Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

Interaction of triton X-100 on silica: A relationship between surface characteristics and adsorption isotherms

Adsorption of Triton X-100 on various silica substrates has been investigated. A number of solids, including a natural quartz, this quartz washed with HCl acid and subsequently heated at 1273 K; two aerosils and one Kieselgel silicas were studied. These solids exhibit surface areas in the range of 5 to 430 m² g^?1. All the Triton adsorption isotherms display an S-shape at the adsorption temperatures studied (298 and 308 K). It has been found that the pretreatments of natural quartz (by water washing, impurities removed by acid and/or high temperature calcination) affect considerably the amounts of TX-100 adsorbed. Measurements of surface composition have been made by X-ray photoelectron spectroscopy (XPS) with particular emphasis on the presence of impurities and on the number of OH groups at the surface of the samples. The nature of the surface hydroxyl has also been studied by infrared spectroscopy. Furthermore, the specific number of hydroxyl groups on the surface of the silica samples has been determined by thermogravimetric analysis. Finally an attempt to correlate solid surface characteristics with adsorption isotherms has been developed.     

Properties of poly(ethylene terephthalate)–poly(ethylene naphthalene 2,6‐dicarboxylate) blends with montmorillonite clay

The production and properties of blends of poly(ethylene terephthalate) (PET) and poly(ethylene naphthalene 2,6‐dicarboxylate) (PEN) with three modified clays are reported. Octadecylammonium chloride and maleic anhydride (MAH) are used to modify the surface of the montmorillonite–Na⁺ clay particles (clay–Na⁺) to produce clay–C18 and clay–MAH, respectively, before they are mixed with the PET/PEN system. The transesterification degree, hydrophobicity and the effect of the clays on the mechanical, rheological and thermal properties are analysed. The PET–PEN/clay–C18 system does not show any improvements in the mechanical properties, which is attributed to poor exfoliation. On the other hand, in the PET–PEN/clay–MAH blends, the modified clay restricts crystallization of the matrix, as evidenced in the low value of the crystallization enthalpy. The process‐induced PET–PEN transesterification reaction is affected by the clay particles. Clay–C18 induces the largest proportion of naphthalate–ethylene–terephthalate (NET) blocks, as opposed to clay–Na⁺ which renders the lowest proportion. The clay readily incorporates in the bulk polymer, but receding contact‐angle measurements reveal a small influence of the particles on the surface properties of the sample. The clay–Na⁺ blend shows a predominant solid‐like behaviour, as evidenced by the magnitude of the storage modulus in the low‐frequency range, which reflects a high entanglement density and a substantial degree of polymer–particle interactions. Copyright © 2005 Society of Chemical Industry     

A Study of Ozone Generation by Negative Corona Discharge Through Different Plasma Chemistry Models

The Steady radial distribution of chemical species in a wire‐to‐cylinder ozone generator filled with pure oxygen has been computed by applying four different plasma chemistry models of increasing complexity. The most complete model considers ten species (e, O₂ ⁺, O₂ ^?, O₃ ^?, O^?, O₂, O₂(¹Δ_g), O₂(¹∑_g ⁺), O and O₃) and 79 reactions, including ionization by electron impact, electron attachment and detachment, electron-ion recombination, charge transfer, etc. The chemical model is coupled with the electrical model through Poisson's equation. The spatially averaged ozone density has been computed as a function of the current intensity and compared with the experimental values obtained by UV spectroscopy.     

Algorithms for processing the group K nearest-neighbor query on distributed frameworks

Distributed and Parallel Databases - Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum...     

