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Due to the complex spatial features of geological formation, it remains a significant challenge to accurately predict geological cross-sections from limited borehole data. This study develops an innovative multi-spatial receptive field (MSRF) XGBoost approach, which encompasses classification and identification modules to forecast geological cross-sections using sparse borehole data. The classification module exclusively employs sparse borehole data to train a series of MSRF XGBoost models for soil classification. The identification module leverages all the trained models to generate potential predictions of unknown soil strata, automatically pinpointing the optimal one via Gaussian filtering and boundary similarity algorithms. A new boundary accuracy criterion is proposed to assess the prediction capacity of different models. Following this, the developed MSRF XGBoost method is compared with an existing conventional XGBoost method using both linear and nonlinear cases. The findings illustrate that our proposed method enhances the prediction accuracy for both linear and nonlinear geological cross-sections. Furthermore, the developed method is employed to determine a geological cross-section in the Netherlands using open-source borehole data. The accuracy of the method in predicting soil layers in all in situ boreholes reaches an impressive 90%, validating its effectiveness in practical geotechnical engineering. • Multi-spatial receptive field is proposed to represent the nonlinear geological characteristics. • Novel MSRF XGBoost method that only use sparse borehole data to predict geological profile is proposed. • Identification module is developed to recommend the optimal geology prediction. • The novel method improves the accuracy of predicting soil layers compared with the conventional XGBoost method. [ABSTRACT FROM AUTHOR]

This paper suggests an image gradient based method that determines the optimal image size for convolutional neural network (CNN)-based diagnosis of fluid-film rotorbearing systems. As distinct patterns improve the diagnosis performance, a criterion is defined to measure the intensity of patterns in an image. The proposed criterion is derived by segmenting an image by the size of the CNN filter and evaluating each segment through the use of image gradient analysis. Vibration signals from a testbed are used to demonstrate the proposed method. First, the signals are transformed into vibration images by using an omnidirectional regeneration technique. Then, vibration images of four different health states are analyzed using the suggested criterion. The analyzed results are compared to the performance of CNN based diagnosis. The results indicate that the proposed criterion can determine the optimal size range of the vibration image that gives the best performance for CNN-based diagnosis. [ABSTRACT FROM AUTHOR]

In some cases, because of the complex internal structure of the machines, the positions of the vibration sensors are far away from the rolling bearings, such as in an aeroengine, causing the fault features to become extremely weak, which brings great challenge to the detection of rolling bearings. To address this problem, an integrated detection method is proposed. First, a method named MEDL is proposed to determine the optimal filter length in minimum entropy deconvolution (MED) to enhance the periodic fault impulse component in the weak signal, which accuracy is 1. After that, the MEDL is combined with variational mode decomposition (VMD) and autocorrelation to extract fault features from strong background noise. A series of fault simulation experiments for rolling bearings were conducted by using an aeroengine rotor experimental rig with casing. The results verify that the accuracy of the integrated detection method is 100 % in different measuring points, speeds and fault types. At the same time, it compared with spectral kurtosis (SK) and empirical wavelet transform (EWT). It proves that the integrated detection method is more robust in extracting the weak fault characteristic of rolling bearings from the casing signals effectively. [ABSTRACT FROM AUTHOR]

GaN devices are gradually getting attention within the industry along with SiC as a potential wide bandgap device. At present, there are almost no high-voltage GaN devices with voltage >650 V, which makes an inverter design difficult for a three-phase input. To address this challenge to some extent, this study brings in for the first time a full 700 V DC-link-based three-phase inverter-fed high power density system using new 900 V GaN devices. The study also describes how a high switching frequency GaN device can benefit reducing filter size and cost, thereby offering an opportunity to integrate the filter within the inverter. This filter can also provide a sine-wave output compared with the traditional pulse-width modulator output. The article discusses multiple aspects of the design such as (a) switching behaviours of this new device, (b) filters, (c) power losses of the devices within the inverter through comprehensive simulation models and experimental investigations at 128 kHz. Some of the practical challenges are discussed, and the study claims that the GaN inverter for three-phase applications is feasible with this new device.

