Model-based detection of synthetic bat echolocation calls using an energy threshold detector for initialization

Detection of echolocation calls is fundamental to quantitative analysis of bat acoustic signals. Automated methods of detection reduce the subjectivity of hand labeling of calls and speed up the detection process in an accurate and repeatable manner. A model-based detector was initialized using a baseline energy threshold detector, removing the need for hand labels to train the model, and shown to be superior to the baseline detector using synthetic calls in two experiments: (1) an artificial environment and (2) a field playback setting. Synthetic calls using a piecewise exponential frequency modulation function from five hypothetical species were employed to control the signal-to-noise ratio (SNR) in each experiment and to provide an absolute ground truth to judge detector performance. The model-based detector outperformed the baseline detector by 2.5 dB SNR in the artificial environment and 1.5 dB SNR in the field playback setting. Atmospheric absorption was measured for the synthetic calls, and 1.5 dB increased the effective detection radius by between 1 and 7 m depending on species. The results demonstrate that hand labels are not necessary for training detection models and that model-based detectors significantly increase the range of detection for a recording system.     

Is the structure of bat echolocation calls an adaptation to the mammalian hearing system?

A common feature of most bat echolocation calls is their hyperbolalike frequency modulation. It is proposed that these calls evolved as an adaptation to the filters in the peripheral hearing system. From an analysis of 420 echolocation sounds of Eptesicus fuscus, the bandwidths of filters giving a minimal error of time-delay estimation are predicted; these could be compared to neurophysiological findings.     

非高斯水声瞬态信号Power-Law检测

根据水声瞬态信号检测的特点,研究了基于高阶谱的power-law算法及其在水声瞬态信号检测中的应用。模拟试验和实际数据处理结果表明基于高阶谱的power-law瞬态信号检测器在检测非高斯瞬态信号方面优于传统的基于DFT的power-law检测器,有较好的应用前景。     

14 MeV neutron detection characteristics using Intercast detector

Neutron detection with a stack of two detector foils of CR-39 (intercast) was studied. A comparison between the experimental results (exposure to 14.8 MeV neutrons) and the results of a computer simulation was performed. Emphasis was given to the detection of particles—products of the break-up reaction of the ¹²C nucleus—and to heavier recoil nuclei. The detectors were chemically etched and analysed with an automatic counting system. All detector surfaces were analysed, and the coincidence tracks produced by the same particles on detector surfaces in contact were determined. These tracks facilitate characterization of the type and energy of the recoil nuclei. Further separation was made on the basis of the distribution of size and darkness of the tracks.     

Acoustic detection of North Atlantic right whale contact calls using spectrogram-based statistics

This paper considers the problem of detection of contact calls produced by the critically endangered North Atlantic right whale, Eubalaena glacialis. To reduce computational time, the class of acceptable detectors is constrained by the detectors implemented as a bank of two-dimensional linear FIR filters and using the data spectrogram as the input. The closed form representations for the detectors are derived and the detection performance is compared with that of the generalized likelihood ratio test (GLRT) detector. The test results demonstrate that in the presence of impulsive noise, the spectrogram-based detector using the French hat wavelet as the filter kernel outperforms the GLRT detector and decreases computational time by a factor of 6.     

Model-based detector and extraction of weak signal frequencies from chaotic data

Detecting a weak signal from chaotic time series is of general interest in science and engineering. In this work we introduce and investigate a signal detection algorithm for which chaos theory, nonlinear dynamical reconstruction techniques, neural networks, and time-frequency analysis are put together in a synergistic manner. By applying the scheme to numerical simulation and different experimental measurement data sets (Henon map, chaotic circuit, and NH(3) laser data sets), we demonstrate that weak signals hidden beneath the noise floor can be detected by using a model-based detector. Particularly, the signal frequencies can be extracted accurately in the time-frequency space. By comparing the model-based method with the standard denoising wavelet technique as well as supervised principal components analysis detector, we further show that the nonlinear dynamics and neural network-based approach performs better in extracting frequencies of weak signals hidden in chaotic time series.     

Acoustic detection of North Atlantic right whale contact calls using the generalized likelihood ratio test

This paper addresses the problem of passive acoustic detection of contact calls produced by the highly endangered North Atlantic right whale Eubalaena glacialis. The proposed solution is based on using a generalized likelihood ratio test detector of polynomial-phase signals with unknown amplitude and polynomial coefficients observed in the presence of locally stationary Gaussian noise. The closed form representation for a minimal sufficient statistic is derived and a realizable detection scheme is developed. The receiver operation characteristic curves are calculated using empirical data recordings containing known right whale calls. The curves demonstrate that the proposed detector provides superior detection performance as compared with other known detection techniques for northern right whale contact calls.     

