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A recent study conducted by researchers at the University of Minho in Braga, Portugal, highlights the rich and diverse nature of European health communication. The study focuses on the international perspectives, scientific approaches, and topics within this field. The research selected four papers for publication through a comprehensive evaluation process. For more information, readers can access the European Journal of Health Communication, which features these papers. The study was conducted in collaboration with the Communication and Society Research Centre at the University of Minho. [Extracted from the article]

This paper presents a mixed-signal SRAM-based in-memory computing (IMC) macro for processing binarized neural networks. The IMC macro consists of $128\times 128$ (16K) SRAM-based bitcells. Each bitcell consists of a standard 6T SRAM bitcell, an XNOR-based binary multiplier, and a pseudo-differential voltage-mode driver (i.e., an accumulator unit). Multiply-and-accumulate (MAC) operations between 64 pairs of inputs and weights (stored in the first 64 SRAM bitcells) are performed in 128 rows of the macro, all in parallel. A weight-stationary architecture, which minimizes off-chip memory accesses, effectively reduces energy-hungry data communications. A row-by-row analog-to-digital converter (ADC) based on 32 replica bitcells and a sense amplifier reduces the ADC area overhead and compensates for nonlinearity and variation. The ADC converts the MAC result from each row to an N-bit digital output taking 2N-1 cycles per conversion by sweeping the reference level of 32 replica bitcells. The remaining 32 replica bitcells in the row are utilized for offset calibration. In addition, this paper presents a pseudo-differential voltage-mode accumulator to address issues in the current-mode or single-ended voltage-mode accumulator. A test chip including a 16Kbit SRAM IMC bitcell array is fabricated using a 65nm CMOS technology. The measured energy- and area-efficiency is 741-87TOPS/W with 1-5bit ADC at 0.5V supply and 3.97TOPS/mm2, respectively. [ABSTRACT FROM AUTHOR]

This paper presents a cycle by cycle Frequency Shift Keying (FSK) demodulator, able to demodulate a FSK signal with 1% frequency modulation index (MI), in a single cycle. Based on the proposed demodulation scheme, a high rate data transmission link can be established through a high-Q inductive coupling link, breaking the basic tradeoff between the power transfer efficiency (PTE) and data rate in single carrier wireless power and data transfer systems. Designed and simulated with $0.18\mu m$ CMOS process, the proposed FSK demodulator, detects successfully a 5Mbps data with a carrier frequency of 5MHz. A test chip is fabricated in 180nm CMOS technology. Measurement results shows that the demodulator is able to demodulate the cycle-by-cycle modulated FSK signals with low modulation index of 2.5%, with a BER of $1.24\times 10^{-5}$. [ABSTRACT FROM AUTHOR]

This paper is concerned with the secure estimation problem for the state of charge of Lithium-ion batteries subject to malicious attacks during the data transmission from sensors to cloud-based battery management system terminal. First, the second-order resistance-capacitance equivalent circuit model, whose parameters are identified by Kalman filter in an off-line manner, is introduced to describe the internal dynamics of lithium-ion batteries. Then, by applying the $\chi ^{2}$ detection mechanism, real-time malicious attacks are first detected and then a secure estimator is designed to suppress the influence of attacks on the estimation performance. An upper bound of the filtering error covariance is determined by solving certain coupled Riccati-like equations, and the filter parameter is obtained by minimizing such an upper bound at each time step. Finally, the validity of the proposed attack detection approach and the effectiveness of the developed estimation scheme are verified by experiment results under Federal Urban Driving Schedule condition. [ABSTRACT FROM AUTHOR]

Demand for high speed data communications (> 1Gbps) and low latency (milliseconds scale or lower) has been on the rise [1,2,3,4,5]. The chief driving forces behind the demand for high speeds & low latency are applications of 8K video, 5G/6G, smart technologies and COVID19 pandemic-induced demands. For the emerging smart medical applications, especially the ones that are in metaverse, super high data speed with low latency is a must. All-optical network (AON) is one way to meet the demand. Perfluorinated graded-index polymer optical fiber (Gi-POF) is among the best media choices offering high data speeds. Gi-POF, complementing glass optical fiber (GOF) with its better bendability, can form all optical networks with optical/optical (O/O) connections. Due to reduced usage of E/O conversions, the latency of all optical networks will potentially be reduced, too. In this paper we will examine the functions of GI-POF O/O GOF. [ABSTRACT FROM AUTHOR]

This paper presents a series of multi-stage hybrid memristor-CMOS ternary combinational logic stages that are optimized for reducing silicon area occupation. Prior demonstrations of memristive logic are typically constrained to single-stage logic due to the variety of challenges that affect device performance. Noise accumulation across subsequent stages can be amortized by integrating ternary logic gates, thus enabling higher density data transmission, where more complex computation can take place within a smaller number of stages when compared to single-bit computation. We present the design of a ternary half adder, a ternary full adder, a ternary multiplier, and a ternary magnitude comparator. These designs are simulated in SPICE using the broadly accessible Knowm memristor model, and we perform experimental validation of individual stages using an in-house fabricated Si-doped HfOx memristor which exhibits low cycle-to-cycle variation, and thus contributes to robust long-term performance. We ultimately show an improvement in data density in each logic block of between $5.2\times - 17.3\times $ , which also accounts for intermediate voltage buffering to alleviate the memristive loading problem. [ABSTRACT FROM AUTHOR]

Large-scale neuromorphic computing requires the multi-chip network to provide high computing power. Efficient routing schemes and on-chip router design are necessary for handling various inter-chip transmission patterns. In this paper, we propose a hybrid-mode on-chip router that supports both multicast and unicast routing for the large-scale neuromorphic simulation. Two routing schemes, namely Cache-like Spike Weight Indexing and General Unicast Flow Control, are proposed to accommodate the chip-to-chip transmission of spike and non-spike data. This work is evaluated on a neuromorphic platform built with an $8\times 8$ FPGA chips array. Running a simulation of 1M neurons at 200MHz, the proposed router achieves a processing latency of 25ns and a chip-to-chip latency of 287ns. Working in the unicast mode, the router can synchronize status flags of all chips within $5 ~\mu \text{s}$. Moreover, it reduces the peak spike traffic by 25.65% with the help of Load-aware Multicast Routing, compared with other multicast routing strategies. [ABSTRACT FROM AUTHOR]

