Search Results (2,014)

To improve the centroid extraction accuracy and efficiency of high-dynamic star sensors, this paper proposes a multi-centroid localization method based on the prior distribution of star trail projections. First, the mapping relationship between attitude information and star trails is constructed based on a geometric imaging model, and an endpoint centroid group extraction strategy is designed from the perspectives of time synchronization and computational complexity. Then, the endpoint position parameters are determined by fitting the star trail grayscale projection using a line spread function, and accurate centroid localization is achieved through principal axis analysis and inter-frame correlation. Finally, the effectiveness of the proposed method under different dynamic scenarios was tested using numerical simulations and semi-physical experiments. The experimental results show that when the three-axis angular velocity reaches 8°/s, the centroid extraction accuracy of the proposed method remains superior to 0.1 pixels, achieving an improvement of over 30% compared to existing methods and simultaneously doubling the attitude measurement frequency. This demonstrates the superiority of this method in high-dynamic attitude measurement tasks. Full article

Rehabilitation of gait function in post-stroke hemiplegic patients is critical for improving mobility and quality of life, requiring a comprehensive understanding of individual gait patterns. Previous studies on gait analysis using unsupervised clustering often involve manual feature extraction, which introduces limitations such as low accuracy, low consistency, and potential bias due to human intervention. This cross-sectional study aimed to identify and cluster gait patterns using an end-to-end deep learning approach that autonomously extracts features from joint angle trajectories for a gait cycle, minimizing human intervention. A total of 74 sub-acute post-stroke hemiplegic patients with lower limb impairments were included in the analysis. The dataset comprised 219 sagittal plane joint angle and angular velocity trajectories from the hip, knee, and ankle joints during gait cycles. Deep temporal clustering was employed to cluster them in an end-to-end manner by simultaneously optimizing feature extraction and clustering, with hyperparameter tuning tailored for kinematic gait cycle data. Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. To clarify the characteristics of the selected groups, in-depth statistics of spatiotemporal, kinematic, and clinical features are presented in the results. The results demonstrate the effectiveness of end-to-end deep learning-based clustering, yielding significant performance improvements without the need for manual feature extraction. While this study primarily utilizes sagittal plane data, future analysis incorporating coronal and transverse planes as well as muscle activity and gait symmetry could provide a more comprehensive understanding of gait patterns. Full article

Locomotives are important vehicles, which serve for towing wagons, i.e., trains. Many factors influence the safe and cost-effective operation of locomotives and trains in general. One of these factors is adhesion at the wheel/rail contact. The adhesion determines how much power the locomotive can deliver and how the braking system will ensure that the train stops. The main way to improve adhesion is to use sand at the wheel/rail contact point. The aim of this study is to improve the efficiency of the sand system of the locomotive. For this purpose, a new sand system nozzle mounting design was proposed. The newly proposed sanding system is equipped with a nozzle mounted to the axlebox unlike the original one, which uses the nozzle attached to the bogie frame. To compare the proposed and existing design, simulation calculations were performed in Simpack software 2024.3. For the simulation computation of the locomotive bogie, two types of railway tracks were chosen. A straight track section with two angular frequencies and three amplitudes of track irregularities was created, and a real track section corresponding to several kilometers of track was modeled in the Simpack software. During the simulations, it was determined that the proposed nozzle mounting design has a smaller amplitude of motion, compared to the existing one; therefore, there is a more accurate and efficient operation of the sand system. This in turn has a favorable effect on the adhesion of the wheel with the rail. It was found out that the newly designed sanding system has a significant positive economic effect regarding saving sand. There is no sand loss during sandblasting compared with the original sanding system. This directly relates to saving costs during locomotive operation. Full article

Positron physical-chemistry has been one important focus of scientific investigation of the last decades, however their low energy scattering by atoms and molecules still offers many questions to be answered, as the low angle scattering effects on the measured cross sections and how the degree of target polarization manifest in the comparison between theoretical and experimental results. In this work, we investigate low energy positron collisions by H₂ molecules, with particular attention to the convergence of the polarization contribution on the scattering potential. The interaction between positron and molecule was represented by a model potential conceived from the composition of a free electron gas correlation term with an asymptotic polarization potential, obtained from perturbation theory. In particular, we investigated how polarization effects beyond the second order perturbation affect the scattering observables. Our results show that the model which includes up to the quadrupole polarization contribution presents better agreement to the recent experimental data when corrected for forward scattering effects, since they were measured from a transmission beam technique. The angular distributions were also examined through the comparison between our results to the folded differential cross sections measurements available in the literature. We propose a simple correction scheme to the experimental folded differential cross sections for energies below 1 eV which then, as we argue, favorably compares to the quadrupole polarization model. Finally, the comparison between our phase shifts and scattering lengths with recent full many body ab initio results that explicitly include virtual positronium effects suggests that these are intrisically included in the adopted model correlation potential. Full article

