Method Of Magnitude Estimation Research Articles

Real-time earthquake magnitude estimation via a deep learning network based on waveform and text mixed modal

Rapid and accurate earthquake magnitude estimations are essential for earthquake early warning (EEW) systems. The distance information between the seismometers and the earthquake hypocenter can be important to the magnitude estimation. We designed a deep-learning, multiple-seismometer-based magnitude estimation method using three heterogeneous multimodalities: three-component acceleration seismograms, differential P-arrivals, and differential seismometer locations, with a specific transformer architecture to introduce the implicit distance information. Using a data-augmentation strategy, we trained and selected the model using 5365 and 728 earthquakes. To evaluate the magnitude estimation performance, we use the root mean square error (RMSE), mean absolute error (MAE), and standard deviation error (ϭ) between the catalog and the predicted magnitude using the 2051 earthquakes. The model could achieve RMSE, MAE, and ϭ less than 0.38, 0.29, and 0.38 when the passing time of the earliest P-arrival is 3 s and stabilize to the final values of 0.20, 0.15, and 0.20 after 14 s. The comparison between the proposed model and model ii, which is retrained without the specific architecture, indicates that the architecture contributes to the magnitude estimation. The P-arrivals picking error testing indicates the model could provide robust magnitude estimation on EEW with an absolute error of less than 0.2 s.Graphical

Default Reference Frames for Angular Expansion in the Perception of Visual Direction.

Prior work has shown that perceived angular elevation relative to a visible horizon/ground plane is exaggerated with a gain of about 1.5. Here, we investigated whether estimates of angular elevation remain exaggerated when no such visual gravitational reference is provided. This was investigated using a series of five experiments, with most using a novel apparatus to view a large field-of-view stereoscopic virtual environment while lying supine, looking straight up. Magnitude estimation methods were used as well as psychometric matches to internal standards with a total of 133 human participants. Generally, it was found that the exaggerated scaling of elevation seemed to be a default for 3D space, even if testing was performed in virtual environments that were nearly empty. Indeed, for supine observers, a strong exaggeration was found even for azimuthal judgments, which is consistent with the idea that, when looking upward, all deviations are in elevation. This suggests that the overarching gravitational frame often serves as a default reference frame.

SCDetect: A SeisComP Module for Real-Time Waveform Cross-Correlation-Based Earthquake Detection

Abstract Enhanced earthquake catalogs based on waveform cross correlation (template matching) have become routine when studying regional or sequence specific seismicity. Currently, there is no existing open-source cross-correlation software that is designed to be fully integrated in real-time operations of seismic networks. To fill this gap, we introduce SCDetect, a software that implements real-time earthquake detection based on waveform cross correlation in the time domain. SCDetect with the extension module scdetect-cc is an open-source SeisComP package written in C++. scdetect-cc can be used to process both archived waveform data (playback mode), and real-time data. In the real-time application, waveforms are fetched through one of the SeisComP RecordStream interfaces, and its output (picks, origin times, amplitudes, and magnitudes) are sent to the SeisComP messaging system. The new origins are associated either with existing events detected by other pick-based SeisComP modules, or create new events. Optionally, the hypocenter location can be refined by downstream application of existing SeisComP modules. scdetect-cc offers two magnitude estimation methods that are based on the amplitudes of the template earthquakes and the new detections. In the real-time application, scdetect-cc can be scaled to handle thousands of templates without overloading the application or becoming too latent, unable to keep up with the data flow. In the playback mode, we applied scdetect-cc to three recent earthquake sequences occurring in Switzerland and surrounding regions between 2019 and 2020. Two scenarios are tested to simulate its performance in real time. The first scenario cross correlates the signals of the nearest station, whereas the second requires four stations. In both cases, we successfully detected most of the cataloged events and added hundreds of new detections. Overall, scdetect-cc is a computationally efficient and highly customizable tool to detect earthquakes for regional networks that implement the SeisComP system for earthquake monitoring.

