Discrete time series generated by mixtures I: Correlational and runs properties

A broad but parametrically simple model for a stationary sequence of dependent discrete random variables is given and several submodels are discussed. The structure of the model is specified by the marginal distribution of the random variables and several other parameters. The sequence of random variables is formed by a probabilistic linear combination of independent, identically distributed discrete random variables and is in general not Markovian. Second-order joint moments and spectra are obtained for the model, as well as some properties for the lengths of runs. The special case of process in which the variables take on only two values is useful as a model for the counting process in a discrete-time point process. An application to the modelling of erros in the transmission of binary data is briefly discussed. (Author)supported by funds provided directly from the Chief of Naval Research under Grant NR-42-284, and the National Science Foundation under Grant NSF-75-02026http://archive.org/details/discretetimeseri00lewiN

Higher order residual analysis for nonlinear time series with autoregressive correlation structures

The paper considers nonlinear time series whose second order autocorrelations satisfy autoregressive Yule-Walker equations. The usual linear residuals are then uncorrelated, but not independent, as would be the case for linear autoregressive processes. Two such types of nonlinear model are treated in some detail; random coefficient autoregression and multiplicative autoregression. The proposed analysis involves crosscorrelation of the usual linear residuals and their squares. This function is obtained for the two types of model considered, and allows differentiation between models with the same autocorrelation structure in the same class. For the random coefficient models it is shown that one side of the crosscorrelation function is zero, giving a useful signature of these processes. The non-zero features of the crosscorrelations are informative of the higher order dependency structure. In applications this residual analysis requires only standard statistical calculations, and extends rather than replaces the usual second order analysisPrepared for: Chief of Naval Research Arlington, VAhttp://archive.org/details/higherorderresid00lewiN00014R4WR 24004NAApproved for public release; distribution is unlimited

A moving average exponential point process (EMA1)

A construction is given for a stationary sequence of random variables the set (X sub i) which have exponential marginal distributions and are random linear combinations of order one of an i.i.d. exponential sequence the set (epsilon sub i). The joint and trivariate exponential distributions of (X sub (i-1), (X sub i) and (X sub (i + 1)) are studied, as well as the intensity function, point spectrum and variance time curve for the point process which has the set (X sub i) sequence for successive times between events. Initial conditions to make the point process count stationary are given, and extensions to higher order moving averages and Gamma point processes are discussedsupported in part by the Office of Naval Research, the National Science Foundation and the United Kingdom Science Research Councilhttp://archive.org/details/movingaverageexp00lawrN

Telerobotic Surgery: An Intelligent Systems Approach to Mitigate the Adverse Effects of Communication Delay

An extremely innovative approach has been presented, which is to have the surgeon operate through a simulator running in real-time enhanced with an intelligent controller component to enhance the safety and efficiency of a remotely conducted operation. The use of a simulator enables the surgeon to operate in a virtual environment free from the impediments of telecommunication delay. The simulator functions as a predictor and periodically the simulator state is corrected with truth data. Three major research areas must be explored in order to ensure achieving the objectives. They are: simulator as predictor, image processing, and intelligent control. Each is equally necessary for success of the project and each of these involves a significant intelligent component in it. These are diverse, interdisciplinary areas of investigation, thereby requiring a highly coordinated effort by all the members of our team, to ensure an integrated system. The following is a brief discussion of those areas. Simulator as a predictor: The delays encountered in remote robotic surgery will be greater than any encountered in human-machine systems analysis, with the possible exception of remote operations in space. Therefore, novel compensation techniques will be developed. Included will be the development of the real-time simulator, which is at the heart of our approach. The simulator will present real-time, stereoscopic images and artificial haptic stimuli to the surgeon. Image processing: Because of the delay and the possibility of insufficient bandwidth a high level of novel image processing is necessary. This image processing will include several innovative aspects, including image interpretation, video to graphical conversion, texture extraction, geometric processing, image compression and image generation at the surgeon station. Intelligent control: Since the approach we propose is in a sense predictor based, albeit a very sophisticated predictor, a controller, which not only optimizes end effector trajectory but also avoids error, is essential. We propose to investigate two different approaches to the controller design. One approach employs an optimal controller based on modern control theory; the other one involves soft computing techniques, i.e. fuzzy logic, neural networks, genetic algorithms and hybrids of these

Biliary Duct Granular Cell Tumor: A Rare But Surgically Curable Benign Tumor

Granulosa cell tumors are rare benign tumors which may be found throughout the body. Rare cases are isolated within the biliary tree. If completely resected, surgical excision is curative

Fluid/solid transition in a hard-core system

We prove that a system of particles in the plane, interacting only with a certain hard-core constraint, undergoes a fluid/solid phase transition

SN 2006bp: Probing the Shock Breakout of a Type II-P Supernova

HET optical spectroscopy and unfiltered ROTSE-III photometry spanning the first 11 months since explosion of the Type II-P SN 2006bp are presented. Flux limits from the days before discovery combined with the initial rapid brightening suggest the supernova was first detected just hours after shock breakout. Optical spectra obtained about 2 days after breakout exhibit narrow emission lines corresponding to HeII 4200, HeII 4686, and CIV 5805 in the rest frame, and these features persist in a second observation obtained 5 hours later; however, these emission lines are not detected the following night nor in subsequent observations. We suggest that these lines emanate from material close to the explosion site, possibly in the outer layers of the progenitor that have been ionized by the high energy photons released at shock breakout. A P-Cygni profile is observed around 4450 A in the +2 and +3 day spectra. Previous studies have attributed this feature to high velocity H-beta, but we discuss the possibility that this profile is instead due to HeII 4687. Further HET observations (14 nights in total) covering the spectral evolution across the photometric plateau up to 73 days after breakout and during the nebular phase around day +340 are presented, and expansion velocities are derived for key features. The measured decay slope for the unfiltered light curve is 0.0073 +/- 0.0004 mag/day between days +121 and +335, which is significantly slower than the decay of rate 56Co. We combine our HET measurements with published X-ray, UV, and optical data to obtain a quasi-bolometric light curve through day +60. We see a slow cooling over the first 25 days, but no sign of an early sharp peak; any such feature from the shock breakout must have lasted less than ~1 day.[ABRIDGED]Comment: ApJ accepted, 43 page