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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

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Fuzzy-Based secure Clustering with Routing technique for VANEts

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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

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

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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

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

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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

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Optimal Deep Learning Enabled statistical Analysis Model for traffic Prediction

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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

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

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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

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the impact of alpha-fetoprotein(AFP),child-turcotte-pugh(CtP)score and disease staging on the survival of hepatocellular carcinoma(HCC)patients:a retrospective cohort from single oncology center

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Oncology Research 2025年第1期33卷 149-160页

作者： NAssER MULLA YOUsEF KAtIB AsIM M.ALMUGHAMsI DUAA s.ALKHAYAt MOHAMED MOsAAD sAMIR t.ALFOtIH RAWAN ALAOFI Department of Internal Medicine Faculty of MedicineTaibah UniversityMadinah42278Saudi Arabia Department of Radiology Faculty of MedicineTaibah UniversityMadinah42278Saudi Arabia Department of surgery Faculty of MedicineTaibah UniversityMadinah42278Saudi Arabia Department of Endemic and Infectious Diseases Suez Canal UniversityIsmailia41522Egypt King salman bin Abdulaziz Medical City Madinah42311Saudi Arabia Prince Mohammed Bin Abdulaziz Hospital Madinah41511Saudi Arabia

Background:Hepatocellular carcinoma(HCC)is the most common cause of cancer-related death in saudi *** study aimed to investigate the patterns of HCC and the effect of tNM staging,Alfa-fetoprotein(AFP),and Child-turcotte Pugh(CtP)on patients’overall survival(Os).Methods:A retrospective analysis was conducted on 43 HCC patients at a single oncology center in saudi Arabia from 2015 to *** patients had to fulfill one of the following criteria:(a)a liver lesion reported as definitive HCC on dynamic imaging and/or(b)a biopsy-confirmed ***:the mean patient age of all HCC cases was 66.8 with a male-to-female ratio of 3.3:*** patients were stratified into two groups:viral HCC(n=22,51%)and non-viral HCC(n=21,49%).Among viral-HCC patients,55%were due to HBV and 45%due to *** was diagnosed in 79%of *** and sex did not significantly statistically differ in Os among viral and non-viral HCC patients(p-value>0.05).About 65%of patients had tumor size>5 cm during the diagnosis,with a significant statistical difference in Os(p-value=0.027).AFP was>400 ng/ml in 45%of the *** was a statistically significant difference in the Os in terms of AFP levels(p-value=0.021).A statistically significant difference was also observed between the CtP score and Os(p-value=0.02).CtP class B had the longest *** was the most common treatment provided to HCC patients followed by sorafenib *** was a significant statistical difference in Os among viral and non-viral HCC patients(p-value=0.008).Conclusions:the most common predictors for Os were the underlying cause of HCC,AFP,and tumor *** having non-viral etiology,a tumor size>5 cm,an AFP>400 ng/mL,and a CtP score class C were all negatively associated with Os.

关键词： Hepatocellular carcinoma Pattern Alpha-fetoprotein(AFP) Child-turcotte-pugh Progression free survival

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

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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： Kinetic energy

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Acute pancreatitis in pregnancy

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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

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Defensive nature of sargassum polycystum (Brown alga) against acetaminophen-induced toxic hepatitis in rats: Role of drug metabolizing microsomal enzyme system, tumor necrosis factor-a and fate of liver cell structural integrity

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World Journal of Gastroenterology 2006年第24期12卷 3829-3834页

作者： H balaji raghavendran A sathivel t Devaki Department of Biochemistry University of Madras Guindy campusChennai-25India

AIM： to assess the defensive nature of sargassum polycystum （s. polycystum）（Brown alga） against acetaminophen （AAP）-induced changes in drug metabolizing microsomal enzyme system, tumor necrosis factor （tNF-α） and fine structural features of the liver during toxic hepatitis in rats. MEtHODs： Male albino Wistar strain rats used for the study were randomly categorized into 4 groups. Group Ⅰ consisted of normal control rats fed with standard diet. Group II rats were administered with acetaminophen （800 mg/kg body weight, intraperitoneally）. Group Ⅲ rats were pre-treated with s. polycystum extract alone. Group IV rats were orally pre-treated with s. polycystum extract （200 mg/kg body weight for 21 d） prior to acetaminophen induction （800 mg/kg body weight, intraperitoneally）. serum separated and liver was excised and microsomal fraction was isolated for assaying cytochrome P450, NADPH Cyt P450 reductase and bs. serum tNF-α was detected using ELIsA. Fine structural features of liver were examined by transmission electron microscopy. REsULts： Rats intoxicated with acetaminophen showed considerable impairment in the activities of drug metabolizing microsomal enzymes, such as cytochrome P450, NADPH Cyt P450 reductase and bs when compared with the control rats. the rats intoxicated with acetaminophen also significantly triggered serum tNF-a when compared with the control rats. these severe alterations in the drug metabolizing enzymes were appreciably pretreated with s. polycystum. prevented in the rats the rats pretreated withs. polycystum showed considerable inhibition in the elevation of tNF-α compared to the rats intoxicated with acetaminophen. the electron microscopic observation showed considerable loss of structural integrity of the endoplasmic reticulum, lipid infiltration and ballooning of mitochondria in the acetaminophen-intoxicated rats, whereas the rats treated with s. polycystum showed considerable protection against acetaminophen-induced alterations in structur

关键词： sargassum polycystum Acetaminophen toxic hepatitis NAPQI Free radical

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