Optimizing distortion magnitude for data augmentation in few-shot remote sensing scene classification

ABSTRACT In the domain of few-shot classification tasks for remote sensing images, the impact of data augmentation is often overlooked, and conventional methods offer only modest gains in classification performance. To better exploit the potential of data augmentation in few-shot learning, we propose an innovative data augmentation method tailored to optimize few-shot remote sensing scene classification. We begin by dissecting the relationship between various types of feature distortions and classification performance, introducing an optimal distortion magnitude estimation method for different feature types. Subsequently, we integrate multiple distortion magnitude optimization pathways into the model learning process, achieving a dual optimization of model parameters and distortion magnitudes. The extended data provide the model with distorted samples from multiple feature perspectives, and the dynamic optimization of distortion magnitudes enhances the effectiveness of the extended data for classification. Ultimately, we evaluate the performance of our method on general remote sensing datasets, demonstrating a significant advantage in classification accuracy over baseline methods. This approach offers a new perspective in robustness research for few-shot remote sensing scene classification models based on data augmentation.

Audiovisual effects of roadside tree plantings on perception of road traffic sounds

This study investigated the psychological influence of the surrounding landscapes related to the plantings along roadside areas on the subjective impressions of road traffic noise. Herein a subjective evaluation scheme incorporating the semantic differential and magnitude estimation methods was adopted. Under the virtual experimental environment, the conditions with only a visual stimulus and with both visual and auditory stimuli were comparatively evaluated. The results revealed significant differences between when only the visual environment was presented and when the auditory environment was also presented. It suggested that a realistic evaluation of the living environment is possible only when both the visual and auditory environments are explored together. Tree plantings located along the road were found to interact with the SPL of the road traffic noise and the urban environment visible through the windows. It indicated that the psychological noise reduction effect of plantings on noise annoyance varies significantly depending on the audiovisual environment.

Experimental study on effects of sound on vibratory sensation of horizontal vibration

Humans are exposed to both vibration and noise when riding in vehicles such as cars and trains. Therefore, an evaluation of the vibratory sensation based on the combined effect of vibration and noise is needed. This study aims to determine the effects of sound on whole-body vibratory sensations of horizontal vibration. In this study, we conducted two experiments to research the influence of sound on vibratory sensation using an electrodynamic vibration test machine. The first experiment measured the point of subjective equality of the magnitudes of vibration and sound, and the second experiment measured the psychological effects of sound on vibratory sensations using the magnitude estimation method and the seven-grade rating scale method. This paper describes the results of investigating vibration dominance in a combined environment of vibration and sound and the effects of sound on the subjective magnitude of vibration and vibration discomfort.

Psychological responses to amplitude-modulated low-frequency sound

Amplitude-modulated low-frequency sound is a sound in which a pure tone with a carrier frequency lower than 100 Hz is a carrier wave, and the sound pressure level continuously fluctuates over time. This study measured psychological responses to amplitude-modulated low-frequency sounds using psychological questionnaires. We measured three sensations peculiar to low-frequency sounds, annoyance, vibratory sensation, and oppressive sensation caused by amplitude-modulated low-frequency sounds using a seven-grade rating scale. In addition, we measured the loudness and fluctuating sensation caused by amplitude-modulated low-frequency sounds using a magnitude estimation method. This paper discusses the relationship between the psychological response quantities and the physical quantity that constitutes the amplitude-modulated low-frequency sound, the dose-response relationship when exposed to amplitude-modulated low-frequency sound above the sensation threshold.

