Speed Tracking Research Articles

Exploring Social Media Commentary Pertaining to Physical and Sexual Abuse in South Korean Ice-Skating

The purpose of this study was to examine how South Korean individuals responded to Olympic short track speed skater Shim Suk-hee’s sexual abuse accusations toward her former coach Cho Jae-bum, as well as the perceptions associated with the culture of South Korea’s elite sport organization, the Korea Skating Union. Specifically, Facebook comments made to posts on the three digital news platforms (Dispatch, Insight, and SBS News) in South Korea were analyzed through the lens of framing theory. Data were analyzed using a thematic analysis. Three themes emerged inductively from the data analysis including (a) emotions; (b) punishment for authority figures; and (c) further investigations of similar cases. Comments illustrated South Korean publics’ anger with their desire to see Cho face stricter punishment for his abuse of Shim. In addition, comments discussed calling for more thorough investigations into similar cases of abuse. Lastly, South Korean individuals showed an overall dissatisfaction of the current system and culture of the Korean Skating Union without transparency.

IMPACTOS DO TREINAMENTO DE COORDENAÇÃO FÍSICA SOBRE A VELOCIDADE NA PATINAÇÃO DE VELOCIDADE EM PISTA CURTA

ABSTRACT Introduction Although the development time of short-track speed skating in China is relatively short, with the joint efforts of many athletes and coaches, the special technical level can be comparable with that of European and American countries. Objective Verify the impacts of physical coordination training on speed in short track speed skating. Methods Athletes from the provincial skating team were randomly selected and distributed into control and experimental groups to apply the training method on physical coordination in short track speed skating. Results The average body fat rate of the skaters in the control group was 15.24%, the average body fat rate in the control group was 15.20%, and the T value of the experimental group and control group was 1.00, P = 0.374 < 0.05. Conclusion Because they are special equipment, the turn resistance training device and the air resistance parachute played an important role in improving the special fitness of Chinese short track speed skaters. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

RISTrack: Learning Response Interference Suppression Correlation Filters for UAV Tracking

With the high computation efficiency and tracking accuracy, discriminative correlation filters (DCF) have been applied to UAV tracking. However, in the scenarios ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> ., complex background and temporary occlusion), DCF-based trackers usually generate low credibility response under the influence of background distractors, which contains multiple side peaks and declines the tracking performance. Motivated by the response consistency in adjacent frames and background information penalization, we propose learning a response interference suppression (RIS) correlation filter to tackle this problem. Specifically, we introduce a RIS regularization into the DCF-based framework, which aims to keep the target area response consistent in adjacent frames and repress distractors’ response in the background. Besides, we adopt a response auxiliary strategy (RAS) to smooth the target response, which intends to obtain the precise location and avoid target drift. Furthermore, extensive experiments on three UAV benchmarks demonstrate the excellent performance of the proposed method against other 19 state-of-the-art trackers. Moreover, the tracking speed of the proposed method can reach 42 FPS on a single CPU.

Infrared Small Target Tracking Algorithm via Segmentation Network and Multistrategy Fusion

To solve the problem of infrared (IR) small target tracking loss or error caused by factors such as scale changes, motion blur, occlusion, etc., this paper proposes a multi-strategy fusion tracking algorithm using an IR small target segmentation network as the detection head, which mainly includes six strategies: target pixel clustering, target feature threshold adjustment, large area search, small area tracking, gate tracking, and coordinate solution. First, candidate targets are obtained through the IR small target segmentation network and pixel clustering strategy. Second, the range of candidate targets is further reduced through threshold adjustment strategies. Then, real-time tracking of IR small targets is achieved through large area search, small area tracking, and wave gate tracking strategies. Finally, the longitude, latitude, and altitude of the tracked target are obtained through coordinate calculation strategies. Both qualitative and quantitative experiments based on real IR small target sequences verify that our algorithm can achieve more satisfactory performances in terms of success rate, precision, and robustness compared with other typical visual trackers. In addition, we have deployed tracking algorithms on the Orange Pi 5 embedded platform, and the tracking speed meets the real-time requirements.

Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm

The existing Maximum Power Point Tracking (MPPT) method has low tracking efficiency and poor stability. It is easy to fall into the Local Maximum Power Point (LMPP) in Partial Shading Condition (PSC), resulting in the degradation of output power quality and efficiency. It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms, and their performance in tracking the Global Maximum Power Point (GMPP) varies. Thus, a Cuckoo search algorithm (CSA) combined with the Incremental conductance Algorithm (INC) is proposed (CSA-INC) is put forward for the MPPT method of photovoltaic power generation. The method can improve the tracking speed by more than 52% compared with the traditional Cuckoo Search Algorithm (CSA), and the results of the study using this algorithm are compared with the popular Particle Swarm Optimization (PSO) and the Gravitational Search Algorithm (GSA). CSA-INC has an average tracking efficiency of 99.99% and an average tracking time of 0.19 s when tracking the GMPP, which improves PV power generation’s efficiency and power quality.

TO THE HISTORY OF THE LOCOMOTIVE APPARATUS STUDY BY THE SCIENTISTS KYIV SCHOOL OF COMPARATIVE MORPHOLOGISTS

The issue has been considered of studying the apparatus of animal movement by representatives of the Kyiv School of Comparative Morphologists. In the 20s of the 20th century, scientific works of representatives of the Kyiv School of Comparative Morphologists under the leadership of B.O. Dombrovsky began studying the structure of the animal movement apparatus, especially in the comparative aspect. In the course of his scientific activity, B. O. Dombrovskyi introduced a new direction in comparative anatomy to scientific research - the method of establishing and taking into account correlation as a method of synthesizing structures and analyzing processes. V. G. Kasyanenko's scientific research was devoted to the study of the structure and function of the joints of mammals, namely the structure of the horse's hock joint in the light of its biological evolution and domestication. Research on the biomechanics of statolocomotion organs was also new - the distribution of the limit of strength and the modulus of elasticity of parts of the bones of the limbs and the biomechanics of joints (Manziy S.F.). In addition, new methods were introduced in morphological studies, in particular electrophysiological ones, which were carried out by Kyiv morphologists for the first time in the Soviet Union. Along with this, non-structural laboratories were formed at the institute: functional analysis of limb joints and the role of synovium (O.G. Berezkin), zoological biomechanics (K.P. Melnyk, V.I. Klykov), research of limb muscles (V.F. Moroz), morphology of birds (V.F. Sych), morphology of bats (M.F. Kovtun), innervation of joints (M.M. Ilyenko), group for the study of limb vessels (P.M. Mazhuga). In the laboratory of limb muscle research organized by V.F. Moroz., registration of biopotentials from muscles in the state of statics and dynamics was carried out. An important device was a treadmill with track speed control and simultaneously working biopotential recorders. This made it possible for the first time to give a reliable picture of the coordinated functioning of each muscle and muscle group. The direction of scientific research of O.P. Melnyk: Biomorphology of vertebrate locomotion organs in a comparative aspect using a large number of taxonomic groups of animals that occupy different biological niches in nature.

A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation

The saturation of the nonlinear magnetic circuit of synchronous generators is often neglected when performing Kalman filter-based dynamic state estimation (DSE), yielding significant estimation bias. This letter addresses this problem and proposes a generalized DSE framework to handle magnetic saturation. Moreover, this letter derives a state initialization procedure that improves the Kalman filter tracking speed. The framework is flexible in dealing with different saturation functions and generator models. Numerical results on the Texas 2000-bus system verify the effectiveness of the proposed method.

국내 쇼트트랙 스피드스케이팅의 연구동향

The purpose of this study was to examine the research trends of ‘short track speed skating in Korea’, to present academic reflection and development direction through research analysis, and to provide basic data. A total of 167 domestic theses and journal articles were collected through six keywords. In addition, the following research questions were raised. There will be differences in the classification of papers, research subjects, research areas, and research methods of domestic short track speed skating by research year. In order to derive the results of these research problems, SPSS 29.0 was used to analyze the results. Based on the results of the analysis, reliability of the research was secured by measuring the reliability among the evaluators. The results of the analysis are as follows: First, the number of theses and journals has steadily increased, but the number of theses has recently decreased. Second, there were many studies on participants, and the study on instructors, parents, and equipment was insufficient. Third, the research division was concentrated on sports psychology, exercise physiology, and exercise mechanics, and recently it has been decreasing in all research divisions except sports industry and management. Fourth, quantitative research accounted for the largest proportion of research methods, followed by qualitative research and mixed research.

