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The current sea monitoring equipment's are being used for a variety of purposes around the world. Currently used vehicles have some drawbacks. The first is the high fuel cost. The Vehicle engines cost more fuel as they have to release more power and environment and pollution. As well as not being able to stay under the sea for long days, there will often be a need for vehicles to come to the surface to refuel. The second is the vibrations and noise of these vehicles. The vibrations caused by these can be detrimental to the biodiversity of the ocean. Also, the noise makes it easier for enemies to identify our vehicles. Similarly when these vehicles go under water, water waves form on the surface. With this in mind, radar can detect what a vehicle under the sea looks like. In this paper, an artificial intelligence based microbiological model was proposed to monitor the sea level. With this biological model can greatly reduce fuels. It can get more capacity than normal vehicles. As fuel consumption decreases, so it does environmental pollution and since it operates quietly and without high vibrations, there is no threat to the biodiversity of the ocean. [ABSTRACT FROM AUTHOR]

The evaluation of a soundscape is a challenging task as the object of study is not a stationary event of sensation but rather a dynamic and complex scene stretching over a specific period. To do justice to the time dimension in such acoustic scenes, we utilized the Continuous Evaluation Procedure (CEP). Extending common standard instruments asking participants for a singular integral at the end of the sound experience (e.g., on a rating scale), the participants in this study were enabled to continuously evaluate the evolving acoustic scene of accelerating electrified vehicles (EVs) using CEP. With the increasing electrification of powertrains in the automotive industry, acoustic engineers face the challenge of defining innovative sounds using the availabilities of now low-noise emission platforms of EVs that deviate in their noise profiles from familiar but technologically outdated internal combustion engine vehicles (ICEVs), which have defined the general sound schemes for more than a century. To capture dynamic aspects in the quality perception of powertrain noise in EVs, we asked 37 participants to evaluate acoustic recordings of different vehicles in varying acceleration modes in a high-quality three-dimensional (3D) acoustic simulator. Thereby, we revealed much more detailed and timedependent quality aspects, which do not come forth in an integral singular measure (ISM) where all impressions experienced during the ongoing acoustic scene are blended together. We, therefore, propagate the systematic application of the CEP method when it comes to the qualitative evaluation of transient acoustic scenes. CEP opens the great opportunity to unfold, detect, and analyze dynamic effects in soundscapes and noise profiles, but of any kind of acoustic signal. [ABSTRACT FROM AUTHOR]

Recently, active mounting systems have been applied to automotive engine mounts to effectively mitigate structure-borne vibrations throughout the vehicle chassis. Active mounting systems have been investigated extensively to alleviate the vibration and noise of automobiles; however, the actual engine mounting orientation is not considered, and only an extremely small range of specific vibration and noise control is examined. This paper presents the modeling, analysis, and control of a source structure with an active mounting system while considering the location and direction of actual automotive engine mounts. Two active mounts comprising a piezoelectric stack actuator arranged in series with an elastomeric mount are applied to mitigate both vertical and horizontal vibrations by setting a variable parameter via the dynamic relation of the source structure. When harmonic excitation forces are employed, the secondary force required by each active mount can be calculated mathematically, and a control signal is applied to reduce vibrations through destructive interference with the input signal. Simulation results show that the excitation vibration can be reduced using this bidirectional active mount. Hence, noise vibration harshness is expected to be improved by controlling the vibration of the actual automotive engine structure and the secondary force of actuators. [ABSTRACT FROM AUTHOR]

Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both data quality and quantity. In response to these considerations, this paper introduces an innovative approach for predicting vehicle road noise by integrating mechanism-driven and data-driven methodologies. Specifically, a series model is devised, amalgamating mechanism analysis with data-driven techniques to predict vehicle interior noise. The simulation results from dynamic models serve as inputs to the data-driven model, ultimately generating outputs through the utilization of the Long Short-Term Memory with Autoencoder (AE-LSTM) architecture. The study subsequently undertakes a comparative analysis between different dynamic models and data-driven models, thereby validating the efficacy of the proposed series vehicle road noise prediction model. This series model, encapsulating the rigid-flexible coupling dynamic model and AE-LSTM series model, not only demonstrates heightened computational efficiency but also attains superior prediction accuracy. [ABSTRACT FROM AUTHOR]

A water-lubricated rubber stern bearing causes frictional vibration and noise under extreme conditions, severely threatening the survivability and concealment performance of underwater vehicles. To investigate the mechanism of friction-induced vibration and noise, a four-degree-of-freedom nonlinear dynamic model that included bearing support vibration, frictional bearing vibration and torsional shaft vibration was proposed. The velocity-dependent Stribeck friction model described the dynamic friction characteristics between the rubber bearing and stern shaft. Nonlinear system stability was examined using the Lyapunov indirect method and the transient dynamic responses determined by the Runge-Kutta method. Meanwhile, a high-speed in situ measurement experimental study was adopted to explore the mechanism of frictional and torsional vibrations in a water-lubricated bearing-shaft system. Results showed that nonlinear friction excitation was the fatal cause of friction-induced vibration in bearing-shaft system. Under different friction excitations, the coupling vibrations formed between the bearing and bearing support were different, resulting in two main modes of friction-induced vibration: "Chatter" and "Squeal." The frictional vibration of the bearing and torsional vibration of the stern shaft were tightly coupled. These trends and results might provide a theoretical basis for further research on frictional vibration and wear control in water-lubricated rubber bearing-shaft systems. [ABSTRACT FROM AUTHOR]