A preliminary study on the effect of rough sound on discomfort

Acoustic roughness was proposed as a psychoacoustic metric, indicating that rough sound would attract attention or cause unpleasant feelings. Noting that some previous studies have found a negative relation between roughness and discomfort caused by noise, we intend to investigate the effect of roughness on discomfort. The 1000Hz tone was amplitude modulated with the modulation frequency range of 10-140Hz and a modulation depth of 100% as the test stimuli. Forty-eight subjects rated the discomfort caused by the test stimuli relative to the reference stimulus having a standard 1 asper roughness (i.e., 1000Hz tone with a modulation frequency of 70 Hz and a modulation depth of 100%) using the method of relative magnitude estimation. Each stimulus had a sound pressure level of 60 dB and a duration of 1 second. We identified a nonlinear pattern of discomfort with the increasing modulation frequency, with the lowest discomfort for the standard 1 asper roughness at a modulation frequency of 70 Hz. A modification weighting dependent on the modulation frequency would better quantify the roughness metric to reflect the effect of rough sound on discomfort.

K-band Absolute Magnitude Relations of Red Clump Stars Separated by Age

Red clump (RC) stars form a distinguishable clump on the color-magnitude diagram, making it a good distance indicator. Currently, the two main absolute magnitude estimation methods in the I-band (700–900 nm) conflict: one assumes a constant RC magnitude as supported by empirical data and one relates magnitude with other physical characteristics as supported by theoretical models. Studies attribute these discrepancies to population effects, such as dust, and recommend the K-band (2000–2400 nm) to minimize them. Past studies analyzed relations between the K-band magnitude, color, metallicity, and age, including those stratified by age at 2 Gyr. This study aims to investigate these different relations to clarify trends from past studies, discover new trends, and compare them to similar relations in the I-band. After analyzing cluster RC data from Gaia DR3, 2MASS, and Gaia-ESO DR5, K-band magnitude exhibits insignificant correlation in all relations (p>0.05) but has the greatest dependence and the least root mean square error (RMS) with metallicity in the old RC. Significant correlation was found between I-band magnitude and metallicity for all RC and young RC (p<0.05), especially the latter (R2 = 0.804). This consistency with theoretical trends suggests weaker I-band population effects than previously believed. Overall, these three relations yield more accurate predictions than the mean magnitude. Thus, studies cannot solely rely on the mean K-band or I-band magnitude to estimate distance, and magnitude relations stratified by age can potentially lead to more accurate RC distance estimations and a more accurately calibrated distance ladder.

Discomfort estimation for aircraft cabin noise using linear regression and modified psychoacoustic annoyance approaches.

Appropriate sound quality models for noise-induced discomfort are necessary for a better acoustic comfort design in the aircraft cabin. This study investigates the acoustic discomfort in two large passenger aeroplanes (i.e., planes A and B). We recorded the noise at 21 positions in each aircraft cabin and selected 42 stimuli ranging from 72 to 81 dB(A) during the cruising flights. Twenty-four participants rated the noise discomfort by the absolute magnitude estimation method. The discomfort values in the middle section of the aircraft cabin are 10% points higher than in the front or rear section. The discomfort magnitude was dominated by loudness and influenced by roughness and sharpness. A multiple linear (MA) discomfort model was established, accounting for the relationship between the discomfort and sound quality metrics (i.e., loudness, sharpness, and roughness). The MA model estimated noise discomfort better than the Zwicker and other (i.e., More and Di) psychoacoustic annoyance (PA) models. We modified the coefficients of independent variables in the formulations of Zwicker, Di, and More PA models, respectively, according to the present experimental results. The correlation coefficients between the estimated and measured values of the modified models were at least 20% points higher than the original ones.

Subjective evaluation of wind turbine noise using 3-dimensional audio- visual reproduction system

In recent years, the installation of new wind turbines has been promoted in Japan. Since wind turbines are often installed in quiet countryside, it is necessary to properly evaluate the noise impact of wind turbine installation. Since wind turbines are thought to have visual as well as auditory effects, we conducted a subjective evaluation experiment on the loudness and annoyance of wind turbine noise (WTN) and road traffic noise (RTN) by magnitude estimation method, using a three-dimensional audio-visual reproduction system consisting of 6 channels of loudspeakers installed around the sound receiving point and a dome screen. As a result, the loudness and annoyance of WTN tended to be evaluated higher than that of RTN. These results were considered to be influenced by the amplitude modulation called "swish sound" and the low-frequency dominant frequency characteristics, which are characteristics of WTN. In addition, when comparing the differences in loudness and annoyance with and without visual information, the two attributes tended to be lower when visual information was present.

