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As members of a social species, we spend most of our time interacting with others. In interactions, we tend to mutually align our behavior and brain responses to communicate more effectively. In a semi-computerized version of the Rock-Paper-Scissors game, we investigated whether people show enhanced interpersonal neural synchronization when making explicit predictions about others' actions. Across four experimental conditions, we measured the dynamic brain activity using the functional near-infrared spectroscopy (fNIRS) hyperscanning method. Results showed that interpersonal neural synchrony was enhanced when participants played the game together as they would do in real life in comparison to when they played the game on their own. We found no evidence of increased neural synchrony when participants made explicit predictions about others' actions. Hence, neural synchrony may depend on mutual natural interaction rather than an explicit prediction strategy. This study is important, as it examines one of the presumed functions of neural synchronization namely facilitating predictions. [ABSTRACT FROM AUTHOR]

We propose a Drawing-Frequency based Layered (DFL) Canvas approach to reduce a synchronization delay in collaborative web applications. The synchronization delay consists of a network delay and a drawing delay. The network delay is well-argued topic by various researches. We focus on the drawing delay, which is a primary bottleneck of Canvas objects synchronizations. We introduce the DFL Canvas approach in order to solve the drawing problem. The DFL Canvas divides Canvas objects by drawingfrequency. We implemented a collaborative paper editing support system with the DFL Canvas. Users can edit the same document and share Canvas objects on papers in real-time on web browsers. We present an evaluation result that indicates the approach is suited for collaborative paper editing support systems.

Since its creation, the ImageNet-1k benchmark set has played a significant role as a benchmark for ascertaining the accuracy of different deep neural net (DNN) models on the image classification problem. Moreover, in recent years it has also served as the principal benchmark for assessing different approaches to DNN training. Finishing a 90-epoch ImageNet-1k training with ResNet-50 on a NVIDIA M40 GPU takes 14 days. This training requires $10^{18}$1018 single precision operations in total. On the other hand, the world's current fastest supercomputer can finish $3 \times 10^{17}$3×1017 single precision operations per second (according to the Nov 2018 Top 500 results). If we can make full use of the computing capability of the fastest supercomputer, we should be able to finish the training in several seconds. Over the last two years, researchers have focused on closing this significant performance gap through scaling DNN training to larger numbers of processors. Most successful approaches to scaling ImageNet training have used the synchronous mini-batch stochastic gradient descent (SGD). However, to scale synchronous SGD one must also increase the batch size used in each iteration. Thus, for many researchers, the focus on scaling DNN training has translated into a focus on developing training algorithms that enable increasing the batch size in data-parallel synchronous SGD without losing accuracy over a fixed number of epochs. In this paper, we investigate supercomputers' capability of speeding up DNN training. Our approach is to use a large batch size, powered by the Layer-wise Adaptive Rate Scaling (LARS) algorithm, for efficient usage of massive computing resources. Our approach is generic, as we empirically evaluate the effectiveness on five neural networks: AlexNet, AlexNet-BN, GNMT, ResNet-50, and ResNet-50-v2 trained with large datasets while preserving the state-of-the-art test accuracy. Compared to the baseline of a previous study from Goyal et al. [1] , our approach shows higher test accuracy on batch sizes that are larger than 16K. When we use the same baseline, our results are better than Goyal et al. for all the batch sizes (Fig. 20). Using 2,048 Intel Xeon Platinum 8160 processors, we reduce the 100-epoch AlexNet training time from hours to 11 minutes. With 2,048 Intel Xeon Phi 7250 Processors, we reduce the 90-epoch ResNet-50 training time from hours to 20 minutes. Our implementation is open source and has been released in the Intel distribution of Caffe, Facebook's PyTorch, and Google's TensorFlow. The difference between this paper and the conference-version of our work [2] includes: (1) we implement our approach on Google's cloud Tensor Processing Unit (TPU) platform, which verifies our previous success on CPUs and GPUs. (2) we scale the batch size of ResNet-50-v2 to 32K and achieve 76.3 percent accuracy, which is better than the 75.3 percent accuracy achieved in our conference paper. (3) we apply our approach to Google's Neural Machine Translation (GNMT) application, which helps us to achieves 4× speedup on the cloud TPUs. [ABSTRACT FROM AUTHOR]

Phase synchronization serves as an effective method for analyzing the synchronization of electroencephalogram (EEG) signals among brain regions and the dynamic changes of the brain. The purpose of this paper is to study the construction of the functional brain network (FBN) based on phase synchronization, with a special focus on neural processes related to human balance regulation. This paper designed four balance paradigms of different difficulty by blocking vision or proprioception and collected 19-channel EEG signals. Firstly, the EEG sequences are segmented by sliding windows. The phase-locking value (PLV) of core node pairs serves as the phase-screening index to extract the valid data segments, which are recombined into new EEG sequences. Subsequently, the multichannel weighted phase lag index (wPLI) is calculated based on the new EEG sequences to construct the FBN. The experimental results show that due to the randomness of the time points of body balance adjustment, the degree of phase synchronization of the datasets screened by PLV is more obvious, improving the effective information expression of the subsequent EEG data segments. The FBN topological structures of the wPLI show that the connectivity of various brain regions changes structurally as the difficulty of human balance tasks increases. The frontal lobe area is the core brain region for information integration. When vision or proprioception is obstructed, the EEG synchronization level of the corresponding occipital lobe area or central area decreases. The synchronization level of the frontal lobe area increases, which strengthens the synergistic effect among the brain regions and compensates for the imbalanced response caused by the lack of sensory information. These results show the brain regional characteristics of the process of human balance regulation under different balance paradigms, providing new insights into endogenous neural mechanisms of standing balance and methods of constructing brain networks. [ABSTRACT FROM AUTHOR]