Featured Application: The research of propagation characteristics can provide a significance and value for McPherson suspension system design. Tire cavity resonance noise (TCRN) is one of main contributors to vehicle interior noise, which has long been a concern in the automotive industry and academia. As suspension is crucial for the propagation of TCRN energy into the vehicle, the propagation characteristics of energy in automobile suspension is studied in this research. Firstly, the finite element model of a McPherson suspension system connected to an aluminum alloy wheel with a Y-shaped spoke was established. Then, a modal analysis and response calculations of the McPherson suspension system connected to the aluminum alloy wheel with a Y-shaped spoke were carried out. Finally, the propagation characteristics of TCRN in the McPherson suspension system connected to the aluminum alloy wheel with a Y-shaped spoke were studied and analyzed by the power flow method under different working conditions. The power flow output via the lower arm front bushing was the largest, while the output via the rear bushing was the smallest in the Y-spoke aluminum alloy wheel and suspension system. The areas in the suspension system with high stress are located at the steering knuckle, lower swing arm, and shock absorber. Therefore, study of the propagation characteristics can provide a basis for a McPherson suspension system design. [ABSTRACT FROM AUTHOR]

The association of atmosphere and wildlife population is prominent in ecological management strategies. Meteorological changes do not only determine the behavioral activity of wildlife, rather also play a major role in surviving them in their habitats. Many bird species survive climatic conditions, such as extreme temperature situations through migratory movements to other areas with conducive climate. The coastal region of Cameroon is rich in bird population and species, but very little studies have been carried out on their inventory, social organization, and ecological impact on their behavior. Hence, the aim of this study was to assess the impact of meteorological conditions on the behavioral activity of birds in Limbe Botanic Garden. Research data was collected each day from 8:00 am - 5:00 pm, for three months. Both behavioral activity and atmospheric environmental factors were collected simultaneously. In the study meteorological conditions showed a significant association, X² = 23.352 df=6 P=0.001, X² = 5.751 df=6 P<0.05, and X² = 43.227 df=45 P<0.05 on automobile traffic noise, food type, and bird type respectively. More so, meteorological conditions recorded 59% on sunshine, 24% on rainfall, 11% on cloud, and 6% on wind respectively. The most observed birde were African thrush (Turdus pelios) 18%, common bulbul (Pycnonotus barbatus) 13%, and grey-backed camaroptera (Camaroptera brevicaudata) 11%, while the least observed were grey-crowned negrofinch (Nigrita canicapillus) 2%, black-and-white mannikin (Lonchura bicolor) 2%, and african palm swift (Cypsiurus parvus) 2% respectively. Also, bird type showed a positive significance X² = 19.682 df=15 P<0.05 on landscape. Furthermore, landscape revealed a positive correlation significance r = 0.102 P<0.05, and r = 0,308 P=0.023 on meteorological conditions and food type respectively. The study examined three key birds' activity, feeding 39%, movement 37%, and roosting 24% respectively. However, the rich floral vegetation with many bird species is a key attraction to research and tourism in the garden. Most of the bird species in this garden are sea birds, since the garden is adjacent to the sea. Finally, the study recommends an inventory on the population of birds in the garden in order to enhance their conservation. Understanding the number of bird species, their population and ecology is important to wildlife conservation management plan. [ABSTRACT FROM AUTHOR]

Noise from cars is one of the main sources of harmful pollution. In the presented paper, an octave frequency band analysis is conducted according to standard methods of external and internal noise measurement. Experiments at different speeds, with three types of cars--conventional gasoline (GV), hybrid (HEV) and pure electric (BEV)--were carried out on two types of pavement--damaged coarse-grained and smooth fine-grained asphalt. The results show variations in external and internal noise levels vs. speed in different octave bands. At each speed, a spectral analysis was done. The diagrams with results show changes in noise level vs. speed and the positions of noise maximums. Regression models for the octave spectrum at different speeds and pavements are developed. [ABSTRACT FROM AUTHOR]

The contribution analysis of various automobile noise sources to the interior noise is important, enabling to design an automobile with a low interior noise level. However, it is difficult to experimentally analyze the contribution of physically meaningful noise sources to the interior noise using the state-of-the-art contribution analysis method, for example, based on the transmissibility matrix method and the singular value decomposition (SVD), since the source strengths decomposed by using the SVD procedure are difficult to be associated with physical sources. Here, it is proposed to decompose an interior noise auto-spectrum into multiple auto-spectra, each represents the contribution of a physically meaningful noise source to the interior noise, by using the LDL decomposition. Through an experiment with the three speakers driven by three independent, filtered random noise signals, it was shown that the measured noise spectrum could be successfully decomposed into three contributions, each associated with noise radiated from only one speaker. Then, an automobile instrumented with 64 exterior and 4 interior microphones was tested on a highway at the speeds of 65 miles per hour (mph) and 80 mph. The contribution results obtained by processing the measured microphone signals indicated the highest contributions of the aeroacoustic sources on the windows and the hood to the interior noise. [ABSTRACT FROM AUTHOR]

Semi-supervised learning (SSL) is a widely used model training paradigm that effectively utilizes a limited set of labeled data and a substantially larger pool of unlabeled data. Historically, the focus of SSL research has predominantly been on classification tasks, employing methods such as consistency regularization and pseudo-labeling. However, the direct application of these methods to regression tasks presents significant challenges, primarily due to the complexities associated with evaluating the reliability of pseudo-labels in a regression context. This paper introduces SimRegMatch, a novel semi-supervised regression (SSR) framework devised to overcome this specific challenge, by combining an uncertainty-based filtering mechanism with a similarity-based pseudo-label calibration approach. The former component is tasked with discerning which unlabeled examples possess pseudo-labels of sufficient reliability, achieved through the estimation of uncertainty levels. The latter component then refines these pseudo-labels by propagating information from labeled to unlabeled examples, thereby enhancing the overall quality of the pseudo-labels. The efficacy of SimRegMatch was rigorously tested through experiments conducted on the publicly available AgeDB dataset, which is centered around age prediction, as well as on a practical regression problem focused on the detection of interior noise levels in automobiles using accelerometer data. When benchmarked against current state-of-the-art methods in semi-supervised regression, SimRegMatch exhibited notable improvements in regression performance. Additionally, a series of ablation studies were carried out to dissect and understand the specific elements of the framework that were instrumental in achieving these performance enhancements. SimRegMatch addresses a pivotal issue in semi-supervised regression – the assessment of regression pseudo-label reliability – and substantially elevates model performance. By combining the strengths of uncertainty estimation and pseudo-label calibration, SimRegMatch emerges as a robust and versatile framework with significant potential for broad applicability in various SSR scenarios. A PyTorch implementation is publicly available at https://github.com/YongwonJo/SimRegMatch. • Uncertainty-based filtering is used to select examples with reliable pseudo-label. • Similarity-based pseudo-label fuse information from labeled and unlabeled examples. • Calibrated pseudo-labels using labeled data improve regression performance. [ABSTRACT FROM AUTHOR]

