Uncertainty Analysis of Four-Terminal-Pair Capacitance Characterization up 30 MHz

The Impedance Group Laboratories of National Metrology Institute of Turkey previously developed a new method for the characterization of Agilent 16380A-type four-terminal-pair air dielectric capacitance standards ranged from 1 to 1,000 pF up to 30 MHz. This method is based on obtaining all resonance frequencies of standard capacitors using a vector network analyzer in order to calculate inductive residual parameters of the standards. As a continuation of the study, this paper gives a detailed uncertainty analysis for the method.     

Automatic Generation of Language-based Tools

Many tools can be automatically derived from formal language definitions, such as compilers/interpreters, editors, analyzers, visualizers/animators, etc. Some examples of language-based tools generated automatically by the LISA system are described in the paper. In addition the specification of an algorithm animator and program visualizer, Alma, generated from an extended LISA input-grammar is discussed; LISA principles and code are reused in Alma implementation.     

Multi-scale directional-filtering-based method for follicular lymphoma grading

Follicular lymphoma (FL) is a group of malignancies of lymphocyte origin that arise from lymph nodes, spleen, and bone marrow in the lymphatic system. It is the second most common non-Hodgkins lymphoma. Characteristic of FL is the presence of follicle center B cells consisting of centrocytes and centroblasts. Typically, FL images are graded by an expert manually counting the centroblasts in an image. This is time consuming. In this paper, we present a novel multi-scale directional filtering scheme and utilize it to classify FL images into different grades. Instead of counting the centroblasts individually, we classify the texture formed by centroblasts. We apply our multi-scale directional filtering scheme in two scales and along eight orientations, and use the mean and the standard deviation of each filter output as feature parameters. For classification, we use support vector machines with the radial basis function kernel. We map the features into two dimensions using linear discriminant analysis prior to classification. Experimental results are presented.     

3D Model compression using Connectivity-Guided Adaptive Wavelet Transform built into 2D SPIHT

Connectivity-Guided Adaptive Wavelet Transform based mesh compression framework is proposed. The transformation uses the connectivity information of the 3D model to exploit the inter-pixel correlations. Orthographic projection is used for converting the 3D mesh into a 2D image-like representation. The proposed conversion method does not change the connectivity among the vertices of the 3D model. There is a correlation between the pixels of the composed image due to the connectivity of the 3D mesh. The proposed wavelet transform uses an adaptive predictor that exploits the connectivity information of the 3D model. Known image compression tools cannot take advantage of the correlations between the samples. The wavelet transformed data is then encoded using a zero-tree wavelet based method. Since the encoder creates a hierarchical bitstream, the proposed technique is a progressive mesh compression technique. Experimental results show that the proposed method has a better rate distortion performance than MPEG-3DGC/MPEG-4 mesh coder.     

CCII-based PID controllers employing grounded passive components

In this paper, both of current-mode and voltage-mode proportional plus integral plus derivative (PID) controllers employing the second-generation current conveyors (CCIIs) as active elements are developed. The presented novel PID controllers have grounded passive elements that do not need passive element matching, and realize independently adjustable PID parameters. Thus, it is easy to implement these PID controllers in integrated circuits. Several computer simulations are presented to demonstrate the behavior of these proposed PID controllers.     

All‐Carbon Nanoarchitectures as High‐Performance Separation Membranes with Superior Stability

The application of graphene‐based membranes is hindered by their poor stability under practical hydrodynamic conditions. Here, nanocarbon architectures are designed by intercalating surface‐functionalized, small‐diameter, multi‐walled carbon nanotubes (MWCNTs) into reduced graphene oxide (rGO) sheets to create highly stable membranes with improved water permeability and enhanced membrane selectivity. With the intercalation of 10 nm diameter MWCNTs, the water permeability reaches 52.7 L m^?2 h^?1 bar^?1, which is 4.8 times that of pristine rGO membrane and five to ten times higher than most commercial nanofiltration membranes. The membrane also attains almost 100% rejection for three organic dyes of different charges. More importantly, the membrane can endure a turbulent hydrodynamic flow with cross‐flow rates up to 2000 mL min^?1 and a Reynolds number of 4667. Physicochemical characterization reveals that the inner graphitic walls of the MWCNTs can serve as spacers, while nanoscale rGO foliates on the outer walls interconnect with the assimilated rGO sheets to instill superior membrane stability. In contrast, intercalating with single‐walled nanotubes fails to reproduce such stability. Overall, this nanoarchitectured design is highly versatile in creating both graphene‐rich and CNT‐rich all‐carbon membranes with engineered nanochannels, and is regarded as a general approach in obtaining stable membranes for realizing practical applications of graphene‐based membranes.     

Special issue on microscopic image processing

The applications of biometric technology for automated personal identification become ubiquitous. Iris recognition is well known for high accuracy and reliability among the biometric traits. This paper presents an efficient noise-removing approach for non-cooperative iris recognition systems. Proposed method removed the noise factors including eyelids, eyelashes, reflections, out of framework, pupil and sclera. The novelty is to detect eyelashes and reflections through finding appropriate thresholds using a procedure called statistical decision making. The eyelids are detected using parabolic Hough transform in normalized iris image to increase computational speed. In addition, a coarse-to-fine strategy for accurate and fast iris localization is proposed. The Gabor-wavelet and a novel encoding strategy proposed in our previous work are also used here to generate the iris codes. We elaborate the principle of mask code generation to assign noisy bits in an iris code to exclude them in matching step. Experimental results on CASIA-IrisV3-Interval database show superiority of the proposed scheme among other state-of-the-art methods available in the literature.