基于新曝光冲突性消息的网络舆论逆转研究

对网络舆论逆转过程进行研究具有十分重要的意义,它有助于管理者有效引导舆论朝良性方向发展.目前,网络舆论逆转研究主要集中于动力学模型构建与仿真实验分析,其研究结果具有一定的理论价值.然而,这是否适用于真实社交网络环境,还尚未经过测试.为了对舆论逆转过程进行研究,构建了符合实际的模型,并对网络舆论逆转典型事例进行了深入分析.通过观察统计,发现网络舆论逆转具有自身的规律:新曝光冲突性消息是导致舆论发生逆转的根本原因;消息的传播影响着群体的发声与沉默;消息的属性包括传播率、可信度、观点倾向、起始传播时间和消息源中心度决定着舆论逆转的幅度.依据这一规律,设置了消息属性参数,并将消息传播与观点演化过程相结合,构建了网络舆论逆转模型.模型的仿真实验结果表明,新冲突性消息的传播率、可信度和消息源中心度正向影响着舆论逆转幅度,其中可信度较传播率影响更大.新的冲突性消息曝光的时间越早,舆论逆转的速率越快,幅度越大.该模型与实际相符,可为理解和解释网络舆论逆转过程、引导网络舆论提供理论依据.     

Bifurcations in globally coupled map lattices

The dynamics of globally coupled map lattices can be described in terms of a nonlinear Frobenius-Perron equation in the limit of large system size. This approach allows for an analytical computation of stationary states and their stability. The bifurcation behavior of coupled tent maps near the chaotic band merging point is presented. Furthermore, the time-independent states of coupled logistic equations are analyzed. The bifurcation diagram of the uncoupled map carries over to the map lattice. The analytical results are supplemented with numerical simulations     

Dynamics in two-elevator traffic system with real-time information

We study the dynamics of traffic system with two elevators using a elevator choice scenario. The two-elevator traffic system with real-time information is similar to the two-route vehicular traffic system. The dynamics of two-elevator traffic system is described by the two-dimensional nonlinear map. An elevator runs a neck-and-neck race with another elevator. The motion of two elevators displays such a complex behavior as quasi-periodic one. The return map of two-dimensional map shows a piecewise map.     

Fairness in opinion dynamics

The opinion dynamics studies how a final consensus emerges from a diversified initial configuration. The final result can be an artifact arising in the voting processes and overlook the features of the initial configuration, which leads to the unfair result. We explore the concept of fairness in opinion dynamics and propose a quantitative measurement in a model system, which allows us to reach a final consensus reflecting impartially the major opinion. For a two-choice system, the unfairness alternates with the increase of meeting agents M. With an odd M, the fair results can be expected; with an even M, the unfairness decays monotonically with an increasing M. When the number of choices is larger than two, such an alternating is smeared out. The fairness at an odd M can no longer be reached. The unfairness increases a bit with the increasing number of choices. Similar M-dependence can be observed for different number of choices. We conclude that the number of choices plays a minor role in reaching a fair final consensus. The fairness is mainly controlled by the meeting size.     

Towards understanding the behavior of physical systems using information theory

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.     

Studies of phase return map and symbolic dynamics in a periodically driven Hodgkin–Huxley neuron

How neuronal spike trains encode external information is a hot topic in neurodynamics studies.In this paper,we investigate the dynamical states of the Hodgkin–Huxley neuron under periodic forcing.Depending on the parameters of the stimulus,the neuron exhibits periodic,quasiperiodic and chaotic spike trains.In order to analyze these spike trains quantitatively,we use the phase return map to describe the dynamical behavior on a one-dimensional(1D)map.According to the monotonicity or discontinuous point of the 1D map,the spike trains are transformed into symbolic sequences by implementing a coarse-grained algorithm—symbolic dynamics.Based on the ordering rules of symbolic dynamics,the parameters of the external stimulus can be measured in high resolution with finite length symbolic sequences.A reasonable explanation for why the nervous system can discriminate or cognize the small change of the external signals in a short time is also presented.     

Bifurcation analysis of the logistic map via two periodic impulsive forces

The complex dynamics of the logistic map via two periodic impulsive forces is investigated in this paper. The influences of the system parameter and the impulsive forces on the dynamics of the system are studied respectively. With the parameter varying, the system produces the phenomenon such as periodic solutions, chaotic solutions, and chaotic crisis. Furthermore, the system can evolve to chaos by a cascading of period-doubling bifurcations. The Poincare′ map of the logistic map via two periodic impulsive forces is constructed and its bifurcation is analyzed. Finally, the Floquet theory is extended to explore the bifurcation mechanism for the periodic solutions of this non-smooth map.     