Vibration isolation technology is one of the main methods for controlling the vibration and noise of underwater vehicles. This paper presents a vibration analysis and vibration isolator component design method of the power system in autonomous underwater gliders (AUGs). The dynamic models of the single-layer and double-layers vibration isolation systems of the power system of the AUG are established to analyze the force transfer rate in the system. A reasonable stiffness range of the vibration isolation system is obtained according to the results of the dynamic model. To validate the vibration isolation performances of the presented vibration isolation systems, the finite element (FE) models of single-layer and double-layers vibration isolation systems are established. The vibration responses and vibration isolation performances of the system with and without the rubber isolation systems are compared. Moreover, the effect of stiffness on the vibration isolation performances of the system is discussed. The presented results can provide some guidance for the design method of the vibration isolation system in the power system of AUGs. [ABSTRACT FROM AUTHOR]

To reduce the intake noise of automobile engines, an active control system model of engine intake noise is established with the Filtered-x least mean square (FxLMS) algorithm. The offline identification method is adopted to identify the secondary path. The engine speed signal is used to construct the reference signal of a sound source to avoid interference of a secondary sound source to the reference signal. A variable-step algorithm is proposed, in which parameters are added to the normalized algorithm instead of the sinusoidal variable-step algorithm to adjust the amplitude range. This algorithm not only has the advantages of fast convergence speed and small steady-state error but also adapts to the characteristics of a time-varying reference signal and easy selection of parameters. In this paper, the noise of automobile engines under the New European Driving Cycle (NEDC) is studied and the proposed algorithm has faster convergence speed compared with the normalization algorithm, better adaptability to the change of the reference signal, and better stability compared with the sinusoidal variable step-size algorithm. The results show that the algorithm proposed can effectively reduce the intake noise of the engine at each speed and the noise reduction effect can reach 23.11 dB at a certain frequency. Meanwhile, the stability of the system is improved. [ABSTRACT FROM AUTHOR]

The use of battery tools is very common in many fields of work. In fact, the electric engine and batteries have several advantages over traditional endothermic engines, including low emissions, in terms of pollutants, vibration and noise. In this context, the chainsaw market started producing electric models powered by batteries. These machines can be useful in forestry, but information on their performance is scarce. The aim of this work was to compare the performance, in terms of cutting times, of three Stihl chainsaw models: the MS 220C-B (battery powered), and the MS 201 C-M and MS 261 C-M (both petrol powered). The study was carried out on five different wood species, also taking into consideration the presence/absence of wood defects in the cutting. More than 800 cuts on 15 m × 15 cm wood beams were video recorded, and the cutting times were later obtained to a resolution of 4/100 of a sec, using video-editing software. The results showed a poorer performance of the battery chainsaw than the petrol chainsaws, especially on certain wood species. However, this difference has been reduced when compared with older models. In conclusion, battery chainsaws need some additional improvements to be introduced into forestry, but their high potential is evident. [ABSTRACT FROM AUTHOR]

With the transformation of the trend of vehicle electrification, the overall noise level in the vehicle is gradually reduced. The problem of low-frequency noise in the vehicle, which was previously ignored, is becoming more and more prominent. To solve the vehicle low-frequency noise problem, a combination of real-vehicle tests and simulation analysis is carried out. During the test, the driver and passengers feel that there is a relatively obvious low-frequency roar noise in the car, which results from the structural radiation noise of the trunk door vibration. Therefore, to solve this problem, we design an acoustic metamaterial with lightweight and miniaturized features based on the local resonance principle of phononic crystals. Firstly, the selection of the resonant unit configuration and the design of the band gap are implemented. Then, the layout planning of the whole vehicle, the layout of the resonance unit and the design of the base frame are implemented. The actual vehicle test results show that: after attaching the designed acoustic metamaterial, the low-frequency noise sound pressure levels in the front and rear of the vehicle were reduced by 2.0 dB (A) and 2.3 dB (A), respectively, meanwhile, the interior noise sound quality was improved. The sound pressure level at the driver's right ear in the car has an abnormal peak of around 35Hz. In addition, the driver and passengers feel that there is a relatively obvious low-frequency roar noise in the car, and through low-pass filtering of the collected signals, it is confirmed that the peak frequency is the main cause of the low-frequency roar in the car. The low-frequency steady-state noise of the car is generally considered to be the low-frequency vibration of the body panel and the radiation occurs. Through the finite element simulation analysis (Grid Participation Analysis) of the abnormal peak frequency, the results show that the low-frequency roar is caused by the low-frequency vibration of the tailgate sheet metal, and the problem peak frequency is not coupled with the acoustic cavity mode. Facing the problem of the low-frequency roar radiated into the car by the vibration of the tailgate sheet metal parts, based on the local resonance band gap theory, we developed a design to suppress the 35 Hz vibration of the tailgate sheet metal parts and meet the characteristics of lightweight and miniaturization. By attaching the acoustic metamaterial to the tailgate and performing CAE simulation of the whole vehicle, it is determined that the structure can indeed reduce the 35 Hz noise in the car and the peak value of the tailgate sheet metal vibration. [ABSTRACT FROM AUTHOR]

