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This paper presents an overview of three information‐theoretic methods, which have been used extensively in many areas such as signal/image processing, pattern recognition and statistical inference. These are: the maximum entropy (ME), minimum cross‐entropy (MCE) and mutual information (MI) methods. The development history of these techniques is reviewed, their essential philosophy is explained, and typical applications, supported by simulation results, are discussed.

With the rapid development of Internet technology, cybersecurity threats such as security loopholes, data leaks, network fraud, and ransomware have become increasingly prominent, and organized and purposeful cyberattacks have increased, posing more challenges to cybersecurity protection. Therefore, reliable network risk assessment methods and effective network security protection schemes are urgently needed.

Based on the dynamic behavior patterns of attackers and defenders, a Bayesian network attack graph is constructed, and a multitarget risk dynamic assessment model is proposed based on network availability, network utilization impact and vulnerability attack possibility. Then, the self-organizing multiobjective evolutionary algorithm based on grey wolf optimization is proposed. And the authors use this algorithm to solve the multiobjective risk assessment model, and a variety of different attack strategies are obtained.

The experimental results demonstrate that the method yields 29 distinct attack strategies, and then attacker's preferences can be obtained according to these attack strategies. Furthermore, the method efficiently addresses the security assessment problem involving multiple decision variables, thereby providing constructive guidance for the construction of security network, security reinforcement and active defense.

A method for network risk assessment methods is given. And this study proposed a multiobjective risk dynamic assessment model based on network availability, network utilization impact and the possibility of vulnerability attacks. The example demonstrates the effectiveness of the method in addressing network security risks.

Multiple Information Principle (MIP) is reviewed as a method of assigning a prior probability mass of density function to a random variable in the presence of some prior information. It is compared to the Maximum Information (MI) method and shown to be more general and inclusive of prior data available to the investigator. The image restoration problem is outlined as an inverse source problem with insufficient data for yielding a unique solution.

The possibility of improving the quality of the minimum relative entropy spectral estimates by properly selecting the set of autocorrelation values is demonstrated. The study concentrates on two aspects: resolvability and accuracy of peak location. Several numerical examples are given.

The current study’s goal is to investigate how lean, agile, resilient and sustainable human resource management (LARS HRM) affects green innovation and environmental performance, both directly and indirectly.

Partial least squares-structural equation modeling (PLS-SEM) was used to analyze the data based on a sample of 273 Tunisian businesses in the industrial and service sectors that were certified ISO 9001.

With the exception of AHRM–GPdtI, the results show that the mainstream advanced theory on direct effects was verified. With regard to indirect effects, everything of the literature that was presented was accepted, with the exception of the relationship between AHRM–GPdtI–EP, AHRM–GPssI–EP and RHRM–GPdtI–EP.

This research is distinctive in that it aims to incorporate every LARGS paradigm within the HRM field. By taking green innovation into consideration, it closes the current gaps on the direct and indirect effects of LARS HRM on environmental performance. Our study is unique in that it incorporates large, industry-operating, certified ISO 9001 firms with those in the service sector, with the goal of achieving greater generalization of results.