Search results for "HM"
showing 10 items of 10594 documents
Hopcroft’s Algorithm and Tree-like Automata
2009
In order to analyze some extremal cases of Hopcroft’s algorithm we deepened the relationship between combinatorial properties of circular words and the ex- ecution of the algorithm on cyclic automata associated to such words.In this paper we highlight the notion of word tree and in particular, we char- acterize the word trees for which Hopcroft’s algorithm on the associated tree-like automata has a unique refinement process. Moreover, we show the relationship between the time complexity of the refinements process of the Hopcroft’s algo- rithm on unary cyclic automata and binary tree-like automata. Such a result allows to exhibit a family of tree-like automata representing the worst case of …
Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection
2016
International audience; Automated systems for road crack detection are extremely important in road maintenance for vehicle safety and traveler's comfort. Emerging cracks in roads need to be detected and accordingly repaired as early as possible to avoid further damage thus reducing rehabilitation cost. In this paper, a robust method for Gabor filter parameters optimization for automatic road crack detection is discussed. Gabor filter has been used in previous literature for similar applications. However, there is a need for automatic selection of optimized Gabor filter parameters due to variation in texture of roads and cracks. The problem of change of background, which in fact is road text…
LogDet divergence-based metric learning with triplet constraints and its applications.
2014
How to select and weigh features has always been a difficult problem in many image processing and pattern recognition applications. A data-dependent distance measure can address this problem to a certain extent, and therefore an accurate and efficient metric learning becomes necessary. In this paper, we propose a LogDet divergence-based metric learning with triplet constraints (LDMLT) approach, which can learn Mahalanobis distance metric accurately and efficiently. First of all, we demonstrate the good properties of triplet constraints and apply it in LogDet divergence-based metric learning model. Then, to deal with high-dimensional data, we apply a compressed representation method to learn…
A Case Study on Vestibular Sensations in Driving Simulators.
2022
Motion platforms have been used in simulators of all types for several decades. Since it is impossible to reproduce the accelerations of a vehicle without limitations through a physically limited system (platform), it is common to use washout filters and motion cueing algorithms (MCA) to select which accelerations are reproduced and which are not. Despite the time that has passed since their development, most of these algorithms still use the classical washout algorithm. In the use of these MCAs, there is always information that is lost and, if that information is important for the purpose of the simulator (the training simulators), the result obtained by the users of that simulator will no…
Detection of steering direction using EEG recordings based on sample entropy and time-frequency analysis.
2016
Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, in this preliminary study we recorded high resolution electroencephalography (EEG) from 5 subjects while driving a car under real conditions along with an accelerometer which detects the onset of steering. Two sensor-level analyses, sample entropy and time-frequency analysis, have been implemented to observe the dynamics before the onset of steering. Thus, in order to classify the steering direction we applied a machine learning algorithm consisting of: dimensionality reduction and classification using principal-component-analysis (PCA) and sup…
On the Difference Between Necessary and Unnecessary Glances Away From the Forward Roadway : An Occlusion Study on the Motorway
2019
Objective The present study strove to distinguish traffic-related glances away from the forward roadway from non-traffic-related glances while assessing the minimum amount of visual information intake necessary for safe driving in particular scenarios. Background Published gaze-based distraction detection algorithms and guidelines for distraction prevention essentially measure the time spent looking away from the forward roadway, without incorporating situation-based attentional requirements. Incorporating situation-based attentional requirements would entail an approach that not only considers the time spent looking elsewhere but also checks whether all necessary information has been sampl…
Impaired circadian heart rate variability in Parkinson’s disease: a time-domain analysis in ambulatory setting
2020
Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. The purpose of this pilot study is to evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals. Methods Idiopathic PD patients without comorbidity impairing HRV, and age-matched healthy individuals were recruited in a pilot study. A long-term time domain analysis of HRV using 24-h ambulatory ECG was performed. Results Overall, 18 PD patients fulfilling inclusion criteria completed the evaluation (mean age was 55.6 ± 8.8, disease duration: 5.0 ± 4.7). Mean SCOPA-AUT scor…
Effects of anxiety during mental arithmetic stress on heart rate variability in healthy subjects
2011
Aim: Anxiety may cause an increased risk of myocardial infarction by reductions in heart rate variability (HRV). However, no data exists on the effect of anxiety on a standard mental test of HRV. The aim of this study was to evaluate the association between anxiety elicited by mental stress and HRV. Methods: Effect of anxiety in the actual state (A-State) and in everyday life (A-Trait) has been assessed in 13 healthy subjects and its association to low (LF) and high-frequency (HF) of HRV during mental arithmetic stress has been tested through correlation analysis. Results: A significant increase from baseline through arithmetic stress was observed in the LF component (LF(nu) from 56.87 ± 4.…
A Two-Dimensional Autoregressive Model for MIMO Wideband Mobile Radio Channels
2008
In this work, we propose the multichannel two- dimensional (2D) autoregressive (AR) model for multiple-input multiple-output (MIMO) wideband mobile wireless channels. The parameters of the proposed model can be estimated from the real- world measurement data. For this purpose, we suggest using a straightforward extension of the prediction error minimization (PEM) algorithm. We also address the problem of possible instability of the multichannel 2D AR model. A model stabilization procedure based on numerical optimization techniques is proposed. The performance of the multichannel 2D AR model has been evaluated based on the synthetic data generated using two different channel simulators.
Learning-Graph-Based Quantum Algorithm for k-distinctness
2012
We present a quantum algorithm solving the $k$-distinctness problem in $O(n^{1-2^{k-2}/(2^k-1)})$ queries with a bounded error. This improves the previous $O(n^{k/(k+1)})$-query algorithm by Ambainis. The construction uses a modified learning graph approach. Compared to the recent paper by Belovs and Lee arXiv:1108.3022, the algorithm doesn't require any prior information on the input, and the complexity analysis is much simpler. Additionally, we introduce an $O(\sqrt{n}\alpha^{1/6})$ algorithm for the graph collision problem where $\alpha$ is the independence number of the graph.