This paper focuses on the distributed consensus seeking of multi-agent systems (MASs) with discrete-time control updating and intermittent communications among agents. Compared with existing linearly coupled protocols, a nonlinear coupled Zeno-free event-triggered controller is first proposed, which is further to project the static and dynamic triggering mechanisms exploited by using the deadband control method. Then, the node-based nonlinear coupled adaptive event-triggered controller with online self-tuning of time-varying coupling weight and its corresponding to static and dynamic deadband-based event-triggered mechanisms are designed, respectively. The exploited adaptive event-triggered controller does not rely on any global information of interaction structure and is implemented in a fully distributed fashion. In addition, two dynamic proposals not only cover existing static strategies as special cases, but also show that the minimal inter-execution time of dynamic one is not smaller than that of static one. Theoretical analysis shows that the proposed static and dynamic deadband-based event-triggered mechanisms can not only ensure the average consensus with Zeno-freeness, but also achieve the data reduction of communication and control. Finally, the proposed algorithms applied to circuit implementation are corroborated to prove its practical merits and validity. [ABSTRACT FROM AUTHOR]

Keywords: Galway; Ireland; Europe; Cloud Computing; Data Transmission; Electronics; Information Technology EN Galway Ireland Europe Cloud Computing Data Transmission Electronics Information Technology 489 489 1 10/24/23 20231026 NES 231026 2023 OCT 29 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Devices & Surgical Technology Week -- Fresh data on Information Technology - Cloud Computing are presented in a new report. Keywords for this news article include: Galway, Ireland, Europe, Cloud Computing, Data Transmission, Electronics, Information Technology, National University of Ireland Galway. Galway, Ireland, Europe, Cloud Computing, Data Transmission, Electronics, Information Technology. [Extracted from the article]

Demand for super high speed data communications (> 1Gbps) and low latency (milliseconds scale or lower) has been on the rise. The chief driving forces behind the demand for super high speeds & low latency are applications of 8K video, 5G/6G, smart technologies and COVID19 pandemic-induced demands. In high-level autopiloting for automotives, high-speed rail trains, drones and other similar settings, it is essential to have lightweight, robust, no-interference and especially vital to have fast-acting, low-latency and high bandwidth in data communications and controls capabilities. In this paper, functions of perfluorinated graded-index polymer optical fiber (Gi-POF) as in-vehicle LAN communication and sensor-GPU linkages, step-index plastic optical fiber (SI-POF) as controls and glass optical fiber (GOF) as communication backbones are examined and compared. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of fault estimation for cyber–physical systems (CPSs) with intermittent measurement transmissions. A novel hybrid observer-based fault estimation scheme is proposed to generate estimations of the system state and the fault. Specifically, the correction terms of the designed observer are updated while new output measurements are available. Moreover, the estimation performance of the designed observer is analyzed within a framework of hybrid systems, and sufficient conditions are established to guarantee exponential input-to-state stability with a prescribed convergence rate based on the elaborately constructed Lyapunov function candidate. In contrast to the existing estimation schemes, the requirements of continuous or periodical communication are eliminated, and therefore the proposed one is more applicable for the modern industrial systems integrated with data communication networks. Finally, the application to an aircraft model is presented to illustrate the effectiveness of the developed methods. • Compared with the existing fault estimation schemes depending upon continuous measurements, the proposed one is developed based on the sporadic measurements, and therefore more applicable for CPSs integrated with data communication networks. • Inspired by considerations from the efficient utilization of available resources, an intermediate variable and two output error correction terms updated while new measurements get available are incorporated with the designed observer. Specifically, by employing the elaborately constructed Lyapunov function candidate, it is proved that the estimation error system is exponentially input-to-state stable with a prescribed convergence rate. • The estimation performance of the designed observer is analyzed within a framework of hybrid systems, which reveals the intermittent innovation properties triggered by the arrived measurements and helps to construct computationally tractable observer synthesis conditions. [ABSTRACT FROM AUTHOR]

This paper is concerned with the containment control problem for multi-unmanned aerial vehicle (multi-UAV) systems with data transmission among agents during a limited-bandwidth network. A good deal of data transmitted during a limited-bandwidth network may result in data collision, which brings negative effects on controller design and containment tracking implementation. To reduce the network load during data transmission, a consensus condition and a triggering subsidiary condition are first proposed to realize the containment tracking with H ∞ performance by using the triggered states. Then a self-triggered scheme is established under a multi-agent framework, in which the next triggering instant is calculated beforehand by using the past states. Combined with the self-triggered scheme, a containment controller is obtained via solving the derived consensus condition, which ensures that follower UAVs are driven into a convex set surrounded by leader UAVs. Finally, the validity of the self-triggered containment control method is proved through a simulation experience. [ABSTRACT FROM AUTHOR]

