2,165 research outputs found
A mean-field game economic growth model
Here, we examine a mean-field game (MFG) that models the economic growth of a
population of non-cooperative rational agents. In this MFG, agents are
described by two state variables - the capital and consumer goods they own.
Each agent seeks to maximize their utility by taking into account statistical
data of the total population. The individual actions drive the evolution of the
players, and a market-clearing condition determines the relative price of
capital and consumer goods. We study the existence and uniqueness of optimal
strategies of the agents and develop numerical methods to compute these
strategies and the equilibrium price
Design exploration and performance strategies towards power-efficient FPGA-based achitectures for sound source localization
Many applications rely on MEMS microphone arrays for locating sound sources prior to their execution. Those applications not only are executed under real-time constraints but also are often embedded on low-power devices. These environments become challenging when increasing the number of microphones or requiring dynamic responses. Field-Programmable Gate Arrays (FPGAs) are usually chosen due to their flexibility and computational power. This work intends to guide the design of reconfigurable acoustic beamforming architectures, which are not only able to accurately determine the sound Direction-Of-Arrival (DoA) but also capable to satisfy the most demanding applications in terms of power efficiency. Design considerations of the required operations performing the sound location are discussed and analysed in order to facilitate the elaboration of reconfigurable acoustic beamforming architectures. Performance strategies are proposed and evaluated based on the characteristics of the presented architecture. This power-efficient architecture is compared to a different architecture prioritizing performance in order to reveal the unavoidable design trade-offs
SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization
Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass's hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field
a clinical reappraisal
Funding Information: This research was supported by funding from the Bill & Melinda Gates Foundation to the New York Academy of Sciences (Grant number OPP1176128). We thank Megan Bourassa for her valuable comments to the manuscript and Rado Randriambovonjy, as well as Rija Rakotondralambo for their contribution (partial literature sorting). Publisher Copyright: © 2021 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of New York Academy of Sciences.Often thought to be a nutritional issue limited to low- and middle-income countries (LMICs), pediatric thiamine deficiency (PTD) is perceived as being eradicated or anecdotal in high-income countries (HICs). In HICs, classic beriberi cases in breastfed infants by thiamine-deficient mothers living in disadvantaged socioeconomic conditions are thought to be rare. This study aims to assess PTD in HICs in the 21st century. Literature searches were conducted to identify case reports of PTD observed in HICs and published between 2000 and 2020. The analyzed variables were age, country, underlying conditions, clinical manifestations of PTD, and response to thiamine supplementation. One hundred and ten articles were identified, totaling 389 PTD cases that were classified into four age groups: neonates, infants, children, and adolescents. Eleven categories of PTD-predisposing factors were identified, including genetic causes, lifestyle (diabetes, obesity, and excessive consumption of sweetened beverages), eating disorders, cancer, gastrointestinal disorders/surgeries, critical illness, and artificial nutrition. TD-associated hyperlactatemia and Wernicke encephalopathy were the most frequent clinical manifestations. The circumstances surrounding PTD in HICs differ from classic PTD observed in LMICs and this study delineates its mutiple predisposing factors. Further studies are required to estimate its magnitude. Awareness is of utmost importance in clinical practice.publishersversionpublishe
CABE : a cloud-based acoustic beamforming emulator for FPGA-based sound source localization
Microphone arrays are gaining in popularity thanks to the availability of low-cost microphones. Applications including sonar, binaural hearing aid devices, acoustic indoor localization techniques and speech recognition are proposed by several research groups and companies. In most of the available implementations, the microphones utilized are assumed to offer an ideal response in a given frequency domain. Several toolboxes and software can be used to obtain a theoretical response of a microphone array with a given beamforming algorithm. However, a tool facilitating the design of a microphone array taking into account the non-ideal characteristics could not be found. Moreover, generating packages facilitating the implementation on Field Programmable Gate Arrays has, to our knowledge, not been carried out yet. Visualizing the responses in 2D and 3D also poses an engineering challenge. To alleviate these shortcomings, a scalable Cloud-based Acoustic Beamforming Emulator (CABE) is proposed. The non-ideal characteristics of microphones are considered during the computations and results are validated with acoustic data captured from microphones. It is also possible to generate hardware description language packages containing delay tables facilitating the implementation of Delay-and-Sum beamformers in embedded hardware. Truncation error analysis can also be carried out for fixed-point signal processing. The effects of disabling a given group of microphones within the microphone array can also be calculated. Results and packages can be visualized with a dedicated client application. Users can create and configure several parameters of an emulation, including sound source placement, the shape of the microphone array and the required signal processing flow. Depending on the user configuration, 2D and 3D graphs showing the beamforming results, waterfall diagrams and performance metrics can be generated by the client application. The emulations are also validated with captured data from existing microphone arrays.</jats:p
Statistical distributions in the folding of elastic structures
The behaviour of elastic structures undergoing large deformations is the
result of the competition between confining conditions, self-avoidance and
elasticity. This combination of multiple phenomena creates a geometrical
frustration that leads to complex fold patterns. By studying the case of a rod
confined isotropically into a disk, we show that the emergence of the
complexity is associated with a well defined underlying statistical measure
that determines the energy distribution of sub-elements,``branches'', of the
rod. This result suggests that branches act as the ``microscopic'' degrees of
freedom laying the foundations for a statistical mechanical theory of this
athermal and amorphous system
A multimode SoC FPGA-based acoustic camera for wireless sensor networks
Acoustic cameras allow the visualization of sound sources using microphone arrays and beamforming techniques. The required computational power increases with the number of microphones in the array, the acoustic images resolution, and in particular, when targeting real-time. Such computational demand leads to a prohibitive power consumption for Wireless Sensor Networks (WSNs). In this paper, we present a SoC FPGA based architecture to perform a low-power and real-time accurate acoustic imaging for WSNs. The high computational demand is satisfied by performing the acoustic acquisition and the beamforming technique on the FPGA side. The hard-core processor enhances and compresses the acoustic images before transmitting to the WSN. As a result, the WSN manages the supported configuration modes of the acoustic camera. For instance, the resolution of the acoustic images can be adapted on-demand to satisfy the available network's BW while performing real-time acoustic imaging. Our performance measurements show that acoustic images are generated on the FPGA in real time with resolutions of 160x120 pixels operating at 32 frames-per-second. Nevertheless, higher resolutions are achievable thanks to the exploitation of the hard-core processor available in SoC FPGAs such as Zynq
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