Combined quality loss (CQL) concept in WPCA-based Taguchi philosophy for optimization of multiple surface quality characteristics of UNS C34000 brass in cylindrical grinding

The present study highlights a multi-objective optimization problem by applying Weighted Principal Component Analysis (WPCA) coupled with Taguchi method through a case study in cylindrical grinding of UNS C34000 Medium Leaded Brass. The study aimed at evaluating the best process environment which could simultaneously satisfy multiple requirements of surface quality. In view of the fact that traditional Taguchi method fails to solve a multi-objective optimization problem, to overcome this limitation, WPCA has been coupled with Taguchi method. Furthermore, to follow the basic assumption of Taguchi method, i.e., quality attributes should be uncorrelated or independent; which is not always satisfied in practical situation; the study applied WPCA to eliminate response correlation and to evaluate independent or uncorrelated quality indices called principal components which were aggregated by WPCA to compute overall quality index denoted as Multi-Response Performance Index. A combined quality loss was then estimated which was optimized (minimized) finally. The study combined WPCA and Taguchi method for predicting optimal setting. Optimal result was verified through confirmatory test. This indicates application feasibility of the aforesaid methodology proposed for multi-response optimization and off-line control of correlated multiple surface quality characteristics in cylindrical grinding.     

Impact of gate-oxide tunneling on mixed-signal design and simulation of a nano-CMOS VCO

Design optimization for performance enhancement in analog and mixed-signal circuits is an active area of research as technology scaling is moving towards the nanometer scale. This paper presents an approach towards the efficient simulation and characterization of mixed-signal circuits, using a 45 nm CMOS voltage controlled oscillator (VCO) with frequency divider as a case study. The performance characteristics of the analog and digital blocks in the circuit are simulated and the accuracy issues arising due to separate analog and digital simulation engines are considered. The tremendous impact of gate tunneling current on device performance is quantitatively analyzed with the help of an “effective tunneling capacitance”, which allows accurate modeling and simulation of digital blocks with almost analog accuracy. To meet the design specifications of the analog VCO using digital CMOS technology, we follow a design of experiments (DOE) approach. The functional specifications of the VCO optimized in this design are the center frequency and minimization of overall power consumption as well as minimization of power due to gate-oxide tunneling current leakage, a component that was not important in previous generations of CMOS technologies but is dominant at 45 nm and below. Due to the large number of available design parameter (gate-oxide thickness and transistor sizes), the concurrent achievement of all optimization goals is difficult. A DOE approach is shown to be very effective and a viable alternative to standard design exploration in the nanometer regime.     

Treatment of simulated arsenic contaminated groundwater using GAC‐Cu in batch reactor: Optimization of process parameters

This article deals with the experimental investigation related to the removal of arsenic from a simulated contaminated groundwater by the adsorption onto Cu²⁺ impregnated granular activated carbon (GAC‐Cu) in presence of impurities like Fe and Mn. The effects of adsorbent concentration, pH, and temperature on the percentage removal of total arsenic (As(T)), As(III), and As(V) have been discussed. Under the experimental conditions, the optimum adsorbent concentration for GAC‐Cu has been found to be 6 g/L with an agitation time of 24 h, which reduces the As(T) concentration from 188 to 8.5 µg/L. Maximum removal of As(V) and As(III) has been observed in the pH range of 7–9 and 9–11, respectively. Removal of all the above said arsenic species decreases slightly with increase in temperature. Presence of Fe and Mn increases the adsorption of arsenic species. Under the experimental conditions, at 30°C, maximum % removals of As(T), As(III), As(V), Fe, and Mn are found to be 95.5%, 93%, 98%, 100%, and 40%, respectively. It has also been observed that maximum regeneration (～94%) of spent GAC‐Cu is exhibited by a 5NH₂SO₄ solution.     

Laboratory based approaches for arsenic remediation from contaminated water: recent developments

Arsenic contamination in water has posed severe health problems around the world. In spite of the availability of some conventional techniques for arsenic removal from contaminated water, development of new laboratory based techniques along with enhancement and cost reduction of conventional techniques are essential for the benefit of common people. This paper provides an overview of the arsenic issue in water such as modes of contamination of ground water as well as surface water by arsenic, its metabolism and health impacts, factors influencing arsenic poisoning, fundamentals of arsenic poisoning mechanism and world scenario of arsenic poisoning. It discusses and compares the conventional laboratory based techniques, like precipitation with alum, iron, Fe/Mn, lime softening, reverse osmosis, electro dialysis, ion exchanges, adsorption on activated alumina/carbon, etc., for arsenic removal from contaminated water. It also discusses the best available techniques and mentions the cost comparison among these techniques too. Recent developments in the research on the laboratory based arsenic removal techniques, like improvement of conventional techniques and advances in removal technology along with its scopes and limitations have also been reviewed.     

Detection of Chlorophenolic Compounds in Bleaching Effluents of Chemical Pulps

Laboratory bleaching effluents from the chlorination and caustic extraction stages of mixed wood kraft pulp processing have been analysed both qualitatively and quantitatively for various chlorophenolics by using GC.A number of chlorinated derivaties of phenols,catechols,guaiacols and syringaldehydes have been detected and their concentrations are estimated.The results are compared with that of different agriculture residue / hardwood pulps,which were reported in literature.The concentrations of various compounds detected have also been compared with their reported 96LC50 values.     

