Information Transmission In Networks Research Articles

Coupled propagation between one communicable disease and related two types of information on multiplex networks with simplicial complexes

Currently, regarding the coupling transmission of information and disease, most researches only focus on the impact of one type of information on disease transmission, and some works may be correlated with two types of information, but they are usually based upon pairwise interactions, which ignored the complexity and diversity of information transmission. In real life, the characteristics of interpersonal networks often involve both group interactions and pairwise interactions. Aiming to explore the influence of active or passive information diffusion on the transmission of epidemics on a higher-order network, the coupled two-layered multiplex network model between communicable disease and information transmission is presented. Here, the upper layer characterizes the information transmission network constructed from random simplicial complexes, while the lower layer provides the underlying network that can transmit communicable diseases. First, on the basis of micro Markov chain (MMC) method, the epidemic threshold is analytically derived for the proposed model, indicating that the diffusion of positive and negative preventive information can exert a substantial influence on the critical threshold. Then, by comparing the results acquired by MMC and Monte Carlo simulations (MCS), it can be explicitly expressed that the differences between them are minimal, which implies that the model can predict the transmission of epidemics in the network well. Finally, through extensive MCS, it is also indicated that introducing a 2-simplex into the information layer helps to suppress the propagation or outbreak of communicable diseases, which offers some new ideas or routes for formulating strategies to inhibit communicable diseases.

人工智能技术在网络信息安全中的应用研究

With the continuous iterative development of computer technology, computer technology has been widely applied in various fields of real society, and artificial intelligence technology is also developing synchronously with computer technology. In the computer network environment, supporting artificial intelligence technology through programming techniques can mimic human neural networks and achieve various intelligent operation functions. However, in today’s society, the network environment is becoming increasingly complex, and the security of network information transmission is gradually being affected. Therefore, it is necessary to ensure the security of the network information environment through the improvement and application of artificial intelligence technology, in order to conduct deeper research on artificial intelligence technology and create a favorable objective environment for its application.

GEOPOLITICS, UNCERTAINTY, AND CRYPTOCURRENCY: A LOVE TRIANGLE GONE WRONG

This study aims to investigate the spillover effects from geopolitical risks (proxied by the geopolitical risk index GPRD) and cryptocurrencies-related uncertainty (proxied by the Cryptocurrency Uncertainty Index UCRY) to cryptocurrencies. We utilize the Baruník and Křehlík (2018) framework to detect time-frequency connectedness. Our investigation for the period 2017 to 2022 discovers significant spillover effects from both indices (GPRD and UCRY) to cryptocurrencies. Utilizing the information transmission theory and network graphs, our findings reveal that some cryptocurrencies function as net receivers of spillovers from geopolitical risks and uncertainty in the short-term, while over longer time horizons they transform into net transmitters of spillovers to uncertainty. The study underscores the importance of comprehending how uncertainty due to various factors (geopolitical, policy changes, regulatory changes, etc.) could affect the cryptocurrencies’ markets.

Spiking Neural Membrane Systems with Adaptive Synaptic Time Delay.

Spiking neural membrane systems (or spiking neural P systems, SNP systems) are a new type of computation model which have attracted the attention of plentiful scholars for parallelism, time encoding, interpretability and extensibility. The original SNP systems only consider the time delay caused by the execution of rules within neurons, but not caused by the transmission of spikes via synapses between neurons and its adaptive adjustment. In view of the importance of time delay for SNP systems, which are a time encoding computation model, this study proposes SNP systems with adaptive synaptic time delay (ADSNP systems) based on the dynamic regulation mechanism of synaptic transmission delay in neural systems. In ADSNP systems, besides neurons, astrocytes that can generate adenosine triphosphate (ATP) are introduced. After receiving spikes, astrocytes convert spikes into ATP and send ATP to the synapses controlled by them to change the synaptic time delays. The Turing universality of ADSNP systems in number generating and accepting modes is proved. In addition, a small universal ADSNP system using 93 neurons and astrocytes is given. The superiority of the ADSNP system is demonstrated by comparison with the six variants. Finally, an ADSNP system is constructed for credit card fraud detection, which verifies the feasibility of the ADSNP system for solving real-world problems. By considering the adaptive synaptic delay, ADSNP systems better restore the process of information transmission in biological neural networks, and enhance the adaptability of SNP systems, making the control of time more accurate.

Functional connectivity characteristics of the brain network involved in prickle perception of single fiber stimulation.