In cyber–physical systems (CPSs), secure estimation observes the states of a physical plant remotely with potentially attacked data. Most attacks in CPSs are carefully designed such that they can not only ruin the estimation but also bypass the detector. These attacked estimations would corrupt decision-making and control, leading to decreased production efficiency and even equipment damage. Therefore, detecting these attacks is of great importance. It is noted that one of the reasons that these attacks can be successfully launched is that attackers can inject arbitrary false data into the communication channel at any time step, which makes it possible that the transmission data is tampered with by any designed attack sequences. In this paper, a modified data transmission mechanism is deployed to limit the attacker's ability, and attack detectors are designed for detecting tampering attacks. Specifically, first of all, a one-bit event-triggered mechanism is deployed to binarize the transmitted data. Secondly, a primary detector is deployed to detect non-binary data received by the observer, and hence the attacker's ability is greatly reduced. Thirdly, a main detector is designed, which definitely detects tampering attacks that can bypass the primary detector.The necessary and sufficient conditions for definite attack detection are given, with which the gain of interval observable and the threshold of the event-trigger mechanism are designed. Finally, simulation results are presented to verify the analysis. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic output-feedback control for networked control systems (NCSs). The data transmissions in the sensor-to-controller and the controller-to-actuator channels are generated by the dynamic periodic event-triggering mechanism. Due to the existence of time-varying delays in the two channels, the updated data is received after a time delay. To cope with this problem, a hybrid dynamical framework of the NCSs is established. With the help of Lyapunov function-based approach, a new event-triggering condition is designed and sufficient conditions on input-to-state stability are derived. By introducing an auxiliary function, the obtained sufficient conditions are transformed into linear matrix inequalities and the explicit forms of the dynamic output-feedback controller gains are provided. Moreover, the upper bounds on the maximum allowable transfer intervals and the maximum allowable delays are derived. Finally, a numerical example illustrates the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Addressed in this paper is the observer-based waiting event-triggered control issue in multi-area load frequency control (LFC) power system subject to random communication delay and data packet dropout. In order to maintain the grid frequency stability of the multi-area LFC power system in an open communication network, an observer-based waiting event-triggered scheme (WETS) is proposed to deal with frequency fluctuation and extend the life of control equipments. Compared with the existing event-triggered mechanism, the proposed WETS has the merits of continuous event-triggered scheme and the periodic sampling event-triggered scheme in the both of theory and application. Then, by well considering the negative factors of data packet dropout and random time delay in data transmission, a stochastic delay-dependent multi-area LFC model is established, which involves the information of observer-based WETS, random communication delay and packet dropout in a unified structure. Further, an improved Lyapunov–Krasovskii functional (LKF) is constructed by dividing the interval of transmitted delay. Based on the constructed Lyapunov functional, Park's theorem and Jensen's integral inequality, some less conservative stabilization criteria are obtained. Finally, the validity of the proposed control method is verified via numerical examples. [ABSTRACT FROM AUTHOR]

In today's information era, cyber–physical systems (CPS) have been widely used in many industrial and infrastructure fields, and the study of security problems of CPS has become a crucial issue. For linear discrete-time systems, this paper investigates the state estimation problem based on the quantized innovations and transmission data tampering scenarios. From the attacker's view, by designing the tampering matrix and combining the property of the error function, the optimal attack strategy in the sense of maximizing the prediction error covariance matrix is given. From the defender's view, the optimal defense scheme based on multiplicative compensation is given in the case of a known attack strategy. Moreover, in the case of unknown attack strategies, a joint estimation algorithm is designed to give the optimal defense scheme subject to error constraints. In this paper, state estimators in recursive form are given for all above cases, and the algorithms are proved to be consistent. The theoretical results obtained are verified by simulations. • The recursive algorithms of state updating for system with quantized observations under data tampering attack. • Asymptotic performance of modified algebraic Riccati equation (MARE). • The optimal attack strategy in tampering transmission data to maximize hit impact. • A novel joint estimation approach to minimize attack impact when the attack strategy is known and unknown. • The optimal defense scheme to reach a balance between attack strategy estimations and the state estimation covariance matrix. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive event-triggered (AET) control, efficient model predictive control (EMPC) and output feedback control co-design approach for uncertain nonlinear systems over networks with bounded disturbance and data loss. The AET control involving a novel adaptive law is utilized to further reduce data transmission in networked control systems. Involving the technique of quadratic boundedness (QB), a class of output feedback predictive controllers based on the EMPC strategy are designed by minimizing several offline optimization problems and one online optimization problem. The approach in this paper, which transfers abundant online design work to offline, provides an offline determined augmented control invariant set for significantly reducing real-time computational load. Through the introduction of a novel matrix partition method moreover, the conventional online optimization problem of EMPC is transformed into a new form which is convenient to solve in this paper. A numerical example including some comparative experiments is proposed to clarify the availability of this approach. [ABSTRACT FROM AUTHOR]

The dynamic event-triggered control issue for multi-input and multi-output (MIMO) nonlinear systems with unknown dynamics and disturbances is solved in this paper. It is the first attempt to design a dynamic event-triggered mechanism for MIMO systems, which can further reduce data transmission from controller to actuator, thereby producing fewer event. The unknown dynamics of MIMO systems are approximated by neural networks. Then, the composited uncertain vector consisting of approximated terms and disturbances is transformed into a linear parameterized form with a single parameter. In addition, the dynamic event-triggered adaptive control method is designed under the backstepping framework. Finally, the validity of the presented dynamic event-triggered control solution is verified by simulation example and comparison analysis. [ABSTRACT FROM AUTHOR]

This paper is concerned with the communication protocol-based zonotopic state and fault estimation issue for a class of discrete time-varying industrial cyber-physical systems under bounded disturbances and constrained communication resources. First, in order to alleviate resource consumption, a round-robin protocol is developed to schedule the data transmission between the local sensor and the remote estimator. Second, a zonotopic set-membership estimation algorithm is developed to guarantee that the unavailable system state and fault signals could be simultaneously estimated and enclosed in a zonotope at every instant of time. Subsequently, the size of such a zonotope is minimized at each iteration by appropriately selecting a correlation matrix. Furthermore, the rigorous stability and performance analysis for the developed zonotopic estimation algorithm is provided. Finally, two simulation examples are provided to verify the obtained theoretical results. • Novel zonotopic set-membership estimation algorithm, where the zonotope guarantees to contain unknown system state and fault a rigorous stability analysis for the developed estimation scheme is provided by analyzing the boundedness of zonotope. • Finally two simulation examples are provided to show the effectiveness of the proposed estimation scheme. [ABSTRACT FROM AUTHOR]

