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State Law Reference— Noise Regulation, G.S. 160A-184
State Law reference— Noise regulation, G.S. 160A-184. Sec. 17-8. - Certain noises and sounds prohibited. It shall be unlawful, except as expressly permitted in this chapter, to make, cause, or allow the making of any noise or sound which exceeds the limits set forth in sections 17-9 through 17-13. (Code 1961, § 21-30.1; Ord. No. S2013-025, § 1, 11-18-2013) Sec. 17-9. - Terminology and standards regarding noises and sounds. (a) Terminology and standards. All terminology used in the provisions of sections 17-7 through 17-16 not defined in subsection (b) of this section, shall be in conformance with applicable publications of the American National Standards Institute (ANSI) or its successor body. (b) Definitions: Ambient sound means the total noise in a given environment. A-weighted sound level means the sound pressure level in decibels as measured on a sound level meter using the A-weighting network. The level so read is designated dB(A). A-weighted sound level meter means an instrument which includes an omnidirectional microphone, an amplifier, an output meter, and frequency weighting network for the measurement of sound. A sound meter that meets these requirements shall be utilized for conducting sound measurements. Background noise means ambient sound. Classification of use occupancies. For the purpose of defining the "use occupancy" all premises containing habitually occupied sleeping quarters shall be considered in residential use. All premises containing transient commercial sleeping quarters shall be considered tourist use. All premises containing businesses where sales, professional, or other commercial use is legally permitted shall be considered commercial use. -
SCDOT Traffic Noise Abatement Policy
CONTENTS SECTION 1: INTRODUCTION Page 4 1.1 What is noise? Page 4 1.2 How is noise measured? Page 4 1.3 How have noise regulations evolved over time? Page 4 1.4 What is the purpose and applicability of this policy? Page 5 1.5 When is a noise analysis needed? Page 5 SECTION 2: DEFINITIONS Page 6 SECTION 3: TYPES OF SCDOT NOISE ANALYSIS Page 10 3.1 Scoping the Level of Noise Analysis Page 10 3.2 What are the required elements of a SCDOT detailed noise analysis? Page 12 3.3 What are the required elements and/or considerations of a SCDOT final design Page 13 noise analysis? SECTION 4: ELEMENTS OF A SCDOT NOISE ANALYSIS Page 13 4.1 Average Pavement Page 13 4.2 Noise Contours Page 14 4.3 Traffic Characteristics Page 14 4.4 Posted vs. Design Speeds Page 14 4.5 TNM Input Parameters for a SCDOT Noise Analysis Page 14 Receivers Page 14 Roadways Page 16 4.6 Required Additional TNM Input Parameters Page 16 Receivers Page 17 Roadways Page 17 Building Rows/Terrain Lines/Ground Zones/Tree Zones Page 17 4.7 Quality Assurance/Quality Control Page 17 SECTION 5: ANALYSIS OF TRAFFIC NOISE IMPACTS Page 17 5.1 Field Noise Measurements Page 17 5.2 Model Validation Page 19 5.3 Model Calibration Page 19 5.4 Prediction of Future Highway Traffic Noise Levels for Study Alternatives Page 20 5.5 Identification of Highway Traffic Noise Impacts for Study Alternations Page 20 Activity Category A Page 21 Activity Category B Page 22 Activity Category C Page 22 Activity Category D Page 22 Activity Category E Page 23 Activity Category F Page 23 Activity Category G Page 23 -
AN279: Estimating Period Jitter from Phase Noise
AN279 ESTIMATING PERIOD JITTER FROM PHASE NOISE 1. Introduction This application note reviews how RMS period jitter may be estimated from phase noise data. This approach is useful for estimating period jitter when sufficiently accurate time domain instruments, such as jitter measuring oscilloscopes or Time Interval Analyzers (TIAs), are unavailable. 2. Terminology In this application note, the following definitions apply: Cycle-to-cycle jitter—The short-term variation in clock period between adjacent clock cycles. This jitter measure, abbreviated here as JCC, may be specified as either an RMS or peak-to-peak quantity. Jitter—Short-term variations of the significant instants of a digital signal from their ideal positions in time (Ref: Telcordia GR-499-CORE). In this application note, the digital signal is a clock source or oscillator. Short- term here means phase noise contributions are restricted to frequencies greater than or equal to 10 Hz (Ref: Telcordia GR-1244-CORE). Period jitter—The short-term variation in clock period over all measured clock cycles, compared to the average clock period. This jitter measure, abbreviated here as JPER, may be specified as either an RMS or peak-to-peak quantity. This application note will concentrate on estimating the RMS value of this jitter parameter. The illustration in Figure 1 suggests how one might measure the RMS period jitter in the time domain. The first edge is the reference edge or trigger edge as if we were using an oscilloscope. Clock Period Distribution J PER(RMS) = T = 0 T = TPER Figure 1. RMS Period Jitter Example Phase jitter—The integrated jitter (area under the curve) of a phase noise plot over a particular jitter bandwidth. -
Signal-To-Noise Ratio and Dynamic Range Definitions
