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Due to the dependence of consensus theory on multi‐agent systems (MAS) and the need to openly exchange status information with neighbors on each agent, private status and information are inevitably exposed to the public. In this paper, we present a consensus privacy protection algorithm to solve the consensus privacy problem of second‐order MAS. The proposed approach is based on the Paillier algorithm with semi‐homomorphic characteristics while combining a distributed control perspective to solve the privacy issues of sharing system status information. Under the conditions of our design, as long as there is at least one trustworthy neighbor node, the privacy of the topology nodes can be protected, and thus, the interconnected nodes are unable to detect the state information of systems from one another. We provide a new method for the privacy of the state information of the discrete‐time MAS and use restricted hardware devices to implement the consensus control. Finally, experiments verify the effectiveness of our method, while meeting the actual applicability [ABSTRACT FROM AUTHOR]

This article is aimed at the problems encountered by the fishing ground of set nets in Taiwan when the set net operators need to work when the weather is bad at sea. We developed a velocimeter that can be placed in the ocean for a long time and change sensing directions with the flow direction. The self-designed velocimeter has advantages, such as simple operation, low cost, and easy maintenance. With wireless monitoring and an early warning system, it can monitor current velocity, flow direction, sea temperature, and displacement. The data is transmitted back to the operator through the radio transmission module as a basis for dispatching personnel to go out to sea for fishing. To prevent the set net from drifting into the open sea due to bad weather, a GPS module is used to monitor the current location of the set net. If the waves wash away the set net, the warning signal can be received the first time to prevent the floating set net from endangering the safety of ship navigation and the survival of marine life. This innovative technology aligns with SDG 14, which aims to "conserve and sustainably use the oceans, seas, and marine resources for sustainable development". [ABSTRACT FROM AUTHOR]

With the development of technology, people work hard on image processing and artificial intelligence which require a lot of computer resources. Instead of simply speeding up calculations with processors, people develop the technology of the Cloud with the Internet which performs high‐quality calculations and has quite a huge amount of storage. Thus, in this paper, the authors use a kind of encryption methods, Secure Multi‐Party Computation (SMPC), to protect the important information which is based on the absence of a trusted party and does not use specific keys or methods to maintain the confidentiality of data. Furthermore, the authors also use the error correction, Berlekamp–Welch (BW) algorithm, to double‐check the correction of the information. To apply the two algorithms to image enhancement and convolution neural networks (CNN), the authors will also discuss the homomorphism in all operations, including addition, multiplication, division etc., and find the best way to encrypt and decrypt the information. Finally, the authors will implement the system with cloud computing to decrease the consumption of computer resources and build a system that can do image enhancement and CNN. [ABSTRACT FROM AUTHOR]

Different fish species and different growth stages require different amounts of fish pellets. Excessive fish pellets increase the cost of aquaculture, and the leftover fish pellets sink to the bottom of the fish farm. This causes water pollution in the fish farm. Weather changes and providing too many or too little fish pellets affect the growth of the fish. In light of the abovementioned factors, this article uses the artificial intelligence of things (AIoT) precision feeding management system to improve an existing fish feeder. The AIoT precision feeding management system is placed on the water surface of the breeding pond to measure the water surface fluctuations in the area of fish pellet application. The buoy, with s built-in three-axis accelerometer, senses the water surface fluctuations when the fish are foraging. Then, through the wireless transmission module, the data are sent back to the receiver and control device of the fish feeder. When the fish feeder receives the signal, it judges the returned value to adjust the feeding time. Through this system, the intelligent feeding of fish can be achieved by adjusting the amount of fish pellets in order to reduce the cost of aquaculture. [ABSTRACT FROM AUTHOR]

