Effect of bismuth replacement at barium site in Y-Ba-Cu-O system

X-ray diffraction, electron paramagnetic resonance, microwave absorption and resistivity measurements were carried out on YBa_2−x Bi _x Cu₃O₇ (0≤x≤0·5) superconductors in order to study the effect of bismuth on the structural and superconducting properties. A decrease in sintering temperature increased the amount of impurity phase. Transition from an orthorhombic (superconducting) phase to tetragonal structure produced no significant change in EPR zero-field signal at liquid nitrogen temperature (LNT). The non-resonance signal height decreased on higher concentration of bismuth. Sintered YBa_2−x Bi _x Cu₃O₇ superconductor had a strong EPR zero-field signal at LNT. We have evaluated particle size from XRD and EPR studies. The average particle size was about 0·4μm.     

A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imaging

Alzheimer's disease (AD) is the most prevalent form of dementia. Although fewer people, who suffer from AD are correctly and promptly diagnosed, due to a lack of knowledge of its cause and unavailability of treatment, AD is more manageable if the symptoms of mild cognitive impairment (MCI) are in an early stage. In recent years, computer‐aided diagnosis has been widely used for the diagnosis of AD. The main motive of this paper is to improve the classification and prediction accuracy of AD. In this paper, a novel approach is developed to classify MCI, normal control (NC), and AD using structural magnetic resonance imaging (sMRI) from the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset (50 AD, 50 NC, 50 MCI subjects). FreeSurfer is used to process these MRI data and obtain cortical features such as volume, surface area, thickness, white matter (WM), and intrinsic curvature of the brain regions. These features are modified by normalizing each cortical region's features using the absolute maximum value of that region's features from all subjects in each group of MCI, NC, and AD independently. A total of 420 features are obtained. To address the curse of dimensionality, the obtained features are reduced to 30 features using a sequential feature selection technique. Three classifiers, namely the twin support vector machine (TSVM), least squares TSVM (LSTSVM), and robust energy‐based least squares TSVM (RELS‐TSVM), are used to evaluate the classification accuracy from the obtained features. Five‐fold and 10‐fold cross‐validation are used to validate the proposed method. Experimental results show an accuracy of 100% for the studied database. The proposed approach is innovative due to its higher classification accuracy compared to methods in the existing literature.     

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions

Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.     

Numerical modelling of the NGI-DSS test and cyclic threshold shear strain for degradation in sand

Ability of laboratory determination of a sand behaviour in static and dynamic loading conditions are influenced by (among other things): sample preparation, number of tests, size of strains, speed of loading and averaging of the errors during examination. Dynamic load per se causes accumulation of the pore water pressure and the phenomenon of stiffening-threshold-degradation which makes the understanding of the sand behaviour more difficult. The complex behaviour of granular material, i.e. sand, is caused by chemical and physical properties of individual particles and their mutual interaction. Obviously, these interrelationships could not be analysed on the basis of laboratory testing. One way to analyse it is numerically, with algorithm that takes into consideration the characteristics of individual particles as well as their interaction in the sand matrix. Discrete element method (DEM) is a numerical method which takes into consideration the discrete nature of sand and shape of particles and is used as an elementary research tool for sand behaviour. Program package PFC3D is based on DEM and allows the modelling of the laboratory equipment, materials and calibration of its micro-characteristics, based on experimental results. The research of cyclic threshold shear strain for degradation in sand includes observation and visualization of the sample preparation (creation of the material skeleton), pouring of the material (transition from liquid to meta-stable state), influence of the particle shape (interlocking, arching), consolidation (deformation of the skeleton) and development and braking of force chains through the sample. This paper explores the suitability of the selected numerical method for modelling of NGI-DSS device, calibration of the tested granular material (Nevada sand) and preparation of the sample for testing and presentation of the stiffening-threshold-degradation phenomenon.     

Automatic classification of sleep stages based on the time-frequency image of EEG signals

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner–Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals.     

Ink-Jet Printing of Binders for Ceramic Components

Layered manufacturing methods for fabricating ceramic components can involve selective deposition of binder using ink-jet printing. Selection of a proper binder plays a critical role in fabricating parts with good surface finish, dimensional accuracy, and high resolution. Several polymeric solution-phase binders were investigated in terms of their physical properties, printing performance, and binder-powder bed interaction. It was observed that the molecular weight should be <15 000 for the binder to be penetrated into dense powder compacts. Binder infiltration kinetics and printed line width were also significantly influenced by powder-bed characteristics, such as surface roughness and pore size, as well as the physical properties of the binder, such as viscosity and surface tension.     

Integrated Dual-Display-Based 3G Mobile Phone / Wireless Terminal

In this paper, we describe HW and SW features of the developed prototype of a hybrid 3G mobile phone and wireless terminal, which provides integral video projection onto two VGA/2 displays that, when put side-by-side, form the integrated display with the ratio of the overall width to its overall height, equal to 4:3, so providing the integral video VGA format and enabling visual presentation of standard full-size web pages, PC mainstream SW screens (such as e.g. the ones of e-mail clients), multi-media content etc. When not in use, the displays can be fold back one onto each other, so preserving the industry-standard dimensions of the device. The two displays that share the image provide it with overall resolution of 640 x 480 pixels per inch. The device is driven by Texas Instruments OMAP 2420 multimedia processor with ARM1136 core and Linux operating system. In addition, the device is equipped with specially developped prototypes of unique spring/microgenerator-based battery charger as well as with ultra-thin mountable foil-based QWERTY keyboard.     

Electrical properties of semimetallic and semiconducting alloys of Bi-Sb

Electrical resistivity studies have been carried out on three different Bi-Sb alloys in the temperature range 100–300 K. The observed behaviour of all the samples, in which one is semimetallic and other two are semiconductors, can be explained on the basis of the model presented for Bi-Sb energy bands at low temperature.