Signal-to-noise ratio and dynamic range definitions The Signal-to-Noise Ratio (SNR) and Dynamic Range (DR) are two common parameters used to specify the electrical performance of a spectrometer. This technical note will describe how they are defined and how to measure and calculate them. Figure 1: Definitions of SNR and SR. The signal out of the spectrometer is a digital signal between 0 and 2N-1, where N is the number of bits in the Analogue-to-Digital (A/D) converter on the electronics. Typical numbers for N range from 10 to 16 leading to maximum signal level between 1,023 and 65,535 counts. The Noise is the stochastic variation of the signal around a mean value. In Figure 1 we have shown a spectrum with a single peak in wavelength and time. As indicated on the figure the peak signal level will fluctuate a small amount around the mean value due to the noise of the electronics. Noise is measured by the Root-Mean-Squared (RMS) value of the fluctuations over time. The SNR is defined as the average over time of the peak signal divided by the RMS noise of the peak signal over the same time. In order to get an accurate result for the SNR it is generally required to measure over 25 -50 time samples of the spectrum. It is very important that your input to the spectrometer is constant during SNR measurements. Otherwise, you will be measuring other things like drift of you lamp power or time dependent signal levels from your sample. -
Noise Analysis Technical Report 183A Toll Road Phase III, Austin District And
Noise Analysis Technical Report 183A Toll Road Phase III, Austin District and Central Texas Regional Mobility Authority From Hero Way to 1.1 miles north of State Highway 29 CSJ Number: 0914-05-192 Williamson County, Texas March 2019 The environmental review, consultation, and other actions required by applicable Federal environmental laws for this project are being, or have been, carried out by the Texas Department of Transportation (TxDOT) pursuant to 23 U.S.C. 327 and a Memorandum of Understanding dated December 16, 2014, and executed by the Federal Highway Administration and TxDOT. This page intentionally left blank 183A Phase III Williamson County, Texas Table of Contents I. Project Description, Land Use Description and Noise Study Methods .....................1 A. Project Description .......................................................................................................1 B. Sound/Noise Fundamentals .........................................................................................2 C. Surrounding Terrain and Land Use ...............................................................................2 D. Methods .......................................................................................................................2 E. Noise Regulation and Impact Criteria ...........................................................................5 II. Existing Noise Levels ....................................................................................................5 III. Traffic Noise Impacts ....................................................................................................5 -
Image Denoising by Autoencoder: Learning Core Representations
Image Denoising by AutoEncoder: Learning Core Representations Zhenyu Zhao College of Engineering and Computer Science, The Australian National University, Australia, [email protected] Abstract. In this paper, we implement an image denoising method which can be generally used in all kinds of noisy images. We achieve denoising process by adding Gaussian noise to raw images and then feed them into AutoEncoder to learn its core representations(raw images itself or high-level representations).We use pre- trained classifier to test the quality of the representations with the classification accuracy. Our result shows that in task-specific classification neuron networks, the performance of the network with noisy input images is far below the preprocessing images that using denoising AutoEncoder. In the meanwhile, our experiments also show that the preprocessed images can achieve compatible result with the noiseless input images. Keywords: Image Denoising, Image Representations, Neuron Networks, Deep Learning, AutoEncoder. 1 Introduction 1.1 Image Denoising Image is the object that stores and reflects visual perception. Images are also important information carriers today. Acquisition channel and artificial editing are the two main ways that corrupt observed images. The goal of image restoration techniques [1] is to restore the original image from a noisy observation of it. Image denoising is common image restoration problems that are useful by to many industrial and scientific applications. Image denoising prob- lems arise when an image is corrupted by additive white Gaussian noise which is common result of many acquisition channels. The white Gaussian noise can be harmful to many image applications. Hence, it is of great importance to remove Gaussian noise from images. -
Crowdsourcing of Noise Map Pollution Using Smartphones Journées Des Laboratoires SIG De Suisse Romande Changins, Suisse - 16 Juin 2015
