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Artigos de revistas sobre o tema "Inertial Gradient Methods"

Autor: Grafiati

Publicado: 23 de novembro de 2024

Última modificação: 19 de julho de 2025

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1

Li, Jing, Xiao Wei, Fengpin Wang, and Jinjia Wang. "IPGM: Inertial Proximal Gradient Method for Convolutional Dictionary Learning." Electronics 10, no. 23 (2021): 3021. http://dx.doi.org/10.3390/electronics10233021.

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Inspired by the recent success of the proximal gradient method (PGM) and recent efforts to develop an inertial algorithm, we propose an inertial PGM (IPGM) for convolutional dictionary learning (CDL) by jointly optimizing both an ℓ2-norm data fidelity term and a sparsity term that enforces an ℓ1 penalty. Contrary to other CDL methods, in the proposed approach, the dictionary and needles are updated with an inertial force by the PGM. We obtain a novel derivative formula for the needles and dictionary with respect to the data fidelity term. At the same time, a gradient descent step is designed t

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Zhang, Yanwei, and James N. Moum. "Inertial-Convective Subrange Estimates of Thermal Variance Dissipation Rate from Moored Temperature Measurements." Journal of Atmospheric and Oceanic Technology 27, no. 11 (2010): 1950–59. http://dx.doi.org/10.1175/2010jtecho746.1.

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Abstract A procedure for estimating thermal variance dissipation rate χT by scaling the inertial-convective subrange of temperature gradient spectra from thermistor measurements on a Tropical Atmosphere Ocean (TAO) equatorial mooring, maintained by NOAA’s National Data Buoy Center, is demonstrated. The inertial-convective subrange of wavenumbers/frequencies is contaminated by the vertical motion induced by the pumping of the surface float by surface gravity waves through the local vertical temperature gradient. The uncontaminated signal can be retrieved by removing the part of the measured sig

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Ahmad, Abdulwahab, Poom Kumam, Yeolb Je Cho, and Kanokwan Sıtthıthakerngkıet. "Halpern-type relaxed algorithms with alternated and multi-step inertia for split feasibility problems with applications in classification problems." Constructive Mathematical Analysis 8, no. 2 (2025): 50–80. https://doi.org/10.33205/cma.1563173.

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In this article, we construct two Halpern-type relaxed algorithms with alternated and multi-step inertial extrapolation steps for split feasibility problems in infinite-dimensional Hilbert spaces. The first is the most general inertial method that employs three inertial steps in a single algorithm, one of which is an alternated inertial step, while the others are multi-step inertial steps, representing the recent improvements over the classical inertial step. Besides the inertial steps, the second algorithm uses a three-term conjugate gradient-like direction, which accelerates the sequence of

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Kesornprom, Suparat, and Prasit Cholamjiak. "A modified inertial proximal gradient method for minimization problems and applications." AIMS Mathematics 7, no. 5 (2022): 8147–61. http://dx.doi.org/10.3934/math.2022453.

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<abstract><p>In this paper, the aim is to design a new proximal gradient algorithm by using the inertial technique with adaptive stepsize for solving convex minimization problems and prove convergence of the iterates under some suitable assumptions. Some numerical implementations of image deblurring are performed to show the efficiency of the proposed methods.</p></abstract>

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Ahmad, Abdulwahab, Poom Kumam, and Thidaporn Seangwattana. "Strong convergence multi-step inertial golden ratio-based algorithms for split feasibility problems with applications." Mathematical Modelling and Numerical Simulation with Applications 5, no. 2 (2025): 307–47. https://doi.org/10.53391/mmnsa.1595657.

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In this work, we construct four efficient multi-step inertial relaxed algorithms based on the monotonic step-length criterion which does not require any information about the norm of the underlying operator or the use of a line search procedure for split feasibility problems in infinite-dimensional Hilbert spaces. The first and the third are the general multi-step inertial-type methods, which unify two steps of the multi-step inertial terms with the golden ratio-based and an alternating golden ratio-based extrapolation steps, respectively, to improve the speed of convergence of their sequences

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Sheng, Guangrun, Guowei Gao, and Boyuan Zhang. "Application of Improved Wavelet Thresholding Method and an RBF Network in the Error Compensating of an MEMS Gyroscope." Micromachines 10, no. 9 (2019): 608. http://dx.doi.org/10.3390/mi10090608.

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The large random errors in Micro-Electro-Mechanical System (MEMS) gyros are one of the major factors that affect the precision of inertial navigation systems. Based on the indoor inertial navigation system, an improved wavelet threshold de-noising method was proposed and combined with a gradient radial basis function (RBF) neural network to better compensate errors. We analyzed the random errors in an MEMS gyroscope by using Allan variance, and introduced the traditional wavelet threshold methods. Then, we improved the methods and proposed a new threshold function. The new method can be used m

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Milder, A. L., A. S. Joglekar, W. Rozmus, and D. H. Froula. "Qualitative and quantitative enhancement of parameter estimation for model-based diagnostics using automatic differentiation with an application to inertial fusion." Machine Learning: Science and Technology 5, no. 1 (2024): 015026. http://dx.doi.org/10.1088/2632-2153/ad2493.

