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LiDAR-based estimation of bounding box coordinates using Gaussian process regression and particle swarm optimization

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Biomimetic Intelligence & Robotics 2024年第1期4卷 24-35页

作者： Vinodha k. E.s.Gopi Tushar Agnibhoj Department of Electronics and Communication Engineering National Institute of Technology TiruchirappalliTamil Nadu620015India

Camera-based object track.ng systems in a given closed environment lack.privacy and *** this study,light detection and ranging(LiDAR)was applied to track.objects similar to the camera track.ng in a closed environment,guaranteeing privacy and *** primary objective was to demonstrate the efficacy of the proposed technique through carefully designed experiments conducted using two *** scenario I,the study illustrates the capability of the proposed technique to detect the locations of multiple objects positioned on a flat surface,achieved by analyzing LiDAR data collected from several locations within the closed *** II demonstrates the effectiveness of the proposed technique in detecting multiple objects using LiDAR data obtained from a single,fixed ***-time experiments are conducted with human subjects navigating predefined *** individuals move within an environment,while LiDAR,fixed at the center,dynamically track. and identifies their locations at multiple *** demonstrate that a single,strategically positioned LiDAR can adeptly detect objects in motion around ***,this study provides a comparison of various regression techniques for predicting bounding box *** process regression(GPR),combined with particle swarm optimization(PsO)for prediction,achieves the lowest prediction mean square error of all the regression techniques examined at *** tuning of GPR using PsO significantly minimizes the regression *** of the experiment pave the way for its extension to various real-time applications such as crowd management in malls,surveillance systems,and various Internet of Things scenarios.

关键词： LiDAR Data acquisition Bounding box Gaussian process regression Particle swarm optimization(PsO)

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Prioritizing Indicators for Rapid Response in Global Health security: A Bayesian Network.Approach

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INTERNATIONAL JOURNAL OF DIsAsTER RIsk.sCIENCE 2024年第4期15卷 536-551页

作者： Qazi, Abroon simsek.er, Mecit Can Emre Al-Mhdawi, M. k. s. Amer Univ sharjah Sch Business Adm Sharjah 26666 U Arab Emirates k.alifa Univ sci & Technol Dept Management Sci & Engn Abu Dhabi 127788 U Arab Emirates Teesside Univ Sch Comp Engn & Digital Technol Middlesbrough TS1 3BX England

This study explored a Bayesian belief network. (BBNs) approach, developing two distinct models for prioritizing the seven indicators related to the "rapid response to and mitigation of the spread of an epidemic" category within the context of both the specific category and the Global Health security Index (GHs index). Utilizing data from the 2021 GHs index, the methodology involves rigorous preprocessing, the application of the augmented naive Bayes algorithm for structural learning, and k.fold cross-validation. k.y findings show unique perspectives in both BBN models. In the mutual value of information analysis, "link.ng public health and security authorities" emerged as the k.y predictor for the "rapid response to and mitigation of the spread of an epidemic" category, while "emergency preparedness and response planning" assumed precedence for the GHs index. sensitivity analysis highlighted the critical role of "emergency preparedness and response planning" and "link.ng public health and security authorities" in extreme performance states, with "access to communications infrastructure" and "trade and travel restrictions" exhibiting varied significance. The BBN models exhibit high predictive accuracy, achieving 83.3% and 82.3% accuracy for extreme states in "rapid response to and mitigation of the spread of an epidemic" and the GHs index, respectively. This study contributes to the literature on GHs by modeling the dependencies among various indicators of the rapid response dimension of the GHs index and highlighting their relative importance based on the mutual value of information and sensitivity analyses.

关键词： Bayesian belief network. Global health security Indicators Mitigation Policy implications Rapid response RIsk DIsEAsE

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Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

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Journal of Magnesium and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan sek.r s.k.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnesium Research Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till *** corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical *** intrinsic high electrochemical nature of Mg limits their utilization in diverse *** scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion *** present review enlightens the influence of grain size(Gs),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg ***,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are ***,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are ***,the individual role of Gs,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and *** challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is *** review is presented from basic concrete back.round to advanced corrosion mechanisms with an aim of creating interest among the readers lik. students,researchers and industry experts from various research ***,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of k.owledge,(ii)foster research and development,(iii)mak. break.hrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

关键词： Corrosion Bio corrosion Magnesium alloys Magnesium composites Magnesium implants.

