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predictive active control of building structures using LQR and artificial intelligence

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 489-502页

作者： Nirmal S.mehta Vishisht Bhaiya K.A.patel Ehsan Noroozinejad Farsangi Department of Civil Engineering SVNIT SuratGujarat 395007India Urban Transformations Research Centre Western Sydney UniversityNSWAustralia

This study presents a neural network-based model for predicting linear quadratic regulator(LQR)weighting matrices for achieving a target response *** on the expected weighting matrices,the LQR algorithm is used to determine the various responses of the *** responses are determined by numerically analyzing the governing equation of motion using the state-space *** training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQR weighting *** study the effectiveness of an LQR-based neural network(LQRNN),the actual percentage reduction in the responses obtained from using LQRNN is compared with the target percentage ***,to investigate the efficacy of an active control system using LQRNN,the controlled responses of a system are compared to the corresponding uncontrolled *** trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage *** on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using ***,the LQRNN algorithm can replace conventional LQR control with the use of an active control system.

关键词： active control system linear quadratic regulator artificial neural networks state-space approach response effectiveness factor resilience

pr(Ⅲ) and Nd(Ⅲ) Absorption Spectroscopic probe to Investigate Interaction with Lysozyme (HEW)

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Journal of Rare Earths 2006年第6期24卷 648-652页

作者： Jignasu p.mehta prashant N.Bhatt Sudhindra N. Misra Department of Chemistry Bhavnagar UniversityBhavnagar-364002India

pr（ Ⅲ ） and Nd（ Ⅲ ） can be utilized as absorption spectroscopic probes to investigate the interaction of biomolecules like Lysozyme （HEW） with Ca（ Ⅱ ） in-vitro ; the most abundant metal ion in the human body system. The spectroscopic techniques involving comparative absorption, absorption difference, and quantitative intensity analysis using 4f-4f transitions are utilized for changes in the inner sphere coordination pattern of pr（ Ⅲ ） and Nd（Ⅲ ） in solution as well as in solid state. The present study deals with an important biomolecule in human metabolism, that is, Lysozyme （HEW）. The absorption er-Condon the probab spectral parameters such as the oscillator strength （p）, the Judd-Ofelt （Tλ） intensity parameters, and the Slatinter electronic parameters are calculated using chi square methods. The obtained results are used to determine le geometry of the complex in the solution, the nature of the bond between pr（Ⅲ）/Nd（Ⅲ） with lysozyme, and the inner sphere coordination environment of f-f transitions. The results obtained from various experimental conditions are utilized to investigate the coordination changes in the pr（Ⅲ）/Nd（Ⅲ） complexes caused by different coordinating sites of lysozyme, normalized bite, denticity, the solvent nature, the coordination number, the nature of bond and other parameters to mimic the interaction of the Ca（ Ⅱ ） ion with such biomolecule.

关键词： absorption spectra pr(Ⅲ), Nd(Ⅲ) Lysozyme (HEW) spectral parameters rare earths

Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1051-1070页

作者： p.S.REDDY p.SREEDEVI Department of Mathematics Rajeev Gandhi Memorial College of Engineering and TechnologyNandyal 518501India

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEpCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing *** effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEpCMs,ranging from 2%to 6%,the Stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity ***,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented *** results indicate that the time taken by the NEpCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf ***,the contours of the heat capacity ratio Cr decrease with the increase in the Stefan number Ste.

关键词： volume fraction of nano-encapsulated phase change material(NEpCM) radiation Stefan number heat capacity ratio entropy generation

A Hybrid Optimization Approach of Single point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with principal Component Analysiss

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Journal of Wuhan University of Technology(Materials Science) 2024年第1期39卷 160-166页

作者： A Visagan p Ganesh Department of production Technology Madras Institute of TechnologyChennai-600044India

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with principal Component Analysis(pCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with pCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

关键词： single point incremental forming AISI 316L taguchi grey relation analysis principal component analysis surface roughness scanning electron microscopy

Role of lymphocyte-to-monocyte ratio as a predictive marker for diabetic coronary artery disease: A cross-sectional study

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World Journal of Methodology 2024年第3期14卷 48-54页

