生存资料的二次研究系列之二:R软件重建time-to-event结局的单个患者数据

在原始研究中,对time-to-event结局的报道往往仅限于中位time to event和风险比。本文介绍一种使用R软件利用文献报道的Kaplan-Meier曲线、特定时间点无事件患者数(numbers at risk)和总事件数重建单个患者数据(IPD)的方法。

Intrusion Detection System for PS-Poll DoS Attack in 802.11 Networks Using Real Time Discrete Event System

Wi-Fi devices have limited battery life because of which conserving battery life is imperative. The 802.11 Wi-Fi standard provides power management feature that allows stations(STAs) to enter into sleep state to preserve energy without any frame losses. After the STA wakes up, it sends a null data or PS-Poll frame to retrieve frame(s) buffered by the access point(AP), if any during its sleep period. An attacker can launch a power save denial of service(PS-DoS) attack on the sleeping STA(s) by transmitting a spoofed null data or PS-Poll frame(s) to retrieve the buffered frame(s) of the sleeping STA(s) from the AP causing frame losses for the targeted STA(s). Current approaches to prevent or detect the PS-DoS attack require encryption,change in protocol or installation of proprietary hardware. These solutions suffer from expensive setup, maintenance, scalability and deployment issues. The PS-DoS attack does not differ in semantics or statistics under normal and attack circumstances.So signature and anomaly based intrusion detection system(IDS) are unfit to detect the PS-DoS attack. In this paper we propose a timed IDS based on real time discrete event system(RTDES) for detecting PS-DoS attack. The proposed DES based IDS overcomes the drawbacks of existing systems and detects the PS-DoS attack with high accuracy and detection rate. The correctness of the RTDES based IDS is proved by experimenting all possible attack scenarios.

Stratigraphical Time——Correlation and Mass Extinction Event Near Permian——Triassic Boundary in South China

Shaw's method used to correlate 40 sections across the Permo-Triassic boundary in South China is applied in the paper. Two steps are adopted to get an Integral Composite Section (ICS) by synthesizing these data : First , South China is divided into five areas and composite section developed for each area . Then the second step . the Changxing composite section is regarded as a composite standard (CSRS) while the ICS is produced by matching the CSRS with composite sections of the other areas. Three biozones in the Changxingian and two biozones in the Griesbachian can be discerned on the basis of computing Z values in the ICS. These biozones are marked by the Z values which quantitatively represent their time ranges ; therefore , they may increase accuracy of stratigraphic time correlation . The mass extinction at the end of the Permian is an abrupt event that is supported by the relative rate of extinction near the P/T boundary . About 90% of invertebrate species died out by the end of the Permian . The duration of the mass extinction is rather short ,approximately 0.018Ma .

RFID Complex Event Processing: Applications in Real-Time Locating System

Complex event processing (CEP) can extract meaningful events for real-time locating system (RTLS) applications. To identify complex event accurately in RTLS, we propose a new RFID complex event processing method GEEP, which is based on the timed automata (TA) theory. By devising RFID locating application into complex events, we model the timing diagram of RFID data streams based on the TA. We optimize the constraint of the event streams and propose a novel method to derive the constraint between objects, as well as the constraint between object and location. Experiments prove the proposed method reduces the cost of RFID complex event processing, and improves the efficiency of the RTLS.

Cyclic Reconfigurable Flow Shop under Different Configurations Modeling and Optimization Based on Timed Event Graph

Based on the idea that modules are independent of machines, different combinations of modules and machines result in different configurations and the system performances differ under different configurations, a kind of cyclic reconfigurable flow shops are proposed for the new manufacturing paradigm-reconfigurable manufacturing system. The cyclic reconfigurable flow shop is modeled as a timed event graph. The optimal configuration is defined as the one under which the cyclic reconfigurable flow shop functions with the minimum cycle time and the minimum number of pallets. The optimal configuration, the minimum cycle time and the minimum number of pallets can be obtained in two steps.

Adaptive Conditional Hazard Regression Modeling of Multiple Event Times

Recurrent event time data and more general multiple event time data are commonly analyzed using extensions of Cox regression, or proportional hazards regression, as used with single event time data. These methods treat covariates, either time-invariant or time-varying, as having multiplicative effects while general dependence on time is left un-estimated. An adaptive approach is formulated for analyzing multiple event time data. Conditional hazard rates are modeled in terms of dependence on both time and covariates using fractional polynomials restricted so that the conditional hazard rates are positive-valued and so that excess time probability functions (generalizing survival functions for single event times) are decreasing. Maximum likelihood is used to estimate parameters adjusting for right censored event times. Likelihood cross-validation (LCV) scores are used to compare models. Adaptive searches through alternate conditional hazard rate models are controlled by LCV scores combined with tolerance parameters. These searches identify effective models for the underlying multiple event time data. Conditional hazard regression is demonstrated using data on times between tumor recurrence for bladder cancer patients. Analyses of theory-based models for these data using extensions of Cox regression provide conflicting results on effects to treatment group and the initial number of tumors. On the other hand, fractional polynomial analyses of these theory-based models provide consistent results identifying significant effects to treatment group and initial number of tumors using both model-based and robust empirical tests. Adaptive analyses further identify distinct moderation by group of the effect of tumor order and an additive effect to group after controlling for nonlinear effects to initial number of tumors and tumor order. Results of example analyses indicate that adaptive conditional hazard rate modeling can generate useful insights into multiple event time data.