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Abstract Parameter estimation using observables is a fundamental concept in the experimental sciences. Mathematical models that represent the physical processes can enable reconstructions of the experimental observables and greatly assist in parameter estimation by turning it into an optimization problem which can be solved by gradient-free or gradient-based methods. In this work, the recent rise in flexible frameworks for developing differentiable scientific computing programs is leveraged in order to dramatically accelerate data analysis of a common experimental diagnostic relevant to laser–

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Ceng, Lu-Chuan, Adrian Petruşel, Ching-Feng Wen, and Jen-Chih Yao. "Inertial-Like Subgradient Extragradient Methods for Variational Inequalities and Fixed Points of Asymptotically Nonexpansive and Strictly Pseudocontractive Mappings." Mathematics 7, no. 9 (2019): 860. http://dx.doi.org/10.3390/math7090860.

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Let VIP indicate the variational inequality problem with Lipschitzian and pseudomonotone operator and let CFPP denote the common fixed-point problem of an asymptotically nonexpansive mapping and a strictly pseudocontractive mapping in a real Hilbert space. Our object in this article is to establish strong convergence results for solving the VIP and CFPP by utilizing an inertial-like gradient-like extragradient method with line-search process. Via suitable assumptions, it is shown that the sequences generated by such a method converge strongly to a common solution of the VIP and CFPP, which als

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Kesornprom, Suparat, Papatsara Inkrong, Uamporn Witthayarat, and Prasit Cholamjiak. "A recent proximal gradient algorithm for convex minimization problem using double inertial extrapolations." AIMS Mathematics 9, no. 7 (2024): 18841–59. http://dx.doi.org/10.3934/math.2024917.

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<abstract><p>In this study, we suggest a new class of forward-backward (FB) algorithms designed to solve convex minimization problems. Our method incorporates a linesearch technique, eliminating the need to choose Lipschitz assumptions explicitly. Additionally, we apply double inertial extrapolations to enhance the algorithm's convergence rate. We establish a weak convergence theorem under some mild conditions. Furthermore, we perform numerical tests, and apply the algorithm to image restoration and data classification as a practical application. The experimental results show our a

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Rasmussen, John, Sebastian Skejø, and Rasmus Plenge Waagepetersen. "Predicting Tissue Loads in Running from Inertial Measurement Units." Sensors 23, no. 24 (2023): 9836. http://dx.doi.org/10.3390/s23249836.

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Background: Runners have high incidence of repetitive load injuries, and habitual runners often use smartwatches with embedded IMU sensors to track their performance and training. If accelerometer information from such IMUs can provide information about individual tissue loads, then running watches may be used to prevent injuries. Methods: We investigate a combined physics-based simulation and data-based method. A total of 285 running trials from 76 real runners are subjected to physics-based simulation to recover forces in the Achilles tendon and patella ligament, and the collected data are u

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Michielsen, M., C. Aerts, and D. M. Bowman. "Probing the temperature gradient in the core boundary layer of stars with gravito-inertial modes." Astronomy & Astrophysics 650 (June 2021): A175. http://dx.doi.org/10.1051/0004-6361/202039926.

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Aims. We investigated the thermal and chemical structure in the near-core region of stars with a convective core by means of gravito-inertial modes. We determined the probing power of different asteroseismic observables and fitting methodologies. We focus on the case of the B-type star KIC 7760680, rotating at a quarter of its critical rotation velocity. Methods. We computed grids of 1D stellar structure and evolution models for two different prescriptions of the temperature gradient and mixing profile in the near-core region. We determined which of these prescriptions is preferred according t

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Neuwirth, Christina, Cory Snyder, Wolfgang Kremser, Richard Brunauer, Helmut Holzer, and Thomas Stöggl. "Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units." Sensors 20, no. 15 (2020): 4232. http://dx.doi.org/10.3390/s20154232.

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In alpine skiing, four commonly used turning styles are snowplow, snowplow-steering, drifting and carving. They differ significantly in speed, directional control and difficulty to execute. While they are visually distinguishable, data-driven classification is underexplored. The aim of this work is to classify alpine skiing styles based on a global navigation satellite system (GNSS) and inertial measurement units (IMU). Data of 2000 turns of 20 advanced or expert skiers were collected with two IMU sensors on the upper cuff of each ski boot and a mobile phone with GNSS. After feature extraction

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Tomiło, Paweł. "Classification of the Condition of Pavement with the Use of Machine Learning Methods." Transport and Telecommunication Journal 24, no. 2 (2023): 158–66. http://dx.doi.org/10.2478/ttj-2023-0014.

