Special cause management: A knowledge-based approach to statistical process control

In this paper we discuss a set of software tools developed to support the tasks associated with managing special causes of variation in a manufacturing process. These tasks include the detection of significant changes in process variables, a diagnosis of the causes of those changes, the discovery of new causes, the management of performance data, and the reporting of results. The software tools include automatic recognition of out-of-control features in critical process variables, rule-based diagnosis of special causes, a model-based search for symptoms where a diagnosis is not possible, and automated reporting aids. It is hoped that these tools will enhance the efficiency of special cause management.     

Characteristics of a high brightness gaseous field ion source employing tungsten-carbon doped NiAl needles

We report on the characterization of a high brightness gaseous field ion source using an emitter made of a NiAl needle containing tiny spherical tungsten-carbon precipitates. By field evaporation of such a multiphase alloy, a surface protrusion is formed out of a precipitate, which can act as a small source size field ion emitter. The emission current-voltage characteristics of this emitter were recorded for a variety of parameters. The results obtained suggest that its application as a stable ion source is possible even on long term operation.     

A cooling change-point model of community-aggregate electrical load

Estimates of daily electrical cooling load for a city of 800,000 are developed based on the relationship between weather variables and daily-average electricity consumption over 1 year. The relationship is found to be nearly linear above a threshold temperature. Temperature and humidity were found to be the largest, at 59%, and second largest, at 21%, contributors to electrical cooling load. Direct normal irradiation intercepted by a vertical cylinder, DNI sin θ, was found to be a useful explanatory variable when modeling aggregates of buildings without a known or dominant orientation. The best study case model used DNI sin θ and diffuse horizontal irradiation (DHI) as distinct explanatory variables with annual electrical cooling load contributions of 9% and 11% respectively. Although the seasonal variation in electrical cooling load is large - on peak summer days more than 1.5 times the winter base load - the combined direct and diffuse solar contribution is essentially flat through the year, a condition at odds with the common assumption that solar cooling always provides a good match between supply and demand. The final model gives an electrical cooling load estimate for Abu Dhabi Island that corresponds to 40% of the total annual electrical load and 61% on the peak day.     

Effect of the preparation method on the surface coverage of Mo/Al2O3 catalysts

Two series of Mo/Al₂O₃ catalysts were prepared by equilibrium adsorption and incipient wetness impregnation methods. The effect of preparation method on the surface coverages of the calcined catalysts was investigated by the combined use of CO₂ chemisorption, low temperature CO adsorption and ion scattering spectroscopy (ISS). For a given Mo loading, the CO₂ and CO adsorption results showed little difference between the two preparation methods. As previously noted, the CO₂ chemisorption method overestimated the Mo surface coverage. In contrast to the adsorption methods, the ISS technique gave different Mo surface coverage values for a given Mo content of the two series of catalysts. This apparent discrepancy was attributed to different repartition of the Mo phase between the internal and external surfaces which can only be detected by ISS. This interpretation is supported by the observed agreement between the coverage values measured from ISS and low temperature CO adsorption for presumably uniform catalysts obtained by the equilibrium adsorption method.     

Vibrational and thermodynamic properties of LiBH4 polymorphs from first-principles calculations

The study of phonons describes the thermodynamic properties behavior of compounds with small atoms because phonons have an important influence on its properties. Lithium borohydride, LiBH₄, is one of the suitable materials for hydrogen storage solid state. Although the transformations of Lithium borohydride LiBH₄ were repeatedly studied by experiments and fundamental side, these transformations are still under discussion. In the present work, the mode vibrational analysis of orthorhombic and hexagonal LiBH₄ structures were considered with ab initio lattice-dynamics based on the quasi-harmonic approximation approach as implemented in Phonopy code. The results show that the orthorhombic structure is thermodynamically stable, while the hexagonal structure is unstable owing to the presence of negative mode frequency. The thermal expansion behavior and various thermodynamic properties stability like heat capacity, entropy and Helmholtz energy were also studied and the obtained results are in good agreement with experiments. This shows a deep connection between stability and strength and helps researchers to estimate accurately the thermodynamic performance of LiBH₄ materials.     

