Auditory Sampling of Frogs: Detection Efficiency in Relation to Survey Duration

2004 ◽  
Vol 38 (4) ◽  
pp. 495-500 ◽  
Author(s):  
Benjamin A. Pierce ◽  
Kevin J. Gutzwiller
Keyword(s):  
Detection Efficiency ◽  
Auditory Sampling

Fresnel interference in point-projection imaging of purple membrane

1995 ◽  
Vol 53 ◽  
pp. 846-847
Author(s):  
X. Zhang ◽  
J. Spence ◽  
W. Qian ◽  
D. Taylor ◽  
K. Taylor
Keyword(s):  
Detection Efficiency ◽  
Mean Free Path ◽  
Purple Membrane ◽  
Unit Cell Dimension ◽  
Experimental Point ◽  
Membrane Thickness ◽  
Low Energies ◽  
Channel Plate ◽  
Point Projection ◽  
Inelastic Mean Free Path

Experimental point-projection shadow microscope (PPM) images of uncoated, unstained purple membrane (PM, bacteriorhodopsin, a membrane protein from Halobacterium holobium) were obtained recently using 100 volt electrons. The membrane thickness is about 5 nm and the hexagonal unit cell dimension 6 nm. The images show contrast around the edges of small holes, as shown in figure 1. The interior of the film is opaque. Since the inelastic mean free path for 100V electrons in carbon (about 6 Å) is much less than the sample thickness, the question arises that how much, if any, transmission of elastically scattered electrons occurs. A large inelastic contribution is also expected, attenuated by the reduced detection efficiency of the channel plate at low energies. Quantitative experiments using an energy-loss spectrometer are planned. Recently Shedd has shown that at about 100V contrast in PPM images of thin gold films can be explained as Fresnel interference effects between different pinholes in the film, separated by less than the coherence width.

Effect of energy filtering on micro-diffraction in the SEM

1994 ◽  
Vol 52 ◽  
pp. 604-605
Author(s):  
James F. Mancuso ◽  
Leo A. Fama ◽  
William B. Maxwell ◽  
Jerry L. Lehman ◽  
Hasso Weiland ◽  
...  
Keyword(s):  
Detection Efficiency ◽  
Ccd Camera ◽  
High Gain ◽  
Microchannel Plate ◽  
Electrostatic Energy ◽  
Energy Filtering ◽  
Electron Channelling ◽  
Low Energy Electrons ◽  
Low Sensitivity ◽  
Angular Field Of View

Micro-diffraction based crystallography is essential to the design and development of many classes of ‘crafted materials’. Although the scanning electron microscope can provide crystallographic information with high spatial resolution, its current utility is severely limited by the low sensitivity of existing diffraction techniques (ref: Dingley). Previously, Joy showed that energy filtering increased contrast and pattern visibility in electron channelling. This present paper discribes the effect of energy filtering on EBSP sensitivity and backscattered SEM imaging.The EBSP detector consisted of an electron energy filter, a microchannel plate detector, a phosphor screen, optical coupler, and a slow scan CCD camera. The electrostatic energy filter used in this experiment was constructed as a cone with 5 coaxial electrodes. The angular field-of-view of the filter was approximately 38°. The microchannel plate, which was the initial sensing component, had high gain and had 50% to 80% detection efficiency for the low energy electrons that passed through the retarding field filter.

Trace nanoanalysis

1994 ◽  
Vol 52 ◽  
pp. 940-941
Author(s):  
D. E. Newbury ◽  
R. D. Leapman
Keyword(s):  
High Performance ◽  
Secondary Ion Mass Spectrometry ◽  
Detection Efficiency ◽  
Volume Element ◽  
And Performance ◽  
Trace Constituents ◽  
Secondary Ion ◽  
Concentration Levels ◽  
Structure Properties

Trace constituents, which can be very loosely defined as those present at concentration levels below 1 percent, often exert influence on structure, properties, and performance far greater than what might be estimated from their proportion alone. Defining the role of trace constituents in the microstructure, or indeed even determining their location, makes great demands on the available array of microanalytical tools. These demands become increasingly more challenging as the dimensions of the volume element to be probed become smaller. For example, a cubic volume element of silicon with an edge dimension of 1 micrometer contains approximately 5×1010 atoms. High performance secondary ion mass spectrometry (SIMS) can be used to measure trace constituents to levels of hundreds of parts per billion from such a volume element (e. g., detection of at least 100 atoms to give 10% reproducibility with an overall detection efficiency of 1%, considering ionization, transmission, and counting).

