Tracking Characteristics Research Articles

Modeling and Robust Tracking Decoupling Control of a Coaxial Unmanned Helicopter Based on the Improved Alternating Direction Method of Multipliers.

In this paper, a robust tracking control strategy based on the dynamic feedback linearization method is proposed for the nonlinear and highly coupled dynamic characteristics of coaxial unmanned helicopter. The mathematical model of the coaxial unmanned helicopter is determined by fault analysis. Then the high-order state system is dynamically feedback linearized by extending the state variables, and the dynamic characteristics of the zeros are analyzed according to the expected tracking characteristics of the inner loop. The pole placement of the subsystem realizes robust monitoring of height and position commands by designing robust compensators. On this basis, an outer loop proportional derivative controller is designed for the horizontal positioning subsystem to realize position tracking. Loop tracking simulation ensures the good separation characteristics of feedback linearization method, and trajectory tracking simulation under fault conditions ensures the control ability and durability of the designed controller.

Numerical study of multilayer cold spray additive manufacturing with oblique impacting powders using the SPH method

<p indent="0mm">As a novel solid-state additive manufacturing technique, metal powder cold spray (CS) can rapidly deposit materials and be suitable for large-scale manufacturing of metal structures. Hence, the CS technique has attracted considerable interest in engineering and science. CS involves several complex processes, such as high-velocity impacting of metal powders, large material deformations, phase change, and jetting, which are difficult to simulate accurately. This work employs an improved smoothed particle hydrodynamics (SPH) method to effectively model multilayer CS with oblique impacting powders. The deformation characteristics and bonding effects between powders and a substrate are numerically investigated. Moreover, the multilayer CS processes with multiple impacting powders are analyzed. Results showed that the bonding effects between powders and a substrate under oblique impacting conditions have several differences from that under normal impacting conditions. The separation between powders and cavities can be observed in oblique impacting CS. Furthermore, the entire CS process with the movement of the nozzle has been reproduced by the present SPH method. The geometric characteristics of the powder track in CS with different impacting angles have also been analyzed, which can help develop and improve additive manufacturing techniques.

Phosphate Glass Detectors for Heavy Ion Identification

The problem of the boundaries of the Mendeleev table of chemical elements is closely related to the understanding of the properties of nuclear matter. In this regard, the synthesis of superheavy nuclei on accelerators and the registration of their decay products are of fundamental scientific interest. The Joint Institute of Nuclear Research in Dubna (JINR) conducts research on the synthesis of superheavy nuclei on the new DC-280 cyclotron (the Factory of Superheavy Elements). As part of the development of this experiment, the possibility of using phosphate glass as a material for detectors of heavy and superheavy nuclei is being considered. This issue requires test experiments to study the recording properties of the glass at different irradiation and treatment conditions. The article presents a method for identifying heavy ions in phosphate glass detectors under various conditions by the geometric characteristics of ion tracks. The results obtained indicate the possibility of using the KNFS-3 phosphate glass detectors for registration and identification of accelerated superheavy nuclei.

Comparison of Tools for Digitally Tracking Changes in Text

Tracking changes in digital texts is a longstanding interface challenge, as early digital technologies left no recorded traces of alterations. Currently, two key categories of tools track text changes: code editing and word processing tools. Each has implemented different interface patterns to accomplish several goals: attributing change authorship, tracking the time of change, recording the change action taken, and specifying the location and content of the change. While some visual characteristics of change tracking are consistent across all tools, there are significant differences in change representation divided along the tool-type line, that may reflect their specific cultures of use. Overall, however, there is a limited range of visual methods for representing changes to digital text over time.

Speech Understanding Oppositely Affects Acoustic and Linguistic Neural Tracking in a Speech Rate Manipulation Paradigm.

