Background Noise Filtering and Distribution Dividing for Crowd Counting

2020 ◽  
Vol 29 ◽  
pp. 8199-8212
Author(s):  
Hong Mo ◽  
Wenqi Ren ◽  
Yuan Xiong ◽  
Xiaoqi Pan ◽  
Zhong Zhou ◽  
...  
Keyword(s):  
Background Noise ◽  
Noise Filtering ◽  
Crowd Counting

scholarly journals Efficient method for the global noise filtering in measuring channels of the VVER NPP leak monitoring systems

2021 ◽  
Vol 7 (1) ◽  
pp. 67-72
Author(s):  
Yevgeniy L. Trykov ◽  
Andrey A. Kudryaev ◽  
Konstantin I. Kotsoyev ◽  
Aleksey A. Ananyev
Keyword(s):  
Monitoring System ◽  
Background Noise ◽  
Power Plants ◽  
Measuring Channel ◽  
Monitoring Systems ◽  
Noise Filtering ◽  
Level Control ◽  
Operating Personnel ◽  
Integrated Diagnostics ◽  
Diagnostics System

In accordance with Ref. (GOST R 58328-2018 “Pipelines of Nuclear Power Plants. Leak Before Break Concept”), NPPs with VVER-1200 reactors operate an acoustic leak monitoring system (ALMS) and a humidity leak monitoring system (HLMS), each performing the leak monitoring functions locally, independently of the other. The diagnostics results are conveyed to the upper level control system (LCS) to be further displayed for the main control room (MCR) operating personnel. There is also an integrated diagnostics system (IDS) intended to confirm the diagnosis and to update the leak rate values and coordinates based on analyzing the leak monitoring system readings and I&C signals. The system measuring channel readings are composed of background noise, the source for which are processes on the part of the reactor facility’s key components and auxiliary systems, and the leak signal in response to the leak occurrence. A major factor that affects the capability of leak monitoring systems to detect the leak is the quality of the background noise filtering. A new efficient global noise filtering method is proposed for being used as part of the integrated diagnostics system (IDS).

scholarly journals Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area

2019 ◽  
Vol 11 (8) ◽  
pp. 980 ◽  
Author(s):  
Jiapeng Huang ◽  
Yanqiu Xing ◽  
Haotian You ◽  
Lei Qin ◽  
Jing Tian ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Background Noise ◽  
Spatial Clustering ◽  
Particle Swarm ◽  
Noise Filtering ◽  
Swarm Optimization ◽  
Cloud Data ◽  
Filtering Algorithm ◽  
Statistical Algorithm ◽  
The Mean

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), which is equipped with the Advanced Topographic Laser Altimeter System (ATLAS), was launched successfully in 15 September 2018. The ATLAS represents a micro-pulse photon-counting laser system, which is expected to provide more comprehensive and scientific data for carbon storage. However, the ATLAS system is sensitive to the background noise, which poses a tremendous challenge to the photon cloud noise filtering. Moreover, the Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a commonly used algorithm for noise removal from the photon cloud but there has not been an in-depth study on its parameter selection yet. This paper presents an automatic photon cloud filtering algorithm based on the Particle Swarm Optimization (PSO) algorithm, which can be used to optimize the two key parameters of the DBSCAN algorithm instead of using the manual parameter adjustment. The Particle Swarm Optimization Density Based Spatial Clustering of Applications with Noise (PSODBSCAN) algorithm was tested at different laser intensities and laser pointing types using the MATLAS dataset of the forests located in Virginia, East Coast, and the West Coast, USA. The results showed that the PSODBSCAN algorithm and the localized statistical algorithm were effective in identifying the background noise and preserving the signal photons in the raw MATLAS data. Namely, the PSODBSCAN achieved the mean F value of 0.9759, and the localized statistical algorithm achieved the mean F value of 0.6978. For both laser pointing types and laser intensities, the proposed algorithm achieved better results than the localized statistical algorithm. Therefore, the PSODBSCAN algorithm could support the MATLAS photon cloud data noise filtering applicably without manually selecting parameters.

Background Noise Filtering and Clustering with 3D LiDAR Deployed in Roadside of Urban Environments

2021 ◽  
pp. 1-1
Author(s):  
Jianying Zheng ◽  
Siyuan Yang ◽  
Xiang Wang ◽  
Yang Xiao ◽  
Tieshan Li
Keyword(s):  
Background Noise ◽  
Urban Environments ◽  
Noise Filtering ◽  
3D Lidar

scholarly journals THE APPLICATION OF SATURATING DETECTORS TO A DCT-DOMAIN WATERMARKING SCHEME

2008 ◽  
Vol 08 (01) ◽  
pp. L65-L79 ◽  
Author(s):  
FABING DUAN ◽  
DEREK ABBOTT ◽  
FRANÇOIS CHAPEAU-BLONDEAU
Keyword(s):  
Background Noise ◽  
Pulse Amplitude ◽  
Noise Filtering ◽  
Frequency Range ◽  
Arnold Transform ◽  
Matched Filters ◽  
Nonlinear Dynamical ◽  
Dct Domain ◽  
Dct Coefficients ◽  
Watermarking Scheme

The present paper proposes a discrete cosine transform (DCT) domain watermarking scheme by exploiting nonlinear dynamical saturating detectors in the design of a watermark detection process. A binary copyright character, i.e. watermark to be hidden into an image, is firstly reordered into a binary zig-zag sequence, and then mapped onto the pulse amplitude modulated signal. A certain desynchronization time delay can be deliberately placed into one code of the modulated signal, and is tolerated due to the superior robustness of nonlinear detectors over matched filters. A selected set of DCT coefficients of a host image in a mid frequency range is shuffled by the Arnold transform, which makes it look more like background noise with respect to the watermark signal. Then, the watermark signal is embedded in the set of shuffled DCT coefficients. The copyright character can be extracted by a nonlinear saturating detector without prior knowledge of the original image and watermark, i.e. blind watermark detection. Interestingly, a higher match between the original watermark character and the extracted one can be further achieved by a parallel array of nonlinear detectors via the mechanism of array stochastic resonance. Robustness of the proposed watermarking scheme is shown in the presence of noise, filtering, cropping, and compression.