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Abstract The publication includes a review of information on the methods of pavement condition recognition using various methods. Measurement system has been presented that allows to determine the condition of the pavement using the Inertial Measurement Unit (IMU) and machine learning methods. Three machine learning methods were considered: random forest, gradient boosted tree and custom architecture neural network (roadNet). Due to the developed system the set of learning and validation data was created on 3 vehicles: Opel Corsa, Honda Accord, Volkswagen Passat. All of the listed vehicles hav

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Zak, Idan, Itzik Klein, and Reuven Katz. "A Feasibility Study of Machine Learning Based Coarse Alignment." Proceedings 4, no. 1 (2018): 50. http://dx.doi.org/10.3390/ecsa-5-05735.

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Inertial navigation systems (INSs) require an initial attitude before its operation. To that end, the coarse alignment process is applied using inertial sensors readings. For low-cost inertial sensors, only the accelerometers readings are processed to yield the initial roll and pitch angles. The accuracy of the coarse alignment procedure is vitally important for the navigation solution accuracy due to the navigation solution drift accumulating over time. In this paper, we propose using machine learning (ML) approaches, instead of traditional approaches, to conduct the coarse alignment procedur

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Ofem, Austine Efut, Jacob Ashiwere Abuchu, Godwin Chidi Ugwunnadi, Hossam A. Nabwey, Abubakar Adamu, and Ojen Kumar Narain. "Double inertial steps extragadient-type methods for solving optimal control and image restoration problems." AIMS Mathematics 9, no. 5 (2024): 12870–905. http://dx.doi.org/10.3934/math.2024629.

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<abstract><p>In order to approximate the common solution of quasi-nonexpansive fixed point and pseudo-monotone variational inequality problems in real Hilbert spaces, this paper presented three new modified sub-gradient extragradient-type methods. Our algorithms incorporated viscosity terms and double inertial extrapolations to ensure strong convergence and to speed up convergence. No line search methods of the Armijo type were required by our algorithms. Instead, they employed a novel self-adaptive step size technique that produced a non-monotonic sequence of step sizes while also

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Hu, Bo, Bing Zhou, Shanshan Bu, Xinghua Wu, and Baoping Gong. "Holistic Hydraulic Simulation for Pebble Bed Using Porous Media Approach." Energies 17, no. 14 (2024): 3562. http://dx.doi.org/10.3390/en17143562.

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The porous media approach is regarded as an appropriate methodology for hydraulic simulations of complex pebble beds in fusion reactors. In order to determine the parameters (permeability α and inertial loss coefficient C) of the porous media accurately, two methods are proposed: the correction method and the fitting method. In this paper, a single-channel model with sequentially packed pebbles is constructed in order to obtain the pressure drop gradient against superficial velocities. Two methods, the correction method and fitting method, are employed to determine the permeability and inertia

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Harris, D. Lee. "WIND TIDE AND SEICHES IN THE GREAT LAKES." Coastal Engineering Proceedings 1, no. 4 (2000): 3. http://dx.doi.org/10.9753/icce.v4.3.

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Because of the unusually high lake stages of recent years, the Weather Bureau was called on to forecast the short period variations of lake level, which were believed to be caused by wind stress and atmospheric pressure gradient. It became necessary to investigate the feasibility of such forecasts. In a review of the available literature, many papers were found which described methods of computing the free periods of oscillation for lakes when no external forces were acting. Other papers were found which described methods of computing the steady state relation between a constant atmospheric fo

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Wan, Liang Jin, and Chun Dong. "Application of Rotation Vector in SINS Algorithms." Applied Mechanics and Materials 615 (August 2014): 229–35. http://dx.doi.org/10.4028/www.scientific.net/amm.615.229.

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Updating attitude precisely in time is the primary task of strapdown inertial navigation system(SINS) algorithms. This paper mainly studied the application of rotation vector in three different methods of data fusion respectively named linear interpolation, gradient descent and complementary filter for attitude-updating, using low-cost MEMS inertial sensors in SINS. Meanwhile, an idea that the quaternion attitude could be updated by constructing micro-rotation quaternion from rotation vector in the sampling interval is proposed. The idea is based on geometric interpretation of space rotation t

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Xie, Rong, and Chunjun Chen. "Optimized Detection Algorithm for Vertical Irregularities in Vertical Curve Segments." Applied Sciences 14, no. 22 (2024): 10753. http://dx.doi.org/10.3390/app142210753.