GaN devices are gradually getting attention within the industry along with SiC as a potential wide bandgap device. At present, there are almost no high-voltage GaN devices with voltage >650 V, which makes an inverter design difficult for a three-phase input. To address this challenge to some extent, this study brings in for the first time a full 700 V DC-link-based three-phase inverter-fed high power density system using new 900 V GaN devices. The study also describes how a high switching frequency GaN device can benefit reducing filter size and cost, thereby offering an opportunity to integrate the filter within the inverter. This filter can also provide a sine-wave output compared with the traditional pulse-width modulator output. The article discusses multiple aspects of the design such as (a) switching behaviours of this new device, (b) filters, (c) power losses of the devices within the inverter through comprehensive simulation models and experimental investigations at 128 kHz. Some of the practical challenges are discussed, and the study claims that the GaN inverter for three-phase applications is feasible with this new device. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this study was to assess the influences of filter size, inflow rate and inlet–outlet configuration on short-circuiting, effective volume, distribution of active/dead zones, dispersion and dye propagation in simulated constructed wetlands. A subsurface quasi two dimensional flow constructed wetland was set up for chloride tracer test and dye visualization. Three levels of filter size, inflow rate and inlet–outlet configurations were involved. Totally 81 combinations were determined. Breakthrough curves for residence time distribution and images for dye tracer propagation were obtained. Results showed that the inflow rate and inlet–outlet configurations had significant effects on hydraulic behavior. Bigger filter size and low influent decreased short-circuiting and reduced dead zones, thus increasing active area. Bigger filter size enhanced plug flow by decreasing porous water velocity, reducing preferential flow. High flow rate yielded low plug flow with lower CSTRs number caused by higher linear velocities and enlarged dispersion. Inlet–outlet configuration had most influences on flow distribution. Inflow rate had larger impacts on dead zones distribution for low inlet–high outlet configuration. For practical constructed wetland design, choice of inlet–outlet configuration and inflow rate would improve the treatment efficiency. Larger porous size, lower inflow rate with bottom inlet–top outlet configuration could help improve hydraulic behavior, thus enhancing wastewater treatment. [Copyright &y& Elsevier]

The gray line profile method is widely used for detecting the boundaries between yarns in woven fabric surface images. One lack of the approach is the absence of generally accepted filtering method to eliminate minimum values which do not correspond to the yarn boundaries. Aim of this research is to propose a method which automatically determines the filter size for sliding filters so as to detect the true local minimum points those correspond to the boundary positions of weft and warp yarns. The method is tested with real fabric images. Experimental findings demonstrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

In magnetic resonance imaging based brain morphometry, Gaussian smoothing is often applied to increase the signal-to-noise ratio and to increase the detection power of statistical parametric maps. However, most existing studies used a single smoothing filter without adequately justifying their choices. In this article, we want to determine the extent for which performing a morphometry analysis using multiple smoothing filters, namely conducting a scale space search, improves or decreases the detection power. We first compared scale space search with single-filter analysis through a simulated population study. The multiple comparisons in our four-dimensional scale space searches were corrected for using a unified P-value approach. Our results illustrate that, compared with a single-filter analysis, a scale space search analysis can properly capture the variations in analysis results caused by variations in smoothing, and more importantly, it can obviously increase the sensitivity for detecting brain morphometric changes. We also show that the cost of an increased critical threshold for conducting a scale space search is very small. In the second experiment, we investigated age and gender effects on cortical volume, thickness, and surface area in 104 normal subjects using scale space search. The obtained results provide a perspective of scale space theory on the morphological changes with age and gender. These results suggest that, in exploratory studies of aging, gender, and disease, conducting a scale space search is essential, if we are to produce a complete description of the structural changes or abnormalities associated with these dimensions. Hum Brain Mapp 34:2113-2128, 2013. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Input-parallel output-parallel (IPOP) connected converter systems allow the use of low-power converter modules for high-power applications, with interleaving control scheme resulting in smaller filter size, better dynamic performance, and higher power density. In this paper, a new IPOP converter system is proposed, which consists of multiple dual-active half-bridge (DAHB) dc-dc converter modules. Moreover, by applying a common-duty-ratio control scheme, without a dedicated current-sharing controller, the automatic sharing of input currents or load currents is achieved in the IPOP converter even in the presence of substantial differences of 10% in various module parameters. The current-sharing performance of the proposed control method is analyzed using both a small-signal model and a steady-state dc model of the IPOP system. It is concluded that the equal sharing of currents among modules can be achieved by reducing the mismatches in various module parameters, which is achievable in practice. The current-sharing performance of the IPOP converter is also verified by Saber simulation and a 400-W experimental prototype consisting of two DAHB modules. The common-duty-ratio control method can be extended to any IPOP system that consists of three or more converter modules, including traditional dual-active bridge dc-dc converters, which have a characteristic of current source. [ABSTRACT FROM AUTHOR]