Applications of aeromagnetic data to detect the Basement Tectonics of Eastern Yemen region

The present study aims to throw light on the tectonic implications concerned with the distribution of the sedimentary sequence belts and the related basement complex zones, as well as to differentiate between the causative sources (contacts, dykes and faults) of Eastern Yemen region. The total intensity aeromagnetic map of the study area was first corrected by the application of the Reduction To the magnetic pole (for low latitude areas). The visual inspection of the RTP magnetic map defines a rapid change in the subsurface geologic conditions in the form of lithologic characters and tectonic inferences. On the other hand, this map showed different anomalies of varying frequencies and amplitudes that revealed various causative sources, as well as varying compositions and depths. At the interpretation stage, various techniques and software tools are available for extracting the geologic information from the data concerned. The magnetic fields of shallow sources can be separated from those of deeper causatives, using two processes known as power spectrum transformation and matched band pass filtering. Three methods for locating magnetic sources (Magnitude of Horizontal Gradients (HGM), the analytical signals (AS) and the local wavenumbers (LW)) in three dimensions and identifying the properties of their sources indicated that, the area was affected by some intrusions at various depths in sill or dyke forms, almost oriented in the NW–SE, NE–SW, E–W and N–S trends. Tectonically, the area is highly affected by the tectonics related to the Arabian Sea, Gulf of Aden and Red Sea. It is affecting both the basement and sedimentary rocks, dividing the study area into several faulted blocks.     

Kinetic Monte Carlo and density functional study of hydrogen diffusion in magnesium hydride MgH2

In this work, we propose a model to investigate the hydrogen storage ab/desorption kinetic properties for the pure MgH₂ using Kinetic Monte Carlo (KMC) simulations. To do such computations, the activation energies for different elementary processes have been estimated. Moreover, the different thermodynamical quantities of interest are determined by performing the ab-initio calculations. Then, we discuss the hydrogen diffusion in magnesium hydride (such as adsorption, diffusion and desorption). More precisely, we study the effect of each elementary mechanism on the diffusion that we characterize through the density distribution of hydrogen atoms including filling ratios, diffusion time, temperature and pressure. Among others, we show that all elementary mechanisms are needed to reproduce a behavior of ab/desorption which correlates well with the experimental results reported in literature. In particular, at high temperature and pressure, the results of simulations indicate that the studied material involves slow kinetics.     

Compact low-power time-based conversion with noise immunity similar to digital conversion

An analog signal representation based on the inter-pulse-interval (IPI) time is presented. Voltage-to-IPI and IPI-to-voltage conversion circuits based on the representation are described. The circuits have been fabricated using a 0.35 μm mixed-signal CMOS process. Simulation and test results agree with the theory. Voltage-to-IPI conversion needs significantly less area and power than ADC and is significantly more immune to noise and other problems than using analog voltage/current signals.     

Parallel Fiber Coding in the Cerebellum for Life-Long Learning

Continuous and real-time learning is a difficult problem in robotics. To learn efficiently, it is important to recognize the current situation and learn appropriately for that context. To be effective, this requires the integration of a large number of sensorimotor and cognitive signals. So far, few principles on how to perform this integration have been proposed. Another limitation is the difficulty to include the complete contextual information to avoid destructive interference while learning different tasks.We suggest that a vertebrate brain structure important for sensorimotor coordination, the cerebellum, may provide answers to these difficult problems. We investigate how learning in the input layer of the cerebellum may successfully encode contextual knowledge in a representation useful for coordination and life-long learning. We propose that a sparsely-distributed and statistically-independent representation provides a valid criterion for the self-organizing classification and integration of context signals. A biologically motivated unsupervised learning algorithm that approximate such a representation is derived from maximum likelihood. This representation is beneficial for learning in the cerebellum by simplifying the credit assignment problem between what must be learned and the relevant signals in the current context for learning it. Due to its statistical independence, this representation is also beneficial for life-long learning by reducing the destructive interference across tasks, while retaining the ability to generalize. The benefits of the learning algorithm are investigated in a spiking model that learns to generate predictive smooth pursuit eye movements to follow target trajectories.