Over 40 years, Step Index Plastic Optical fiber (SI-POF) has been utilized for wide variety of application like lighting, sensing, and data communication. Thanks to its large core diameter (typically 1 mm) and large numerical aperture (typically 0.5), dimensional tolerance of SI-POF can be extremely large. Using the advantage of SI-POF, the data communication application usages for much type of transportation system and industrial data communication system are expanding world widely. This paper introduces about the history of SI-POF technology requested from market and a potential market near future. [ABSTRACT FROM AUTHOR]

This paper aims to develop an improved sampled-data controller for T–S fuzzy systems in the presence of external disturbances and network-induced delays. To take more advantage of information about system state responses excited during sampling and data transmission, this paper introduces novel time integrals of the weighted derivative of the system state and they are utilized to construct an improved looped functional. Additionally, a refined discontinuous function is incorporated into the Lyapunov–Krasovskii functional, and three additional zero-equalities are incorporated into the stabilization conditions to enhance the relationship between the time integrals and other components of the augmented state. Moreover, this paper devises a less conservative relaxation technique that can numerically solve the dissipativity-based stabilization conditions dependent on affine-matched fuzzy-basis functions by exploiting their strict constraints. Finally, two examples are presented to illustrate the validity and applicability of the proposed approach. • Novel time integrals of the weighted derivative of the system state are introduced. • Refined discontinuous function is included in the Lyapunov–Krasovskii functional. • Additional zero-equalities are incorporated into the stabilization conditions. • A less conservative relaxation technique for parameterized stabilization conditions. [ABSTRACT FROM AUTHOR]

This paper investigates the algorithm design problem of recursive state estimation (RSE) for a class of complex networks (CNs) subject to quantized coupled parameter, missing measurements (MMs) and amplify-and-forward (AF) relay. In the node-to-node network channels, the signals before entering into the communication networks are quantized. In addition, a series of Bernoulli random variables is employed to model the phenomenon of MMs and an AF relay is deployed in the sensor-to-estimator network channels with the purpose of achieving the task of remote data transmission. A recursive state estimator is constructed such that, for all quantized coupled signal, MMs and AF relay, a state estimation error covariance (SEEC) upper bound (SEECUB) is presented and then the estimator gain (EG) is parameterized by optimizing the trace of SEECUB. Subsequently, a rigorous theoretical analysis is given to establish the monotonicity relationship between the trace of the minimized SEECUB and the probabilities of MMs. Finally, a simulation study is carried out for the proposed RSE approach to demonstrate the feasibility and validity of such state estimation strategy. • The recursive state estimation issue is addressed for coupled complex networks under amplify-and-forward relay communication. • New optimized state estimation scheme is given via parameterizing estimator gain in a proper way. • The monotonicity analysis regarding the trace of upper bound and probabilities of missing measurements is presented. [ABSTRACT FROM AUTHOR]

This paper discusses a control problem for a class of interval type-2 T-S fuzzy systems with mixed time delays. A multi-description coding and decoding mechanism is utilized to improve the reliability of data transmission. The measurement output is separately coded into two descriptions with rank and file information, and then the coded two descriptions are transmitted to the decoder via two independent communication channels which are random occurring packet dropouts. Sufficient conditions are established to assess the exponentially input-to-state stable in mean-square sense, and an explicit relationship is proposed for the effect of packet dropouts on decoding accuracy. Furthermore, the controller gains are calculated by applying the orthogonal decomposition technique. Finally, the applicability and effectiveness of the control method is illustrated by numerical simulation results. [ABSTRACT FROM AUTHOR]

• We propose a verifiable way to judge whether cloud mining pools are honest. This method enables fast verification without being affected by the performance limitations of IoT devices, while also helping IoT devices to select high-performance cloud mining pools in BCoT. • By implementing the additive homomorphic ElGamal cryptosystem, we not only achieve privacy protection in data transmission but also utilize a semi-honest cloud server to reduce the computational overhead of resource-constrained IoT devices. • We design the scheme in detail and analyzed the correctness and security of the scheme. Simultaneously, after the performance analysis and comparison with related schemes, our scheme has higher efficiency in the stage of aggregation and encryption and decryption. Blockchain of Things (BCoT), as a new paradigm that incorporates blockchain with the Internet of Things (IoT), can address the privacy and extensibility issues in IoT systems and effectively enhance the data management of IoT devices. Asmost of theIoT devices are resource-constrained in terms of computing power, storage capacity, and energy consumption. Meanwhile,the enormous computational consumption in the consensus process of the blockchain makes it difficult to integrate with IoT closely and exert the great potential of BCoT. latterly, the "cloud mining" mechanism has been proposed to address these issues, however,some potential problems still exist, such as data privacy and dishonest cloud mining pools, etc. In this paper, we propose a v erifiable and p rivacy- p reserving c loud m ining p ool s election scheme in BCoT (namely , VPP-CMPS). To obtain a better solution for cloud mining pool selection, we implement an improved time-locked puzzles technique to identify dishonest mining pools and perform the authenticity for mining pool selection.Afterwards,we obtain the privacy protection of the data during the entire selection process by adopting additively homomorphic ElGamal cryptosystem. Meanwhile, considering the resource-constrained case in IoT devices, we use a semi-honest cloud server to cooperate in dealing with the selection procedure, thereby reducing the computational overhead of IoT devices. Experimental results indicate that our scheme is more efficient and provides less computational cost. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time cooperative control problem for a class of multiple-master/multiple-slave (MMMS) teleoperation systems with external disturbances and internal system uncertainties is addressed. The MMMS teleoperation system has many potential applications due to its obvious structure advantages such as powerful environmental applicability, excellent load capacity, flexible collaboration and so on. Meanwhile, considering a large amount of data transmission, various uncertainties and collaborative coupling among the multiple operators and multiple manipulators, it is challenging to design a control strategy for the MMMS teleoperation system to achieve satisfactory control performance. To solve these issues, a novel robust fixed-time control strategy 15 is proposed for the uncertain MMMS teleoperation system. At first, a new virtual master-slave control framework for the MMMS system is constructed, which enhances the transparency of the system and makes system stability analysis easier. Then, new fixed-time disturbance observers (DOs) are designed separately for the master and the slave sides to accurately estimate the internal uncertainties and external disturbances under a more realistic assumption. Moreover, a new multi-dimension nonsingular sliding mode (SM) surface is presented, on which the states of the system can tend to the desired equilibrium in fixed time not affected by the initial state values. The cooperative control strategy based on the new DO and SM surface can not only ensure the fixed-time stability of the system, but also improve the system robustness to the external disturbances and internal uncertainties. In the end, simulations are performed to prove the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper deals with the H ∞ exponential synchronization problem of singular semi-Markov switched complex dynamical networks (CDNs) subject to transmitted delays. Firstly, an event-triggered communication mechanism (ETCM) is developed to save singular semi-Markov switched CDNs bandwidth. A positive constant sampled-data interval is applied to avoid the Zeno behavior in an ETCM. Secondly, by discussing the data transmission of sensors and controllers, the novel delays singular semi-Markov switched CDNs are modeled to investigate the H ∞ exponential synchronization problem of singular semi-Markov switched CDNs with transmitted delays via the based-on ETCM output control protocol. Moreover, some new sufficient conditions are established such that H ∞ exponential synchronization of singular semi-Markov switched CDNs can be achieved. Finally, the simulation result of the presented method is shown via two cases, which demonstrates the effectiveness of the main results. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time consensus control problem for a class of nonlinear multiagent systems (MASs) based on dynamic event-triggered mechanism. In contrast to the already-existing fixed-time control schemes, which cannot address the singularity problem, by constructing a virtual signal and using inequality technology, a new processing method is provided to solve such a problem. In addition, a novel fixed-time nonlinear filter that converges in a fixed time is introduced, which effectively solves the "explosion of complexity" problem existed in backstepping. Moreover, to improve the utilization of resources, an event-triggered mechanism with internal dynamic variables is proposed. It is worth noting that some existing static event-triggered mechanisms are special cases of the dynamic ones. On this basis, an effective fixed-time event-triggered control scheme is developed for MASs, which minimizes the data transmission as much as possible while ensuring the system performance. More importantly, the scheme can ensure the convergence of the system in a fixed time. Finally, simulation results are shown to support the validity of the developed approach. • Compared with the early results that may lead to the singularity problem, a practical fixed-time stability theory is introduced in this paper, which not only guarantees the convergence of MASs in fixed time, but also avoids the above problems in early results. • A novel fixed-time nonlinear filter is presented in this paper, which can not only solve the problem of "explosion of complexity", but also ensure that the designed nonlinear filter converges in a fixed time. • The controller developed herein is updated if only if the dynamic event-triggered condition is satisfied, which reduces the computational and communication burden, that is, the lower bound on inter-execution time in previous results is no greater than that in this paper. [ABSTRACT FROM AUTHOR]

