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In this article, we construct a novel generalized policy iteration framework to address optimal regulation problems for discrete-time nonlinear systems in a more efficient way. Relevant properties are investigated for the framework, including ...

Information diffusion prediction aims to forecast the path of information spreading in social networks by exploiting user correlations or preferences. Recent works focus on characterizing the dynamic of user preferences and propose to capture users' ...

With the increasing complexity of cyber threats and the expanding scope of cyberspace, there exist progressively more challenges in cyber threat detection. It is proven that most previous threat detection models may become inadequate due to the ...

• Comprehensive review of LLMs for cyber threat detection stage.
• Explore four suitable cyber threat detection scenarios for LLMs.
• Explore different roles of LLMs in common cyber threat detection tasks.
• Discussion of extra ...

While the academic community has proposed dozens of probabilistic password guessing models to improve the success rate of password guessing, few studies have considered the speed of generating password guesses (which is a crucial factor in realistic ...

High-level synthesis (HLS) is an automated design process that transforms high-level code into optimized hardware designs, enabling rapid development of efficient hardware accelerators for various applications such as image processing, machine learning, ...

In this paper, a robust algorithm for enhancing indoor positioning accuracy utilizing time difference of arrivals is proposed. Addressing limitations of maximum likelihood estimation and traditional weighted least squares methods, which often ...$\mathit{}$

This paper investigates the optimal tracking issue for continuous-time (CT) nonlinear asymmetric constrained zero-sum games (ZSGs) by exploiting the neural critic technique. Initially, an improved algorithm is constructed to tackle the tracking ...

Multi-signature schemes have attracted considerable attention in recent years due to their popular applications in PoS blockchains. However, the use of general multi-signature schemes poses a critical threat to the security of PoS blockchains once ...

Most existing targeted password guessing models view users' reuse behaviors as sequences of edit operations (e.g., insert and delete) performed on old passwords. These atomic edit operations are limited to modifying one character at a time and cannot ...

In this article, an evolution-guided value iteration (EGVI) algorithm is established to address optimal tracking problems for nonlinear nonaffine systems. Conventional adaptive dynamic programming algorithms rely on gradient information to ...

In practical industrial processes, the receding optimization solution of nonlinear model predictive control (NMPC) is always a very knotty problem. Based on adaptive dynamic programming, the accelerated value iteration predictive control (AVI-PC) ...

With the rapid development of industry, the amount of wastewater discharge is increasing. In order to improve the efficiency of the wastewater treatment process (WWTP), we often desire that the dissolved oxygen (DO) concentration and the nitrate ...

• A SUP-HDP control algorithm is developed for the WWTP.
• This algorithm combines the advantages of PID algorithm and HDP algorithm.
• We give the proof of convergence and the implementation process of the algorithm.
• The SUP-HDP ...

The increasing use of multi-biometric authentication has raised concerns about the security of biometric templates. Many template protection methods based on convolutional neural network have been presented, but most involve a trade-off between ...

In this paper, an adjustable Q-learning scheme is developed to solve the discrete-time nonlinear zero-sum game problem, which can accelerate the convergence rate of the iterative Q-function sequence. First, the monotonicity and convergence of the ...

With the deepening of modernization and industrialization, the issues of water pollution and scarcity have become more pressing. To address these issues, many wastewater treatment factories have been built to improve the reuse of water resources. ...

In this paper, an optimal trajectory tracking control problem for general nonlinear systems is investigated. An adaptive critic control method with the digital twin (DT) theory is developed. Divergent from the existing tracking control methods, ...

Wastewater treatment is important for maintaining a balanced urban ecosystem. To ensure the success of wastewater treatment, the tracking error between the crucial variable concentrations and the set point needs to be minimized as much as ...

Prior work has developed responsible AI (RAI) toolkits and studied how AI practitioners use such resources when practicing RAI. However, AI practitioners may not have the relevant skills or knowledge to effectively use RAI resources—particularly as pre-...

In this article, an accelerated Q-learning algorithm with evolving control is established to solve the optimal tracking control problem. First, an accelerated Q-learning scheme is constructed with an advanced Q-function. By utilizing the advanced ...

This article aims to design a model‐free adaptive tracking controller for discrete‐time nonlinear systems with unknown dynamics and asymmetric control constraints. First, a new Q‐function structure is designed by introducing the control input ...