The localization accuracy of a track-before-detect search for a target moving across a distributed sensor field is examined in this paper. The localization accuracy of the search is defined in terms of the area of intersection of the spatial-temporal sensor coverage regions, as seen from the perspective of the target. The expected value and variance of this area are derived for sensors distribu...

Temporal uncertainty in raw data can impede the inference of temporal and causal relationships between events and compromise the output of data-to-text NLG systems. In this paper, we introduce a framework to reason with and represent temporal uncertainty from the raw data to the generated text, in order to provide a faithful picture to the user of a particular situation. The model is grounded i...

In a distributed system, it is often important to detect the causal relationships between events, where event e 1 is causally before event e 2 if e 1 happened before e 2 and could possibly have aaected the occurrence of e 2. In this paper we argue that detecting causal relationships among events can be important for security, in the sense that it may be essential to the correct implementation o...

It is easy to live for the day. All lazybones do that and legitimately those who have finally taken a rest and enjoy in a relaxed way what is offered to them. The more eventful the better since then it is easy to forget what happened before and since unconnected impressions can be grasped in a particularly fresh way, in a virtually raw way. And in the same way as one might live for the moment, ...

As the name indicates, a renewal process is one that “renews” itself regularly. That is, there is a sequence of times {Tn, n ∈ Z} such that the process after time Tn is independent of what happened before that time and has a distribution that does not depend on n. We have seen examples of such processes before. As a simple example, one could consider a Poisson process with jump times Tn. As ano...

I propose a new measure of common, time-varying tail risk for large cross sections of stock returns. Stock return tails are described by a power law in which the power law exponent is allowed to transition smoothly through time as a function of recent data. It is motivated by asset pricing theory and is estimable via quasi-maximum likelihood. Estimates indicate substantial time variation in sto...

In a distributed system, it is often important to detect the causal relationships between events, where event e1 is causally before event e2 if e1 happened before e2 and could possibly have aaected the occurrence of e2. In this paper we argue that it can be essential to security that a process determine, in the face of malicious attack, how two events are causally related. We formulate attacks ...

In this article, we present a particle filter (PF)-based track-before-detect (PF TBD) procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/ absence, trajectory and shape parameters under unknown nuis...