Ryerson University

About: Ryerson University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 7671 authors who have published 20164 publications receiving 394976 citations. The organization is also known as: Ryerson Polytechnical Institute & Ryerson Institute of Technology.

Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria

Abstract: Modelling spatial heterogeneity (SH) is a controversial subject in real estate economics. Single-family-home prices in Austria are explored to investigate the capability of global and locally weighted hedonic models. Even if regional indicators are not fully capable to model SH and technical amendments are required to account for unmodelled SH, the results emphasise their importance to achieve a well-specified model. Due to SH beyond the level of regional indicators, locally weighted regressions are proposed. Mixed geographically weighted regression (MGWR) prevents the limitations of fixed effects by exploring spatially stationary and non-stationary price effects. Besides reducing prediction errors, it is concluded that global model misspecifications arise from improper selected fixed effects. Reported findings provide evidence that the SH of implicit prices is more complex than can be modelled by regional indicators or purely local models. The existence of both stationary and non-stationary effects implies that the Austrian housing market is economically connected.

Automated Road Information Extraction From Mobile Laser Scanning Data

Abstract: This paper presents a survey of literature about road feature extraction, giving a detailed description of a Mobile Laser Scanning (MLS) system (RIEGL VMX-450) for transportation-related applications. This paper describes the development of automated algorithms for extracting road features (road surfaces, road markings, and pavement cracks) from MLS point cloud data. The proposed road surface extraction algorithm detects road curbs from a set of profiles that are sliced along vehicle trajectory data. Based on segmented road surface points, we create Geo-Referenced Feature (GRF) images and develop two algorithms, respectively, for extracting the following: 1) road markings with high retroreflectivity and 2) cracks containing low contrast with their surroundings, low signal-to-noise ratio, and poor continuity. A comprehensive comparison illustrates satisfactory performance of the proposed algorithms and concludes that MLS is a reliable and cost-effective alternative for rapid road inspection.

Discrimination of pathological voices using a time-frequency approach

Abstract: Acoustical measures of vocal function are routinely used in the assessments of disordered voice, and for monitoring the patient's progress over the course of voice therapy. Typically, acoustic measures are extracted from sustained vowel stimuli where short-term and long-term perturbations in fundamental frequency and intensity, and the level of "glottal noise" are used to characterize the vocal function. However, acoustic measures extracted from continuous speech samples may well be required for accurate prediction of abnormal voice quality that is relevant to the client's "real world" experience. In contrast with sustained vowel research, there is relatively sparse literature on the effectiveness of acoustic measures extracted from continuous speech samples. This is partially due to the challenge of segmenting the speech signal into voiced, unvoiced, and silence periods before features can be extracted for vocal function characterization. We propose a joint time-frequency approach for classifying pathological voices using continuous speech signals that obviates the need for such segmentation. The speech signals were decomposed using an adaptive time-frequency transform algorithm, and several features such as the octave max, octave mean, energy ratio, length ratio, and frequency ratio were extracted from the decomposition parameters and analyzed using statistical pattern classification techniques. Experiments with a database consisting of continuous speech samples from 51 normal and 161 pathological talkers yielded a classification accuracy of 93.4%.

Distributed Attitude Coordination Control for Spacecraft Formation Flying

Abstract: A distributed attitude coordination control scheme using terminal sliding mode (TSM) is proposed for a group of spacecraft in the presence of external disturbances. A novel fast terminal sliding manifold is presented, and a robust control term based on the hyperbolic tangent function is employed to suppress bounded external disturbances. The finite-time stability of the overall closed-loop system is guaranteed by a Lyapunov-based approach, and numerical simulations are presented to demonstrate the performance of the proposed controller.