The mask of (2b + 4)-point n-ary subdivision scheme

In this paper, we present general formulae for the mask of (2b + 4)-point n-ary approximating as well as interpolating subdivision schemes for any integers ${b\,\geqslant\,0}$ and ${n\,\geqslant\,2}$ . These formulae corresponding to the mask not only generalize and unify several well-known schemes but also provide the mask of higher arity schemes. Moreover, the 4-point and 6-point a-ary schemes introduced by Lian [Appl Appl Math Int J 3(1):18–29, 2008] are special cases of our general formulae.     

Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR

This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as // can drop below 35% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research.     

Differential response of glaciers with varying debris cover extent: evidence from changing glacier parameters

Supraglacial debris (SGD) cover on mountain glaciers is known to greatly influence various glacier processes and alter their response to climate change. In this study, vital glacier parameters of five glaciers with varying debris coverage (about 7–26%), located in Zanskar basin, Ladakh Himalaya, were monitored using Landsat imagery (from 1977 to 2013) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM). Results reveal how varying amounts of SGD induce categorically distinct responses on glaciers, sharing same geographical settings. The clean glaciers (CG) in the area were found to have higher retreat rates (about 8–19 m year^?1), comparable areal shrinkage (about 13–15%), higher accumulation area ratios (AARs) (>0.5), rapid increase in SGD (about 1.6–3.0-fold), and association with increasing numbers of peri- and proglacial lakes (2–8 per glacier). The debris-covered glaciers (DCG) showed minimal frontal changes (about 2–5 m year^?1), higher areal shrinkage (about 14–21%), low AARs (<0.5), slow SGD changes (about ≤1.2-fold), and association with increasing numbers of peri- and supraglacial lakes (SGLs) (2–39 per glacier). Moreover, while changes in SGD had a strong negative correlation with changes in glacier area, retreat rates, and AAR, they were positively related with increase in area of SGLs.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.     

Modeling of Dispersive Materials Using Dispersion Models for FDTD Application

A nonlinear optimization algorithm based on the Nelder Mead method is used to characterize the frequency dependent permittivity of 15 materials based on Lorentz, modified Lorentz, Drude and Lorentz-Drude models. The optimized model parameters are used to calculate the complex relative permittivity of each material and compare it with experimental data. In each case, a very good match is found between the optimized and experimental data over a long wavelength range. Comparative study of the models used for each material is performed based on accuracy, wavelength range of applicability and computational efficiency. The parameters presented can be used for computer simulation of electromagnetic wave phenomena involving these materials.     

Rice-like CuO nanostructures for sensitive electrochemical sensing of hydrazine

In this work, a low temperature aqueous chemical growth methodology was used for the fabrication of CuO nanostructures. The as-synthesised nanostructures were then elaborately characterised by number of analytical techniques such as scanning electron microscopy (SEM) and X-ray powder diffraction (XRD). The obtained nanostructures were observed to possess interlaced rice-shaped structural features with the length and width of individual rice determined to be in the range of 200–300 nm and 50–100 nm respectively. The unique nanostructures when utilised as electrode material exhibited excellent electro-catalytic potential towards oxidation of hydrazine in alkaline media. The excellent conductive of CuO added by the high surface area of obtained nanorice-like structures enabled development of highly sensitive (3087 µA mM⁻¹ cm⁻²), selective and stable electrochemical sensor for hydrazine. In addition, the successfully application of the developed sensor in spiked tap, bottled and industrial water samples for the detection of hydrazine suggested its feasibility for practical environmental application.

     

Comparative Analysis of Ti,Ni,and Au Electrodes on Characteristics of TiO2 Nanofibers for Humidity Sensor Application

The effect of metal（Ti,Ni,and Au） electrodes on humidity sensing properties of electrospun TiO₂ nanofibers was investigated in this work.The devices were fabricated by evaporating metal contacts on SiO₂ layer thermally grown on silicon substrate.The separation between the electrodes was 90μm for all sensors.The sensors were tested from 40%to 90%relative humidity（RH） by AC electrical characterization at room temperature. When sensors are switched between 40%and 90%RH,the corresponding response and recovery time are 3 s and 5 s for Ti-electrode sensor,4 s and 7 s for Ni-electrode sensor,and 7 s and 13 s for Au-electrode sensor.The hysteresis was 3%,5%and 15%for Ti-,Ni-,and Au-electrode sensor,respectively.The sensitivity of Ti,Ni,and Au-electrode sensors are 7.53 MΩ/%RH,5.29 MΩ/%RH and 4.01 MΩ/%RH respectively at 100 Hz.Therefore Ti-electrode sensor is found to have linear response,fast response and recovery time and higher sensitivity as compared with those of Ni- and Au-electrode sensors.Comparison of humidity sensing properties of sensors with different electrode material may propose a compelling route for designing and optimizing humidity sensors.