Optical and Morphological Properties of Sol Gel derived Titanium dioxide Films

Titanium oxide (Titania) thin films were synthesized on different substrates via the sol-gel dip-coating method using alkoxide solution. Some selected samples were also prepared with different percentage of Lead (Pb). The influence of Pb addition in precursor sol on the optical properties of titanium dioxide thin films was studied. The optical transmittance in the visible region has increased with increase in weight percentage of lead. The refractive index was slightly decreased with Pb addition. Crystallization of these coatings was achieved through thermal annealing at temperatures above 400 degrees C. The structural properties and surface morphology of the crystallized coatings were studied by Scanning Electron Microscopy. Increase in average grain size from 250 nm to 350 nm with increase in Pb concentration is observed. Films were appeared to more coarse with increase in Pb addition. An increase in Pb addition resulted increase in average roughness from 12 nm to 25 nm.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.

Morphological transitions and buckling characteristics in a nanoparticle-laden sessile droplet resting on a heated hydrophobic substrate

In this work, we have established the evaporation-liquid flow coupling mechanism by which sessile nanofluid droplets on a hydrophobic substrate evaporate and agglomerate to form unique morphological features under controlled external heating. It is well understood that evaporation coupled with internal liquid flow controls particle transport in a spatiotemporal sense. Flow characteristics inside the heated droplet are investigated and found to be driven by the buoyancy effects. Velocity magnitudes are observed to increase by an order at higher temperatures with similar looking flow profiles. The recirculating flow induced particle transport coupled with collision of particles and shear interaction between them leads to the formation of dome shaped viscoelastic shells of different dimensions depending on the surface temperature. These shells undergo sol-gel transition and subsequently undergo buckling instability leading to the formation of daughter cavities. With an increase in the surface temperature, droplets exhibit buckling from multiple sites over a larger sector in the top half of the droplet. Irrespective of the initial nanoparticle concentration and substrate temperature, growth of a daughter cavity (subsequent to buckling) inside the droplet is found to be controlled by the solvent evaporation rate from the droplet periphery and is shown to exhibit a universal trend.

A mode-shape classification technique for robust speech rate estimation and syllable nuclei detection

Acoustic feature based speech (syllable) rate estimation and syllable nuclei detection are important problems in automatic speech recognition (ASR), computer assisted language learning (CALL) and fluency analysis. A typical solution for both the problems consists of two stages. The first stage involves computing a short-time feature contour such that most of the peaks of the contour correspond to the syllabic nuclei. In the second stage, the peaks corresponding to the syllable nuclei are detected. In this work, instead of the peak detection, we perform a mode-shape classification, which is formulated as a supervised binary classification problem - mode-shapes representing the syllabic nuclei as one class and remaining as the other. We use the temporal correlation and selected sub-band correlation (TCSSBC) feature contour and the mode-shapes in the TCSSBC feature contour are converted into a set of feature vectors using an interpolation technique. A support vector machine classifier is used for the classification. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora in a five-fold cross validation setup. The average correlation coefficients for the syllable rate estimation turn out to be 0.6761, 0.6928 and 0.3604 for three corpora respectively, which outperform those obtained by the best of the existing peak detection techniques. Similarly, the average F-scores (syllable level) for the syllable nuclei detection are 0.8917, 0.8200 and 0.7637 for three corpora respectively. (C) 2016 Elsevier B.V. All rights reserved.

Morphological Evolution During Synthesis of New AlPO4 Center dot H2O Crystal

A new crystal of aluminophosphate, AIPO(4)(.)H(2)O, is synthesized from two-batch aqueous solution under hydrothermal conditions. Three types of the crystal habits, i.e. the tetragonal double pyramid, the tetragonal prism and the plate-type tetragonal prism, are found from batch-A solution. Two types of the crystal habits, i.e. the hexagonal pyramid and the strip-type tetragonal prism, are found from batch-B solution. The change of crystal morphology is originated from the fluctuation of the synthesis conditions, such as the supersaturation, the temperature and the impurity content. It causes change of the step energies, the defect density and the step roughness, and further, change of the growth rates. Since the crystal morphology is sensitive to the mass transport mechanism, the crystal habits could be changed under the microgravity.

Morphological Stability of Epitaxial Thin Elastic Films by Van Der Waals Force

The morphological stability of epitaxial thin elastic films on a substrate by van der Waals force is discussed. It is found that only van der Waals force with negative Hamaker constant (A < 0) tends to stabilize the film, and the lower bound for the Hamaker constant is also obtained for the stability of thin film. The critical value of the undulation wavelength is found to be a function of both film thickness and external stress. The charateristic time-scale for surface mass diffusion scales to the fourth power to the wavelength of the perturbation.

Probabilistic graphical models for semi-supervised traffic classification

Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.

Case Study: Influence Of Morphological Changes On Flooding In Jingjiang River

The middle reach of the Yangtze River, customarily called the Jingjiang River, together with its diversion channels and Dongting Lake, form a large complicated drainage system. In the last five decades, significant geomorphological changes have occurred in the drainage system, including the shrinkage of diversion channels, contraction of Dongting Lake, changes in the rating curve at the Luoshan station, and cutoffs of the lower Jingjiang River. These changes are believed to be the cause of the occurrence of abnormal floods in the Jingjiang River. Qualitative analyses suggest that the first three factors aggravate the flood situation in the lower Jingjiang River, while the last factor seems beneficial for flood prevention. To quantitatively evaluate these conclusions, a finite-volume numerical model was constructed. A series of numerical simulations were carried out to test the individual and combined effects of the aforementioned four factors, and these simulations showed that high flood stages in the Jingjiang River clearly are related to the geomorphological changes.