Preprogramming Floating Time of Liquid Marble

Non-sticking droplets wrapped with fine hydrophobic particles, namely liquid marbles, can be transported both on solid and water pool without an undesired spill of the inner encapsulated liquid. While the stimuli-responsive release of the inner liquid in the target area is proposed, the time-programmed release is not yet achieved. Herein, the hydrophobicity of nanoclay is modulated via a catalyst-free 1,4-conjugate addition reaction to form liquid marbles. This nanoclay liquid marble is robust and stable in air but collapses on the liquid pool with a specific lifetime. The lifetime of the liquid marble can be modulated over seconds to hours scale depending on the selection of chemically modulated wettability of the nanoclay. The critical mechanism of lifetime modulation is responsible for controlling the coalescence kinetics between the water pool and inner liquid by nanoclays’ high diffusion length and chemically varied water spreading potential. The NC liquid marble's programmable lifetime to ‘time-bomb’ type drug release and cascade chemical reaction is applied—without requiring any external intervention.     

A symmetry based multiobjective clustering technique for automatic evolution of clusters

In this paper the problem of automatic clustering a data set is posed as solving a multiobjective optimization (MOO) problem, optimizing a set of cluster validity indices simultaneously. The proposed multiobjective clustering technique utilizes a recently developed simulated annealing based multiobjective optimization method as the underlying optimization strategy. Here variable number of cluster centers is encoded in the string. The number of clusters present in different strings varies over a range. The points are assigned to different clusters based on the newly developed point symmetry based distance rather than the existing Euclidean distance. Two cluster validity indices, one based on the Euclidean distance, XB-index, and another recently developed point symmetry distance based cluster validity index, Sym-index, are optimized simultaneously in order to determine the appropriate number of clusters present in a data set. Thus the proposed clustering technique is able to detect both the proper number of clusters and the appropriate partitioning from data sets either having hyperspherical clusters or having point symmetric clusters. A new semi-supervised method is also proposed in the present paper to select a single solution from the final Pareto optimal front of the proposed multiobjective clustering technique. The efficacy of the proposed algorithm is shown for seven artificial data sets and six real-life data sets of varying complexities. Results are also compared with those obtained by another multiobjective clustering technique, MOCK, two single objective genetic algorithm based automatic clustering techniques, VGAPS clustering and GCUK clustering.     

Automatic MR brain image segmentation using a multiseed based multiobjective clustering approach

In this paper, the automatic segmentation of a multispectral magnetic resonance image of the brain is posed as a clustering problem in the intensity space. The automatic clustering problem is thereafter modelled as solving a multiobjective optimization (MOO) problem, optimizing a set of cluster validity indices simultaneously. A multiobjective clustering technique, named MCMOClust, is used to solve this problem. MCMOClust utilizes a recently developed simulated annealing based multiobjective optimization method as the underlying optimization strategy. Each cluster is divided into several small hyperspherical subclusters and the centers of all these small sub-clusters are encoded in a string to represent the whole clustering. For assigning points to different clusters, these local sub-clusters are considered individually. For the purpose of objective function evaluation, these sub-clusters are merged appropriately to form a variable number of global clusters. Two cluster validity indices, one based on the Euclidean distance, XB-index, and another recently developed point symmetry distance based cluster validity index, Sym-index, are optimized simultaneously to automatically evolve the appropriate number of clusters present in MR brain images. A semi-supervised method is used to select a single solution from the final Pareto optimal front of MCMOClust. The present method is applied on several simulated T1-weighted, T2-weighted and proton density normal and MS lesion magnetic resonance brain images. Superiority of the present method over Fuzzy C-means, Expectation Maximization clustering algorithms and a newly developed symmetry based fuzzy genetic clustering technique (Fuzzy-VGAPS), are demonstrated quantitatively. The automatic segmentation obtained by multiseed based multiobjective clustering technique (MCMOClust) is also compared with the available ground truth information.     

