Complexity最新文献

With the rapid development of the digital economy, there has been an explosion in the amount of data generated. Data have become a vital resource for nations, just as tangible assets and human capital are crucial factors of production. Consequently, protecting digital security has become paramount. However, the increasing frequency of various data security incidents in recent years has exposed issues such as inadequate platform governance, lack of government regulation, and incomplete digital security governance (DSG) mechanisms. This study aims to create a healthy and open digital ecosystem and proposes a new digital security governance framework. It subdivides traditional government departments into local governments and the central government. Together with third-party platforms, they are analyzed as participants in an evolutionary game. The study examines the evolutionary stability of strategy choices made by each party and explores the relationship between key factors such as negative externalities, data security incident probabilities, and their impacts on strategy selection using numerical simulations. The research findings indicate the following. (1) Key parameters such as implicit benefits, government subsidies, and negative externalities play a significantly positive role in the development of the digital ecosystem. (2) The central government consistently tends towards emergency response, considering the overall societal perspective, as long as it is capable of bearing the costs. (3) Local governments may exhibit free-riding behavior during the governance process. To address this, it is important to increase the willingness of third-party platforms to govern and oversee the participation of local governments, which is an effective way to prevent data crises. The study also identifies different governance models in various environments: (1) a digital security governance model in a stable market environment, involving increased central government intervention and supervision of local governments’ participation; and (2) a digital security governance model in the event of a data crisis, where the central government establishes subsidies that exceed the governance costs of local governments to enhance the willingness of third-party platforms to govern. Finally, recommendations and strategies are presented to enhance the level of digital security governance.

In recent years, in the classic battles and armed conflicts around the world, battlefield environment reconnaissance and the collection and processing of operational information play an increasingly critical role in the victory and defeat of the battlefield. Unmanned equipment, especially UAV equipment, is used by more and more countries in the field of combat reconnaissance. Meanwhile, the types of UAV are gradually diversified with the change of operational requirements. UAVs adapted to different combat environments shine brightly on the battlefield. In terms of naval battle field, due to the limitations and deficiencies of reconnaissance methods such as surface radar, UAVs play a more prominent role in combat reconnaissance. There are more scenarios for UAVs to be used in combat reconnaissance in naval battle field and higher requirements for UAVs’ combat effectiveness. Therefore, this paper takes UAVs’ naval battle reconnaissance missions as the research object. By using PSO as the research method, this paper studies the combat reconnaissance task configuration of UAVs, hoping to contribute to the improvement of UAVs’ combat reconnaissance capability and combat effectiveness.

The heat kernel associated with a discrete graph Laplacian is the basic solution to the heat diffusion equation of a strict graph or network. In addition, this kernel represents the heat transfer that occurs over time across the network edges. Its computation involves exponentiating the Laplacian eigensystem with respect to time. In this paper, we expand upon this concept by considering a novel network-theoretic approach developed in recent years, which involves defining the k-path Laplacian operator for networks. Prior studies have adopted the notion of integrating long-range interactions (LRI) in the transmission of “information” across the nodes and edges of the network. Various methods have been employed to consider long-range interactions. We explore here the incorporation of long-range interactions in network analysis through the use of Mellin and Laplace transforms applied to the k-path Laplacian matrix. The contribution of this paper is the computation of the heat kernel associated with the k-path Laplacian, called the generalized heat kernel (GHK), and its employment as the basis for extracting stable and useful novel versions of invariants for graph characterization. The results presented in this paper demonstrate that the use of LRI improves the results obtained with classical diffusion methods for networks characterization.

This paper is offered as a contribution to understanding historical trade. The method of input-output modelling is utilised to evaluate the evolution of cities (and their associated regions) in England and Wales between 1851 and 1911. The construction of input-output accounts for each city region is based on “heroic” data assumptions, which enable the construction of a demonstration model illustrating a new iterative approach to historical analysis. In its current application, the model enables estimates to be made of mesolevel trade between cities, which enhances our analysis of urban evolution in this period.

Consumers in developing countries, particularly Africans, are strongly criticized for their unfavorable feeling about locally produced apparel products. With this concern, this paper explores the determinants of Ethiopian consumers’ purchasing behavior towards locally produced apparel products by using the extended theory of planned behavior (TPB) model. A self-administered questionnaire which consists of open and closed-ended questions was developed based on the literature. Cross-sectional data were collected from 478 Ethiopian consumers by following the convenience sampling technique and were analyzed by structural equation modeling with AMOS V.26.0. The ethnocentric tendency of Ethiopian consumers was found at a moderate level. The consumers had a very high purchasing intention towards locally produced apparel products but had a low actual purchasing behavior. The result also showed that Ethiopian consumers use price, garment fitness, comfort, and color as the most important attributes, while the country of origin and notions were found to be the moderate important attributes. Moreover, consumers’ attitude towards locally produced apparel products was found as the most influential factor, while perceived behavioral control and subjective norms were the least influential factors in affecting consumers’ purchasing intention. The study’s findings provide insight into domestic apparel consumption as well as the factors affecting consumer purchasing intentions and behavior in the Ethiopian context. The study incorporates product attributes and ethnocentrism into the TPB model to investigate their impact on consumer purchasing intentions which are rarely investigated together.