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The vertical curve is designed to smooth sudden gradient changes in the longitudinal profile, enhancing train operational safety and passenger comfort. However, dynamic detection in these segments has consistently encountered issues with long-wavelength vertical irregularities exceeding tolerance limits. To investigate the root causes of this phenomenon and develop a targeted solution, a comprehensive vehicle-track dynamics simulation model was first constructed, based on the design principles for intercity railway vertical curves. The inertial reference method was then applied to process the

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Kaewyong, Nattakarn, and Kanokwan Sitthithakerngkiet. "An Inertial Extragradient Direction Method with Self-Adaptive Step Size for Solving Split Minimization Problems and Its Applications to Compressed Sensing." Mathematics 10, no. 6 (2022): 874. http://dx.doi.org/10.3390/math10060874.

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The purpose of this work is to construct iterative methods for solving a split minimization problem using a self-adaptive step size, conjugate gradient direction, and inertia technique. We introduce and prove a strong convergence theorem in the framework of Hilbert spaces. We then demonstrate numerically how the extrapolation factor (θn) in the inertia term and a step size parameter affect the performance of our proposed algorithm. Additionally, we apply our proposed algorithms to solve the signal recovery problem. Finally, we compared our algorithm’s recovery signal quality performance to tha

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21

Rehman, Habib ur, Poom Kumam, Ioannis K. Argyros, Nasser Aedh Alreshidi, Wiyada Kumam, and Wachirapong Jirakitpuwapat. "A Self-Adaptive Extra-Gradient Methods for a Family of Pseudomonotone Equilibrium Programming with Application in Different Classes of Variational Inequality Problems." Symmetry 12, no. 4 (2020): 523. http://dx.doi.org/10.3390/sym12040523.

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The main objective of this article is to propose a new method that would extend Popov’s extragradient method by changing two natural projections with two convex optimization problems. We also show the weak convergence of our designed method by taking mild assumptions on a cost bifunction. The method is evaluating only one value of the bifunction per iteration and it is uses an explicit formula for identifying the appropriate stepsize parameter for each iteration. The variable stepsize is going to be effective for enhancing iterative algorithm performance. The variable stepsize is updating for

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Choi, Man Ho, Robert Porter, and Bijan Shirinzadeh. "Comparison of Attitude Determination Methodologies for Implementation with 9DOF, Low Cost Inertial Measurement Unit for Autonomous Aerial Vehicles." International Journal of Intelligent Mechatronics and Robotics 3, no. 2 (2013): 1–15. http://dx.doi.org/10.4018/ijimr.2013040101.

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The performances of three attitude determination algorithms are compared in this paper. The three methods are the Complementary Filter, a Quaternion-based Kalman Filter and a Quaternion-based Gradient Descent Algorithm. An analysis of their performance based on an experimental investigation was undertaken. This paper shows that the Complementary Filter requires the least computational power; Quaternion-based Kalman Filter has the best noise filtering ability; and the Quaternion-based Gradient Descent Algorithm produced estimates with the highest accuracy. As many attitude determination methodo

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Lee, Jae-Neung, Yeong-Hyeon Byeon, and Keun-Chang Kwak. "Design of Ensemble Stacked Auto-Encoder for Classification of Horse Gaits with MEMS Inertial Sensor Technology." Micromachines 9, no. 8 (2018): 411. http://dx.doi.org/10.3390/mi9080411.

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This paper discusses the classification of horse gaits for self-coaching using an ensemble stacked auto-encoder (ESAE) based on wavelet packets from the motion data of the horse rider. For this purpose, we built an ESAE and used probability values at the end of the softmax classifier. First, we initialized variables such as hidden nodes, weight, and max epoch using the options of the auto-encoder (AE). Second, the ESAE model is trained by feedforward, back propagation, and gradient calculation. Next, the parameters are updated by a gradient descent mechanism as new parameters. Finally, once th

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Lu, Zhenglong, Jie Li, Xi Zhang, et al. "A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System." Sensors 20, no. 2 (2020): 512. http://dx.doi.org/10.3390/s20020512.

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The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations—also called double-vectors—have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which

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Kozlov, N. V., E. A. Mosheva, and A. V. Shmyrov. "Visualization of hydrodynamic and physico-chemical processes in rotating and vibrating containers." Journal of Physics: Conference Series 2127, no. 1 (2021): 012004. http://dx.doi.org/10.1088/1742-6596/2127/1/012004.

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Abstract Variable inertial fields are an efficient way to control the behaviour of hydrodynamic systems. Forces of inertia can be used, for example, to stabilize or destabilize systems with an interface or density gradient, to mix multiphase or non-isothermal fluids. The implementation of this approach means that liquids fill the periodically moving containers. In this paper, the situations are considered when the containers perform either rotation or translational vibrations. Methods for measuring the density and velocity fields of convective flows in reacting hydrodynamic systems are describ

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Shuttleworth, Matthew Peter, Oliver Vickers, Mackenzie Smeeton, et al. "Inertial Tracking System for Monitoring Dual Mobility Hip Implants In Vitro." Sensors 23, no. 2 (2023): 904. http://dx.doi.org/10.3390/s23020904.