Adaptive Spatial Regularization Target Tracking Algorithm Based on Multifeature Fusion

The accuracy and robustness of object-tracking algorithms are challenging tasks in the field of artificial intelligence. The discriminative correlation filter has fast tracking speed and target discrimination ability in visual target tracking, but it will be affected by unnecessary boundary effects. Although spatially regularized discriminative correlation filters (SRDCF) effectively solve this problem, it faces a slow tracking speed and cannot meet the real-time requirement. Moreover, the constraints added by this algorithm are fixed during the tracking process, which needs to reflect better the characteristics and appearance changes of a particular object. Therefore, we propose an adaptive spatial regularization target tracking model based on multifeature fusion and learn the spatial regularization weights by adaptive spatial regularization terms, so that the filter can adapt to the changes of the target, which can highlight the target area and suppress the background area more accurately. At the same time, in order to cope with the problem of target loss when the target is obscured by a large area or rotated to a large extent, texture features are introduced to improve the deficiencies of HOG features and CN features, so as to achieve the complementary advantages among different features. In addition, the benchmark algorithm SRDCF uses Gaussian–Seidel iterative method to solve the filter, which makes the tracking speed very slow and cannot be tracked in real time. Therefore, this paper proposes an ADMM (alternating direction method of multiplier) algorithm to optimize the solution of the filter and achieve the tracking real-time requirement. The experimental results on the OTB-2015 dataset show that the accuracy and success rate of the improved algorithm reach 86% and 81.9%, respectively. At the same time, in the OTB-2013 dataset, it has increased by 3.4% and 6.3%, respectively, on the basis of the benchmark algorithm. It is verified that the improved model not only improves the robustness of the algorithm but also can better adapt to the changes of the target, while effectively reducing the computational overhead and meeting the tracking real-time requirements.

Optimum solar energy harvesting system using artificial intelligence

AbstractRenewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high‐gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&amp;O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step‐size P&amp;O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step‐size and conventional P&amp;O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&amp;O.

Visual tracking speed threshold in NCAA Division I women’s soccer predicting match performance

Correlations between sport performance and visual training have been previously demonstrated. However, it remains unclear if these relationships exist between visual tracking thresholds and in-competition decision-making metrics. Therefore, the purpose of this study was to investigate the relationship between visual tracking speed (VTS) and soccer-specific performance measures. 19 NCAA Division I soccer players VTS was measured from 1-core session on a 3-demensional multiple object tracking (3D-MOT) software NeuroTracker (NT) and soccer performance metrics were obtained from WyScout. Spearman’s rank order correlation coefficient was utilized to examine potential correlations between criterion variables. There was nonsignificant correlation between VTS score and passing accuracy (r = -0.380). However, there was a strong correlation found between consistency score and passing accuracy (r = 0.650). When examining players based on their positional role, for attacking players there were nonsignificant strong correlation with consistency and passing accuracy (r = 0.730). For defenders, consistency and defensive win rate had a strong correlation (r = 0.731). Although there was no significant correlation seen between VTS and decision-making variables when examining the entire team, there was a significant strong positive relationship between consistency scores and passing accuracy. Future research should seek to include multiple teams for improved sample size.

Robust Intelligent Tracking Control Technique for Single-Phase SPWM Inverters

This paper presents a robust intelligent tracking-control technique which is subsequently applied to single-phase SPWM inverters. The proposed technique mixes advanced sliding mode control (ASMC) with grey-Markov model (GMM). The advanced sliding mode control allows the system state to converge quickly to the origin in a limited amount of time. Unfortunately, a chattering problem frequently occurs when the inverter suffers drastically from highly nonlinear or internal parameters changes. The large power losses and high harmonic distortion emerge in the inverter output. The role that the grey-Markov model plays is to reduce the chattering of the ASMC during system uncertainty overestimation, or to reduce the steady-state error caused by underestimation of system uncertainty. In conjunction with the GMM and the ASMC, fast transient response, low distortion of the sinusoidal output-voltage and reduced chattering can be obtained. Simulation results of the proposed single-phase SPWM inverter are carried out in MATLAB/Simulink. The experimental results have been validated through digital signal processors, enabling the single-phase SPWM inverter output to effectively improve the transient tracking speed and steady-state performance.

