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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 tracking 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 tracking 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 tracks 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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Mechanistic insights toward identification and interaction of plant parasitic nematodes:A review

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soil ecology Letters 2024年第1期6卷 11-27页

作者： Bisma Jan ali Haider shah Mudasir Ahmad Bhat Arif Tasleem Jan Ishfaq Ahmad Wani ali Asghar shah section of Microbiology Baba Ghulam Shah Badshah UniversityRajouriJ&K185234India Department of Biotechnology Baba Ghulam Shah Badshah University RajouriJ&K185234India Department of Botany Baba Ghulam Shah Badshah University RajouriJ&K185234India Department of Zoology School of Biosciences and BiotechnologyBaba Ghulam Shah Badshah University RajouriJ&K185234India

Nematode identification serves as an important param-eter to study their behaviour,importance and *** of classical morphometric based identifica-tion methods prove to be lacking due to insufficient knowledge on morphological variations among closely related *** approaches such as DNA and protein-based information,microarray,probing,sequence-based methods and others have been used to supplement morphology-based methods for nematode *** and certain protein-based nematode-associated molecular patterns(NAMPs),can be perceived by the host plants,and can initiate a signalling *** review primarily emphasizes on an updated account of different classical and modern tools used for the identification of *** we also summa-rize the mechanism of some important signalling pathways which are involved in the different plant nematode *** constitute most diverse and least studied group of soil inhabiting *** are ecologically and physiologically important,however,wide range of nematodes show harmful impact on the individuals that live within their *** parasitic nematodes(PPNs)are transparent,pseudocoelomate,free living or parasitic *** lack morphometric identification methods due to insufficient knowl-edge on morphological variations among closely related *** such,molecular approaches such as DNA and protein-based information,microarray,probing,sequence-based methods and others have been used to supplement morphology-based methods for their *** invade the defense response of different plant species,parasitic nematodes have evolved different molecular *** and certain protein-based nematode-associated molecular patterns(NAMPs),can be perceived by the host plants,and can initiate a signaling *** overcome the host confrontation and develop certain nematode feeding sites,some members can inject effectors into

关键词： nematode identification plant nematode interaction DNA fingerprinting nematode-associated molecular patterns signaling path-ways

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Performance enhancement of XML Parsing Using Regression and Parallelism

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Computer systems science & engineering 2024年第2期48卷 287-303页

作者： Muhammad ali Minhaj Ahmad Khan Department of Computer science Bahauddin Zakariya UniversityMultan60000Pakistan

The extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the *** the existing Document Object Model(DOM)based parsing,the performance degrades due to sequential processing and large memory requirements,thereby requiring an efficient XML parser to mitigate these *** this paper,we propose a Parallel XML Tree Generator(PXTG)algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework(RXPF)that analyzes and predicts performance through profiling,regression,and code generation for efficient *** PXTG algorithm is based on dividing the XML file into n parts and producing n trees in *** profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including stAX,sAX,DOM,JDOM,and PXTG on different cores by using multiple file *** regression phase produces the prediction model,based on which the final code for efficient parsing of XML files is produced through the code generation *** RXPF framework has shown a significant improvement in performance varying from 9.54%to 32.34%over other existing models used for parsing XML files.

关键词： Regression parallel parsing multi-cores XML

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Nanomotion of bacteria to determine metabolic profile

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Nanotechnology and Precision engineering 2024年第1期7卷 1-9页

作者： s.N.Pleskova e.V.Lazarenko N.A.Bezrukov R.N.Kriukov A.V.Boryakov M.e.Dokukin s.I.surodin Research Laboratory of scanning Probe Microscopy Lobachevsky State University of Nizhny NovgorodNizhny Novgorod 603950Russia Department of Nanotechnology and Biotechnology Nizhny Novgorod State Technical University n.a.R.E.AlekseevNizhny Novgorod 603950Russia sarov Physics and Technology Institute National Research Nuclear University MEPhISarov 607186Russia

In addition to their visible motion such as swimming(e.g.,with the help ofﬂagella),bacteria can also exhibit nanomotion that is detectable only with highly sensitive instruments,and this study shows that it is possible to detect bacterial nanomotion using an AFM detection *** results show that the nanomotion characteristics depend on the bacterial strain,and that nanomotion can be used to sense the metabolic activity of bacteria because the oscillations are sensitive to the food preferences of the bacteria and the type of surrounding medium.

