209 resultados para Acoustic devices


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Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

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Acoustic recordings of the environment provide an effective means to monitor bird species diversity. To facilitate exploration of acoustic recordings, we describe a content-based birdcall retrieval algorithm. A query birdcall is a region of spectrogram bounded by frequency and time. Retrieval depends on a similarity measure derived from the orientation and distribution of spectral ridges. The spectral ridge detection method caters for a broad range of birdcall structures. In this paper, we extend previous work by incorporating a spectrogram scaling step in order to improve the detection of spectral ridges. Compared to an existing approach based on MFCC features, our feature representation achieves better retrieval performance for multiple bird species in noisy recordings.

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Current mobile devices and streaming video services support high definition (HD) video, increasing expectation for more contents. HD video streaming generally requires large bandwidth, exerting pressures on existing networks. New generation of video compression codecs, such as VP9 and H.265/HEVC, are expected to be more effective for reducing bandwidth. Existing studies to measure the impact of its compression on users’ perceived quality have not been focused on mobile devices. Here we propose new Quality of Experience (QoE) models that consider both subjective and objective assessments of mobile video quality. We introduce novel predictors, such as the correlations between video resolution and size of coding unit, and achieve a high goodness-of-fit to the collected subjective assessment data (adjusted R-square >83%). The performance analysis shows that H.265 can potentially achieve 44% to 59% bit rate saving compared to H.264/AVC, slightly better than VP9 at 33% to 53%, depending on video content and resolution.

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In various embodiments, optoelectronic devices are described herein. The optoelectronic device may include an optoelectronic cell arranged so as to wrap around a central axis wherein the cell includes a first conductive layer, a semi-conductive layer disposed over and in electrical communication with the first conductive layer, and a second conductive layer disposed over and in electrical communication with the semi-conductive layer. In various embodiments, methods for making optoelectronic devices are described herein. The methods may include forming an optoelectronic cell while flat and wrapping the optoelectronic cell around a central axis. The optoelectronic devices may be photovoltaic devices. Alternatively, the optoelectronic devices may be organic light emitting diodes.

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We have designed, synthesized and utilized a new non-fullerene electron acceptor, 9,9′-(9,9-dioctyl-9H-fluorene-2,7-diyl)bis(2,7-dioctyl-4-(octylamino)benzo[lmn][3,8]phenanthroline-1,3,6,8(2H,7H)-tetraone) (B2), for use in solution-processable bulk-heterojunction devices. B2 is based on a central fluorene moiety, which was capped at both ends with an electron-accepting naphthalenediimide functionality. B2 exhibited excellent solubility (>30 mg mL−1 in chloroform), high thermal and photochemical stability, and appropriate energy levels for use with the classical polymer donor regioregular poly(3-hexylthiophene). A power conversion efficiency of 1.16 % was achieved for primitive bulk-heterojunction devices with a high fill factor of approximately 54 %.

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Diketopyrrolopyrole-naphthalene polymer (PDPP-TNT), a donor-acceptor co-polymer, has shown versatile behavior demonstrating high performances in organic field-effect transistors (OFETs) and organic photovoltaic (OPV) devices. In this paper we report investigation of charge carrier dynamics in PDPP-TNT, and [6,6]-phenyl C71 butyric acid methyl ester (PC71BM) bulk-heterojunction based inverted OPV devices using current density-voltage (J-V) characteristics, space charge limited current (SCLC) measurements, capacitance-voltage (C-V) characteristics, and impedance spectroscopy (IS). OPV devices in inverted architecture, ITO/ZnO/PDPP-TNT:PC71BM/MoO3/Ag, are processed and characterized at room conditions. The power conversion efficiency (PCE) of these devices are measured ∼3.8%, with reasonably good fill-factor 54.6%. The analysis of impedance spectra exhibits electron’s mobility ∼2 × 10−3 cm2V−1s−1, and lifetime in the range of 0.03-0.23 ms. SCLC measurements give hole mobility of 1.12 × 10−5 cm2V−1s−1, and electron mobility of 8.7 × 10−4 cm2V−1s−1.

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Mobile devices are very popular among tertiary student populations. This study looks at student use of hand-held mobile devices within the context of a first year programming unit. This research sought for ways in which an educational app on these devices could be successfully integrated into such a class's learning.

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Biventricular support with dual rotary ventricular assist devices (VADs) has been implemented clinically with restriction of the right VAD (RVAD) outflow cannula to artificially increase afterload and, therefore, operate within recommended design speed ranges. However, the low preload and high afterload sensitivity of these devices increase the susceptibility of suction events. Active control systems are prone to sensor drift or inaccurate inferred (sensor-less) data, therefore an alternative solution may be of benefit. This study presents the in vitro evaluation of a compliant outflow cannula designed to passively decrease the afterload sensitivity of rotary RVADs and minimize left-sided suction events. A one-way fluid-structure interaction model was initially used to produce a design with suitable flow dynamics and radial deformation. The resultant geometry was cast with different initial cross-sectional restrictions and concentrations of a softening diluent before evaluation in a mock circulation loop. Pulmonary vascular resistance (PVR) was increased from 50 dyne s/cm5 until left-sided suction events occurred with each compliant cannula and a rigid, 4.5 mm diameter outflow cannula for comparison. Early suction events (PVR ∼ 300 dyne s/cm5) were observed with the rigid outflow cannula. Addition of the compliant section with an initial 3 mm diameter restriction and 10% diluent expanded the outflow restriction as PVR increased, thus increasing RVAD flow rate and preventing left-sided suction events at PVR levels beyond 1000 dyne s/cm5. Therefore, the compliant, restricted outflow cannula provided a passive control system to assist in the prevention of suction events with rotary biventricular support while maintaining pump speeds within normal ranges of operation.

