ChestLive

Voice-based authentication is prevalent on smart devices to verify the legitimacy of users, but is vulnerable to replay attacks. In this paper, we propose to leverage the distinctive chest motions during speaking to establish a secure multi-factor authentication system, named ChestLive. Compared with other biometric-based authentication systems, ChestLive does not require users to remember any complicated information (e.g., hand gestures, doodles) and the working distance is much longer (30cm). We use acoustic sensing to monitor chest motions with a built-in speaker and microphone on smartphones. To obtain fine-grained chest motion signals during speaking for reliable user authentication, we derive Channel Energy (CE) of acoustic signals to capture the chest movement, and then remove the static and non-static interference from the aggregated CE signals. Representative features are extracted from the correlation between voice signal and corresponding chest motion signal. Unlike learning-based image or speech recognition models with millions of available training samples, our system needs to deal with a limited number of samples from legitimate users during enrollment. To address this problem, we resort to meta-learning, which initializes a general model with good generalization property that can be quickly fine-tuned to identify a new user. We implement ChestLive as an application and evaluate its performance in the wild with 61 volunteers using their smartphones. Experiment results show that ChestLive achieves an authentication accuracy of 98.31% and less than 2% of false accept rate against replay attacks and impersonation attacks. We also validate that ChestLive is robust to various factors, including training set size, distance, angle, posture, phone models, and environment noises.

Trajectory Track for the Landing of Carrier Aircraft with the Forecast on the Aircraft Carrier Deck Motion

The paper presents a prediction method of deck lateral-directional motion for the control of landing trajectory of aircraft. Firstly, through the analysis of the process of aircraft returning to the ship, the modeling of the motion has been built. Secondly, in view of the delay of trajectory tracking captured in the actual process of aircraft landing on the ship, the error caused by the carrier motion signal has been analyzed. Based on the simulation results, the recommended prediction time of carrier motion has been proposed.

Perception of opposite-direction motion in random dot kinematograms

Computational models for motion perception suggest a possibility that read-out of motion signal can yield the perception of opposite direction of the true stimulus motion direction. However, this possibility was not obvious in a standard 2AFC motion discrimination (e.g., leftward vs.rightward). By allowing the motion direction to vary over 360° in typical random-dot kinematograms (RDKs) displays, and by asking observers to estimate the exact direction of motion, we were able to detect the presence of opposite-direction motion perception in RDKs.This opposite-direction motion perception was replicable across multiple display types andfeedback conditions, and participants had greater confidence in their opposite-direction responses than in true guess responses. When we fed RDKs into a computational model of motion processing, we found that the model estimated substantial motion activity in the direction opposite to the coherent stimulus direction, even though no such motion was objectively present in the stimuli, suggesting that the opposite-direction motion perception may be a consequenceof the properties of motion-selective neurons in visual cortex. Together, these results demonstrate that the perception of opposite-direction motion in RDKs is consistent with the known properties of the visual system.

Phase-Based GLRT Detection of Moving Targets with Pixel Tracking in Low-Resolution SAR Image Sequences

Spaceborne synthetic aperture radar (SAR) can provide ground area monitoring with large coverage. However, achieving a wide observation scope comes at the cost of resolution reduction owing to the trade-off between these parameters in conventional SAR. In low-resolution imaging, the moving target appears unresolved, weakly scattered, and slow moving in the image sequence, which can be generated by the subaperture technique. This article proposes a novel moving target detection method. First, interferometric phase statistics are combined with the generalized likelihood ratio test detector. A pixel tracking strategy is further exploited to determine whether a motion signal is present. These methods rely on the approximation of both clutter and noise statistics using Gaussian distributions in a low-resolution scenario. In addition, the motion signals are imaged with a subpixel offset. The proposed method is primarily validated using four real image sequences from TerraSAR-X data, which represent two types of homogeneous areas. The results reveal that moving targets can be detected in nearby areas using this strategy. The method is compared with the stack averaged coherence change detection and particle-filter-based tracking strategies.

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.

Processing The Ground Motion Signal Recording Using Correction Instrument Method

<em>The instrument correction method is a way to eliminate interference with the signal from the recording instrument response. Signal processing by the instrument correction method using the inverse filter method created using the MATLAB program. In this research using Honshu earthquake data, Japan with Mw 7.4 (dated September 5, 2004) recorded by the MERAMEX seismometer type L4C-3D type short seismometer and Japan Tohoku-Oki earthquake with a strength of Mw 9.0 (March 11, 2011) the data from four seismic stations in Padang, West Sumatra with a DS-4A type short-period seismometer. From the research known, the signal can clearly show the phase of the P and S waves. This can help to determine the parameters of the hypocenter, receiver function, moment tensors, studies of</em> <em>. The surface wave phase can be reconstructed well. This is very useful for studies using surface wave data, moment tensor solutions, seismic wave dispersion studies. Based on the amplitude of the instrument correction results compared with theoretical data, the gain or amplification </em> <strong><em>.</em></strong>

Signal envelope and speech intelligibility differentially impact auditory motion perception

Our acoustic environment contains a plethora of complex sounds that are often in motion. To gauge approaching danger and communicate effectively, listeners need to localize and identify sounds, which includes determining sound motion. This study addresses which acoustic cues impact listeners’ ability to determine sound motion. Signal envelope (ENV) cues are implicated in both sound motion tracking and stimulus intelligibility, suggesting that these processes could be competing for sound processing resources. We created auditory chimaera from speech and noise stimuli and varied the number of frequency bands, effectively manipulating speech intelligibility. Normal-hearing adults were presented with stationary or moving chimaeras and reported perceived sound motion and content. Results show that sensitivity to sound motion is not affected by speech intelligibility, but shows a clear difference for original noise and speech stimuli. Further, acoustic chimaera with speech-like ENVs which had intelligible content induced a strong bias in listeners to report sounds as stationary. Increasing stimulus intelligibility systematically increased that bias and removing intelligible content reduced it, suggesting that sound content may be prioritized over sound motion. These findings suggest that sound motion processing in the auditory system can be biased by acoustic parameters related to speech intelligibility.