Transport policy represents a process of regulating and controlling the provision of transport services. In the past, the main emphasis was on the efficient transport connections and safety of drivers and other participants in transportation. These issues are still important and topical; however, due to the enormous increase of vehicles on the streets and harmful gas emissions, noise, congestions, and other negative effects of transportation, some other topics emerged that need to be considered in the design of sustainable development strategies, especially in big cities. This explanation leads to the conclusion that setting a transport policy represents a typical multi-criteria decision-making problem. There are usually certain alternative directions in the design of transport policy that should be assessed by more evaluation criteria, often opposed to each other. This is exactly the problem that is considered in this paper where three concepts of last-mile delivery of postal items are analyzed as the possible directions in the design of transport policy in cities. We applied three multi-criteria decision-making techniques: WASPAS, ARAS, and CoCoSo. The proposed methodology is tested and verified in a real-life case study considering the city of Niš. In the concrete case, the results showed that the best alternative in the design of last-mile delivery activities at the city level is the introduction of inner-city hubs. [ABSTRACT FROM AUTHOR]

Accurate and efficient environmental awareness is a fundamental capability of autonomous driving technology and the real-time data collected by sensors offer autonomous vehicles an intuitive impression of their environment. Unfortunately, the ambient noise caused by varying weather conditions immediately affects the ability of autonomous vehicles to accurately understand their environment and its expected impact. In recent years, researchers have improved the environmental perception capabilities of simultaneous localization and mapping (SLAM), object detection and tracking, semantic segmentation and panoptic segmentation, but relatively few studies have focused on enhancing environmental perception capabilities in adverse weather conditions, such as rain, snow and fog. To enhance the environmental perception of autonomous vehicles in adverse weather, we developed a dynamic filtering method called Dynamic Distance–Intensity Outlier Removal (DDIOR), which integrates the distance and intensity of points based on the systematic and accurate analysis of LiDAR point cloud data characteristics in snowy weather. Experiments on the publicly available WADS dataset (Winter Adverse Driving dataSet) showed that our method can efficiently remove snow noise while fully preserving the detailed features of the environment. [ABSTRACT FROM AUTHOR]

Copyright of Actualidad Jurídica Ambiental is the property of CIEMAT, through its Centro Internacional de Estudios de Derecho Ambiental (CIEDA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present research work analyzes the noise pollution of the automobile fleet in the District of Jesús María located in Lima - Perú. The general objective was "To determine the incidence of the application of Ordinance N° 310-2009-MDJM. in the noise pollution of the vehicle fleet in the district of Jesús María, 2020" the type of research is applied; descriptive and explanatory level and non-experimental design. The population object of study was constituted by the inhabitants of the district and the floating population, considering a non-probabilistic sample of 210 people. The instruments used were: measurements of sound pressure in fixed stations, counting of public and private vehicles in the time of measurement of good pressure, and a questionnaire that was validated by expert judges, the same one that constituted 32 items of the scale of Likert. The results found in the sound pressure measurements exceeded the maximum sustainability of the analyzed Ordinance, showing noise pollution. The statistical test used was the Spearman correlation coefficient, determining that there are differences in noise pollution at the stations and not at the timetables; that public and private vehicles increase sound pressure measurements under different conditions; concluding that: "The application of Ordinance N° 310-2009-MDJM significantly affects noise pollution in the vehicle fleet in the district of Jesús María, 2020". [ABSTRACT FROM AUTHOR]

Many science departments encourage students to gain experience conducting research. However, finding ecological research projects that allow students to test a hypothesis in the field, over the relatively short time span of a semester, can be challenging. This article describes an inquiry-based research activity examining the influence that urban noise has on the behavior of gray squirrels. One of the consequences of urbanization is increased noise from automobiles and other human activities. This research project allows students to pose hypotheses regarding how squirrel behavior changes in response to human noise and then test those hypotheses. This activity is well suited for students in ecology, animal behavior, or vertebrate biology classes. It allows students flexibility in the hypothesis they test and the methods they use, while giving students a framework that lets them successfully complete a field research project. Students gain experience developing hypotheses, designing a field experiment, writing a research proposal, collecting field data, conducting data analysis, and presenting the results of their project. [ABSTRACT FROM AUTHOR]

The financial system development has got considerable attention due to its association with the environment of the country. To address the apprehension of the researchers about the effect of the determinants of the financial system on the environmental quality of high-income developed countries, we analyze the data of twenty developed countries with sound and strong financial systems for the period 2001 to 2018. We consider both banking development and stock market development as the main key determinants of the financial system. We employ numerous modern-day penal data estimation techniques, namely Dynamic Penal GMM in both linear and non-linear form, Common Correlated Effect Mean Group (CCEMG), and Dynamic Fixed Effect for capturing the issues of heterogeneity, endogeneity, and cross-sectional dependence. Our results show that banking development substantiates the environmental quality in high-income developed countries. The positive gesture of the banking development on environmental quality could be the reason for the established environmentally friendly policies in the developed part of the world. Hence, we conclude that banking development in high-income developed countries significantly reduces the emissions of dangerous gases, which resultantly enhances the environmental quality. The study reveals an insignificant and tenuous impact of the market development on the environmental quality that might be due to the adoption of cleaner technologies by firms in the developed world that are environmentally friendly. The results of our long-term estimations also predict the significant effect of banking development and an insignificant effect of the market development on environmental quality. In addition, our results also demonstrate an inverted U-shaped relationship of the determinants of the financial system and environmental quality. More institutional and legal initiatives must be made for a more robust banking and stock market development framework by the policy makers with a view to substantiating the quality of the environment to a more sustainable level in the developed world. [ABSTRACT FROM AUTHOR]