The asymptotic synchronization problem of chaotic Lur'e systems in the master-slave framework was explored in this paper. A time-varying delay feedback controller with quantization considerations and a delay-product-type Lyapunov-Krasovskii functional technique were employed to tackle this problem. Consider an error system based on master and slave systems, for which sufficient asymptotic stability requirements are developed to assure that the addressed system achieves proper synchronization. Following that, the desired control gain was determined by finding a feasible solution to these stability requirements. The results of this paper were validated using a numerical example with simulations, which revealed that they were superior to previously published ones. [ABSTRACT FROM AUTHOR]

Transverse synchronization of vertical displacements of all jacking-up points is an important monitoring indicator to replace bearings in assembled multigirder bridges during the jacking phase. Currently, using target paper to identify the 3D coordinates of control points reduces the complexity of monitoring operations and improves the stability of data precision. However, the existing planar target locating methods have low accuracy, inefficiency, and subjectivity, which seriously hinders the construction process of bearing replacement. Accurately obtaining the center coordinates of multiple targets from a point cloud in a short monitoring period remains a challenge. This study proposes a high-precision automated algorithm to extract target center points in low-density point clouds to quickly calculate real target center points. First, we construct a standard point cloud model of the target papers for scanning, including color and geometric features. Then, we extract the measured point cloud of the typical jacking operation phase based on the reflection intensity and size information. Next, we map the intensity values of the measured point cloud into the color channel and register the measured point cloud with its standard point cloud model using the normal vector estimation and colored ICP algorithms. Finally, we extract the center point of the measured targets. Numerical experiments and engineering test results show that the proposed method converges quickly with high precision and good robustness, which saves 91.4% of the time compared with the traditional method. In general, this research can provide effective technical support for 3D laser scanning in monitoring the operation phase of bridge jacking. [ABSTRACT FROM AUTHOR]

We analyze chaos in the well-known nonautonomous Double-Gyre system. A key focus is on folding, which is possibly the less-studied aspect of the "stretching+folding=chaos" mantra of chaotic dynamics. Despite the Double-Gyre not having the classical homoclinic structure for the usage of the Smale--Birkhoff theorem to establish chaos, we use the concept of folding to prove the existence of an embedded horseshoe map. We also show how curvature of manifolds can be used to identify fold points in the Double-Gyre. This method is applicable to general nonautonomous flows in two dimensions, defined for either finite or infinite times. [ABSTRACT FROM AUTHOR]

Ensuring the swift and precise tracking of power system signal parameters, especially the frequency, is imperative for the secure and stable operation of power grids. In instances of faults within the distribution network, abrupt changes in frequency may occur, presenting a challenge for existing algorithms that struggle to effectively track such signal variations. Addressing the need for enhanced performance in the face of frequency mutations, this paper introduces an innovative approach--the Covariance Reconstruction Extended Kalman Filter (CREKF) algorithm. Initially, the dynamic signal model of electric power is meticulously analyzed, establishing a dynamic signal relationship based on high-precision time source sampling tailored to the signal model's characteristics. Subsequently, the filter gain, covariance matrix, and variance iteration equation are determined based on the signal relationship among three sampling points. In a final step, recognizing the impact of the covariance matrix on algorithmic tracking ability, the paper proposes a covariance matrix reset mechanism utilizing hysteresis induced by output errors. Through extensive verification with simulated signals, the results conclusively demonstrate that the CREKF algorithm exhibits superior measurement accuracy and accelerated tracking speed when confronted with mutating signals. [ABSTRACT FROM AUTHOR]

The traditional Internet has many security problems. It is difficult to guarantee the authenticity, integrity, and synchronization of message transmission, and it lacks a message-traceability mechanism, which is caused by its performance-oriented design. To address these problems, this paper proposes a memorable communication method based on cryptographic accumulators. In this method, both parties in the communication can verify the message data sent and received arbitrarily by virtue of the memory value. As long as a simple memory value comparison is performed, the strong consistency of all message data can be ensured. This method has the security advantages of synchronization, verification, traceability, and non-tamperability, as well as the performance advantages brought by batch signature and verification. In this paper, the memorable communication model, the memory function, and the memorable communication process are designed, and theoretical analysis shows that the memorable communication method has synchronization and traceability and can realize batch signature and authentication. In addition, a chain-key can be constructed based on a memory value to achieve key per-packet updating. Comparative analysis shows the transmission efficiency, traceability efficiency, and security performance of the memorable communication method. [ABSTRACT FROM AUTHOR]

