Microstructural evolution and fracture toughness of plasma sprayed CNT reinforced Yttria-stabilized Hafnia coating

Yttria (8 wt%)-stabilized hafnia (YSH) and carbon nanotubes (CNTs) (1 wt%) reinforced yttria-stabilized hafnia (YSHC) coatings were fabricated on alumina substrate using atmospheric plasma spray technique. Raman spectra confirmed the survival of CNTs in plasma sprayed YSHC coating and indicated about graphitization of CNTs. Whereas, the FE-SEM micrograph infers the presence of few 2-D graphene platelet-like structure in plasma sprayed YSHC coating. Addition of 1 wt% CNTs has significantly increased the densification of YSH coating from 86% to 92%, whereas average hardness and elastic modulus increased by ~57% and ~16%, respectively. A phenomenal increase of ~125% in relative fracture toughness was observed in YSHC coating, which is attributed to three major factors viz. (a) Enhanced densification (b) High fraction of fully melted regions and (c) Various toughening mechanisms, like CNTs pull out, CNTs braiding, graphene splat wrapping, CNTs anchoring.     

Document-level sentiment classification using hybrid machine learning approach

It is a practice that users or customers intend to share their comments or reviews about any product in different social networking sites. An analyst usually processes to reviews properly to obtain any meaningful information from it. Classification of sentiments associated with reviews is one of these processing steps. The reviews framed are often made in text format. While processing the text reviews, each word of the review is considered as a feature. Thus, selection of right kind of features needs to be carried out to select the best feature from the set of all features. In this paper, the machine learning algorithm, i.e., support vector machine, is used to select the best features from the training data. These features are then given input to artificial neural network method, to process further. Different performance evaluation parameters such as precision, recall, f-measure, accuracy have been considered to evaluate the performance of the proposed approach on two different datasets, i.e., IMDb dataset and polarity dataset.     

Energy optimization for CAN bus and media controls in electric vehicles using deep learning algorithms

The Journal of Supercomputing - This study offers a neural network-based deep learning method for energy optimization modeling in electric vehicles (EV). The pre-processed driving cycle is...     

Monte Carlo techniques for phrase-based translation

Recent advances in statistical machine translation have used approximate beam search for NP-complete inference within probabilistic translation models. We present an alternative approach of sampling from the posterior distribution defined by a translation model. We define a novel Gibbs sampler for sampling translations given a source sentence and show that it effectively explores this posterior distribution. In doing so we overcome the limitations of heuristic beam search and obtain theoretically sound solutions to inference problems such as finding the maximum probability translation and minimum risk training and decoding.     

A method for automatic classification of gender based on text- independent handwriting

Handwriting recognition is used for the prediction of various demographic traits such as age, gender, nationality, etc. Out of all the applications gender prediction is mainly admired topic among researchers. The relation between gender and handwriting can be seen from the physical appearance of the handwriting. This research work predicts gender from handwriting using the landmarks of differences between the two genders. We use the shape or visual appearance of the handwriting for extracting features of the handwriting such as slanteness (direction), area (no of pixels occupied by text), perimeter (length of edges), etc. Classification is carried out using the Support Vector Machine (SVM) as a classifier which transforms the nonlinear problem into linear using its kernel trick, logistic regression, KNN and at the end to enhance the classification rates we use Majority Voting. The experimental results obtained on a dataset of 282 writers with 2 samples per writer shows that the proposed method attains appealing performance on writer detection and text-independent environment.

     

Estimation of impact forces during multi-point collisions involving small deformations

Multibody System Dynamics - Collision between hard objects causes abrupt changes in the velocities of the system, which are characterized by very large contact forces over very small time...     

HSIC-based affinity measure for learning on graphs

Pattern Analysis and Applications - The performance of graph-based learning techniques largely relies on the edges defined between the vertices of the graph. These edges that represent the affinity...     

Novel analysis of the size and orientation dependent resonance phenomenon of the microstrip line coupled complementary split‐ring resonator

The purpose of this article is to provide a comprehensive investigation on the resonance phenomenon of microstrip line coupled complementary split‐ring resonator (CSRR) with different orientation and relative size. It is shown that when the relative size of the CSRR is smaller than the host line, the CSRR with its slit oriented orthogonal to the line axis will not excite effectively and show weak resonance behavior. However, when the slit is positioned along the line axis, the cross‐polarization effect comes into play, which excites the CSRR through the mixed coupling. To ensure the correctness, several numerical simulations are carried out for different substrate height and relative permittivity. Finally, a prototype is fabricated and measured for the experimental validation.     

An address assignment for the automatic configuration of mobile ad hoc networks

Mobile ad hoc networks (MANETs) are infrastructure-less, multi-hop wireless networks, which can be deployed without any pre-existing setup. MANETs are mobile in nature and any node can join and leave the network at any time. Due to mobility, MANETs must be able to configure themselves without human intervention. Configuration (such as address assignment) of a node in such a network is an important issue. In this paper, we present a solution for address assignment, which is distributed in nature and can be used for IP address configuration in MANETs. Each node can allocate the address independent of others. Although our solution uses broadcast messages, results show that by fixing a few parameter values we can reduce the number of broadcast messages. We simulate the protocol and results show that our solution yields better performance those of the earlier algorithms.

Providing Dynamic Visual Information for Collaborative Tasks: Experiments With Automatic Camera Control

One possibility presented by novel communication technologies is the ability for remotely located experts to provide guidance to others who are performing difficult technical tasks in the real world, such as medical procedures or engine repair. In these scenarios, video views and other visual information seem likely to be useful in the ongoing negotiation of shared understanding, or common ground, but actual results with experimental systems have been mixed. One difficulty in designing these systems is achieving a balance between close-up shots that allow for discussion of detail and wide shots that allow for orientation or establishing a mutual point of focus in a larger space. Achieving this balance can be difficult without disorienting or overloading task participants. In this article we present results from two experiments involving three automated camera control systems for remote repair tasks. Results show that a system providing both detailed and overview information was superior to systems providing only one or the other in terms of performance but that some participants preferred the detail-only system.