Pierre Robillard

Estimating the O-D matrix from observed link volumes☆

Abstract Until now the traffic volume data have been used almost exclusively for the study of circulation control and road construction. We present a methodology to use these data for transportation planning where traditionally the data needed came from an O-D survey. We demonstrate that the traffic volume data are informative enough to be useful for this purpose. Most specifically we want to study the estimate of the O-D matrix obtained using observed link volumes for the class of proportional assignment methods. These methods are essentially the ones which do not take into account explicitly or implicitly any constraints of capacities. We show that for this class of method the estimation of the O-D matrix is equivalent to a linear regression problem. We discuss the problem of estimability of the parameters and relate this question with the sample of traffic volume needed. The discussion is illustrated by an example.

Impact of PACS on Dictation Turnaround Time and Productivity

This study was conducted to measure the impact of PACS on dictation turnaround time and productivity. The radiology information system (RIS) database was interrogated to calculate the time interval between image production and dictation for every exam performed during three 90-day periods (the 3 months preceding PACS implementation, the 3 months immediately following PACS deployment, and a 3-month period 1 year after PACS implementation). Data were obtained for three exam types: chest radiographs, abdominal CT, and spine MRI. The mean dictation turnaround times obtained during the different pre- and post-PACS periods were compared using analysis of variance (ANOVA). Productivity was also determined for each period and for each exam type, and was expressed as the number of studies interpreted per full-time equivalent (FTE) radiologist. In the immediate post-PACS period, dictation turnaround time decreased 20% (p < 0.001) for radiography, but increased 13% (ns) for CT and 28% (p < 0.001) for MRI. One year after PACS was implemented, dictation turnaround time decreased 45% (p < 0.001) for radiography and 36% (p < 0.001) for MRI. For CT, 1 year post-PACS, turnaround times returned to pre-PACS levels. Productivity in the immediate post-PACS period increased 3% and 38% for radiography and CT, respectively, whereas a 6% decrease was observed for MRI. One year after implementation, productivity increased 27%, 98%, and 19% in radiography, CT, and MRI, respectively. PACS benefits, namely, shortened dictation turnaround time and increased productivity, are evident 1 year after PACS implementation. In the immediate post-PACS period, results vary with the different imaging modalities.

Technical Note—Expected Completion Time in Pert Networks

This note introduces a general approach to obtain lower bounds for the expected completion time in PERT networks where activity durations are random (discrete or continuous) variables. We show that some well-known bounds can be derived as particular cases of this general approach based on Jensens inequality. We assume that the durations of the activities terminating at a node are independent of the durations of the activities terminating at another node and that all the activity durations have a finite positive range.

Spatial Resolution of Four Electrode Array

The in vivo measurement of specific impedance in brain tissue involves several technical aspects. The most stringent difficulties relate to electrode polarization and spatial resolution of the measuring system. The polarization is solved by usinga four electrode arrangement with a very high impedance preamplifier on the potential electrodes. This paper discusses the relative effectiveness of the various possible linear configurations of four electrodes in terms of spatial resolution. The accuracy of computed spatial resolution with respect to corresponding experimental ones is specified.

The Completion Time of PERT Networks

PERT and critical path techniques have exceptionally wide applications. These techniques and their applications have contributed significantly to better planning, control, and general organization of many programs. This paper is concerned with a technical improvement in PERT methodology by introducing a new approach to approximating, in a computationally efficient way, the total duration distribution function of a program. It is assumed that the activity durations are independent random variables and have a finite range. The first part of the paper considers PERT networks and deals with the lower bound approximation to the total duration distribution function of the program. Then we use this approximation and CPM to propose bounds for the different moments of the distribution function. We illustrate this with numerical examples. In the second part of the paper we adapt our results to PERT decision networks.

Schematic pseudocode for program constructs and its computer automation by SCHEMACODE

To achieve program control flow representation that is relatively independent of any given programming language, schematic pseudocode (SPC) uses a perceptual notation system composed of schemata whose syntax rules are described by a grammar. Source code documentation is supported by operational comments, and translation into a target procedural language is fully automatic.