The branch of physics known as magnetohydrodynamics (MHD) emerged in the middle of the 20th century. MHD models, being substantially nonlinear, are quite challenging for theoretical study and allow nontrivial consideration only in particular limited cases. Thus, due to the exceptional growth of calculation power, research on MHD is now primarily concentrated on numerical modeling. The achievements are considerable; however, there is a possibility of overlooking some phenomena or missing an optimal approach to modeling and calculating that could be identified with theoretical guidance. The paper presents a theoretical study of a particular class of boundary and initial conditions. The flow of a viscous, electrically conductive fluid on a rotating plate in the presence of a magnetic field is considered. The fluid and the bounding plate rotate together with a constant angular velocity around an axis that is not perpendicular to the plane. The flow is induced by sudden longitudinal vibrations of the plate, injection (suction) of the medium through the plate, and an applied magnetic field directed normal to the plate. The full equation of magnetic induction is used, taking into account both the induction effect and energy dissipation due to the flow of electric currents. An analytical solution of three-dimensional magnetohydrodynamics equations in a half-space bounded by a plate is presented. The solution is given in the form of a superposition of plane waves propagating with certain wave numbers along the y-coordinate axis. For certain regions of system parameters, the vibration of the bounding plate does not cause waves in the media. Full article

Portable monitoring devices based on Inertial Measurement Units (IMUs) have the potential to serve as quantitative assessments of human movement. This article proposes a new method to identify the optimal placements of the IMUs and quantify the smoothness of the gait. First, it identifies gait events: foot-strike (FS) and foot-off (FO). Second, it segments the signals of linear acceleration and angular velocities obtained from the IMUs at four locations into steps and strides. Finally, it applies three smoothness metrics (SPARC, PM, and LDLJ) to determine the most reliable metric and the best location for the sensor, using data from 20 healthy subjects who walked an average of 25 steps on a flat surface for this study (117 measurements were processed). All events were identified with less than a 2% difference from those obtained with the photogrammetry system. The smoothness metric with the least variance in all measurements was SPARC. For the smoothness metrics with the least variance, we found significant differences between applying the metrics with the complete signal (C) and the signal segmented by strides (S). This method is practical, time-effective, and low-cost in terms of computation. Furthermore, it is shown that analyzing gait signals segmented by strides provides more information about gait progression. Full article

The research presented by the author investigates a polyatomic reaction occurring in the gas phase. This study employs the Quasi-Classical Trajectory (QCT) approach using the Wu–Schatz–Lendvay–Fang–Harding (WSLFH) potential energy surface (PES), recognized as one of the most reliable PES models for this type of analysis. The substantial sample size enables the derivation of detailed results that corroborate previous findings while also identifying potential objectives for future experimental work. The Gaussian Binning (GB) technique is utilized to more effectively highlight the variation in the total angular momentum (J′) of the excited product molecule, HOD*. A key aim of the study is to explore the reaction dynamics due to their importance in excitation and emission processes, which may contribute to the development of a chemical laser based on this reaction. Increasing the vibrational level, v, of one reactant, D₂, significantly enhances the excitation of HOD* and shifts the P(J′) distributions towards higher J′ values, while also broadening the distribution. Although the current research focuses on a few initial conditions, the author plans to extend the study to encompass a wider range of initial conditions within the reaction chamber of this type of chemical laser. Full article

In this analysis, we investigate hydrogen and pionic atoms subjected to Dirac and Klein-Gordon oscillators, respectively, in the global monopole spacetime. Through a purely analytical analysis, we determine solutions of bound state, in which we define the allowed energy values for the lowest energy state of both proposed systems. In addition to the influence of the topological defect on the results obtained, we note another quantum effect: the oscillation frequencies of both systems depend on the system quantum numbers, that is, the angular frequencies are quantized. Full article