Deploying 5G in new and diverse use cases, such as Industry 4.0 and factory automation, requires 5G systems to harmonize with the communication technologies used in these industries. To this end, 3GPP Release 16 and Release 17 have made significant progress in integrating 5G systems with the IEEE 802.1 working group specifications on Time-Sensitive Networking (TSN). This paper explains a method and architecture for supporting TSN over a wireless channel in a 5G network that adds the TSN synchronization function in a Small Cell gNB implementing the TSN Translator function (SC-TT). This TSN-capable small cell provides TSN over the wireless network to synchronize UEs with the Grand Master (GM) using the physical layer signal of the 5G radio frame and the transmission of the GM reference time to provide high-precision synchronization. This paper explores the pivotal role of a Slot Indicator Signal in enhancing synchronization precision, ensuring that the UE-GM synchronization occurs within an exceptionally narrow timeframe as small as 10 ns. [ABSTRACT FROM AUTHOR]

This paper mainly discusses the problem of fast fixed-time bipartite synchronization in the complex networks with signed graph that is based on TS fuzzy system. By designing suitable and effective controller, the synchronization of the considered complex networks has been achieved successfully in this paper, whose convergence rate is superior to the great majority of existing results. With the assistance of a comparison system being built and using the theory of Lyapunov stability, this paper has established sufficient criteria successfully that are able to achieve fast fixed-time bipartite synchronization. And a numerical simulation example displays the performance of the obtained new results at the end of this paper. [ABSTRACT FROM AUTHOR]

This paper investigates the practical generalized finite-time synchronization (PGFETS) of duplex networks with quantized and delayed couplings. Given that continuous transmission of signals will increase the load and cost of communication, we introduce quantized couplings in the model. Then, via the theorem of finite-time stability, the PGFETS is proposed based on the fact that PGFETS is much more extensive and practical than classical finite-time synchronization. Some sufficient criteria are formulated to achieve the goal of synchronization by utilizing quantized intermittent control schemes. Lastly, the validity of the theoretical results is illustrated by numerical simulations. [ABSTRACT FROM AUTHOR]

The increased use of renewable energy in modern power grids has led to a demand for innovative technologies that can efficiently harness intermittent energy sources. Multi-Point Absorber (MPA) systems have emerged as a promising solution for capturing wave and tidal energy sustainably. This study focuses on developing advanced control strategies for MPA systems to improve their performance and coordination in power generation and grid integration for both AC and DC networks. The research begins with a comprehensive review of MPA technologies, highlighting their challenges and opportunities. It then explores the development of control algorithms that dynamically adjust MPA parameters in real-time, optimizing energy extraction efficiency. The paper also addresses the crucial aspect of grid integration, investigating power electronics interfaces and synchronization techniques to enhance grid stability. Additionally, bidirectional power flow capabilities are discussed, enabling functions like frequency regulation and voltage control. The novelty of this work lies in the development of adaptive control algorithms for MPA systems, surpassing previous efforts by incorporating real-time data for parameter adjustments. The study demonstrates the effectiveness of these advanced control strategies through simulations and implementation, evaluating energy conversion efficiency, grid compatibility, and system reliability across various conditions compared to conventional methods. The results emphasize the significance of bidirectional power flow capabilities in achieving enhanced functionality, such as frequency regulation and voltage control. This paper provides valuable insights into optimizing MPA systems, showcasing their potential to revolutionize sustainable energy capture and integration into modern power grids. [ABSTRACT FROM AUTHOR]

To construct a nonlinear fractional-order neural network reflecting the complex environment of the real world, this paper considers the common factors such as uncertainties, perturbations, and delays that affect the stability of the network system. In particular, not only does the activation function include multiple time delays, but the memristive connection weights also consider transmission delays. Stemming from the characteristics of neural networks, two different types of discontinuous controllers with state information and sign functions are devised to effectuate network synchronization objectives. Combining the finite-time convergence criterion and the theory of fractional-order calculus, Mittag-Leffler synchronization conditions for fractional-order multi-delayed memristive neural networks (FMMNNs) are derived, and the upper bound of the setting time can be confirmed. Unlike previous jobs, this article focuses on applying different inequality techniques in the synchronous analysis process, rather than comparison principles to manage the multi-delay effects. In addition, this study removes the restrictive requirement that the activation function has a zero value at the switching jumps, and the discontinuous control protocol in this paper makes the networks achieve synchronization over a finite time, with some advantages in terms of the convergence speed. [ABSTRACT FROM AUTHOR]