The complex network connections, information transmission and organization play key roles in brain cognition on sensory stimulation. Previous studies showed that several brain regions of somatosensory, motor, emotional, cognitive, etc. are linked to fabric-evoked prickle. But the functional connectivity characteristics of the brain network involved in prickle perception is still unclear. In the present study, resting state fMRI (functional magnetic resonance imaging) with functional connectivity analysis was adopted to build the initial brain functional network, and task fMRI with psychophysiological interaction analysis was employed to investigate modulation features of prickling task to functional connections in the brain network. The results showed that, in resting state, six groups or sub-networks can be identified in the prickle network, and when the subjects performed the prickling task, functional connectivity strength between some seed regions (e.g., somatosensory regions and precuneus, emotional regions and the prefrontal cortex, etc.) in the network increased. Combining resting-state fMRI with task fMRI is a feasible and promising method to study functional connectivity characteristics of the brain network involved in prickle perception. It is inferred that the "itch" ingredient of prickle sensation was transmitted from somatosensory cortices to precuneus, and emotional attribute (e.g., pain) from somatosensory cortices to the prefrontal cortex and at last to emotional regions.

Identifying key players in complex networks via network entanglement

Empirical networks exhibit significant heterogeneity in node connections, resulting in a few vertices playing critical roles in various scenarios, including decision-making, viral marketing, and population immunization. Thus, identifying key vertices is a fundamental research problem in Network Science. In this paper, we introduce vertex entanglement (VE), an entanglement-based metric capable of quantifying the perturbations caused by individual vertices on spectral entropy, residing at the intersection of quantum information and network science. Our analytical analysis reveals that VE is closely related to network robustness and information transmission ability. As an application, VE offers an approach to the challenging problem of optimal network dismantling, and empirical experiments demonstrate its superiority over state-of-the-art algorithms. Furthermore, VE also contributes to the diagnosis of autism spectrum disorder (ASD), with significant distinctions in hub disruption indices based on VE between ASD and typical controls, promising a diagnostic role for VE in ASD assessment.

High-capacity medical information hiding scheme with P-tensor product secret image sharing for wireless body area networks

Given the escalating demand for information transmission in the resource-restricted wireless body area networks (WBANs), securing medical data and minimizing energy consumption are paramount. We present an innovative information hiding scheme that employs P-tensor product secret image sharing (PTP-SIS) and multiple information-hiders for WBANs. Considering the remarkable compression performance demonstrated by compressed sensing (CS), as well as its link to Shamir's (k, n) secret sharing method, using CS rather than traditional secret sharing techniques for image processing purposes could potentially help alleviate transmission burden of sensor nodes. However, utilizing CS to process high-dimensional signals poses a significant challenge due to the large dimensionality of the measurement matrix. The P-tensor product (PTP) is a tool that offers outstanding universality and can overcome the dimension limitations of traditional matrix multiplication, it is applied in the secret sharing stage. Moreover, applying the ideas of secret sharing leads to less stress on an individual device as well as lower communication spending, and multiple hiders have the ability to independently embed additional secrets into shadow images for efficient information backup. Theoretical analysis and experiments validate that the proposed scheme ensures information security and transmission efficiency while achieving superior image recovery performance and higher information embedding rates compared to other approaches.

Stability detection method of large-scale network information transmission based on digital twin technology

Stability detection method of large-scale network information transmission based on digital twin technology

Heuristic Greedy-Gradient Route Search Method for Finding an Optimal Traffic Distribution in Telecommunication Networks

Rapid growth in the volume of transmitted information has lead to the emergence of new wireless networking technologies with variable heterogeneous topologies. With limited radio frequency resources, optimal routing problems arise, both at the network design stage and during its operation. We propose an algorithm based on a minimum loss intensity (greedy-gradient algorithm) to search for optimal routes of information transmission in telecommunication networks. The relevance of the developed algorithm is determined by its practical use in data-transmitting modeling systems. The proposed algorithm satisfies several requirements, such as the speed of the calculations performed, the fulfillment of the conditions for its convergence, and its independence on the selected loss probability function, as well as on the network topology. The idea of the algorithm is a step-by-step recalculation of metrics based on derivatives of the loss intensity function with simultaneous redistribution of information flows along the routes determined by the Floyd algorithm. The comparative efficiency of the proposed algorithm is demonstrated by computational experiments on various network topologies (up to 100 nodes) with various traffic intensities.

Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain’s computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapt across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in male mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.

Analysis of Spatial Diversity Technology based on MIMO Antenna Structures

Antenna technology has been continuously evolving and innovating in information transmission networks, providing essential support for information transfer and network infrastructure. This article focuses on introducing the key technologies of MIMO technology and space diversity technology, and analyzes the advantages of space diversity technology based on MIMO antenna structure. By exploring these key technologies in depth, this article helps readers better understand antenna technology and its applications.

On distance-based topological indices and co-indices of fractal-type molecular graphs and their respective graph entropies.

