A Time Truncated Moving Average Chart for the Weibull Distribution

A control chart of monitoring the number of failures is proposed with a moving average scheme, when the life of an item follows a Weibull distribution. A specified number of items are put on a time truncated life test and the number of failures is observed. The proposed control chart has been evaluated by the average run lengths (ARLs) under different parameter settings. The control constant and the test time multiplier are to be determined by considering the in-control ARL. It is observed that the proposed control chart is more efficient in detecting a shift in the process as compared with the existing time truncated control chart. ? 2013 IEEE.11Ysciescopu

Modelling of Metallurgical Processes Using Chaos Theory and Hybrid Computational Intelligence

The main objective of the present work is to develop a framework for modelling and controlling of a real world multi-input and multi-output (MIMO) continuously drifting metallurgical process, which is shown to be a complex system. A small change in the properties of the charge composition may lead to entirely different outcome of the process. The newly emerging paradigm of soft-computing or Hybrid Computational Intelligence Systems approach which is based on neural networks, fuzzy sets, genetic algorithms and chaos theory has been applied to tackle this problem In this framework first a feed-forward neuro-model has been developed based on the data collected from a working Submerged Arc Furnace (SAF). Then the process is analysed for the existence of the chaos with the chaos theory (calculating indices like embedding dimension, Lyapunov exponent etc). After that an effort is made to evolve a fuzzy logic controller for the dynamical process using combination of genetic algorithms and the neural networks based forward model to predict the system’s behaviour or conditions in advance and to further suggest modifications to be made to achieve the desired results

Applications of self-assembled monolayers in Materials Chemistry

Self-assembly provides a simple route to organise suitable organic molecules on noble metal and selected nanocluster surfaces by using monolayers of long chain organic molecules with various functionalities like -SH,-COOH,-NH2, silanes etc. These surfaces can be effectively used to build-up interesting nano level architectures. Flexibility with respect to the terminal functionalities of the organic molecules allows the control of the hydrophobicity or hydrophilicity of metal surface, while the selection of length scale can be used to tune the distant-dependent electron transfer behaviour. Organo-inorganic materials tailored in this fashion are extremely important in nanotechnology to construct nanoelctronic devices, sensor arrays, supercapacitors, catalysts, rechargeable power sources etc. by virtue of their size and shape-dependent electrical, optical or magnetic properties. The interesting applications of monolayers and monolayer-protected clusters in materials chemistry are discussed using recent examples of size and shape control of the properties of several metallic and semiconducting nanoparticles. The potential benefits of using these nanostructured systems for molecular electronic components are illustrated using Au and Ag nanoclusters with suitable bifunctional SAMs

The Atmospheric Lifetime Experiment and the Global Atmospheric Gas Experiment (ALE/GAGE)

The ALE/GAGE project was designed to determine the global atmospheric lifetimes of the chlorofluorocarbons CCl3F and CCl2F2 (F-11 and F-12), which had been identified as the main gases that cause stratospheric ozone depletion. The experimental procedures also provided the concentrations of CH3CCl3, CCl4 and N2O. The extended role of the project was to evaluate the mass balances of these gases as well. Methylchloroform (CH3CCl3) serves as a tracer of average atmospheric OH concentrations and hence the oxidizing capacity of the atmosphere. Nitrous oxide (N2O) is a potent greenhouse gas and can also deplete the ozone layer. Measurements of these gases were taken with optimized instruments in the field at a frequency of about 1 sample/hr. Toward the end of the present project methane measurements were added to the program. The final report deals with the research of the Oregon Graduate Institute (OGI) as part of the ALE/GAGE program between 4/1/1988 and 1/31/1991. The report defines the scope of the OGI project, the approach, and the results

Measurements of branching fractions, absolute transition probabilities and J-file sum rule for the 4p(5)5p -\u3e 4p(5)5s transitions array in neutral krypton

We present new results of transition rates for twenty two electric dipole transitions of neutral krypton associated with the 4p55p→4p55 s configurations-based levels covering the wavelength region from 500 to 1000 nm using a krypton filled hollow cathode discharge lamp coupled with a set of four miniature spectrometers. The branching fractions of various dipole allowed transitions were extracted using the observed line intensity ratios, whereas, the absolute values of the transition probabilities were deduced from the measured branching fractions in combination with the known lifetimes of the upper levels. The experimental data are in good agreement with that calculated in the intermediate angular momentum coupling scheme. In addition, line strengths for all the transitions have been extracted using the measured transition probabilities. The J-file sum rule was also tested for each level attached to the 4p55p→4p55 s configurations based on the recently measured and calculated normalized multiplet strengths