Bifurcations in a System of Interacting Fronts

We show that the bifurcation scenario in a high-dimensional system with interacting moving fronts can be related to the universal U-sequence which is known from the symbolic analysis of iterated one-dimensional maps. This connection is corroborated for a model of a semiconductor superlattice, which describes the complex dynamics of electron accumulation and depletion fronts. By a suitable Poincaré section we reduce the dynamics to a low-dimensional iterated map, for which in the most elementary case the bifurcation points can be determined analytically.     

Numerical investigation of cavitation generated by an ultrasonic dental scaler tip vibrating in a compressible liquid

Bacterial biofilm accumulation around dental implants is a significant problem leading to peri-implant diseases and implant failure. Cavitation occurring in the cooling water around ultrasonic scaler tips can be used as a novel solution to remove debris without any surface damage. However, current clinically available instruments provide insufficient cavitation around the activated tip surface. To solve this problem a critical understanding of the vibro-acoustic behaviour of the scaler tip and the associated cavitation dynamics is necessary. In this research, we carried out a numerical study for an ultrasound dental scaler with a curved shape tip vibrating in water, using ABAQUS based on the finite element method. We simulated the three-dimensional, nonlinear and transient interaction between the vibration and deformation of the scaler tip, the water flow around the scaler and the cavitation formation and dynamics. The numerical model was well validated with the experiments and there was excellent agreement for displacement at the free end of the scaler. A systematic parametric study has been carried out for the cavitation volume around the scaler tip in terms of the frequency, amplitude and power of the tip vibration. The numerical results indicate that the amount of cavitation around the scaler tip increases with the frequency and amplitude of the vibration. However, if the frequency is far from the natural frequency, the cavitation volume around the free end decreases due to reduced free end vibration amplitude.     

基于视觉SLAM和目标检测的语义地图构建

语义信息对于移动机器人理解环境内容、执行复杂任务至关重要,针对ORB-SLAM2构建的点云过于稀疏、缺乏语义信息、点云所占存储空间大等问题,提出将目标检测算法与视觉SLAM(同时定位与地图构建)技术紧密结合,构建环境的稠密点云语义地图.首先,通过目标检测网络YOLO v3及对象正则化准确获取物体的2D标签,并经过ORB...     

Adaptive control of chaotic systems based on a single layer neural network

This Letter presents an adaptive neural network control method for the chaos control problem. Based on a single layer neural network, the dynamic about the unstable fixed period point of the chaotic system can be adaptively identified without detailed information about the chaotic system. And the controlled chaotic system can be stabilized on the unstable fixed period orbit. Simulation results of Henon map and Lorenz system verify the effectiveness of the proposed control method.     

Symbolic local information transfer

Recently, the permutation-information theoretic approach has been used in a broad range of research fields. In particular, in the study of high-dimensional dynamical systems, it has been shown that this approach can be effective in characterizing global properties, including the complexity of their spatiotemporal dynamics. Here, we show that this approach can also be applied to reveal local spatiotemporal profiles of distributed computations existing at each spatiotemporal point in the system. J. T. Lizier et al. have recently introduced the concept of local information dynamics, which consists of information storage, transfer, and modification. This concept has been intensively studied with regard to cellular automata, and has provided quantitative evidence of several characteristic behaviors observed in the system. In this paper, by focusing on the local information transfer, we demonstrate that the application of the permutation-information theoretic approach, which introduces natural symbolization methods, makes the concept easily extendible to systems that have continuous states. We propose measures called symbolic local transfer entropies, and apply these measures to two test models, the coupled map lattice (CML) system and the Bak-Sneppen model (BS-model), to show their relevance to spatiotemporal systems that have continuous states. In the CML, we demonstrate that it can be successfully used as a spatiotemporal filter to stress a coherent structure buried in the system. In particular, we show that the approach can clearly stress out defect turbulences or Brownian motion of defects from the background, which gives quantitative evidence suggesting that these moving patterns are the information transfer substrate in the spatiotemporal system. We then show that these measures reveal qualitatively different properties from the conventional approach using the sliding window method, and are also robust against external noise. In the BS-model, we demonstrate that these measures can provide novel insight to the model, featuring how symbolic local information transfer is related to the dynamical properties of the elements involved in a spatiotemporal dynamics.     

Decision Accuracy and the Role of Spatial Interaction in Opinion Dynamics

The opinions and actions of individuals within interacting groups are frequently determined by both social and personal information. When sociality (or the pressure to conform) is strong and individual preferences are weak, groups will remain cohesive until a consensus decision is reached. When group decisions are subject to a bias, representing for example private information known by some members of the population or imperfect information known by all, then the accuracy achieved for a fixed level of bias will increase with population size. In this work we determine how the scaling between accuracy and group size can be related to the microscopic properties of the decision-making process. By simulating a spatial model of opinion dynamics we show that the relationship between the instantaneous fraction of leaders in the population (L), system size (N), and accuracy depends on the frequency of individual opinion switches and the level of population viscosity. When social mixing is slow, and individual opinion changes are frequent, accuracy is determined by the absolute number of informed individuals. As mixing rates increase, or the rate of opinion updates decrease, a transition occurs to a regime where accuracy is determined by the value of $L\sqrt{ N}$ . We investigate the transition between different scaling regimes analytically by examining a well-mixed limit.     