关键词： Nanomotion Bacteria Cantilever Oscillation Atomic force microscopy Metabolism

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Correlation of work function and stacking fault energy through Kelvin probe force microscopy and nanohardness in diluteα-magnesium

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Journal of Magnesium and Alloys 2024年第1期12卷 237-250页

作者： Yigit Türe ali Arslan Kaya Hüseyin Aydin Jiang Peng servet Turan eskisehir Technical University Porsuk Vocational SchoolElectronics and Automation DepartmentProgram of MechatronicsEskisehirTurkey Mugla sitki Kocman University Engineering FacultyMetallurgy and Materials Engineering DepartmentMuglaTurkey Hüseying Aydın TUBITAK MRCTurkey Jiang Peng Chongqing UniversityChina eskisehir Technical University Engineering FacultyMaterials Science and Engineering DepartmentEskisehirTurkey

electronic interactions of the Group 2A elements with magnesium have been studied through the dilute solid solutions in binary Mg-Ca,Mg-sr and Mg-Ba *** investigation incorporated the difference in the‘Work Function'(ΔWF)measured via Kelvin Probe Force Microscopy(KPFM),as a property directly affected by interatomic bond types,*** electronic structure,nanoindentation measurements,and stacking Fault energy values reported in the *** was shown that the nano-hardness of the solid-solutionα-Mg phase changed in the order of Mg-Ca>Mg-sr>***,it was shown,by also considering the nano-hardness levels,that sFe of a solid-solution is closely correlated with its‘Work Function'***-hardness measurements on the eutectics andΔWF difference between eutectic phases enabled an assessment of the relative bond strength and the pertinent electronic structures of the eutectics in the three *** withΔWF and at least qualitative verification of those computed sFe values with some experimental measurement techniques were considered important as those computational methods are based on zero Kelvin degree,relatively simple atomic models and a number of *** asserted by this investigation,if the results of measurement techniques can be qualitatively correlated with those of the computational methods,it can be possible to evaluate the electronic structures in alloys,starting from binary systems,going to ternary and then multi-elemental *** investigation has shown that such a qualitative correlation is *** all,the sFe values are not treated as absolute values but rather become essential in comparative investigations when assessing the influences of alloying elements at a fundamental level,that is,free electron density *** study indicated that the principles of‘electronic metallurgy'in developing multi-elemental alloy systems can be followed via practical experimental methods,i.e.ΔWF measurements using KPF

关键词： Mg alloys Dilute alloys Work function stacking fault energy Kelvin probe force microscopy short range order Miedema Nanoindentation eutectics

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An Ingenious IoT Based Crop Prediction system Using ML and eL

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Computers, Materials & Continua 2024年第4期79卷 183-199页

作者： shabana Ramzan Yazeed Yasin Ghadi Hanan Aljuaid Aqsa Mahmood Basharat ali Department of Computer science&IT Government Sadiq CollegeWomen UniversityBahawalpur63100Pakistan Department of Computer science/software engineering Al Ain UniversityAl Ain64141UAE Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)Riyadh11671Saudi Arabia Agronomic Research station Bahawalpur63100Pakistan

Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers haveno proper knowledge to select which crop is suitable to grow according to the environmental factors and soilcharacteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sectorof the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning,and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (eC),and environmental factors like temperature to improve crop yield. These parameters play a vital role in suggestinga suitable crop to cope the food scarcity. This paper proposes a systemcomprised of twomodules, first module usesstatic data and the second module takes hybrid data collection (IoT-based real-time data and manual data) withmachine learning and ensemble learning algorithms to suggest the suitable crop in the farm to maximize the *** is used to train the model that predicts the crop. This system proposed an intelligent and low-cost solutionfor the farmers to process the data and predict the suitable *** implemented the proposed system in the *** efficiency and accuracy of the proposed system are confirmed by the generated results to predict the crop.