In this paper, the resilient distributed filtering problem is studied for time-varying nonlinear multi-rate systems (TVNMRSs) with integral measurements over sensor networks, where the lifting technology is utilized during the analysis of the TVNMRSs. In order to reduce unnecessary data transmissions, the memory-event-triggered communication mechanism (METCM) is adopted to determine whether the sensor nodes communicate with each other. The purpose of this paper is to design a resilient distributed filtering method such that, for all multi-rate sampling, integral measurements, filter gain fluctuations and METCM, an upper bound on the filtering error covariance is guaranteed and minimized subsequently by choosing the appropriate filter gains. Besides, a sufficient condition with rigorous theoretical proof is provided to discuss the uniform boundedness of the upper bound on the filtering error covariance. In the end, the simulations with comparative experiments are made to demonstrate the effectiveness of proposed resilient distributed filtering algorithm based on METCM. • The METCM is used to regulate the communication among sensor nodes. • A new resilient distributed filtering scheme with recursive characteristic is proposed. • A sufficient condition is given to ensure the uniform boundedness of upper bound on the filtering error covariance. [ABSTRACT FROM AUTHOR]

[Display omitted] • The scheme does not require users' original data to be exchanged and relies on homomorphic encryption to ensure data security during processing and transmission. • Each operation in the scheme is performed using encrypted data. To ensure that the normal business of trusted institutions is not affected, the amount of calculation is kept to a minimum. • The system's security, execution efficiency, and final result accuracy are evaluated using both theoretical and experimental methods. In the Internet of Medical Things(IoMT), developing models using machine learning algorithms can detect and assist users effectively in identifying health issues. Due to the risk of private user information being leaked during the machine learning application process, the widespread application and development of IoMT applications are hampered. Encrypting data is a good way to protect user privacy. However, given the participants' limited resources, processing and analyzing ciphertext data presents a significant challenge. As a result, this paper proposes a secure and efficient assisted decision-making scheme (SEMMI) that is appropriate for the IoMT applications. SEMMI performs a thorough analysis of each participant's resource constraints, divides the data circulation process into four stages, and constructs a data circulation and ciphertext calculation protocol. Data transmission security is ensured through the use of stream encryption and homomorphic encryption. Each participant sends the ciphertext to the cloud, and the cloud calculates the ciphertext data, effectively relieving each participant's computational load. The security of the final result is guaranteed by matching the result with pre-decryption. The scheme's security and efficiency are demonstrated experimentally. The results indicate that the accuracy loss of each data set under the ciphertext is no more than 3% at most and that the cloud performs most of the calculations for each participant. Finally, SEMMI is applied to the FedAvg algorithm, demonstrating the scheme's universality. [ABSTRACT FROM AUTHOR]

