Magnetotellurics is an exploration method which is based on measurement of natural electric and magnetic fields of the Earth and is increasingly used in geological applications, petroleum industry, geothermal sources detection and crust and lithosphere studies. In this work, discrete wavelet transform of magnetotelluric signals was performed. Discrete wavelet transform decomposes signals into coefficients in multi-scales. noise and signal portions are separable in multi-scale mode. Therefore, noise can be discarded in each scale; a threshold value is constructed dependent to coefficients of the scale then, the noise coefficients are discarded by thresholding the coefficients with the proper values. Proportional threshold values can be used to remove white and 1/f noise from time series. After that, a new signal is constructed using clean coefficients. This method is widely used in various fields of sciences from image processing to seismic studies. This work tried to show the effectiveness of this technique in decreasing pervasive noise from magnetotelluric signals. The results emphasized the advantageous effect of wavelet techniques in magnetotelluric data noise removing process.

This paper is concerned with the tele-operation of autonomous vehicles over analog Additive white Gaussian noise (AWGN) channel, which is subject to transmission noise and power constraint. The nonlinear dynamic of autonomous vehicles is described by the unicycle model and is cascaded with a bandpass  lter acting as encoder. Using the describing function method, the nonlinear dynamic of autonomous vehicles is represented by an approximate linear system. Then, the available results for linear control over analog AWGN channel are extended to account for linear continuous time systems with non-real valued and multiple real valued eigenvalues and for tracking a non-zero reference signal. Subsequently, by applying the extended results on the describing function of autonomous vehicles, a mean square control technique including an encoder, a decoder, and a controller is presented for reference tracking of the tele-operation of autonomous vehicles over AWGN channel. The satisfactory performance of the proposed control technique is illustrated by computer simulations.

Background: white noise (WN), because of its unique behavior and characteristics, has different applications in different sciences. Nevertheless, the results of studies and reviews of the literature on occupational safety and health found that this type of noise is often used as a noise source to assess the effects of hearing and its physi-cal characteristics. Its possible applications in this area have not received as much attention. The present review study aimed to answer the question, "Can WN be used as a means of promoting occupational safety and health at the workplace? ". Methods: In this review, we reviewed the articles published in reputable databases from 1990 to 2020. Our study included 33 articles from 120 that were searched in full text and followed the inclusion and exclusion cri-teria. Results: Various applications were examined, including noise masking, white noise therapy, cognitive functions, and sleep. WN can enhance the work environment and meet occupational safety and health objectives based on the study's results. The results of this study will provide a basis for continuing research into the use of WN in the workplace as an engineering and management control method. Conclusion: WN is being used in various fields that may hold promise for its application in occupational health sciences and maintaining the well-being of workplace workers.

This paper is concerned with state tracking as well as reference tracking of nonlinear dynamic systems with process and measurement noise over the Additive white Gaussian noise (AWGN) channel which is subject to transmission noise and transmission power constraints. The AWGN channel is a continuous alphabet channel. Therefore, this channel is very suitable for controlling dynamic systems over wireless communication links. To address these problems, a novel encoder, decoder and controller by implementing a novel linearization method for linearizing the nonlinear dynamic systems on operating points are proposed. This method compensates for communication imperfections and maintains real-time state and reference tracking at the end of the communication link. For identifying the exact time of linearization in the encoder and decoder, the Monte-Carlo approximation is applied. Using the Monte-Carlo approximator provides a possible approximation of the estimation error in the encoder and decoder at the same time. The linearization method is based on the variable (optimal) linearization rate. A proper encoder, decoder and controller for real-time state estimation and reference tracking are proposed. The nonlinear dynamic systems which were considered in this paper have process and measurement noises. Simulation results illustrate the satisfactory state tracking and reference tracking performances of the proposed technique; while variable linearization technique is used.

The main purpose of this paper is to introduce a new method to analyze the effects of the white and colored noise perturbations on the robotic arms. To show the efficiency of the presented idea the simplest manipulator, two link robotic arm, is considered. Most previous noise analyses of manipulators are done using mechanical or electrical modeling. Applying exact kinematic equations of the robots is the novelty of the proposed research. For this purpose, by adding white and colored noise terms in each angle function of the robotic arm, the end effector linear velocity is studied. Also, mechanical variation's effect on the final velocity in noisy space is considered. The longer the length of the links, the more the noise effect. Analysis of simulation results shows that the root mean square error in 2nd order is more than when angle functions are of the first order. Also, the mean square error is less when colored noise is added in comparison to the white noise. The Matlab programming is used to perform numerical examples to show the efficiency and accuracy of the presented idea.

The effect of personal and attitudinal factors, noise level, hearing status and psychological traits on traffic-related noise annoyance among white-collar employees working in Tehran has been carefully analyzed. This survey has been conducted by interviewing 495 citizens working in non-manufacturing industries in Tehran, using questionnaires, Weinstein noise sensitivity scale, Beck’s depression, Buss and perry’s aggression, Zung’s anxiety, job satisfaction and Eysenc’s personality inventory. These citizens were office workers or store employees. noise annoyance was determined both by numerical-based questionnaire criterion and by verbal index. Personal information, attitudinal factors and hearing conditions were determined using a general questionnaire. The amount of workplace noise the participants were exposed to was directly measured at their workplaces. It was revealed that among personal factors, age (p=0.030), marital status (p=0.004), residential period (p=0.001) and wealth (p=0.04) were related to noise annoyance. Attitudinal factors including sensitivity to noise (p=0.001), individual’s opinion on the need to control the noise (p=0.000) and individuals’ assessment of the amount of the workplace ambient noise (p= 0.000) were found to have relationship with noise annoyance. No meaningful relationship was seen between the equivalent noise level (p=0.879) and statistical noise level of L90 (p=0.909). The present study revealed that among all effective factors involved in noise annoyance, attitudinal factors had the most significant role in this regard.

Introduction: Sleep disorders are a common problem in patients in the critical care unit. The objective of the present study was to determine the effect of white noise on the quality of sleep in patients admitted to the CCU.Methods: The present study was single-blind, quasi-experimental study. A total of 60 patients were selected using the purposive sampling method. Quality of sleep was measured with PSQI on the first day in admission, then after three nights of admission without any intervention for control group and for the experimental group quality of sleep measured by white noise with intensity of 50-60 dB then Quality of sleep was measured with PSQI. Data were analyzed by SPSS 13 software.Results: The average total sleep time in the control group before the study reached from 7.08 (0.8) to 4.75 (0.66) hours after three nights of hospitalization, while in the experimental group, no significant changes were seen in the average sleep hours (6.69±0.84 vs.6.92±0.89, P=0.15).The average minutes of sleep in the control group before the study reached from 12.66 (7.51) to 25.83 (11.75) minutes after a three- night stay, while in the experimental group, no significant changes were observed in the average sleep duration (12.16±7.50 vs.11±6.07, P=0.16).Conclusion: The use of white noise is recommended as a method for masking environmental noises, improving sleep, and maintaining sleep in the coronary care unit.