Complexity最新文献

This article proposed an image encryption scheme along a novel five-dimensional hyperchaotic system and a Fibonacci Q-matrix (FQ-matrix) for gray images. This designed algorithm follows two key stages: the confusion stage and the diffusion stage. In the confusion step and diffusion step, the placement of the plain image pixels is replaced by a 5D hyperchaotic map and pixel values are changed using the FQ-matrix, respectively. The fortitude of the designed encryption scheme is concluded by countering the algorithm on statistical analysis like histogram analysis, chi-square test, correlation coefficient analysis, information entropy analysis, differential attacks (NPCR, UACI), and NIST suite test. The produced algorithm’s experimental evaluation indicates that the entropy, NPCR, and UACI values tend to be ideal values. The numerous analyses indicate that the proposed algorithm has a lot of characteristics like the low correlation of adjacent cipher pixels, strong security, and large key space, which can give high confidentiality in image data.

The periodic oscillation transmission of infectious diseases is widespread, deep understanding of this periodic pattern and exploring the generation mechanism, and identifying the specific factors that lead to such periodic outbreaks, which are of very importanceto predict and control the spread of infectious diseases. In this study, to further reveal the mathematical mechanism of spontaneous generation of periodic oscillation solution, we investigate a type of SEIR epidemic model with a small intrinsic growth rate. By utilizing the singular perturbation theory and center manifold theorem, we extend the relaxation oscillation of three-dimensional SIR models to the four-dimensional SEIR models and prove the existence of stable relaxation oscillation with a large amplitude in the model. Numerical simulations are performed to verify our theoretical results. The results presented in this study provide a new idea for the study of the intrinsic mechanism of periodic oscillation in epidemiology, enrich the dynamics of epidemic models, and deepen the understanding of the global dynamics of these models.

The present paper introduces a novel object of study, a language fractal structure; we hypothesize that a set of embeddings of all n-grams of a natural language constitutes a representative sample of this fractal set. (We use the term Hailonakea to refer to the sum total of all language fractal structures, over all n). The paper estimates intrinsic (genuine) dimensions of language fractal structures for the Russian and English languages. To this end, we employ methods based on (1) topological data analysis and (2) a minimum spanning tree of a data graph for a cloud of points considered (Steele theorem). For both languages, for all n, the intrinsic dimensions appear to be noninteger values (typical for fractal sets), close to 9 for both of the Russian and English language.

At present, there are three main methods for analyzing the causes of ship collision accidents: statistical analysis, accident causation models, and knowledge graphs. With the deepening of research, the analysis methods pay more attention to the objective correlation between various factors of the accident, and the analysis results obtained are more objective and accurate. On this basis, this paper proposes a method for analyzing the contribution degree of different causes and accident conduction paths in ship collision accidents based on the construction of the Ship Collision Accidents Event Graph (SCAEG). Firstly, the ontology is constructed based on the grounded theory. Secondly, events and relationships are extracted after fine-tuning the UIE model. Thirdly, the SCAEG is constructed after event coreference resolution. Finally, this research conducts the contribution degree analysis, accident conduction path analysis, and accident spatial distribution analysis based on SCAEG. The advantages of this method include the following: (i) it can construct a more complete and accurate ontology; (ii) adopting this approach can unify various information extraction tasks and achieve good results based on small sample annotation data; and (iii) using this method, we can conduct contribution degree analysis of different causes, accident conduction path analysis, and spatial distribution analysis. Experimental evidence demonstrates the effectiveness of this method. The analytical results obtained from the experiments can provide assistant decision-making for relevant departments to reduce the occurrence of ship collision accidents and improve maritime traffic safety.

In this paper, we analyze the problem of managing users from different slices connecting to a software-defined network (SDN). We seek to minimize the propagation latency between switches and controllers as well as between controllers themselves. We also minimize the connection latency between users and their network access nodes. Thus, the main highlights of the paper are to formally represent the problem utilizing two equivalent mixed-integer quadratic programming models. The first one represents the user requirements of each slice by using a membership matrix. The second one consists of subsets of users separated within each slice requirement. Subsequently, the above models are analyzed in a standard linearized version. Finally, they are compared with a proposed local search math-heuristic algorithm. The proposed models and algorithm are solved with the CPLEX solver with default options. To the best of our knowledge, this journal paper constitutes a first attempt to incorporate network slicing in SDN allowing flexibility, resource efficiency, security, and effective management of the network facilitating the deployment of customized and adaptive services. Besides, our models allow us to deal with the management of connecting users to either controller or switch-type nodes depending on the slice to which each user belongs. For security reasons, a certain slice could only have access to the network controllers, while the rest of the users that belong to the other slices can connect to the switch-type nodes of the network. From the numerical experiments, we observe that the linear models show a better performance in terms of CPU times and the best solutions obtained. Similarly, our proposed approximation algorithm achieves near-optimal solutions in significantly shorter CPU times, for all the input graph networks, when compared to the proposed exact models which allows for finding the optimal solutions.