Drainage pipelines face significant threats to underground safety due to external defects. Ground Penetrating Radar (GPR) is a primary tool for detecting such defects from within the pipeline. However, existing methods are limited to single or multiple axial scan lines, which cannot provide the precise spatial coordinates of the defects. To address this limitation, this study introduces a novel GPR-based drainage pipeline inspection robot system integrated with multiple sensors. The system incorporates MEMS-IMU, encoder modules, and ultrasonic ranging modules to control the GPR antenna for axial and circumferential scanning. A novel Cross-Line Fusion of GPR (CLF-GPR) method is introduced to integrate axial and circumferential scan data for the precise localization of external pipeline defects. Laboratory simulations were performed to assess the effectiveness of the proposed technology and method, while its practical applicability was further validated through real-world drainage pipeline inspections. The results demonstrate that the proposed approach achieves axial positioning errors of less than 2.0 cm, spatial angular positioning errors below 2°, and depth coordinate errors within 2.3 cm. These findings indicate that the proposed approach is reliable and has the potential to support the transparency and digitalization of urban underground drainage networks. Full article

This study aimed to evaluate the efficacy of various nickel–titanium (Ni-Ti) root canal instrumentation systems in preserving root canal anatomy, focusing on their capacity to limit changes in canal angulation. One hundred canals in fifty extracted human molars were prepared with different techniques: Step-Back, Reciproc, MTwo, ProTaper Universal (PTU), and ProTaper Next (PTN). The curvature of each canal was measured before and after treatment using Schneider’s methodology, a widely accepted method for assessing canal curvature. Descriptive and statistical analyses, including the Kruskal–Wallis test, were employed to compare angular changes across the systems. The results indicated that all techniques effectively reduced canal curvature, with each system exhibiting a reduction in mean canal angle after instrumentation. Although the Reciproc system showed the smallest mean change in angulation, no statistically significant differences were identified between any of the systems (p = 0.182). This finding suggests that while minor differences in performance may exist, they do not translate into clinically meaningful distinctions in preserving root canal anatomy. The Reciproc system’s slight advantage aligns with other studies, highlighting its conservative design and minimal dentinal stress; however, its superiority was not statistically validated in this study. The results suggest that all five systems are clinically comparable in preserving root canal anatomy, highlighting that dentists can choose from these widely available techniques without compromising anatomical preservation. While this study had limitations, including a relatively small sample size and an in vitro design, it aligns with previous findings on the mechanical behavior of Ni-Ti systems in endodontic practice. Full article

Motion control of modern and advanced aircraft has to be provided under conditions of incomplete and inaccurate knowledge of their parameters and characteristics, possible flight modes, and environmental influences. In addition, various abnormal situations may occur during flight, in particular, equipment failures and structural damage. These circumstances cause the problem of a rapid adjustment of the used control laws so that the control system can adapt to the mentioned changes. However, most adaptive control schemes have a model of the control object, which plays a crucial role in adjusting the control law. That is, it is required to solve also the identification problem for dynamical systems. We propose an approach to solving the above-mentioned problems based on artificial neural networks (ANNs) and hybrid technologies. In the class of traditional neural network technologies, we use recurrent neural networks of the NARX type, which allow us to obtain black-box models for controlled dynamical systems. It is shown that in a number of cases, in particular, for control objects with complicated dynamic properties, this approach turns out to be inefficient. One of the possible alternatives to this approach, investigated in the paper, consists of the transition to hybrid neural network models of the gray box type. These are semi-empirical models that combine in the resulting network structure both empirical data on the behavior of an object and theoretical knowledge about its nature. They allow solving with high accuracy the problems inaccessible by the level of complexity for ANN models of the black-box type. However, the process of forming such models requires a very large consumption of computational resources. For this reason, the paper considers another variant of the hybrid ANN model. In it, the hybrid model consists not of the combination of empirical and theoretical elements, resulting in a recurrent network of a special kind, but of the combination of elements of feedforward networks and recurrent networks. Such a variant opens up the possibility of involving deep learning technology in the construction of motion models for controlled systems. As a result of this study, data were obtained that allow us to evaluate the effectiveness of two variants of hybrid neural networks, which can be used to solve problems of modeling, identification, and control of aircraft. The capabilities and limitations of these variants are demonstrated on several examples. Namely, on the example of the problem of aircraft longitudinal angular motion, the possibilities of modeling the motion using the NARX network as applied to a supersonic transport aircraft (SST) are first considered. It is shown that under complicated operating conditions this network does not always provide acceptable modeling accuracy. Further, the same problem, but applied to a maneuverable aircraft, as a more complex object of modeling and identification, is solved using both a NARX network (black box) and a semi-empirical model (gray box). The significant advantage of the gray box model over the black box one is shown. The capabilities of the hybrid model realizing deep learning technologies are demonstrated by forming a model of the control object (SST) and neurocontroller on the example of the MRAC adaptive control scheme. The efficiency of the obtained solution is illustrated by comparing the response of the control object with a failure situation (a decrease in the efficiency of longitudinal control by 50%) with and without adaptation. Full article