This paper investigates the security tracking controller design for discrete-time networked control systems (NCSs) with stochastic cyber-attacks via dynamic event-triggered communication approach (DETCA). The DETCA is introduced to adjust the amount of data transmission in the network based on variation of the tracking error while keeping the tracking performance of the system. Stochastic cyber-attacks such as the denial-of-service and deception attacks are assumed to be encountered during the signal transmitted in the network. A sufficient condition to guarantee the asymptotical stability of the tracking error system is achieved with the Lyapunov stability theory. The tracking controller gain and the event-triggering parameter are co-designed by solving a linear matrix inequality. Finally, two simulation examples are given to verify the availability of theoretical results. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of robust stabilization for networked control systems (NCS) where the stochastic behavior of the network does not allow correct and complete transmission of data to both the actuators and the controller. The objective is to model the NCS using Takagi-Sugeno (T-S) fuzzy systems with uncertainties and external disturbances and to design a time-varying delay fuzzy controller such that the closed-loop system is robustly exponentially stable with a prescribed decay rate. Sufficient conditions are derived using the delay-dependent Lyapunov-Krasovskii functional with a robust H ∞ controller in terms of linear matrix inequalities (LMIs). Accordingly, desired fuzzy controllers are designed by using feasible solutions to the obtained LMIs. The proposed fuzzy controller can keep the T-S fuzzy system stable in the presence of time-varying delay, uncertainties, and external disturbance. Two numerical examples with different conditions on parameters are provided to illustrate the performance and robustness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the problem of joint communication and computation design for probability graph-based semantic communication over wireless networks is investigated. In the considered model, the base station (BS) extracts the compressed small-sized semantic data by removing redundant information based on the shared knowledge base between the transceivers. In particular, the knowledge base is represented as a probability graph, which summarizes the statistic relations of massive knowledge graphs. On the user side, the compressed information is accurately inferred on the basis of the same probability graph as the BS. Although this approach brings additional computation resource consumption for semantic information extraction, it effectively reduces communication resource consumption through the transmission of small-sized data. Both the communication and computation cost models are derived based on the inference process of the probability graph. Based on the formulated models, the problem of joint communication and computation resource allocation is proposed to minimize the total energy consumption of the network considering both latency and power limitations. To solve this problem, the closed-form solution of the transmission power is obtained with fixed semantic compression ratio. Then, an effective linear search-based algorithm is proposed to obtain the optimal solution of the considered problem with low complexity. Simulation results demonstrate the effectiveness of the proposed system compared with the conventional non-semantic schemes. [ABSTRACT FROM AUTHOR]

In this paper, the event-triggered filtering issue is addressed for a class of discrete-time nonlinear complex networks (CNs) considering random coupling strength (RCS) and missing measurements (MMs) under the condition that partial nodes information is accessible. To begin with, a uniformly distributed random variable over a settled interval is employed to model random changes in coupling strength. Then, a Bernoulli distributed random variable is considered to depict the phenomenon of MMs with uncertain occurrence probability. The event-triggered communication (ETC) protocol is applied to schedule data to relieve transmission burden. Subsequently, a novel partial-node-based recursive filtering algorithm is constructed by taking the influence of RCS, MMs and ETC mechanism into account, in which the filter gain is parameterized to achieve the minimization for the upper bound of filtering error covariance (UBFEC). Besides, performance discussion for the developed filter is provided through strict theoretical derivations, including the uniform boundedness and monotonicity relationship. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed estimation scheme. [ABSTRACT FROM AUTHOR]

The development of digital, networked and intelligent communication technology has led to significant growth in data and services. Especially in the communication scenario of monitoring data, a variety of downstream tasks bring significant technical challenges for high-performance data transmission, information mining, and data distribution. The problem to be solved is the coding and low bit-rate transmission of large amounts of surveillance data. Concepts and methods that utilize semantic communication are needed. This paper proposes a communication architecture based on the object–attribute–relation (OAR) semantic knowledge base. The sender uses the model parameters and prior knowledge in the knowledge base to drive the OAR extraction model to encode the image. After semantic coding and channel coding, the signal is transmitted to the receiver through the physical channel. At the receiver, the signal is decoded into a semantic vector. The OAR global vector is generated by structured processing, which is used for downstream tasks such as image retrieval or image reconstruction. Experimental comparison and analysis illustrate the effectiveness and superiority of each part of the communication framework. This approach provides a new solution for improving data utilization and processing efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes a novel network steganography (NS) based security framework to ensure the security operation of the cyber-physical systems (CPSs). Firstly, a new covert channel is established to conceal the existence of the secret data exchange by exploiting the dynamical system's measurements with no extra communication overhead. The covert channel evades the imperceptible and statistical detections in an effective manner. Next, combining covert transmission with data consistency, a data-based attack detection methodology is explored, which is capable of detecting a broad class of cyber-attacks and differs from the existing detection methods that enhance detection performance by degrading system performance or adding redundant systems. Then, combining covert transmission with simple linear encryption, an eavesdropping defense methodology is proposed, which guarantees that the authorized user's estimation performance is optimal and renders the eavesdropper's error covariance unbounded. Moreover, the detection and defense methods take small memory and computational overhead of the embedded system, which ensures the ease of implementation in real-world systems. Finally, the effectiveness of the proposed security framework is demonstrated by a proof-of-concept implementation on a CPS prototype called permanent magnet synchronous machine (PMSM) monitoring system. [ABSTRACT FROM AUTHOR]

This paper studies the observer-based fault detection problem for a class of semi-Markov jump systems with conic-type nonlinearity and unknown transition rates by an event-impulse mixed triggered (EIMT) scheme. The EIMT scheme is used to obtain well-developed sampled data and save communication resources. In order to ensure the sensitivity to faults and the robustness against disturbances, a multi-target fault detection strategy is proposed based on the given H _ / H ∞ index. Then, sufficient conditions for the presence of fault detection observer are derived, and a fault detection optimization algorithm is employed to improve the H _ / H ∞ performance. Finally, the effectiveness and superiority of the proposed method are proved by a DC motor simulation experiment. [ABSTRACT FROM AUTHOR]

The article discusses Huawei's call for joint efforts to drive industry development and bring Net5.5G into reality. The Broadband Development Conference (BDC) held during MWC Barcelona 2024 focused on network evolution and telco to techco transformation. Huawei's President, Leon Wang, emphasized the importance of Net5.5G in supporting ubiquitous 10 Gbps connections, ultra-broadband transport, hyper-converged data centers, and autonomous network self-optimization. The article also mentions the industry consensus on Net5.5G, its service scenarios, and the accelerated commercial deployment of the network. Additionally, it provides information about the World Broadband Association (WBBA) and its efforts to bridge the digital divide. [Extracted from the article]