作者： pradeep Kumar Dabla Dharmsheel Shrivastav pratishtha Mehra Vimal mehta Department of Biochemistry Govind Ballabh Pant Institute of Postgraduate Medical Education and ResearchDelhi 110002India Department of Biochemistry Govind Ballabh Pant Institute of Post Graduate and Medical ResearchDelhi 110002India Department of Cardiology Govind Ballabh Pant Institute of Postgraduate Medical Education and ResearchDelhi 110002India

BACKGROUND The lymphocyte to monocyte ratio(LMR)is considered a marker of systemic inflammation in cardiovascular disease and acts as predictor of mortality in coronary artery *** To investigate the predictive role of LMR in diabetic coronary artery disease *** This cross-sectional study was conducted at tertiary care super-specialty hospital at New Delhi,India.A total of 200 angiography-proven coronary artery disease(CAD)patients were enrolled and grouped into two categories:Group I[CAD patients with type 2 diabetes mellitus(T2DM)and glycated hemoglobin(HbA1c)levels≥6.5%],and Group II(CAD patients without T2DM and HbA1c levelspoproteins,HbA1c,and complete blood count of enrolled patients were analyzed using fully automatic *** The logistic regression analysis showed an odds ratio of 1.48(95%CI:1.28-1.72,ppatients(Group I)in unadjusted *** adjusting for age,gender,diet,smoking,and hypertension history,the odds ratio increased to 1.49(95%CI:1.29-1.74,ppperating characteristic curve analysis revealed 74%sensitivity,64%specificity,and 0.74 area under the curve(95%CI:0.67-0.80,ppredictive accuracy for diabetic CAD *** LMR showed positive association with diabetic coronary artery disease,with moderate predictive *** findings have implications for improving CAD management in diabetics,necessitating further research and targeted interventions.

关键词： Coronary artery disease Type 2 diabetes mellitus HbA1c Lymphocyte to monocyte ratio Lymphocyte to monocyte ratio

Discovering hidden patterns:Association rules for cardiovascular diseases in type 2 diabetes mellitus

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World Journal of Methodology 2024年第2期14卷 97-106页

作者： pradeep Kumar Dabla Kamal Upreti Dharmsheel Shrivastav Vimal mehta Divakar Singh Department of Biochemistry Govind Ballabh Pant Institute of Postgraduate Medical Education and ResearchDelhi 110002India Department of Computer Science CHRISTGhaziabad 201003India Department of Cardiology Govind Ballabh Pant Institute of Postgraduate Medical Education and ResearchDelhi 110002India Barkatullah University Institute of Technology Barkatullah UniversityBhopal 462026India

BACKGROUND It is increasingly common to find patients affected by a combination of type 2 diabetes mellitus(T2DM)and coronary artery disease(CAD),and studies are able to correlate their relationships with available biological and clinical *** aim of the current study was to apply association rule mining(ARM)to discover whether there are consistent patterns of clinical features relevant to these *** leverages clinical and laboratory data to the meaningful patterns for diabetic CAD by harnessing the power help of data-driven algorithms to optimise the decision-making in patient *** To reinforce the evidence of the T2DM-CAD interplay and demonstrate the ability of ARM to provide new insights into multivariate pattern *** This cross-sectional study was conducted at the Department of Biochemistry in a specialized tertiary care centre in Delhi,involving a total of 300 consented subjects categorized into three groups:CAD with diabetes,CAD without diabetes,and healthy controls,with 100 subjects in each *** participants were enrolled from the Cardiology IpD&OpD for the sample *** study employed ARM technique to extract the meaningful patterns and relationships from the clinical data with its original *** The clinical dataset comprised 35 attributes from enrolled *** analysis produced rules with a maximum branching factor of 4 and a rule length of 5,necessitating a 1%probability increase for *** patterns emerged,highlighting strong links between health indicators and diabetes likelihood,particularly elevated HbA1C and random blood sugar *** ARM technique identified individuals with a random blood sugar level>175 and HbA1C>6.6 are likely in the“CAD-with-diabetes”group,offering valuable insights into health indicators and influencing factors on disease *** The application of this method holds promise for healthcare practitioners to offer valuable insights for enhanc

关键词： Coronary artery disease Type 2 diabetes mellitus Coronary angiography Association rule mining Artificial intelligence

On the functions of astrocyte-mediated neuronal slow inward currents

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Neural Regeneration Research 2024年第12期19卷 2602-2612页

作者： Balázs pál Department of physiology Faculty of MedicineUniversity of DebrecenDebrecenHungary