When listening to continuous speech, the human brain can track features of the presented speech signal. It has been shown that neural tracking of acoustic features is a prerequisite for speech understanding and can predict speech understanding in controlled circumstances. However, the brain also tracks linguistic features of speech, which may be more directly related to speech understanding. We investigated acoustic and linguistic speech processing as a function of varying speech understanding by manipulating the speech rate. In this paradigm, acoustic and linguistic speech processing is affected simultaneously but in opposite directions: When the speech rate increases, more acoustic information per second is present. In contrast, the tracking of linguistic information becomes more challenging when speech is less intelligible at higher speech rates. We measured the EEG of 18 participants (4 male) who listened to speech at various speech rates. As expected and confirmed by the behavioral results, speech understanding decreased with increasing speech rate. Accordingly, linguistic neural tracking decreased with increasing speech rate, but acoustic neural tracking increased. This indicates that neural tracking of linguistic representations can capture the gradual effect of decreasing speech understanding. In addition, increased acoustic neural tracking does not necessarily imply better speech understanding. This suggests that, although more challenging to measure because of the low signal-to-noise ratio, linguistic neural tracking may be a more direct predictor of speech understanding.SIGNIFICANCE STATEMENT An increasingly popular method to investigate neural speech processing is to measure neural tracking. Although much research has been done on how the brain tracks acoustic speech features, linguistic speech features have received less attention. In this study, we disentangled acoustic and linguistic characteristics of neural speech tracking via manipulating the speech rate. A proper way of objectively measuring auditory and language processing paves the way toward clinical applications: An objective measure of speech understanding would allow for behavioral-free evaluation of speech understanding, which allows to evaluate hearing loss and adjust hearing aids based on brain responses. This objective measure would benefit populations from whom obtaining behavioral measures may be complex, such as young children or people with cognitive impairments.

Analysis of Teaching Tactics Characteristics of Track and Field Sports Training in Colleges and Universities Based on Deep Neural Network.

In the analysis of the teaching tactical characteristics of track and field sports training in colleges and universities, the teaching tactical characteristics are not quantified, which leads to the low key degree of determining the influencing factor indicators in colleges and universities, and the error in the evaluation of the teaching tactical characteristics of track and field sports training is large. Therefore, this paper designs a method to analyze the tactical characteristics of college track and field sports training teaching based on deep neural network. Firstly, by analyzing the current situation of track and field sports training teaching in colleges and universities, it determines the areas that need to be improved in teaching. Then, by determining the factors of teaching environment, the core competitiveness of track and field teams, and the teaching ability of track and field coaches, these factors are determined as the key characteristics, the data basis is analyzed, and the unified data quantitative processing is carried out to determine the key factor indexes affecting the analysis of tactical characteristics. Finally, the deep neural network is introduced to construct the evaluation model of the tactical characteristics of college track and field sports training teaching, and the characteristic analysis results are further modified with the help of cascade noise reduction self-encoder to complete the analysis of the tactical characteristics of college track and field sports training teaching. The experimental results show that the proposed method can effectively analyze the teaching tactical characteristics of track and field sports training in colleges and universities and improve the performance of the evaluation of the teaching tactical characteristics of track and field sports training.

Who Is Able to Resist What Is Forbidden?-The Relationship between Health Literacy and Risk Behaviours in Secondary School Students in the Broader Social and Educational Context.

In the last Health Behaviour in School-Aged Children (HBSC) survey conducted in Poland in 2018, a group of 17-year-old adolescents (n = 1663; mean age 17.63 ± 0.36 years) was included outside the international protocol. This allowed an assessment to be made of their level of health literacy (HL) using the 10-point HBSC research tool. The aim of the study was to investigate the relationship between HL and risk behaviours (RB). A standardised index of RB in the last 30 days was considered as an outcome measure. This index was significantly higher in the group with low HL (0.318 ± 1.269) in comparison with the group with high HL (−0.083 ± 0.962). In a multivariate linear regression model, the strongest predictors of RB were gender, academic performance and level of regional deprivation, but the association with HL remained significant. This significant association persisted in general schools and in girls but disappeared in vocational schools and in boys. It was also shown that in rural areas, good academic performance has a less significant impact on RB if the HL level is low. The analyses led to the conclusion that when examining the relationship between HL and RB in older adolescents, it is advisable to take into account gender, the educational track and neighbourhood characteristics.

