Line Filtering Research Articles

Size Effect of Electrolyte Ions on the Electric Double-Layer Structure and Supercapacitive Behavior

Finding a viable electrolyte for next-generation supercapacitors is of primary importance for developing supercapacitors with high power and energy densities. Herein, we synthesized a conducting salt, tetramethylphosphonium tetrafluoroborate (TMPBF4), and compared the electrochemical characteristics of supercapacitor devices containing TMPBF4 or 1,1-dimethylpyrrolidinium tetrafluoroborate (DMPBF4). The TMPBF4 salt was selected based on the generally accepted design rule that smaller ions and solvation shells contribute to higher energy and power densities. However, at a low current density (0.1 A g–1), supercapacitors with TMPBF4 in acetonitrile (AN) exhibited a slightly lower capacitance (24.6 ± 0.1 F g–1) than those with DMPBF4 (25.0 ± 0.2 F g–1). Clarification of this behavior using electrochemical and theoretical methods revealed that the total capacitance is influenced by not only the size of the ions but also the degree of cation–anion interactions near the electrodes. By contrast, at a high current density of 10 A g–1, supercapacitors with TMPBF4 showed an 18% increase in capacitance relative to those with DMPBF4. Supercapacitors with TMPBF4 exhibited both high capacitance and a remarkably long cycle life (10,000 cycles) at a high working voltage (3.2 V) and high current density (10 A g–1). Furthermore, supercapacitors utilizing TMPBF4/AN provided a sufficiently fast frequency response for 60 Hz alternating current (ac) line filtering. These insights into the influence of the investigated electrolyte salts on the formation of electric double-layer structures offer design rules for developing electrolytes for supercapacitors.

Weakly-supervised learning for catheter segmentation in 3D frustum ultrasound.

Accurate and efficient catheter segmentation in 3D ultrasound (US) is essential for ultrasound-guided cardiac interventions. State-of-the-art segmentation algorithms, based on convolutional neural networks (CNNs), suffer from high computational cost and large 3D data size for GPU implementation, which are far from satisfactory for real-time applications. In this paper, we propose a novel approach for efficient catheter segmentation in 3D US. Instead of using Cartesian US, our approach performs catheter segmentation in Frustum US (i.e., the US data before scan conversion). Compared to Cartesian US, Frustum US has a much smaller volume size, therefore the catheter can be segmented more efficiently in Frustum US. However, annotating the irregular and deformed Frustum images is challenging, and it is laborious to obtain the voxel-level annotation. To address this, we propose a weakly supervised learning framework, which requires only bounding-box annotations. The labels of the voxels are generated by incorporating class activation maps with line filtering, which are iteratively updated during the training cycles. Our experimental results show that, compared to Cartesian US, the catheter can be segmented much more efficiently in Frustum US (i.e., 0.25s per volume) with better accuracy. Extensive experiments also validate the effectiveness of the proposed weakly supervised learning method.

基于顶点向量角的改进型扫描线滤波算法

基于顶点向量角的改进型扫描线滤波算法

Flexible RF Filtering Front-End For Simultaneous Multinuclear MR Spectroscopy.

Simultaneously interrogation of multiple nuclei has been of interest since the very earliest days of MRI [1]-[3]. Our group and several others are revisiting this topic [4]-[6]. Very fast broadband electronics make it possible to digitize a wide spectrum, including multiple nuclei, but this places great demands on data throughput. Another issue is that there can be great variance between RF preamplifier gain required for the different nuclei. To overcome the data problem, it is desirable to use undersampling, but this requires passband filtering around the resonant frequency of each nuclei. Here we present a frequency agile front end that provides separate data paths for each nucleus, either from a single coil or from multiple ports, allows independent gain, filters each using very flexible transmission line filtering, and then combines them back for undersampling.

COMPARATIVE EVALUATION OF PAVEMENT CRACK DETECTION USING KERNEL-BASED TECHNIQUES IN ASPHALT ROAD SURFACES

With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and evaluation of the actual road conditions. This is due in part to the resulting large volumes of road pavement data captured through digital surveys, and also to the requirements for rapid data processing and evaluations. In this study, the Canon 5D Mark II RGB camera with a resolution of 21 megapixels is used for the road pavement condition mapping. Even though many imaging and mapping sensors are available, the development of automated pavement distress detection, recognition and extraction systems for pavement condition is still a challenge. In order to detect and extract pavement cracks, a comparative evaluation of kernel-based segmentation methods comprising line filtering (LF), local binary pattern (LBP) and high-pass filtering (HPF) is carried out. While the LF and LBP methods are based on the principle of rotation-invariance for pattern matching, the HPF applies the same principle for filtering, but with a rotational invariant matrix. With respect to the processing speeds, HPF is fastest due to the fact that it is based on a single kernel, as compared to LF and LBP which are based on several kernels. Experiments with 20 sample images which contain linear, block and alligator cracks are carried out. On an average a completeness of distress extraction with values of 81.2%, 76.2% and 81.1% have been found for LF, HPF and LBP respectively.