The challenge in designing distributed controllers for vehicle platoon synchronization arises when full-state information for control algorithm calculations cannot be obtained from the entire vehicle. Therefore, this paper presents a control scheme using a cooperative observer to estimate full-state information, enabling its use in calculating control signals. Instead of relying solely on a control signal proportional to the cooperative tracking error, the proposed control signal includes an additional integral form of the cooperative tracking error. This addition is expected to mitigate the effects of disturbances experienced by follower vehicles. Distributed control generally comprises two major components: The proportional-integral (PI) controller and the cooperative observer. The paper provides conditions for choosing control parameter values to guarantee the stability of the vehicle platoon. A numerical simulation of a vehicle platoon comprising one leader and ten followers is presented to demonstrate performance and validate the research results. Simulation results indicate that the controller performs effectively when followers experience constant disturbances, demonstrating the continuous achievement of vehicle platoon synchronization. [ABSTRACT FROM AUTHOR]

The Antimalware Scan Interface (AMSI) plays a crucial role in detecting malware within Windows operating systems. This paper presents ScriptBlock Smuggling, a novel evasion and log spoofing technique exploiting PowerShell and.NET environments to circumvent the AMSI. By focusing on the manipulation of ScriptBlocks within the Abstract Syntax Tree (AST), this method creates dual AST representations, one for compiler execution and another for antivirus and log analysis, enabling the evasion of AMSI detection and challenging traditional memory patching bypass methods. This research provides a detailed analysis of PowerShell's ScriptBlock creation and its inherent security features and pinpoints critical limitations in the AMSI's capabilities to scrutinize ScriptBlocks and the implications of log spoofing as part of this evasion method. The findings highlight potential avenues for attackers to exploit these vulnerabilities, suggesting the possibility of a new class of AMSI bypasses and their use for log spoofing. In response, this paper proposes a synchronization strategy for ASTs, intended to unify the compilation and malware scanning processes to reduce the threat surfaces in PowerShell and.NET environments. [ABSTRACT FROM AUTHOR]

In order to improve the position high-precision synchronization performance of multi-motor synchronous control, a multi-motor position synchronization control method based on non-singular fast terminal sliding mode control (NFTSMC) combined with an improved deviation coupling control structure (Improved Deviation Coupling Control(IDCC), NFTSMC+IDCC). Firstly, this paper designs a sliding mode controller using a non-singular fast terminal sliding mode surface with a Permanent Magnet Synchronous Motor (PMSM) as the control object. Secondly, the deviation coupling is improved to enhance the coupling between multiple motors and achieve position synchronization. Finally, the simulation results show that the total error of multi-motor position synchronization under NFTSMC control is 0.553r in the simulation of multi-motor synchronization control under the same working conditions, which is 2.873r and 1.772r less than that of SMC and FTSMC in terms of speed error, and the anti-disturbance performance is 83.68% and 76.22% higher than that of both of them, respectively. In the subsequent simulation of the improved multi-motor position synchronization structure, the total error of the multi-motor position is in the range of 0.56r-0.58r at three speeds, which is much smaller than the synchronization error under the Ring Coupling Control (RCC) structure and Deviation Coupling Control (DCC) structure, showing a better The synchronization error is much smaller than that of the RCC structure and DCC structure, which shows better position synchronization performance. Therefore, the multi-motor position synchronization control method proposed in this paper has a good position synchronization effect and achieves the control effect of small displacement error and fast convergence of the multi-motor position synchronization control system after being disturbed, the control performance is significantly improved. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. In contrast to existing synchronization network models, the current study considers both internal time‐varying delays and coupling time‐varying delays. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a new inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. To demonstrate the effectiveness of the present approach, simulation results are illustrated. In this paper, we consider the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. Different from the existing synchronization of the networks model, we take the internal time‐varying delays and the coupling time‐varying delays into account. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a novel inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. [ABSTRACT FROM AUTHOR]

The scope of complex dynamical networks (CDNs) with dynamic edges is very wide, as it is composed of a class of realistic networks including web-winding systems, communication networks, neural networks, etc. However, a classic research topic in CDNs, the synchronization control problem, has not been effectively solved for CDNs with dynamic edges. This paper will investigate the emergence mechanism of synchronization from the perspective of large-scale systems. Firstly, a CDN with dynamic edges is conceptualized as an interconnected coupled system composed of an edge subsystem (ES) and a node subsystem (NS). Then, based on the proposed improved directed matrix ES model and expanded matrix inequality, this paper overcomes the limitations of coupling term design in node models and the strong correlation of tracking targets between nodes and edges. Due to the effect of the synthesized node controller and the auxiliary effect of the ES, state synchronization can be realized in the CDN. Finally, through simulation examples, the validity and advantages of our work compared to existing methods are demonstrated. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time projective synchronization (FTPS) problem of fractionalorder quaternion-valued fuzzy memristor neural networks (FOQVFMNNs) is studied. Through establishing a feedback controller with signed functions and an adaptive controller, sufficient conditions for FTPS for FOQVFMNNs are obtained. Furthermore, the synchronization establishment time is calculated. Finally, the practicability of the conclusions is verified by numerical simulations. [ABSTRACT FROM AUTHOR]

