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 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.

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.

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.

一种基于Event-B语言的时间触发系统建模方法

安全关键信息物理系统的时间属性建模和验证至关重要。Event-B模型验证避免了基于状态遍历模型检查方法的状态空间爆炸问题,验证时耗少,适用于高并发系统。然而,常规的Event-B方法缺乏时间语义表达结构,特别是缺乏对可提高系统可预测性的时间触发属性的支持。首先,介绍支持时间触发系统的抽象建模框架TTEB,从系统行为和实现2个抽象层次对时间属性进行建模和精化。然后,通过有序事件链组成的时间触发转移描述行为层时间触发属性;通过全局时钟到分布式本地时钟的精化和分解实现行为模型到实现模型的转化;运用时间触发转移建模分布式时钟周期同步。最后,基于从车跟车系统建模与验证说明方法的可用性和有效性。

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.

基于FAERS数据库的喹硫平不良事件信号挖掘与分析

目的基于美国食品药品监督管理局(FDA)不良事件报告系统(FAERS)数据库挖掘喹硫平的药物不良事件(ADE)信号,为该药的临床安全使用提供参考。方法检索FAERS数据库中2004年至2023年共79个季度关于喹硫平的不良反应报告,同时采用报告比值比法、比例报告比值法、贝叶斯置信区间神经网络传播法、多重伽马-泊松收缩估计法,按药物不良事件术语集的首选术语(PT)和系统器官分类(SOC)对纳入的ADE报告进行分类并计算风险信号。结果共收集主要怀疑药物为喹硫平的ADE报告261725份,涉及的患者有68012例,其中以女性(37495份,55.13%)及老年患者(>65岁)(35312份,占51.9%)居多,报告国家以美国为主,结局多为其他严重后果、住院、死亡和危及患者生命。共挖掘出喹硫平阳性风险信号PT 713个,涉及SOC 27个,所得信号基本与药品说明书一致,其中报告数最多的ADE为糖尿病,且信号强度较高。报告数超过500例的ADE中,共挖掘47个阳性风险信号PT,其中横纹肌溶解为说明书中未收载的ADE。喹硫平引起ADE发生的时间不一,常在用药后30 d内或用药一年以上发生。结论临床在使用喹硫平时除应在全程关注药品说明书收录的ADE外,还应警惕说明书未提及的ADE,并且根据性别、年龄等制订个体化的用药监护方案。

考虑时延的异质协作车队事件触发控制研究

针对目前研究较少考虑车辆混行造成的异质问题与时延问题,本文提出了一种具有时延的异质协作式自动驾驶车队事件触发控制方法 .首先,建立了考虑混行的异质车辆时延模型;其次,基于PID(proportional-integral-derivative)控制与模型预测控制(MPC),设计了不同模式下的事件触发控制器;然后,在城市和紧急情况下,对所提出的控制器进行了仿真分析;最后,基于Jetson Nano模型车进行了实车实验.仿真与实验结果表明,所提出的事件触发控制方法能够在不同情况下更好地权衡控制精度与计算速度间的矛盾.在带有通信时延的紧急情况下,仍能够保持较低的误差.