Data‐driven maintenance planning and scheduling based on predicted railway track condition

AbstractTimely planning and scheduling of railway infrastructure maintenance interventions are crucial for increased safety, improved availability, and reduced cost. We propose a data‐driven decision‐support framework integrating track condition predictions with tactical maintenance planning and operational scheduling. The framework acknowledges prediction uncertainties by using a Wiener process‐based prediction model at the tactical level. We also develop planning and scheduling algorithms at the operational level. One algorithm focuses on cost‐optimisation, and one algorithm considers the multi‐component characteristics of the railway track by grouping track segments near each other for one maintenance activity. The proposed framework's performance is evaluated using track geometry measurement data from a 34 km railway section in northern Sweden, focusing on the tamping maintenance action. We analyse maintenance costs and demonstrate potential efficiency increases by applying the decision‐support framework.

Long-term tracking and population characteristics of lipoprotein (a) in the Cardiovascular Risk in Young Finns Study

Background and aimsLipoprotein (a) (Lp(a)) is a causal risk factor for cardiovascular diseases and its levels are under strict genetic control. Therefore, it is hypothesized that the concentration of Lp(a) remains stable throughout life. Finns have lower Lp(a) levels than central Europeans, but it is unknown whether there are differences within Finland, especially between the eastern and western parts of the country with known genetic duality and persistent differences in cardiovascular disease rates. We have examined the long-term stability of Lp(a) levels over 25 years in the Cardiovascular Risk in Young Finns Study (YFS), and the characteristics of individuals with different Lp(a) levels, including their geographical origin within Finland. MethodsIn YFS, the first large baseline examination was conducted in 1980 (baseline age, 3–18 years). Several follow-ups during the past 40 years have been conducted to investigate the determinants of cardiometabolic health. Lp(a) levels have been measured in study years 1986 (N = 2464, ages 9–24 years), 2001 (N = 2281, ages 24–39 years), 2007 (N = 2204, ages 35–45 years) and 2011 (N = 2044, ages 39–49 years). Tracking of Lp(a) was estimated by calculating Spearman's rank order correlations between the study years, and by cross-tabulating how many individuals diagnosed with either elevated or non-elevated Lp(a) levels in 1986, 2001 and 2007 remained in the same category in the latest follow-up in 2011. ResultsSpearman's correlation coefficients varied between r = 0.84–0.96. Most individuals (87–94%) who had a high Lp(a) level (>30 mg/dl) in any of the previous study years had a high level also in 2011. On average, the median Lp(a) levels were consistently ∼20% higher in the individuals originating from eastern Finland compared to those from western Finland, but there were no differences in the distribution of known genetic determinants between eastern and western Finns that would have explained the observed difference. ConclusionsThese data confirm that Lp(a) levels remain very stable over the life-course. In line with the genetic duality between eastern and western parts of Finland, we observed about 20% higher Lp(a) levels in individuals originating from eastern Finland compared to those originating from western Finland.

An intelligent fault diagnosis framework based on piecewise aggregate approximation, statistical moments, and sparse autoencoder

Rotating machines (RMs) have vast applicability in almost all the industries in mechanical domain. Rolling element bearings (RBs) are the key elements to ensure that the RMs perform efficiently. RBs are highly prone to wear and tear which could have devastating consequences such as massive economic losses and accidents. In the past, many time-domain based condition-indicators such as root mean square (RMS), skewness and kurtosis, etc. have been proposed by researchers to diagnose the bearing faults and prevent RM failures. However, they are often insensitive to early stage faults, affected by outliers and possess poor degradation tracking characteristics. To overcome these shortcomings, this paper proposes a novel statistical feature extraction technique called as multiscale statistical moment (MSM) analysis, in combination with sparse autoencoder to detect the incipient faults as well as track the progression of wear. Firstly, the vibration signal are acquired from the bearings to be monitored. Secondly, the MSM features are extracted from the vibration signals. Thirdly, the MSM features corresponding to normal conditions are utilized to train the sparse autoencoder network. Fourthly, the MSM features corresponding to test conditions are supplied to the pre-trained sparse autoencoder model. The MSM technique offers the advantage that it extracts the fault properties contained in multiple time-scales of the vibration signals instead of a single time-scale only. Finally, the dissimilarity between the actual and predicted output is measured to obtain the bearing health indicator (BHI). The experimental results demonstrate that the suggested BHI detects the faults at early stages, possess better sensitivity and trends the bearing degradation more accurately as compared to the traditional techniques such as RMS, kurtosis, and BHI obtained with statistical moment features at single-scale only.