关键词： Machine learning Internet of Things sensors ensemble learning

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Model Predictive Current Control for Low-Cost shunt Active Power Filter

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Csee Journal of Power and energy systems 2024年第4期10卷 1589-1598页

作者： ali A.Abdel-Aziz Mohamed A.elgenedy Barry W.Williams the electronic and electrical engineering Department Strathclyde UniversityGlasgowG11XQUK school of Computing Engineering and the Built Environment(SCEBE)Glasgow Caledonian UniversityGlasgowG40BAUK

Performance of a three-phase shunt active power filter(sAPF)relies on the capability of the controller to track the reference ***,designing an accurate current controller is crucial to guarantee satisfactory sAPF *** paper presents a model predictive current controller(MPCC)for a low-cost,four-switch,shunt active power filter for power quality improvement.A four-switch,B4,converter topology is adopted as an sAPF,hence offering a simple,robust,and low-cost *** addition,to further reduce overall cost,only two interfacing filter inductors,instead of three,are used to eliminate switching current *** proposed sAPF model MPCC is detailed for implementation,where simulation and experimental results validate effectiveness of the proposed control algorithm showing a 20%improvement in total harmonic distortion compared with a conventional hysteresis band current controller.

关键词： Four-switch converter harmonic distortion model predictive current control power quality shunt active power filter

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Theories behind Bacillus Calmette-Guerin failure in high-risk non-muscle-invasive bladder cancer and update on current management

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Cancer Pathogenesis and Therapy 2024年第2期2卷 74-80页

作者： Hanna Maroof Louise Paramore Ahmed ali Department of Urology Frimley Park HospitalPortsmouth RdFrimleyCamberley GU167UJUnited Kingdom

Bladder cancer encapsulates a wide spectrum of disease severities,with non-muscle invasive bladder cancer(NMIBC)representing an entirely different entity from muscle-invasive *** Calmette-Guerin(BCG)is one of the most successful intravesical treatment methods for patients ***,a considerable pro-portion of patients fail to respond to BCG *** the propensity for recurrence in patients with high-risk bladder cancer,these patients present with surgical *** is currently no gold standard for salvage treatment post-BCG failure or unified definition as to what that *** this review,we discuss the mechanisms of action and pathophysiology of BCG,potential theories behind BCG failure,and the scope of novel treatments forthis surgical conundrum.

关键词： Cystectomy Hyperthermia Induced Immunotherapy Mycobacterium bovis Non-muscle-invasive bladder cancer

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Convective drying of wood chips:Accelerating coupled DeM-CFD simulations with parametrized reduced single particle models

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Particuology 2024年第1期84卷 158-167页

作者： Lucas Reineking Jonas Fischer ali Mjalled enric Illana siegmar Wirtz Viktor scherer Martin Monnigmann Automatic Control and system Theory Ruhr-Universität-BochumUniversitätstraße 150Bochum44801Germany energy Plant Technology Ruhr-Universität-BochumUniversitätstraße 150Bochum44801Germany

The simulation of industry-scale reactive bulks is challenging due to the complex interaction between fluid and *** particles in the bulk and their interaction with the fluid flow can be described by combined Discrete element Method-Computational Fluid Dynamics(DeM-CFD)***,the computational cost of the Finite Volume(FV)methods deployed in these models can become prohibi-tively expensive,especially for high inner-particle *** particle Reduced Models(RMs)can be used to achieve both fast and accurate descriptions of the processes in each *** an example of bulk systems comprising heat and mass transfer,we compared FV and RM simulations for the drying of wood chips in a bulk reactor.A manifold-based nonlinear interpolation was applied to resolve changing boundary conditions for the *** simulations showed that RMs provide accurate values for the thermodynamic state variables of the ***,the time required for the bulk simulation was reduced by 67%with the *** is evident that simulations with high inner-particle resolution can be accelerated by RMs if manifold-based nonlinear interpolation is used to address changing boundary conditions.

关键词： Reduced model Reactive bulk Discrete element method Manifold-based interpolation Drying of porous mediaDeM-CFD

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sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz ali Maqbool Khan Khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as english, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

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