989 resultados para Acoustic event classification


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The Alliance for Coastal Technologies (ACT) convened a workshop, sponsored by the Hawaii-Pacific and Alaska Regional Partners, entitled Underwater Passive Acoustic Monitoring for Remote Regions at the Hawaii Institute of Marine Biology from February 7-9, 2007. The workshop was designed to summarize existing passive acoustic technologies and their uses, as well as to make strategic recommendations for future development and collaborative programs that use passive acoustic tools for scientific investigation and resource management. The workshop was attended by 29 people representing three sectors: research scientists, resource managers, and technology developers. The majority of passive acoustic tools are being developed by individual scientists for specific applications and few tools are available commercially. Most scientists are developing hydrophone-based systems to listen for species-specific information on fish or cetaceans; a few scientists are listening for biological indicators of ecosystem health. Resource managers are interested in passive acoustics primarily for vessel detection in remote protected areas and secondarily to obtain biological and ecological information. The military has been monitoring with hydrophones for decades;however, data and signal processing software has not been readily available to the scientific community, and future collaboration is greatly needed. The challenges that impede future development of passive acoustics are surmountable with greater collaboration. Hardware exists and is accessible; the limits are in the software and in the interpretation of sounds and their correlation with ecological events. Collaboration with the military and the private companies it contracts will assist scientists and managers with obtaining and developing software and data analysis tools. Collaborative proposals among scientists to receive larger pools of money for exploratory acoustic science will further develop the ability to correlate noise with ecological activities. The existing technologies and data analysis are adequate to meet resource managers' needs for vessel detection. However, collaboration is needed among resource managers to prepare large-scale programs that include centralized processing in an effort to address the lack of local capacity within management agencies to analyze and interpret the data. Workshop participants suggested that ACT might facilitate such collaborations through its website and by providing recommendations to key agencies and programs, such as DOD, NOAA, and I00s. There is a need to standardize data formats and archive acoustic environmental data at the national and international levels. Specifically, there is a need for local training and primers for public education, as well as by pilot demonstration projects, perhaps in conjunction with National Marine Sanctuaries. Passive acoustic technologies should be implemented immediately to address vessel monitoring needs. Ecological and health monitoring applications should be developed as vessel monitoring programs provide additional data and opportunities for more exploratory research. Passive acoustic monitoring should also be correlated with water quality monitoring to ease integration into long-term monitoring programs, such as the ocean observing systems. [PDF contains 52 pages]

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The Alliance for Coastal Technologies (ACT) Workshop on Optical Remote Sensing of Coastal Habitats was convened January 9-11, 2006 at Moss Landing Marine Laboratories in Moss Landing, California, sponsored by the ACT West Coast regional partnership comprised of the Moss Landing Marine Laboratories (MLML) and the Monterey Bay Aquarium Research Institute (MBARI). The "Optical Remote Sensing of Coastal Habitats" (ORS) Workshop completes ACT'S Remote Sensing Technology series by building upon the success of ACT'S West Coast Regional Partner Workshop "Acoustic Remote Sensing Technologies for Coastal Imaging and Resource Assessment" (ACT 04-07). Drs. Paul Bissett of the Florida Environmental Research Institute (FERI) and Scott McClean of Satlantic, Inc. were the ORS workshop co-chairs. Invited participants were selected to provide a uniform representation of the academic researchers, private sector product developers, and existing and potential data product users from the resource management community to enable development of broad consensus opinions on the role of ORS technologies in coastal resource assessment and management. The workshop was organized to examine the current state of multi- and hyper-spectral imaging technologies with the intent to assess the current limits on their routine application for habitat classification and resource monitoring of coastal watersheds, nearshore shallow water environments, and adjacent optically deep waters. Breakout discussions focused on the capabilities, advantages ,and limitations of the different technologies (e.g., spectral & spatial resolution), as well as practical issues related to instrument and platform availability, reliability, hardware, software, and technical skill levels required to exploit the data products generated by these instruments. Specifically, the participants were charged to address the following: (1) Identify the types of ORS data products currently used for coastal resource assessment and how they can assist coastal managers in fulfilling their regulatory and management responsibilities; (2) Identify barriers and challenges to the application of ORS technologies in management and research activities; (3) Recommend a series of community actions to overcome identified barriers and challenges. Plenary presentations by Drs. Curtiss 0. Davis (Oregon State University) and Stephan Lataille (ITRES Research, Ltd.) provided background summaries on the varieties of ORS technologies available, deployment platform options, and tradeoffs for application of ORS data products with specific applications to the assessment of coastal zone water quality and habitat characterization. Dr. Jim Aiken (CASIX) described how multiscale ground-truth measurements were essential for developing robust assessment of modeled biogeochemical interpretations derived from optically based earth observation data sets. While continuing improvements in sensor spectral resolution, signal to noise and dynamic range coupled with sensor-integrated GPS, improved processing algorithms for georectification, and atmospheric correction have made ORS data products invaluable synoptic tools for oceanographic research, their adoption as management tools has lagged. Seth Blitch (Apalachicola National Estuarine Research Reserve) described the obvious needs for, yet substantial challenges hindering the adoption of advanced spectroscopic imaging data products to supplement the current dominance of digital ortho-quad imagery by the resource management community, especially when they impinge on regulatory issues. (pdf contains 32 pages)

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An approach which combines direct numerical simulation (DNS) with the Lighthill acoustic analogy theory is used to study the potential noise sources during the transition process of a Mach 2.25 flat plate boundary layer. The quadrupole sound sources due to the flow fluctuations and the dipole sound sources due to the fluctuating surface stress are obtained. Numerical results suggest that formation of the high shear layers leads to a dramatic amplification of amplitude of the fluctuating quadrupole sound sources. Compared with the quadrupole sound source, the energy of dipole sound source is concentrated in the relatively low frequency range.

