A quick search method for audio signals based on a piecewise linear representation of feature trajectories

This paper presents a new method for a quick similarity-based search through long unlabeled audio streams to detect and locate audio clips provided by users. The method involves feature-dimension reduction based on a piecewise linear representation of a sequential feature trajectory extracted from a long audio stream. Two techniques enable us to obtain a piecewise linear representation: the dynamic segmentation of feature trajectories and the segment-based Karhunen-L\'{o}eve (KL) transform. The proposed search method guarantees the same search results as the search method without the proposed feature-dimension reduction method in principle. Experiment results indicate significant improvements in search speed. For example the proposed method reduced the total search time to approximately 1/12 that of previous methods and detected queries in approximately 0.3 seconds from a 200-hour audio database.Comment: 20 pages, to appear in IEEE Transactions on Audio, Speech and Language Processin

What Is the Gaze Behavior of Pedestrians in Interactions with an Automated Vehicle When They Do Not Understand Its Intentions?

Interactions between pedestrians and automated vehicles (AVs) will increase significantly with the popularity of AV. However, pedestrians often have not enough trust on the AVs , particularly when they are confused about an AV's intention in a interaction. This study seeks to evaluate if pedestrians clearly understand the driving intentions of AVs in interactions and presents experimental research on the relationship between gaze behaviors of pedestrians and their understanding of the intentions of the AV. The hypothesis investigated in this study was that the less the pedestrian understands the driving intentions of the AV, the longer the duration of their gazing behavior will be. A pedestrian--vehicle interaction experiment was designed to verify the proposed hypothesis. A robotic wheelchair was used as the manual driving vehicle (MV) and AV for interacting with pedestrians while pedestrians' gaze data and their subjective evaluation of the driving intentions were recorded. The experimental results supported our hypothesis as there was a negative correlation between the pedestrians' gaze duration on the AV and their understanding of the driving intentions of the AV. Moreover, the gaze duration of most of the pedestrians on the MV was shorter than that on an AV. Therefore, we conclude with two recommendations to designers of external human-machine interfaces (eHMI): (1) when a pedestrian is engaged in an interaction with an AV, the driving intentions of the AV should be provided; (2) if the pedestrian still gazes at the AV after the AV displays its driving intentions, the AV should provide clearer information about its driving intentions.Comment: 10 pages, 10 figure

Effect of excitatory and inhibitory agents and a glial inhibitor on optically-recorded primary-afferent excitation

The effects of GABA, excitatory amino-acid receptors antagonists and a glial metabolism inhibitor on primary-afferent excitation in the spinal dorsal horn were studied by imaging the presynaptic excitation of high-threshold afferents in cord slices from young rats with a voltage-sensitive dye. Primary afferent fibers and terminals were anterogradely labeled with a voltage-sensitive dye from the dorsal root attached to the spinal cord slice. Single-pulse stimulation of C fiber-activating strength to the dorsal root elicited compound action potential-like optical responses in the superficial dorsal horn. The evoked presynaptic excitation was increased by the GABAA receptor antagonists picrotoxin and bicuculline, by glutamate receptor antagonists D-AP5 and CNQX, and by the glial metabolism inhibitor mono-fluoroacetic acid (MFA). The increase in presynaptic excitation by picrotoxin was inhibited in the presence of D-AP5, CNQX and MFA. Presynaptic modulation in the central terminal of fine primary afferents by excitatory and inhibitory amino acids may represent a mechanism that regulates the transmission of pain

Parametric Feature Detection

We propose an algorithm to automatically construct feature detectors for arbitrary parametric features. To obtain a high level of robustness we advocate the use of realistic multi-parameter feature models and incorporate optical and sensing effects. Each feature is represented as a densely sampled parametric manifold in a low dimensional subspace of a Hilbert space. During detection, the brightness distribution around each image pixel is projected into the subspace. If the projection lies sufficiently close to the feature manifold, the feature is detected and the location of the closest manifold point yields the feature parameters. The concepts of parameter reduction by normalization, dimension reduction, pattern rejection, and heuristic search are all employed to achieve the required efficiency. By applying the algorithm to appropriate parametric feature models, detectors have been constructed for five features, namely, step edge, roof edge, line, corner, and circular disc. Detailed experiments are reported on the robustness of detection and the accuracy of parameter estimation. In the case of the step edge, our results are compared with those obtained using popular detectors. We conclude with a brief discussion on the use of relaxation to rene outputs from multiple feature detectors, and sketch a hardware architecture for a general feature detection machine

