive model. Low forecast accuracy is justone of the reasons why energy consumption and prediction models havefailed to advance. therefore, the purpose of this study is to create an Iotbasedenergy prediction (Iot-EP) model that can reliably estimate the energyconsumption of smart buildings. A real-world test case on power predictionsis conducted on a local electricity grid to test the practicality of the *** proposed (Iot-EP) model selects the significant features as input neurons,the predictable data is selected as output nodes, and a multi-layer perceptronis constructed along with the features of the Convolution Neural Network(CNN) algorithm. the analysis of the proposed Iot-EP model has higheraccuracy of 90%, correlation of 89%, and variance of 16% in less training timeof 29.2 s, and with a higher prediction speed of 396 (observation/sec). Whencompared to existing models, the results showed that the proposed (Iot-EP)model outperforms with a satisfactory level of accuracy in predicting energyconsumption in smart buildings.

关键词： Machine learning wireless networks internet of things energy prediction

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Conceptual comparison of metabolic pathways with electronic circuits

引用

Journal of Bionic Engineering 2004年第3期1卷 175-182页

作者： s. balaji s. Lakshminarayanan Lecturer-Bioinformatics School of Chemical and Biotechnology SASTRA Deemed UniversityThanjavur Tamilnadu IndiaM.Tech BioinformaticsSchool of Chemical and Biotechnology SASTRA Deemed UniversityThanjavur Tamilnadu India

An electronic circuit has been designed to mimic glycolysis, the Citric Acid (tCA) cycle and the electron transport chain. Enzymes play a vital role in metabolic pathways; similarly transistors play a vital role in electronic circuits; the characteristics of enzymes in comparison with those of transistors suggests that the properties are analagous. Enzymes possess an active site into which the substrate binds, similarly the transistor possess a layer in which the recombination of holes and electrons takes place. Hence the applied voltage in the circuit is considered as the substrate. the enthalpy values of the enzymes are converted into volts, which is to be applied to the circuit. AtP is the energy source in the metabolic pathway which functions like a potential in the electronic circuit. some enzymes can function only with the help of a cofactor; here modelled as a switch. Using all the above electronic circuit analogues, which possess the similar characteristics of the metabolic pathway constituents, circuits have been designed.

关键词： metabolic circuit molecular biomimetics enzyme transistor

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：