Mainstream research on information theory within the field of living systems involves the application of analytical tools to understand a broad range of life processes. This paper is dedicated to an opposite problem: it explores the information theory and communication engineering methods that have counterparts in the data transmission process by way of DNA structures and neural fibers. Considering the requirements of modern multimedia, transmission methods chosen by nature may be different, suboptimal, or even far from optimal. However, nature is known for rational resource usage, so its methods have a significant advantage: they are proven to be sustainable. Perhaps understanding the engineering aspects of methods of nature can inspire a design of alternative green, stable, and low-cost transmission. [ABSTRACT FROM AUTHOR]

This paper discusses the synchronization problem of impulsive stochastic bidirectional associative memory neural networks with a diffusion term, specifically focusing on the fixed-time (FXT) and predefined-time (PDT) synchronization. First, a number of more relaxed lemmas are introduced for the FXT and PDT stability of general types of impulsive nonlinear systems. A controller that does not require a sign function is then proposed to ensure that the synchronization error converges to zero within a predetermined time. The controllerdesigned in this paper serves the additional purpose of preventing the use of an unreliable inequality in the course of proving the main results. Next, to guarantee FXT and PDT synchronization of the drive–response systems, this paper employs the Lyapunov function method and derives sufficient conditions. Finally, a numerical simulation is presented to validate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the clustering component synchronization of nonlinearly coupled complex dynamical networks with nonidentical nodes was investigated. By applying feedback injections to those nodes who have connections with other clusters, some criteria for achieving clustering component synchronization were obtained. A numerical simulation was also included to verify the correctness of the results obtained. [ABSTRACT FROM AUTHOR]

With the expansion of network scale, new network services are emerging. Segment Routing over IPv6 (SRv6) can meet the diverse needs of more new services due to its excellent scalability and programmability. In the intelligent 6-Generation (6G) scenario, frequent SRv6 Traffic Engineering (TE) policy updates will result in the serious problem of unsynchronized updates across routers. Existing solutions suffer from issues such as long update cycles or large data overhead. To optimize the policy-update process, this paper proposes a scheme called Synchronous Update with the Division and Combination of SRv6 Policy (SUDC). Based on the characteristics of the SRv6 TE policy, SUDC divides the policies and introduces Bit Index Explicit Replication IPv6 Encapsulation (BIERv6) to multicast the policy blocks derived from policy dividing. The contribution of this paper is to propose the policy-dividing and combination mechanism and the policy-dividing algorithm. The simulation results demonstrate that compared with the existing schemes, the update overhead and update cycle of SUDC are reduced by 46.71% and 46.6%, respectively. The problem of unsynchronized updates across routers has been further improved. [ABSTRACT FROM AUTHOR]

In this paper, the fixed/predefined-time generalized synchronization problem of stochastic complex dynamical networks with delays is studied for the first time. First, based on the feedback controller without linear terms, the results show that the controlled system has strong stability. Second, stochastic analysis methods, inequality techniques, and an extension of the existing fixed/predefined-time stability lemma ( η range extension) are used to make the results of this paper more general. The sufficient conditions for generalized synchronization are established, and the settling time independent of the initial values are given. To illustrate the theoretical results, a numerical example is given. In this paper, the fixed/predefined-time generalized synchronization problem of stochastic complex dynamical networks with delays is studied for the first time. First, based on the feedback controller without linear terms, the results show that the controlled system has strong stability. Second, stochastic analysis methods, inequality techniques, and an extension of the existing fixed/predefined-time stability lemma ( range extension) are used to make the results of this paper more general. The sufficient conditions for generalized synchronization are established, and the settling time independent of the initial values are given. To illustrate the theoretical results, a numerical example is given. [ABSTRACT FROM AUTHOR]

Multi-motor synchronous drive system is increasingly widely used in industry and manufacturing, where its control structure and control strategy affect the quality and efficiency of production. In order to solve the contradiction between fastness and overshoot, and the difficulty in determining the compensation law in the conventional PID, cross-coupling control, and master-slave control strategies used in multi-motor control, this paper proposes a self-coupling PID control strategy based on ring adjacent compensation to reduce the complexity of the control structure. Furthermore, this paper analyzes the self-coupling PID parameter tuning rules and establishes the control structure of the ring coupling strategy, and proves its validity mathematically. The simulation results verify that the proposed strategy provides a fast response speed, high control precision, good disturbance rejection, and synchronization performance. [ABSTRACT FROM AUTHOR]

Precise timing plays a key role in the time‐sensitive industrial Internet of Things (IIoT). However, precise time synchronization requires more frequent packet exchange, which consumes more communication bandwidth and energy. This is a particular challenge in battery‐powered wireless nodes, and low communication costs have become an important factor in clock synchronization. To address the challenge of achieving low communication cost clock synchronization in distributed wireless sensor networks, this paper proposes an improved event‐triggered control and synchronization scheme with a novel asynchronous broadcast packet exchange protocol. Unlike the traditional event‐triggered control scheme which is based on synchronous polling packet exchange, this proposed asynchronous broadcast packet exchange is more communication efficient and requires fewer number of packet exchanges. And it is worth noting that the proposed algorithm in this paper is a distributed algorithm and does not require real‐time acquisition of information from neighbouring nodes. Finally, a numerical example is given to illustrate the effectiveness of the proposed event‐triggered control strategy. The efficiency and precision of the proposed clock synchronization method is evaluated by intensive simulations, which show that the number of packet exchange is reduced by 60% for a moderate IIoT network and is particularly useful for large scale network. [ABSTRACT FROM AUTHOR]

