Towards a super-resolution based approach for improved face recognition in low resolution environment

Multimedia Tools and Applications - The video surveillance activity generates a vast amount of data, which can be processed to detect miscreants. The task of identifying and recognizing an object...     

Impact behavior of aminosilane functionalized nanosilica based shear thickening fluid impregnated Kevlar fabrics

In the present work, two types of shear thickening fluids have been synthesized by using neat and aminosilane functionalized silica nanoparticles and their viscosity curves have been obtained by the rheometer. Based on the values of peak viscosity of synthesized shear thickening fluids, the surface functionalized nanosilica based shear thickening fluid has been chosen as a best candidate due to the high viscosity for impregnation into the neat Kevlar of different layers viz. four (04) and eight (08) layers for velocity impact study. The experimental investigations reveal high energy absorption of shear thickening fluid impregnated Kevlar as compared to the neat Kevlar. The maximum energy absorption 62 J is achieved corresponding to the initial velocity 154 m∙s⁻¹ for 08 layers shear thickening fluid impregnated Kevlar specimen. The data have also been analytically determined and validated with the experimental data. The experimental data have good agreement with the analytical data within the accuracy of around 15 to 20%. The present findings can have significant inferences towards the fabrication of shear thickening fluids using nanomaterials for numerous applications such as soft armors, dampers, nanofinishing and so forth.     

Instability due to Viscosity Stratification Downstream of a Centerline Injector

A common injector geometry upstream of a static mixer is the centerline injector. A flow instability can arise due to viscosity differences between the injected core‐flow and the outer co‐flow. This instability can adversely affect the effectiveness of the mixing operation. An experimental investigation of miscible viscosity‐stratified flow in a circular geometry was performed using Laser Induced Fluorescence (LIF) and Particle Image Velocimetry (PIV). The experimental results for the stable region agree with the analytical results. The unstable region exhibits different modes depending on the viscosity ratio, volume flux ratio, and Reynolds number. The modes include wavy core‐flow with fissures and wavy core‐flow with core breakup. The time‐averaged experiment velocity profiles for the unstable core indicate a broadening of the jet at the centerline, which is consistent with the LIF visualization.     

Characterization of in Vitro Transdermal Iontophoretic Delivery of Insulin

In-vitro studies were conducted to characterize the transdermal iontophoretic delivery of insulin, thus avoiding potential complications from various biological variations, which may be encountered during in-vivo studies. The proteolytic degradation of insulin in skin homogenates and degradation under the experimental conditions used was investigated. Appropriate adjuvants were incorporated to minimize the potential degradation problems of insulin. ¹²⁵I-Insulin was observed to penetrate into and accumulate in the skin during the iontophoresis period. It was then released gradually from this depot, as a mixture of intact and ¹²⁵-I labelled fragments, into the receptor medium. Drug desorption studies supported the theory of skin depot or reservoir formation. It was found that an electric field could be used to facilitate the desorption of drug from the depot. The post-application flux of insulin (or its fragments) from the skin depot formed during iontophoresis was monitored to study the factors affecting the iontophoretic delivery of insulin. Stripping and delipidization of the skin were noted to increase the skin permeation rate of insulin. The cumulative radioactivity permeated and accumulated in the skin was higher at pH 3.6 than at pH 7.4. The iontophoresis-facilitated transdermal delivery was observed to increase with increasing duration of current application and increasing donor concentration of insulin. Modulation of drug delivery by multiple applications was also found to be feasible.     

TopoAct: Visually Exploring the Shape of Activations in Deep Learning

Deep neural networks such as GoogLeNet, ResNet, and BERT have achieved impressive performance in tasks such as image and text classification. To understand how such performance is achieved, we probe a trained deep neural network by studying neuron activations, i.e.combinations of neuron firings, at various layers of the network in response to a particular input. With a large number of inputs, we aim to obtain a global view of what neurons detect by studying their activations. In particular, we develop visualizations that show the shape of the activation space, the organizational principle behind neuron activations, and the relationships of these activations within a layer. Applying tools from topological data analysis, we present TopoAct , a visual exploration system to study topological summaries of activation vectors. We present exploration scenarios using TopoAct that provide valuable insights into learned representations of neural networks. We expect TopoAct to give a topological perspective that enriches the current toolbox of neural network analysis, and to provide a basis for network architecture diagnosis and data anomaly detection.     