Featured Application: A slit-type soundproof panel can be applied to attenuate low-frequency noise and withstand wind load alongside traffic roads. With the rapid increase in automobiles, the importance of reducing low-frequency noise is being emphasized for a comfortable urban environment. Helmholtz resonators are widely used to attenuate low-frequency noise over a narrow range. In this study, a slit-type soundproof panel is designed to achieve low-frequency noise attenuation in the range of 500 Hz to 1000 Hz with the characteristics of a Helmholtz resonator and the ability to pass air through the slits on the panel surface for reducing wind load. The basic dimension of the soundproof panel is determined using the classical formula and numerical analysis using a commercial program, COMSOL Multiphysics, for transmission loss prediction. From the numerical study, it is identified that the transmission loss performance is improved compared to the basic design according to the shape change and configuration method of the Helmholtz resonator. Although the correlation according to the shape change and configuration method cannot be derived, it is confirmed that it can be used as an effective method for deriving a soundproof panel design that satisfies the basic performance. [ABSTRACT FROM AUTHOR]

The tidal response of Mars, due to the Sun and the Martian moons, Phobos and Deimos, provides information about the interior structure of Mars. By using the Very Broad Band (VBB) seismometer of Seismic Experiment for Interior Structure (SEIS) as a gravimeter on the surface of Mars, the InSight mission will provide the long‐period data suited to tidal analysis: most notably, the proximity of Phobos implies that degree 2, 3, 4, and further tides will be detectable by the VBB and are expected to provide information about the rheology at different depths within Mars. In order to expedite the recovery of these tidal signals in the SEIS measurements, we model the tides raised by Phobos using a tidal potential deduced from JPL Horizons ephemerides. From this potential, we calculate the expected tidal acceleration at InSight's location and gravimetric factors using a set of plausible interior models of Mars. To simulate the expected long period signal on the VBB seismometer, we use the InSight Auxiliary Payload Sensor Suite data to model the noise seen at low frequency by SEIS mainly due to temperature and pressure variations. Based on this synthetic signal, by applying filtering methods such as stacking and matched filtering to these synthetic data, we show that by recovering the gravimetric factors, it should be possible to constrain the state of the core and its size with an accuracy of 125 km after two Earth years. Plain Language Summary: On Mars since November 26, 2018, the NASA InSight mission made weather measurements of the atmosphere's temperature, wind, and pressure. It has also put a seismometer at the surface of Mars to see Mars quakes. However, the seismometer can also be used to measure the tides due to the Martian moon Phobos: by deforming the surface of the planet, the Phobos tides will create a change in the gravity at the surface of Mars, which can be recorded. As Phobos is closer to Mars than the Moon is to Earth, the shape of the tides on Mars is more complicated, but can be used to determine the interior structure of Mars. In particular, its deepest part, the core, is not well determined: it is still unsure whether it is liquid or solid, and how big it is. We model the expected tides at InSight's location and noises due to temperature and pressure variations based on the measurements made to guess what the seismometer will record. This study shows that after two Earth years, we should be able to see the Phobos tides accurately enough to know the core state and size with an accuracy of 125 km. Key Points: The Phobos tides of degree 2, 3, and 4 should be detectable by the Very Broad Band seismometer on InSight's Seismic Experiment for Interior Structure (SEIS)We model these tides, the Martian interior and SEIS low frequency noise with recent InSight dataOver 2 Earth years, determining the core state and size with 125 km accuracy should be possible [ABSTRACT FROM AUTHOR]

Electric vehicle has got more advantages than normal combustion engine vehicles with no air pollution, no noise, saving energy and reduced carbon dioxide emissions. In general, an electric vehicle runs on rechargeable battery. We charge those batteries from an external power supply, which takes long time to charge completely. Charging stations are not portable and there won't be any charging station in remote areas. In our proposed system we are reducing the time by charging the battery using solar flexible PV modules which help in charging the battery by converting light energy from sun to electrical power. In case of an electric car, flexible solar cells will be stitched with the car cover which helps covering large area of the car providing high energy to charge the battery. The solar cells cannot generate power up to its potential. So, Maximum Power Point Tracker (MPPT) is used to track high power and transfers energy to the battery. With this, in good sunny days, it is possible to charge 40% of battery completely using solar energy. In battery management system in order to increase the life of the battery low-cutoff and high-cutoff circuits are proposed. [ABSTRACT FROM AUTHOR]

A worldwide increase in the number of vehicles on the road has led to an increase in the frequency of serious traffic accidents, causing loss of life and property. Autonomous vehicles could be part of the solution, but their safe operation is dependent on the onboard LiDAR (light detection and ranging) systems used for the detection of the environment outside the vehicle. Unfortunately, problems with the application of LiDAR in autonomous vehicles remain, for example, the weakening of the echo detection capability in adverse weather conditions. The signal is also affected, even drowned out, by sensory noise outside the vehicles, and the problem can become so severe that the autonomous vehicle cannot move. Clearly, the accuracy of the stereo images sensed by the LiDAR must be improved. In this study, we developed a method to improve the acquisition of LiDAR data in adverse weather by using a combination of a Kalman filter and nearby point cloud denoising. The overall LiDAR framework was tested in experiments in a space 2 m in length and width and 0.6 m high. Normal weather and three kinds of adverse weather conditions (rain, thick smoke, and rain and thick smoke) were simulated. The results show that this system can be used to recover normal weather data from data measured by LiDAR even in adverse weather conditions. The results showed an effective improvement of 10% to 30% in the LiDAR stereo images. This method can be developed and widely applied in the future. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to effectively extract the characteristics of nonstationary vibration signals from hydropower units under noise interference, an adaptive stochastic resonance and Fourier decomposition method (FDM) based on genetic algorithm (GA) are proposed in this paper. Firstly, GA is used to optimize the resonance parameters so that the signal can reach the optimal resonance and the signal-to-noise ratio (SNR) can be improved. Secondly, FDM is used to process the signal and the appropriate frequency band function is selected for reconstruction. Finally, Hilbert envelope demodulation analysis was performed on the reconstructed signal to obtain the fault characteristics from the envelope spectrum. In order to prove the effectiveness and superiority of the proposed method, comparative experiments are designed by using the simulated signal and the measured swing signal of a hydropower unit. The results show that this method can effectively remove the noise interference and improve the SNR and extract the characteristic frequency of the signal, which has the extensive engineering application value to the fault diagnosis of hydropower units. [ABSTRACT FROM AUTHOR]

