Linear and Nonlinear Encoding Properties of an Identified Mechanoreceptor on the Fly wing Measured with Mechanical Noise Stimuli

The wing blades of most flies contain a small set of distal campaniform sensilla, mechanoreceptors that respond to deformations of the cuticle. This paper describes a method of analysis based upon mechanical noise stimuli which is used to quantify the encoding properties of one of these sensilla (the d-HCV cell) on the wing of the blowfly Calliphora vomitoria (L.). The neurone is modelled as two components, a linear filter that accounts for the frequency response and phase characteristics of the cell, followed by a static nonlinearity that limits the spike discharge to a narrow portion of the stimulus cycle. The model is successful in predicting the response of campaniform neurones to arbitrary stimuli, and provides a convenient method for quantifying the encoding properties of the sensilla. The d-HCV neurone is only broadly frequency tuned, but its maximal response near 150 Hz corresponds to the wingbeat frequency of Calliphora. In the range of frequencies likely to be encountered during flight, the d-HCV neurone fires a single phase-locked action potential for each stimulus cycle. The phase lag of the cell decreases linearly with increasing frequency such that the absolute delay between stimulus and response remains nearly constant. Thus, during flight the neurone is capable of firing one precisely timed action potential during each wingbeat, and might be used to modulate motor activity that requires afferent input on a cycle-by-cycle basis

Multi-time delay, multi-point Linear Stochastic Estimation of a cavity shear layer velocity from wall-pressure measurements

Multi-time-delay Linear Stochastic Estimation (MTD-LSE) technique is thoroughly described, focusing on its fundamental properties and potentialities. In the multi-time-delay ap- proach, the estimate of the temporal evolution of the velocity at a given location in the flow field is obtained from multiple past samples of the unconditional sources. The technique is applied to estimate the velocity in a cavity shear layer flow, based on wall-pressure measurements from multiple sensor

An Opportunistic Error Correction Layer for OFDM Systems

In this paper, we propose a novel cross layer scheme to lower power\ud consumption of ADCs in OFDM systems, which is based on resolution\ud adaptive ADCs and Fountain codes. The key part in the new proposed\ud system is that the dynamic range of ADCs can be reduced by\ud discarding the packets which are transmitted over 'bad' sub\ud carriers. Correspondingly, the power consumption in ADCs can be\ud reduced. Also, the new system does not process all the packets but\ud only processes surviving packets. This new error correction layer\ud does not require perfect channel knowledge, so it can be used in a\ud realistic system where the channel is estimated. With this new\ud approach, more than 70% of the energy consumption in the ADC can be\ud saved compared with the conventional IEEE 802.11a WLAN system under\ud the same channel conditions and throughput. The ADC in a receiver\ud can consume up to 50% of the total baseband energy. Moreover, to\ud reduce the overhead of Fountain codes, we apply message passing and\ud Gaussian elimination in the decoder. In this way, the overhead is\ud 3% for a small block size (i.e. 500 packets). Using both methods\ud results in an efficient system with low delay

Development and Demonstration of a TDOA-Based GNSS Interference Signal Localization System

Background theory, a reference design, and demonstration results are given for a Global Navigation Satellite System (GNSS) interference localization system comprising a distributed radio-frequency sensor network that simultaneously locates multiple interference sources by measuring their signals’ time difference of arrival (TDOA) between pairs of nodes in the network. The end-to-end solution offered here draws from previous work in single-emitter group delay estimation, very long baseline interferometry, subspace-based estimation, radar, and passive geolocation. Synchronization and automatic localization of sensor nodes is achieved through a tightly-coupled receiver architecture that enables phase-coherent and synchronous sampling of the interference signals and so-called reference signals which carry timing and positioning information. Signal and crosscorrelation models are developed and implemented in a simulator. Multiple-emitter subspace-based TDOA estimation techniques are developed as well as emitter identification and localization algorithms. Simulator performance is compared to the CramérRao lower bound for single-emitter TDOA precision. Results are given for a test exercise in which the system accurately locates emitters broadcasting in the amateur radio band in Austin, TX.Aerospace Engineering and Engineering Mechanic

Synesthesia: Detecting Screen Content via Remote Acoustic Side Channels

We show that subtle acoustic noises emanating from within computer screens can be used to detect the content displayed on the screens. This sound can be picked up by ordinary microphones built into webcams or screens, and is inadvertently transmitted to other parties, e.g., during a videoconference call or archived recordings. It can also be recorded by a smartphone or "smart speaker" placed on a desk next to the screen, or from as far as 10 meters away using a parabolic microphone. Empirically demonstrating various attack scenarios, we show how this channel can be used for real-time detection of on-screen text, or users' input into on-screen virtual keyboards. We also demonstrate how an attacker can analyze the audio received during video call (e.g., on Google Hangout) to infer whether the other side is browsing the web in lieu of watching the video call, and which web site is displayed on their screen