Slow inward currents are known as neuronal excitatory currents mediated by glutamate release and activation of neuronal extra synaptic N-met hyl-D-aspartate receptors with the contribution of *** events are significantly slower than the excitatory postsynaptic *** of slow inward currents are determined by seve ral factors including the mechanisms of astrocytic activation and glutamate release,as well as the diffusion pathways from the release site towards the extra synaptic recepto *** are stimulated by neuronal network activity,which in turn excite neurons,forming an astrocyte-neuron feedback *** as a consequence of brain edema,astrocytic swelling can also induce slow inward currents under pathological *** is a growing body of evidence on the roles of slow inward currents on a single neuron or local network *** events often occur in synchro ny on neurons located in the same astrocytic *** synchronization of neuronal excitability,slow inward currents also set synaptic strength via eliciting timing-dependent synaptic *** addition,slow inward currents are also subject to non-synaptic plasticity triggered by long-la sting stimulation of the excitatory *** note,there might be important regionspecific differences in the roles and actions triggering slow inward *** greater networks,the pathophysiological roles of slow inward currents can be better understood than physiological *** inward currents are identified in the pathophysiological background of autism,as slow inward currents drive early hypersynchrony of the neural *** inward currents are significant contributors to paroxysmal depolarizational shifts/interictal *** events are related to epilepsy,but also found in Alzheimer's disease,parkinson's disease,and stroke,leading to the decline of cognitive *** with features overlapping with slow inward currents(excitatory,N-methyl-Dasp

关键词： astrocyte cortical spreading depolarization gliotransmission glutamate neural synchronization NMDA receptor paroxysmal depolarizational shift slow inward current

An Efficient Approach to Escalate the Speed of Training Convolution Neural Networks

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China Communications 2024年第2期21卷 258-269页

作者： p pabitha Anusha Jayasimhan Department of Computer Technology Anna UniversityMadras Institute of Technology CampusChennai 600044India

Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model *** experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOps with a degradation of just 0.11% accuracy.

关键词： CNN deep learning image classification model compression

Cryogenic and conventional milling of AZ91 magnesium alloy

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Journal of Magnesium and Alloys 2024年第6期12卷 2503-2519页

作者： Vikas Marakini Srinivasa pai p Gururaj Bolar Bhaskara p Achar Department of Mechanical Engineering Nitte(Deemed to be University)NMAM Institute of Technology(NMAMIT)Nitte 574110India Department of Mechanical and Industrial Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipal 576104India

Use of magnesium is the need of the hour due to its low density as well as its high strength-to-weight and stiffness-to-weight ratio *** study focuses on the effectiveness of liquid nitrogen(LN_(2))assisted cryogenic machining on the surface integrity(SI)characteristics of AZ91 magnesium *** milling using uncoated carbide inserts have been performed under liquid nitrogen(LN_(2))assisted cryogenic condition and compared with conventional(dry)*** are performed using machining parameters in terms of cutting speeds of 325,475,625 m/min,feed rates of 0.05,0.1,0.15 mm/teeth and depth of cuts of 0.5,1,1.5 mm *** significant surface integrity characteristics such as surface roughness,microhardness,microstructure,and residual stresses have been *** of SI characteristics with respect to milling parameters have been identified using statistical technique such as ANOVA and signal-to-noise(S/N)ratio ***,the multi criteria decision making(MCDM)techniques such as additive ratio assessment method(ARAS)and complex proportional assessment(COpRAS)have been utilized to identify the optimal conditions for milling AZ91 magnesium alloy under both dry and cryogenic *** of LN_(2)during machining,resulted in reduction in machining temperature by upto 29%with a temperature drop from 251.2℃under dry condition to 178.5℃in cryogenic *** showed the advantage of performing cryogenic milling in improving the surface integrity to a significant *** machining considerably minimized the roughness by upto 28%and maximised the microhardness by upto 23%,when compared to dry *** speed has caused significant impact on surface roughness(95.33%-dry,92.92%-cryogenic)and surface microhardness(80.33%-dry,82.15%-cryogenic).Due to the reduction in machining temperature,cryogenic condition resulted in compressive residual stresses(maximumσ║=-113 Mpa)on the alloy *** indicate no

关键词： Magnesium alloy Cryogenic machining Roughness Microhardness Microstructure Residual stress Multi criteria decision making