In graph theory, a topological index is a numerical value that is in good correlation with certain physical properties of a molecule. It serves as an indicator of how a chemical structure behaves. The Shannon's entropy describes a comparable loss of data in information transmission networks. It has found use in the field of information theory. Inspired by the concept of Shannon's entropy, we have calculated some topological descriptors for fractal and Cayley-type dendrimer trees. We also find the entropy that is predicted by these indices.

Anti-resonance fiber propagating 86 orbital angular momentum modes with high purity for a long distance

Future advances in information transmission technology require better capacities for fiber optics communication. As a new degree of freedom, the orbital angular momentum (OAM) has attracted extensive attention in the field of mode division multiplexing. Herein, an anti-resonance fiber (ARF) is designed with three different materials, SF11, LaSF09, and SiO2, for the negative curvature tube. Systematic analysis and optimization are carried out to determine the number of layers of the negative curvature tubes in the cladding, the number of second-layer cladding tubes, and thickness of the annular area. The finite element analysis software COMSOL is utilized to calculate the effective refractive index difference, dispersion, limiting loss, and other characteristics. The ARF can stably transmit 86 OAM modes in the wavelength range between 1.2 and 2.0[Formula: see text][Formula: see text]m, and the minimum refractive index difference is greater than [Formula: see text], which effectively reduces the mode abridgment. The nonlinear coefficients of the HE[Formula: see text] mode and the OAM purity of HE[Formula: see text] mode are 0.34[Formula: see text]km[Formula: see text][Formula: see text]⋅[Formula: see text]W[Formula: see text] and 99.43%, respectively, thus facilitating stable transmission of OAM modes for a long transmission distance. The anti-resonance fiber has significant application potential in long-distance network information transmission, relay communication, and other communication areas.

Information Transmission in a Social Network: A Field Experiment

Information Transmission in a Social Network: A Field Experiment

Eesti mobilisatsioonipõgenike kirjasuhtlusest Soome Jätkusõja ajal

The article deals with the letters of young men who escaped from Estonia to Finland during the German occupation in order to avoid the mobilization announced in 1943. Almost immediately after arriving in Finland, some of the refugees illegally emigrated to Sweden, but the majority started looking for temporary accommodation and work in Helsinki and its surroundings. The Continuation War (1941–1944) was going on, and thus a large number of Estonian male refugees were recruited into the Finnish army as volunteers; they started fighting on the Karelian front against the Soviet Union. The letters analysed in the article come from the years 1943–1944 and were sent by the men who remained in Finland to their friends who escaped to Sweden. The letters show that both civilians and soldiers faced problems caused by the political situation resulting from the Second World War and the complicated allied relations between Finland and Germany. The refugees did not have enough knowledge of life in wartime Finland and their language skills were also poor. In the course of escaping from Estonia to Finland, friends had lost sight of each other. After arriving in Finland, they started to restore their contacts in order to share experiences and find some support. The main aim of the article is to demonstrate the role of epistolary communication in finding solutions to the problems of Estonian refugees. The article gives an insight into the main topics of the letters, in which the authors of the letters tell stories about their escape from Estonia to Finland, share information about the destiny of their schoolmates and friends, but also discuss fine arts, and dream about life in peacetime. The letters show that they wish to get away from the war and continue their unfinished university studies in some war-neutral country. In their letters, they came to understanding that in order to implement their future plans, they had to get to Sweden and thus, already in the late autumn of 1943, the topic of fleeing from Finland to Sweden became dominant. At that time, the legal emigration of Estonians to another western country was limited by Finnish legislation, and, as field post letters were censored, writing about this topic was risky. The letters contain interesting examples of what verbal and visual means of expression were used to hide the true content of the messages from the censor. Compared to ordinary private letters, war letters also have another peculiarity: they contain some features of collective communication. For instance, an envelope addressed by one person to another may contain a letter consisting of messages written by several people and these messages can be intended to be distributed to several persons. Thus, wartime correspondence has similarities with the principles of information transmission in modern social media networks.

Study of the Telecommunication Networks Performance and Reliability Indicators

It is currently urgent to improve the technical characteristics and increase the efficiency of telecommunication networks because of the global problem of ensuring the reliable transmission, processing and protection of commercial information in telecommunication networks. The aim of this study is to assess the reliability indicators of telecommunication networks and analyse the level of their development. The aim was achieved through the methods that were used to assess the reliability of the entire network: the generalized method of analytical assessment of the telecommunication network reliability; connection-based metrics; scaling of telecommunication networks, and application of unified reliability indicators to routine control, operation and maintenance. As a result of the research, the indicators of telecommunication networks were studied with and without using connection-based metrics. As a result, the network metrics were also divided into distribution and generation/transmission reliability and telecommunication network metrics – into connection-, performance-, and condition-based metrics, which showed improvements in network performance and reliability. As a prospect for further research, studying and improving the telecommunication network reliability indicators is suggested.

