Mining association rules for the quality improvement of the production process

Academics and practitioners have a common interest in the continuing development of methods and computer applications that support or perform knowledge-intensive engineering tasks. Operations management dysfunctions and lost production time are problems of enormous magnitude that impact the performance and quality of industrial systems as well as their cost of production. Association rule mining is a data mining technique used to find out useful and invaluable information from huge databases. This work develops a better conceptual base for improving the application of association rule mining methods to extract knowledge on operations and information management. The emphasis of the paper is on the improvement of the operations processes. The application example details an industrial experiment in which association rule mining is used to analyze the manufacturing process of a fully integrated provider of drilling products. The study reports some new interesting results with data mining and knowledge discovery techniques applied to a drill production process. Experiment’s results on real-life data sets show that the proposed approach is useful in finding effective knowledge associated to dysfunctions causes.     

Analysis of photocurrents at the semiconductor—eletrolyte junction

The photocurrent vs potential characateristics for three different electrolyte—semiconductor junctions, representative of those generally found in semiconductor photoelectrochemistry, are analyzed in detail using parameters which define both the semiconductor and the electrolyte. It is shown that, in general, the behaviour of junctions including semiconductors with sufficiently wide energy pags and large free carriers densities, may be accurately described using the Gärtner model in the potential region which does not include the onset of the photocurrent. In this case, it is the characteristics of the semiconductor which control the photoresponse and the electrolyte does not induce limiting steps in the charge transfer across the interface. If certain restrictive conditions are fulfilled concerning the relative orders of magnitude of the semiconductor space charge region, diffusion length of minority carriers and penetration depth of light into the semiconductor, the value of the flat band potential may be easily determined by ploting i²_phvs V and extrapolating to i²_ph = 0. In the other cases, the relation established by Gärtner between i_ph and V has been verified provided that the free carriers density be sufficiently large.     

A prismoid framework for languages with resources

Inspired by the Multiplicative Exponential fragment of Linear Logic, we define a framework called the prismoid of resources where each vertex is a language which refines the λ-calculus by using a different choice to make explicit or implicit (meta-level) the definition of the contraction, weakening, and substitution operations. For all the calculi in the prismoid we show simulation of β-reduction, confluence, preservation of β-strong normalisation and strong normalisation for typed terms. Full composition also holds for all the calculi of the prismoid handling explicit substitutions. The whole development of the prismoid is done by making the set of resources a parameter of the formalism, so that all the properties for each vertex are obtained as a particular case of the general abstract proofs.     

Three‐dimensional localization for the MagneBike inspection robot

The MagneBike inspection robot is a climbing robot equipped with magnetic wheels. The robot is designed to drive on three‐dimensional (3D) complexly shaped pipe structures; therefore it is necessary to provide 3D visualization tools for the user, who remotely controls the robot out of sight. The localization system is required to provide a 3D map of the unknown environment and the 3D location of the robot in the environment's map. The localization strategy proposed in this paper consists of combining 3D odometry with 3D scan registration. The odometry model is based on wheel encoders and a three‐axis accelerometer. Odometry enables the tracking of the robot trajectory between consecutive 3D scans and is used as a prior for the scan matching algorithm. The 3D scan registration facilitates the construction of a 3D map of the environment and refines the robot position computed with odometry. This paper describes in detail the implementation of the localization concept. It presents the lightweight, small‐sized 3D range finder that has been developed for the MagneBike. It also proposes an innovative 3D odometry model that estimates the local surface curvature to compensate for the absence of angular velocity inputs. The different tools are characterized in detail based on laboratory and field experiments. They show that the localization concepts reliably track the robot moving in the specific application environment. We also describe various techniques to optimize the 3D scanning process, which is time consuming, and to compensate for the identified limitations. These techniques are useful inputs for the future automatization of the robot's control and optimization of its localization process. © 2010 Wiley Periodicals, Inc.     

A shape analysis framework for neuromorphometry

This paper addresses in an integrated and systematic fashion the relatively overlooked but increasingly important issue of measuring and characterizing the geometrical properties of nerve cells and structures, an area often called neuromorphology. After discussing the main motivation for such an endeavour, a comprehensive mathematical framework for characterizing neural shapes, capable of expressing variations over time, is presented and used to underline the main issues in neuromorphology. Three particularly powerful and versatile families of neuromorphological approaches, including differential measures, symmetry axes/skeletons, and complexity, are presented and their respective potentials for applications in neuroscience are identified. Examples of applications of such measures are provided based on experimental investigations related to automated dendrogram extraction, mental retardation characterization, and axon growth analysis.     

Collaborative software infrastructure for adaptive multiple model simulation

This paper presents a software infrastructure being developed to support the implementation of adaptive multiple model simulations. The paper first describes an abstraction of single and multiple model simulations into the individual operational components with a focus on the relationships and transformations that relate them. Building on that abstraction, consideration is then given to how adaptively controlled multiple model simulations can be constructed using existing simulation components interacting through functional interfaces. This includes addressing how experts would provide the infrastructure with the needed components and define the relations and transformations needed to interact with other components, and for users to define the simulations they wish to be executed. Next, a discussion of the software environment used to implement the multiple model simulation infrastructure is given. Finally, there is discussion of the implementation, using this infrastructure, of two multiscale and one multiple fidelity model simulation applications.     

Explicit modelling of the double‐gate MOSFET with VHDL‐AMS

This paper presents a new compact model for the undoped, long‐channel double‐gate (DG) MOSFET under symmetrical operation. In particular, we propose a robust algorithm for computing the mobile charge density as an explicit function of the terminal voltages. It allows to greatly reduce the computation time without losing any accuracy. In order to validate the analytical model, we have also developed the 2D simulations of a DG MOSFET structure and performed both static and dynamic electrical simulations of the device. Comparisons with the 2D numerical simulations give evidence for the good behaviour and the accuracy of the model. Finally, we present the VHDL‐AMS code of the DG MOSFET model and related simulation results. Copyright © 2006 John Wiley & Sons, Ltd.     

Comparison of 2D simultaneous multi-slice and 3D GRASE readout schemes for pseudo-continuous arterial spin labeling of cerebral perfusion at 3 T

Objective

In this perfusion magnetic resonance imaging study, the performances of different pseudo-continuous arterial spin labeling (PCASL) sequences were compared: two-dimensional (2D) single-shot readout with simultaneous multislice (SMS), 2D single-shot echo-planar imaging (EPI) and multishot three-dimensional (3D) gradient and spin echo (GRASE) sequences combined with a background-suppression (BS) module.

Materials and methods

Whole-brain PCASL images were acquired from seven healthy volunteers. The performance of each protocol was evaluated by extracting regional cerebral blood flow (rCBF) measures using an inline morphometric segmentation prototype. Image data postprocessing and subsequent statistical analyses enabled comparisons at the regional and sub-regional levels.

Results

The main findings were as follows: (i) Mean global CBF obtained across methods was were highly correlated, and these correlations were significantly higher among the same readout sequences. (ii) Temporal signal-to-noise ratio and gray-matter-to-white-matter CBF ratio were found to be equivalent for all 2D variants but lower than those of 3D-GRASE.

Discussion

Our study demonstrates that the accelerated SMS readout can provide increased acquisition efficiency and/or a higher temporal resolution than conventional 2D and 3D readout sequences. Among all of the methods, 3D-GRASE showed the lowest variability in CBF measurements and thus highest robustness against noise.