Computer Vision Techniques Applied for Diagnostic Analysis of Retinal OCT Images: A Review

The retina is a tiny layer at the posterior pole of an eye and is made up of tissues sensitive to light, these tissues generate nerve signals that pass through the optic nerve to the brain. A retinal disorder occurs when the retina malfunctions; glaucoma, diabetic retinopathy and pathologic myopia are retinal disorders and principal causes of blindness worldwide. These retinal disorders are often diagnosed and treated by an ophthalmologist. However, to accurately assess a retinal disease, ophthalmologist would need qualitative and quantitative analysis of the disease, it’s early and current statistics, but acquisition of these measurements are not possible through manual techniques, there should be automated computer aided diagnosis (CAD) systems to assist ophthalmologists. In this comprehensive review, an analysis and evaluation has been performed of different computer vision and image processing approaches applied to OCT images for automatic diagnosis of retinal disorders. We also reported disease causes, symptoms and pathologies manifestations within OCT images, which can serve as baseline knowledge for development of an automated CAD system. Hence, this disease specific review offers a good understanding to analyze visual impairments from retinal OCT images which will help researcher to design enhanced therapeutic systems for retinal disorders.     

SAFE: An Efficient Feature Extraction Technique

This paper proposes an efficient window-based semi-automatic feature extraction technique which uses simulated annealing for minimizing the energy of an active contour within a specified image region. The energy is computed based on a chamfer image, in which pixel values are a function of distance to image edges. A user places a number of control points close to the feature of interest. B-spline fitted to these points provides an initial approximation of the contour. A window containing both the initial contour and the feature of interest is considered. The contour with minimum energy inside the window provides the final delineation. Comparison of the performance of the proposed algorithm with traditional snake, a popular feature extraction technique based on energy minimization, demonstrates the superiority of the SAFE technique. Received 18 August 1999 / Revised 25 October 2000 / Accepted in revised form 8 December 2000     

Magnetization reversal mechanism of chemically synthesized linear chains of α-Fe nanospheres

Journal of Materials Science - We report upon synthesis of stable chains of magnetically aligned zero-valent α-Fe nanoparticles and investigation of their magnetization reversal mechanism. The...     

Green composites based on high‐density polyethylene and Saccharum spontaneum: Effect of filler content on morphology,thermal, and mechanical properties

Here we report the preparation and characterization of a green composite based on high‐density polyethylene and Kaans grass (Saccharum spontaneum). The composites were prepared by conventional melt‐mixing method, using maximum loading of Kaans grass in powder form (KG‐filler) to achieve acceptable range of required properties. Maleic anhydride grafted polyethylene was used as compatibilizer to achieve effective interaction for improved surface adhesion which was confirmed by FT‐IR spectroscopy. Morphological studies revealed good interaction between the base polymer matrices and the KG‐fillers that improved the mechanical and thermal properties of the composites up to certain (10 phr) KG‐filler loading. Study on water absorption property revealed moderate increase in weight at higher KG‐filler loadings. Thermogravimetric analysis (TGA) and melt flow index (MFI) studies indicated retention of thermal stability and flow property of the HDPE/KG‐filler composite at lower filler loadings. POLYM. COMPOS., 36:2157–2166, 2015. © 2014 Society of Plastics Engineers     

Studies on Transport Phenomena during Continuous Casting of an Al-Alloy in Presence of Electromagnetic Stirring

In the present work, a numerical study is performed to predict the transport phenomena during continuous casting of an aluminum alloy (A356) in presence of weak stirring. A set of volume averaged single phase conservation equations (mass, momentum, energy and species) is used to represent the casting process. The electromagnetic forces are incorporated in the momentum equations. The governing equations are solved based on the pressure-based finite volume method according to the SIMPLER algorithm using TDMA solver along with an enthalpy update scheme. The simulation predicts the temperature, solid fraction and species in the computational domain. A parametric study is also performed.