Emissions Of Greenhouse Gases From Rice Agriculture

This project produced detailed data on the processes that affect methane and nitrous oxide emissions from rice agriculture and their inter-relationships. It defines the shifting roles and potential future of these gases in causing global warming and the benefits and tradeoffs of reducing emissions. The major results include: 1). Mechanisms and Processes Leading to Methane Emissions are Delineated. Our experiments have tested the standard model of methane emissions from rice fields and found new results on the processes that control the flux. A mathematical mass balance model was used to unravel the production, oxidation and transport of methane from rice. The results suggested that when large amounts of organic matter are applied, the additional flux that is observed is due to both greater production and reduced oxidation of methane. 2). Methane Emissions From China Have Been Decreasing Over the Last Two Decades. We have calculated that methane emissions from rice fields have been falling in recent decades. This decrease is particularly large in China. While some of this is due to reduced area of rice agriculture, the bigger effect is from the reduction in the emission factor which is the annual amount of methane emitted per hectare of rice. The two most important changes that cause this decreasing emission from China are the reduced use of organic amendments which have been replaced by commercial nitrogen fertilizers, and the increased practice of intermittent flooding as greater demands are placed on water resources. 3). Global Methane Emissions Have Been Constant For More Than 20 Years. While the concentrations of methane in the atmosphere have been leveling off in recent years, our studies show that this is caused by a near constant total global source of methane for the last 20 years or more. This is probably because as some anthropogenic sources have increased, others, such as the rice agriculture source, have fallen. Changes in natural emissions appear small. 4). Nitrous Oxide Emissions From Rice Fields Increase as Methane Emissions Drop. Inundated conditions favor anaerobic methane production with high emission rates and de-nitrification resulting in modest nitrous oxide emissions. Under drier conditions such as intermittent flooding, methane emissions fall and nitrous oxide emissions increase. Increased nitrogen fertilizer use increases nitrous oxide emissions and is usually accompanied by reduced organic matter applications which decreases methane emissions. These mechanisms cause a generally inverse relationship between methane and nitrous oxide emissions. Reduction of methane from rice agriculture to control global warming comes with tradeoffs with increased nitrous oxide emissions. 5). High Spatial Resolution Maps of Emissions Produced. Maps of methane and nitrous oxide emissions at a resolution of 5 min × 5 min have been produced based on the composite results of this research. These maps are necessary for both scientific and policy uses

Deep learning-based meta-learner strategy for electricity theft detection

Electricity theft damages power grid infrastructure and is also responsible for huge revenue losses for electric utilities. Integrating smart meters in traditional power grids enables real-time monitoring and collection of consumers’ electricity consumption (EC) data. Based on the collected data, it is possible to identify the normal and malicious behavior of consumers by analyzing the data using machine learning (ML) and deep learning methods. This paper proposes a deep learning-based meta-learner model to distinguish between normal and malicious patterns in EC data. The proposed model consists of two stages. In Fold-0, the ML classifiers extract diverse knowledge and learns based on EC data. In Fold-1, a multilayer perceptron is used as a meta-learner, which takes the prediction results of Fold-0 classifiers as input, automatically learns non-linear relationships among them, and extracts hidden complicated features to classify normal and malicious behaviors. Therefore, the proposed model controls the overfitting problem and achieves high accuracy. Moreover, extensive experiments are conducted to compare its performance with boosting, bagging, standalone conventional ML classifiers, and baseline models published in top-tier outlets. The proposed model is evaluated using a real EC dataset, which is provided by the Energy Informatics Group in Pakistan. The model achieves 0.910 ROC-AUC and 0.988 PR-AUC values on the test dataset, which are higher than those of the compared models

Quantitative analysis of a brass alloy using CF- LIBS and a laser ablation time-of-flight mass spectrometer

We present a quantitative analysis of a brass alloy using laser induced breakdown spectroscopy, energy dispersive x-ray spectroscopy (EDX) and laser ablation time-of-flight mass spectrometry (LA-TOF-MS). The emission lines of copper (Cu I) and zinc (Zn I), and the constituent elements of the brass alloy were used to calculate the plasma parameters. The plasma temperature was calculated from the Boltzmann plot as (10 000 ± 1000) K and the electron number density was determined as (2.0 ± 0.5) × 1017 cm−3 from the Stark-broadened Cu I line as well as using the Saha–Boltzmann equation. The elemental composition was deduced using these techniques: the Boltzmann plot method (70% Cu and 30% Zn), internal reference self-absorption correction (63.36% Cu and 36.64% Zn), EDX (61.75% Cu and 38.25% Zn), and LA-TOF (62% Cu and 38% Zn), whereas, the certified composition is (62% Cu and 38% Zn). It was observed that the internal reference self-absorption correction method yields analytical results comparable to that of EDX and LA-TOF-MS