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Hybrid generative regressionbased deep intelligence to predict the risk of chronic disease

International Journal of Intelligent Computing and Cybernetics 2022年第1期15卷 144-164页

作者： Sandeep Kumar Hegde monica r.mundada Department of Computer Science and Engineering M.S.Ramaiah Institute of TechnologyBangaloreIndia Department of Computer Science and Engineering NMAM Institute of TechnologyNitteIndia Visvesvaraya Technological University BelagaviIndia

Purpose-Chronic diseases are considered as one of the serious concerns and threats to public health across the *** such as chronic diabetes mellitus(CDM),cardio vasculardisease(CVD)and chronic kidney disease(CKD)are major chronic diseases responsible for millions of *** of these diseases is considered as a risk factor for the other two ***,noteworthy attention is being paid to reduce the risk of these *** amount of medical data is generated in digital form from smart healthcare appliances in the current *** numerous machine learning(ML)algorithms are proposed for the early prediction of chronic diseases,these algorithmic models are neither generalized nor adaptive when the model is imposed on new disease ***,these algorithms have to process a huge amount of disease data iteratively until the model *** limitation may make it difficult forMLmodels to fit and produce imprecise results.A single algorithm may not yield accurate ***,an ensemble of classifiers built from multiple models,that works based on a voting principle has been successfully applied to solve many classification *** purpose of this paper is to make early prediction of chronic diseases using hybrid generative regression based deep intelligence network(HGrDIN)***/methodology/approach-In the proposed paper generative regression(Gr)model is used in combination with deep neural network(DNN)for the early prediction of chronic *** Gr model will obtain prior knowledge about the labelled data by analyzing the correlation between features and class ***,the weight assignment process of DNN is influenced by the relationship between attributes rather than random *** knowledge obtained through these processes is passed as input to the DNN network for further *** the inference about the input data instances is drawn at the DNN through the Gr model,the model is named as

关键词： Deep neural network Generative regression Chronic disease regularization Maximum likelihood estimation

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解压指南

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健与美 2025年第1期 169-173页

作者： monica

不摧毁压力，就会被压力摧毁。如果你总是感觉充满压力——无论是内在的还是外在的，就不可能长期保持健康和健美。本文将帮助你从压力的奴隶，变成压力的老板。要怪就怪那些不断发送短信、提醒音和电子邮件给我们的智能手机，要怪就怪...

不摧毁压力，就会被压力摧毁。如果你总是感觉充满压力——无论是内在的还是外在的，就不可能长期保持健康和健美。本文将帮助你从压力的奴隶，变成压力的老板。要怪就怪那些不断发送短信、提醒音和电子邮件给我们的智能手机，要怪就怪拥挤的地铁、高速公路和大卖场吧，要怪就怪大萧条、全球变暖、网络泡沫，或者你手上那杯不便宜的拿铁咖啡吧。

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减量增效中级水平选手的最佳训练模式

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健与美 2025年第1期 160-163页

作者： monica

本文是受到奥赛冠军多里安·耶茨在1983～1986年期间的训练计划的启发而产生的。对于自然健美运动员来说，最大的错误就是训练量太大。如果你目前的训练效果不尽人意，不妨试试下面的增肌策略，效果很可能比你以前采用的方法更好。

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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

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Efficient Gait Analysis Using Deep Learning Techniques

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Computers, Materials & Continua 2023年第3期74卷 6229-6249页

作者： K.M.monica r.Parvathi School of Computer Science and Engineering Vellore Institute of TechnologyChennai600117India

Human Activity recognition(HAr)has always been a difficult task to *** is mainly used in security surveillance,human-computer interaction,and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things(IoT).Human Activity recognition data can be recorded with the help of sensors,images,or *** daily routine-based human activities such as walking,standing,sitting,etc.,could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network(2D CNN)MODEL,Long Short Term Memory(LSTM)Model,Bidirectional long short-term memory(Bi-LSTM)are used for the *** has been demonstrated that recognizing the daily routine-based on human activities can be extremely accurate,with almost all activities accurately getting recognized over 90%of the ***,because all the examples are generated from only 20 s of data,these actions can be recognised *** from classification,the work extended to verify and investigate the need for wearable sensing devices in individually walking patients with Cerebral Palsy(CP)for the evaluation of chosen Spatio-temporal features based on 3D foot ***-control research was conducted with 35 persons with CP ranging in weight from 25 to 65 *** Motion Capture(OMC)equipment was used as the referral method to assess the functionality and quality of the foot-worn *** average accuracy±precision for stride length,cadence,and step length was 3.5±4.3,4.1±3.8,and 0.6±2.7 cm *** cadence,stride length,swing,and step length,people with CP had considerably high inter-stride ***-worn sensing devices made it easier to examine Gait Spatio-temporal data even without a laboratory set up with high accuracy and precision about gait abnormalities in people who have CP during linear walking.

关键词： Human activity recognition neural networks gait analysis wearable sensors kinetic analysis cerebral palsy

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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

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Dealing with detection error in site occupancy surveys: what can we do with a single survey?

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Journal of Plant Ecology 2012年第1期5卷 22-31页

作者： Subhash r.Lele monica Moreno Erin Bayne Department of Mathematical and Statistical Sciences University of AlbertaEdmontonAlbertaCanada T6G 2G1 Department of Biological Sciences University of AlbertaEdmontonAlbertaCanada T6G 2G1

Aim Site occupancy probabilities of target species are commonly used in various ecological studies,*** monitor current status and trends in *** error introduces bias in the estimators of site *** methods for estimating occupancy probability in the presence of detection error use replicate *** methods assume population closure,*** site occupancy status remains constant across surveys,and independence between *** present an approach for estimating site occupancy probability in the presence of detection error that requires only a single survey and does not require assumption of population closure or *** place of the closure assumption,this method requires covariates that affect detection and *** Penalized maximum-likelihood method was used to estimate the *** of the parameters was checked using data *** boostrapping method was used for computing confidence *** Findings The single-survey approach facilitates analysis of historical datasets where replicate surveys are unavailable,situations where replicate surveys are expensive to conduct and when the assumptions of closure or independence are not *** method saves significant amounts of time,energy and money in ecological surveys without sacrificing statistical ***,we show that occupancy and habitat suitability are not synonymous and suggest a method to estimate habitat suitability using single-survey data.

关键词： abundance estimation biodiversity BBS closed population data cloning penalized likelihood species occurrence

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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

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Non-perturbative multiphoton excitation studies in an excitonic coupled quantum well system using high-intensity THz laser fields

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Chinese Physics B 2019年第8期28卷 355-363页

作者： monica Gambhir Vinod Prasad Department of Physics Swami Shraddhanand CollegeUniversity of DelhiDelhi 110036India Departmento de Quimica Universidad Autonoma MetropolitansSan Rafael Atlixco No186IztapalapaMexico DF 09340Mexico

Multiphoton excitations and nonlinear optical properties of exciton states in GaAs/AlxGa1-xAs coupled quantum well structure have been theoretically investigated under the influence of a time-varying high-intensity terahertz(THz)laser ***-perturbative Floquet theory is employed to solve the time-dependent equation of motion for the laser-driven excitonic quantum well *** response to the field parameters,such as intensity and frequency of the laser electric field on the state populations,can be used in various optical semiconductor device applications,such as photodetectors,sensors,all-optical switches,and terahertz emitters.

关键词： quantum well excitons terahertz non-perturbative multiphoton laser Floquet

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