Wind wave footprint of tropical cyclones from satellite data

AbstractTropical cyclones are associated with extreme winds, waves, and storm surge, being among most destructive natural phenomena. Developing capability for a rapid impact estimate is crucial for coastal applications and risk preparedness. When predicting waves characteristics associated to tropical cyclones, the traditional approach involves a two‐step procedure (a) a Holland‐type wind vortex model and (b) numerical simulations using a wave generation model, using buoy and satellite measurements for validation. In this work, we take advantage of the increasing amount of remote sensing observational data and propose a new empirical model to estimate the wind wave footprint of tropical cyclones. For this purpose, we construct a dataset with over a million satellite observations of waves triggered by tropical cyclones assuming a circular shape of the TC influence area and defining composites of significant wave height as a function of representative parameters of the track characteristics like the minimum pressure, its forward velocity, and its latitude. The validation against buoy data confirms the usefulness of the model for a first and rapid estimation of the wave footprint, although an underestimation of the most extreme events is observed due to the relatively small number of observations recorded. Due to its efficiency, the model can be applied for rapid estimations of wave footprints in operational systems, reconstruction of historical or synthetic events and risk assessments.

Single Track Geometry Prediction of Laser Metal Deposited 316L-Si Via Multi-Physics Modelling and Regression Analysis with Experimental Validation

Laser metal deposition (LMD) is an additive manufacturing process used in manufacturing freeform geometries, repair applications, coating and surface modification, fabrication of functionally graded materials. It has a broad range of applications in various industries, including aviation, space, defence, automotive, tooling, etc. In this work, a multi-physics model of the LMD process was developed to rapidly predict the geometrical characteristics of the single clad track using the commercial software package Flow-3D. The volume of fluid (VOF) method was integrated to differentiate the interface between the metallic and gaseous cells. To validate the numerical model single bead tracks were deposited, and cross-sections of the beads were analysed. Mathematical formulae to predict different aspects of the single clad track (height, width, and depth) were derived using regression analysis. The influence of the process parameters on the geometrical characteristics of the single clad track was analysed in detail using analysis of variance (ANOVA). Both multi-physics model and mathematical regression model results were compared to the experimental measurements. The results were in good agreement with the experimental results.Graphical abstract

Physiotherapists could detect changes of 12 degrees or more in single-plane movement when observing forward bending, squat or hand-over-head: A cross-sectional experiment

BackgroundThe visual accuracy of physiotherapists to detect changes in dynamic joint angles is currently unknown. ObjectiveTo investigate (i) the smallest detectable change in movement that physiotherapists could visually observe, and (ii) whether visual accuracy was associated with the functional activity observed or characteristics of the physiotherapist. MethodsThirty-four physiotherapists viewed and rated videos of squat, hand-over-head, forward bend functional activities and an artificial test condition (a reference movement followed by subsequent movements showing random differences in peak angle from 0° to 15°, so 18 sets of paired videos per functional activity). They rated each range of movement (same/more/less) relative to the reference movement, while their visual tracking was continuously monitored. Accuracy was calculated (multilevel regression) using two thresholds – two correct out of three viewings (2/3) and three correct out of three viewings (3/3). ResultsMore than 80% of physiotherapists were able to detect 9° difference using the 2/3 threshold and 12° using the 3/3 threshold. There was no association (p > 0.05) between visual accuracy and experience, sex, or movement type, except when viewing shoulder abduction compared with knee flexion using the 3/3 threshold. The only association between accuracy and visual tracking characteristics was for assessing lumbar flexion, where use of more visual fixation areas and a shorter fixation time per area were more accurate. ConclusionPhysiotherapists were consistently accurate at detecting changes of ≥12° in single-plane, low-speed functional activities. Visual accuracy was not explained by experience or sex, and rarely associated with functional activity type or visual fixation.