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Dual mobility (DM) implants are being increasingly used for total hip arthroplasties due to the additional range of motion and joint stability they afford over more traditional implant types. Currently, there are no reported methods for monitoring their motions under realistic operating conditions while in vitro and, therefore, it is challenging to predict how they will function under clinically relevant conditions and what failure modes may exist. This study reports the development, calibration, and validation of a novel inertial tracking system that directly mounts to the mobile liner of DM

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Jabbari, Aidin, Leon Boegman, Reza Valipour, Danielle Wain, and Damien Bouffard. "Dissipation of Turbulent Kinetic Energy in the Oscillating Bottom Boundary Layer of a Large Shallow Lake." Journal of Atmospheric and Oceanic Technology 37, no. 3 (2020): 517–31. http://dx.doi.org/10.1175/jtech-d-19-0083.1.

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AbstractMixing rates and biogeochemical fluxes are commonly estimated from the rate of dissipation of turbulent kinetic energy ε as measured with a single instrument and processing method. However, differences in measurements of ε between instruments/methods often vary by one order of magnitude. In an effort to identify error in computing ε, we have applied four common methods to data from the bottom boundary layer of Lake Erie. We applied the second-order structure function method (SFM) to velocity measurements from an acoustic Doppler current profiler, using both canonical and anisotropy-adj

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Ding, Lin, Sajad Razavi Bazaz, Timothy Hall, Graham Vesey, and Majid Ebrahimi Warkiani. "Giardia purification from fecal samples using rigid spiral inertial microfluidics." Biomicrofluidics 16, no. 1 (2022): 014105. http://dx.doi.org/10.1063/5.0069406.

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Giardia is one of the most common waterborne pathogens causing around 200 × 106 diarrheal infections annually. It is of great interest to microbiological research as it is among the oldest known eukaryotic cells. Purifying Giardia from fecal samples for both research and diagnostic purposes presents one of the most difficult challenges. Traditional purification methods rely on density gradient centrifugation, membrane-based filtration, and sedimentation methods, which suffer from low recovery rates, high costs, and poor efficiency. Here, we report on the use of microfluidics to purify Giardia

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Longo, Umile Giuseppe, Sergio De Salvatore, Martina Sassi, Arianna Carnevale, Giovanna De Luca, and Vincenzo Denaro. "Motion Tracking Algorithms Based on Wearable Inertial Sensor: A Focus on Shoulder." Electronics 11, no. 11 (2022): 1741. http://dx.doi.org/10.3390/electronics11111741.

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Shoulder Range of Motion (ROM) has been studied with several devices and methods in recent years. Accurate tracking and assessment of shoulder movements could help us to understand the pathogenetic mechanism of specific conditions in quantifying the improvements after rehabilitation. The assessment methods can be classified as subjective and objective. However, self-reported methods are not accurate, and they do not allow the collection of specific information. Therefore, developing measurement devices that provide quantitative and objective data on shoulder function and range of motion is imp

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Tahir, Sheikh Badar ud din, Abdul Basit Dogar, Rubia Fatima, et al. "Stochastic Recognition of Human Physical Activities via Augmented Feature Descriptors and Random Forest Model." Sensors 22, no. 17 (2022): 6632. http://dx.doi.org/10.3390/s22176632.

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Human physical activity recognition from inertial sensors is shown to be a successful approach for monitoring elderly individuals and children in indoor and outdoor environments. As a result, researchers have shown significant interest in developing state-of-the-art machine learning methods capable of utilizing inertial sensor data and providing key decision support in different scenarios. This paper analyzes data-driven techniques for recognizing human daily living activities. Therefore, to improve the recognition and classification of human physical activities (for example, walking, drinking

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D’Asaro, Eric A., and Ren-Chieh Lien. "Measurement of Scalar Variance Dissipation from Lagrangian Floats." Journal of Atmospheric and Oceanic Technology 24, no. 6 (2007): 1066–77. http://dx.doi.org/10.1175/jtech2031.1.

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Simultaneous measurements of temperature, salinity, their vertical gradients, and the vertical gradient of velocity across a 1.4-m-long Lagrangian float were used to investigate the accuracy with which the dissipation of scalar variance χ can be computed using inertial subrange methods from such a neutrally buoyant float. The float was deployed in a variety of environments in Puget Sound; χ varied by about 3.5 orders of magnitude. A previous study used an inertial subrange method to yield accurate measurements of ε, the rate of dissipation of kinetic energy, from this data. Kolmogorov scaling

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Bussaban, Limpapat, Attapol Kaewkhao, and Suthep Suantai. "Inertial s-iteration forward-backward algorithm for a family of nonexpansive operators with applications to image restoration problems." Filomat 35, no. 3 (2021): 771–82. http://dx.doi.org/10.2298/fil2103771b.

