Trajectory Tracking Method of Volleyball Player’s Arm Hitting Image Based on D-P Algorithm

Aiming at the problems of poor image tracking effect, low precision, and long time in the process of image tracking of volleyball player’s arm hitting, a volleyball player's arm hitting image tracking method based on D-P algorithm is proposed. This paper analyzes the basic concept, basic principle, and basic equation of D-P algorithm and collects the arm stroke trajectory image of volleyball players under the three-dimensional visual model. Using wavelet multiscale decomposition method, the arm stroke trajectory of volleyball players is filtered, and the edge contour feature points of the arm stroke image of volleyball players are extracted. Using the gray histogram feature extraction method, the gray information of volleyball player's arm hitting trajectory image is enhanced. Combined with pixel adaptive enhancement technology, the key action feature points of volleyball player's arm hitting image trajectory are located. Based on D-P algorithm, the volleyball player's arm hitting image trajectory is adjusted and modified to realize the correct tracking of volleyball player's arm hitting image trajectory. The experimental results show that the trajectory tracking effect of volleyball player's arm hitting image is better, which can effectively improve the tracking accuracy and shorten the tracking time.

Multiperson Target Dynamic Tracking Method for Athlete Training Based on Wireless Body Area Network

Aiming at the problems of large tracking error and long tracking time in traditional multiperson target dynamic tracking methods, a new method based on wireless body area network for athlete training multiperson target dynamic tracking is proposed. First, the microinertial sensor in the wireless body area network is used to collect the multiperson image data of the athlete training, and the sparse representation is performed after processing, which improves the reliability of the data and reduces the tracking error. Secondly, the multiperson target dynamic tracking method based on the adaptive search box is used, combined with target isolation and occlusion detection, to judge the athlete’s training target. Finally, the nearest neighbor algorithm is used to construct an adaptive search box to achieve dynamic tracking of multiple targets. Experimental results show that this method can accurately measure the similarity of target features, with small tracking error and short tracking time. The minimum tracking error is only 0.11 frame.

Fractional-order Learning Algorithm for PID Neural Network Decoupling Control Based on Sparrow Search Algorithm

Research on control of multi-variable system with strong coupling has been a significant issue in industry. To accurately eliminate the coupling between system variables and improve the control effect, decoupling control techniques are investigated. In this paper, a decoupling control scheme based on fractional-order proportion integration differentiation neural network and sparrow search algorithm (SSA-FPIDNN) is proposed, where sparrow search algorithm is employed to derive the optimal initial weights, preventing the weights from falling into the local optimum, while the fractional-order algorithm is used to correct its connection weights to improve control accuracy. Compared with traditional PIDNN, the proposed SSA-FPIDNN has better decoupling control performance, and the tracking time can be reduced significantly. Numerical simulation and engineering examples verified its effectiveness.

MPPT control based on improved mayfly optimization algorithm under complex shading conditions

The output power curve of the photovoltaic array presents a multi-peak characteristic under partial shading conditions, which causes the traditional maximum power point tracking technology to fail to guarantee the maximum power output of the photovoltaic cell. In response to this problem, this paper proposes to apply the improved Mayfly Optimization Algorithm (MA) to the maximum power tracking control. By introducing the gravity factor and limiting the search space of male mayfly, the optimization accuracy of the algorithm is enhanced, the vibration of the algorithm near the MPP is reduced, and the occurrence of premature phenomenon is avoided. Three test functions are selected to verify the algorithm, and under the conditions of rapid irradiance changes and complex shadow occlusion, an MPPT model based on the Boost circuit is established to verify the effectiveness of the algorithm. The simulation results show that the improved MA algorithm can effectively converge to MPP under complex shading conditions, and the output efficiency of photovoltaic arrays can be maintained above 99.96%. The average tracking time for different shading patterns is about 0.15 s.

Predictive control strategy for multi-agent relay tracking systems with time delays

This paper investigates the multi-agent systems for target tracking applications, in which the target is cooperatively relay tracked by multiple agents based on the Voronoi diagram. The relay tracking scheme is effective and reduces the tracking time of a target. However, the existence of time delays results in inaccurate determination of boundaries of Voronoi cells. Thus, the replacement of tracking agent is no longer optimal, which consequently affects the tracking time. In order to solve this issue, a predictive controller is proposed for the relay tracking system with time delays. Moreover, the boundaries of Voronoi cells are determined with the predictive values of agents’ information. In order to analyze the stability of the system, an impulse-time-dependent Lyapunov function is designed. Then, the orthogonal polynomials based inequality is applied and the average dwell time switching technique is adopted to solve the difficulty of stability analysis of the overall relay tracking system caused by the agent replacements of time-delay agents. Finally, the effectiveness and advantages of the proposed predictive control method for relay target tracking system with time delays are illustrated by comparative simulations.