Microgrid Inverter Control Strategy Based on Virtual Synchronous Generator

Study the control strategy of distributed power supply grid-connected based on virtual synchronous generator. Establish the mathematical model of the inverter grid connection and the mathematical model of the virtual synchronous generator control scheme. Study the grid-connected active and reactive power regulation scheme, and analyze the influence of inertia and damping parameters on grid-connected power tracking in detail. A self-synchronous control strategy without phase-locked loop is designed, which simulates the characteristics of synchronous generator’s speed regulation system and excitation system and can seamlessly switch between two operating states of off-grid and on-grid, which is conducive to the improvement of micro-grid stability. Finally, a simple microgrid system is built on the Matlab/Simulink platform. It is verified that the proposed control strategy has good power tracking characteristics and can enable the distributed power supply to switch quickly in different operating modes.

Sewerage surveillance tracking characteristics of human antibiotic emission in sewage

Antibiotics discharging are causing the concerns of public health and sustainable production. Further policies on antibiotic production and antibiotic sales are difficult to make when lacking of sewage surveillance. In this study, the dynamic occurrence of 24 typical antibiotics in urban sewerage was investigated throughout a whole year. It was found that 17 of 42 samples had a total antibiotic concentration of more than 1000 ng/L. Sulfonamides, lincosamides, macrolides and tetracyclines were the four most common antibiotic categories in sewerage system, with the average concentration of 1246 ng/L, 2418 ng/L, 1734 ng/L and 1140 ng/L, respectively. The concentration of β-lactams was relatively low in the raw sewage (with the median value of 11 ng/L) and exhibited a tendency of attenuation in sewerage due to its degradability. The total concentration of antibiotics in sewage in different quarters were positively correlated with the dosage of antibiotics prescribed by local hospitals (R = 0.88, p < 0.01). The antibiotics profiles were also determined by the local regional discharge, specific seasons and weather features. Antibiotics consumption significantly affects the level of antibiotic residues in sewage, indicating that sewage surveillance can provide rough information on antibiotic usage. These findings can lead to new ways to understand the actual antibiotic usage in humans, and guide the antibiotic production and usage based on sewage surveillance.

New running gear for improving the lateral dynamic characteristics of rubber-tired light rail vehicles

Rubber-tired light rail vehicles are generally operated on lines which include a number of small curves, steep slopes, or track switching sections to reduce construction costs or to place multiple stations in densely populated areas. Recently, the tendency is to increase acceleration, deceleration, and operation speed to shorten travel time and to increase transportation capacity. These track characteristics and operation patterns may result in deteriorating lateral dynamic characteristics in rubber-tired light rail vehicles. Therefore, running gear in rubber-tired light rail vehicles needs to play a role in effectively damping lateral vibrations and shock transmitted from the guidance rails through the guidance wheels. In this paper, new running gear was proposed to improve the lateral vibration and ride comfort in rubber-tired light rail vehicles. The new running gear has been newly installed with lateral rubber shock absorbers that can dampen lateral vibration on curved routes. In addition, it has been installed with a bi-directional return spring in place of the existing restoring coil spring and hydraulic damper to improve lateral vibration on straight routes. The effect of improving the lateral dynamic characteristics of the new running gear was verified through dynamic analysis and actual vehicle driving tests (field tests).

Tracking of anthropometric characteristics from childhood to adolescence: an 8-year follow-up findings from the Czech ELSPAC study

