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Multiclass recognition of Alzheimer’s and Parkinson’s disease using various machine learning techniques: A study

International Journal of Modeling, simulation, and scientific Computing 2022年第1期13卷 235-250页

作者： Chetan Balaji d.s.suresh department of ECE Channabasaveshwara Institute of Technology Tumkur KarnatakaIndia Visvesvaraya Technological University BelagaviKarnatakaIndia

The aging population is primarily affected by Alzheimer’s disease(Ad)that is an incur-able neurodegenerative *** is a need for an automated efficient technique to diagnose Alzheimer’s in its early *** techniques are used to diagnose *** and neuroimaging methodologies are widely used to highlight changes in the electrical activity of the brain signals that are helpful for early ***’s disease(Pd)is a major neurological disease that results in an average of 50,000 new clinical diagnoses worldwide every *** voice features are majorly used as the main means to diag-nose *** major symptoms of Pd are loss of intensity,the monotony of loudness and pitch,reduction in stress,unidentified silences,and *** though various innovative models are proposed by explorers about Alzheimer’s and Parkinson’s classifi-cation diseases,still there is a need for efficient learning methodologies and *** paper provides a review on using machine learning(ML)together with several fea-ture extraction techniques that is helpful in the early detection of Ad with Parkinson’*** novelty and objective of this study are that the CAd technique is used to improve the accuracy of early diagnosis of *** proposed technique depends on the nonlinear process for data dimension reduction,feature removal,and classification using kernel-based support vector machine(sVM)*** dimension of the input space is radically diminished with kernel *** the learning set is labeled,it creates sense to utilize this information to make a dependable method of dropping the input space *** different techniques of ML are explained under the major approaches ***,artificial neural network(ANN),deep learning(dL),and ensemble methods.A comprehensive assessment is presented at sVM,ANN,and dL approaches for better detection of Alzheimer’s with Pd highlighting future insights.

关键词： Electroencephalograph support vector machine Alzheimer’s disease control normal machine learning

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Quantification of submarine groundwater discharge(sGd) using radon,radium tracers and nutrient inputs in Punnakayal, south coast of India

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Geoscience Frontiers 2021年第1期12卷 29-38页

作者： s.selvam P.Muthukumar sruthy sajeev s.Venkatramanan s.Y.Chung K.Brindha d.s.suresh Babu R.Murugan department of Geology V.O.Chidambaram CollegeThoothukudi628008TamilnaduIndia Registration No:*** Affiliated to Manonmaniam Sundaranar UniversityTirunelveli627012Tamil NaduIndia department for Management of science and Technology development Ton Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Applied sciences Ton Duc Thang UniversityHo Chi Minh CityViet Nam department of Earth&Environmental sciences Pukyong National UniversityBusan608-737South Korea Freie Universitat Berlin Institut für Geologische WissenschaftenArbeitsbereich HydrogeologieMalteserstraße 7410012249BerlinGermany Centre for Earth sciences studies AkkulamTiruvanthapuram695031India department of disaster Management Alagappa UniversityKaraikudiTamil NaduIndia

The present study focused on the estimation of submarine groundwater discharge(sGd)and the effects of nutrient fluxes due to the sGd *** parameters of sGd such as magnitude,character,and nutrient flux in Punnakayal region of south East coast of India were evaluated using multiple tracers of groundwater inputs in *** was found that the elevated values for the tracers in the study area,displayed a gradational change in the values as move from estuarine part to the *** occurrence of fresh and saline sGd is observed on the study ***,indicated that the sGd fluxes ranged from 0.04 to 0.12 m^3 m^-2d^-1 at the estuary and0.03-0.15 m^3 m^-2d^-1at the groundwater site.A substantially increased value for 222 Rn activities is distinguished in the estuary to values over 312 dpm L^-*** embellishments were generally greatest at locations with substantial meteoric elements in groundwater;however,the recirculation of saltwater through the geological formation could provide a way of transferring terrestrially-derived nutrients to the coastal zone at many places.