Existence of a linear flows particle tracking model with a stochastic waiting time depending on the Gaussian jump length

This paper discusses the existence of the tracking model to detect a linear flows particle with a stochastic waiting time depending on the Gaussian jump length. This model is useful to measure the impurity quantification such as Radionuclides and Toxic Chemicals (particle) within the interaction medium (fluid) with minimum time and maximum probability. The particle flows linearly toward the origin (either from the left or the right). The flow line contains a nano programmed sensor (or nano UV detector). This sensor starts the tracking process for the particle (target) from the origin (filtration point) with speed equals one. We obtain the expected value of the tracking time until the sensor return to the origin with the target. Some competitive analysis depends on the uncertain values of the traveled distances which are derived to get necessary conditions for the sensor’s optimal distances. The numerical results demonstrate the efficiency of this model.

Multi-Source Data Fusion and Target Tracking of Heterogeneous Network Based on Data Mining

Thanks to the technical development of target tracking, the multi-source data fusion and target tracking has become a hotspot in the research of huge heterogenous networks. Based on millimeter wave heterogeneous network, this paper constructs a multi-source data fusion and target tracking model. The core of the model is the data mining deep Q network (DM-DQN). Through image filling, the length of the input vector (time window) was extended from 25 to 31, with the aid of CNN heterogeneous network technology. This is to keep the length of input vector in line with that of output vector, and retain the time features of eye tracking data to the greatest extent, thereby expanding the recognition range. Experimental results show that the proposed model achieved a modified mean error of only 1.5m with a tracking time of 160s, that is, the tracking effect is ideal. That is why the DM-DQN outperformed other algorithms in total user delay. The algorithm can improve the energy efficiency of the network, while ensuring the quality of service of the user. In the first 50 iterations, DM-DQN worked poorer than structured data mining. After 50 iterations, DM-DQN began to learn the merits of the latter. After 100 iterations, both DM-DQN and structured data mining tended to be stable, and the former had the better performance. Compared with typical structured data mining, the proposed DM-DQN not only converges fast, but also boasts a relatively good performance.

Investigation on Maximum Power Point Tracking Algorithm (INC and FLC) for Effective Utilization of Power Under Partial Shaded Photovoltaic System

Aim: This paper makes a comparative analysis on two types of maximum power point tracking algorithm to trace the global peak power efficiently with minimum oscillation and less tracking time under partial shaded photovoltaic green energy systems. Materials & Methods: Incremental conductance (INC) and fuzzy logic (FLC) MPPT algorithm are implemented to analyze the tracking efficiency under varying insolation conditions. Results: FLC MPP algorithm extracts peak power of 97.6 W with tracking time of 0.003s while INC extracts 94 W with tracking time of 0.004s. Conclusion: FLC MPPT algorithm provides better efficiency compared to INC algorithm for the selected data set.

Governance nell’innovazione: Sanità Digitale, Mobile Health, Big Data, Virtual Reality

The introduction of modern Information and Communication Technologies (ICT) was one of the most remarkable innovations of recent decades. ICT brings with it a remarkable technological background that conveys all kinds of information and multimedia content with a significant change in human-technology interaction and significant implications also in the health sector. The constant process of digitization is increasingly affecting national health systems (SSN) and they turn out to be influenced by the process itself, where the literature shows itself in favor of the use of technologies in health, improving their effectiveness and efficiency. These include eHealth, Telemedicine, Electronic Health File, Big Data, Virtual Reality, Augmented Reality, ePrescription. The technologies allow, even remotely, to have an always active and direct contact, between the various professionals, and between professionals and users, and are also useful for the training of both healthcare professionals and users themselves. The use of technology in the healthcare sector should therefore be encouraged as it allows direct contacts between users and healthcare personnel, speed and correlation of data analysis, tracking, time and cost savings, reduction of errors and a positive environmental impact with a reduction in the use of printed paper. For all the points listed, the technological revolution in hospital and territorial care can no longer be postponed.