Functional organization units of the cerebral cortex exist over a wide range of spatial scales, from local circuits to entire cortical areas. In the last decades, scale-space representations of neuroimaging data suited to probe the multi-scale nature of cortical functional organization have been introduced and methodologically elaborated. For this purpose, responses are statistically detected over a range of spatial scales using a family of Gaussian filters, with small filters being related to fine and large filters-to coarse spatial scales. The goal of the present study was to investigate the degree of variability of fMRI-response patterns over a broad range of observation scales. To this aim, the same fMRI data set obtained from 18 subjects during a visuomotor task was analyzed with a range of filters from 4- to 16-mm full width at half-maximum (FWHM). We found substantial observation-scale-related variability. For example, using filter widths of 6- to 8-mm FWHM, in the group-level results, significant responses in the right secondary visual but not in the primary visual cortex were detected. However, when larger filters were used, the responses in the right primary visual cortex reached significance. Often, responses in probabilistically defined areas were significant when both small and large filters, but not intermediate filter widths were applied. This suggests that brain responses can be organized in local clusters of multiple distinct activation foci. Our findings illustrate the potential of multi-scale fMRI analysis to reveal novel features in the spatial organization of human brain responses. Hum Brain Mapp, 2011. © 2011 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

This paper surveys three areas: experimental evaluations and operating experience relating to contaminant detrimental effects to the particle size and hardness; importance of film thickness; and self-propagating damage with high-chromium steel rotors and chlorine oil additives. Analytical thermal criteria are also presented for a particle size limit to avoid flash temperature scuffing failures from particles embedding in a bearing at a sliding surface contact. [ABSTRACT FROM AUTHOR]

Abstract: Voxel-based morphometry (VBM) has been used to analyze diffusion tensor MRI (DT-MRI) data in a number of studies. In VBM, following spatial normalization, data are smoothed to improve the validity of statistical inferences and to reduce inter-individual variation. However, the size of the smoothing filter used for VBM of DT-MRI data is highly variable across studies. For example, a literature review revealed that Gaussian smoothing kernels ranging in size (full width at half maximum) from zero to 16 mm have been used in DT-MRI VBM type studies. To investigate the effect of varying filter size in such analyses, whole brain DT-MRI data from 14 schizophrenic patients were compared with those of 14 matched control subjects using VBM, when the filter size was varied from zero to 16 mm. Within this range of smoothing, four different conclusions regarding apparent patient control differences could be made: (i) no significant patient-control differences; (ii) reduced FA in right superior temporal gyrus (STG) in patients; (iii) reduced FA in both right STG and left cerebellum in patients; and (iv) reduced FA only in left cerebellum in patients. These findings stress the importance of recognizing the effect of the matched filter theorem on VBM analyses of DT-MRI data. Finally, we investigated whether one of the underlying assumptions of parametric VBM, i.e., the normality of the residuals, is met. Our results suggest that, even with moderate smoothing, a large number of voxels within central white matter regions may have non-normally distributed residuals thus making valid statistical inferences with a parametric approach problematic in these areas. [Copyright &y& Elsevier]

A novel sixteenth‐mode substrate integrated waveguide (SMSIW) bandpass filter loaded with complementary split‐ring resonator (CSRR) is proposed. The filter size is reduced by introducing the SMSIW circular cavity loaded with CSRR. The SMSIW occupies only 6.25% of the conventional substrate integrated waveguide with same resonant frequency. Further miniaturisation is achieved by loading the SMSIW circular cavities with CSRRs. The designed filter is centred at 2.45 GHz with a bandwidth of 8.2%. The measured minimum insertion loss is 0.9 dB and passband return loss is below 10 dB. Good agreement is achieved between simulated and measured results. [ABSTRACT FROM AUTHOR]