关键词： sGd Radon Radium Nutrients Coastal zone Box model

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Geochemical elements in suspended particulate matter of Ensenada de La Paz Lagoon,Baja California Peninsula,Mexico:sources,distribution,mass balance and ecotoxicological risks

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Journal of Environmental sciences 2024年第2期136卷 422-436页

作者： sandra soledad Morales-García Pilar de Acacia Pérez-Escamilla suresh Babu sujitha Pichaimani Godwyn-Paulson Andrés Felipe Zuniga-Cabezas Muthuswamy Ponniah Jonathan Instituto Politécnico Nacional(IPN) Centro Mexicano para la Producción más Limpia(CMPL)Av.Acueducto s/nCol.Barrio la Laguna TicománDel Gustavo A.MaderoC.P.07340Ciudad de MéxicoMexico Instituto Politécnico Nacional(IPN) Escuela Superior de Ingeniería y Arquitectura(ESIA)Unidad Ticomán***án 600Delg.Gustavo A.MaderoC.P.07340Ciudad de México(CDMX)Mexico Instituto Politécnico Nacional(IPN) Centro Interdisciplinario de Investigaciones y Estudios sobre Medio Ambiente y Desarrollo(CIIEMAD)Calle 30 de Junio de 1520Barrio la Laguna TicománDel.Gustavo A.MaderoC.P.07340Ciudad de MéxicoMéxico

The present study aimed to evaluate multi-element concentrations(Al,As,Ca,Cd,Co,Cr,Cu,Fe,Mg,Mn,Mo,Ni,Pb,sr)in suspended particulate material(sPM)collected from Ensenada de La Paz(ELP)lagoon,Baja California sur,Mexico in two different periods(september and May)to comprehend their origin,geochemical behavior,mass transfer and associated ecotoxicological *** 24 hr variation coefficient of volumetric sPM levels were found to be 51.7%in september and 40.5%in May,signifying the effects of oceanic *** calculated enrichment factor(EF)values for all the studied elements were of higher magnitude because of the high surface area and oxide nature of sPM,and in this study,Mo had the highest EF of 46.77 probably due to its origin from continental *** the ecotoxicological perspective,the integrated toxic risk index revealed low toxic risk to the benthic ***,the mean-ERM-Quotient calculated using the particulate concentrations of As,Cd,Cr,Cu,Ni,Pb indicated 9%probability of toxicity to *** comprehensive geochemical and ecotoxicological assessment of particulate metal concentrations in the ELP lagoon signify low to moderate contamination.

关键词： suspended particulate material Heavy metals Risk assessment Mass transfer Ensenada de La Paz

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smart mid-infrared metasurface microspectrometer gas sensing system

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Microsystems & Nanoengineering 2024年第3期10卷 273-281页

作者： Jiajun Meng sivacarendran Balendhran Ylias sabri suresh K.Bhargava Kenneth B.Crozier school of Physics University of MelbourneVictoriaAustralia Australian Research Council(ARC)Centre of Excellence for Transformative Meta-Optical systems(TMOs) University of MelbourneVictoriaAustralia Centre for Advanced Materials&Industrial Chemistry(CAMIC) STEM collegeRMIT UniversityVictoriaAustralia department of Electrical and Electronic Engineering University of MelbourneVictoriaAustralia

smart,low-cost and portable gas sensors are highly desired due to the importance of air quality monitoring for environmental and defense-related ***,electrochemical and nondispersive infrared(IR)gas sensors are designed to detect a single specific *** IR spectroscopy-based sensors provide superior performance,their deployment is limited due to their large size and high *** this study,a smart,low-cost,multigas sensing system is demonstrated consisting of a mid-infrared microspectrometer and a machine learning *** microspectrometer is a metasurface filter array integrated with a commercial IR camera that is consumable-free,compact(~1 cm^(3))and lightweight(~1 g).The machine learning algorithm is trained to analyze the data from the microspectrometer and predict the gases *** system detects the greenhouse gases carbon dioxide and methane at concentrations ranging from 10 to 100%with 100%*** also detects hazardous gases at low concentrations with an accuracy of 98.4%.Ammonia can be detected at a concentration of 100 ***,methyl-ethyl-ketone can be detected at its permissible exposure limit(200 ppm);this concentration is considered low and *** study demonstrates the viability of using machine learning with IR spectroscopy to provide a smart and low-cost multigas sensing platform.

