Sensor Noise Assessment Approach in a Patterned Region

2013 ◽  
Vol 717 ◽  
pp. 529-532
Author(s):  
Gwang Gil Jeon
Keyword(s):  
Input Signal ◽  
Gaussian Noise ◽  
Noise Level ◽  
Large Range ◽  
Noise Variance ◽  
Noise Levels ◽  
Pass Filter ◽  
Assessment Approach ◽  
Noise Assessment ◽  
High Pass

In this paper, we propose a simple noise assessment approach for sensors. We assume the input signal is contaminated by white additive and zero mean Gaussian noise which. To measure the noise level, we the intensity-homogeneous blocks are found first, and then we evaluate the noise variance in the blocks. To determined intensity-homogeneous blocks, we use high pass filter. Experimental results show that the presented method provides good performance for natural and artificial images over a large range of noise levels.

scholarly journals Urban Noise Modelling in Boka Kotorska Bay

2014 ◽  
Vol 26 (2) ◽  
pp. 151-157
Author(s):  
Aleksandar Nikolić ◽  
Danilo Nikolić ◽  
Emilija Nikolić ◽  
Vesna Vujačić
Keyword(s):  
Noise Level ◽  
Urban Areas ◽  
Road Traffic ◽  
Noise Source ◽  
Empirical Methods ◽  
Noise Levels ◽  
Sound Effects ◽  
Noise Assessment ◽  
A Site ◽  
The Village

Traffic is the most significant noise source in urban areas. The village of Kamenari in Boka Kotorska Bay is a site where, in a relatively small area, road traffic and sea (ferry) traffic take place at the same time. Due to the specificity of the location, i.e. very rare synergy of sound effects of road and sea traffic in the urban area, as well as the expressed need for assessment of noise level in a simple and quick way, a research was conducted, using empirical methods and statistical analysis methods, which led to the creation of acoustic model for the assessment of equivalent noise level (Leq). The developed model for noise assessment in the Village of Kamenari in Boka Kotorska Bay quite realistically provides data on possible noise levels at the observed site, with very little deviations in relation to empirically obtained values.

scholarly journals Traffic-Noise Assessment at Rush Hours in Quetta City

2020 ◽  
pp. 50-56
Keyword(s):  
Health Care ◽  
Noise Level ◽  
Noise Exposure ◽  
Traffic Noise ◽  
Sound Level ◽  
Mitigation Strategies ◽  
Noise Levels ◽  
Contributing Factors ◽  
Community Noise ◽  
Noise Assessment

Noise is an environmental stressor, which leads to various ailments due to the physiological and psychological stresses it creates. It is essential to understand and evaluate the contributing factors of environmental noise, especially in densely polluted areas near major roads, railways and airports, for public health policy and planning. Noise level measurement permits precise and scientific analysis of noise annoyance, and therefore, this study aimed to determine the average noise levels of Quetta city. Seventy-three (73) location’s equivalent noise levels (Leq) were measured at peak rush hours for three consecutive days. Selected areas for measurement included health care centres, educational centres, government offices, public places, residential and commercial areas. All the selected sites were located near to main roads, where the traffic noise was the most prominent noise source. Noise was measured through calibrated microprocessor sound level meter. The results were computed by taking the mean of the three readings. The results showed 74 dBA as average noise level of Quetta city. It has been found that 90% of the selected locations in Quetta city exceeded the 65dBA, while 10 % of the total locations ranged between 55 to 65 dBA. The average noise exposure of the Quetta city was greater than the permissible international noise standard. This study identified the main traffic hubs of Quetta city, which requires mitigation strategies by the policy makers specifically for Health care and Educational sectors. It also requires adequate updated plans for community noise survey and ordinance.

A V-Band Two Pole High-Pass Filter for Frequency Quadrupler Design

2016 ◽  
Vol 6 (1) ◽  
pp. 56
Author(s):  
Maryam Abata ◽  
Mahmoud Mehdi ◽  
Said Mazer ◽  
Moulhime El Bekkali ◽  
Catherine Algani
Keyword(s):  
Pass Filter ◽  
High Pass Filter ◽  
V Band ◽  
High Pass

Baseline-free sensor fault detection for piezoelectric array

2021 ◽  
pp. 1045389X2110188
Author(s):  
Qibo Mao ◽  
Yuande Wang ◽  
Shizuo Huang
Keyword(s):  
Prior Knowledge ◽  
Frequency Response Function ◽  
Sensor Array ◽  
Piezoelectric Element ◽  
Piezoelectric Sensor ◽  
Steel Beam ◽  
Sensor Fault ◽  
Pass Filter ◽  
Sensor Fault Detection ◽  
High Pass

In this study, a new methodology is presented to detect the sensor fault for piezoelectric array based on the filtered frequency response function (FRF) shapes. The proposed method does not require prior knowledge about healthy piezoelectric array. First, the imaginary parts of FRFs from the piezoelectric array during vibration are measured and normalized to obtain the FRF shapes in different frequencies. Then the irregularities in these FRF shapes are extracted by using high-pass filter with properly chosen cut-off frequency. These abnormal irregularities on the filtered FRF shape curves indicate the location of the faulty sensor, due to the irregularity of FRF shapes introduced by the faulty piezoelectric element. The proposed sensor fault method is experimentally demonstrated on a clamped-clamped steel beam mounted with piezoelectric buzzer array. Two common piezoelectric sensor fault types including sensor breakage and debonding are evaluated. The experimental results indicate that the proposed method has great potential in the detection of the sensor fault for piezoelectric array as it is simple and does not require the FRF data of the healthy sensor array as a baseline.