The event-triggered security control and fault detection for nonlinear systems, in which the output signals are wirelessly transmitted to the control and detection module, is investigated in this paper. In particular, quantization before data transmission and deception attacks during data transmission are considered. To ease the data transmission pressure of wireless networks, a dynamic event-triggered protocol is proposed. Specifically, the triggering threshold changes in accordance with the system state. A stochastic sequence is introduced for modelling the time of occurrence of cyber-attacks within an insecure communication environment. By taking the dynamic event-triggered protocol, signal quantization and randomly occurring deception attacks into account, an integrated dynamic output feedback controller and fault detection filter module is developed. With the proposed design, stochastic stability is obtained, while the expected levels of security control performance and detection performance are also guaranteed. Novel algorithms are proposed for determining the parameters of the controller, filter and dynamic event-triggered protocol. A practical example is given to demonstrate the effectiveness of the proposed design idea. [ABSTRACT FROM AUTHOR]

This paper is focus on an event-triggered control design problem for nonlinear networked control systems with missing data and transmission delay in the interval type-2 (IT2) fuzzy form. An event-triggered controller is presented under a sampled-state-error mechanism. By dividing the event-triggered interval into some subsets, stability analysis is carried out based on Lyapunov-Krasovskii functional (LKF), and the stability of the closed-loop system is ensured. The proposed design is applied to the continuous stirred tank reactor system (CSTR) and the manipulator system. The control strategy is effective, and the merit of the event-triggered mechanism is indicated. [ABSTRACT FROM AUTHOR]

Researchers from the Harbin Institute of Technology in China have developed a new framework called DL-CEndo to improve the efficiency of data transmission in wireless capsule endoscopy. The framework uses deep learning to compress unnecessary data and send low-resolution luma images, conserving energy in the device. Additionally, a colorization model is implemented to reconstruct the colors of unnecessary images, and a demo for fast and smart summarization is introduced to aid physicians in the review process. The DL-CEndo framework achieved a high compression ratio of 93.20% and ensures fast diagnostics for physicians. [Extracted from the article]

This paper studies a distributed extended state observer design and dual-side dynamic event-triggered output feedback (DEOF) anti-disturbance control for interconnected systems (ISs) subject to quantization and multi-source disturbances. First, two novel dual-side dynamic event-triggered mechanisms (DETMs) are proposed to alleviate data transmission in both sensor-to-observer (S-O) and controller-to-actuator (C-A) channels. In addition, the DETM in S-O channel is related to the quantization parameter such that a trade-off between triggering frequency and quantization density can be achieved. Second, by using the transmitted system outputs, a distributed extended state observer is constructed to estimate system states and disturbances. Then based on the outputs of distributed extended state observer, a dual-side DEOF H ∞ controller is designed, which can compensate and attenuate two types of disturbances. Subsequently, some sufficient conditions are derived to guarantee system states and estimation errors converge to zero and system output satisfies H ∞ performance. Finally, a numerical simulation is provided to demonstrate the obtained results. • A distributed extended state observer for ISs is designed based on a novel DETM and a logarithmic quantizer. • A DETM containing the quantization parameter is designed such that a trade-off between event-triggered and quantization can be acquired. • A dual-side DETMs in both S-O and C-A channels are proposed to further save communication resources. [ABSTRACT FROM AUTHOR]

This paper delves into the design of an asynchronous Fault Detection Filter (FDF) for Singular Fuzzy Markovian Jump Systems (SFMJSs), particularly under the influence of multi-cyber-attacks, leveraging an enhanced adaptive event-triggered mechanism (AETM). Initially, a Hidden Markovian Model (HMM) is employed to characterize the asynchronous interactions between SFMJSs and FDF. Subsequently, a mode-dependent AETM alongside a dynamic quantization protocol is synergistically utilized to optimize communication bandwidth and augment data transmission efficiency. Additionally, the study introduces an expansive range of multi-cyber-attacks, encompassing deception, replay, and Denial-of-Service (DoS) attacks, to mirror inherent vulnerabilities in wireless signal transmission. Furthermore, the H ∞ performance of the FDF error system is assessed within a comprehensive framework using Linear Matrix Inequalities (LMIs), guided by a generalized performance index. This research establishes innovative admissibility criteria and filter conditions, aimed at guaranteeing the feasibility of desired FDF gains and ensuring the exponential admissibility of the FDF error system, underpinned by a generalized performance index. This manuscript concludes with two illustrative examples to demonstrate the efficacy of the proposed methodologies. [ABSTRACT FROM AUTHOR]

The security of multi-agent systems (MASs) is important particularly when considering the potential threat posed by malicious attackers. Specifically, network attacks and information theft caused by attackers have garnered significant attention due to their potential to destroy the consensus of the system. Therefore, this paper presents a novel approach to achieve leader-following consensus control of continuous-time MASs under DoS attacks, leveraging event-triggered encoding and decoding techniques. When the DoS attacks occur, the transmitted information between agents becomes unavailable. To address this challenge, a buffer is introduced to store the latest transmission data and then the stored data can be used when the DoS attacks exist. We also propose an event-triggered encoding–decoding strategy that can be employed for privacy protection in linear continuous-time MASs. The transmitted data is encoded as a codeword before transmitting, and the encoder updates it when event-triggered conditions are met. The receiving end decodes the data upon receipt. Furthermore, a distributed switching controller is designed using the encoded and stored state values to achieve leader-following consensus. The control gain is calculated to obtain sufficient conditions for DoS attacks through the linear matrix inequalities (LMI) and Lyapunov functions. The boundedness of transmitted data and the Zeno phenomenon are also analyzed. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