Subjective evaluation of the acoustic annoyance in a large passenger aircraft cabin

People demand better acoustic comfort for higher travelling quality and security in aircraft. It is necessary to evaluate and predict the subjective annoyance caused by the noise in aircraft cabins. This study investigates the noise-induced annoyance in a large passenger aircraft. We recorded the noise at 21 positions in the aircraft cabin without passengers and selected 21 stimuli during the cruising. Each stimulus has a duration of 5 seconds and a sound pressure level in the range of 72-81dB(A). The psychoacoustic parameters such as loudness, sharpness, roughness and articulation index were also calculated. Twenty-four subjects evaluated the subjective annoyance of the stimuli by the absolute magnitude estimation method. Results showed the noise annoyance at the middle section of the cabin is significantly higher than that at the front or rear section. The principal component analysis and correlation analysis found that annoyance is mainly affected by loudness, sharpness and roughness and dominated by loudness. We proposed a multiple linear regression model between the subjective magnitudes of annoyance and the psychoacoustic parameters to evaluate and predict the noise annoyance in the aircraft cabin well.

Preference Drivers for Blackberry Nectar (Rubus spp., Rosaceae) with Different Sweeteners.

This study determined the dynamic sensory profile and consumer acceptance of blackberry nectar with different sweeteners. The ideal scale was used to determine the ideal sweetness of the sucrose and the magnitude estimation method for the equivalent sweetness of the sweeteners. The sensory profile was determined by time-intensity analyses with trained panelists. This study determined the dynamic sensory profile and consumer acceptance of blackberry nectar with different sweeteners. First, to determine the concentration of sucrose to promote optimal sweetness in blackberry nectar, a study was carried out by consumers, who used an unstructured 9 cm "Ideal Scale", ranging from the extreme left as "extremely less sweet than ideal" to the extreme right as "extremely sweet than ideal", with the center of the scale being the ideal sweetness point. Then, the magnitude estimation method was applied to determine the concentration of each sweetener studied in order to obtain the same sensation of ideal sweetness in the blackberry nectar. The sensory profile of blackberry nectar in the same equi-sweetness was determined by time-intensity analysis with trained assessors and CATA (Check-All-that-Apply) with consumers. According to our results and the opinion of the involved consumers, the optimal sucrose concentration in blackberry nectar was 9.3%, and the sweetener concentrations equivalent to sucrose were 0.015% of sucralose, 0.052% of aspartame and 0.09% of stevia with different rebaudioside A concentrations. Time intensity and overall liking data were statistically analyzed by partial least squares regression (PLSR), thus generating the temporal preference drivers for blackberry nectar. The results showed that the sucralose and tasteva sweeteners have a temporal profile closer to sucrose, being characterized by a lower intensity and duration of sweet and bitter taste, with a positive impact on consumer acceptance. Concomitant results were found by the CATA analysis, indicating that the attributes of blackberry aroma, blackberry flavor, sweet taste, and brightness also have a positive impact and stand out in the samples with sucrose, sucralose, and tasteva. The samples sweetened with stevia were characterized by a greater intensity of bitter taste and the presence of a sweet and bitter aftertaste, with a negative impact on acceptance. The different rebaudioside A concentrations in stevia (78%, 92%, and 97%) did not interfere with consumer acceptance.

