Bounded multivariate generalized Gaussian mixture model using ICA and IVA

Pattern Analysis and Applications - A bounded multivariate generalized Gaussian mixture model with a full covariance matrix is proposed for modeling data in a bounded support region. For model...     

Insight into the Structural,Magneto-electronic,and Mechanical Characteristic of Y2MnZ (Z = Al,Ga, In) via DFT Computation

Journal of Superconductivity and Novel Magnetism - The first-principle calculations of density functional theory were used to study the structural, electronic, magnetic, mechanic, and half-metallic...     

High-Stability Platinum Nano-Electrocatalyst Synthesized by Cyclic Voltammetry for Oxygen Reduction Reaction

Cyclic voltammetry as a simple electrochemical deposition method was developed in order to prepare a platinum nano-electrocatalyst for oxygen reduction reaction (ORR) in low-temperature fuel cell systems. The morphology of the prepared platinum was evaluated by scanning electron microscopy and energy dispersive x-ray analysis. The effects of platinum concentration in electrodeposition solution and scan numbers of cyclic voltammetry (scan rate: 50 m V s^?1, between 1.489 and ??0.311 versus reversible hydrogen electrode) on the performance of prepared electrocatalysts for ORR were studied. The fabricated electrodes were evaluated by cyclic voltammetry, linear sweep voltammetry, electrochemical impedance spectroscopy and scanning electron microscopy. The results revealed that the optimum conditions for the preparation of electrocatalysts were 2E?3 M H₂PtCl₆ and 30 scan numbers. The optimized electrode showed high stability after 1200 cycles.     

Spatially distributed ice-thickness modelling for Chhota Shigri Glacier in western Himalayas,India

Estimation of glacier ice-thickness distribution is important for many glacio-hydrological applications such as runoff projections, glacial lake outburst flood (GLOF) predictions, future evolution of glaciers. Varieties of modelling approaches are available for estimating ice-thickness distribution depending upon the data availability. In the present study, we estimated the ice-thickness distribution and total ice volume of Chhota Shigri Glacier using an optimally parameterized Glacier Bed Topography version 2 (GlabTop2) model, a shallow ice approximation (SIA)-based spatially distributed approach. Among the model input parameters, the shape factor (f), a non-measurable factor compensating for unaccounted effects such as valley shape needs to be calibrated using field measurements of ice-thickness. However, the lack of direct measurements of ice-thickness over many glaciers worldwide restricts model calibration and effective implementation. Therefore, to overcome this limitation, in this study, a novel approach using a relationship between shape factor, glacier cross-sectional width, and ice-thickness at the centre of a cross-section has been proposed and also tested to estimate optimal shape factor of the study glacier. Additionally, a detailed analysis of the effect of Digital Elevation Model (DEM) resolution and shape factor parameterization on the modelled ice-thickness estimates indicate that improving either the DEM resolution or calibrating the shape factor individually will not lead to improved ice-thickness estimates. In fact, both are necessary for better estimation of ice-thickness distribution. The high resolution DEM used in this study is TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) DEM of 10 × 10 m grid size. Finally, a comparison of the results from a previous study where they used Shuttle Radar Topography Mission (SRTM) 90 m DEM indicates that the improved parameterisation of GlabTop2 model has led to a reduction in the error bounds of the estimated ice-thickness including the total glacier stored ice volume for the year 2013, which is estimated to be 1.74 ± 0.25 km³. Furthermore, based on the obtained results, it can be said that the GlabTop2 model combined with the proposed parameterization approach is having enormous potential to be applied over the wide range of data scarce Himalayan glaciers to quantify reliable ice-thickness estimates.     

Study of silver electrodeposition in deep eutectic solvents using atomic force microscopy

The electrodeposition of metals in ionic liquids and deep eutectic solvents leads to deposits with significantly different morphologies to those seen with aqueous solutions. The classical methods of fitting amperometric data to nucleation and growth mechanisms do not fit the data well in ionic systems and tend to focus on the short time-scale aspects of nucleation. In the current study, ex-situ AFM was used to model crystallite sizes and distributions by digitising and modelling the images. The deposition of silver from a deep eutectic solvent was chosen as it has been studied by several groups with a variety of techniques. The crystallite size data obtained from AFM and chronoamperometry for long time-scale deposition studies are compared and it is shown that the trends are similar, but there is a discrepancy in the nuclear number density of approximately an order of magnitude. The nuclear number density was found to be consistent with aqueous nucleation studies once differences in concentration and mass transport were accounted for.     