In this paper, an event-triggering mechanism (ETM) and a predictor compensation control strategy are proposed for cyber-physical systems (CPSs) with stochastic disturbance under malicious denial-of-service (DoS) attacks. First, a novel ETM excluded Zeno behaviour for CPSs is designed without considering DoS attacks, and the input-to-state stability (ISS) of the closed-loop systems is guaranteed. Second, given that DoS attacks could block the transmission of information, a predictor is used to compensate for the lost signals of CPSs. Then, a control strategy is proposed by combining the ETM and predictor, which can reduce the times of data transmission and control updates. Furthermore, a sufficient condition is derived to guarantee the ISS of the closed-loop system. Finally, the effectiveness of the proposed control strategy is verified by an example. [ABSTRACT FROM AUTHOR]

In this paper, the problem of fuzzy model-based leader-following consensus control for multi-agent systems (MASs) under deception attacks is investigated. For the sake of alleviating the communication burden, a novel memory-based event-triggered scheme (METS) is first proposed for the considered MASs to reduce redundant data transmission, and the leader-following consensus can be achieved faster with a smaller adjustment error by applying the historical released packets. Considering the designed METS and upper-bounded attacks synthetically, the closed-loop fuzzy system model is well established. Furthermore, with the help of Lyapunov-Krasovskii technique, some sufficient conditions are derived to ensure the consensus of MASs subject to deception attacks. Finally, a simulation example is introduced to manifest the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In recent years, the Internet of vehicles (IoV) technology becomes a research hotspot. However, it also becomes a hotbed for malicious attacks. In the IoV, frequent data transmission and complex connections among numerous different nodes increase the complexity and diversity of malicious attacks. In order to realize the accurate and rapid detection of malicious attacks in the IoV environment, in this paper, an intrusion detection method is proposed by combining oversampling, outlier detection and metric learning. The proposed approach improves intrusion detection effect in three main ways: 1) it oversamples the minority classes based on a novel strategy, 2) it introduces a new feature with basis of imbalance ratio, and 3) it reduces the outliers and rescales original samples actively to make the decision boundary clearer by combining outlier detection and distance metric learning. Furthermore, genetic algorithm is used to extract the optimal subset of features. The experimental results show that the proposed method can achieve 98.51% accuracy and maintain 0.82% false alarm rate on UNSW-NB15 dataset. Also, it outperforms the existing methods on ROAD, Car-Hacking and CAN-intrusion dataset for in-vehicle communications. [ABSTRACT FROM AUTHOR]

In this paper, a deadband event-triggered mechanism is used to reduce the transmission data of the network channel to improve the performance of networked control systems (NCSs) with limited communication. In view of the unmeasurable state signal in the actual network system, the dynamic output feedback control problem for the NCSs is studied. When network-induced delays, time-varying sampling intervals and signal transmission deadbands are considered simultaneously, the model of NCSs under the deadband event-triggered mechanism is constructed, and a sufficient condition for the stability of NCSs is given. Furthermore, the design method of the dynamic output feedback controller of NCSs under deadband event-triggered mechanism is proposed. Two simulation examples are used to show that the proposed approach can obtain the dynamic output feedback controller for NCSs with the deadband event-triggered mechanism, and also illustrate the deadband event-triggered mechanism can reduce the signal transmission in the network channel to obtain better system performance. [ABSTRACT FROM AUTHOR]

This paper investigates a multi-agent system with quantized event-triggered communication mechanisms to reduce the communication expenditure. The event-triggered communication mechanism is proposed to reduce the utilization of communication bandwidth, which lowers the communication expenditure in communication frequency. The quantized communication mechanism quantizes the communication information in the multi-agent system with limited communication capacity. First, a quantized periodic communication mechanism system is proposed, which provides a lower bound of the communication interval for the quantized event-triggered communication system to avoid the Zeno behavior. Then the system with quantized event-triggered communication is proved to be convergent to an optimal solution of distributed constraint optimization. With the quantized communication mechanism, the system can reduce the communication cost in the frequency of communication and the amount of transmission data. The proposed method has a tradeoff between energy saving and precision. Finally, the simulation results with comparisons verify the convergence of the system and exhibit the accuracy with different quantizer densities. [ABSTRACT FROM AUTHOR]

This paper is studied with the hierarchical type stability and stabilization of networked control systems (NCSs) with event-triggered mechanism (ETM). In the cause of reducing the amount of data transmission and saving the limited network bandwidth, ETM is introduced into NCSs, and the closed-loop time-delay NCSs model with ETM is presented. An improved Lyapunov–Krasovskii functional (LKF), containing delay-product-type terms and being appropriate for the canonical BesselLegendre inequality (BLI), is first constructed. Then, by utilizing the canonical BLI and the extended reciprocally convex matrix inequality (ERCMI) to deal with the single integral terms of the derivative of LKF, a sufficient condition on asymptotically stable is derived for NCSs. Based on above N-dependent stability criteria, a co-design method is developed, which can be capable of calculating the control gain of controller and the weighting matrix of the ETM. Finally, the feasibility and superiority of the results are verified by two examples. [ABSTRACT FROM AUTHOR]

This paper investigates the event-triggering adaptive neural network (NN) output feedback control problem for networked control systems subject to false data injection (FDI) attacks. To reduce unnecessary data transmission, an event-triggered mechanism (ETM) related to the measured output is designed on the channel of the sensor-to-observer. Meanwhile, a novel ETM associated with the observer state and parameter estimation signal is devised on the channel of the observer-to-controller to save communication resources on the controller-to-actuator channel. Subsequently, NN technique is employed to approximate FDI attacks, then an adaptive neural output feedback controller is designed to counteract the impact of FDI attacks on the system. Sufficient conditions for the semi-globally uniformly ultimately bounded of the system are obtained by means of the Lyapunov function. Additionally, a co-design scheme for the control gain, observer gain and event-triggered parameters is presented. Finally, a practical example is given to demonstrate the effectiveness of the proposed method. • Two ETMs are introduced in the sensor-controller channel to conserve network resources. • By using NN technique to approximate FDI attacks, and then an adaptive technique is employed to counteract their effect on the system. • Proposes a new output feedback control scheme. [ABSTRACT FROM AUTHOR]