Point cloud filtering is a fundamental problem in geometry modeling and processing. Despite of significant advancement in recent years, the existing methods still suffer from two issues: 1) they are either designed without preserving sharp features or less robust in feature preservation; and 2) they usually have many parameters and require tedious parameter tuning. In this article, we propose a novel deep learning approach that automatically and robustly filters point clouds by removing noise and preserving their sharp features. Our point-wise learning architecture consists of an encoder and a decoder. The encoder directly takes points (a point and its neighbors) as input, and learns a latent representation vector which goes through the decoder to relate the ground-truth position with a displacement vector. The trained neural network can automatically generate a set of clean points from a noisy input. Extensive experiments show that our approach outperforms the state-of-the-art deep learning techniques in terms of both visual quality and quantitative error metrics. The source code and dataset can be found at https://github.com/dongbo-BUAA-VR/Pointfilter. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Characterizing multiple risk stemming from automobiles are required from the viewpoint of priority setting for future risk management. However, little is known about such issues given the inadequacy of indicators. In this research, with the illustration of the metropolitan city of Osaka, Japan, using disability-adjusted life years (DALYs), impacts of road traffic noise and exhausts gas (nitrogen dioxide (NO2) and particulate matter (PM2.5)) were quantified and compared with the risks of ischemic heart disease and high sleep disturbance; and respiratory disease as endpoints, respectively. Health risks due to automobile noise were 3102.1 and 97.8 DALYs under the condition of open and closed windows, respectively. The health risks were reduced by 96.8% under closed-window condition. On the other hand, the health risks caused by NO2 and PM2.5 from automobiles were 137.6 DALYs, which was lower than the health risks due to automobile noise. These results indicate the effectiveness of DALYs as an indicator to characterize different kinds of burden of health and environmental impacts from automobiles, and they were successfully used to evaluate the effectiveness of risk reduction options such as the difference between open and closed windows. Furthermore, most people were found to have been exposed to 55–60 dB noise level. Although they easily get used to and can tolerate this level, it is also the stage at which health risks begin to occur. Therefore, with continuous exposure, qualitative estimation showed that open windows under this noise level subsequently leads to high potential health risks. [ABSTRACT FROM AUTHOR]

This article presents an asymptotically optimal technique for estimating environmental parameters from ocean ambient noise. Noise from wind and breaking waves propagates through the water column and reflects off the bottom over a wide range of angles and frequencies and, in doing so, imparts information about the environment to the noise covariance matrix for a receiver array. Most environmental estimation techniques focus on spatial filtering methods aimed at recovering the vertical noise directionality. However, an often overlooked fact is that the noise covariance matrix fully characterizes the probability density function of each snapshot, which forms the basis for an information-theoretic approach. In this light, it is possible to obtain the theoretical bounds on optimal estimator performance while also providing a basis for assessing the utility of different parameterization schemes. Most importantly, it provides a natural definition for a maximum likelihood estimator that meets the optimal bounds in an asymptotic sense. This technique outperforms beamforming-based methods by a significant margin. It also remains unbiased in the presence of strong white noise, is tolerant to array tilt, can operate beyond the array design frequency, but does suffer greater sensitivity to model mismatch. These trade-offs are explored with simulations and analyses of experimental data. [ABSTRACT FROM AUTHOR]

This study aims to minimize the noise generated by automobile cooling fans. Fan blade structures with ridged surfaces based on bio-inspired principles are 3D printed and used to replace the conventional fan blades. The effect of the bio-inspired ridge structures on the noise reduction of the cooling fan is demonstrated by orthogonal experiments in a semi-anechoic chamber. Experimental results show that with an increase in the rotational speed, the effect of the surface textures on the acoustic performance of the cooling fan becomes more significant. For example, at a fan speed of 1750 r/min, all the bio-inspired blade designs reduce noise compared with the original fan and, in particular, the sound pressure level is reduced by 3.83 dB(A) for the design with a ridge width of 4 mm and a ridge pitch of 15 mm. Through variance analysis of the measured noise, the ridge pitch distance has the most significant impact on noise reduction under low speed conditions whilst, under high speed conditions, the ridge width has the most significant influence. In addition to the experimental studies, computational fluid dynamics (CFD) simulations of the cooling fan are carried out to explain the mechanism of noise reduction for the ridged fan blades. When the fan runs, the horseshoe vortexes generated by the ridge structures disturb the flow of the boundary layer, reduce the influence of the fluid flow on the boundary layer, and delay the transition of the fan blade laminar flow to turbulence. It is also seen that there is a reduction of the intensity of the fan blade trailing edge vortices and the scale of the secondary vortices, thereby achieving the overall aim of noise reduction. This research has significance in the noise reduction design of automobile cooling fans. [ABSTRACT FROM AUTHOR]