关键词： smart gases system

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Flexible ultra-thin super-resolution endoscopy

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science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 171-172页

作者： George s.d.Gordon department of Electrical and Electronic Engineering University of NottinghamNottingham NG7 2RDUK

In recent years, multimode fiber(MMF) has become an important tool for high-resolution endoscopic imaging in narrow channels(e.g., in the brain via needles or inside blood vessels) due to its high mode density and fine diameter, typically stacle to widespread deployment in applications is that realistic perturbations, including bending, twisting and changes in temperature, cause unacceptable image degradation.

关键词： fiber resolution typically

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A systematic review of climate change impacts,adaptation strategies,and policy development in West Africa

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Regional sustainability 2024年第2期5卷 13-25页

作者： Camillus Abawiera WONGNAA Alex Amoah sEYRAM suresh BABU department of Agricultural Economics Agribusiness and ExtensionKwame Nkrumah University of Science and TechnologyKumasi00233Ghana International Food Policy Research Institute Washington20005USA

Climate change studies are diverse with no single study giving a comprehensive review of climate change impacts,adaptation strategies,and policy development in West *** unavailability of an all-inclusive study to serve as a guide for practitioners affects the effectiveness of climate change adaptation strategies proposed and adopted in the West African *** purpose of this study was to review the impacts of climate change risks on the crop,fishery,and livestock sectors,as well as the climate change adaptation strategies and climate-related policies aimed at helping to build resilient agricultural production systems in West *** review process followed a series of rigorous stages until the final selection of 56 articles published from 2009 to ***,the results highlighted the adverse effects of climate change risks on food *** found a continuous decline in food crop ***,the livestock sector experienced morbidity and mortality,as well as reduction in meat and milk *** fishery sector recorded loss of fingerlings,reduction in fish stocks,and destruction of mariculture and *** West Africa,climate-smart agriculture technologies,physical protection of fishing,and inclusion of gender perspectives in programs appear to be the major adaptation *** study therefore recommends the inclusion of ecosystem and biodiversity restoration,weather insurance,replacement of unsafe vessels,and strengthening gender equality in all climate change mitigation programs,as these will help to secure enough food for present and future generations.

关键词： Climate change Climate extreme events Food security Adaptation strategies Climate-smart agriculture West Africa

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Generalized polynomial chaos expansion by reanalysis using static condensation based on substructuring

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 819-836页

作者： d.LEE s.CHANG J.LEE department of Automotive Engineering Hanyang UniversitySeoul 04763Republic of Korea school of Mechanical Engineering Chungnam National UniversityDaejeon 34134Republic of Korea department of Mechanical Robotics and Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea

This paper presents a new computational method for forward uncertainty quantification(UQ)analyses on large-scale structural systems in the presence of arbitrary and dependent random *** method consists of a generalized polynomial chaos expansion(GPCE)for statistical moment and reliability analyses associated with the stochastic output and a static reanalysis method to generate the input-output data *** the reanalysis,we employ substructuring for a structure to isolate its local regions that vary due to random *** allows for avoiding repeated computations of invariant substructures while generating the input-output data *** substructuring with static condensation further improves the computational efficiency of the reanalysis without losing ***,the GPCE with the static reanalysis method can achieve significant computational saving,thus mitigating the curse of dimensionality to some degree for UQ under high-dimensional *** numerical results obtained from a simple structure indicate that the proposed method for UQ produces accurate solutions more efficiently than the GPCE using full finite element analyses(FEAs).We also demonstrate the efficiency and scalability of the proposed method by executing UQ for a large-scale wing-box structure under ten-dimensional(all-dependent)random inputs.

关键词： forward uncertainty quantification(UQ) generalized polynomial chaos expansion(GPCE) static reanalysis method static condensation substructuring

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Real Time Thermal Image Based Machine Learning Approach for Early Collision Avoidance system of snowplows

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Journal of Intelligent Learning systems and Applications 2024年第2期16卷 107-142页

作者： Fletcher Wadsworth suresh s. Muknahallipatna Khaled Ksaibati department of Electrical Engineering and Computer science University of Wyoming Laramie WY USA department of Civil and Architectural Engineering University of Wyoming Laramie WY USA

