Non-asymptotic error estimates for the Laplace approximation in Bayesian inverse problems

In this paper we study properties of the Laplace approximation of the posterior distribution arising in nonlinear Bayesian inverse problems. Our work is motivated by Schillings et al. (Numer Math 145:915–971, 2020. 10.1007/s00211-020-01131-1), where it is shown that in such a setting the Laplace approximation error in Hellinger distance converges to zero in the order of the noise level. Here, we prove novel error estimates for a given noise level that also quantify the effect due to the nonlinearity of the forward mapping and the dimension of the problem. In particular, we are interested in settings in which a linear forward mapping is perturbed by a small nonlinear mapping. Our results indicate that in this case, the Laplace approximation error is of the size of the perturbation. The paper provides insight into Bayesian inference in nonlinear inverse problems, where linearization of the forward mapping has suitable approximation properties.

Temporal change in seismic wave attenuation using highly stable vibration sources

We developed a method to detect attenuation changes during seismic wave propagation excited by precisely controlled artificial seismic sources, namely Accurately Controlled Routinely Operated Signal System (ACROSS), and applied it to monitor the temporal changes for in situ data collected by previous studies. Our method, together with the use of the ACROSS sources, is less susceptible to noise level changes, from which conventional methods such as envelope calculation suffer. The method utilizes the noise level that is independently estimated in the frequency domain and eliminates the influence of the noise from the observed signal. For performance testing, we applied this method to a dataset that was obtained in an experiment at Awaji Island, Japan, from 2000 to 2001. We detected a change in amplitude caused by rainfall, variation in atmospheric temperature, and coseismic ground motions. Among them, coseismic changes are of particular interest because there are limited studies on coseismic attenuation change, in contrast to many studies on coseismic velocity decrease. At the 2000 Western Tottori earthquake (MW = 6.6, epicenter distance of 165 km), a sudden decrease in amplitude of up to 5% was observed. The coseismic amplitude reduction and its anisotropic characteristics, which showed a larger reduction in the direction of the major axis of velocity decrease, were consistent with the opening of fluid-filled cracks, as proposed by previous studies. The $$\Delta {Q}^{-1}$$ Δ Q - 1 corresponding to the amplitude change gives similar values to those reported in previous studies using natural earthquakes. Graphical Abstract

INVESTIGATION AND MODELING OF TRANSPORT NOISE DEPENDENCE ON TRAFFIC SPEED AND IMPACT ON POPULATION ANNOYANCE

Transport noise is a serious problem in cities and has a negative impact on both health and economics. In addition to the aforementioned unnoticed health effects, traffic noise has also been identified as one of the leading causes of sleep disorders, annoyance and negative cardiovascular effects. This research consists of three parts: part one involves onsite measurements of traffic noise in Trakai town; part two simulates traffic noise at different average vehicle speeds; part three assesses the number of people affected by traffic noise. The carried-out simulation has demonstrated that the noise level changes very slightly at different average vehicle speeds. It should be noticed that more noise is generated at average vehicle speed of 30 km/h rather than at 50 km/h. The assessment of the annoyance level has disclosed that an average vehicle speed of 30 km/h should cause the highest level of annoyance (highest – 26.8%).

Octave Band Technique for Noise Measurement at the Source, Path, and Receiver of Gas Turbines in Oil and Gas Facilities

Noise measurement is essential for industrial usage. However, further attention to preventing noise pollution is needed, especially when working with equipment generating a high noise level, such as gas turbines. This study aims to determine the best way to perform noise measurement and analyze the octave band frequency generated by noise pollution caused by gas turbine equipment. Data from site measurements show that the gas turbines produce more than 85 dB of noise with a Z-weighted measurement. A noise measuring investigation was conducted to obtain the data for the 1/3 octave band. A frequency-domain was used to comprehend the properties of the noise measurement frequency band. The frequency band was classified into three different zones called low, medium, and high frequency, which is useful in noise measurement analysis to identify a viable solution to reduce the noise. On-site sampling was performed at the source, path, and receiver of three separate gas turbine locations within oil and gas operations. The 1/3 octave band data collection results at the sound source, path, and receiver demonstrate the noise level distribution at the perimeter of gas turbine installations in the low and medium frequency ranges. Most of the high noise frequency range is between 250 Hz and 2 kHz for source, path, and receiver. All acquired values are compared to the Department of Safety and Health (Occupational Safety and Health (Noise Exposure) Regulations 2019 in Malaysia. As a result, oil and gas service operators can monitor and take countermeasures to limit noise exposure at oil and gas facilities.