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Image restoration is an important branch of image processing which has been studied extensively while there are several methods to solve this problem by many authors with the challenges of computational speed and accuracy of algorithms. In this paper, we present two methods, called ?Inertial S-iteration forward-backward algorithm (ISFBA)? and ?A fast iterative shrinkage-thresholding algorithm-Siteration (FISTA-S)?, for finding an approximate solution of least absolute shrinkage and selection operator problem by using a special technique in fixed point theory and prove weak convergence of the p

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Afanasyev, Y. D., P. B. Rhines, and E. G. Lindahl. "Emission of Inertial Waves by Baroclinically Unstable Flows: Laboratory Experiments with Altimetric Imaging Velocimetry." Journal of the Atmospheric Sciences 65, no. 1 (2008): 250–62. http://dx.doi.org/10.1175/2007jas2336.1.

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Abstract Results from new experiments on baroclinic instability of a coastal jet demonstrate that this almost balanced flow spontaneously emits inertial waves when the Rossby radius of deformation is relatively small such that the characteristics of baroclinic meanders match the dispersion relation for the inertial waves. The energy of the waves is small compared to the energy of the flow. A single event of wave emission is identified in the experiment with larger radius of deformation and is interpreted in terms of vorticity dynamics. The flows are generated on a laboratory polar β plane wher

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Pogorilov, Sergij Yurijovich, and Valerij Lvovich Khavin. "Modeling of the thermal regime of a platformless navigation system with thermal stabilization of accelerated warm-up." Bulletin of the National Technical University «KhPI» Series: Dynamics and Strength of Machines, no. 1 (December 31, 2022): 74–80. http://dx.doi.org/10.20998/2078-9130.2022.1.265440.

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Currently, platformless inertial navigation systems (IBS) based on fiber optic gyroscopes (FOG) are widely used in modern aviation and space technology. In connection with the high sensitivity of VOG to the influence of temperature changes, ensuring stable thermal modes of operation is an urgent problem. The most important task of increasing the accuracy of system operation is the development of methods of thermal protection and thermostabilization of VOG. The work is devoted to the modeling of the temperature field of the platformless inertial unit (BIB), which is part of the BINS, in order t

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Lukyanov, Alexander V., Stanislav M. Orlov, and Boris R. Romanenko. "Study of the characteristics of the ascending vortex of the cyclone and the concentration of dust along its section." Vestnik MGSU, no. 8 (August 2021): 1034–44. http://dx.doi.org/10.22227/1997-0935.2021.8.1034-1044.

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Introduction. Protection of the atmosphere is a social and economic problem inextricably linked with the task of creating comfortable conditions for human life and work. Cyclones are the most typical representatives of dry inertial dust collectors. This work is aimed at reducing energy consumption when cleaning gas with cyclones.  Materials and methods. In the course of the work, analytical and experimental research methods were applied.  Results. Analytical dependences of the aerodynamics of the ascending cyclone vortex have been obtained, which showed that the ascendi

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Luce, Hubert, Lakshmi Kantha, Hiroyuki Hashiguchi, and Dale Lawrence. "Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data." Atmosphere 10, no. 7 (2019): 384. http://dx.doi.org/10.3390/atmos10070384.

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Turbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) Observatory during two ShUREX (Shigaraki UAV Radar Experiment) campaigns in 2016 and 2017. The practical processing methods used for estimating turbulence kinetic energy dissipation rate ε and temperature structure function parameter C T 2 from one-dimensional wind and temperature frequency spectra a

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Kim, Yong-Gyun, Sungjoon Kim, Jae Hyeon Park, et al. "Explainable Deep-Learning-Based Gait Analysis of Hip–Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression." Sensors 24, no. 14 (2024): 4504. http://dx.doi.org/10.3390/s24144504.

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Accurate prediction of scoliotic curve progression is crucial for guiding treatment decisions in adolescent idiopathic scoliosis (AIS). Traditional methods of assessing the likelihood of AIS progression are limited by variability and rely on static measurements. This study developed and validated machine learning models for classifying progressive and non-progressive scoliotic curves based on gait analysis using wearable inertial sensors. Gait data from 38 AIS patients were collected using seven inertial measurement unit (IMU) sensors, and hip–knee (HK) cyclograms representing inter-joint coor

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Wang, Zihui, Xianghong Cheng, and Jingjing Du. "Thermal Modeling and Calibration Method in Complex Temperature Field for Single-Axis Rotational Inertial Navigation System." Sensors 20, no. 2 (2020): 384. http://dx.doi.org/10.3390/s20020384.