Microdensitometer—computer correlation analysis of ultrastructural periodicity

1978 ◽  
Vol 36 (2) ◽  
pp. 32-33
Author(s):  
D.R. Ensor ◽  
C.G. Jensen ◽  
J.A. Fillery ◽  
R.J.K. Baker
Keyword(s):  
Correlation Analysis ◽  
Background Noise ◽  
Computer Control ◽  
Optical Diffraction ◽  
Screw Thread ◽  
Straight Line ◽  
Computer Storage ◽  
Correlation Process ◽  
Electron Microscope Image ◽  
Fixed Beam

Because periodicity is a major indicator of structural organisation numerous methods have been devised to demonstrate periodicity masked by background “noise” in the electron microscope image (e.g. photographic image reinforcement, Markham et al, 1964; optical diffraction techniques, Horne, 1977; McIntosh,1974). Computer correlation analysis of a densitometer tracing provides another means of minimising "noise". The correlation process uncovers periodic information by cancelling random elements. The technique is easily executed, the results are readily interpreted and the computer removes tedium, lends accuracy and assists in impartiality.A scanning densitometer was adapted to allow computer control of the scan and to give direct computer storage of the data. A photographic transparency of the image to be scanned is mounted on a stage coupled directly to an accurate screw thread driven by a stepping motor. The stage is moved so that the fixed beam of the densitometer (which is directed normal to the transparency) traces a straight line along the structure of interest in the image.

Use of a Mild-Gain Hearing Aid by Middle-Age Normal-Hearing Adults Who Do and Do Not Self-Report Trouble Hearing in Background Noise

2020 ◽  
Vol 29 (3) ◽  
pp. 419-428
Author(s):  
Jasleen Singh ◽  
Karen A. Doherty
Keyword(s):  
Hearing Aids ◽  
Background Noise ◽  
Middle Age ◽  
Hearing Aid ◽  
Normal Hearing ◽  
Self Report ◽  
Hearing Aid Use ◽  
Hearing Handicap ◽  
Before And After ◽  
Hearing Problems

Purpose The aim of the study was to assess how the use of a mild-gain hearing aid can affect hearing handicap, motivation, and attitudes toward hearing aids for middle-age, normal-hearing adults who do and do not self-report trouble hearing in background noise. Method A total of 20 participants (45–60 years of age) with clinically normal-hearing thresholds (< 25 dB HL) were enrolled in this study. Ten self-reported difficulty hearing in background noise, and 10 did not self-report difficulty hearing in background noise. All participants were fit with mild-gain hearing aids, bilaterally, and were asked to wear them for 2 weeks. Hearing handicap, attitudes toward hearing aids and hearing loss, and motivation to address hearing problems were evaluated before and after participants wore the hearing aids. Participants were also asked if they would consider purchasing a hearing aid before and after 2 weeks of hearing aid use. Results After wearing the hearing aids for 2 weeks, hearing handicap scores decreased for the participants who self-reported difficulty hearing in background noise. No changes in hearing handicap scores were observed for the participants who did not self-report trouble hearing in background noise. The participants who self-reported difficulty hearing in background noise also reported greater personal distress from their hearing problems, were more motivated to address their hearing problems, and had higher levels of hearing handicap compared to the participants who did not self-report trouble hearing in background noise. Only 20% (2/10) of the participants who self-reported trouble hearing in background noise reported that they would consider purchasing a hearing aid after 2 weeks of hearing aid use. Conclusions The use of mild-gain hearing aids has the potential to reduce hearing handicap for normal-hearing, middle-age adults who self-report difficulty hearing in background noise. However, this may not be the most appropriate treatment option for their current hearing problems given that only 20% of these participants would consider purchasing a hearing aid after wearing hearing aids for 2 weeks.

Selecting the Optimal FM System for Children With Cochlear Implants

2008 ◽  
Vol 18 (1) ◽  
pp. 19-24
Author(s):  
Erin C. Schafer
Keyword(s):  
Speech Recognition ◽  
Cochlear Implants ◽  
Empirical Research ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Evidence Based ◽  
Signal To Noise ◽  
Speech Processor ◽  
System Input ◽  
Optimal Type

Children who use cochlear implants experience significant difficulty hearing speech in the presence of background noise, such as in the classroom. To address these difficulties, audiologists often recommend frequency-modulated (FM) systems for children with cochlear implants. The purpose of this article is to examine current empirical research in the area of FM systems and cochlear implants. Discussion topics will include selecting the optimal type of FM receiver, benefits of binaural FM-system input, importance of DAI receiver-gain settings, and effects of speech-processor programming on speech recognition. FM systems significantly improve the signal-to-noise ratio at the child's ear through the use of three types of FM receivers: mounted speakers, desktop speakers, or direct-audio input (DAI). This discussion will aid audiologists in making evidence-based recommendations for children using cochlear implants and FM systems.

Sign in / Sign up

Export Citation Format

Share Document