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Acoustic recordings play an increasingly important role in monitoring terrestrial environments. However, due to rapid advances in technology, ecologists are accumulating more audio than they can listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings by calculating acoustic indices. These are statistics which describe the temporal-spectral distribution of acoustic energy and reflect content of ecological interest. We combine spectral indices to produce false-color spectrogram images. These not only reveal acoustic content but also facilitate navigation. An additional analytic challenge is to find appropriate descriptors to summarize the content of 24-hour recordings, so that it becomes possible to monitor long-term changes in the acoustic environment at a single location and to compare the acoustic environments of different locations. We describe a 24-hour ‘acoustic-fingerprint’ which shows some preliminary promise.

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Bird species richness survey is one of the most intriguing ecological topics for evaluating environmental health. Here, bird species richness denotes the number of unique bird species in a particular area. Factors affecting the investigation of bird species richness include weather, observation bias, and most importantly, the prohibitive costs of conducting surveys at large spatiotemporal scales. Thanks to advances in recording techniques, these problems have been alleviated by deploying sensors for acoustic data collection. Although automated detection techniques have been introduced to identify various bird species, the innate complexity of bird vocalizations, the background noise present in the recording and the escalating volumes of acoustic data pose a challenging task on determination of bird species richness. In this paper we proposed a two-step computer-assisted sampling approach for determining bird species richness in one-day acoustic data. First, a classification model is built based on acoustic indices for filtering out minutes that contain few bird species. Then the classified bird minutes are ordered by an acoustic index and the redundant temporal minutes are removed from the ranked minute sequence. The experimental results show that our method is more efficient in directing experts for determination of bird species compared with the previous methods.

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This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.

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Acoustic classification of anurans (frogs) has received increasing attention for its promising application in biological and environment studies. In this study, a novel feature extraction method for frog call classification is presented based on the analysis of spectrograms. The frog calls are first automatically segmented into syllables. Then, spectral peak tracks are extracted to separate desired signal (frog calls) from background noise. The spectral peak tracks are used to extract various syllable features, including: syllable duration, dominant frequency, oscillation rate, frequency modulation, and energy modulation. Finally, a k-nearest neighbor classifier is used for classifying frog calls based on the results of principal component analysis. The experiment results show that syllable features can achieve an average classification accuracy of 90.5% which outperforms Mel-frequency cepstral coefficients features (79.0%).

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Frog protection has become increasingly essential due to the rapid decline of its biodiversity. Therefore, it is valuable to develop new methods for studying this biodiversity. In this paper, a novel feature extraction method is proposed based on perceptual wavelet packet decomposition for classifying frog calls in noisy environments. Pre-processing and syllable segmentation are first applied to the frog call. Then, a spectral peak track is extracted from each syllable if possible. Track duration, dominant frequency and oscillation rate are directly extracted from the track. With k-means clustering algorithm, the calculated dominant frequency of all frog species is clustered into k parts, which produce a frequency scale for wavelet packet decomposition. Based on the adaptive frequency scale, wavelet packet decomposition is applied to the frog calls. Using the wavelet packet decomposition coefficients, a new feature set named perceptual wavelet packet decomposition sub-band cepstral coefficients is extracted. Finally, a k-nearest neighbour (k-NN) classifier is used for the classification. The experiment results show that the proposed features can achieve an average classification accuracy of 97.45% which outperforms syllable features (86.87%) and Mel-frequency cepstral coefficients (MFCCs) feature (90.80%).

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Over past few decades, frog species have been experiencing dramatic decline around the world. The reason for this decline includes habitat loss, invasive species, climate change and so on. To better know the status of frog species, classifying frogs has become increasingly important. In this study, acoustic features are investigated for multi-level classification of Australian frogs: family, genus and species, including three families, eleven genera and eighty five species which are collected from Queensland, Australia. For each frog species, six instances are selected from which ten acoustic features are calculated. Then, the multicollinearity between ten features are studied for selecting non-correlated features for subsequent analysis. A decision tree (DT) classifier is used to visually and explicitly determine which acoustic features are relatively important for classifying family, which for genus, and which for species. Finally, a weighted support vector machines (SVMs) classifier is used for the multi- level classification with three most important acoustic features respectively. Our experiment results indicate that using different acoustic feature sets can successfully classify frogs at different levels and the average classification accuracy can be up to 85.6%, 86.1% and 56.2% for family, genus and species respectively.

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Electric-motored personal mobility devices (PMDs) are appearing on Australian roads. While legal to import and own, their use is typically illegal for adult riders within the road transport system. However, these devices could provide an answer to traffic congestion by getting people out of cars for short trips (“first-and-last mile” travel). City of Ryde council, Macquarie University, and Transport for NSW examined PMD use within the road transport system. Stage 1 of the project examined PMD use within a controlled pedestrian environment on the Macquarie University campus. Three PMD categories were used: one-wheelers (an electric unicycle, the Solowheel); two-wheelers (an electric scooter, the Egret); and three-wheelers (the Qugo). The two-wheeled PMD was most effective in terms of flexibility. In contrast, the three-wheeled PMD was most effective in terms of speed. One-wheeled PMD riders were very satisfied with their device, especially at speed, but significant training and practice was required. Two-wheeled PMD riders had less difficulty navigating through pedestrian precincts and favoured the manoeuvrability of the device as the relative narrowness of the two-wheeled PMD made it easier to use on a diversity of path widths. The usability of all PMDs was compromised by the weight of the devices, difficulties in ascending steeper gradients, portability, and parking. This was a limited trial, with a small number of participants and within a unique environment. However, agreement has been reached for a Stage 2 extension into the Macquarie Park business precinct for further real-world trials within a fully functional road transport system.