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Single-axis rotational inertial navigation systems (single-axis RINSs) are widely used in high-accuracy navigation because of their ability to restrain the horizontal axis errors of the inertial measurement unit (IMU). The IMU errors, especially the biases, should be constant during each rotation cycle that is to be modulated and restrained. However, the temperature field, consisting of the environment temperature and the power heating of single-axis RINS, affects the IMU performance and changes the biases over time. To improve the precision of single-axis RINS, the change of IMU biases caused

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Rabb, Ethan, and John Josiah Steckenrider. "Walking Trajectory Estimation Using Multi-Sensor Fusion and a Probabilistic Step Model." Sensors 23, no. 14 (2023): 6494. http://dx.doi.org/10.3390/s23146494.

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This paper presents a framework for accurately and efficiently estimating a walking human’s trajectory using a computationally inexpensive non-Gaussian recursive Bayesian estimator. The proposed framework fuses global and inertial measurements with predictions from a kinematically driven step model to provide robustness in localization. A maximum a posteriori-type filter is trained on typical human kinematic parameters and updated based on live measurements. Local step size estimates are generated from inertial measurement units using the zero-velocity update (ZUPT) algorithm, while global mea

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Rehman, Habib ur, Poom Kumam, Ioannis K. Argyros, Wejdan Deebani, and Wiyada Kumam. "Inertial Extra-Gradient Method for Solving a Family of Strongly Pseudomonotone Equilibrium Problems in Real Hilbert Spaces with Application in Variational Inequality Problem." Symmetry 12, no. 4 (2020): 503. http://dx.doi.org/10.3390/sym12040503.

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In this paper, we propose a new method, which is set up by incorporating an inertial step with the extragradient method for solving a strongly pseudomonotone equilibrium problems. This method had to comply with a strongly pseudomonotone property and a certain Lipschitz-type condition of a bifunction. A strong convergence result is provided under some mild conditions, and an iterative sequence is accomplished without previous knowledge of the Lipschitz-type constants of a cost bifunction. A sufficient explanation is that the method operates with a slow-moving stepsize sequence that converges to

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Zhang, Xin, Zihan Song, Do-Myung Park, and Byung-Kwon Park. "An IMU-Based Machine Learning System for Container Collision Position Identification." Journal of Marine Science and Engineering 13, no. 6 (2025): 1144. https://doi.org/10.3390/jmse13061144.

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The accurate identification of collision positions on containers is critical in logistics and trade for enhancing cargo safety and determining accident liability. Traditional visual inspection methods are labor-intensive, time-consuming, and costly. This study leverages data from an Inertial Measurement Unit sensor and evaluates combinations of machine learning models and feature selection methods to identify the optimal approach for collision position detection. Five machine learning models (decision tree, k-nearest neighbors, support vector machine, random forest, and extreme gradient boosti

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Milam, Gary, Baijun Xie, Runnan Liu, et al. "Trainable Quaternion Extended Kalman Filter with Multi-Head Attention for Dead Reckoning in Autonomous Ground Vehicles." Sensors 22, no. 20 (2022): 7701. http://dx.doi.org/10.3390/s22207701.

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Extended Kalman filter (EKF) is one of the most widely used Bayesian estimation methods in the optimal control area. Recent works on mobile robot control and transportation systems have applied various EKF methods, especially for localization. However, it is difficult to obtain adequate and reliable process-noise and measurement-noise models due to the complex and dynamic surrounding environments and sensor uncertainty. Generally, the default noise values of the sensors are provided by the manufacturer, but the values may frequently change depending on the environment. Thus, this paper mainly

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Gadzhiev, I. M., О. G. Barinov, I. N. Myagkova, and S. A. Dolenko. "Using classification methods in forecasting the level of geomagnetic field disturbance based on the <i>Kp<i>-Index." Geomagnetizm i aèronomiâ 64, no. 3 (2024): 441–54. https://doi.org/10.31857/s0016794024030104.

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The paper explores the possibilities of using data classification methods when forecasting time series of the geomagnetic Kp-index by machine learning methods. To classify categories of the Kp-index based on the degree of disturbance, linear and logistic regression, random forest, gradient boosting on top of decision trees, and artificial neural networks of various architectures are used. The results of these methods are compared with a trivial inertial forecast (the statistical indicators of which for problems of this type are always high) at horizons from 3 h to 1 day in 3-h increments. The

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Zhang, Yongli, Kangshuo Li, Kaixuan Zhang, Guangfei Zhu, Zhanpeng Sun, and Jianfang Shi. "Research on the Flow Field Characteristics of the Industrial Elliptical Cyclone Separator." Separations 12, no. 2 (2025): 50. https://doi.org/10.3390/separations12020050.

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A new type of elliptical cyclone separator has been proposed recently, but the flow field characteristics within the industrial device still need to be further investigated. In this paper, the characteristics of the flow field and particle motion inside the circular cyclone and the elliptical cyclone (with a long-to-short axis ratio of 1.2), with the equivalent hydraulic diameter of 300 mm, are comparatively analyzed using CFD methods. The results show that there is a significant change in the flow field distribution of the elliptical cyclone compared to the conventional circular cyclone. The

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Coulaud, O., P. Morel, and J. P. Caltagirone. "Numerical modelling of nonlinear effects in laminar flow through a porous medium." Journal of Fluid Mechanics 190 (May 1988): 393–407. http://dx.doi.org/10.1017/s0022112088001375.