Considering the problem that the timing synchronization calculation in high-speed remote sensing signal reception is complex and it is difficult for it to be parallel, this paper deduces and designs a parallel timing error estimation and correction scheme. This paper presents the design of polyphase DFT filter banks with non-maximum decimation. The feedforward timing error estimation and correction method is then improved to enhance synchronization performance. Finally, an implementation scheme for parallel timing error estimation and correction is proposed using the polyphase filter bank time domain decomposition method and the filter polyphase model. In the estimation module, the parallel implementation structure of the joint second-order and fourth-order cyclic statistics methods is designed, which improves the estimation accuracy. In the correction module, a fractional delay filtering method with higher accuracy is adopted in order to improve the calibration accuracy and reduce the computational complexity. The timing synchronization of a high-speed remote sensing signal with timing error is simulated and verified. The experimental results show that the parallel method proposed in this paper greatly reduces the processing speed of subband data, and has a good synchronization performance, which is close to the theoretical limit in the demodulation error rate. This paper utilizes a multi-phase DFT filter bank architecture to achieve parallel timing synchronization, which presents a novel approach for the future parallel reception of high-speed remote sensing signals. [ABSTRACT FROM AUTHOR]

The integration of large-scale photovoltaics (PVs) into the power grid has significantly altered the transient synchronization dynamics of traditional power systems dominated by synchronous generators (SGs) and posed great challenges to modeling and analysis of PVs integration. In this paper, the transient synchronization stability of the PV-SG system is studied using the singular perturbation technique. Firstly, a nonlinear model of a PV-SG system is established to reveal the multiscale transient synchronization characteristics. Further, the full system is decomposed into a slow subsystem and a fast subsystem by the singular perturbation technique. The fast subsystem containing the dynamics of the DC voltage control, terminal voltage control, and phase-locked loop, and the slow subsystem containing the dynamics of rotor motion can perfectly reflect the dynamics of the full system within the electromagnetic and electromechanical timescales, respectively. The proposed model provides a clearer physical picture of dynamics in the PV-SG system within the electromagnetic and electromechanical timescales. Subsequently, the stability of the slow and fast subsystems is investigated using the energy function and eigenvalue analysis methods, respectively. Meanwhile, the impacts of various operating, control, and structural parameters on the transient synchronization stability are uncovered. Different from the most existing research endeavors on the wide simulations of the PVs integration, the impact of PVs on the synchronization dynamics of SGs without considering the dynamical characteristics of the PV system, and the transient synchronization stability analyses of the PLL-based voltage source converter systems, it is the key contribution to study the transient synchronization dynamical characteristics of the PV system and its interaction with the SG under different timescales. All these are helpful and easy to extend to more complicated PV-SG systems. Finally, the analysis results are validated by extensive simulations. [ABSTRACT FROM AUTHOR]

To enhance the reliability of traditional current protection systems in the evolving landscape of future power grids, this paper proposes a differential protection data synchronization approach that leverages satellite and 5G network timing. This method addresses the risk of inadvertent operation due to 5G communication jitter. It employs the BeiDou satellite system for synchronizing the timing of 5G base stations and terminals. This synchronization extends to the 5G terminal and the protection device, thereby mitigating time deviations caused by air interface delays and reducing the 5G network's end-to-end delay by approximately 4 ms on average. A simulation was conducted to assess the reliability and effectiveness of the proposed method under normal satellite signal conditions. The results indicated a significant improvement in protection accuracy, with the method reducing the protection activation time by approximately 5–7 ms compared to the 5G timing data synchronization method. This advancement offers technical support for the safe and stable operation of new power systems. [ABSTRACT FROM AUTHOR]

Genetic oscillators have been widely used in modeling key processes of biological systems, especially cell cycles and circadian rhythms. In particular, repressilatory genetic oscillators have been employed in modeling the dynamics of mRNA and protein interactions with transcriptional and translational feedback loops at the molecular level. In addition, synchronization of these oscillators is crucial for understanding the underlying mechanisms of the associated biological processes. In this paper, models of fractional-order genetic oscillators and their coupling are established, where the aspects of time delay, coupling strength, noise, and stability are all taken into consideration. Communication in the proposed coupling model is based on quorum sensing. The synchronization of the fractional-order repressilator model has been examined through simulations which show three main findings. Firstly, the synchronization of the fractional-order repressilator model can be optimized through coupling weight selection. Secondly, the synchronization can be enhanced by increasing the fractional order and decreasing the time delay and the noise intensity. Finally, transitions between the states of the fractional-order repressilatory oscillator can be achieved through varying the fractional order. The simulation results verify the biological relevance of the genetic oscillator models, and their potential for explaining the underlying mechanisms of the associated biological processes. [ABSTRACT FROM AUTHOR]

