5,480 research outputs found
Orbital Angular Momentum Waves: Generation, Detection and Emerging Applications
Orbital angular momentum (OAM) has aroused a widespread interest in many
fields, especially in telecommunications due to its potential for unleashing
new capacity in the severely congested spectrum of commercial communication
systems. Beams carrying OAM have a helical phase front and a field strength
with a singularity along the axial center, which can be used for information
transmission, imaging and particle manipulation. The number of orthogonal OAM
modes in a single beam is theoretically infinite and each mode is an element of
a complete orthogonal basis that can be employed for multiplexing different
signals, thus greatly improving the spectrum efficiency. In this paper, we
comprehensively summarize and compare the methods for generation and detection
of optical OAM, radio OAM and acoustic OAM. Then, we represent the applications
and technical challenges of OAM in communications, including free-space optical
communications, optical fiber communications, radio communications and acoustic
communications. To complete our survey, we also discuss the state of art of
particle manipulation and target imaging with OAM beams
Deep Room Recognition Using Inaudible Echos
Recent years have seen the increasing need of location awareness by mobile
applications. This paper presents a room-level indoor localization approach
based on the measured room's echos in response to a two-millisecond single-tone
inaudible chirp emitted by a smartphone's loudspeaker. Different from other
acoustics-based room recognition systems that record full-spectrum audio for up
to ten seconds, our approach records audio in a narrow inaudible band for 0.1
seconds only to preserve the user's privacy. However, the short-time and
narrowband audio signal carries limited information about the room's
characteristics, presenting challenges to accurate room recognition. This paper
applies deep learning to effectively capture the subtle fingerprints in the
rooms' acoustic responses. Our extensive experiments show that a two-layer
convolutional neural network fed with the spectrogram of the inaudible echos
achieve the best performance, compared with alternative designs using other raw
data formats and deep models. Based on this result, we design a RoomRecognize
cloud service and its mobile client library that enable the mobile application
developers to readily implement the room recognition functionality without
resorting to any existing infrastructures and add-on hardware.
Extensive evaluation shows that RoomRecognize achieves 99.7%, 97.7%, 99%, and
89% accuracy in differentiating 22 and 50 residential/office rooms, 19 spots in
a quiet museum, and 15 spots in a crowded museum, respectively. Compared with
the state-of-the-art approaches based on support vector machine, RoomRecognize
significantly improves the Pareto frontier of recognition accuracy versus
robustness against interfering sounds (e.g., ambient music).Comment: 29 page
In situ sensors for measurements in the global trosposphere
Current techniques available for the in situ measurement of ambient trace gas species, particulate composition, and particulate size distribution are reviewed. The operational specifications of the various techniques are described. Most of the techniques described are those that have been used in airborne applications or show promise of being adaptable to airborne applications. Some of the instruments described are specialty items that are not commercially-available. In situ measurement techniques for several meteorological parameters important in the study of the distribution and transport of ambient air pollutants are discussed. Some remote measurement techniques for meteorological parameters are also discussed. State-of-the-art measurement capabilities are compared with a list of capabilities and specifications desired by NASA for ambient measurements in the global troposphere
Non-linear echo cancellation - a Bayesian approach
Echo cancellation literature is reviewed, then a Bayesian model is introduced and it is shown how how it can be used to model and fit nonlinear channels. An algorithm for cancellation of echo over a nonlinear channel is developed and tested. It is shown that this nonlinear algorithm converges for both linear and nonlinear channels and is superior to linear echo cancellation for canceling an echo through a nonlinear echo-path channel
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Mobile Audiovisual Terminal: System Design and Subjective Testing in DECT and UMTS networks
It is anticipated that there will shortly be a requirement
for multimedia terminals that operate via mobile
communications systems. This paper presents a functional specification
for such a terminal operating at 32 kb/s in a digital
European cordless telecommunications (DECT) and universal
mobile telecommunications system (UMTS) radio network. A terminal
has been built, based on a PC with digital signal processor
(DSP) boards for audio and video coding and decoding. Speech
coding is by a phonetically driven code-excited linear prediction
(CELP) speech coder and video coding by a block-oriented hybrid
discrete cosine transform (DCT) coder. Separate channel coding
is provided for the audio and video data. The paper describes the
techniques used for audio and video coding, channel coding, and
synchronization. Methods of subjective testing in a DECT network
and in a UMTS network are also described. These consisted of
subjective tests of first impressions of the mobile audio–visual
terminal (MAVT) quality, interactive tests, and the completion
of an exit questionnaire. The test results showed that the quality
of the audio was sufficiently good for comprehension and the
video was sufficiently good for following and repeating simple
mechanical tasks. However, the quality of the MAVT was not
good enough for general use where high-quality audio and video
was needed, especially when transmission was in a noisy radio
environment
Interference cancellation and network coding for underwater communication systems
It is widely believed that wider access to the aquatic environment will enhance human knowledge and understanding of the world's oceans which constitute the major part of our planet. Hence, the current development of underwater sensing and communication systems will produce scientific, economic and social benefits. New applications will be enabled, such as deeper ocean observation, environmental monitoring, surveying or search and rescue missions. Underwater communications differ from terrestrial communications due to the unpredictable and complex ocean conditions, relying on acoustic waves which are affected by many factors like large propagation losses, long latency, limited bandwidth capacity and channel stability, posing great challenges for reliable data transport in this kind of networks. The aim of this project is to design a future underwater acoustic communication system for dense traffic situations investigating the possibility of Medium Access with Interference Cancellation and Network Coding. The main efforts focus on reliability, low energy consumption, storage capacity, throughput and scalabilit
Fingerprinting Smart Devices Through Embedded Acoustic Components
The widespread use of smart devices gives rise to both security and privacy
concerns. Fingerprinting smart devices can assist in authenticating physical
devices, but it can also jeopardize privacy by allowing remote identification
without user awareness. We propose a novel fingerprinting approach that uses
the microphones and speakers of smart phones to uniquely identify an individual
device. During fabrication, subtle imperfections arise in device microphones
and speakers which induce anomalies in produced and received sounds. We exploit
this observation to fingerprint smart devices through playback and recording of
audio samples. We use audio-metric tools to analyze and explore different
acoustic features and analyze their ability to successfully fingerprint smart
devices. Our experiments show that it is even possible to fingerprint devices
that have the same vendor and model; we were able to accurately distinguish
over 93% of all recorded audio clips from 15 different units of the same model.
Our study identifies the prominent acoustic features capable of fingerprinting
devices with high success rate and examines the effect of background noise and
other variables on fingerprinting accuracy
Automated tracking of the Florida manatee (Trichechus manatus)
The electronic, physical, biological and environmental factors involved in the automated remote tracking of the Florida manatee (Trichechus manatus) are identified. The current status of the manatee as an endangered species is provided. Brief descriptions of existing tracking and position locating systems are presented to identify the state of the art in these fields. An analysis of energy media is conducted to identify those with the highest probability of success for this application. Logistic questions such as the means of attachment and position of any equipment to be placed on the manatee are also investigated. Power sources and manateeborne electronics encapsulation techniques are studied and the results of a compter generated DF network analysis are summarized
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