On the estimation of the solid liquid interfacial energy of glassy alloys as a function of temperature and structure

An attempt has been made to find out a model based on homogeneous nucleation principle to estimate solid liquid interfacial energy as a function of temperature and structure for a number of glassy alloy systems. Easy estimation of interfacial energy is stemmed from the availability of thermal and viscosity data for glassy alloys. Good match has been found in the interfacial energies with the reported values.     

Hybrid Models for Breast Cancer Detection via Transfer Learning Technique

Currently, breast cancer has been a major cause of deaths in women worldwide and the World Health Organization (WHO) has confirmed this. The severity of this disease can be minimized to the large extend, if it is diagnosed properly at an early stage of the disease. Therefore, the proper treatment of a patient having cancer can be processed in better way, if it can be diagnosed properly as early as possible using the better algorithms. Moreover, it has been currently observed that the deep neural networks have delivered remarkable performance for detecting cancer in histopathological images of breast tissues. To address the above said issues, this paper presents a hybrid model using the transfer learning to study the histopathological images, which help in detection and rectification of the disease at a low cost. Extensive dataset experiments were carried out to validate the suggested hybrid model in this paper. The experimental results show that the proposed model outperformed the baseline methods, with F-scores of 0.81 for DenseNet + Logistic Regression hybrid model, (F-score: 0.73) for Visual Geometry Group (VGG) + Logistic Regression hybrid model, (F-score: 0.74) for VGG + Random Forest, (F-score: 0.79) for DenseNet + Random Forest, and (F-score: 0.79) for VGG + Densenet + Logistic Regression hybrid model on the dataset of histopathological images.     

New Modified Controlled Bat Algorithm for Numerical Optimization Problem

Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark test problems. The finding of our technique shows promising performance as compared to the standard PSO and standard BA. The proposed MCBA, BPA, Standard PSO, and Standard BA have been examined for well-known benchmark test problems and training of the a.pngicial neural network (ANN). We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning (ML) repository of UCI. Simulation results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness, with more superiority compared to the traditional methodologies. The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future.     

Variation of physical and rheological properties of fly ash slurries with particle size and its effect on hydraulic transportation at high concentrations

In thermal power plants, fly ash is collected at the bottom of electrostatic precipitator (ESP) hoppers and transported to common sump for further disposal to the ash pond by slurry pipelines. The fly ash from different fields of ESP hoppers vary widely in particle size as well as quantity. Depending on the sequence of evacuation, the overall particle size distribution (PSD) would vary with time which in turn would affect the head requirement in the high concentration slurry disposal (HCSD) system. Fly ash samples from different fields of ESP hoppers of a thermal power plant have been analyzed for their physical properties namely the PSD, specific gravity, settling characteristics, pH of the slurry, etc. and for rheological properties in the concentration range of 60–70% (by weight). The particle size (d_wm) of the fly ash samples decreases with the increase in ESP field, whereas the static settled concentration and specific density increase. The pH values of all samples are almost constant and nonreactive in nature. The rheological properties namely yield stress and Bingham viscosity of the fly ash slurries from different fields of ESP hoppers increase with increase in concentration. Further at any given concentration, these parameters exhibit a strong dependence on particle size. Using these properties and treating the distribution of particles across the pipe cross section as homogeneous in the concentration range of 60–70% (by weight), CFD computations are made to evaluate the head requirement in a HCSD pipeline. The head loss increases with increase in concentration for all fields of ESP hoppers. The present study also shows that head requirement varies significantly by mixing different proportion of fly ash from different ESP fields.     

Possible existence of a higher coverage quasi-one-dimensional phase of argon adsorbed on bundles of single-walled carbon nanotubes

We present results of Ar adsorption isotherms at very low coverages in the first layer and, beyond monolayer completion, on bundles of close-ended single-walled carbon nanotubes. The low coverage results were used to determine the isosteric heat of adsorption and the binding energy of Ar in the groove sites in the first layer. The higher coverage results show evidence of the possible formation of a second-layer groove phase, beyond monolayer completion. Our results for higher coverages are compared with recent computer simulations for this system.     

Structural and optical properties of sol gel derived Cu2ZnSnS4 nanoparticles

The spherical Cu₂ZnSnS₄ nanoparticles with the average diameters (～8–10 nm) have been synthesized by sol gel method. The effects of solvents and reaction temperatures on the properties of the as-synthesized nanoparticles were investigated. The X-ray diffraction shows as grown Cu₂ZnSnS₄ nanoparticles exhibit kesterite crystal structure along preferential orientation (1 1 2) plane. The crystalline nature of nanoparticles was improved in ethylene glycol solvent with the increase in reaction temperature. Rietveld refinement study was performed and structural parameters were determined for the Cu₂ZnSnS₄ nanoparticles. The Raman spectra show the main characteristic peak of A₁ vibrational mode which confirmed the formation of Cu₂ZnSnS₄ phase in all the samples. Scanning electron micrographs depict the irregular aggregate formation of nanoparticles in methanol solvent and uniformly distributed aggregates of nanoparticles with ethylene glycol solvent. Transmission electron microscopy results show the synthesis of polycrystalline porous nanostructures and uniform spherical nanoparticles in methanol and ethylene glycol solvents respectively at the temperature of 250 °C. UV–vis absorption spectra indicated the broad absorption in visible range and the band gap of the nanoparticles was found to 1.38 and 1.45 eV which is suitable for absorbing the solar radiation. The obtained results revealed ethylene glycol as a suitable solvent and 250 °C as the favorable synthesis temperature.     