Due to the facts that epidemic-related parameters vary significantly in different stages of infectious diseases and are relatively stable within the same stage, infectious disease models should be switch-type models. However, research on switch-type infectious disease models is scarce due to the complexity and intricate design of switching rules. This scarcity has motivated the writing of this paper. By assuming that switching instants and impulse times occur at different moments, this paper proposes switch rules suitable for impulse control and derives synchronization criteria for reaction–diffusion switch-type infectious disease systems under impulse control. The effectiveness of this method is validated through numerical simulations. It is important to mention that, based on the information available to us, this paper is currently the sole study focusing on switch-type reaction–diffusion models for infectious diseases. [ABSTRACT FROM AUTHOR]

Cargo transfer vessels (CTVs) are designed to transfer cargo from a floating production storage and offloading (FPSO) unit into conventional tankers. The dynamic positioning system allows the CTV to maintain a safe position relative to the FPSO unit using a flexible cargo transmission pipe, and the CTV tows the tanker during operating conditions. The operation mode can be considered a synchronization tracking control problem. In this paper, a synchronization control strategy is presented based on the virtual leader–follower configuration and an adaptive backstepping control method. The position and heading of the following vessel are proven to be able to globally exponentially converge to the virtual ship by the contraction theorem. Then, the optimization problem of the desired thrust command from the controller is solved through an improved firefly algorithm, which fully considers the physical characteristics of the azimuth thruster and the thrust forbidden zone caused by hydrodynamic interference. To validate the effectiveness of the presented synchronous following strategy and thrust allocation algorithm, a scale model experiment is carried out under a sea state of 4 in a seakeeping basin. The experimental results show that the CTV can effectively maintain a safe distance of 100 m with a maximum deviation of 3.78 m and an average deviation of only 0.99 m in the wave heading 180°, which effectively verifies that the control strategy proposed in this paper can achieve safe and cooperative operation between the CTV and the FPSO unit. To verify the advantages of the SAF algorithm in the thrust allocation, the SQP algorithm and PSO algorithm are used to compare the experimental results. The SAF algorithm outperforms the SQP and PSO algorithms in longitudinal and lateral forces, with the R-squared (R2) values of 0.9996 (yaw moment), 0.9878 (sway force), and 0.9596 (surge force) for the actual thrusts and control commands in the wave heading 180°. The experimental results can provide technical support to improve the safe operation of CTVs. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of synchronizing data acquisition from independent sensor systems in a local network. The network comprises microcontroller-based systems that collect data from physical sensors used for monitoring human gait. The synchronized data are transmitted to a PC or cloud storage through a central controller. The performed research proposes a solution for effectively synchronizing the data acquisition using two alternative data-synchronization approaches. Additionally, it explores techniques to handle varying amounts of data from different sensor types. The experimental research validates the proposed solution by providing trial results and stability evaluations and comparing them to the human-gait-monitoring system requirements. The alternative data-transmission method was used to compare the data-transmission quality and data-loss rate. The developed algorithm allows data acquisition from six pressure sensors and two accelerometer/gyroscope modules, ensuring a 24.6 Hz sampling rate and 1 ms synchronization accuracy. The obtained results prove the algorithm's suitability for human-gait monitoring under its regular activity. The paper concludes with discussions and key insights derived from the obtained results. [ABSTRACT FROM AUTHOR]

IEEE 1588, also known as the Precision Time Protocol (PTP), is a standard protocol for clock synchronization in distributed systems. While it is not architecture-specific, implementing IEEE 1588 on Reduced Instruction Set Computer-V (RISC-V) low-power embedded devices demands considering the system requirements and available resources. This paper explores various approaches and techniques to achieve accurate time synchronization in such instruments. The analysis covers software and hardware implementations, discussing each method's challenges, benefits, and trade-offs. By examining the state-of-the-art in this field, this paper provides valuable insights and guidance for researchers and engineers working on time-critical applications in RISC-V-based embedded systems, aiding in selecting the most-suitable stack for their designs. [ABSTRACT FROM AUTHOR]

In this paper, the low energy cost synchronization control strategy of Markovian switching complex systems/networks is mainly studied and analyzed through multiple perspectives. Firstly, in order to achieve synchronization of Markovian switching complex networks with low energy cost, a control scheme based on the optimal node selection strategy that does not depend on the network coupling strength is improved, and a finite-time controller with a simpler structure is constructed. Secondly, based on the event-triggered control strategy an effective trigger event is designed to achieve the low energy cost synchronization of Markovian switching complex networks on the basis of reducing the information transmission and interaction between networks. Finally, the two control strategies mentioned in this paper are compared and analyzed from multiple perspectives through numerical simulations to better guide practical engineering. [ABSTRACT FROM AUTHOR]