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This paper deals with the introduction of a nonlinear term into Darcy's equation to describe inertial effects in a porous medium. The method chosen is the numerical resolution of flow equations at a pore scale. The medium is modelled by cylinders of either equal or unequal diameters arranged in a regular pattern with a square or triangular base. For a given flow through this medium the pressure drop is evaluated numerically.The Navier-Stokes equations are discretized by the mixed finite-element method. The numerical solution is based on operator-splitting methods whose purpose is to separate t

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AHMAD, ABDULWAHAB, POOM KUMAM, and MURTALA HARUNA HARBAU. "Convergence Theorems for Common Solutions of Nonlinear Problems and Applications." Carpathian Journal of Mathematics 40, no. 2 (2024): 207–41. http://dx.doi.org/10.37193/cjm.2024.02.01.

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In this work, two inertial algorithms for approximating common elements of the sets of solu- tions of three important problems are constructed. The first problem is a generalized mixed equilibrium one involving relaxed monotone mapping, the second is a zero problem of inverse strongly monotone mappings, while the third one is a fixed point problem of a family of relatively nonexpansive mappings. The first algorithm is a shrinking projection type for a common solution of all the three problems. The second is a generalized Alber projection free method for the second and the third problems. Each

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Lateef, Rana Abdulrahman, and Dr Ayad Rodhan Abbas. "A Proposed ConvXGBoost Model for Human Activity Recognition with Multi Optimizers." Webology 19, no. 1 (2022): 1703–15. http://dx.doi.org/10.14704/web/v19i1/web19114.

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The wide use of smartphones and later smartwatches equipped with a set of sensors such as location, motion, and direction blaze the trail for researchers to better recognize human activity. However, researches on using inertial or motion sensors (i.e., accelerometer, gyroscope) for human activity recognition (HAR) has intensified and reside a great confrontation to be faced. Lately, many deep learning methods have been suggested to improve the human activity classification and discrimination performance to reach an optimal accuracy. Therefore, this paper applies a Convolutional eXtreme Gradien

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Prisco, Giuseppe, Maria Agnese Pirozzi, Antonella Santone, et al. "Combining Postural Sway Parameters and Machine Learning to Assess Biomechanical Risk Associated with Load-Lifting Activities." Diagnostics 15, no. 1 (2025): 105. https://doi.org/10.3390/diagnostics15010105.

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Background/Objectives: Long-term work-related musculoskeletal disorders are predominantly influenced by factors such as the duration, intensity, and repetitive nature of load lifting. Although traditional ergonomic assessment tools can be effective, they are often challenging and complex to apply due to the absence of a streamlined, standardized framework. Recently, integrating wearable sensors with artificial intelligence has emerged as a promising approach to effectively monitor and mitigate biomechanical risks. This study aimed to evaluate the potential of machine learning models, trained o

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Sheta, Bassem, Mohamed Elhabiby, and Naser El-Sheimy. "An Assessment of Nonlinear Optimization and Speeded up Robust Features (SURF) Algorithm for Estimating Object Space Transformation Parameters for UAV Pose Estimation." GEOMATICA 66, no. 4 (2012): 307–21. http://dx.doi.org/10.5623/cig2012-056.

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Localizing set of features (with known coordinates) on the ground and finding their matches in the image taken by imaging sensor on the aerial vehicle is the basic concept behind Vision Based Navigation (VBN). The number of matching points necessary for solving the collinearity equation is a critical factor to be investigated while using the VBN approach for navigation. Although a robust scale and rotation invariant image matching algorithm is important for VBN of aerial vehicles, the proper estimation of the collinearity equation object space transformation parameters improves the efficiency

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Thavitchasri, Phummarin, Dechrit Maneetham, and Padma Nyoman Crisnapati. "Intelligent Surface Recognition for Autonomous Tractors Using Ensemble Learning with BNO055 IMU Sensor Data." Agriculture 14, no. 9 (2024): 1557. http://dx.doi.org/10.3390/agriculture14091557.

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This study aims to enhance the navigation capabilities of autonomous tractors by predicting the surface type they are traversing using data collected from BNO055 Inertial Measurement Units (IMU sensors). IMU sensor data were collected from a small mobile robot driven over seven different floor surfaces within a university environment, including tile, carpet, grass, gravel, asphalt, concrete, and sand. Several machine learning models, including Logistic Regression, K-Neighbors, SVC, Decision Tree, Random Forest, Gradient Boosting, AdaBoost, and XGBoost, were trained and evaluated to predict the

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