BackgroundAlthough evidence suggests that obesity track well from childhood to adolescence, most of the research has been done in Western and high-income countries. Moreover, most of the studies have tracked body-mass index, as a proxy of nutritional status, while tracking characteristics of circumferences and skinfold thicknesses have been less studies. Therefore, the main purpose of the study was to explore tracking characteristics of complete anthropometric data from childhood to adolescence.MethodsThis sub-study was part of the Czech ELSPAC study. In the present 8-year longitudinal study, we collected information from pediatrician’s medical records at the ages of 8 y (n = 888), 11 y (n = 1065), 13 y (n = 811) and 15 y (n = 974), including circumferences (head, chest, waist, hips, and arm), indices (body-mass index, waist-to-hip ratio and waist-to-height ratio) and skinfold thicknesses (biceps, triceps, subscapula, suprailiaca, thigh and the sum of 5 skinfolds). Participants were recruited from the two selected regions of the Czech Republic (Brno and Znojmo). Linear generalized estimating equations were conducted to analyze tracking patterns over an 8-year follow-up period for all anthropometric measurements.ResultsTracking coefficients were moderate to strong, ranging from 0.40 to 0.62 for circumferences, 0.41 to 0.74 for indices and 0.72 to 0.86 for skinfolds. According to body-mass index and waist circumference standards, overweight/obese children and children with abdominal obesity at the age of 8 y were 11.31 (95% CI = 8.41 to 15.22, p < 0.001) and 10.73 (95% CI = 7.93 to 14.52, p < 0.001) more likely to remain overweight/obese and to have abdominal obesity at the age of 15 y.ConclusionsFindings show moderate to strong tracking of anthropometric characteristics, i.e. circumferences track moderately well, while strong tracking for indices and skinfold thicknesses is observed. Moreover, strong tracking of general overweight/obesity and abdominal obesity between ages 8 y and 15 y indicates that the detection of these risk factors at the beginning of primary school should be advocated.

Trajectory Tracking Robust Control Method Based on Finite-Time Convergence of Manipulator with Nonsingular Fast Terminal Sliding Mode Surface

In order to make the manipulator track the desired trajectory in a finite time, a new control method based on fast nonsingular terminal sliding mode has been designed. This method combines the traditional fast terminal sliding mode with the nonsingular terminal sliding mode, has rapidity, nonsingularity, finite-time convergence, and strong robustness, and can effectively suppress the inherent chattering phenomenon of the sliding mode controller. The nonsingular fast terminal sliding mode surface is used to accelerate the convergence speed of manipulator trajectory tracking error, and the singularity problem in terminal sliding mode is solved. The finite-time convergence of the algorithm is proved by the Lyapunov function. The simulation results demonstrate that the proposed method can achieve accurate finite-time trajectory tracking characteristics and has robustness against external disturbances.

Futurity of Aritificial Intelligence on Remote Monitoring of Patients in E-Healthcare Through Cloud Computing

People's health is becoming increasingly crucial to track in this 'New Normal' post-COVID-19 modern environment. The need of the hour is for modern technology that uses sensory sensors to track and record critical characteristics while also communicating with others. Keeping track of all of the medical factors is difficult. Collecting post-operative data of persons with non-communicable disorders such as diabetes and heart disease on a regular basis on an ongoing basis The technology we're talking about is intended for those who are confined to their homes. Especially when leaving the house and being exposed to the outside world is forbidden. This paper made a recommendation. For obtaining patient data, a breakthrough health management system based on the Internet of Things (IoT) has been developed. medical characteristics in both urban and rural settings.&#x0D; Keywords: Remote patient monitoring(RMP) , healthcare delivery, e-health arctitechure, telemedicine.

Novel chitosan - graphene quantum dots composite for therapeutic delivery and tracking through enzymatic stimuli response

The designing of highly efficient and biocompatible nanocomposites with multifunctional delivery and tracking characteristics is noteworthy for clinical and therapeutic applications. Herein, we report the proof-of-concept for the delivery of anti-glaucoma drug, latanoprost (LP) under an enzymatic stimulus, lysozyme (Lyz) with novel chitosan (CS) - graphene quantum dots (GQD) nanocomposite via reverse switching photoluminescence (PL) phenomenon. The LP caged CS-GQDs nanocomposite was well characterized through extensive spectral, morphological, band-gap, particle size, and zeta potential studies along with cytotoxicity assays. The regaining of PL not only confirmed LP delivery, but also facilitated intercellular tracking through in vitro bio-imaging against human corneal epithelial (HCE) cells. The AO/EB staining and biocompatibility assays further proved excellent cell viability of >80%. The successfully delivered LP protected HCE cells from oxidative injury induced by 800 μM hydrogen peroxide (H2O2). These findings justify further utility of novel CS-GQDs caged drug nanocomposite for preclinical investigations.