Collapsing transition of spherical tethered surfaces with many holes

We investigate a tethered (i.e. fixed connectivity) surface model on spherical surfaces with many holes by using the canonical Monte Carlo simulations. Our result in this paper reveals that the model has only a collapsing transition at finite bending rigidity, where no surface fluctuation transition can be seen. The first-order collapsing transition separates the smooth phase from the collapsed phase. Both smooth and collapsed phases are characterized by Hausdorff dimension H\simeq 2, consequently, the surface becomes smooth in both phases. The difference between these two phases can be seen only in the size of surface. This is consistent with the fact that we can see no surface fluctuation transition at the collapsing transition point. These two types of transitions are well known to occur at the same transition point in the conventional surface models defined on the fixed connectivity surfaces without holes.Comment: 7 pages with 11 figure

Phase structure of a spherical surface model on fixed connectivity meshes

An elastic surface model is investigated by using the canonical Monte Carlo simulation technique on triangulated spherical meshes. The model undergoes a first-order collapsing transition and a continuous surface fluctuation transition. The shape of surfaces is maintained by a one-dimensional bending energy, which is defined on the mesh, and no two-dimensional bending energy is included in the Hamiltonian.Comment: 13 pages with 9 figure

Sparse Coding of Weather and Illuminations for ADAS and Autonomous Driving

Weather and illumination are critical factors in vision tasks such as road detection, vehicle recognition, and active lighting for autonomous vehicles and ADAS. Understanding the weather and illumination type in a vehicle driving view can guide visual sensing, control vehicle headlight and speed, etc. This paper uses sparse coding technique to identify weather types in driving video, given a set of bases from video samples covering a full spectrum of weather and illumination conditions. We sample traffic and architecture insensitive regions in each video frame for features and obtain clusters of weather and illuminations via unsupervised learning. Then, a set of keys are selected carefully according to the visual appearance of road and sky. For video input, sparse coding of each frame is calculated for representing the vehicle view robustly under a specific illumination. The linear combination of the basis from keys results in weather types for road recognition, active lighting, intelligent vehicle control, etc

Five Prognostic Factors for Readmission in Patients Over 75 Years Old with Worsening Heart Failure

Heart failure （HF） is a common disease in elderly patients, particularly in those presenting as readmission for worsening HF. While recent studies have revealed mortality-associated factors in this population, little is known about prognostic factors associated with worsening HF. To investigate this clinical evidence gap in patients aged over 75 years, we retrospectively investigated 165 patients hospitalized for HF at Showa University Hospital, of whom 65 （39.4％） were readmitted for worsening HF. We extracted the candidate variables based on univariate analysis, and then elucidated the independent prognostic factors by multivariate analysis. Compared with non-readmitted patients, readmitted patients with worsening HF had lower left ventricular ejection fraction （LVEF） （39％ vs. 50％, P＝0.002） and body mass index （BMI） （19.9kg/m2 vs. 21.4kg/m2, P＝0.007）, higher levels of B-type natriuretic peptide （BNP） （478pg/ml vs. 198pg/ml, P＜0.001）, and heart rate （HR） （71.0 beats/min vs. 67.0 beats/min, P＝0.021） upon discharge during the primary admission. Multivariate logistic analysis identified LVEF ＜40％, BMI ＜21kg/m2, BNP ≥500pg/ml, Charlson score ≥3, and HR ≥70 beats/min upon initial discharge as independent prognostic factors. Based on these factors, readmission for worsening HF was more frequent in those with our proposed risk score of ≥3.0 than in those with a risk score ＜3.0 （P＜0.001）, and we suggested five prognostic factors for HF patients over 75 years old. Our proposed risk score combines these factors and might predict readmission for worsening HF in the elderly population