COMPARATIVE EVALUATION OF PAVEMENT CRACK DETECTION USING KERNEL-BASED TECHNIQUES IN ASPHALT ROAD SURFACES

Abstract. With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and evaluation of the actual road conditions. This is due in part to the resulting large volumes of road pavement data captured through digital surveys, and also to the requirements for rapid data processing and evaluations. In this study, the Canon 5D Mark II RGB camera with a resolution of 21 megapixels is used for the road pavement condition mapping. Even though many imaging and mapping sensors are available, the development of automated pavement distress detection, recognition and extraction systems for pavement condition is still a challenge. In order to detect and extract pavement cracks, a comparative evaluation of kernel-based segmentation methods comprising line filtering (LF), local binary pattern (LBP) and high-pass filtering (HPF) is carried out. While the LF and LBP methods are based on the principle of rotation-invariance for pattern matching, the HPF applies the same principle for filtering, but with a rotational invariant matrix. With respect to the processing speeds, HPF is fastest due to the fact that it is based on a single kernel, as compared to LF and LBP which are based on several kernels. Experiments with 20 sample images which contain linear, block and alligator cracks are carried out. On an average a completeness of distress extraction with values of 81.2%, 76.2% and 81.1% have been found for LF, HPF and LBP respectively.

The Assessment of Functional Properties of Surfaces with Morphological Operations

For functional properties such as gliding, sealing, assembling, adhering etc. the outer layer of the surface is the functional related surface. For the functional assessment of the surface this outer layer should be used as the reference for any functional characteristic. With the existing mean line system for the assessment of roughness and waviness, the standardized characteristics do not follow this logic. However there are valid historical reasons for the acceptance of the shortcomings of the mean line system. They are e.g. the alignment of the profile, the removal of form, the assumption of a sinusoidal structure of the waviness on the surface, and the distortion of the surface by the application of the mean line filtering process. To overcome these shortcomings morphological operations have been used to establish a new developed envelope system. In order to define new parameters to characterize and specify functional properties of surfaces, a common datum is necessary. The presented method for the alignment of datums is consistent with the algorithms used to establish datums and datum systems for workpieces, where the datum is established by the location of a tangent geometrical element such as a line, plane, cylinder etc. The orientation is usually derived by the application of the minimum zone algorithm. The benefit of the assessment of the functional properties of surfaces with morphological operations will be presented for two examples.

FDTD modeling incorporating a two-port network for I/O line EMI filtering design

Electromagnetic interference (EMI) filters are often utilized on I/O lines to reduce high-frequency noise from being conducted off the printed circuit board (PCB) and causing EMI problems. The filtering performance is often compromised at high frequencies due to parasitics associated with the filter itself, or the PCB layout and interconnects. Finite difference time domain (FDTD) modeling can be used to quantify the effect of PCB layout and interconnects, as well as filter type, on the EMI performance of I/O line filtering. FDTD modeling of a T-type and /spl pi/-type filter consisting of surface-mount ferrites and capacitors is considered herein. The FDTD method is applied to model PCB layout and interconnect features, as well as the lumped element components, including the nonlinear characteristics of ferrite surface-mount parts. The EMI filters with ferrites; are included in the modeling by incorporating the time-domain Y-parameters of the two-port network into the FDTD time-marching equations. Good agreement between the FDTD modeling and S-parameter measurements supports the new FDTD algorithm for incorporating two-port networks.

Deconstruction of Fractals and its Implications for Cartographic Education

The research reported here was designed for two reasons: firstly, to involve anyone with an interest in cartographic visualization to participate in eliciting cartographic knowledge and to provide them with the opportunity to contribute their practical knowledge and opinions; and secondly, to inform the design of algorithms for line generalization. In the past, there has been some resistance to such mining and codification of expert knowledge. However, many cartographers now welcome highly interactive computer graphics, computer mapping, and virtual reality systems as providing them with new opportunities for launching cartography into a new creative age. Despite nearly thirty years of research on line generalization algorithms, the available algorithms are somewhat simplistic. This research, undertaken under the auspices of the BCS Design Group, explored the behavioural tendencies of cartographers engaged in line filtering. The result show that a carefully contrived, even if obviously artificial, exercise on the deconstruction of lines into meaningless forms can prompt cartographers to observe, record, and discuss their own cognitive processing.

Deconstruction of Fractals and its Implications for Cartographic Education

The research reported here was designed for two reasons: firstly, to involve anyone with an interest in cartographic visualization to participate in eliciting cartographic knowledge and to provide them with the opportunity to contribute their practical knowledge and opinions; and secondly, to inform the design of algorithms for line generalization. In the past, there has been some resistance to such mining and codification of expert knowledge. However, many cartographers now welcome highly interactive computer graphics, computer mapping, and virtual reality systems as providing them with new opportunities for launching cartography into a new creative age. Despite nearly thirty years of research on line generalization algorithms, the available algorithms are somewhat simplistic. This research, undertaken under the auspices of the BCS Design Group, explored the behavioural tendencies of cartographers engaged in line filtering. The result show that a carefully contrived, even if obviously artificial, exercise on the deconstruction of lines into meaningless forms can prompt cartographers to observe, record, and discuss their own cognitive processing.

Economical line filtering for business communication systems

Economical active realizations of low-Q, all-pole, low-pass transfer functions are presented. The realizations allow a unidirectional sequence of functional tuning by trimming only resistors. Also, they have low sensitivities to the passive element variations. Experimental results verified the ease of tuning, the low sensitivity, and the low dependence on temperature and power supply variations.

A REVIEW OF METHODS OF FILTERING SEISMIC DATA

Filtering in its general sense represents an important phase of data processing. In recent years such new methods as delay line filtering and digital filtering as well as conventional seismic filtering have been described in the literature. The purpose of this paper is to clarify the relationship between these methods of filtering and to compare design criteria such as cross‐correlation filtering and zero‐phase filtering. Synthetic records as well as field records are used to illustrate the effects of the various filtering techniques.

To: Magnetic Delay Line Filtering

In paper “Magnetic Delay Line Filtering” by Hal J. Jones, John A. Morrison, G. P. Sarrafian, L. J. Spieker, Geophysics v.20, pages 754 and 761, Fig. 6c and Fig. 13 were inadvertently interchanged.