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Prediction Model Using reinforcement Deep Learning Technique for Osteoarthritis Disease Diagnosis

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Computer Systems Science & Engineering 2022年第7期42卷 257-269页

作者： r.kanthavel r.Dhaya Department of Computer Engineering King Khalid UniversityAbhaSaudi Arabia Department of Computer Science King Khalid University-Sarat Abidha CampusAbhaSaudi Arabia

Osteoarthritis is the most common class of arthritis that involves tears down the soft cartilage between the joints of the *** regeneration of this cartilage tissue is not possible,and thus physicians typically suggest therapeutic measures to prevent further deterioration over ***,bringing about joint replacement is a remedial course of *** itself in joint pain recog-nized with a normal *** learning plays a vital role in predicting the early stages of osteoarthritis by using the MrI pictures of muscles of the knee *** can be used to accurately measure the shape and texture of biological structures can be measured consistently from X-ray ***,deep learning-based computation can be used to design framework to predict whether a given patient will develop *** a framework can identify clear biochemical changes in the focal point of ligaments of the knees of patients who have exhibit pre-indications in standard *** study proposes framework to identify cases of osteoarthritis by using deep learning and reinforcement *** can be used as a clinical mechanism to predict the occurrence of osteoarthritis so that patients can beneﬁt from early intervention.

关键词： Osteoarthritis deeplearning reinforcementlearning arthritis early detection trainingandframework

Detection of Osteoarthritis Based on EHO Thresholding

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Computers, Materials & Continua 2022年第6期71卷 5783-5798页

作者： r.kanthavel r.Dhaya Kanagaraj Venusamy Department of Computer Engineering King Khalid UniversityAbhaSaudi Arabia Department of Computer Science King Khalid UniversitySarat Abidha CampusAbhaSaudi Arabia Department of Engineering University of Technology and Applied SciencesAl MussanahSultanate of Oman

Knee Osteoarthritis(OA)is a joint disease that is commonly observed in people around the *** commonly affects patients who are obese and those above the age of 60.A valid knee image was generated by Computed Tomography(CT).In this work,efficient segmentation of CT images using Elephant Herding Optimization(EHO)optimization is *** initial stage employs,the CT image normalization and the normalized image is incited to image enhancement through histogram ***,the enhanced image is segmented by utilizing Niblack and Bernsen ***(EHO)optimized outcome is evaluated in two *** initial step includes image enhancement with the measure of Mean square error(MSE),Peak signal to noise ratio(PSNr)and Structural similarity index(SSIM).The following step includes the segmentation which includes the measure ofAccuracy,Sensitivity and *** comparative analysis of EHO provides 95%of accuracy,94%of specificity and 93%of sensitivity than that of Active contour and Otsu threshold.

关键词： Osteoarthritis CT images correlation histogram thresholding Niblack&Bernsen algorithm EH optimization

Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of Sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree regression(DTr),and Gaussian Process regression(GPr)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPr method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

Developing Dijik-Primbert Algorithm for Finding Unpredictable Paths over Time-Varying Networks

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Circuits and Systems 2016年第11期7卷 3541-3555页

作者： P. Sushmitha r. kanthavel Velammal Engineering College Chennai India

Cooperation among multiple unmanned vehicles is an intensely challenging topic from a theoretical and practical standpoint, with far reaching indications in scientific and commercial mission scenarios. The difficulty of time coordination for a rapid of multirotor UAVs includes predefined spatial paths according to mission necessities. With the solution proposed, cooperative control is accomplished in the presence of time-varying communication networks, as well as stringent temporal constraints, such as concurrent arrival at the desired final locations. The proposed explanation solves the time-coordination problem under the acceptance that the trajectory-genera- tion and the path-following algorithms meeting convinced cohesion conditions are given. Communication is processed in unpredictable paths by the use of path following and directed communication graph. Dijik-Primbert algorithm for finding the shortest collision free paths is used to avoid and detect collision/congestion in unpredictable paths. Without collision detection, it doesn’t seem agreeable to have collision avoidance because there wouldn’t be everything to avoid. Dijikloyd algorithm is used for finding shortest paths in a weighted directed graph with positive and negative edges. Primloyd algorithm is used for finding shortest paths in a weighted undirected graph for conquering the complexity in matrix coding. In case of conges- tion or collision then the whole network is learned about it to all the communica- tors. Hence, communication is taken place in an unpredictable path in a secured manner.

