Design of a dynamic positioning for unmanned surface vehicles using GPS/INS (VIAM-NAVI-M)

Today, Unmanned Surface Vehicles (USV) maintain the direction and fixed position necessary for many different applications such as security patrol, transmit information, water sampling, environmental monitoring... With USV model with two hull, control and propulsion systems, both of which are specifically designed to allow the vehicel to perform this task flexibly, omnidirectional and maneuverable. With environmental effects, such as wind, waves and currents ..., it has a large impact on ships, leading to large errors or fluctuations. Therefore, a controller designed to produce better performance for USV under changing noise conditions is essential. To improve the ability of navigation for vehicles, Viam-Navi-M GPS/INS Module: integration of Inertial Navigation System (INS) and Global Positioning System (GPS) is developed with low-cost, highly accurate and stable navigation system. At the same time, the article will present the process of system development and software architecture design. Finally, with the four engine and controller propulsion system built and tested, it shows that the boat is well controlled, its ability to maintain specific direction and position for long periods of time. The postion error is maintained less than 1 meter most of the experimental time and the heading error is between -5 and +5 degrees.

A Nonlinear Radiometric Normalization Model for Satellite Imgaes Time Series Based on Artificial Neural Networks and Greedy Algroithm

Satellite Image Time Series (SITS) is a data set that includes satellite images across several years with a high acquisition rate. Radiometric normalization is a fundamental and important preprocessing method for remote sensing applications using SITS due to the radiometric distortion caused by noise between images. Normalizing the subject image based on the reference image is a general strategy when using traditional radiometric normalization methods to normalize multi-temporal imagery (usually two or three scenes in different time phases). However, these methods are unsuitable for calibrating SITS because they cannot minimize the radiometric distortion between any pair of images in SITS. The existing relative radiometric normalization methods for SITS are based on linear assumptions, which cannot effectively reduce nonlinear radiometric distortion caused by continuously changing noise in SITS. To overcome this problem and obtain a more accurate SITS, we propose a nonlinear radiometric normalization model (NMAG) for SITS based on Artificial Neural Networks (ANN) and Greedy Algorithm (GA). In this method, GA is used to determine the correction order of SITS and calculate the error between the image to be corrected and normalized images, which avoids the selection of a single reference image. ANN is used to obtain the optimal solution of error function, which minimizes the radiometric distortion between different images in SITS. The SITS composed of 21 Landsat-8 images in Tianjin, China, from October 2017 to January 2019 was selected to test the method. We compared NMAG with other two contrast methods (Contrast Method 1 (CM1) and Contrast Method 2 (CM2)), and found that the average root mean square error (μRMSE) of NMAG (497.22) is significantly smaller than those of CM1 (641.39) and CM2 (543.47), and the accuracy of normalized SITS obtained using NMAG increases by 22.4% and 8.5% compared with CM1 and CM2, respectively. These experimental results confirm the effectiveness of NMAG in reducing radiometric distortion caused by continuously changing noise between images in SITS.

Social context and noise affect within and between male song adjustments in a common passerine

Across populations, animals that inhabit areas with high anthropogenic noise produce vocalizations that differ from those inhabiting less noisy environments. Such patterns may be due to individuals rapidly adjusting their songs in response to changing noise, but individual variation is seldom explored. Therefore, we tested the hypothesis that male house wrens (Troglodytes aedon) immediately adjust their songs according to changing noise and that social context further modifies responses. We recorded songs, quantified noise, and defined social context within pairs as female fertile status and between males as number of conspecific neighbors. We used a reaction-norm approach to compare song trait intercepts (between-male effects) and slopes (within-male effects) as a function of noise. Individuals immediately adjusted song duration in response to changing noise. How they achieved adjustments varied: some sang shorter and others longer songs with greater noise, and individuals varied in the extent to which they adjusted song duration. Variation in song duration could be affected by competition as between-male noise levels interacted with number of neighbors to affect syllable duration. Neither within- nor between-male noise effects were detected for frequency traits. Rather, males with fertile mates sang lower-frequency songs and increased peak frequency with more neighbors. Among males, social context but not noise affected song frequency, whereas temporal structure varied between and within individuals depending on noise and social factors. Not all males adjusted signals the same way in response to noise, and selection could favor different levels of variation according to noise.

The Effects of Cracks and Fluids on Post-Seismic Healing

<p>It is now well established that large seismic events change the surrounding velocities, and that these velocities slowly recover over time.  Precisely which mechanisms control the recovery process are less well understood.  We present the results of laboratory experiments to better characterise what properties of the underlying material control the recovery process.  We do this by mixing two waves, one which perturbs the velocity of the sample (as an earthquake does in field data) and one which senses the change in velocity (as in changing noise correlations).  This is an inherently nonlinear experiment as we mix two waves and measure the effects of this wave mixing.  Within our experiments, we vary the properties of the samples to understand which are most important in controlling the nonlinear response.  We focus on two mechanisms.  The first is fractures and how changes in fracture properties change the nonlinear response.  The second is fluids, in particular the effect of low saturations on the nonlinear response.  By changing the fluids and fractures we can turn on and off the nonlinear mechanism, helping us to move toward a better understanding of the underlying mechanisms of these wave-wave interactions.</p>

Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: a case study in Svalbard

Time-lapse monitoring of the subsurface using ambient seismic noise is a popular method in environmental seismology. We assess the reliability of the horizontal-to-vertical spectral ratio (HVSR) method for monitoring seasonal permafrost active layer variability in northwest Svalbard. We observe complex HVSR variability between 1 and 50 Hz in the record of a temporary seismic deployment covering frozen and thawed soil conditions between April and August 2016. While strong variations are due to changing noise conditions, mainly affected by wind speed and degrading coupling of instruments during melt season, a seasonal trend is observed at some stations that has most likely a subsurface structural cause. A HVSR peak emerges close to the Nyquist frequency (50 Hz) in beginning of June which is then gradually gliding down, reaching frequencies of about 15–25 Hz in the end of August. This observation is consistent with HVSR forward modeling for a set of structural models that simulate different stages of active layer thawing. Our results reveal a number of potential pitfalls when interpreting HVSRs and suggest a careful analysis of temporal variations since HVSR seasonality is not necessarily related to changes in the subsurface. In addition, we investigate if effects of changing noise sources on HVSRs can be avoided by utilizing a directional, narrowband (4.5 Hz) repeating seismic tremor which is observed at the permanent seismic broadband station in the study area. A significant change of the radial component HVSR shape during summer months is observed for all tremors. We show that a thawed active layer with very low seismic velocities would affect Rayleigh wave ellipticities in the tremor frequency band. We compile a list of recommendations for future experiments, including comments on network layouts suitable for array beamforming and waveform correlation methods that can provide essential information on noise source variability.

Sleep deprivation in Intensive Care Unit – systematic review

BackgroundSleep disturbances in intensive care unit (ICU) patients have been studied worldwide for over 30 years. Factors contributing to sleep disturbances are still being identified, and therapeutic procedures aimed at the mitigation of such ailments are consequently being developed.ObjectivesThe aim of this study was to review the literature on sleep disturbances in intensive care unit patients.Material and MethodsMEDLINE PubMed, OVID, Web of Science, and EBSCO databases have been searched using adequate keywords.ResultsSleep disorders in ICUs were common among all of the analysed articles. Noise plays a significant role in sleep interruption (11.5 - 17% of awakenings). It was noted that the introduction of “white noise” into the ICU environment proved unsuccessful in reducing the magnitude of changing noise levels. Nursing care activities significantly disturb nocturnal rest, and 42.7 such procedures per every 12-hour night shift were registered. Aggregating nursing care interventions was suggested in order to reduce the number of stimuli experienced by the patient.ConclusionChanges in sleep structure developing during an ICU stay may significantly contribute to sleep disorders once the hospitalisation is over.

Averaging principles for SPDEs driven by fractional Brownian motions with random delays modulated by two-time-scale Markov switching processes

This work considers stochastic partial differential equations (SPDEs) driven by fractional Brownian motions (fBm) with random delays modulated by two-time scale Markov switching processes leading to a two-time scale formulation. The two-time scale Markov chains have a fast-varying component and a slowly evolving component. Our aim is to obtain an averaging principle for such systems. Under suitable conditions, it is proved that there is a limit process in which the fast changing “noise” is averaged out. The slow component has a limit that is an average with respect to the stationary distribution of the fast component. The limit process is substantially simpler than the original system leading to reduction of the computational complexity.

Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: A case study in Svalbard

Time-lapse monitoring of the sub-surface using ambient seismic noise is a popular method in environmental seismology. We assess the reliability of the Horizontal-to-Vertical Spectral Ratio (HVSR) method for monitoring seasonal permafrost active layer variability in northwest Svalbard. We observe complex HVSR variability between 1 and 50 Hz in the record of a temporary seismic deployment covering frozen and thawn soil conditions between April and August 2016. While strong variations are due to changing noise conditions, mainly affected by wind speed and degrading coupling of instruments during melt season, a seasonal trend is observed at some stations that has most likely a sub-surface structural cause. A HVSR peak emerges close to the Nyquist frequency (50 Hz) in beginning of June which is then gradually gliding down, reaching frequencies of about 15–25 Hz in the end of August. This observation is consistent with HVSR forward-modeling for a set of structural models that simulate different stages of active layer thawing. Our results reveal a number of potential pitfalls when interpreting HVSRs and suggest a careful analysis of temporal variations since HVSR seasonality is not necessarily related to changes in the sub-surface. We compile a list of recommendations for future experiments, including comments on network layouts suitable for array beamforming and waveform correlation methods that can provide essential information on noise source variability. In addition, we investigate if effects of changing noise sources on HVSRs can be avoided by utilizing a directional, narrow-band (4.5 Hz) repeating seismic tremor which is observed at the permanent seismic broadband station KBS in the study area. A significant change of the radial component HVSR shape during summer months is observed for all tremors. We show that a thawn active layer with very low seismic velocities would affect Rayleigh wave ellipticities in the tremor frequency band.

Personal listening habits and the potential for hearing loss of Canadian university students

Rationale: Personal and external factors, such as earphone type and music preference, can influence music volume adjustment beyond safe levels. The present study attempted to identify which factors are most influential on volume adjustment. Method: A cross-sectional survey of university students (n = 75) who use personal listening devices (PLD) was performed. Additionally, each participant's PLD music volume was measured through their earphones. Results: On average, participants listened to music at safe (<85 dB) but high levels (79.8 dB) for generally less than four hours per day. Nearly 60% of respondents used earbuds and half preferred “noisy” music genres such as hip-hop and rock/folk. The vast majority of respondents indicated listening to music while travelling by bus for the purpose of blocking out environmental noise or out of boredom. About 75% of the participants were categorized as “pro-noise”. Most students claimed to respond to changing noise environments by adjusting music volume, but few enabled PLD built-in volume controls. Impact: This study determined that earphone type, listening environment, music genre, and listening duration were influential on an participants’ adjustment of music volume. Further research is needed to assess earphone quality and to clearly elucidate more complex associations between external or personal factors and volume adjustment.