This paper introduces the complex Rayleigh–van-der- Pol–Duffing oscillators (RVDOs), which are hyperchaotic and can be autonomous or nonautonomous. The fundamental dynamics of the autonomous and nonautonomous complex RVDOs, including dissipation, symmetry, fixed points, and stability, are studied. These oscillators are found in various necessary fields of physics and engineering. The paper proposes a scheme to achieve phase synchronization (PS) and antiphase synchronization (APS) for different dimensional models. These kinds of synchronization are considered a generalization of several other types of synchronization. We use the active control method based on Lyapunov's stability theory for this scheme. By analytically determining the control functions, the scheme achieved PS and APS. Our scheme is applied to study the PS of hyperchaotic behaviors for two distinct hyperchaotic nonautonomous and autonomous complex RVDOs. Additionally, the scheme is employed to achieve the APS of a chaotic real nonautonomous RVDO and a hyperchaotic complex autonomous RVDO, including those with different dimensions. Our work presents numerical results that plot the amplitudes and phases of these hyperchaotic behaviors, demonstrating the achievement of the PS and APS. The encryption and decryption of grayscale images are researched based on APS. The experimental results of image encryption and decryption are computed with information entropy, visual analysis, and histograms. [ABSTRACT FROM AUTHOR]

The dynamics of synaptic interactions within spiking neuron networks play a fundamental role in shaping emergent collective behavior. This paper studies a finite-size network of quadratic integrate-and-fire neurons interconnected via a general synaptic function that accounts for synaptic dynamics and time delays. Through asymptotic analysis, we transform this integrate-and-fire network into the Kuramoto-Sakaguchi model, whose parameters are explicitly expressed via synaptic function characteristics. This reduction yields analytical conditions on synaptic activation rates and time delays determining whether the synaptic coupling is attractive or repulsive. Our analysis reveals alternating stability regions for synchronous and partially synchronous firing, dependent on slow synaptic activation and time delay. We also demonstrate that the reduced microscopic model predicts the emergence of synchronization, weakly stable cyclops states, and non-stationary regimes remarkably well in the original integrate-and-fire network and its theta neuron counterpart. Our reduction approach promises to open the door to rigorous analysis of rhythmogenesis in networks with synaptic adaptation and plasticity. [ABSTRACT FROM AUTHOR]

For enhancing the load torque synchronization performance of dual‐driven systems, the inherent coupling effect between the parallel axes is analyzed first and could be described as two distinct components of the synchronous error. Thus, the feedforward‐feedback composite synchronous control scheme is proposed in this paper to eliminate these desynchronization factors. Secondly, the selection of synchronization objectives such as speeds, positions or currents of parallel axes is analyzed, which may not accurately reflect the actual load desynchronization due to mismatch dynamics. To overcome this drawback, the synchronous feedback controller is modified by incorporating a load torque observer, which can provide good adaptation to modelling errors, disturbances and eliminate the load desynchronization effectively. Simulation and experimental results demonstrate significant improvement in load torque synchronization performance achieved by the proposed control scheme. [ABSTRACT FROM AUTHOR]

Joint localization and synchronization (JLAS) is a technology that simultaneously determines the spatial locations of user nodes and synchronizes the clocks between user nodes (UNs) and anchor nodes (ANs). This technology is crucial for various applications in wireless sensor networks. Existing solutions for JLAS are either computationally demanding or not resilient to noise. This paper addresses the challenge of localizing and synchronizing a mobile user node in broadcast-based JLAS systems using sequential one-way time-of-arrival (TOA) measurements. The AN position uncertainty is considered along with clock offset and skew. Two redundant variables that couple the unknowns are introduced to pseudo-linearize the measurement equation. In projecting the equation to the nullspace spanned by the coefficients of the redundant variables, the affection of them can be eliminated. While the closed-form projection solution provides an initial point for iteration, it is suboptimal and may not achieve the Cramér-Rao lower bound (CRLB) when noise or AN position error is relatively large. To improve performance, we propose a novel robust iterative solution (RIS) formulated through factor graphs and developed via message passing. The RIS outperforms the common Gauss–Newton iteration, especially in high-noise scenarios. It exhibits a lower root mean-square error (RMSE) and a higher probability of converging to the optimal solution, while maintaining manageable computational complexity. Both analytical results and numerical simulations validate the superiority of the proposed solution in terms of performance, resilience, and computational load. [ABSTRACT FROM AUTHOR]

The synchronization phenomenon in nature has been utilized in sensing and timekeeping fields due to its numerous advantages, including amplitude and frequency stabilization, noise reduction, and sensitivity improvement. However, the limited synchronization bandwidth hinders its broader application, and few techniques have been explored to enhance this aspect. In this paper, we conducted theoretical and experimental studies on the unidirectional synchronization characteristics of a resonator with phase lock loop oscillation. A novel enhancement method for the synchronization bandwidth using a parametrically excited MEMS oscillator is proposed, which achieves a remarkably large synchronization bandwidth of 8.85 kHz, covering more than 94% of the hysteresis interval. Importantly, the proposed method exhibits significant potential for high-order synchronization and frequency stabilization compared to the conventional directly excited oscillator. These findings present an effective approach for expanding the synchronization bandwidth, which has promising applications in nonlinear sensing, fully mechanical frequency dividers, and high-precision time references. [ABSTRACT FROM AUTHOR]