MEANet: Magnitude estimation via physics-based features time series, an attention mechanism, and neural networks

The traditional magnitude estimation method, which establishes a linear relationship between a single warning parameter and the magnitude, exhibits considerable scatter and underestimation. In addition, the extraction of features from raw waveforms by a deep learning network is a black box. To provide a more robust magnitude estimation and to construct a deep learning network with an interpretable input, in light of deep learning and earthquake rupture physics, we have established a magnitude estimation network model (MEANet) via the physics-based features time series, an attention mechanism, and neural networks. We use events with 4 ≤ M ≤ 7.5 that occur in Japan and the Sichuan-Yunnan region, China, to train and validate MEANet, and then use MEANet to test additional events. Our results find that MEANet has a more robust magnitude estimation than the traditional [Formula: see text] and [Formula: see text] methods, with a standard deviation of error of ±0.25 magnitude units at a single station with a 3 s P-wave time window. Within 10 s after the first station is triggered, based on the weighted average of the triggered stations, MEANet provides robust magnitude estimation without underestimation for events with 4 ≤ M ≤ 7.5. Our finding implies that the final magnitude is to some degree deterministic by the combination of deep learning and physics-based features. Meanwhile, MEANet might have potential for earthquake early warning.

Effect of landscape design on depth perception in classical Chinese gardens: A quantitative analysis using virtual reality simulation.

It is common for visitors to have rich and varied experiences in the limited space of a classical Chinese garden. This leads to the sense that the garden's scale is much larger than it really is. A main reason for this perceptual bias is the gardener's manipulation of visual information. Most studies have discussed this phenomenon in terms of qualitative description with fragmented perspectives taken from static points, without considering ambient visual information or continuously changing observation points. A general question arises, then, on why depth perception can vary from one observation point to another along a garden path. To better understand the spatial experience in classical Chinese gardens, this study focused on variations in perceived depth among different observation points and aimed to identify influential visual information through psychophysical experimentation. As stimuli for the experiment, panoramic photos of Liu garden were taken from three positions at Lvyin Pavilion. Considering the effects of pictorial visual cues on depth perception, the photos were processed to create 18 kinds of stimuli (six image treatments * three positions). Two tasks were presented to the participants. In Task 1, 71 participants were asked to rate the depth value of the garden using the magnitude estimation method in a cave automatic virtual environment (CAVE). Statistical analysis of Task 1 revealed that depth values differed significantly among different viewpoints. In Task 2, participants were asked to compare 18 stimuli and 3D images presented on three connected monitors and to judge the depth of the garden using the adjustment method. The results of Task 2 again showed that depth values differed significantly among different viewpoints. In both tasks, ambient information (i.e., the perspective of interior space) significantly influenced depth perception.

Evaluation of subjective discomfort of the seated human body exposed to vertical vibration using dynamic body pressure

Pressure distribution has been regarded as a crucial parameter for static comfort evaluation of the seated human body. However, the association between the pressure distribution and subjective rating, exposed to vertical vibration, is still unclear. This study devotes to characterizing the vibration discomfort of the seated human body on a foam seat using dynamic body pressure distribution and investigating the associations between them. First, the dynamic body pressure of twelve subjects seated on a foam seat exposed to vertical random excitation was measured at frequencies from 0.5 to 20 Hz with six magnitudes (0.2, 0.4, 0.6, 0.8, 1.0, and 1.2 m/s2 r.m.s.). Meanwhile, the subjective discomfort rating of the foam seat was evaluated with the relative magnitude estimation method. Then, the influence of vibration magnitude on subjective discomfort ratings and dynamic body pressure indicators was investigated. The results show that with the increase of vibration magnitude, the mean average dynamic pressure, the mean peak dynamic pressure, the mean dynamic contact area, and the normal dynamic force had no significant change. On the contrary, the subjective discomfort ratings, normal dynamic force change rate root-mean-square, and the indicators related to pressure change rate root-mean-square increased significantly. Finally, the relation between the subjective discomfort ratings and dynamic body pressure indicators was analyzed using Stevens’ power law. The linear regression fitting accuracy of the average dynamic pressure change rate root-mean-square, peak dynamic pressure change rate root-mean-square, area pressure change rate root-mean-square, and normal dynamic force change rate root-mean-square with discomfort ratings were above 95%. The four dynamic body pressure indicators are highly correlated with the subjective discomfort ratings, which can be used as objective indicators for vibration discomfort evaluation.