Vulnerable Atherosclerotic Carotid Plaque Evaluation by Ultrasound, Computed Tomography Angiography, and Magnetic Resonance Imaging: An Overview

Ischemic syndromes associated with carotid atherosclerotic disease are often related to plaque rupture. The benefit of endarterectomy for high-grade carotid stenosis in symptomatic patients has been established. However, in asymptomatic patients, the benefit of endarterectomy remains equivocal. Current research seeks to risk stratify asymptomatic patients by characterizing vulnerable, rupture-prone atherosclerotic plaques. Plaque composition, biology, and biomechanics are studied by noninvasive imaging techniques such as magnetic resonance imaging, computed tomography, ultrasound, and ultrasound elastography. These techniques are at a developmental stage and have yet to be used in clinical practice. This review will describe noninvasive techniques in ultrasound, magnetic resonance imaging, and computed tomography imaging modalities used to characterize atherosclerotic plaque, and will discuss their potential clinical applications, benefits, and drawbacks.

Iterative numerical methods for trip distribution problems

Abstract The Furness method is one of the most popular methods used in the trip generation process where one wants to estimate the number of trips likely to be made per unit time, between pair of zones in a residential area. This paper is directed to the numerical analysis of the Furness method. We discuss the rate of convergence of the method which after the question of convergence itself is the most important aspect of the method. This discussion leads us to suggest a complementary method which, used with the original method, would guarantee the accuracy of the results. This complementary method is an adaptation of Newtons method.

Computer analysis and pattern recognition of doppler blood flow spectra for disease classification in the lower limb arteries

In the present study, a computer processing method was developed to objectively classify disease in the lower limb arteries evaluated by noninvasive ultrasonic duplex scanning. This method analyzes Doppler blood flow signals, extracts diagnostic features from Doppler spectrograms and classifies the severity of the disease into three categories of diameter reduction (0-19%, 20-49% and 50-99%). The features investigated were based on frequency features obtained at peak systole, spectral broadening indices and normalized amplitudes of the power spectrogram computed in various positive and negative frequency bands. A total of 379 arterial segments studied from the aorta to the popliteal artery were classified using a pattern recognition method based on the Bayes model. Two classification schemes using a two-node decision rule were tested. Both schemes gave similar results, the first one provided an overall accuracy of 83% (Kappa = 0.42) and the second an overall accuracy of 81% (Kappa = 0.35) when compared with conventional biplane contrast arteriography. These performances, especially for the 0 to 19% lesion category, are better than the one obtained by the technologist (accuracy = 76% and Kappa = 0.33), based on visual interpretation of the Doppler spectrograms. To recognize hemodynamically significant stenoses (50-99% lesions), the pattern recognition system has a sensitivity and a specificity of 50% and 99%, respectively, using classification scheme I. With classification scheme II, the sensitivity and the specificity are 50% and 98%, respectively. Visual interpretation of the Doppler spectrograms leads to a sensitivity and a specificity of 50% and 98%, respectively. These results are the first to be obtained by a pattern recognition system in classifying lower limb arterial stenoses.

MULTIPATH TRAFFIC ASSIGNMENT WITH DYNAMIC INPUT FLOWS

Abstract In this paper we relax an assumption made by almost every traffic model in use today in transportation planning, that is the assumption of the stationarity of the traffic flow where the input flows are assumed constant through time. It is important to refine the presently used traffic models which are supposed to simulate the reality to the case of non stationary models. The study of the dynamic aspect of the traffic flow patterns, their evolution with time and location is a key to a better understanding of the transportation phenomena. We present in this study an approach to the realization of this goal by adapting the probabilistic multipath assignment model to the case of non stationary input flows. The probabilistic multipath assignment model introduced by Dial (Transpn Res. 5, 83–111, 1972) is a multipath generalization of the all-or-nothing model and subsumes it as a particular case. Given non stationary input flows the assignment model evaluates for each point of the transportation network, the flow distribution through time. This allows to study the formation and the evolution of congestion and gives a more precise image of the reality. The algorithm implementing this dynamic model uses repeatedly an adapted version of the algorithm for the stationary case and a fast Fourier transform procedure.