Modified calibrated control charts for monitoring the population mean under stratified sampling

In this research paper, we discuss the use of calibration technique to propose some new estimators under stratified sampling design and its use in reliability engineering. We first proposed the estimators using the calibration technique and then modify the already existing control charts such as Shewhart, exponentially weighted moving average and hybrid exponentially weighted moving averages using these calibration estimators. We also have studied the use of the proposed control charts in detail by showing their efficiency in terms of average run length. We find out that a hybrid control chart is more effective to detect the early shifts in the mean of the process.     

Multimodal Medical Image Registration and Fusion for Quality Enhancement

For the last two decades, physicians and clinical experts have used a single imaging modality to identify the normal and abnormal structure of the human body. However, most of the time, medical experts are unable to accurately analyze and examine the information from a single imaging modality due to the limited information. To overcome this problem, a multimodal approach is adopted to increase the qualitative and quantitative medical information which helps the doctors to easily diagnose diseases in their early stages. In the proposed method, a Multi-resolution Rigid Registration (MRR) technique is used for multimodal image registration while Discrete Wavelet Transform (DWT) along with Principal Component Averaging (PCAv) is utilized for image fusion. The proposed MRR method provides more accurate results as compared with Single Rigid Registration (SRR), while the proposed DWT-PCAv fusion process adds-on more constructive information with less computational time. The proposed method is tested on CT and MRI brain imaging modalities of the HARVARD dataset. The fusion results of the proposed method are compared with the existing fusion techniques. The quality assessment metrics such as Mutual Information (MI), Normalize Cross-correlation (NCC) and Feature Mutual Information (FMI) are computed for statistical comparison of the proposed method. The proposed methodology provides more accurate results, better image quality and valuable information for medical diagnoses.     

A control chart for monitoring the lognormal process variation using repetitive sampling

Control charts are developed to make the specific quality measures for a successful production process and follow normal distribution behaviors. But some real-life practices do not match such practices and exhibit some positively skewed behavior like lognormal distribution. The present study has considered this situation and proposed a monitoring control chart based on lognormal process variation using a repetitive sampling scheme. This concept proved better for detecting shifts as quickly as possible, and compared with the existing concept, results are elaborated through extensive tables. The average run lengths and standard deviations of the run lengths are being used as a performance evaluation measures and computed by using Monte Carlo simulations performed in R language. A real-life situation has been discussed in the example section to strengthen the proposed control chart concept in a real-life situation.     

The effect of silk fibroin nanoparticles on the morphology,rheology, dynamic mechanical properties,and toughness of poly(lactic acid)/poly(ε-caprolactone) nanocomposite

The silk fibroin nanoparticles (SFNPs) were extracted from silkworm cocoons and used as a nanofiller in poly(lactic acid) (PLA)/poly(ε-caprolactone) (PCL) blend. The nanoparticle localization was studied theoretically and experimentally and the effects of SFNP on the morphology, rheology, toughness, and dynamic mechanical properties of the blend were investigated. According to the calculated wetting coefficient, SFNP should be thermodynamically located in the PLA matrix during the melting process. The results of SEM illustrated a common sea-island structure for the PLA/PCL blend and the incorporation of SFNP reduced the PCL domain sizes from 1.170 ± 92 μm to 794 ± 46 nm. The atomic force microscopy results showed that the nanoparticles are mainly located in the PLA matrix and also, partially at the phase interface with a thickness of layers around 80 nm. The rheological tests displayed the network formation of SFNP in the prepared nanocomposites. The dynamic mechanical analysis revealed that by the addition of SFNP, the storage modulus of neat PLA and PLA/PCL blend were increased by around 57 and 50%, respectively and the glass transition temperatures (Tg) values of PLA and PCL shifted toward each other. Additionally, using SFNP caused a lower water uptake and higher impact strength (~64%) of the blend.     

Application of fluorescence spectroscopy for rapid and noninvasive quality determination of yoghurt ice cream using chemometrics

The aim of this study was to explore the potential of fluorescence spectroscopy to determine the quality of yoghurt ice cream, prepared by adding different concentrations of yoghurt (10, 20, 30, 40, 50%). The addition of 50% of yoghurt showed the lowest pH and meltdown values, whereas the highest acidity and overrun rates were observed at the same concentration. Additionally, fluorescence spectra taken at varied emission and excitation ranges were preprocessed for baseline correction. The partial least square regression analysis on proposed excitation wavelengths (270 nm, 280 nm, 290 nm and 315 nm) showed effective prediction of various quality parameters of yoghurt ice cream.