Influence of pH on particle size and sensing response of chemically synthesized chromium oxide nanoparticles to alcohols

Nanoparticles of chromium oxide have been synthesized by following a co-precipitation route at various pH values of the precursor solution. Structural and morphological analysis were carried out by using XRD and TEM techniques which revealed that the size of nanoparticles synthesized at pH 9 was smaller as compared to those synthesized at other pH values. The thick films of synthesized samples were deposited on alumina substrate and their sensing response to methanol, ethanol and isopropanol was investigated at different operating temperatures. It was observed that all the sensors gave optimum response at 250 °C. It has been observed that sample prepared at pH 9, being a collection of smallest particles as compared to other samples, exhibited high sensing response to alcohol vapour. Sensor response of all the samples tested was significantly higher towards isopropanol vapour than towards methanol or ethanol.In the present study the effect of particle size on intergranular activation energy has been studied as well. It was found that smaller particles possess high activation energy and exhibit higher sensing response as compared to that of larger particles. This type of study may help in the selection of particle suitable for gas sensing.     

First-principles study of ground-state properties and phase stability of vanadium nitrides

Using a series of density functional electronic structure total energy calculations, we have systematically studied the ground-state properties and phase stability of vanadium nitrides. Comparison of enthalpy of formation shows that V ₂N is equally stable (polymorphic) in , and Fe₂C phases within a few meV. Formation enthalpy of the various phases considered for perfect stoichiometric V N_1.0 shows that it has enhanced stability in hexagonal WC and NiAs structures in relation to NaCl-type δ-phase. The TiAs phase of VN has nearly same energy as NaCl structure. Comparison of energetics of -type , for x=0 and 0.3333 and of , for x=0, 0.0625, 0.125 and 0.25 shows that vacancies on the nitrogen sublattice lowers the formation enthalpy in relation to respective stoichiometric phases which is in agreement with experiments, as bulk vanadium nitrides are known to be generally non-stoichiometric. The calculated dilute heat of solution for the interstitial nitrogen is found to be in good agreement with experimental values and shows that nitrogen prefers to occupy the octahedral sites in bcc vanadium. The α^′-FeN and martensite structures, considered for the metastable phases of vanadium nitrides, have higher formation enthalpy in relation to equilibrium phases. Analysis of electronic density of states of V ₂N shows that the low energy , and Fe₂C phases are characterized by broad V 3d-N 2p and V 3d bonding bands. Density of states of VN shows that in the low energy WC and NiAs phases some of the antibonding states are made empty, leading to a minimum near the Fermi level. For and , density of states shows that vacancies on the nitrogen sublattice introduce additional filled states in the 3d band below Fermi level enabling enhanced bonding. Comparison between bulk moduli and atomic volumes for the various phases of vanadium nitrides shows that higher bulk moduli are dominated by increased V–N bonds combined with low atomic volumes.     

Implementation of a Gaussian process-based machine learning grasp predictor

With the goal of advancing the state of automatic robotic grasping, we present a novel approach that combines machine learning techniques and physical validation on a robotic platform to develop a comprehensive grasp predictor. After collecting a large grasp sample set (522 grasps), we first conduct a statistical analysis of the predictive ability of grasp quality metrics that are commonly used in the robotics literature. We then apply principal component analysis and Gaussian process (GP) algorithms on the grasp metrics that are discriminative to build a classifier, validate its performance, and compare the results to existing grasp planners. The key findings are as follows: (i) several of the existing grasp metrics are weak predictors of grasp quality when implemented on a robotic platform; (ii) the GP-based classifier significantly improves grasp prediction by combining multiple grasp metrics to increase true positive classification at low false positive rates; (iii) The GP classifier can be used generate new grasps to improve bad grasp samples by performing a local search to find neighboring grasps which have improved contact points and higher success rate.     

Two-echelon fuzzy stochastic supply chain for the manufacturer–buyer integrated production–inventory system

This paper deals with two-echelon integrated procurement production model for the manufacturer and the buyer integrated inventory system. The manufacturer procures raw material from outside suppliers (not a part of supply chain) then proceed to convert it as finished product, and finally delivers to the buyer, who faces imprecise and uncertain, called fuzzy random demand of customers. The manufacturer and the buyer work under joint channel, in which a centralized decision maker makes all decisions to optimize the joint total relevant cost (JTRC) of entire supply chain. In this account, in one production cycle of the manufacturer we determine an optimal multi-ordering policy for the buyer. To be part of this, we first derive the JTRC in stochastic framework, and then extend it in fuzzy stochastic environment. In order to scalarize the fuzzy stochastic JTRC, we use an evaluation method wherein randomness is estimated by probabilistic expectation and fuzziness is estimated by possibilistic mean based on possibility evaluation measure. To derive the optimal policies for both parties, an algorithm is proposed. A numerical illustration addresses the situations of paddy procurement, conversion to rice and fulfillment of uncertain demand of rice. Furthermore, sensitivity of parameters is examined to illustrate the model and algorithm.     

Tri‐band composite cylindrical dielectric resonator antenna with hybrid mode excitation and cross‐polarization suppression

This communication investigates composite cylindrical dielectric resonator antenna (CDRA) for various wireless applications. Three important features of proposed antenna design are (i) realization of two different hybrid modes, that is, HEM_11δ and HEM_12δ mode in CDRA with the help of modified annular ring printed line (work as both magnetic dipole and electric dipole), both the hybrid modes support broadside radiation characteristics (ii) suppression of HEM_21δ mode, in order to reduce the cross‐polarization level in H‐plane of other hybrid modes (HEM_11δ and HEM_12δ mode) by an amount of 8‐10 dB (iii) creation of triple‐band attribute using the concept of composite antenna. The proposed antenna design has been fabricated and practically tested. Simulated outcomes show good agreement with measured outcomes. It works in three frequency bands, that is, 2.25‐2.79 GHz, 3.1‐4.0 GHz, and 5.05‐5.6 GHz. The designed antenna structure is appropriate for WLAN and WiMAX applications.     

Combining the Power of Taverna and caGrid: Scientific Workflows that Enable Web-Scale Collaboration

Service-oriented architecture represents a promising approach to integrating data and software across different institutional and disciplinary sources, thus facilitating Web-scale collaboration while avoiding the need to convert different data and software to common formats. The US National Cancer Institute's Biomedical Information Grid program seeks to create both a service-oriented infrastructure (caGrid) and a suite of data and analytic services. Workflow tools in caGrid facilitate both the use and creation of services by accelerating service discovery, composition, and orchestration tasks. The authors present caGrid's workflow requirements and explain how they met these requirements by adopting and extending the Taverna system.     

An empirical investigation into the difficulties experienced by visually impaired Internet users

In this paper, an empirical based study is described which has been conducted to gain a deeper understanding of the challenges faced by the visually impaired community when accessing the Web. The study, involving 30 blind and partially sighted computer users, has identified navigation strategies, perceptions of page layout and graphics using assistive devices such as screen readers. Analysis of the data has revealed that current assistive technologies impose navigational constraints and provide limited information on web page layout. Conveying additional spatial information could enhance the exploration process for visually impaired Internet users. It could also assist the process of collaboration between blind and sighted users when performing web-based tasks. The findings from the survey have informed the development of a non-visual interface, which uses the benefits of multimodal technologies to present spatial and navigational cues to the user.