Coupled map lattices as cellular automata

We approach the problem of the complex dynamics of coupled map lattices (CML) by proposing a reduction to deterministic cellular automata (CA) with more than two states per site. The reduction scheme replaces the local map by an approximation in terms of a step function based on a straightforward analysis of the local dynamics. The variation of the spatial coupling in the CML then translates itself as a path in the spaces of rules for the equivalent deterministic CA. The transition to turbulence via spatiotemporal intermittency in the CML is then interpreted as a transition in the space of rules. The observed nonuniversality of this transition can be traced back to the nature of the rules involved on both sides of the transition region and to the character of the escape process from the turbulent state, either strongly deterministic or quasiprobabilistic. The relation between CML, deterministic, and probabilistic CA and the possibility of a mean-field treatment of the dynamics of CML are discussed at a more formal level.     

Complex motion of elevators in piecewise map model combined with circle map

We study the dynamic behavior in the elevator traffic controlled by capacity when the inflow rate of passengers into elevators varies periodically with time. The dynamics of elevators is described by the piecewise map model combined with the circle map. The motion of the elevators depends on the inflow rate, its period, and the number of elevators. The motion in the piecewise map model combined with the circle map shows a complex behavior different from the motion in the piecewise map model.     

Bifurcation analysis on a hybrid systems model of intermittent hormonal therapy for prostate cancer

Hybrid systems are widely used to model dynamical phenomena that are characterized by interplay between continuous dynamics and discrete events. An example of biomedical application is modeling of disease progression of prostate cancer under intermittent hormonal therapy, where continuous tumor dynamics is switched by interruption and reinstitution of medication. In the present paper, we study a hybrid systems model representing intermittent androgen suppression (IAS) therapy for advanced prostate cancer. Intermittent medication with switching between on-treatment and off-treatment periods is intended to possibly prevent a prostatic tumor from developing into a hormone-refractory state and is anticipated as a possible strategy for delaying or hopefully averting a cancer relapse which most patients undergo as a result of long-term hormonal suppression. Clinical efficacy of IAS therapy for prostate cancer is still under investigation but at least worth considering in terms of reduction of side effects and economic costs during off-treatment periods. In the model of IAS therapy, it depends on some clinically controllable parameters whether a relapse of prostate cancer occurs or not. Therefore, we examine nonlinear dynamics and bifurcation structure of the model by exploiting a numerical method to clarify bifurcation sets in the hybrid system. Our results suggest that adjustment of the normal androgen level in combination with appropriate medication scheduling could enhance the possibility of relapse prevention. Moreover, a two-dimensional piecewise-linear system reduced from the original model highlights the origin of nonlinear phenomena specific to the hybrid system.     

管道清管器实时远程跟踪定位系统的设计与实现

清管器在油气管道的清理过程中具有重要的作用,但若管道内杂质堆积物过多会将清管器卡堵在管道中而影响清管作业的顺利完成。为了保证油气管道的正常运营,需要对工作中的清管器进行实时远程跟踪定位。本文开发了一套管道清管器实时远程跟踪定位系统。在清管器接收机中内置GPS模块,接收机检测到清管器发射的低频信号时向GPS模块发送指令进行导航定位,并将得到的定位信息通过访问网址的方式发送给指定的服务器,由服务器调用Google地图显示清管器所在位置以及运动轨迹,从而实现清管器实时远程追踪和定位。     

Quantum Speed Limit and Divisibility of the Dynamical Map

The quantum speed limit (QSL) is the theoretical lower limit of the time for a quantum system to evolve from a given state to another one. Interestingly, it has been shown that non-Markovianity can be used to speed-up the dynamics and to lower the QSL time, although this behaviour is not universal. In this paper, we further carry on the investigation on the connection between QSL and non-Markovianity by looking at the effects of P- and CP-divisibility of the dynamical map to the quantum speed limit. We show that the speed-up can also be observed under P- and CP-divisible dynamics, and that the speed-up is not necessarily tied to the transition from P-divisible to non-P-divisible dynamics.     

耦合双稳映象格子模型的时空混沌控制

变量反馈技术实现了耦合双稳映象格子模型的时空混沌控制.数值实验结果表明,利用不同的反馈技术和不同的反馈强度,可以将双稳映象系统的混沌及耦合双稳映象格子模型的时空混沌控制到不动点或周期轨道.变量反馈控制法除了局域双稳映象系统的定态点外,不需要先获取耦合双稳映象格子时空系统的动力学信息,它对抑制耦合双稳映象系统中的湍流具有一定的指导作用.