Opinion Dynamics is an interdisciplinary area of research. Disciplines of Psychology and Sociology have proposed models of how individuals form opinions and how social interactions influence this process. Sociophysicists have interpreted the observed patterns in opinion formation in individuals as arising out of nonlinearity in the underlying process and helped shape the models. Agent-based modelling has offered an excellent platform to study the Opinion Dynamics of large groups of interacting individuals. In this paper, we take recent models in opinion formation in individuals. We recast them to create a proper dynamical system and inject the idea of clock time into evolving individuals’ opinions. Thus, the time interval between two successive receipts of new information (i.e., the frequency of information receipts) by an individual becomes a factor that can be studied. In recent decades, social media has continuously shrunk time intervals between receipt of new information (i.e., increased frequency of information receipts). The recast models are used to show that as the time interval between successive receipts of new information gets shorter and the number of individuals in one’s network becomes larger, the propensity for polarization of an individual increases. This explains how social media could have caused polarisation. We use the word “polarisation” to mean an individual’s inability to hold a neutral opinion. A polarisation number based on sociological parameters is proposed. Critical values of the polarisation number beyond which an individual is prone to polarization are identified. These critical values depend on psychological parameters. The reduced time intervals between the receipt of new information and an increase in the size of groups that interact can push the polarisation number to approach and cross the critical value and could have played a crucial role in polarising individuals and social groups. We also define the extent of polarisation as the width of the region around neutral within which an individual is unable to have an opinion. Reported results are for values of model parameters found in the literature. Our findings offer an opportunity to adjust model parameters to align with empirical evidence. The models of opinion formation in individuals and the understanding arrived at in this study will help study Opinion Dynamics with all its nuances and details on large social networks using agent-based​ modelling.

The delayed intervention techniques in real-world problem modelling have a significant role in behavioural, social, physical, and biological engineering, biomathematical sciences, and many more disciplines. Delayed modelling of real-world problems is a powerful tool and nonpharmaceutical technique for understanding the dynamics of disease in a population. This paper considers real-world problems like the Lassa fever model. According to the World Health Organization (WHO), Benin, Ghana, Guinea, Liberia, Mali, Sierra Leone, Togo, Nigeria, and West Africa are the most affected countries with Lassa fever. The most dangerous situation is that eighty percent of the infected persons have no symptoms. To study the dynamics of Lassa fever, two types of populations are considered humans and rats. The human population includes susceptible, infected, and recovered. The rat population includes susceptible and infectious rodents. By introducing a delay parameter and decay exponential term into the existing model in the literature, we got the system of highly nonlinear delay differential equations (DDEs). The fundamental properties such as positivity, boundedness, existence, and uniqueness are verified for the said model. The equilibrium and reproduction number of the model are discussed. The reproduction number for the Lassa fever model is analyzed using the next-generation matrix method. If the reproduction number is less than one, this situation helps eradicate the disease. If the reproduction number is more significant than one, then the virus will spread rapidly in human beings. We have also investigated the effect of the delay factor on reproduction numbers. The local and global stabilities for both equilibria of the model have also been presented. Furthermore, computer simulations are designed to analyze the academic behaviour of the model.

We consider a deterministic optimal control approach with cost-effectiveness analysis for the diphtheria outbreak in the Rohingya refugee camp in Bangladesh. A deterministic epidemic dynamical model for diphtheria outbreaks has been developed with three optimal controls: vaccination, latent, and infectious treatment. Here, the qualitative study of the model has been interpreted. An objective function has been regarded as a cost function introduced by the optimal controls and the diseases themselves. Then, the existence and uniqueness of the optimal system have also been shown with the help of Pontryagin’s minimum principle. A numerical investigation has been carried out to solve the state and adjoint systems of optimality conditions. Furthermore, it has been investigated using several levels of availability of the optimal controls (vaccination, latent, and infectious treatment) to identify which level gives the best outcomes. Moreover, the cost-effective analysis has been inquired with the numerical value of the cost function and the total cured population in each control strategy to clarify the strategy with the least cost but maximum remediation.

We find that in the upstream status of global value chain, country effects are relatively stronger than industry effects; industry effects dominate country effects downstream of the global value chain. During financial crisis, downstream in the value chain, the influence of industry effects waned and country effects rose. Moreover, for developed countries, the negative impact of the upstream status of value chain weakened considerably; the impact of upstream status strengthened for emerging markets after the subprime mortgage crisis. For tradable industries, the negative impact of global value chain upstream status on pure industry-specific returns strengthens significantly.

We consider a continuous-time model describing the interaction between phytoplankton and zooplankton using a Holling type-II response. We then transform this continuous-time model into a discrete-time counterpart using a fractional-order discretization method. The paper explores the local stability of this obtained system concerning all equilibrium points and establishes the global asymptotic stability of its positive fixed point. The study also demonstrates that, under specific mathematical conditions, the system undergoes a Neimark–Sacker bifurcation around its positive equilibrium point. To effectively manage this bifurcation, two modified hybrid control techniques are introduced. The paper concludes by presenting illustrative numerical examples that validate the theoretical findings and assess the effectiveness and feasibility of the newly proposed control strategies. In addition, a comparative analysis is conducted between the modified hybrid techniques and an existing hybrid approach.