Remote-sensing and GIS-based landslide-susceptibility zonation using the landslide index method in Igo River Basin,Eastern Himalaya,India

A remote-sensing and geographical information sysytem (GIS)-based quantitative methodology for landslide-susceptibility zonation is described in a stepwise manner with its application in the Igo River Basin in the West Siang District of Arunachal Pradesh, Eastern Himalaya, India. Parameters such as geology, physiography, slope angle, slope length, slope aspect, slope type, generic landforms, lineament distance, road distance, drainage distance, altitudinal zones and land cover are used for landslide-susceptibility zonation. The quantitative relation between landslides and the selected parameters is established through the landslide index method of the International Institute for Geo-Information Science and Earth Observation (ITC), The Netherlands, by assigning weights. A weight value for a certain parameter class is defined as the natural logarithm of the landslide density in the class divided by the landslide density in the entire map. The final layer containing the composite index is divided into seven landslide-susceptibility categories. The maximum portion of the study area experiences moderately low to moderate landslide susceptibility, and each portion occupies an area of 91 km², representing 30% of the total area. High concentrations of very high and extremely high-susceptibility landslide areas are noticed in the steep slope areas, especially in the Sub-Himalayas. The settlements are found in the safe areas of very low, low and moderately low landslide-susceptibility categories. About 9% and 1.99% of the roads are exposed to high and very high landslide-susceptibility areas, respectively. About 15% of the slash-and-burn cultivation (jhum) is found along the high-susceptibility areas, 3.89% is found in very high-susceptibility areas and 0.19% is prone to extremely high susceptibility. The high-susceptibility zones are also found under dense and moderately dense forests.     

Modeling of wideband radio frequency power amplifiers using Zernike polynomials

In this article, we suggest a new set of basis functions that are based on Zernike polynomials for the behavioral modeling of radio frequency power amplifiers (PAs). The modeling of highly nonlinear PAs exhibits numerical instability that degrades the accuracy of the model parameters and predistorter modeling efficiency. Simulation results show that the proposed polynomial model is more suitable to resolve the numerical instability problem and proves to have greater accuracy with reduced complexity. A Doherty PA driven by a multicarrier wideband code division multiple access signal was used for validation; and, the obtained results show that the new model exhibits superior numerical stability as the nonlinearity order and memory depth of the model increase. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

Use of initial rise method to analyze a general-order kinetic thermoluminescence glow curve

The application of the initial rise method, in the case of the general-order kinetics of thermoluminescence, has so far been limited to finding the thermal activation energy. However, the order of kinetics and pre-exponential factors could not be evaluated using this method so one has to resort to other methods of glow curve analysis. In the present paper, a novel method is suggested to calculate the kinetic order and the pre-exponential factor from the Arrhenius plots of the initial rise part of the thermoluminescence glow curve. The method uses the intercept values on the thermoluminescence intensity axis of the Arrhenius plots at two or more known doses to evaluate the value of kinetic order.     

A study of physicochemical characteristics of respirable dust in an Indian coal mine

The respirable coal dust samples were collected from the mine atmosphere during drilling of coal seams using ‘Hexlet’ apparatus. Sixteen dust samples were collected from each three different seams for investigations. After destruction of the organic matter by wet oxidation and filtering off the clay and silica, Fe, Ca, Mg, Na, K, Mn, Zn, Cu, Cd and Ni were determined directly in the resulting solution by atomic absorption spectrophotometric methods. The x-ray diffraction studies have shown the presence of kaolinite, quartz, pirrsonite, and beidellite clay minerals in the coal dust.The mass-size distribution of the coal dust has been studied by using micron photosizer. The results showed that the distribution are unimodal, asymmetric, and positively skew. Although the assumption of log-normality was useful in interpreting the results, closer observations indicated that the relationship between the size and weight of the particles can be represented by a second degree parabolic equation W = a + bS + cS², where W and S are weight and size of the particles and a, b and c are constants. This equation helps us to characterise the mass of the respirable particles if the size is known.The studies throw light on the nature and mode of trace elements found in Indian Coal as well as on the causes of respiratory disease, pneumoconiosis, affecting the workers in the mine environmental condition.