关键词： Multirotor Spacecraft Formation Flying UAV Control Collision Avoidance

Emerging potential of progranulin-dependent SorCS2 signaling in healthy and diseased nervous systems

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Neural regeneration research 2025年第9期20卷 2591-2593页

作者： Alena Salasova Anders Nykjær Danish research Institute of Translational Neuroscience DANDrITE-Nordic EMBL Partnership for Molecular Medicine and Centre of Excellence PROMEMODepartment of BiomedicineAarhus UniversityAarhusDenmark

The formation of the mammalian nervous system and its maturation into sensory,motor,cognitive,and behavioral circuits is a complex process that begins during early embryogenesis and lasts until young *** neurodevelopm... 详细信息

关键词： progr jointly CS2

Power Analysis of Sensor Node Using Simulation Tool

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Circuits and Systems 2016年第13期7卷 4236-4247页

作者： r. Sittalatchoumy r. kanthavel r. Seetharaman Department of Electronics and Communication Engineering Anna University Chennai India Department of Electronics and Communication Engineering Velammal Engineering College Chennai India

Power consumption of sensor node is analyzed in this paper. In order to analyze the energy consumption, the node model is simulated using Proteus Software tool. The proposed sensor node’s power characteristics are measured by using different combinations of microprocessors and sensors. Using this, the energy consumption of the node is calculated. This is a cost-effective method and provides appropriate power model for specific applications.

关键词： Wireless Sensor Networks Microcontroller Lifetime Differential Encoding

A comprehensive investigation on nonlinear vibration and bending characteristics of bio-inspired helicoidal laminated composite structures

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 81-100页

作者： S.SAUrABH r.KIrAN D.SINGH r.VAISH V.S.CHAUHAN School of Mechanical and Materials Engineering Indian Institute of Technology Mandi

Bio-inspired helicoidal composite laminates, inspired by the intricate helical structures found in nature, present a promising frontier for enhancing the mechanical properties of structural designs. Hence, this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates. The inverse hyperbolic shear deformation theory(IHSDT) of plates is employed to characterize the displacement field, with the incorporation of Green-Lagrange nonlinearity. The problem is modeled using the C0finite element method(FEM), and an in-house code is developed in the MATLAB environment to solve it numerically. Various helicoidal layup configurations including helicoidal recursive(Hr), helicoidal exponential(HE), helicoidal semi-circular(HS), linear helicoidal(LH), and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied. The model is validated, and parametric studies are conducted. These studies investigate the effects of layup configurations, side-to-thickness ratio, modulus ratios, boundary conditions, and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates. The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors. Moreover, this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.

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Antisense oligonucleotides provide optimism to the therapeutic landscape for tauopathies

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Neural regeneration research 2025年第3期20卷 803-804页

作者： Glenn A.Harris Lauren r.Hirschfeld rainwater Charitable Foundation Fort WorthTXUSA

Tauopathies are a group of neurodegenerative diseases characterized by abnormal metabolism of the misfolded tau protein. Tau is encoded by the microtubule-associated protein tau gene(MAPT) and can be classified as either 3-repeat(3r) or 4-repeat(4r) based on the number of repeat domains from alternative splicing of exon 10 of the MAPT gene.

关键词： tau metabolism diseases

Effect of Bio-filler on Hybrid Sisal-Banana-Kenaf-Flax Based Epoxy Composites:A Statistical Correlation on Flexural Strength

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Journal of Bionic Engineering 2020年第6期17卷 1263-1271页

作者： Somasundaram Vivek Karuppusamy Kanthave Arun Torris Vijayananth Kavimani Department of Mechanical Engineering Anna University Regional CampusCoimbatore 641046Tamil NaduIndia Polymer Science and Engineering Division CSIR-National Chemical LaboratoryDr.Homi Bhabha RoadPune411008MaharashtraIndia Department of Mechanical Engineering Karpagam Academy of Higher EducationCoimbatore 641021Tamil NaduIndia

This work deals with the investigation of the synergistic effect of bagasse ash with sisal-banana-kenaf-flax fibers reinforced epoxy composite for their flexural *** composites with three combinations of hybrid fibers ***/kenaf(HSK),banana/kenaf(HBK),and banana/flax(HBF)with bagasse ash(BGA)as filler material are fabricated using vacuum bag assisted resin transfer *** were conducted based on L27 orthogonal array to understand the influence of control factor *** volume,alkali concentration&BGA over output response.A'-ray micro computed tomography analysis was conducted over the developed sample to infer the uniform dispersion of fiber and filler *** experimental results reveal that the addition of fiber up to 30 vol%depicts better strength and further addition results in a negative *** in order of BGA decreases the flexural strength of the developed composites.

关键词： bagasse ash natural fiber flexural strength X-ray micro computed tomography vacuum bag assisted resin transfer molding