Estimating time-series changes in social sentiment @Twitter in U.S. metropolises during the COVID-19 pandemic.

Since early 2020, the global coronavirus pandemic has strained economic activities and traditional lifestyles. For such emergencies, our paper proposes a social sentiment estimation model that changes in response to infection conditions and state government orders. By designing mediation keywords that do not directly evoke coronavirus, it is possible to observe sentiment waveforms that vary as confirmed cases increase or decrease and as behavioral restrictions are ordered or lifted over a long period. The model demonstrates guaranteed performance with transformer-based neural network models and has been validated in New York City, Los Angeles, and Chicago, given that coronavirus infections explode in overcrowded cities. The time-series of the extracted social sentiment reflected the infection conditions of each city during the 2-year period from pre-pandemic to the new normal and shows a concurrency of waveforms common to the three cities. The methods of this paper could be applied not only to analysis of the COVID-19 pandemic but also to analyses of a wide range of emergencies and they could be a policy support tool that complements traditional surveys in the future.

The 20k Samples-Per-Second Real Time Detection of Acoustic Vibration Based on Displacement Estimation of One-Dimensional Laser Speckle Images.

Audio signal acquisition using a laser speckle image is an appealing topic since it provides an accurate and non-contact solution for vibration measurement. However, due to the limitation of camera frame rate and image processing speed, previous research could not achieve real time reconstruction of an audio signal. In this manuscript, we use a one-dimensional laser speckle image to measure the acoustic vibration of sound source and propose a fast and sub-pixel accuracy algorithm to estimate the displacement of captured one-dimensional laser speckle images. Compared with previous research, the proposed method is faster and more accurate in displacement estimation. Owing to this, the frequency bandwidth and the robustness are significantly increased. Experiment results show that the proposed system can achieve 20k samples-per-second sampling rate, and the audio signal can be reconstructed with high quality in real time.

Delta-Sigma Modulated Visible Light Communication Illumination System Using a Projector with the Digital Micro-Mirror Device.

There is a unique transmission method of visible light communication (VLC) that can transmit multiple data in multiple directions simultaneously by using a projector with the digital micro-mirror device (DMD). Previously, we proposed a method of transmitting data from the projector that transmits digitally modulated VLC signal from each pixel, and in this paper, we propose an extension of the method to transmit audio signal by using a special type of modulation called delta-sigma-modulation (DSM). The DSM-VLC system employs a simple receiver that comprises simple analog electric circuits, which contribute to low power consumption. We made a DSM-VLC prototype and verified that the prototype was able to send four different waves to different directions. Additionally, the experiments' results agree very well with the simulation results. Furthermore, we designed two types of DSM: pulse width modulation (PWM) and pulse density modulation (PDM), and we verified that the PDM-VLC is better than the PWM-VLC regarding the DMD switching frequency's efficiency. Our proposed DSM-VLC can be used for such applications as voice information guidance systems with direction-selective messages.