MK-FSVM-SVDD: A Multiple Kernel-based Fuzzy SVM Model for Predicting DNA-binding Proteins via Support Vector Data Description

2020 ◽  
Vol 15 ◽  
Author(s):  
Yi Zou ◽  
Hongjie Wu ◽  
Xiaoyi Guo ◽  
Li Peng ◽  
Yijie Ding ◽  
...  
Keyword(s):  
Dna Binding ◽  
Binding Proteins ◽  
Detection Efficiency ◽  
Dna Binding Proteins ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Vector Data ◽  
Data Description ◽  
Multiple Kernel ◽  
Svm Model

Background: Detecting DNA-binding proetins (DBPs) based on biological and chemical methods is time consuming and expensive. Objective: In recent years, the rise of computational biology methods based on Machine Learning (ML) has greatly improved the detection efficiency of DBPs. Method: In this study, Multiple Kernel-based Fuzzy SVM Model with Support Vector Data Description (MK-FSVM-SVDD) is proposed to predict DBPs. Firstly, sex features are extracted from protein sequence. Secondly, multiple kernels are constructed via these sequence feature. Than, multiple kernels are integrated by Centered Kernel Alignment-based Multiple Kernel Learning (CKA-MKL). Next, fuzzy membership scores of training samples are calculated with Support Vector Data Description (SVDD). FSVM is trained and employed to detect new DBPs. Results: Our model is test on several benchmark datasets. Compared with other methods, MK-FSVM-SVDD achieves best Matthew's Correlation Coefficient (MCC) on PDB186 (0.7250) and PDB2272 (0.5476). Conclusion: We can conclude that MK-FSVM-SVDD is more suitable than common SVM, as the classifier for DNA-binding proteins identification.

Collection and counting efficiency

2017 ◽  
Author(s):  
A. G. Wright
Keyword(s):  
Quantum Efficiency ◽  
Standard Method ◽  
Shot Noise ◽  
Count Rate ◽  
Detection Efficiency ◽  
Collection Efficiency ◽  
Counting Efficiency ◽  
Single Electron ◽  
Anode Current ◽  
Secondary Electrons

Standards laboratories can provide a photocathode calibration for quantum efficiency, as a function of wavelength, but their measurements are performed with the photomultiplier operating as a photodiode. Each photoelectron released makes a contribution to the photocathode current but, if it is lost or fails to create secondary electrons at d1, it makes no contribution to anode current. This is the basis of collection efficiency, F. The anode detection efficiency, ε‎, allied to F, refers to the counting efficiency of output pulses. The standard method for determining F involves photocurrent, anode current, count rate, and the use of highly attenuating filters; F may also be measured using methods based on single-electron responses (SERs), shot noise, or the SER at the first dynode.

scholarly journals Characterization of Highly Irradiated ALPIDE Silicon Sensors

Universe ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 91
Author(s):  
Valentina Raskina ◽  
Filip Křížek
Keyword(s):  
Nuclear Physics ◽  
Detection Efficiency ◽  
Tracking System ◽  
Physics Institute ◽  
Total Ionization ◽  
Silicon Sensors ◽  
Active Pixel ◽  
Academy Of Sciences

The ALICE (A Large Ion Collider Experiment) experiment at CERN will upgrade its Inner Tracking System (ITS) detector. The new ITS will consist of seven coaxial cylindrical layers of ALPIDE silicon sensors which are based on Monolithic Active Pixel Sensor (MAPS) technology. We have studied the radiation hardness of ALPIDE sensors using a 30 MeV proton beam provided by the cyclotron U-120M of the Nuclear Physics Institute of the Czech Academy of Sciences in Řež. In this paper, these long-term measurements will be described. After being irradiated up to the total ionization dose 2.7 Mrad and non-ionizing energy loss 2.7 × 10 13 1 MeV n eq · cm - 2 , ALPIDE sensors fulfill ITS upgrade project technical design requirements in terms of detection efficiency and fake-hit rate.

scholarly journals Overcoming detection loss and noise in squeezing-based optical sensing

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Gaetano Frascella ◽  
Sascha Agne ◽  
Farid Ya. Khalili ◽  
Maria V. Chekhova
Keyword(s):  
Shot Noise ◽  
Optical Sensing ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Real Life ◽  
Squeezed States ◽  
Squeezed Light ◽  
Noise Limit ◽  
Imaging And Spectroscopy ◽  
Shot Noise Limit