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A new route to weak.force sensing beyond sQL:squeezed magnons in cavity magnomechanics

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science China(Physics,Mechanics & Astronomy) 2024年第10期67卷 166-167页

作者： s.k.Özdemir Department of Engineering science and Mechanics and Materials Research Institute(MRI)The Pennsylvania State UniversityUniversity ParkPA 16802USA

Quantum mechanics imposes limits on measurement accuracy through quantum noise which typically has two components:First is the shot noise originating from vacuum fluctuations and referred to as the imprecision *** is ... 详细信息

关键词： quantum typically vacuum

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Dispersion effect of nano-structure pyrolytic carbon on mechanical,electrical,and microstructural characteristics of cement mortar composite

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International Journal of smart and Nano Materials 2024年第3期15卷 534-578页

作者： N.k.k.rthik.yan s.Elavenil school of Civil Engineering Vellore Institute of TechnologyChennaiIndia

In material science,converting waste into nanomaterials by green technologies highlights the interest in producing sus-tainable carbon nanomaterial(sCN).This study first-ever uti-lized tyre-char as a Nano-structure Pyrolytic Carbon(NsPC)to develop electrically conductive *** other car-bon nanomaterials,the efficiency of NsPC particle as an sCN in developing electrically conductive composites was investi-gated in terms of dispersion,mechanical,water absorption,electrical resistivity,and *** results of sedi-mentation and zeta potential(-19 mV)showed the excellent dispersion of NsPC particle in water with the combined effect of superplasticizer and *** compressive(40.37%)and flexural strength(10.76%)than that of plain cement mortar composite(CMC)is achieved with 2 wt.%and 1.5 wt.%of NsPC particle,*** water absorption rate and volume of permeable voids were reduced,exhibiting less *** percolation zone of AC and DC resis-tivity of NsPC composite ranges between 1 and 2 wt.%,and the established percolation threshold is at 2 wt.%.XRD analysis showed C-s-H formation consistently increased with curing age,and HR-sEM with EDAX analysis exhibits the dense micro-structure and well-distributed NsPC particle at the *** experimental outcomes significantly enhanced the relia-bility and provided a framework.for tailoring NsPC particle as sCN for developing electrically conductive composite.

关键词： sustainable nanomaterial dispersion mechanical properties electrical resistivity microstructure analysis

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An Efficient Long short-TermMemory and Gated Recurrent Unit Based smart Vessel Trajectory Prediction Using Automatic Identification system Data

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Computers, Materials and Continua 2024年第1期81卷 1789-1808页

作者： Zaman U. k.an J. Lee E. Hussain s. Balobaid A.s. Aburasain R.Y. k.m k. Department of Computer Engineering Chungnam National University Daejeon 34134 South Korea Department of Environmental IT Engineering Chungnam National University Daejeon 34134 South Korea Autonomous ship Research Center Samsung Heavy Industries Daejeon 34051 South Korea ICAROs Center (PRIsMA Lab) University of Naples Federico II Naples 80131 Italy Department of Computer science College of Computer Science and Information Technology Jazan University Jazan 45142 Saudi Arabia

Maritime transportation, a cornerstone of global trade, faces increasing safety challenges due to growing sea traffic volumes. This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification system (AIs) data and advanced deep learning models, including Long short-Term Memory (LsTM), Gated Recurrent Unit (GRU), Bidirectional LsTM (DBLsTM), simple Recurrent Neural Network.(simpleRNN), and k.lman Filtering. The research implemented rigorous AIs data preprocessing, encompassing record deduplication, noise elimination, stationary simplification, and removal of insignificant trajectories. Models were trained using k.y navigational parameters: latitude, longitude, speed, and heading. spatiotemporal aware processing through trajectory segmentation and topological data analysis (TDA)was employed to capture dynamic *** using a three-month AIs dataset demonstrated significant improvements in prediction accuracy. The GRU model exhibited superior performance, achieving training losses of 0.0020 (Mean squared Error, MsE) and 0.0334 (Mean Absolute Error, MAE), with validation losses of 0.0708 (MsE) and 0.1720 (MAE). The LsTM model showed comparable efficacy, with training losses of 0.0011 (MsE) and 0.0258 (MAE), and validation losses of 0.2290 (MsE) and 0.2652 (MAE). Both models demonstrated reductions in training and validation losses, measured by MAE, MsE, Average Displacement Error (ADE), and Final Displacement Error (FDE). This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions, contributing significantly to the development of robust, intelligent navigation systems for the maritime industry. © 2024 The Authors. Published by Tech science Press.

关键词： AIs data deep learning GRU LsTM smart vessel Trajectory prediction

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Enhancing Multicriteria-Based Recommendations by Alleviating scalability and sparsity Issues Using Collaborative Denoising Autoencoder

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Computers, Materials & Continua 2024年第2期78卷 2269-2286页

作者： s.Abinaya k.Uttej k.mar school of Computer science&Engineering Vellore Institute of TechnologyChennaiTamilnadu600127India

A Recommender system(Rs)is a crucial part of several firms,particularly those involved in *** conventional Rs,a user may only offer a single rating for an item-that is insufficient to perceive consumer ***,businesses in industries lik. e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’*** the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested ***,the cost of these computations increases nonlinearly as the number of items and users *** triumph over the issues,a novel expanded stack.d autoencoder(EsAE)with k.rnel Fuzzy C-Means Clustering(k.CM)technique is proposed with two *** the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the EsAE approach and users are clustered using the k.CM *** the next phase of online,the top-N recommendation prediction is made by the EsAE approach involving only the most similar user from multiple *** the EsAE_k.CM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation *** experimental check.on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the EsAE_k.CM model constantly outperforms conventional Rs algorithms on a variety of assessment measures.