In an effort to reduce vehicle collisions with snowplows in poor weather conditions, this paper details the development of a real time thermal image based machine learning approach to an early collision avoidance system for snowplows, which intends to detect and estimate the distance of trailing vehicles. due to the operational conditions of snowplows, which include heavy-blowing snow, traditional optical sensors like LidAR and visible spectrum cameras have reduced effectiveness in detecting objects in such environments. Thus, we propose using a thermal infrared camera as the primary sensor along with machine learning algorithms. First, we curate a large dataset of thermal images of vehicles in heavy snow conditions. Using the curated dataset, two machine-learning models based on the modified ResNet architectures were trained to detect and estimate the trailing vehicle distance using real-time thermal images. The trained detection network was capable of detecting trailing vehicles 99.0% of the time at 1500.0 ft distance from the snowplow. The trained trailing distance network was capable of estimating distance with an average estimation error of 10.70 ft. The inference performance of the trained models is discussed, along with the interpretation of the performance.

关键词： Convolutional Neural Networks Residual Networks Object detection Image Processing Thermal Imaging

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sim-to-Real: A Performance Comparison of PPO, Td3, and sAC Reinforcement Learning Algorithms for Quadruped Walking Gait Generation

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Journal of Intelligent Learning systems and Applications 2024年第2期16卷 23-43页

作者： James W. Mock suresh s. Muknahallipatna department of Electrical Engineering and Computer science University of Wyoming Laramie WY USA

The performance of the state-of-the-art deep Reinforcement algorithms such as Proximal Policy Optimization, Twin delayed deep deterministic Policy Gradient, and soft Actor-Critic for generating a quadruped walking gait in a virtual environment was presented in previous research work titled “A Comparison of PPO, Td3, and sAC Reinforcement Algorithms for Quadruped Walking Gait Generation”. We demonstrated that the soft Actor-Critic Reinforcement algorithm had the best performance generating the walking gait for a quadruped in certain instances of sensor configurations in the virtual environment. In this work, we present the performance analysis of the state-of-the-art deep Reinforcement algorithms above for quadruped walking gait generation in a physical environment. The performance is determined in the physical environment by transfer learning augmented by real-time reinforcement learning for gait generation on a physical quadruped. The performance is analyzed on a quadruped equipped with a range of sensors such as position tracking using a stereo camera, contact sensing of each of the robot legs through force resistive sensors, and proprioceptive information of the robot body and legs using nine inertial measurement units. The performance comparison is presented using the metrics associated with the walking gait: average forward velocity (m/s), average forward velocity variance, average lateral velocity (m/s), average lateral velocity variance, and quaternion root mean square deviation. The strengths and weaknesses of each algorithm for the given task on the physical quadruped are discussed.

关键词： Reinforcement Learning Reality Gap Position Tracking Action spaces domain Randomization

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decoding bovine coronavirus immune targets:an epitope informatics approach

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Animal diseases 2024年第2期4卷 138-153页

作者： swati Rani Mehnaj Khatoon Jagadish Hiremath Kuralayanapalya Puttahonnappa suresh Jayashree Anandakumar Nagendra Nath Barman sheethal Manjunath Yamini sri s sharanagouda s.Patil spatial Epidemiology Lab ICAR-National Institute of Veterinary Epidemiology and Disease InformaticsYelahankaBengaluruKarnataka 560064India College of Veterinary science Assam Agricultural UniversityGuwahatiAssam 785013India Yuvaraja’s College Mysuru University of MysuruMysuruKarnataka 570005India

Bovine coronavirus(BCoV)poses a significant threat to the global cattle industry,causing both respiratory and gastrointestinal infections in cattle *** necessitates the development of efficacious *** several inactivated and live BCoV vaccines exist,they are predominantly limited to *** immunization of adult cattle is imperative for BCoV infection control,as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the *** study presents an in silico methodology for devising a multiepitope vaccine targeting *** spike glycoprotein(s)and nucleocapsid(N)proteins,which are integral elements of the BCoV structure,play pivotal roles in the viral infection cycle and immune *** constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV *** immunoinformatics technology,B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in *** in silico construct was characterized,and assessment of its physicochemical properties revealed the formation of a stable vaccine *** 3d modeling of the vaccine construct,molecular docking revealed a stable interaction with the bovine receptor ***,the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a(+)*** applying immunoinformatics approaches,researchers aim to better understand the immune response to bovine coronavirus,discover potential targets for intervention,and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock *** anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle,opening the door for furthe

关键词： Immunoinformatics Bovine coronavirus Multiepitope vaccine Molecular docking In silico cloning

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