AbstractAmong the known resources of quantum metrology, one of the most practical and efficient is squeezing. Squeezed states of atoms and light improve the sensing of the phase, magnetic field, polarization, mechanical displacement. They promise to considerably increase signal-to-noise ratio in imaging and spectroscopy, and are already used in real-life gravitational-wave detectors. But despite being more robust than other states, they are still very fragile, which narrows the scope of their application. In particular, squeezed states are useless in measurements where the detection is inefficient or the noise is high. Here, we experimentally demonstrate a remedy against loss and noise: strong noiseless amplification before detection. This way, we achieve loss-tolerant operation of an interferometer fed with squeezed and coherent light. With only 50% detection efficiency and with noise exceeding the level of squeezed light more than 50 times, we overcome the shot-noise limit by 6 dB. Sub-shot-noise phase sensitivity survives up to 87% loss. Application of this technique to other types of optical sensing and imaging promises a full use of quantum resources in these fields.

scholarly journals Detection Efficiency Modelling and Joint Activity and Attenuation Reconstruction in non-TOF 3D PET from Multiple-Energy Window Data

2021 ◽  
pp. 1-1
Author(s):  
Ludovica Brusaferri ◽  
Elise C. Emond ◽  
Alexandre Bousse ◽  
Robert Twyman ◽  
Alexander C. Whitehead ◽  
...  
Keyword(s):  
Detection Efficiency ◽  
Energy Window ◽  
Joint Activity ◽  
3D Pet

scholarly journals Preliminary Research on a Comparison and Evaluation of FY-4A LMI and ADTD Data through a Moving Amplification Matching Algorithm

2020 ◽  
Vol 13 (1) ◽  
pp. 11
Author(s):  
Pengfei Li ◽  
Guofu Zhai ◽  
Wenjing Pang ◽  
Wen Hui ◽  
Wenjuan Zhang ◽  
...  
Keyword(s):  
Detection Efficiency ◽  
Spherical Surface ◽  
Operation Time ◽  
Mean Value ◽  
China Meteorological Administration ◽  
Matching Algorithm ◽  
Lightning Detection ◽  
Spatial Differences ◽  
System Data ◽  
Spatial Threshold

In this study, a new moving amplification matching algorithm was proposed, and then the temporal and spatial differences and correlation were analysed and evaluated by comparing the FengYun-4A Lightning Mapping Imager (FY-4A LMI) data and the China Meteorological Administration Lightning Detection Network Advanced TOA and Direction (CMA-LDN ADTD) system data of southwest China in July 2018. The results are as follows. Firstly, the new moving amplification matching algorithm could effectively reduce the number of invalid operations and save the operation time in comparison to the conventional ergodic algorithms. Secondly, LMI has less detection efficiency during the daytime, using ADTD as a reference. The lightning number detected by ADTD increased from 5:00 AM UTC (13:00 PM BJT, Beijing Time) and almost lasted for a whole day. Thirdly, the trends of lightning data change of LMI and ADTD were the same as the whole. The average daily lightning matching rate of the LMI in July was 63.23%. The average hourly lightning matching rate of the LMI in July was 75.08%. Lastly, the mean value of the spherical surface distance in the matched array was 35.49 km, and roughly 80% of the matched distance was within 57 km, indicating that the spatial threshold limit was relatively stable. The correlation between LMI lightning radiation intensity and ADTD lighting current intensity was low.

scholarly journals Feature-Selection and Mutual-Clustering Approaches to Improve DoS Detection and Maintain WSNs’ Lifetime

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4821
Author(s):  
Rami Ahmad ◽  
Raniyah Wazirali ◽  
Qusay Bsoul ◽  
Tarik Abu-Ain ◽  
Waleed Abu-Ain
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Open Field ◽  
Network Lifetime ◽  
Detection Efficiency ◽  
Denial Of Service ◽  
Harmony Search ◽  
Machine Learning Algorithms ◽  
Transport Layer ◽  
Feature Selection Techniques

Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algorithm, to improve anomaly detection efficiency over a WSN’s lifetime. Furthermore, the use of feature selection techniques with machine learning algorithms in examining WSN node traffic and the effect of these techniques on the lifetime of WSNs was evaluated. The evaluation results showed that the Water Cycle (WC) feature selection displayed the best average performance accuracy of 2%, 5%, 3%, and 3% greater than Particle Swarm Optimization (PSO), Simulated Annealing (SA), Harmony Search (HS), and Genetic Algorithm (GA), respectively. Moreover, the WC with Decision Tree (DT) classifier showed 100% accuracy with only one feature. In addition, the CH_Rotations algorithm improved network lifetime by 30% compared to the standard LEACH protocol. Network lifetime using the WC + DT technique was reduced by 5% compared to other WC + DT-free scenarios.

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