A review of the unique features of HDL apoproteins

The human plasma high density lipoproteins (HDL) are a heterogeneous ensemble of five proteins associated with both neutral and polar lipids. The sequences of all five proteins are known. ApoA-I and apoA-II are the major protein components; apoC-I, apoC-II and apoC-III are the minor protein components. All these apoproteins spontaneously recombine with phospholipids to give stable lipid-protein complexes and freely exchange between the two major HDL subclasses, HDL₂ and HDL₃. In addition, ApoC-I, apoC-II, and apoC-III exchange between HDL and very low density lipoproteins. Furthermore, certain HDL apoproteins are activators for plasma enzymes that are important in lipid metabolism. ApoA-I and apoC-I activate lecithin/cholesterol acyltransferase; apoC-II is an activator of lipoprotein lipase. The regions of apoC-I and apoC-II that are involved in the activation of these enzymes have been localized with synthetic peptides. Studies of synthetic and native fragments of apoA-II, apoC-I, apoC-II, and apoC-III as well as model lipid-binding peptides have identified specific regions with structural features common to lipid-binding proteins. These special properties, which include helical potential, sequences with a critical amphipathic length, and high hydrophobicity of the nonpolar side of the amphipathic helix, are the determinants of HDL structure and metabolism.     

Inverse analysis procedure to determine flow stress and friction data for finite element modeling of machining

This paper describes an inverse procedure to determine the constitutive constants and the friction conditions in the machining processes using Finite Elements (FE) simulations. In general, the FE modeling of machining processes is an effective tool to analyze the materials machinability under different cutting conditions. However, the use of reliable rheological and friction models represents the basis of a correct numerical investigation. The presented inverse procedure was based on the numerical results obtained using a commercial FE code and was developed considering a specific optimization problem, in which the objective functions that have to be minimized is the experimental/numerical error. This problem was performed by a routine developed in a commercial optimization software. In order to verify the goodness and the robustness of the methodology, it was applied on a Super Duplex Stainless Steel (SDSS) and on an Austenitic Stainless Steel (AUSS) orthogonal machining processes. This work, then, was focused on the identification of the Johnson-Cook (JC) coefficients (A,B,C, n and m) and on the calibration of a Coulomb friction model, in the specific cases of the SAF2507 SDSS and of an AISI 316 Based AUSS Alloy (AISI 316 ASBA). The identification phases were performed considering forces and temperatures experimental data, collected in two specific experimental tasks in which different orthogonal cutting tests were carried out under different cutting parameters conditions.     

An internet of things–based personal device for diabetes therapy management in ambient assisted living (AAL)

Diabetes therapy management in AAL environments, such as old people and diabetes patients homes, is a very difficult task since many factors affect a patient’s blood sugar levels. Factors such as illness, treatments, physical and psychological stress, physical activity, drugs, intravenous fluids and change in the meal plan cause unpredictable and potentially dangerous fluctuations in blood sugar levels. Right now, operations related to dosage are based on insulin infusion protocol boards, which are provided by physicians to the patients. These boards are not considering very influential factors such as glycemic index from the diet, consequently patients need to estimate the dosage leading to dose error, which culminates in hyperglycemia and hypoglycemia episode. Therefore, right insulin infusion calculation needs to be supported by the next generation of personal-care devices. For this reason, a personal device has been developed to assist and consider more factors in the insulin therapy dosage calculation. The proposed solution is based on Internet of things in order to, on the one hand, support a patient’s profile management architecture based on personal RFID cards and, on the other hand, provide global connectivity between the developed patient’s personal device based on 6LoWPAN, nurses/physicians desktop application to manage personal health cards, glycemic index information system, and patient’s web portal. This solution has been evaluated by a multidisciplinary group formed by patients, physicians, and nurses.     

A proposal for student modeling based on ontologies and diagnosis rules

The advances in the educational field and the high complexity of student modeling have provoked it to be one of the aspects more investigated in Intelligent Tutoring Systems (ITSs). The Student Models (SMs) should not only represent the student’s knowledge, but rather they should reflect, as faithfully as possible, the student’s reasoning process. To facilitate this goal, in this article a new approach to student modeling is proposed that benefits from the advantages of Ontological Engineering, advancing in the pursue of a more granular and complete knowledge representation. It’s focused, mainly, on the SM cognitive diagnosis process, and we present a method providing a rich diagnosis about the student’s knowledge state – especially, about the state of learning objectives reached or not. The main goal is to achieve SMs with a good adaptability to the student’s features and a high flexibility for its integration in varied ITSs.