A New Approach for Selection of Optimal Process Parameters in Abrasive Water Jet Cutting

This paper presents a new approach, based on the principles of fuzzy logic and Genetic Algorithm (GA) for selection of optimal process parameters in Abrasive Water Jet (AWJ) cutting of granite to any predetermined depth, using multi-criteria optimization technique. The proposed approach suggests the best combination of process parameters such as water jet pressure, jet traverse rate and abrasive flow rate for cutting granite material to any predetermined depth. GA, in combination with the model built based on fuzzy approach, generates several sets of process parameters satisfying the objective of achieving the desired depth of cut. These sets of parameters are subjected to multi-criteria optimization procedure which suggests a set of process parameters that can minimize the cost of production by increasing the rate of production and reducing the consumption of abrasives, maintaining the desired depth of cut within the specified limits. The proposed approach is validated with suitable experiments conducted on Paradiso granite.     

Methionine-pyrene hybrid based fluorescent probe for trace level detection and estimation of Hg(II) in aqueous environmental samples: experimental and computational studies

A new fluorescent, Hg(2+) selective chemosensor, 4-methylsulfanyl-2-[(pyren-4-ylmethylene)-amino] butyric acid methyl ester (L, MP) was synthesized by blending methionine with pyrene. It was well characterized by different analytical techniques, viz. (1)H NMR, (13)C NMR, QTOF mass spectra, elemental analysis, FTIR and UV-vis spectroscopy. The reaction of this ligand with Hg(2+) was studied by steady state and time-resolved fluorescence spectroscopy. The Hg(2+) complexation process was confirmed by comparing FTIR, UV-vis, thermal, QTOF mass spectra and (1)H NMR data of the product with that of the free ligand values. The composition (Hg(2+):L=1:1) of the Hg(2+) complex in solution was evaluated by fluorescence titration method. Based on the chelation assisted fluorescence quenching, a highly sensitive spectrofluorometric method was developed for the determination of trace amounts of Hg(2+) in water. The ligand had an excitation and emission maxima at 360 nm and 455 nm, respectively. The fluorescence life times of the ligand and its Hg(2+) complex were 1.54 ns and 0.72 ns respectively. The binding constant of the ligand, L with Hg(2+) was calculated using Benesi-Hildebrand equation and was found to be 7.5630×10(4). The linear range of the method was from 0 to 16 μg L(-1) with a detection limit of 0.056 μg L(-1) for Hg(2+). The quantum yields of the ligand and its Hg(2+) complex were found to be 0.1206 and 0.0757 respectively. Both the ligand and its Hg(2+) complex have been studied computationally (Ab-initio, Hartree Fock method) to get their optimized structure and other related physical parameters, including bond lengths, bond angles, dipole moments, orbital interactions etc. The binding sites of the ligand to the Hg(2+) ion as obtained from the theoretical calculations were well supported by (1)H NMR titration. The interference of foreign ions was negligible. This method has been successfully applied to the determination of mercury(II) in industrial waste water.     

Trinary magnitude comparator using SLM based Savart plate

The demand of present technology inviting the popularity of multivalued optical computation system to coup up with the latest scenario of ultrahigh processing speed and handling large amount of data The magnitude comparator is the heart of the arithmetic and logic unit (ALU) in any logical processing and computing system. In this paper, a trinary magnitude comparator circuit has been proposed and implemented with modified trinary number (MTN) system. Optical tree architecture (OTA) of the proposed circuit has been realized reasonably using Savart plate and spatial light modulators (SLM). A simulation algorithm has also been developed and implemented to prove the authenticity of the proposed circuit through the simulation.     

Simultaneous Radar Observations of Vertical Profile of Rain Features from Space and Ground at Ku and Ka Bands at a Tropical Location

In this paper parameters of precipitation profiles obtained from precipitation radar aboard tropical rainfall measuring mission satellite and from ground based micro rain radar observations have been compared for different rain events. The dual frequency radar observations of precipitating atmosphere have been utilized to study the vertical profiles of radar reflectivity and rain rate. It is shown that the inclination of the ray path of the satellite borne radar significantly influences the rain rate measurements. The study demonstrates the efficacy of combining space borne and ground-based measurement in obtaining a complete profile of vertical rain structure.     

Electrical properties of hollow glass particle filled vinyl ester matrix syntactic foams

Low dielectric constant materials play a key role in modern electronics. In this regard, hollow particle reinforced polymer matrix composites called syntactic foams may be useful due to their low and tailored dielectric constant. In the current study, vinyl ester matrix/glass hollow particle syntactic foams are analyzed to understand the effect of hollow particle wall thickness and volume fraction on the dielectric constant of syntactic foams. The dielectric constant is found to decrease with increase in the hollow particle volume fraction and decrease in the wall thickness. Theoretical estimates are obtained for the dielectric constant of syntactic foams. Parametric studies are conducted using the theoretical model. It is found that a wide range of syntactic foam compositions can be tailored to have the same dielectric constant, which provides possibility of independently tailoring density and other properties based on the requirement of the application.     

Software diversity: state of the art and perspectives

Diversity is prevalent in modern software systems to facilitate adapting the software to customer requirements or the execution environment. Diversity has an impact on all phases of the software development process. Appropriate means and organizational structures are required to deal with the additional complexity introduced by software variability. This introductory article to the special section “Software Diversity—Modeling, Analysis and Evolution” provides an overview of the current state of the art in diverse systems development and discusses challenges and potential solutions. The article covers requirements analysis, design, implementation, verification and validation, maintenance and evolution as well as organizational aspects. It also provides an overview of the articles which are part of this special section and addresses particular issues of diverse systems development.     

Microwave synthesis of electrode materials for lithium batteries

A novel microwave method is described for the preparation of electrode materials required for lithium batteries. The method is simple, fast and carried out in most cases with the same starting material as in conventional methods. Good crystallinity has been noted and lower temperatures of reaction has been inferred in cases where low temperature products have been identified     

Tribological Behavior of AZ31 Alloy Against Si3N4 Using In-vitro and In-silico Submodeling Approach for Human Hip Prosthesis

Silicon - The use of magnesium alloy (AZ31) has profound applications in biomedical field as a substitute for joint replacements. The present study aims at analyzing the tribological behavior of...     

Learning latent actions to control assistive robots

Autonomous Robots - Assistive robot arms enable people with disabilities to conduct everyday tasks on their own. These arms are dexterous and high-dimensional; however, the interfaces people must...     

Detection and classification of microcalcification from digital mammograms with firefly algorithm,extreme learning machine and non-linear regression models: A comparison

In this study, abnormalities in medical images are analysed using three classifiers, and the results are compared. Breast cancer remains a major public health problem among women worldwide. Recently, many algorithms have evolved for the investigation of breast cancer diagnosis through medical imaging. A computer-aided microcalcification detection method is proposed to categorise the nature of breast cancer as either benign or malignant from input mammogram images. The standard mammogram image corpus, the Mammogram Image Analysis Society database is utilised, and feature extraction is performed using five different wavelet families at level 4 and level 6 decomposition. The work is accomplished through firefly algorithm (FA), extreme learning machine (ELM) and least-square-based non-linear regression (LSNLR) classifiers. The performance of the classifiers is compared by benchmark metrics, such as total error rate, specificity, sensitivity, area under the receiver operating characteristic curve, precision, F1 score and the Matthews correlation coefficient. As validation of the classifier results, a kappa analysis is included to determine the agreement among classifiers. The LSNLR classifier attains a 3% to 7% improvement in average accuracy compared with the average classification accuracy of the FA (86.75%) and ELM (90.836%) classifiers.