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Bridge wear and deterioration occur over time under typical operations. Inspections can be resource intensive, infrequent, and sometimes require bridge closure. Instrumented passing vehicles may be used to record vibration responses and extract damage‐sensitive bridge frequency response characteristics. This paper presents a methodology for extracting bridge frequencies from crowdsourced dynamic response data recorded within passing vehicles. Detected bridge frequency changes and a novel point cloud methodology are used to identify critical damage scenarios and estimate remaining life. The use of a novel crowdsourced Welch methodology allows for spectra averaging that reduces the influence of noise and transient events. Numerical and experimental studies illustrate that bridge frequencies can be accurately estimated and that changes in bridge frequency caused by different damage scenarios can be characterized. Numerical examples for the damage scenario analysis, including estimation of remaining life, are provided for two bridge types and three specific damage scenarios. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is one of the most unparalleled disasters the world has ever seen. Previously, the global community has faced the Middle East Respiratory Syndrome (MERS), Ebola Virus Disease (EVD), and Severe Acute Respiratory (SARS). However, the tremendous rate of infection created by the global COVID-19 pandemic is unmatchable with its rapid spread all over the world. Therefore, it is considered as a Black Swan event as created previously by the 2008 financial crisis, SARS, and 9/11 terrorist attack. All these events have triggered panic selling that affected the confidence of investors and businesses. Subsequently, stock market performance has affected the choice of investment decisions that translated into stock return. Therefore, this paper was undertaken to investigate the co-integration and causality relationship among global COVID-19 daily infected cases, COVID-19 recoveries rate, COVID-19 death rate, investor sentiment, government policy, foreign exchange rate, Malaysia gold price, and crude oil price towards the KLCI stock market return. This study employed an exploratory sequential mixed methods approach along with Johansen and Julius Co-Integration and Granger Causality in explaining the Malaysia stock market return. The empirical analysis concluded that COVID-19 daily cases, COVID-19 recoveries rate, government policy and foreign exchange have had a long-term effect in explaining the Malaysia stock return. On the other hand, all the study variables, except for government policy indicated a short-term effect on the Malaysia stock return. This study will contribute significantly to the body of finance literature on the impact of a disease outbreak, with highlights on the considerations of investors on the global COVID-19 pandemic in illuminating the variation of Malaysia stock market returns. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the model for a Gaussian soft-handover channel (SHC), which adds a new dimension of flexibility to the well-known interference channel (IC). We provide a unified framework for computing achievable rate regions for the SHC in both the uplink and downlink cases. This achievable rate region for SHC is given by the convex hull of the union of certain multiple-access, interference, broadcast, and Z-channels. Some properties of the achievable region are studied. Specifically, we show the following key results: 1) In an uplink SHC, there are channel conditions under which decoding at a single receiver based, for example, on a maximum SNR condition does not achieve the entire boundary of the achievable region; 2) in a downlink SHC, multiple base stations should transmit independent information to all users to achieve the boundary points of the achievable region; and 3) when a mobile communicates with multiple base stations, the ratio of the uplink rates with different base stations could be different from the ratio of the downlink rates with those base stations. A simple outer bound on SHC capacity based on the capacity of multiple-input-multiple-output (MIMO) systems is also given. Index Terms--Interference channel (IC), multiuser capacity, soft handover.

A framework is proposed for optimal joint design of the optical and reconstruction filters in a computational imaging system. First, a technique for the design of a physically unconstrained system is proposed whose performance serves as a universal bound on any realistic computational imaging system. Increasing levels of constraints are then imposed to emulate a physically realizable optical filter. The proposed design employs a generalized Benders' decomposition method to yield multiple globally optimal solutions to the nonconvex optimization problem. Structured, closed-form solutions for the design of observation and reconstruction filters, in terms of the system input and noise autocorrelation matrices, are presented. Numerical comparison with a state-of-the-art optical system shows the advantage of joint optimization and concurrent design. OCIS codes: 110.1758, 110.3010.

A thin, agile multiresolution, computational imaging sensor architecture, termed PANOPTES (processing arrays of Nyguist-limited observations to produce a thin electro-optic sensor), which utilizes arrays of microelectromechanical mirrors to adaptively redirect the fields of view of multiple low-resolution subimagers, is described. An information theory-based algorithm adapts the system and restores the image. The modulation transfer function (MTF) effects of utilizing micromirror arrays to steering imaging systems are analyzed, and computational methods for combining data collected from systems with differing MTFs are presented. OCIS codes: 110.2970, 230.3990, 100.6640.