European NEtwork for Redistributing Geospatial Information to user Communities - Open Data Crowdsourcing of Noise Map Pollution using Smartphones Journées des Laboratoires SIG de Suisse romande Changins, Suisse - 16 juin 2015 CNRS (E. Bocher, G. Guillaume, N. Fortin) Ecole Centrale de Nantes (G. Petit, S. Palominos) Ifsttar (J. Picaut, A. Can, B. Gauvreau) This project is partially funded under the ICT Policy Support Programme (ICT PSP) as part of the Competitiveness and Innovation Framework Programme by the European Community Introduction European NEtwork for Redistributing Geospatial Information to user Communities - Open Data Noise societal and environmental issues Context : Green Paper on Future Noise Policy (1996) published by the Commission of the European Communities reports that between 17 and 22% (close on 80 million people) of the Union’s population are exposed to continuous daytime outdoor noise levels caused by transport above what are generally considered to be acceptable - more than 65 dB(A), which is the level at which people become seriously annoyed during the daytime. Cause : road transport noise stands for the dominant noise source and accounts for 90% of the population exposed to noise levels higher to 65 dB(A). Consequences : Noise can cause annoyance and fatigue, interfere with communication and sleep, reduce efficiency and damage hearing. Anthropogenic activities - especially motorized transportation modes - result in pervasive noise that implies a lessening of both the richness and abundance of the animal species, an alteration of the communication which can threaten the reproduction and predation. ENERGIC-OD, 15 juin 2015 (Changins, Suisse) Noise regulation European NEtwork for Redistributing Geospatial Information to user Communities - Open Data At french level The law n° 92-1444 from 31 december 1992 regarding fight against noise codifies at once the prevention, the reduction and the limitation of both noise emission and propagation susceptible to harming resident health. -
Active Noise Control Over Space: a Subspace Method for Performance Analysis
applied sciences Article Active Noise Control over Space: A Subspace Method for Performance Analysis Jihui Zhang 1,* , Thushara D. Abhayapala 1 , Wen Zhang 1,2 and Prasanga N. Samarasinghe 1 1 Audio & Acoustic Signal Processing Group, College of Engineering and Computer Science, Australian National University, Canberra 2601, Australia; [email protected] (T.D.A.); [email protected] (W.Z.); [email protected] (P.N.S.) 2 Center of Intelligent Acoustics and Immersive Communications, School of Marine Science and Technology, Northwestern Polytechnical University, Xi0an 710072, China * Correspondence: [email protected] Received: 28 February 2019; Accepted: 20 March 2019; Published: 25 March 2019 Abstract: In this paper, we investigate the maximum active noise control performance over a three-dimensional (3-D) spatial space, for a given set of secondary sources in a particular environment. We first formulate the spatial active noise control (ANC) problem in a 3-D room. Then we discuss a wave-domain least squares method by matching the secondary noise field to the primary noise field in the wave domain. Furthermore, we extract the subspace from wave-domain coefficients of the secondary paths and propose a subspace method by matching the secondary noise field to the projection of primary noise field in the subspace. Simulation results demonstrate the effectiveness of the proposed algorithms by comparison between the wave-domain least squares method and the subspace method, more specifically the energy of the loudspeaker driving signals, noise reduction inside the region, and residual noise field outside the region. We also investigate the ANC performance under different loudspeaker configurations and noise source positions. -
Guidelines for Selection and Approval of Noise Barrier Products Final Report
Guidelines for Selection and Approval of Noise Barrier Products Final Report Prepared for: National Cooperative Highway Research Program Project 25-25, Task 40 Prepared by: ICF International 33 Hayden Avenue Lexington, MA 02421 July 2008 The information contained in this report was prepared as part of NCHRP Project 25-25 Task 40, National Cooperative Highway Research Program, Transportation Research Board. Acknowledgement This study was conducted as part of National Cooperative Highway Research Program (NCHRP) Project 25-25, in cooperation with the American Association of State Highway and Transportation Officials (AASHTO) and the U.S. Department of Transportation. The report was prepared by David Ernst, Leiran Biton, Steven Reichenbacher, and Melissa Zgola of ICF International, and Cary Adkins of Harris Miller Miller & Hanson Inc. The project was managed by Christopher Hedges, NCHRP Senior Program Officer. Disclaimer The opinions and conclusions expressed or implied are those of the research agency that performed the research and are not necessarily those of the Transportation Research Board or its sponsors. This report has not been reviewed or accepted by the Transportation Research Board's Executive Committee or the Governing Board of the National Research Council. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by NCHRP, the Transportation Research Board or the National Research Council. i Abstract State departments of transportation (DOTs) have identified a need for guidance on noise barrier materials products. This study identified and reviewed literature relevant to noise barrier materials and products with respect to characteristics, testing, selection, and approval. -
Local Noise Action Plans
