Search

The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been employed by agencies as an innovative method for pavement design since the National Cooperative Highway Research Program (NCHRP) Project 1-37A was implemented in 2004. Over the years, the MEPDG has evolved into the AASHTOWare Pavement ME Design software (AASHTOWare®). Local calibration of the performance models in the AASHTOWare® is a crucial and challenging task to improve the effectiveness of its application. The accuracy of the calibration depends on efficient methods and validation processes. This paper aims at developing local calibration methods for joint faulting prediction model of Jointed Plain Concrete Pavement (JPCP). This study not only focuses on improving the prediction accuracy of the joint faulting model but also demonstrating the various optimisation procedures in detail. A total of 27 representative JPCP sections were used in the processes of calibration. Three optimisation approaches were used: (1) One-At-a-Time (OAT) through the trial-and-error procedure, (2) generalised reduced gradient (GRG) using MS Excel® Solver, and (3) Levenberg-Marquardt Algorithm (LMA) fitting the functions. The prediction accuracy of local models was improved as compared with the global ones. Average Bias (AB) reduced from 0.3083 to 0.0578, and Standard Error of the Estimate (SEE) reduced from 0.3345 to 0.1912. Among the three local calibration approaches, approach 2 and approach 3 had more significant improvement on results than approach 1. Finally, the integral procedures were provided for local calibration in Ontario. [ABSTRACT FROM AUTHOR]

Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results. [ABSTRACT FROM AUTHOR]

Police agencies in Canada and elsewhere have received much criticism over how they respond to persons with serious mental disorders. The adequacy of training provided to police officers on mental health issues and in particular on recognizing indicators of serious mental disorders has been a major concern. This paper describes the process that led to the development of a new brief mental health screener (interRAI Brief Mental Health Screener, BMHS) designed to assist police officers to better identify persons with serious mental disorders. The interRAI BMHS was developed in collaboration with interRAI, an international, not-for-profit consortium of researchers. The government of Ontario had previously partnered with interRAI to develop and implement the Resident Assessment Instrument for Mental Health (RAI-MH), the assessment system mandated for use on all persons admitted into inpatient psychiatric care in the province. Core items on the interRAI BMHS were obtained through analysis (N=41,019) of RAI-MH data together with input from representatives from health care, police services, and patient groups. Two police services in southwestern Ontario completed forms (N=235) on persons thought to have a mental disorder. Patient records were later accessed to determine patient disposition. The use of summary and inferential statistics revealed that the variables significantly associated with being taken to hospital by police included performing a self-injurious act in the past 30days, and others being concerned over the person's risk for self-injury. Variables significantly associated with being admitted included abnormal thought process, delusions, and hallucinations. The results of the study indicate that the 14-variable algorithm used to construct the interRAI BMHS is a good predictor of who was most likely to be taken to hospital by police officers and who was most likely to be admitted. The instrument is an effective means of capturing and standardizing police officer observations enabling them to provide more and better quality information to emergency department (ED) staff. Teaching police officers to use the form constitutes enhanced training on major indicators of serious mental disorders. Further, given that items on the interRAI BMHS are written in the language of the health system, language acts as common currency between police officers and ED staff laying the foundation for a more collaborative approach between the systems. [ABSTRACT FROM AUTHOR]

This paper develops a model for cancer screening and cancer incidence data, accommodating the partially unobserved disease status, clustered data structures, general covariate effects, and dependence between exams. The true unobserved cancer and detection status of screening participants are treated as latent variables, and a Markov Chain Monte Carlo algorithm is used to estimate the Bayesian posterior distributions of the diagnostic error rates and disease prevalence. We show how the Bayesian approach can be used to draw inferences about screening exam properties and disease prevalence while allowing for the possibility of conditional dependence between two exams. The techniques are applied to the estimation of the diagnostic accuracy of mammography and clinical breast examination using data from the Ontario Breast Screening Program in Canada. [ABSTRACT FROM AUTHOR]

Abstract: The package r.sun within the open source Geographical Resources Analysis Support System (GRASS) can be used to compute insolation including temporal and spatial variation of albedo and solar photovoltaic yield. A complete algorithm is presented covering the steps of data acquisition and preprocessing to post-simulation whereby candidate lands for incoming solar farms projects are identified. The optimal resolution to acquire reliable solar energy outputs to be integrated into PV system design software was determined to be 1square km. A case study using the algorithm developed here was performed on a North American region encompassing fourteen counties in South-eastern Ontario. It was confirmed for the case study that Ontario has a large potential for solar electricity. This region is found to possess over 935,000 acres appropriate for solar farm development, which could provide 90GW of PV. This is nearly 60% of Ontario’s projected peak electricity demand in 2025. The algorithm developed and tested in this paper can be generalized to any region in the world in order to foster the most environmentally-responsible development of large-scale solar farms. [Copyright &y& Elsevier]

Forest background, consisting of understory, moss, litter, and soil, contributes significantly to optical remote sensing signals from forests in the borealregion. In this paper, we present results of background reflectance retrieval from multiangle high-resolution Compact Airborne Spectrographic Imager sensor data over a boreal forest area near Sudbury, ON, Canada. Modifications of the background by white and black plastic sheets at two sites provide two extreme limits for the development and testing of an algorithm for retrieving the background information from multiangle data. Measured background reflectances in red and near-infrared bands at six sites in the vicinity of these modified sites are used to validate the algorithm. We also explore the effect of uncertainties in the input forest structural parameters on this retrieval. The results document: 1) capability of the algorithm to retrieve meaningful background reflectance values for various forest stand conditions, particularly in the low to intermediate canopy density range; 2) the effect of background bidirectional reflectance distribution function on retrieved values; 3) performance of the algorithm using data with different cross angle values; and 4) verification of the internal consistency of the geometric-optical 4-Scale model used. The results provide an important platform for the operational estimation of the vegetation background reflectance from the bidirectional reflections observed by the Multiangle Imaging Spectroradiometer instrument. [ABSTRACT FROM AUTHOR]

Abstract: Trip decisions are complex and involve choosing the activity destination, mode and subsequently the route for travel. This paper presents detailed information on the planned and observed route choices for the home-to-work commute. Specifically, the study examines how people formulate their route plans and describe their attitudes and preferences for their selected routes. A geographic information system (GIS) records the planned route information with the route planning sequence. Observing route choice is a difficult procedure; however, through the use of the global positioning system (GPS), one can accurately record route choice. An automated activity–trip detection algorithm processes GPS data and displays results within an internet-based prompted recall diary. The diary is used to verify trip start and end times. This combination of GPS, GIS and diary responses provides great insight into the route choice decision-making process. Thirty-one individuals from Ontario, Canada participated in answering survey questions and the collection of person-based GPS data. Results indicate a preference to minimize travel time as stated by participants in deciding what route to travel. Participants also affirmed a desire to minimize the number of stop lights/signs, as well as, avoid congestion and maximize route directness. A comparison between planned and observed routes, reveals about one-fifth of participants deviated from their planned route. This study demonstrates the need for qualitative and quantitative survey methods for exploring planned and observed route choice. [Copyright &y& Elsevier]

The article discusses the highlights of research papers on short read sequencing and algorithms presented at the 2008 Intelligent Systems in Molecular Biology conference held in Toronto, Ontario. Keynote address was delivered by Dr. Edwin Cuppen of the Hubrecht Laboratory. Topics discussed included the advent of high-throughput sequencing, RNA sequencing and advantage of short read sequencing.