In the last decade, substantial progress has been made to improve the performance of optical gyroscopes for inertial navigation applications in terms of critical parameters such as bias stability, scale factor stability, and angular random walk (ARW). Specifically, resonant fiber optic gyroscopes (RFOGs) have emerged as a viable alternative to widely popular interferometric fiber optic gyroscopes (IFOGs). In a conventional RFOG, a single-wavelength laser source is used to generate counter-propagating waves in a ring resonator, for which the phase difference is measured in terms of the resonant frequency shift to obtain the rotation rate. However, the primary limitation of RFOG performance is the bias drift, which can be attributed to nonreciprocal effects such as Rayleigh backscattering, back-reflections, polarization instabilities, Kerr nonlinearity, and environmental fluctuations. In this paper, we review the challenges and opportunities of achieving performance enhancement in RFOGs. Full article

A novel hybrid Severe Plastic Deformation (SPD) method called Vortex Extrusion–Equal-Channel Angular Pressing (Vo-CAP) was developed and applied to AA6082 workpieces in this study. Before experimental application, a comprehensive optimization of the die design was performed considering effective strain, strain inhomogeneity, and pressing load parameters. The optimization process utilized an integrated approach combining Finite Element Analysis (FEA), artificial neural networks (ANNs), and the non-dominated sorting genetic algorithm II (NSGA-II). The optimized die successfully achieved a balance between maximizing effective strain while minimizing pressing load and strain inhomogeneity. The Vo-CAP process incorporates a unique conical die design that enables assembly without traditional fasteners. Moreover, this novel die combines VE and ECAP advantages in a single-pass operation. While VE has been previously studied, experimental work was limited to specific configurations, and its integration with ECAP had not been explored. Through the development of Vo-CAP, this research gap has been addressed. The results showed substantial enhancements in hardness values, ultimate tensile strength, and strain homogeneity. These findings demonstrate that Vo-CAP represents a significant advancement in SPD, offering an efficient single-pass process for improving the mechanical properties of aluminum alloys through grain refinement. Full article

The cavitation water jet cleaning and coating removal technique represents an innovative sustainable method for cleaning and removing coatings, with the nozzle serving as a crucial component of this technology. Developing an artificially submerged nozzle with a reliable structure and excellent cavitation performance is essential for enhancing cavitation water jets’ cleaning and coating removal efficacy in an atmosphere environment (non-submerged state). This study is based on the shear flow cavitation mechanism of an angular nozzle, the resonance principle of an organ pipe, and the jet pump principle. A dual-nozzle co-current cavitation water jet nozzle structure was designed and manufactured. The impact of the nozzle’s inlet pressure on the vapor volume percentage, as well as the axial and radial velocities inside the flow field, were examined utilizing ANSYS Fluent software with the CFD method. The dynamic change rule of the cavitation cloud is derived by analyzing the picture of the cavitation cloud in the nozzle’s outflow field utilizing pseudo-color imaging techniques. The results show that the maximum vapor volume percentage is more significant than 95% for different inlet pressures in the internal nozzle. The changes that occur in the cavitation cloud exhibit notable regularity, including the four stages of cavitation, which are inception, development, shedding, and collapse. A change period is 1.5 ms, which proves that the homemade co-current cavitation water jet nozzle can achieve good cavitation effects. Full article

Within the framework of noncommutative (NC) deformation of gauge field theory by the angular twist, we first rederive the NC scalar and gauge field model from our previous papers, and then generalize it to the second order in the Seiberg–Witten (SW) map. It turns out that SW expansion is finite and that it ceases at the second order in the deformation parameter, ultimately giving rise to the equation of motion for the scalar field in the Reissner–Nordström (RN) metric that is nonperturbative and exact at the same order. As a further step, we show that the effective metric put forth and constructed in our previous work satisfies the equations of Einstein–Maxwell gravity, but only within the first order of deformation and when the gauge field is fixed by the Coulomb potential of the charged black hole. Thus, the obtained NC deformation of the Reissner–Nordström (RN) metric appears to have an additional off-diagonal element which scales linearly with a deformation parameter. We analyze various properties of this metric. Full article