This investigation centers on megastable systems, distinguished by their countable infinite attractors, with a particular emphasis on the Quadratic Megastable Oscillator (QMO). Unlike traditional megastable oscillators reliant on external excitation, our proposed QMO operates autonomously, contributing to its distinctiveness. Through a comprehensive exploration of the QMO, we elucidate various dynamical behaviors, enriching the understanding of its complex system dynamics. In contrast to conventional megastable oscillators, the QMO yields nested types of multiple attractors for diverse initial conditions, elegantly depicted in phase portraits. To gauge the sustainability of chaotic oscillation, we employ influential parameter bifurcation plots, providing a nuanced insight into the system’s dynamical evolution. The complexity of the proposed system is further underscored by its intricate basins of attraction, accommodating an infinite number of coexisting attractors. Exploring trajectory dynamics, we observe that certain initial conditions lead trajectories to distant destinations, evading the influence of local attractors. This behavior underscores the uniqueness of the QMO and highlights its potential applications in scenarios requiring nonlocalized attractor behaviors. Taking a practical turn, the QMO is applied to biometric fingerprint image encryption, demonstrating its efficacy in real-world applications. Rigorous statistical analyses and vulnerability assessments confirm the success of the QMO in providing secure encryption within chaotic system-based frameworks. This research contributes not only to the theoretical understanding of megastable systems but also establishes the QMO as a valuable tool in encryption applications, emphasizing its robustness and versatility in complex dynamical scenarios.

This study, employing convenience sampling of art specialists, investigates the emotional resonance of young consumers with Chinese bamboo patterns, underscoring their significance in the realm of contemporary design. Through the lens of Kansei engineering, we delve into the intricate world of bamboo weaving patterns, scrutinizing their perceptual evaluations and user preferences among 104 art university students aged 18–23. Our analysis not only identifies pivotal factors for innovative redesign but also underscores the pivotal role of these traditional patterns in enhancing the emotional and aesthetic appeal of products for the younger generation. The findings illuminate a notable appreciation among this demographic for the ecofriendly and culturally rich bamboo patterns, positioning them as essential elements in modern lifestyle products. The study advances the discourse on integrating cultural heritage into product innovation, advocating for designs that resonate with the aesthetic sensibilities and environmental values of today’s youth. This aligns with the critical insights into the various categories of patterns and their diverse applications in contemporary design, addressing the cognitive gap between designers and consumers and highlighting the importance of cultural motifs in product development.

This study addresses an adaptive neural funnel fault-tolerant control problem for a class of strict-feedback nonlinear systems with actuator faults and input dead zone. To guarantee the boundedness of the tracking error, a modified transformation for funnel error is devised and incorporated into the control design process. To manage unknown nonlinear functions, radial basis function neural networks (RBFNN) are employed in designing an adaptive neural funnel fault-tolerant controller through the backstepping technique. The proposed controller guarantees the output tracking error stays within a predefined funnel, and all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, simulations of a rigid robot manipulator system and an inverted pendulum system are conducted to validate the practicality and effectiveness of the proposed control method.

In this paper, a mathematical model is formulated, suitable to explain the evolution of income distribution over a population in the presence of production. The model is conceived from the perspective of complexity. Indeed, the income distribution emerges as the result of a myriad of economic exchanges taking place between individuals. In fact, the aim of the paper is to provide a framework and mathematical tools for the construction and the investigation of models having an exploratory character. The framework is expressed in the form of a system of nonlinear ordinary differential equations, as many as the income classes are, involving transition probabilities. Numerical solutions of these systems are constructed under different assumptions on the law of production and in the presence of different fiscal systems, which provides an example of the versatility of the method.

Tourist resorts play a crucial role in providing people with diverse and high-quality leisure and vacation options. The development of tourist resorts is integral to the high-quality growth of the national tourism industry. This study utilizes a combination of the nearest neighbour index, kernel density analysis, and geographic concentration index to examine the spatial and temporal distribution of 758 national and provincial tourist resorts in China. The analysis reveals several key findings: (1) the years 1992 and 2015 were pivotal for the development of China’s tourist resorts, with significant government attention and steady growth in the number of national tourism resorts from 2015 to 2023. (2) The distribution of China’s tourist resorts shows an overall uneven distribution at a national level but a more balanced distribution locally. The southeast region exhibits a high and even distribution density, while the northwest region has a lower density and quantity of resorts. (3) Some specific areas have emerged such as the junction of Anhui, Hubei, and Jiangxi provinces as the first core gathering areas and the junction of Shanxi, Jiangsu, and Zhejiang provinces as the secondary core areas. These core areas have gradually weakened and spread to other regions, leading to changes in the distribution patterns of tourist resorts. (4) The distribution of China’s tourist resorts is influenced by various factors, including economic development, resource endowment, source market, and government support. Government support is a key factor in accelerating the development of tourism resorts. These findings shed light on the complex dynamics shaping the distribution of tourist resorts in China.