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Composite materials with interpenetrating network structures usually exhibit unexpected merit due to the cooperative interaction. Locally resonant phononic crystals (LRPC) exhibit excellent sound attenuation performance based on a periodical arrangement of sound wave scatters. Inspired by the interpenetrating network structure and the LRPC concept, we develop a locally network anechoic coating (LNAC) that can achieve a wide band of underwater strong acoustic absorption. The experimental results show that the LNAC possesses an excellent underwater acoustic absorbing capacity in a wide frequency range. Moreover, in order to investigate the impact of the interpenetrating network structure, we fabricate a faultage structure sample and the network is disconnected by hard polyurethane (PU). The experimental comparison between the LNAC and the faultage structure sample shows that the interpenetrating network structure of the LNAC plays an important role in achieving a wide band strong acoustic absorption.

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To meet the demand of modern acoustic absorbing material for which acoustic absorbing frequency region can be readily tailored, we introduced woodpile structure into locally resonant phononic crystal (LRPC) and fabricated an underwater acoustic absorbing material, which is called locally resonant phononic woodpile (LRPW). Experimental results show that LRPW has a strong capability of absorbing sound in a wide frequency range. Further theoretical research revealed that LRPC units and woodpile structure in LRPW play an important role in realization of wide band underwater strong acoustic absorption.

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[EN] In this study, we explore native and non-native syntactic processing, paying special attention to the language distance factor. To this end, we compared how native speakers of Basque and highly proficient non-native speakers of Basque who are native speakers of Spanish process certain core aspects of Basque syntax. Our results suggest that differences in native versus non-native language processing strongly correlate with language distance: native/non-native processing differences obtain if a syntactic parameter of the non-native grammar diverges from the native grammar. Otherwise, non-native processing will approximate native processing as levels of proficiency increase. We focus on three syntactic parameters: (i) the head parameter, (ii) argument alignment (ergative/accusative), and (iii) verb agreement. The first two diverge in Basque and Spanish, but the third is the same in both languages. Our results reveal that native and non-native processing differs for the diverging syntactic parameters, but not for the convergent one. These findings indicate that language distance has a significant impact in non-native language processing.

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A 32.1 W laser-diode-stack pumped acoustic-optic Q-switched Nd:YVO4 slab laser with hybrid resonator at 1064 nm was demonstrated with the pumping power of 112 W and repetition rate of 40 kHz, the pulse duration was 32.47 ns. The slope efficiency and optical-to-optical efficiency were 37 and 28.7%, respectively. At the repetition rate of 20 kHz and pumping power of 90 W, the average output power and pulse duration were 20.4 W and 20.43 ns, respectively. With the pumping power of 112 W, the beam quality M-2 factors in CW operation were measured to be 1.3 in stable direction and 1.6 in unstable direction.

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Humans are able of distinguishing more than 5000 visual categories even in complex environments using a variety of different visual systems all working in tandem. We seem to be capable of distinguishing thousands of different odors as well. In the machine learning community, many commonly used multi-class classifiers do not scale well to such large numbers of categories. This thesis demonstrates a method of automatically creating application-specific taxonomies to aid in scaling classification algorithms to more than 100 cate- gories using both visual and olfactory data. The visual data consists of images collected online and pollen slides scanned under a microscope. The olfactory data was acquired by constructing a small portable sniffing apparatus which draws air over 10 carbon black polymer composite sensors. We investigate performance when classifying 256 visual categories, 8 or more species of pollen and 130 olfactory categories sampled from common household items and a standardized scratch-and-sniff test. Taxonomies are employed in a divide-and-conquer classification framework which improves classification time while allowing the end user to trade performance for specificity as needed. Before classification can even take place, the pollen counter and electronic nose must filter out a high volume of background “clutter” to detect the categories of interest. In the case of pollen this is done with an efficient cascade of classifiers that rule out most non-pollen before invoking slower multi-class classifiers. In the case of the electronic nose, much of the extraneous noise encountered in outdoor environments can be filtered using a sniffing strategy which preferentially samples the visensor response at frequencies that are relatively immune to background contributions from ambient water vapor. This combination of efficient background rejection with scalable classification algorithms is tested in detail for three separate projects: 1) the Caltech-256 Image Dataset, 2) the Caltech Automated Pollen Identification and Counting System (CAPICS) and 3) a portable electronic nose specially constructed for outdoor use.

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This thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time. Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks. This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events. In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.