Practitioner Handbook for Local Noise Action Plans Recommendations from the SILENCE project SILENCE is an Integrated Project co-funded by the European Commission under the Sixth Framework Programme for R&D, Priority 6 Sustainable Development, Global Change and Ecosystems Guidance for readers Step 1: Getting started – responsibilities and competences • These pages give an overview on the steps of action planning and Objective To defi ne a leader with suffi cient capacities and competences to the noise abatement measures and are especially interesting for successfully setting up a local noise action plan. To involve all relevant stakeholders and make them contribute to the implementation of the plan clear competences with the leading department are needed. The END ... DECISION MAKERS and TRANSPORT PLANNERS. Content Requirements of the END and any other national or The current responsibilities for noise abatement within the local regional legislation regarding authorities will be considered and it will be assessed whether these noise abatement should be institutional settings are well fi tted for the complex task of noise considered from the very action planning. It might be advisable to attribute the leadership to beginning! another department or even to create a new organisation. The organisational settings for steering and carrying out the work to be done will be decided. The fi nancial situation will be clarifi ed. A work plan will be set up. If support from external experts is needed, it will be determined in this stage. To keep in mind For many departments, noise action planning will be an additional task. It is necessary to convince them of the benefi ts and the synergies with other policy fi elds and to include persons in the steering and working group that are willing and able to promote the issue within their departments. -
Noise Reduction Through Active Noise Control Using Stereophonic Sound for Increasing Quite Zone
Noise reduction through active noise control using stereophonic sound for increasing quite zone Dongki Min1; Junjong Kim2; Sangwon Nam3; Junhong Park4 1,2,3,4 Hanyang University, Korea ABSTRACT The low frequency impact noise generated during machine operation is difficult to control by conventional active noise control. The Active Noise Control (ANC) is a destructive interference technic of noise source and control sound by generating anti-phase control sound. Its efficiency is limited to small space near the error microphones. At different locations, the noise level may increase due to control sounds. In this study, the ANC method using stereophonic sound was investigated to reduce interior low frequency noise and increase the quite zone. The Distance Based Amplitude Panning (DBAP) algorithm based on the distance between the virtual sound source and the speaker was used to create a virtual sound source by adjusting the volume proportions of multi speakers respectively. The 3-Dimensional sound ANC system was able to change the position of virtual control source using DBAP algorithm. The quiet zone was formed using fixed multi speaker system for various locations of noise sources. Keywords: Active noise control, stereophonic sound I-INCE Classification of Subjects Number(s): 38.2 1. INTRODUCTION The noise reduction is a main issue according to improvement of living condition. There are passive and active control methods for noise reduction. The passive noise control uses sound absorption material which has efficiency about high frequency. The Active Noise Control (ANC) which is the method for generating anti phase control sound is able to reduce low frequency. -
Reducing Development Risks in Communications Applications with High-Performance Oscillators. by James Wilson
Next wave in timing innovation Reducing development risks in communications applications with high-performance oscillators. By James Wilson. s optical networks, hyperscale In addition, 56G PAM4 PHYs, offer any-frequency synthesis, ultra-low data centres and mobile 100G/200G/400G Ethernet, and jitter of 80fs rms and are available in A fronthaul/backhaul networks 100G/400G OTN require a more standard, small form factor oscillator move to higher data rates to support diverse mix of frequencies, increasing footprints. By providing best-in-class rapidly increasing Internet traffic timing complexity. jitter margin and frequency flexibility, demands, SerDes reference clock The Si54x Ultra Series of oscillator the Ultra series is intended to make it performance is becoming increasingly products from Silicon Labs is easy for hardware designers to de-risk important. purpose-built to address the needs product development. If reference clock jitter is too high, of these demanding high-speed The device can be programmed it results in unacceptably high system communications and data centre and customised to meet the target bit-error rate (BER), lost traffic or loss applications. frequency during outgoing test and, of system communication. These high-performance oscillators by using this approach, the Si54x can be mass customised in order to meet High-speed communications and data centre timing requirements each customer’s requirements. The Si54x Ultra series supports Target Reference clock any frequency from 200kHz to 1.5GHz, Standard Data Rate frequencies max phase jitter* enabling a single product family to support both standard and custom CEI-28G 28Gbit/s 106.25MHz 150fs frequency applications. CEI-56G PAM4 56Gbit/s 125.00MHz 150fs Designed in 55nm CMOS technology, the fourth generation 100G Ethernet 4x25.8Gbit/s 156.25MHz 180fs DSPLL leverages a highly digital CAUI-4 4x25.8Gbit/s 161.13281MHz 240fs architecture to deliver improved 16G Fibre Channel 14.0Gbit/s 175MHz 240fs frequency flexibility and jitter performance.