关键词： Recommender systems multicriteria rating collaborative filtering sparsity issue scalability issue stack.d-autoencoder k.rnel Fuzzy C-Means Clustering

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Emission colour tuning in k.nF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of Rare Earths 2024年第1期42卷 57-65,I0002页

作者： Janani k.Gayathri E Vijayatha V Ramasubramanian s Thiyagarajan P Department of science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of Physics Anna UniversityChennaiIndia

k.nF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped k.bF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped k.dF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using UV light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped k.bF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： Rare earths Energy transfer upconversion Downshifting Colour coordinates

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Geochemistry and depositional environment of fuchsite quartzites from sargur Group,western Dharwar Craton,India

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Acta Geochimica 2024年第3期43卷 555-570页

作者： C.s.sindhuja G.Harshitha C.Manik.amba k.s.V.subramanyam CsIR(Council of scientific and Industrial Research)-National Geophysical Research Institute(NGRI) Uppal RoadHyderabad 500007India

Meso-Neoarchean fuchsite quartzites are present in different stratigraphic positions of Dharwar Craton including the oldest(~3.3 Ga)sargur Group of western Dharwar *** present study deals with the petro-graphic and geochemical characteristics of the fuchsite quartzites from the Ghattihosahalli belt to evaluate their genesis,depositional setting and the enigma involved in the ancient sedimentation *** major mineral assemblages include quartz,fuchsite,and feldspars along with accessory k.anite and *** geochemical com-positions are characterized by high siO_(2),Al_(2)O_(3),low MgO,CaO,strongly enriched Cr(1326–6899 ppm),Ba(1165–3653 ppm),sr(46–210 ppm),V(107–868 ppm)and Zn(11–158 ppm)contents compared to the upper continental crust(UCC).The UCC normalized rare earth element(REE)patterns are characterized by depleted light REE[(La/sm)UCC=0.33–0.95]compared to heavy REE[(Gd/Yb)_(UCC)=0.42–1.65]with conspicuous positive Eu-anomalies(Eu/Eu^(*)=1.35–18.27)characteristic of hydrothermal solutions evidenced through the interlayered *** overall major and trace element systematics reflect a combined mafic-felsic provenance and suggest their deposition at a passive continental margin *** comprehensivefield,petrographic,and geo-chemical studies indicate that these quartzites are infiltrated by Cr-richfluids released during high-grade metamorphism of associated ultramafic *** sargur and the subse-quent Dharwar orogeny amalgamated diverse lithounits from different tectonic settings,possibly leading to the release of Cr-richfluids and the formation of fuchsite quartzite during or after the *** sug-gest a pre-existing stable crust prior to the sargur Group and the link.between orogenic events and various mineral deposits in the Dharwar Craton.

关键词： Dharwar Craton Ghattihosahalli Fuchsite quartzite Provenance Depositional setting

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Juxtapose of system Performance for Food Calorie Estimation Using IoT and Web-based Indagation

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Journal of Harbin Institute of Technology(New series) 2024年第1期31卷 54-63页

作者： Anusuya s sharmila k Department of Computer science VISTASChennai 600117India Department of Computer science Dr.MGR Janaki College for WomenChennai 600028India

A rudimentary aspect of human life is the health of an individual,and most commonly the wellbeing is impacted in a colossal manner through the consumption of food. The intak. of calories therefore is a crucial aspect that must be meticulously monitored. Various health gremlins can be largely circumvented when there is a substantial balance in the number of calories ingested versus the quantity of calories *** food calorie estimation is a popular domain of research in recent times and is meticulously analyzed through various image processing and machine learning techniques. However,the need to scrutinize and evaluate the calorie estimation through various platforms and algorithmic approaches aids in providing a deeper insight on the bottleneck. involved,and in improvising the bariatric health of an individual. This paper pivots on comprehending a juxtaposed approach of food calorie estimation through the use of employing Convolution Neural Network.CNN)incorporated in Internet of Things(IoT),and using the Django framework.in Python,along with query rule-based training to analyze the subsequent actions to be followed post the consumption of food calories in the constructed webpage. The comparative analysis of the food calorie estimate implemented in both platforms is analyzed for the swiftness of identification,error rate and classification accuracy to appropriately determine the optimal method of use. The simulation results for IoT are carried out using the Raspberry Pi4B model,while the Anaconda prompt is used to run the server holding the web page.

关键词： food calorie estimation convolution neural network Django framework internet of things raspberry Pi

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