STAGES OF KARTING FORMATION AS ONE OF THE POPULAR AUTOSPORT

Autosport appeared at the end of the 19th century and over time conquered the entire world by giving interested persons a race in the literal and metaphorical sense to develop and transform technical ideas that are based on wheels. Autosport (in English "autosport"), motor sports, also in English "motorsport" — is a category of technical types of sports in which participants compete with each other behind the wheel of cars (prototype, car, truck, SUV, and so on). As of today, there are many different subtypes of motorsport, each of which has its own rules and regulations. Competitions can be for track speed, efficiency, reliability, maneuverability, and so on. Kart racing - a small car consisting of a frame, a motorcycle engine and a seat. Karts cost less than any racing car and are relatively safe. Karting is therefore the ideal sport for beginners and car enthusiasts.

Power maximization in standalone photovoltaic system: an adaptive PSO approach

A control strategy for power maximization which is an important mechanism to extract maximum power under changing environmental conditions using Adaptive Particle Swarm Optimization (APSO) is proposed in this paper. An Adaptive Inertia Weighting Factor (AIWF) is utilized in the velocity update equation of traditional PSO for the improvement in speed of convergence and precision in tracking Maximum Power Point (MPP) in standalone Photovoltaic system. Adaptation of weights based on the success rate of particles toward maximum power extraction is the most promising feature of AIWF. The inertia weight is kept constant in traditional PSO for the complete duration of optimization process. The MPPT in PV system poses a dynamic optimization problem and the proposed APSO approach paves way not only to track MPP under uniform irradiation conditions, but also to track MPP under non-uniform irradiation conditions. Simulations are done in MATLAB/Simulink environment to verify the effectiveness of proposed technique in comparison with the existing PSO technique. With change in irradiation and temperature, the APSO technique is found to provide better results in terms of tracking speed and efficiency. Hardware utilizing dSPACE DS1104 controller board is developed in the laboratory to verify the effectiveness of APSO method in real time.

Super-twisting sliding-mode observer-based model reference adaptive speed control for PMSM drives

This paper develops a super-twisting sliding-mode observer-based model reference adaptive speed controller (STSMO-MRA-SC) for the permanent-magnet synchronous motor-based variable speed drive (PMSM-VSD) system. A stable first-order linear model is selected as the reference model to describe the required speed trajectory. To make the actual speed of the PMSM-VSD system follow this trajectory, the proposed STSMO-MRA-SC comprises three terms: (1) the stabilization term dependent on known parameters of the motion dynamics and the selected reference model for stabilizing the speed tracking error dynamics asymptotically; (2) the disturbance compensation term based on the STSMO for compensating the lumped disturbance in the speed tracking error dynamics; and (3) the error compensation term updated online by the adaptive law for confronting the estimation error of the STSMO in practice. Comparative experimental tests among the classic MRA-SC, the radial basis function neural network-based MRA-SC and the proposed STSMO-MRA-SC are performed. Experimental results have verified the effectiveness and the superiority of the proposed STSMO-MRA-SC.

Linear Active Disturbance Rejection Control-Based Diagonal Recurrent Neural Network for Radar Position Servo Systems with Dead Zone and Friction

This paper proposes a control scheme for the radar position servo system facing dead zone and friction nonlinearities. The controller consists of the linear active disturbance rejection controller (LADRC) and diagonal recurrent neural network (DRNN). The LADRC is designed to estimate in real time and compensate for the disturbance with vast matched and mismatched uncertainties, including the internal dead zone and friction nonlinearities and external noise disturbance. The DRNN is introduced to optimize the parameters in the linear state error feedback (LSEF) of the LADRC in real time and estimate the model information, namely Jacobian information, of the plant on-line. In addition, considering the Cauchy distribution, an adaptive tracking differentiator (ATD) is designed in order to manage the contradiction between filtering performance and tracking speed, which is introduced to the LADRC. Another novel idea is that the back propagation neuron network (BPNN) is also introduced to tune the parameters of the LADRC, just as in the DRNN, and the comparison results show that the DRNN is more suitable for high precision control due to its feedback structure compared with the static BPNN. Moreover, the regular controller performances and robust performance of the proposed control approach are verified based on the radar position servo system by MATLAB simulations.