Biogeochemical processes in ethanol stimulated uranium-contaminated subsurface sediments

A laboratory incubation experiment was conducted with uranium-contaminated subsurface sediment to assess the geochemical and microbial community response to ethanol amendment. A classical sequence of terminal electron-accepting processes (TEAPs) was observed in ethanol-amended slurries, with NO3- reduction, Fe(III) reduction, SO4(2-) reduction, and CH4 production proceeding in sequence until all of the added 13C-ethanol (9 mM) was consumed. Approximately 60% of the U(VI) content of the sediment was reduced during the period of Fe(III) reduction. No additional U(VI) reduction took place during the sulfate-reducing and methanogenic phases of the experiment Only gradual reduction of NO3-, and no reduction of U(VI), took place in ethanol-free slurries. Stimulation of additional Fe(III) or SO4(2-) reduction in the ethanol-amended slurries failed to promote further U(VI) reduction. Reverse transcribed 16S rRNA clone libraries revealed major increases in the abundance of organisms related to Dechloromonas, Geobacter, and Herbaspirillum in the ethanol-amended slurries. Phospholipid fatty acids (PLFAs) indicative of Geobacter showed a distinct increase in the amended slurries, and analysis of PLFA 13C/12C ratios confirmed the incorporation of ethanol into these PLFAs. A increase in the abundance of 13C-labeled PLFAs indicative of Desulfobacter, Desulfotomaculum, and Desulfovibrio took place during the brief period of sulfate reduction that followed the Fe(III) reduction phase. Our results show that major redox processes in ethanol-amended sediments can be reliably interpreted in terms of standard conceptual models of TEAPs in sediments. However, the redox speciation of uranium is complex and cannot be explained based on simplified thermodynamic considerations.     

CL-AGKA: certificateless authenticated group key agreement protocol for mobile networks

Wireless Networks - Wireless group communication has gained much popularity recently due to the increase in portable, lightweight devices. These devices are capable of performing group...     

Coexistence of interfacial stress and charge transfer in graphene oxide-based magnetic nanocomposites

In this paper, the existence of both compressive stress and charge transfer process in hydrothermally synthesized cobalt ferrite–graphene oxide (CoFe₂O₄/GO) nanocomposites has been established. Transmission electron microscopy results reveal the decoration of CoFe₂O₄ nanoparticles on GO sheets. Magnetic response of nanocomposites was confirmed from superconducting quantum interference device magnetometer measurement. Optical properties of these nanocomposites were investigated by Raman spectroscopy. The interfacial compressive stress involved in this system has been evaluated from observed blue shift of characteristic G peak of graphene oxide. Increase in the full-width half-maximum value as well as upshift in D and G peaks is clear indications of involvement of charge transfer process between GO sheets and dispersed magnetic nanoparticles. The effect of charge transfer process is quantified in terms of shifting of Fermi energy level of these nanocomposites. This is evaluated from variation in contact surface potential difference using scanning Kelvin probe microscopy. XRD spectra of CoFe₂O₄/GO confirm the polycrystalline nature of CoFe₂O₄ nanoparticles. Lattice strain estimated from XRD peaks is correlated with the observed Raman shift.     

Improving the capacity,redox activities of Li-ion batteries through Si3N4@MoS2 hetero-structure design

Journal of Materials Science - To develop advanced anode materials for Li-ion batteries (LIB), an extensive research effort is being employed. The effort focuses much on silicon-based anodes due to...     

Machine learning approach to recognize ventricular arrhythmias using VMD based features

The occurrence of life-threatening ventricular arrhythmias (VAs) such as Ventricular tachycardia (VT) and Ventricular fibrillation (VF) leads to sudden cardiac death which requires detection at an early stage. The main aim of this work is to develop an automated system using machine learning tool for accurate prediction of VAs that may reduce the mortality rate. In this paper, a novel method using variational mode decomposition (VMD) based features and C4.5 classifier for detection of ventricular arrhythmias is presented. The VMD model was used to decompose the electrocardiography (ECG) signals to extract useful informative features. The method was tested for ECG signals obtained from PhysioNet database. Two standard databases i.e. CUDB (Creighton University Ventricular Tachyarrhythmia Database) and VFDB (MIT-BIH Malignant Ventricular Ectopy Database) were considered for this work. A set of time–frequency features were extracted and ranked by the gain ratio attribute evaluation method. The ranked features are subjected to support vector machine (SVM) and C4.5 classifier for classification of normal, VT and VF classes. The best detection was obtained with sensitivity of 97.97%, specificity of 99.15%, and accuracy of 99.18% for C4.5 classifier with a 5 s data analysis window. These results were better than SVM classifier result having an average accuracy of 86.87%. Hence, the proposed method demonstrates the efficiency in detecting the life-threatening VAs and can serve as an assistive tool to clinicians in the diagnosis process.