Model-based analysis of dispersion curves using chirplets

Time-frequency representations, like the spectrogram or the scalogram, are widely used to characterize dispersive waves. The resulting energy distributions, however, suffer from the uncertainty principle, which complicates the allocation of energy to individual propagation modes (especially when the dispersion curves of these modes are close to each other in the time-frequency domain). This research applies the chirplet as a tool to analyze dispersive wave signals based on a dispersion model. The chirplet transform, a generalization of both the wavelet and the short-time Fourier transform, enables the extraction of components of a signal with a particular instantaneous frequency and group delay. An adaptive algorithm identifies frequency regions for which quantitative statements can be made about an individual mode's energy, and employs chirplets (locally adapted to a dispersion curve model) to extract the (proportional) energy distribution of that single mode from a multimode dispersive wave signal. The effectiveness of this algorithm is demonstrated on a multimode synthetic Lamb wave signal for which the ground-truth energy distribution is known for each mode. Finally, the robustness of this algorithm is demonstrated on real, experimentally measured Lamb wave signals by an adaption of a correlation technique developed in previous research.     

Sensitive and automated detection of iron-oxide-labeled cells using phase image cross-correlation analysis

Superparamagnetic iron oxide (SPIO) nanoparticles are increasingly being used to noninvasively track cells, target specific molecules and monitor gene expression in vivo. Contrast changes that are subtle relative to intrinsic sources of contrast present a significant detection challenge. Here, we describe a postprocessing algorithm, called Phase map cross-correlation Detection and Quantification (PDQ), with the purpose of automating identification and quantification of localized accumulations of SPIO agents. The method is designed to sacrifice little flexibility - it works on previously acquired data and allows the use of conventional high-SNR pulse sequences with no extra scan time. We first investigated the theoretical detection limits of PDQ using a simulated dipole field. This method was then applied to three-dimensional (3D) MRI data sets of agarose gel containing isolated dipoles and ex vivo transplanted allogenic rat hearts infiltrated by numerous iron-oxide-labeled macrophages as a result of organ rejection. A simulated dipole field showed this method to be robust in very low signal-to-noise ratio images. Analysis of agarose gel and allogenic rat heart shows that this method can automatically identify and count dipoles while visualizing their biodistribution in 3D renderings. In the heart, this information was used to calculate a quantitative index that may indicate its degree of cellular infiltration.     

The study of the target emissivity and detection using a superconducting detector in the submillimeter wave region

This paper researches mainly the radiation characteristics of the target and detecting techniques by superconducting detector in the submillimeter wave(SMMW) region. The calculation of transition wavelength(TW) between Planck and Rayleigh-Jeans is given out. The experiment of detecting different targets is finished by use of superconducting detector possessing high performances. Through the experiments in paper we can select and determine the wave bands of SMMW detecting and imaging system. The many novel theoretical analyses and experimental results are expressed in Figs and tables of the paper. Finally, a part of calculating results and experimental datum detected by a superconducting detector in SMMW regions are given in this paper.     

使用四象限探测器测量微小位移

四象限探测器的工作原理是光生伏特效应,通过4个象限电势的变化可算出光源的位移.使用四象限探测器测量了光源横向和纵向的位移,分析了实验误差的来源并给出了修正方法.实验结果表明,四象限探测器测量位移具有较高的测量精度和较短的时间响应,纵向测量的灵敏度比横向测量的灵敏度低.     

Elliptic flow studies using the CMS detector

The azimuthal anisotropy of charged particles in heavy ion collisions is an important probe of quark-gluon plasma evolution at early stages. The nuclear reaction plane can be determined independently by different detector subsystems and using different analysis methods. This paper reports the capability of the CMS detector at the LHC to reconstruct the reaction plane of the collision and to me asure elliptic flow with calorimetry and a tracking system. The analysis is based on a full CMS detector simulation of Pb + Pb events with the HYDJET event generator.     

Design of a wide-field target detection and tracking system using the segmented planar imaging detector for electro-optical reconnaissance

Detecting and tracking multiple targets simultaneously for space-based surveillance requires multiple cameras,which leads to a large system volume and weight. To address this problem, we propose a wide-field detection and tracking system using the segmented planar imaging detector for electro-optical reconnaissance. This study realizes two operating modes by changing the working paired lenslets and corresponding waveguide arrays: a detection mode and a tracking mode. A model system was simulated and evaluated using the peak signal-to-noise ratio method. The simulation results indicate that the detection and tracking system can realize wide-field detection and narrow-field, multi-target, high-resolution tracking without moving parts.     

The energy ratio mapping algorithm: a tool to improve the energy-based detection of odontocete echolocation clicks

The energy ratio mapping algorithm (ERMA) was developed to improve the performance of energy-based detection of odontocete echolocation clicks, especially for application in environments with limited computational power and energy such as acoustic gliders. ERMA systematically evaluates many frequency bands for energy ratio-based detection of echolocation clicks produced by a target species in the presence of the species mix in a given geographic area. To evaluate the performance of ERMA, a Teager-Kaiser energy operator was applied to the series of energy ratios as derived by ERMA. A noise-adaptive threshold was then applied to the Teager-Kaiser function to identify clicks in data sets. The method was tested for detecting clicks of Blainville's beaked whales while rejecting echolocation clicks of Risso's dolphins and pilot whales. Results showed that the ERMA-based detector correctly identified 81.6% of the beaked whale clicks in an extended evaluation data set. Average false-positive detection rate was 6.3% (3.4% for Risso's dolphins and 2.9% for pilot whales).     