scholarly journals Noise in Otolaryngology – Head and Neck Surgery operating rooms: a systematic review

2021 ◽  
Vol 50 (1) ◽  
Author(s):  
Gianluca Sampieri ◽  
Amirpouyan Namavarian ◽  
Marc Levin ◽  
Justine Philteos ◽  
Jong Wook Lee ◽  
...  
Keyword(s):  
Systematic Review ◽  
Head And Neck ◽  
Patient Outcomes ◽  
Noise Level ◽  
Neck Surgery ◽  
Operating Rooms ◽  
Head And Neck Surgery ◽  
Noise Levels ◽  
Surgical Performance ◽  
The Mean

Abstract Objective Noise in operating rooms (OR) can have negative effects on both patients and surgical care workers. Noise can also impact surgical performance, team communication, and patient outcomes. Such implications of noise have been studied in orthopedics, neurosurgery, and urology. High noise levels have also been demonstrated in Otolaryngology-Head and Neck Surgery (OHNS) procedures. Despite this, no previous study has amalgamated the data on noise across all OHNS ORs to determine how much noise is present during OHNS surgeries. This study aims to review all the literature on noise associated with OHNS ORs and procedures. Methods Ovid Medline, EMBASE Classic, Pubmed, SCOPUS and Cochrane databases were searched following PRISMA guidelines. Data was collected on noise measurement location and surgery type. Descriptive results and statistical analysis were completed using Stata. Results This search identified 2914 articles. Final inclusion consisted of 22 studies. The majority of articles analyzed noise level exposures during mastoid surgery (18/22, 82%). The maximum noise level across all OHNS ORs and OHNS cadaver studies were 95.5 a-weighted decibels (dBA) and 106.6 c-weighted decibels (dBC), respectively (P = 0.2068). The mean noise level across all studies was significantly higher in OHNS cadaver labs (96.9 dBA) compared to OHNS ORs (70.1 dBA) (P = 0.0038). When analyzed together, the mean noise levels were 84.9 dBA. Conclusions This systematic review demonstrates that noise exposure in OHNS surgery exceeds safety thresholds. Further research is needed to understand how noise may affect team communication, surgical performance and patient outcomes in OHNS ORs. Graphical abstract

Effective splicing localization based on noise level inconsistencies

2021 ◽  
pp. 1-11
Author(s):  
P. N. R. L. Chandra Sekhar Author ◽  
T. N. Shankar Author
Keyword(s):  
Digital Technology ◽  
Social Networking Sites ◽  
Noise Level ◽  
Research Work ◽  
Multimedia Content ◽  
Noise Levels ◽  
Multimedia Forensics ◽  
The Past ◽  
Photo Editing ◽  
State Of Art

In the era of digital technology, it becomes easy to share photographs and videos using smartphones and social networking sites to their loved ones. On the other hand, many photo editing tools evolved to make it effortless to alter multimedia content. It makes people accustomed to modifying their photographs or videos either for fun or extracting attention from others. This altering brings a questionable validity and integrity to the kind of multimedia content shared over the internet when used as evidence in Journalism and Court of Law. In multimedia forensics, intense research work is underway over the past two decades to bring trustworthiness to the multimedia content. This paper proposes an efficient way of identifying the manipulated region based on Noise Level inconsistencies of spliced mage. The spliced image segmented into irregular objects and extracts the noise features in both pixel and residual domains. The manipulated region is then exposed based on the cosine similarity of noise levels among pairs of individual objects. The experimental results reveal the effectiveness of the proposed method over other state-of-art methods.

scholarly journals Characterization of Noise Level Inside a Vehicle under Different Conditions

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2471 ◽  
Author(s):  
Daniel Flor ◽  
Danilo Pena ◽  
Luan Pena ◽  
Vicente A. de Sousa ◽  
Allan Martins
Keyword(s):  
Regression Analysis ◽  
Noise Level ◽  
Acoustic Noise ◽  
Experimental Setup ◽  
Strongly Correlated ◽  
Noise Levels ◽  
Noise Sources ◽  
Statistical Tools ◽  
Window Position

Vehicular acoustic noise evaluations are a concern of researchers due to health and comfort effects on humans and are fundamental for anyone interested in mitigating audio noise. This paper focuses on the evaluation of the noise level inside a vehicle by using statistical tools. First, an experimental setup was developed with microphones and a microcomputer located strategically on the car’s panel, and measurements were carried out with different conditions such as car window position, rain, traffic, and car speed. Regression analysis was performed to evaluate the similarity of the noise level from those conditions. Thus, we were able to discuss the relevance of the variables that contribute to the noise level inside a car. Finally, our results revealed that the car speed is strongly correlated to interior noise levels, suggesting the most relevant noise sources are in the vehicle itself.

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