Yiannis Kamarianakis

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This paper discusses the application of space-time autoregressive integrated moving average (STARIMA) methodology for representing traffic flow patterns. Traffic flow data are in the form of spatial time series and are collected at specific locations at constant intervals of time. Important spatial characteristics of the space-time process are incorporated(More)
Several univariate and multivariate models have been proposed for performing short term forecasting of traffic flow. In this paper two different univariate (historical average and ARIMA) and two multivariate (VARMA and STARIMA) models are presented and discussed. A comparison of the forecasting performance of these four models is undertaken using datasets(More)
This article discusses the application of Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) time series models for representing the dynamics of traffic flow volatility. The methods encountered in the literature so far, focus on the levels of traffic flows while regarding variance constant through time. The approach adopted in this paper(More)
BACKGROUND Zoonotic cutaneous leishmaniasis (ZCL) is endemic in many rural areas of the Southern and Eastern Mediterranean region where different transmission patterns of the disease have been described. This study was carried out in a region located in Central Tunisia and aimed to investigate the spatio-temporal dynamics of the disease from 1999 to 2004.(More)
This report summarizes the methodologies and techniques we developed and applied for tackling task 3 of the IEEE ICDM Contest on predicting traffic velocity based on GPS data. The major components of our solution include 1) A pre-processing procedure to map GPS data to the network, 2) A K-nearest neighbor approach for identifying the most similar training(More)
In this paper, we describe our solution for ICDM 2010 Contest Task 2 (Jams), where the task is to predict future where the next traffic jams will occur in morning rush hour, given data gathered during the initial phase of this peak period. Our solution, which is based on an ensemble approach, finished Second in the final evaluation.
Longitudinal studies of vascular diseases often need to establish correspondence between follow-up images, as the diseased regions may change shape over time. In addition, spatial data structures should be taken into account in the statistical analyses to avoid inferential errors. This study investigates the association between hemodynamics and thrombus(More)
Disclaimer The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. The contents do not necessarily reflect the official views or policies of the UTRC or the Federal Highway Administration. This report does not constitute a standard, specification or regulation.(More)