Predictors of people's responses to noise inside cars are used by car companies to identify and address potential noise problems from tests. Because significant improvements have been made in engine, powertrain, and tire/road noise, it is now important to pursue improvements in wind or aerodynamic noise.While models of loudness are commonly used to predict people's responses to stationary wind noise, some wind noises are less acceptable than is predicted by loudness metrics. Additional sound characteristics may account for this. Three listening studies were designed to examine the usefulness of including additional sound quality metrics with loudness in models used to predict acceptability for stationary wind-noise sounds. Test sounds were based on recordings made in cars in a wind tunnel. Signalmodification techniques were developed to decorrelate metrics across a set of sounds and to examine howacceptability changes with strengths of particular sound characteristics. Models of acceptability for stationary wind noise are significantly improved when a metric that predicts the sharpness of a sound is included in the model with the loudness metric. [ABSTRACT FROM AUTHOR]

Cloud system‐resolving models (CSRMs) routinely calculate radiative flux profiles via the Independent Column Approximation (ICA). The ICA applies 1D radiative transfer models (RTMs) to all N columns in a CSRM's domain. For this study, the Partitioned Gauss–Legendre Quadrature (PGLQ) method replaced the ICA in a CSRM. The PGLQ applies RTMs to nG=N columns, identified with GLQ rules, and distributes their flux profiles to the other N−nG columns. The PGLQ approach is likened to a lossy compression algorithm that trades information for efficiency. While verification and validation of an audio compression algorithm rest, respectively, on file size reduction and sound quality according to listeners, for the PGLQ they rest on increasing fRT=N/nG while maintaining, according to experimenters, the integrity of CSRM simulations. A CSRM was run for 80 days in radiative‐convective equilibrium (1,024 × 1,024 columns and horizontal grid‐spacing of 0.25 km) for sea‐surface temperature SST = 295 and 300 K; the last 40 days were analysed. Simulations using the ICA represent the control; experiments used the PGLQ calling the RTMs fRT = 200, 5,000 and 50,000 fewer times than the control. For fRT = 50,000, several key variables spanning time/domain‐averaged cloud and radiation properties, a measure of cloud (convection) aggregation, and horizontal fluctuations of cloud and radiation fields, differ significantly from the control. In contrast, corresponding differences between the control and PGLQ with fRT ≤ 5,000, for both a given SST and differences between SSTs, are often minor, in all respects, and appear to be drawn from a single population. While these results partially validate the PGLQ method for fRT ≤ 5,000, they also indicate that overly large reductions in radiative information are detrimental. [ABSTRACT FROM AUTHOR]

Emission is one of the key problems in the automotive industry, which engineers try to eliminate by lowering emissions to the minimum. Transmission emission plays an important part here. The basic characteristics of gears include their shape, load capacity, and emissions. The most significant source of noise and vibration in the gearbox is the step change in the meshing stiffness of the gearing, which depends on the path of meshing at the entry and exit of the meshed teeth. Ensuring a permanent multi-pair mesh is a way to mitigate these step changes as much as possible. This leads to the design and implementation of gears in an integer contact ratio. In addition to this, the article deals with the impact of individual parameters on the stiffness of the gearing, which is a source of noise and vibration. The meshing stiffness of the gearing was determined on the deformation basis of the gearing, as solved by the Finite Element Method. [ABSTRACT FROM AUTHOR]

In order to further promote the development of functional pavement technology, a Special Issue of "Achievements and Prospects of Functional Pavement" has been proposed by a group of guest editors. To reach this objective, articles included in this Special Issue are related to different aspects of functional pavement, including green roads to decrease carbon emission, noise, and pollution, safety pavement to increase skid resistance by water drainage and snow removal, intelligent roads for monitoring, power generation, temperature control and management, and durable roads to increase service life with new theory, new design methods, and prediction models, as highlighted in this editorial. [ABSTRACT FROM AUTHOR]

The outside rear-view mirror (OSRVM) is installed on the vehicle's surface, which causes unwanted aerodynamic noise and wind drag during driving. It is important to use simulation methods to predict the performance of aerodynamic noise and wind drag of commercial vehicles due to the OSRVM. Considering the wind drag of the OSRVM, a combinational simulation strategy is employed to calculate external flow and interior acoustic fields of commercial vehicles, respectively. The flow field is computed a priori with an incompressible flow solver. The acoustic field was then computed based on the information extracted from the CFD solver. To obtain the interior noise level at the driver's ears, a vibroacoustic model is used to calculate the response of the window glass structure and interior cavities, where the unsteady aerodynamic pressure loading on the two side windows' surface is treated as the acoustic source field. The paper provides flow field and acoustic simulations for three OSRVM configuration models. The results are compared to data obtained in road sliding test measurement on the commercial vehicle. The accuracy of the hybrid simulation method is proved, and the comparative analyses verify that the OSRVM B model dramatically reduces the interior noise and wind drag of commercial vehicles. [ABSTRACT FROM AUTHOR]

The environmental concern has become the top trend nowadays and the ideas of environmental protection, green orientation and green innovation, highly concern from the last few decades in all research areas. The construction industry is one of those that has a very strong impact on the environment. Air, water, noise and vibration, as well as soil pollution caused during construction processes, negatively impact on the environment and its natural ecosystems, as well as on humans at a global level. Construction waste generated during the construction, renovation and demolition process occupies huge landfills due to significant volumes. It may also contain substances that are hazardous to the environment and human health. This paper summarizes the research results on the possibilities for more efficient construction waste management as well as the experience of companies operating in the construction sector with a purpose to reduce the causes of pollution. The data obtained within the framework of the survey on people's understanding in the field of construction pollution and waste in Latvia have been analyzed. The main goal of the study is to present the main findings of the authors' survey and to discuss the current construction waste management challenges and potential innovations in Latvia. The authors used the following research methods: literature review, analysis of statistical data; questionnaire creation and conduction a survey; interviews with waste management companies. The research was conducted during the period from October 2019 to July 2020. The obtained results showed that there was a huge potential for innovation because the current situation was far from ideal. The results of an empirical analysis demonstrated that the collection of sorted construction waste on construction sites currently was practically impossible, as the industry points to the human factor in the waste sorting process. Although the data obtained within the framework of the survey clearly indicated the interest of employees in sorting construction waste already on the construction site, waste industry companies currently consider such a practice impossible also due to the influence of other side factors related to economic considerations. It is necessary to develop a normative framework for the implementation of the construction waste certification system to promote the reuse of construction waste in construction as efficiently as possible. [ABSTRACT FROM AUTHOR]