The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR

Background Q.Clear is a block sequential regularized expectation maximization penalized-likelihood reconstruction algorithm for Positron Emission Tomography (PET). It has shown high potential in improving image reconstruction quality and quantification accuracy in PET/CT system. However, the evaluation of Q.Clear in PET/MR system, especially for clinical applications, is still rare. This study aimed to evaluate the impact of Q.Clear on the 18F-fluorodeoxyglucose (FDG) PET/MR system and to determine the optimal penalization factor β for clinical use. Methods A PET National Electrical Manufacturers Association/ International Electrotechnical Commission (NEMA/IEC) phantom was scanned on GE SIGNA PET/MR, based on NEMA NU 2-2012 standard. Metrics including contrast recovery (CR), background variability (BV), signal-to-noise ratio (SNR) and spatial resolution were evaluated for phantom data. For clinical data, lesion SNR, signal to background ratio (SBR), noise level and visual scores were evaluated. PET images reconstructed from OSEM + TOF and Q.Clear were visually compared and statistically analyzed, where OSEM + TOF adopted point spread function as default procedure, and Q.Clear used different β values of 100, 200, 300, 400, 500, 800, 1100 and 1400. Results For phantom data, as β value increased, CR and BV of all sizes of spheres decreased in general; images reconstructed from Q.Clear reached the peak SNR with β value of 400 and generally had better resolution than those from OSEM + TOF. For clinical data, compared with OSEM + TOF, Q.Clear with β value of 400 achieved 138% increment in median SNR (from 58.8 to 166.0), 59% increment in median SBR (from 4.2 to 6.8) and 38% decrement in median noise level (from 0.14 to 0.09). Based on visual assessment from two physicians, Q.Clear with β values ranging from 200 to 400 consistently achieved higher scores than OSEM + TOF, where β value of 400 was considered optimal. Conclusions The present study indicated that, on 18F-FDG PET/MR, Q.Clear reconstruction improved the image quality compared to OSEM + TOF. β value of 400 was optimal for Q.Clear reconstruction.

Acoustical Environment Studies in the Modern Urban University Campuses

The quality of the acoustic environments at Xi’an Jiatong-Liverpool University (XJTLU) and Soochow University (Dushuhu Campus, SUDC) in Suzhou City were investigated in the present work through real-time noise level measurements and questionnaire surveys. Before commencing the measurements and surveys, these two campuses’ sound sources were summarized and classified into four categories through on-site observation: human-made, machinery, living creatures, and natural physical sounds. For the zones near the main traffic road, with a high volume of crowds and surrounded by a park, sound from road vehicles, humans talking, and birds/insects were selected by the interviewees as the major sound sources, respectively. Only zone 3 (near to a park) at XJTLU could be classified as A zone (noise level < 55 dBA) with an excellent quality acoustical environment. All other zones had either good or average quality acoustical environments, except zone 1 (near to main traffic road) at XJTLU, with a fair-quality acoustical environment.

PENGARUH CELAH CAMSHAFT TERHADAP NOISE PADA CYLINDER HEAD HONDA CB 150 R

Noise on a motorcycle is unwanted sound because it does not fit the context of space and time thus affecting ride comfort . Noise caused by the vibrating object or objects collide . Which became the main object causes of noise in the Cylinder Head Honda cb 150 R is due to the large gap camshaft causing collision between the camshaft with holder. This research was conducted entirely in the workshop by examining the influence of several variations of the gap camshaft to noise generated in the cylinder head . Variations slit used was 0,75 mm , 0,85 mm , 0,95 mm , 1,05 mm, and 1,15 mm . The results showed that the variation of the gap camshaft significant effect on the noise generated , namely : a gap of 0,75 mm camshaft generate noise by 78,12 dB , 0,85 mm gap camshaft generate noise with a value of 78,37 dB , 0,95 mm gap camshaft generate noise 78,93 dB , 1,05 mm gap camshaft generate noise levels at 79,95 dB, and 1,15 mm gap camshafts produce 80,23 dB. Based on the results of the research with camshaft gap variation can be concluded that the lowest noise level generated by the camshaft gap of 0,75 mm .

Prediction of L10 and Leq Noise Levels Due to Vehicular Traffic in Urban Area Using ANN and Adaptive Neuro-Fuzzy Interface System (ANFIS) Approach

Recently in urban areas, road traffic noise is one of the primary sources of noise pollution. Variation in noise level is impacted by the synthesis of traffic and the percentage of heavy vehicles. Presentation to high noise levels may cause serious impact on the health of an individual or community residing near the roadside. Thus, predicting the vehicular traffic noise level is important. The present study aims at the formulation of regression, an artificial neural network (ANN) and an adaptive neuro-fuzzy interface system (ANFIS) model using the data of observed noise levels, traffic volume, and average speed of vehicles for the prediction of L10 and Leq. Measured noise levels are compared to the noise levels predicted by the experimental model. It is observed that the ANFIS approach is more superior when compared to output given by regression and an ANN model. Also, there exists a positive correlation between measured and predicted noise levels. The proposed ANFIS model can be utilized as a tool for traffic direction and planning of new roads in zones of similar land use pattern.