Modeling public opinion dissemination in a multilayer network with SEIR model based on real social networks

Due to the complexity of social relationships, Internet users are active in multiple social networks and receive or release information in various ways and channels. Therefore, the spread of public opinion is not limited to a closed single network. Considering the structural characteristics of WeChat, Weibo and Tiktok, we built a multi-layer network based on the complex network theory. Based on the environmental and personal factors, the calculation methods of transmission rate and immunity rate is proposed. The trends of information transmission in the multi-layer network is simulated through an improved SEIR model. Through simulation, the differences of information transmission between multi-layer networks and single-layer networks are explored, and the impacts of network structure, coupling strength between layers and interlayer connection mode on information transmission are studied. More than 76,000 tweets from 7 events on Weibo are collected to verify the effectiveness of the model and explore the dissemination trends of actual public opinions. Through the research, it is found that (1) the public opinion transmission efficiency of multi-layer network is higher, the scale is larger, and the time is longer. (2) Compared with Weibo and Tiktok, the information transmission in WeChat is more efficient and lasts longer, and promotes the information transmission in the other two networks. (3) With the increase of coupling strength between layers, the efficiency of information transmission becomes higher and the scale becomes larger. This study provides new ideas for the research of public opinion dissemination, and helps relevant departments to correctly guide public opinion.

Cooperative jamming aided securing wireless communications without CSI of eavesdroppers

Physical layer security was designed as an effective solution to provide the security and confidentiality of information transmission in wireless networks, and secrecy transmission capacity (STC) played a key role in analyzing the impact of system parameters on physical layer security. Different from the previous works, which exploited cooperative jamming to improve the security with the assumption of perfect channel state information (CSI) of eavesdroppers (Eves), in this paper, without considering Eves’ CSI, we designed two secrecy improvement strategies aided by cooperative jamming with transmit power allocation scheme, i.e., connection guard zone (CGZ) and improved interferer protected zone (IIPZ). Specifically, we established an analytical framework of the STC by applying the tools of stochastic geometry and derived conditions that achieved a positive STC. In addition, we consider the impact of Random WayPoint (RWP) mobile receiver and active eavesdroppers on physical layer security. Simulations showed that IIPZ achieves the best reliability performance and CGZ makes the best secrecy performance than existing popular protections, and RWP mobile destination can achieve a higher level of reliability and STC than these achievable in static scenarios.

Readily prepared and processed multifunctional MXene nanocomposite hydrogels for smart electronics

AbstractBooming sophisticated robotics and prosthetics put forward high requirements on soft conductive materials that can bridge electronics and biology, those soft conductive materials should imitate the mechanical properties of biological tissues and build information transmission networks. Until now, it remains a great challenge to handle the trade‐off among ease of preparation, high conductivity, processability, mechanical adaptability, and external stimuli responsiveness. Herein, a kind of readily prepared and processed multifunctional MXene nanocomposite hydrogel is reported, which is prepared via the fast gelation of cationic monomer initiated by delaminated MXene sheets. The gelation time can be adjusted (several seconds to minutes) based on the MXene loadings. By adjusting the MXene ratio, the resulting nanocomposites are ultrastretchable (>5000%), three‐dimensional (3D) printable, and show outstanding mechanical and electrical self‐healing. As expected, the integration of multifunctional systems onto various substrates (e.g., gloves and masks) is further demonstrated via 3D printing and could achieve diverse sensory capabilities toward strain, pressure, and temperature, showing great prospects as smart flexible electronics.

LAP and IRS Enhanced Secure Transmissions for 6G-Oriented Vehicular IoT Services

In 6G-oriented vehicular Internet of things (IoT) services, the integration of a low altitude platform (LAP) and intelligent reflecting surfaces (IRS) provides a promising solution to achieve seamless coverage and massive connections at low cost. However, due to the open nature of wireless channels, how to protect the transmission of privacy information in LAP-based IRS symbiotic vehicular networks remains a challenge. Motivated by the above, this paper investigates the LAP and IRS enhanced secure transmission problem in the presence of an eavesdropper. Specifically, we first deploy a fixed LAP equipped with IRS to overcome the blockages and introduce artificial noise against the eavesdropper. Next, we formulate a total secure channel capacity maximization problem by optimizing the phase shift, power distribution coefficient, and channel allocation. To effectively solve the formulated problem, we design an iterative algorithm with polynomial complexity, where the optimization variables are solved in turn. In addition, the complexity and convergence of the proposed iterative algorithm are analyzed theoretically. Finally, numerical results show that our proposed secure transmission scheme outperforms the comparison schemes in terms of the total secure channel capacity.