Adaptive disturbance observer-based improved super-twisting sliding mode control for electromagnetic direct-drive pump

In this study, to enhance the frequency-flow characteristics of the novel electromagnetic direct-drive pump (EDDP). An adaptive disturbance observer-based improved super-twisting sliding mode control (ISTSMC-ADOB) is proposed to address the problem in which the response quality is deteriorated by factors such as parameter mismatch and disturbance. An adaptive disturbance observer (ADOB) is designed to achieve adaptive compensation, avoid the use of high-gain feedback, and extend the applicability of the conventional disturbance observer. An improved super-twisting sliding mode control (ISTSMC) based on the fast terminal sliding mode algorithm is designed to ensure faster convergence of the error in finite time. By combining the ADOB with the ISTSMC, the conservative parameter selection of the sliding mode control (SMC) is avoided, and the accuracy and robustness are further strengthened. The stability is analyzed based on Lyapunov. The results show that the proposed method effectively improves the steady-state accuracy, response speed, and robustness in trajectory tracking of the electromagnetic linear actuator for the EDDP. This further enhances the frequency-flow characteristics of the system.

Increased Expression Levels of Soluble Fms-Like Tyrosine Kinase-1 Inhibit the Development of the Nervous System

Introduction: Preeclampsia (PE) remains a leading cause of maternal and perinatal morbidity. At present, only limited options are available for the treatment of PE. Consequently, many patients need to terminate their pregnancies to relieve the disease. Soluble fms-like tyrosine kinase-1 (sFlt-1) is a decoy receptor of placental growth factor and vascular endothelial growth factor which can promote angiogenesis. Throughout pregnancy, the expression level of sFlt-1 continues to increase in both the mother with PE and her offspring. Material and Methods: In this experiment, we generated a zebrafish line expressing high levels of sFlt-1 and investigated changes in behavior and development of the nervous system. Results: At 96 h post-fertilization (hpf), the brain volume area of zebrafish in the experimental group (zFLT1+CasRx) was significantly smaller after injection than in the WT group (p < 0.05) and the negative control group (CasRx) (p < 0.05). At 96 hpf, compared with the WT group, the cerebral blood vessels in the CasRx control group and experimental group (zFLT1-sgRNA+CasRx) were significantly lower after injection (p < 0.05). Compared with the CasRx control group, the track movement distance and the mean track speed of zebrafish in the experimental group (zFLT1-sgRNA+CasRx) after the 6th injection were significantly decreased (p < 0.05). Conclusions: The increased expression levels of sFlt-1 in zebrafish inhibited the development of the cerebral blood vessels, influenced brain volumes, and inhibited behavioral activities. Our data suggest that the elevation of sFlt-1 in the pathological state of PE can inhibit the development of the nervous system in offspring.

Quantifi cation of Changes in the Functional Status of a Person During the Aircraft Flight

The article is devoted to the approach to the quantitative estimation of changes in the functional state of a person during an airplane flight based on the results of stabilometric and oculographic examinations of airplane passengers carried out before and after the flight. Fourteen volunteers of both sexes participated in the study. They performed 21 pairs of pre-flight and post-flight examinations. For the existing sample of volunteers, parameters were identified that had a consistent trend of change. These parameters include visual tracking quality and stabilometric characteristics. In 70 % probes a decrease in the slow phases of optokinetic nystagmus average speed was noted. In most volunteers, changes in the stabilometric parameters for the optokinetic test and the balance test on an unstable support in the form of foam plate are noticeable. The tracking speeds, the average velocity of the pressure center, and the quality index of the equilibrium function decreased after the flight in more than 70 % of all samples. It was noted that the Hurst index after the flight decreased compared to background sample, during get up on the polyurethane foam plate in the vast majority of volunteers. In test before the flight the change in this parameter was multidirectional. In a stabilometric test with a "stepped deviation", in which a volunteer on command made quick bends at a small angle due to a change in the angle in the ankle joint, 75 % of the subjects after the flights showed a decrease in the average speed.

Speed Tracking Control for Unmanned Driving Robot Vehicle Based on Fuzzy Adaptive Sliding Mode Control

To achieve accuracy and stable speed tracking under different conditions, a speed tracking method for the unmanned driving robot vehicle with sliding mode gains adjusted by a fuzzy adaptive system is proposed. Using the complex vector method and equivalent substitution method, kinematics and dynamics models of driving mechanical legs are established. Combined with models of driving and brake systems of manipulated vehicles, the longitudinal dynamics model is built. Then the longitudinal manipulation strategy is established. Based on the dynamics model of the mechanical leg, the sliding mode controller's control law is deduced. In addition, the fuzzy adaptive approximation is constructed and the fuzzy adaptive law is designed. Furthermore, the stability of the fuzzy sliding mode controller is proven using the Lyapunov function. Finally, through simulation and experiment, a comparison among the proposed method and several existing control methods demonstrates the effectiveness of the proposed method.