Visible‐light‐induced controlled/living radical polymerization of styrene with a phenyl seleno group at one terminal chain end: 1‐(Phenylseleno)ethyl benzene as a photoiniferter

The photopolymerization of styrene with a well‐defined molecular architecture and a low polydispersity index and with methyl and phenylseleno (? SePh) groups at α‐ and ω‐chain ends, respectively, was performed via a controlled/living radical polymerization with a new initiating system, 1‐(phenylseleno)ethyl benzene/tert‐butyl diphenyl (phenylseleno) silane, through the absorption of visible light at room temperature. A novel initiating living radical polymerization was examined. The yield and number‐average molecular weight (M_n) of the resulting polymer increased with the reaction time. Furthermore, a linear relationship was found in a plot of M_n versus the polymer yield. These results indicated that this polymerization proceeded through a living radical mechanism. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 348–355, 2004     

Optimization of reactive SMB and Varicol systems

A comprehensive optimization study on a simulated moving bed reactor (SMBR) system is reported in this article for the direct synthesis of methyl tertiary butyl ether (MTBE) from tertiary butyl alcohol (TBA) and methanol. The applicability of the Varicol process, which is based on non-synchronous shift of the inlet and outlet ports, is explored for the first time for a reactive system. Multi-objective (two and three objective functions) optimization has been performed for both existing as well as design stage for SMBR and Varicol systems and their efficiencies are compared. The optimization problem involves relatively large number of decision variables; both continuous variables, such as flow rates in various sections and length of the columns and discrete variables, such as number of columns and column configuration. Pareto optimal solutions are obtained. It is observed that a five-column Varicol performs better than an equivalent five-column SMBR and its performance is nearly equal to that of a six-column SMBR in terms of purity and yield of MTBE and minimal eluent consumption. This is an important inference as it enables the reduction of fixed and operating costs while at the same time helps to achieve high purity and yield of the desired product and conversion of the limiting reactant. A state-of-the-art optimization technique, viz., non-dominated sorting genetic algorithm (NSGA), which allows handling of these complex optimization problems, is employed for this study. This is the first time that, not only the separating potential of Varicol has been extended to reaction systems, but also was optimized for multiple objectives.     

Detecting stable locality-aware predicates

In a large-scale locality-driven network such as in modular robotics and wireless sensor networks, knowing the state of a local area is sometimes necessary due to either interactions being local and driven by neighborhood proximity or the users being interested in the state of a certain region. We define locality-aware predicates (LAP) that aim at detecting a predicate within a specified area. We model the area of interest as the set of processes that are within a breadth-first search tree (BFST) of height k$k$ rooted at the initiator process. Although a locality-aware predicate specifies a predicate only within a local area, observing the area consistently requires considering the entire system in a consistent manner. This raises the challenge of making the complexities of the corresponding predicate detection algorithms scale-free, i.e., independent of the size of the system. Since all existing algorithms for getting a consistent view of the system require either a global snapshot of the entire system or vector clocks of the size of the system, a new solution is needed. We focus on stable LAP, which are those LAP that remain true once they become true. We propose a scale-free algorithm to detect stable LAP within a k$k$-height BFST. Our algorithm can detect both stable conjunctive LAP and stable relational LAP. In the process of designing our algorithm, we also propose the first distributed algorithm for building a BFST within an area of interest in a graph, and the first distributed algorithm for recording a consistent sub-cut within the area of interest. This paper demonstrates that LAPs are a natural fit for detecting distributed properties in large-scale distributed systems, and stable LAPs can be practically detected at low cost.     

Sustainable conducting polymer composites: study of mechanical and tribological properties of natural fiber reinforced PVA composites with carbon nanofillers

ABSTRACT

Ball milled jute fiber (JF) was added to Polyvinyl Alcohol (PVA)/20 wt.% multi-layer graphene (MLG) composites in various proportions (0, 5, 10, 15 and 20 wt.%) to prepare sustainable and biodegradable conducting polymer composites. Also, PVA/17.5wt.%MLG/2.5wt.%MWCNT/20wt.% JF composite was prepared for comparison purpose. A dynamic mechanical analysis of the composites was conducted to analyze their viscoelastic nature. The electrical conductivity of the composites was measured to study their suitability for various applications. Jute reinforcement increased the electrical conductivity of PVA/MLG nanocomposites. The PVA/20wt.%JF/17.5wt.%MLG/2.5wt.%MWCNT hybrid composite had the highest electrical conductivity of 3.64 × 10^?4 S/cm among all the composites prepared. Multilayered structures of the hybrid composite films were made by hot-pressing, and their effectiveness in electromagnetic interference shielding was tested. The shielding effectiveness of the composites decreased with jute addition. The wear resistance of PVA/MLG/JF composites increased with an increase in the jute content up to an optimum value of 10 wt.%, and then it started deteriorating.