Adaptive Conditional Hazard Regression Modeling of Multiple Event Times

Recurrent event time data and more general multiple event time data are commonly analyzed using extensions of Cox regression, or proportional hazards regression, as used with single event time data. These methods treat covariates, either time-invariant or time-varying, as having multiplicative effects while general dependence on time is left un-estimated. An adaptive approach is formulated for analyzing multiple event time data. Conditional hazard rates are modeled in terms of dependence on both time and covariates using fractional polynomials restricted so that the conditional hazard rates are positive-valued and so that excess time probability functions (generalizing survival functions for single event times) are decreasing. Maximum likelihood is used to estimate parameters adjusting for right censored event times. Likelihood cross-validation (LCV) scores are used to compare models. Adaptive searches through alternate conditional hazard rate models are controlled by LCV scores combined with tolerance parameters. These searches identify effective models for the underlying multiple event time data. Conditional hazard regression is demonstrated using data on times between tumor recurrence for bladder cancer patients. Analyses of theory-based models for these data using extensions of Cox regression provide conflicting results on effects to treatment group and the initial number of tumors. On the other hand, fractional polynomial analyses of these theory-based models provide consistent results identifying significant effects to treatment group and initial number of tumors using both model-based and robust empirical tests. Adaptive analyses further identify distinct moderation by group of the effect of tumor order and an additive effect to group after controlling for nonlinear effects to initial number of tumors and tumor order. Results of example analyses indicate that adaptive conditional hazard rate modeling can generate useful insights into multiple event time data.

Event-Triggered Finite-Time <i>H</i>_∞Control for Switched Stochastic Systems

This paper investigates the problem of event-triggered finite-time H∞ control for a class of switched stochastic systems. The main objective of this study is to design an event-triggered state feedback H∞ controller such that the resulting closed-loop system is finite-time bounded and satisfies a prescribed H∞ level in some given finite-time interval. Based on stochastic differential equations theory and average dwell time approach, sufficient conditions are derived to ensure the finite-time stochastic stability with the prescribed H∞ performance for the relevant closed-loop system by employing the linear matrix inequality technique. Finally, the desired state feedback H∞ controller gain matrices can be expressed in an explicit form.

Key Dolerite Dyke Swarms of Amazonia:U-Pb Constraints on Supercontinent Cycles and Geodynamic Connections with Global LIP Events Through Time

High-resolution U–Pb(ID-TIMS,baddeleyite)ages are presented for mafic dykes from selected swarms in two important Amazonian regions:the Carajás Province in the east,and the Rio Apa block in the southwest–areas

A Study of Visual Event-Related Potential and Reaction Time in Elderly People: Comparative Analysis of the Scores of Intelligence Test in 30 Subjects

The results of visual event-related potential(ERP)examinations and reactiontime(RT)tests were reported in 30 elders and compared with their performanceintellegence quotient(PIQ)scores.The subjects consisted of 18 males and 12 femalesaged 50-71(mean 61.4)years old.No history of central nervous system disease wasfound.The visual stimuli were randomly presented to the subject,including three sym-bols:E as target stimulus with 0.15 probability,and H and E as nontarget stimuliwith 0.15 and 0.70 probability respectively.The recording electrodes were placed on Fzand Pz.The duration from the subject seeing the target to touching a button immediatelywas considered as reaction time(RT).It was shown that the P3 latency at Pz was longer than that at Fz and the P3amplitude at Pz was larger than that at Fz,and that the RT was longer than P3 latencywith obvious effect of distribution(P【0.05 at Fz and P】0.05 at Pz)as well .The higherthe PIQ scores,the longer the RT and the P3 latency.It is suggested that the ERPmight reflect the differences of PIQ scores,and the P3 is an objective index.We considerthat the research of ERP is of great interest in the neuropsychological and neurological sci-ences.

Modified <i>f(R)</i>Gravity and Thermodynamics of Time-Dependent Wormholes at Event Horizon

In the context of modified gravity theory, we study time-dependent wormhole spacetimes in the radiation background. In this framework, we attempt to generalize the thermodynamic properties of time-dependent wormholes in gravity. Finally, at event horizon, the rate of change of total entropy has been discussed.

