The Additive-multiplicative Hazards Model for Multiple Type of Recurrent Gap Times

Recurrent event gap times data frequently arise in biomedical studies and often more than one type of event is of interest. To evaluate the effects of covariates on the marginal recurrent event hazards functions, there exist two types of hazards models： the multiplicative hazards model and the additive hazards model. In the paper, we propose a more flexible additive-multiplicative hazards model for multiple type of recurrent gap times data, wherein some covariates are assumed to be additive while others are multiplicative. An estimating equation approach is presented to estimate the regression parameters. We establish asymptotic properties of the proposed estimators.

The Proportional Hazards Model for Multiple Type Recurrent Gap Times

Recurrent events data and gap times between recurrent events are frequently encountered in many clinical and observational studies,and often more than one type of recurrent events is of interest.In this paper,we consider a proportional hazards model for multiple type recurrent gap times data to assess the effect of covaxiates on the censored event processes of interest.An estimating equation approach is used to obtain the estimators of regression coefficients and baseline cumulative hazard functions.We examine asymptotic properties of the proposed estimators.Finite sample properties of these estimators are demonstrated by simulations.

An Additive Hazards Model for Clustered Recurrent Gap Times

In this article, clustered recurrent gap time is investigated. A marginal additive haz- ards model is proposed without specifying the association of the individuals within the same cluster. The relationship among the gap times for the same individual is also left unspecified. An estimating equation-based inference procedure is developed for the model parameters, and the asymptotic proper- ties of the resulting estimators are established. In addition, a lack-of-fit test is presented to assess the adequacy of the model. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease （CGD） is illustrated.

Research on Multiple Access Algorithms for Wireless Network

Nodes in the communication network mainly depend on the Media Access Control(MAC)layer protocol design.To ensure the MAC protocol achieves high throughput,low latency,and high service quality,this paper designed a“centralized-distribution”system MAC protocol combined with a slot allocation algorithm.This allows it to quickly adapt to the topology changes in the network and the overall network frame structure.For the centralized time slot allocation,since the system’s frame structure changes across the entire network,the root node must gather information from other nodes.This ensures that the root node can collect the latest topology information when the network topology changes and subsequently adjust the frame structure of the whole network for the distributed time slot allocation.The simulation results show that the adaptive time-division multiple access mechanism can quickly adapt to changes in topology and the network’s frame structure.It enables adaptive changes in node transmission times,ensures the rapid transmission and circulation of large-capacity data between nodes,and improves transmission efficiency.

Examining the characteristics between time and distance gaps of secondary crashes

Understanding the characteristics of time and distance gaps between the primary(PC)and secondary crashes(SC)is crucial for preventing SC ccurrences and improving road safety.Although previous studies have tried to analyse the variation of gaps,there is limited evidence in quantifying the relationships between different gaps and various influential factors.This study proposed a two-layer stacking framework to discuss the time and distance gaps.Specifically,the framework took random forests(RF),gradient boosting decision tree(GBDT)and eXtreme gradient boosting as the base classifiers in the first layer and applied logistic regression(LR)as a combiner in the second layer.On this basis,the local interpretable model-agnostic explanations(LIME)technology was used to interpret the output of the stacking model from both local and global perspectives.Through SC dentification and feature selection,346 SCs and 22 crash-related factors were collected from California interstate freeways.The results showed that the stacking model outperformed base models evaluated by accuracy,precision,and recall indicators.The explanations based on LIME suggest that collision type,distance,speed and volume are the critical features that affect the time and distance gaps.Higher volume can prolong queue length and increase the distance gap from the SCs to PCs.And collision types,peak periods,workday,truck involved and tow away likely induce a long-distance gap.Conversely,there is a shorter distance gap when secondary roads run in the same direction and are close to the primary roads.Lower speed is a significant factor resulting in a long-time gap,while the higher speed is correlated with a short-time gap.These results are expected to provide insights into how contributory features affect the time and distance gaps and help decision-makers develop accurate decisions to prevent SCs.

Birefringence via Doppler broadening and prevention of information hacking

We propose a new scheme for the coherent control of birefringent light pulses propagation in a four-level atomic medium. We modify the splitting of a light pulse by controlling the electric and magnetic responses. The Doppler broad- ening effect is also noted on the propagation of the birefringent pulses. The dispersions of the birefringence beams are oppositely manipulated for delay and advancement of time at a Doppler width of 10Y. A time gap is created between the birefringence beams, which protects from hacking of information. The time gap is then closed to restore the pulse into the original form by a reverse manipulation of the dispersion of the birefringence beams, i.e., introducing another medium whose transfer function is the complex conjugate of that of the original medium. The results are useful for secure communication technology.