Prediction model for perceptual gloss by physical measurement of flat objects

Although a physical gloss exists as a physically measurable index, people can also perceive a perceptual gloss on object surfaces. However, the physical gloss does not always match the perceptual gloss. Because the physical gloss is calculated based only on the specular gloss and does not reflect other physical features that affect the perceptual gloss. Thus, we analysed the relationships between physical features and perceptual gloss by measuring many physical properties of object surfaces, including their physical gloss. We prepared 127 flat objects comprising three materials: paper, resin and metal plating. The perceptual gloss was visually evaluated for observation angles of 20°, 60° and 85° using a magnitude estimation method. Multiple measurements were conducted to obtain physical features such as the gloss unit (GU), haze, distinctness of image and high dynamic range luminance. We then constructed prediction models for the perceptual gloss using these physical features and multiple regression analyses. By combining these multiple physical quantities and using the GU in the power scale, the prediction accuracy was improved. By the optimal power index (0.33 for physical gloss in the common prediction model, independent of the observation angle), we found that human gloss perception may be related to brightness perception.

Sound quality modelling of hairdryer noise

The demand for acoustic comfort in domestic appliances increases with the rapid growth of living quality requirements. As a common domestic appliance, the hairdryer produces unwanted noise that affects comfort during working. Manufacturers make great efforts to control the hairdryer noise, e.g., reduce the sound pressure level (SPL) by increasing blades number to make the frequency of noise energy above the hearing range. This study investigated the noise discomfort of a supersonic hairdryer (SHD) and three standard hairdryers (HD). We measured and recorded hairdryer noise at all operating conditions, and generated 120 test stimuli at SPLs ranging from 60 to 72 dB(A) in 3 dB steps based on 24 sound samples. Twenty-four subjects evaluated the noise discomfort of all stimuli using the absolute magnitude estimation (AME) method. The contribution of psychoacoustic metrics, i.e. loudness, sharpness, roughness, fluctuation strength, tonality (hearing model) and articulation index, to the noise discomfort was analysed by partial correlation analysis. Hairdryer noise discomfort was dominated by loudness and significantly influenced by tonality. The sound quality models were established for SHD and HD by multiple linear regression between the discomfort and two psychoacoustic metrics, i.e., loudness and tonality. The SHD performed better in sound quality for less discomfort and interference of communication than the HD, yet the adverse effects of the ultra-high frequencies on comfort and health need further consideration.

Multiple Spatial Spectral Components of Static Skin Deformation for Predicting Macroscopic Roughness Perception.

A previous study suggested a relationship between the spatial spectrum of finger pad skin deformation and perception of macroscopic roughness features. This study tested a new hypothesis that macroscopic roughness perception is the result of a weighted linear combination of multiple spatial spectral components of skin deformation. Experiments were conducted by capturing close-up images of finger pad deformation while the pads were pushed onto specimens with macroscopic features. Additionally, the roughness perceptions of these specimens were collected using a magnitude estimation method. The combination of spectral components predicted the roughness perception more accurately than any single spectral component. This suggests that roughness perception is mediated by multiple Gabor filter-like neural systems with different spatial periods, such as visual perception.

A Synchronous Magnitude Estimation with P-Wave Phases' Detection Used in Earthquake Early Warning System.

How to estimate an earthquake’s magnitude rapidly and accurately is a challenge for any earthquake early warning system. In order to reach a balance between accuracy and timeliness, a synchronous magnitude estimation method with P-wave phases’ detection is proposed. In this method, the P-wave phases are detected by the changes of the signal-to-noise ratio (SNR) of the seismic records, where the SNRs are calculated by the short-term power and long-term power ratio (STP/LTP). Meanwhile, the variations of the SNR are applied to estimate the magnitude of the earthquake. By the statistics of some earthquake cases, a synchronous magnitude estimation model of the variation of the P-wave phases’ SNR, the earthquake magnitude, and the hypocentral distance was built. Compared with some other magnitude estimation methods, the suggested method inherits the robustness of the STP/LTP method and is more accurate and rapid than the peak displacement () method.