Off-line diagnosis of deterministic faults in continuous dynamic multivariable processes using speech recognition methods

Faults or special events which occur occasionally in continuous processes generate dynamic patterns in a large number of process variables. However, the patterns arising from the same fault can exhibit different time durations (depending on the operating conditions), magnitudes and directions. Any robust fault diagnosis method must be able to correctly classify these faults under these different conditions. This paper presents an off-line fault diagnosis method based on pattern recognition principles for multivariate dynamic data. The method consist of a filtering and scaling step, where the magnitude dependent information is removed, and a similarity assessment step via dynamic time warping (DTW). DTW is a flexible pattern matching method used in the area of speech recognition. The method presented in this paper is designed to classify faults independently of their magnitude, duration, direction and plant production level. As a further feature extraction step, principal component analysis is used to reduce the dimension of the multivariate problem and enhance the distance-based classification. Case studies from the Tennessee-Eastman plant are used to test the method and to illustrate its advantages and limitations.     

Planar Feedback Vertex Set and Face Cover: Combinatorial Bounds and Subexponential Algorithms

The Planar Feedback Vertex Set problem asks whether an n-vertex planar graph contains at most k vertices meeting all its cycles. The Face Cover problem asks whether all vertices of a plane graph G lie on the boundary of at most k faces of G. Standard techniques from parameterized algorithm design indicate that both problems can be solved by sub-exponential parameterized algorithms (where k is the parameter). In this paper we improve the algorithmic analysis of both problems by proving a series of combinatorial results relating the branchwidth of planar graphs with their face cover. Combining this fact with duality properties of branchwidth, allows us to derive analogous results on feedback vertex set. As a consequence, it follows that Planar Feedback Vertex Set and Face Cover can be solved in \(O(2^{15.11\cdot\sqrt{k}}+n^{2})\) and \(O(2^{10.1\cdot\sqrt {k}}+n^{2})\) steps, respectively.     

Extraction of Contamination of Automotive Gas Tank Material by Extrusion with Supercritical Carbon Dioxide

During their working life, plastics can be exposed to contaminating media which limit their recyclability. A continuous extraction process with supercritical CO₂ has been developed. Contaminated material is extruded through two twin‐screw extruders in a cascade. The first extruder purifies with scCO₂ and the second extruder is for degassing and hot‐cut pelletisation. Post‐consumer automotive diesel fuel tank material has been processed. A direct flow and a counter‐flow process with different screw configurations have been developed. Characterisation has been performed by headspace gas chromatography. Results show that contaminants were extracted out of the plastic for both process variants. However, direct flow yielded better extraction efficiency.

     

Large work function shift of organic semiconductors inducing enhanced interfacial electron transfer in organic optoelectronics enabled by porphyrin aggregated nanostructures

We report on large work function shifts induced by the coverage of several organic semiconducting （OSC） films commonly used in organic light emitting diodes （OLEDs） and organic photovoltaics （OPVs） with a porphyrin aggregated layer. The insertion between the organic film and the aluminum cathode of an aggregated layer based on the meso-tetrakis（1-methylpyridinium-4-yl） porphyrin chloride （porphyrin 1）, with its molecules adopting a face-to-face orientation parallel to the organic substrate, results in a significant shift of the OSC work function towards lower values due to the formation of a large interfacial dipole and induces large enhancement of either the OLED or OPV device efficiency. OLEDs based on poly[（9,9-dioctylfluorenyl-2,7-diyl）-co-（1,4-benzo-2,1＇,3-thiadiazole）J （F8BT） and incorporating the porphyrin 1 at the cathode interface exhibited current efficiency values up to 13.8 cd/A, an almost three-fold improvement over the efficiency of 4.5 cd/A of the reference device. Accordingly, OPVs based on poly（3- hexylthiophene） （P3HT）, [6,6]-phenyl-C61 butyric acid methyl ester （PC61BM） and porphyrin 1 increased their external quantum efficiencies to 4.4% relative to 2.7% for the reference device without the porphyrin layer. The incorporation of a layer based on the zinc meso-tetrakis （1-methylpyridinium-4-yl）porphyrin chloride （porphyrin 2）, with its molecules adopting an edge-to-edge orientation, also introduced improvements, albeit more modest in all cases, highlighting the impact of molecular orientation.     

Granular neural networks for land use classification

Granulation of information is a new way to describe the increased complexity of natural phenomena. The lack of clear borders in nature calls for a more efficient way to process such data. Land use both in general but also as perceived in satellite images is a typical example of data that are inherently not clearly delimited. A granular neural network (GNN) approach is used here to facilitate land use classification. The GNN model used combines membership functions of spectral as well as non-spectral spatial information to produce land use categories. Spectral information refers to IRS satellite image bands and non-spectral data are here of topographic nature, namely slope, aspect and elevation. The processing is done through a standard neural network trained by back-propagation learning algorithm. A thorough presentation of the results is given in order to evaluate the merits of this method.     

Mechanical Forces Induce Changes in VEGF and VEGFR-1/sFlt-1 Expression in Human Chondrocytes

Expression of the pro-angiogenic vascular endothelial growth factor (VEGF) stimulates angiogenesis and correlates with the progression of osteoarthritis. Mechanical joint loading seems to contribute to this cartilage pathology. Cyclic equibiaxial strains of 1% to 16% for 12 h, respectively, induced expression of VEGF in human chondrocytes dose- and frequency-dependently. Stretch-mediated VEGF induction was more prominent in the human chondrocyte cell line C-28/I2 than in primary articular chondrocytes. Twelve hours of 8% stretch induced VEGF expression to 175% of unstrained controls for at least 24 h post stretching, in promoter reporter and enzyme-linked immunosorbent assay (ELISA) studies. High affinity soluble VEGF-receptor, sVEGFR-1/sFlt-1 was less stretch-inducible than its ligand, VEGF-A, in these cells. ELISA assays demonstrated, for the first time, a stretch-mediated suppression of sVEGFR-1 secretion 24 h after stretching. Overall, strained chondrocytes activate their VEGF expression, but in contrast, strain appears to suppress the secretion of the major VEGF decoy receptor (sVEGFR-1/sFlt-1). The latter may deplete a biologically relevant feedback regulation to inhibit destructive angiogenesis in articular cartilage. Our data suggest that mechanical stretch can induce morphological changes in human chondrocytes in vitro. More importantly, it induces disturbed VEGF signaling, providing a molecular mechanism for a stress-induced increase in angiogenesis in cartilage pathologies.     

Connectionist modeling of speech perception.

Connectionist models of perception and cognition, including the process of deducing meaningful messages from patterns of acoustic waves emitted by vocal tracts, are developed and refined as human understanding of brain function, psychological processes, and the properties of massively parallel architectures advances. The present article presents several important contributions from diverse points of view in the area of connectionist modeling of speech perception and discusses their relative merits with respect to specific theoretical issues and empirical findings. TRACE, the Elman/Norris net, and Adaptive Resonance Theory constitute pivotal points exemplifying overall modeling success, progress in temporal representation, and plausible modeling of learning, respectively. Other modeling efforts are presented for the specific insights they offer, and the article concludes with a discussion of computational versus dynamic modeling of phonological processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)