The purpose of this research is to develop a high-efficiency, low-cost, and easy-to-use tracking system for vehicles, and it is expected that the system can be extended to areas such as service robots, autonomous driving, and manufacturing. In this paper, we introduced an object detection algorithm based on convolutional neural networks to realize face recognition, which has better efficiency and robustness than traditional machine learning methods. With the concept of edge computing, we deployed the model on the local embedded system to improve the information transmission and security issues of cloud computing. In order to realize the tracking system, this paper builds a mecanum-wheel vehicle with omnidirectional mobility, and proposes a parallel-cascade PID controller architecture based on the mecanum-wheel vehicle. The fixed distance linear tracking control can be realized through the dual-loop feedback control of distance and yaw angle; moreover, the vehicle slipping which is caused by difference rotation speed can be improved. Finally, through algorithm optimization, controller parameter adjustment, and system integration, an omnidirectional mobile vehicle with recognition and tracking functions is realized. The experiment results indicate that the system is stable and robust during actual operation. [ABSTRACT FROM AUTHOR]

This paper is concerned with the global asymptotic stability (GAS) of a class of planar systems with a state‐dependent Riccati equation (SDRE) control. Based on the philosophy of feedback domination along with the depiction of the influence arising from system nonlinearities, a sufficient condition indicating the allowable intervals of control gains is established by which the GAS of the system with SDRE control can be guaranteed successfully. The presented condition is delicately equipped with a tunable parameter skillfully enhancing the feasibility while providing a new insight and perspective in ensuring global stability of the SDRE control. A numerical example is provided to verify the effectiveness of the proposed result. [ABSTRACT FROM AUTHOR]

This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov--Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov--Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results. Index Terms--Cellular neural networks (CNNs), linear matrix inequality (LMI), Lyapunov--Krasovskii functional theory, Takagi--Sugeno (T--S) fuzzy model, time-varying delay.

Several stability conditions for a class of systems with retarded-type delays are presented in the literature. However, no results have yet been presented for neural networks with neutral-type delays. Accordingly, this correspondence investigates the globally asymptotic stability of a class of neutral-type neural networks with delays. This class of systems includes Hopfield neural networks, cellular neural networks, and Cohen-Grossberg neural networks. Based on the Lyapunov stability method, two delay-independent sufficient stability conditions are derived. These stability conditions are easily checked and can be derived from the connection matrix and the network parameters without the requirement for any assumptions regarding the symmetry of the interconnections. Two illustrative examples are presented to demonstrate the validity of the proposed stability criteria. Index Terms--Cellular neural networks (CNNs), Cohen-Grossberg neural networks (CGNNs), Hopfield neural networks (HNNs), neutral-type neural networks.

This paper aims to present a synchronization scheme for a class of delayed neural networks, which covers the Hopfield neural networks and cellular neural networks with time-varying delays. A feedback control gain matrix is derived to achieve the exponential synchronization of the drive-response structure of neural networks by using the Lyapunov stability theory, and its exponential synchronization condition can be verified if a certain Hamiltonian matrix with no eigenvalues on the imaginary axis. This condition can avoid solving an algebraic Riccati equation. Both the cellular neural networks and Hopfield neural networks with time-varying delays are given as examples for illustration. Index Terms--Chaotic systems, Hamiltonian matrix, neural networks, synchronization.

In this paper a systematic approach, based on the linear-state-observer design for constructing two chaotically synchronized systems, is developed. The proposed method is then applied to suggest a means to secure communications. The method combines chaotic masking and chaotic modulation, where the information signal is injected into the transmitter and simultaneously transmitted to the receiver. Furthermore, two well-known chaotic systems, Rossler and Lorenz, and a hyperchaotic ROssler system are considered as illustrative examples to demonstrate the effectiveness of the proposed approach. Index Terms - Chaos, chaotic synchronization, secure communication, state observer.

A novel technique for transmission of information through visible light communication (VLC) is developed in this study. A light-emitting diode is used as the light source at the transmitting side to send the encrypted information. At the receiving side, a light sensor, OPT-101, is used to receive the light signals that carry the encrypted information. The Arduino Due microcontroller board is used for digital signal processing at both the transmitting and receiving sides. Furthermore, to prevent the transmitted message from being intercepted, two chaotic systems, a master and a slave, with a synchronization controller are designed to obtain the transmitted audio signals. The design enables not only a VLC system with the light transmission path as a straight line (so that data cannot be stolen) but also the encryption of the audio signals with the chaotic system (Rössler system) to enhance data transmission security. The effectiveness of this system is then experimentally verified. [ABSTRACT FROM AUTHOR]