Time-varying formation for general linear multi-agent systems via distributed event-triggered control under switching topologies

This paper investigates the time-varying formation problem for general linear multi-agent systems using distributed event-triggered control strategy.Different from the previous works,to achieve the desired time-varying formation,a distributed control scheme is designed in an event-triggered way,in which for each agent the controller is triggered only at its own event times.The interaction topology among agents is assumed to be switching.The common Lyapunov function as well as Riccati inequality is applied to solve the time-varying formation problem.Moreover,the Zeno behavior of triggering time sequences can be excluded for each agent.Finally,a simulation example is presented to illustrate the effectiveness of the theoretical results.

The Relation between the Stabilization Problem for Discrete Event Systems Modeled with Timed Petri Nets via Lyapunov Methods and Max-Plus Algebra

A discrete event system is a dynamical system whose state evolves in time by the occurrence of events at possibly irregular time intervals. Timed Petri nets are a graphical and mathematical modeling tool applicable to discrete event systems in order to represent its states evolution where the timing at which the state changes is taken into consideration. One of the most important performance issues to be considered in a discrete event system is its stability. Lyapunov theory provides the required tools needed to aboard the stability and stabilization problems for discrete event systems modeled with timed Petri nets whose mathematical model is given in terms of difference equations. By proving stability one guarantees a bound on the discrete event systems state dynamics. When the system is unstable, a sufficient condition to stabilize the system is given. It is shown that it is possible to restrict the discrete event systems state space in such a way that boundedness is achieved. However, the restriction is not numerically precisely known. This inconvenience is overcome by considering a specific recurrence equation, in the max-plus algebra, which is assigned to the timed Petri net graphical model.

A discrete-event model to simulate the effect of truck bunching due to payload variance on cycle time, hauled mine materials and fuel consumption

Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.

Event-Triggered Zero-Gradient-Sum Distributed Algorithm for Convex Optimization with Time-Varying Communication Delays and Switching Directed Topologies

Nowadays, distributed optimization algorithms are widely used in various complex networks. In order to expand the theory of distributed optimization algorithms in the direction of directed graph, the distributed convex optimization problem with time-varying delays and switching topologies in the case of directed graph topology is studied. The event-triggered communication mechanism is adopted, that is, the communication between agents is determined by the trigger conditions, and the information exchange is carried out only when the conditions are met. Compared with continuous communication, this greatly saves network resources and reduces communication cost. Using Lyapunov-Krasovskii function method and inequality analysis, a new sufficient condition is proposed to ensure that the agent state finally reaches the optimal state. The upper bound of the maximum allowable delay is given. In addition, Zeno behavior will be proved not to exist during the operation of the algorithm. Finally, a simulation example is given to illustrate the correctness of the results in this paper.

Event-Triggered Finite-Time H∞ Filtering for Discrete-Time Nonlinear Stochastic Systems

This paper addresses the problem of event-triggered finite-time H∞ filter design for a class of discrete-time nonlinear stochastic systems with exogenous disturbances. The stochastic Lyapunov-Krasoviskii functional method is adopted to design a filter such that the filtering error system is stochastic finite-time stable (SFTS) and preserves a prescribed performance level according to the pre-defined event-triggered criteria. Based on stochastic differential equations theory, some sufficient conditions for the existence of H∞ filter are obtained for the suggested system by employing linear matrix inequality technique. Finally, the desired H∞ filter gain matrices can be expressed in an explicit form.

离散时间多智能体系统间歇事件触发输出一致性

对离散时间多智能体系统间歇事件触发输出一致性进行了研究。首先,结合间歇控制和事件触发机制,针对离散多智能体系统提出一个输出一致性控制协议。然后,构造误差系统,基于Lyapunov稳定性理论得到了依赖于网络的Laplacian矩阵和系统增益的输出一致性条件,实现离散时间多智能体系统间歇事件触发输出一致性。最后,利用具体的仿真例子对结果的有效性进行分析验证。

Timer控件在地质滑坡监测软件中的精确定时

Visual Basic 6.0自带的Timer(定时器)控件的Interval(时间间隔)属性,可用来设置两次触发Timer事件的时间间隔,实现定时功能。由于系统硬件和该属性固有的限制,定时程序在运行过程中会出现定时误差大和时间间隔有限等不足,其定时误差约为5%。针对这两个问题,介绍了如何利用主动查询对比系统时间的算法,不断修正Timer控件的定时误差,防止误差的累积,从而实现高精度定时和任意整数秒时间间隔定时。经过实验测试,该算法可消除定时器的固有误差,达到无误差定时。

基于PDES系统的Time Warp性能研究

随着分布式仿真规模的日益扩大,高性能并行计算技术的不断发展,并行与分布式仿真正逐渐成为新的研究热点。时间管理技术是决定并行与分布式仿真正确性和可重复性的关键技术,直接影响着仿真系统的整体性能。而TW乐观时间管理机制的许多思想和概念一直为现在各种算法所借鉴和沿用。文章建立了一个TW的性能分析模型,利用该模型对事件数量、平均回退长度、回退概率及其上限等进行了分析,分析结果对并行离散事件仿真系统的研发与改进具有一定的指导意义和参考价值。