Fast two‐dimensional detection for X‐ray photon correlation spectroscopy using the PILATUS detector

The first X‐ray photon correlation spectroscopy experiments using the fast single‐photon‐counting detector PILATUS (Paul Scherrer Institut, Switzerland) have been performed. The short readout time of this detector permits access to intensity autocorrelation functions describing dynamics in the millisecond range that are difficult to access with charge‐coupled device detectors with typical readout times of several seconds. Showing no readout noise the PILATUS detector enables measurements of samples that either display fast dynamics or possess only low scattering power with an unprecedented signal‐to‐noise ratio.     

Industrial resin inspection for display production using automated fluid-inspection based on multimodal optical detection techniques

The large-scale liquid-crystal display (LCD) industry requires an accurate inspection system for identifying defects, as the LCD quality can be drastically degraded because of defects. In particular, the refractive index of LCD panels can be changed by internal micrometer-range substances, which form as a result of defectiveness and the insufficient solidification of industrial liquid resins. Intrinsically, the defect inspection of the raw materials must be performed prior to the LCD manufacturing process. Thus, optical coherence tomography (OCT) based automated fluid-inspection (AFI) methodology was introduced to demarcate and enumerate the defects in industrial liquid resins and the final product (LCD smartphone). The accuracy of the method was enhanced by implementing an intensity-detection algorithm. Subsequently, the optimal solidification rates of liquid resins were investigated using a fluorescence sensor-based ultraviolet hardening method to prevent the formation of defects between the internal layers of the LCD panel. Therefore, AFI can be implemented as an effective and cost-saving method in the smartphone industry for improving the quality of the final product.     

Alpha particle detection by the diacel solid state track detector

The characteristics of diacel plastic track detector are investigated for the detection of alpha particles. The influence of different radiations viz. electrons, gamma rays, ultraviolet rays, infrared rays and neutrons on the detector has also been studied.     

The influence of flight speed on the ranging performance of bats using frequency modulated echolocation pulses

Many species of bat use ultrasonic frequency modulated (FM) pulses to measure the distance to objects by timing the emission and reception of each pulse. Echolocation is mainly used in flight. Since the flight speed of bats often exceeds 1% of the speed of sound, Doppler effects will lead to compression of the time between emission and reception as well as an elevation of the echo frequencies, resulting in a distortion of the perceived range. This paper describes the consequences of these Doppler effects on the ranging performance of bats using different pulse designs. The consequences of Doppler effects on ranging performance described in this paper assume bats to have a very accurate ranging resolution, which is feasible with a filterbank receiver. By modeling two receiver types, it was first established that the effects of Doppler compression are virtually independent of the receiver type. Then, used a cross-correlation model was used to investigate the effect of flight speed on Doppler tolerance and range-Doppler coupling separately. This paper further shows how pulse duration, bandwidth, function type, and harmonics influence Doppler tolerance and range-Doppler coupling. The influence of each signal parameter is illustrated using calls of several bat species. It is argued that range-Doppler coupling is a significant source of error in bat echolocation, and various strategies bats could employ to deal with this problem, including the use of range rate information are discussed.     

Classification of Risso's and Pacific white-sided dolphins using spectral properties of echolocation clicks

The spectral and temporal properties of echolocation clicks and the use of clicks for species classification are investigated for five species of free-ranging dolphins found offshore of southern California: short-beaked common (Delphinus delphis), long-beaked common (D. capensis), Risso's (Grampus griseus), Pacific white-sided (Lagenorhynchus obliquidens), and bottlenose (Tursiops truncatus) dolphins. Spectral properties are compared among the five species and unique spectral peak and notch patterns are described for two species. The spectral peak mean values from Pacific white-sided dolphin clicks are 22.2, 26.6, 33.7, and 37.3 kHz and from Risso's dolphins are 22.4, 25.5, 30.5, and 38.8 kHz. The spectral notch mean values from Pacific white-sided dolphin clicks are 19.0, 24.5, and 29.7 kHz and from Risso's dolphins are 19.6, 27.7, and 35.9 kHz. Analysis of variance analyses indicate that spectral peaks and notches within the frequency band 24-35 kHz are distinct between the two species and exhibit low variation within each species. Post hoc tests divide Pacific white-sided dolphin recordings into two distinct subsets containing different click types, which are hypothesized to represent the different populations that occur within the region. Bottlenose and common dolphin clicks do not show consistent patterns of spectral peaks or notches within the frequency band examined (1-100 kHz).