In order to solve the problem of low efficiency and low efficiency of traditional methods, a method based on discrete wavelet is proposed to suppress the torsional vibration noise of automobile transmission system. Based on the operation mechanism of automobile transmission system, the transmission system model is built. In this model, the features of torsional vibration of transmission system were analyzed and the vibration signals were measured. The hardware equipments were used to collect the noise caused by torsional vibration, and then the discrete wavelet processing technology was used to quantify the torsional vibration noise. Based on the quantized noise data, the torsional vibration noise of automobile driveline was suppressed by active suppression and passive suppression. The experimental results show that the suppression time of this method for different noise size is less than 0.5 s, far less than the traditional method. Experimental results prove that the designed noise suppression method can greatly reduce the torsional vibration noise, so it has good application effect. [ABSTRACT FROM AUTHOR]

This work shows that normal-mode attenuation coefficients can be extracted from ship noise and used to estimate the sound speed in gas-saturated sediments. In an experiment in the Sea of Galilee, a research vessel served as a noise source approaching a vertical hydrophone array at a constant speed. Twelve narrow-band components of the vessel noise in the frequency band 20–100 Hz were identified and mode filtered to estimate the normal-mode attenuation coefficients. The inversion results indicate that the sound speed in the sediments was approximately 170 m/s. [ABSTRACT FROM AUTHOR]

Acoustic noise from automobile traffic impedes communication between signaling animals. To overcome the acoustic interference imposed by anthropogenic noise, species across taxa adjust their signaling behavior to increase signal saliency. As most of the spectral energy of anthropogenic noise is concentrated at low acoustic frequencies, species with lower frequency signals are expected to be more affected. Thus, species with low‐frequency signals are under stronger pressure to adjust their signaling behaviors to avoid auditory masking than species with higher frequency signals. Similarly, for a species with multiple types of signals that differ in spectral characteristics, different signal types are expected to be differentially masked. We investigate how the different call types of a Japanese stream breeding treefrog (Buergeria japonica) are affected by automobile traffic noise. Male B. japonica produce two call types that differ in their spectral elements, a Type I call with lower dominant frequency and a Type II call with higher dominant frequency. In response to acoustic playbacks of traffic noise, B. japonica reduced the duration of their Type I calls, but not Type II calls. In addition, B. japonica increased the call effort of their Type I calls and decreased the call effort of their Type II calls. This result contrasts with prior studies in other taxa, which suggest that signalers may switch to higher frequency signal types in response to traffic noise. Furthermore, the increase in Type I call effort was only a short‐term response to noise, while reduced Type II call effort persisted after the playbacks had ended. Overall, such differential effects on signal types suggest that some social functions will be disrupted more than others. By considering the effects of anthropogenic noise across multiple signal types, these results provide a more in‐depth understanding of the behavioral impacts of anthropogenic noise within a species. [ABSTRACT FROM AUTHOR]

The present study dwells the assessment of vibration and noise levels with the use of biodiesel and hydrogen in dual fuel mode in a single-cylinder, 4-stroke CI engine at different compression ratios (16, 17.5, and 18.5). Niger seed oil methyl ester (NSOME) blends B10, B20, and B40 were used as test fuels and conducted the experimental test at full load (12 kgf) by maintaining the constant engine speed of 1500 rpm. Further, the blend B20 was enriched with different hydrogen flow rates of 5 lpm, 10 lpm, and 15 lpm. The vibration (velocity) and noise levels were measured at the engine body and estimated in terms of RMS values for different test fuels. The vibration levels were decreased when operated with NSOME blends, and B20 has shown fewer vibrations at all the compression ratios compared to other test fuels used. Similarly, the noise levels of NSOME blends were observed to be lower than diesel fuel. Further, the vibration and noise levels of B20 were decreased at higher flow rates of hydrogen. For all the test fuels used, the increasing trend of vibrations was observed at higher compression ratios. [ABSTRACT FROM AUTHOR]

The dense seismo-acoustic network of the Institute of Geophysical Research (IGR), National Nuclear Center of the Republic of Kazakhstan, has been operating in Kazakhstan since the late nineties of the last century. It consists of four seismic and three infrasonic arrays. The IGR network includes stations part of several national and global monitoring systems. Infrasonic and seismic data are processed using the Progressive Multi-Channel Correlation (PMCC) detector to characterize the temporal variability of microbarom and microseism signals from 2014 to 2017. The non-linear interaction of ocean waves is simulated using the microseism source model distributed by the French Research Institute for Exploitation of the Sea (IFREMER). The wave attenuation is calculated using a semi-empirical propagation law in a range independent atmosphere. Comparing the observed and predicted seismic and infrasonic signals reveals the dominating directions of arrivals at each station of the IGR network and the associated source regions. Both multi-year and intra-seasonal parameter variations are analysed. The level of low-frequency noise is significantly higher in winter than in summer. In winter, sources of infrasound ambient noise are mainly located in the North Atlantic and in the North Pacific during Sudden Stratospheric Warming (SSW) events. Signals observed in summer, likely originating from source regions in the southern hemisphere, are discussed. [ABSTRACT FROM AUTHOR]