Abstract: An oxidation catalyst is described for treating an exhaust gas from a diesel engine, which oxidation catalyst comprises: a substrate; a first washcoat region disposed on the substrate, wherein the first washcoat region comprises a first platinum group metal (PGM) and a first support material; a second washcoat region adjacent to the first washcoat region, wherein the second washcoat region comprises a second platinum group metal (PGM) and a second support material; a third washcoat region disposed on the substrate, wherein the third washcoat region comprises a third platinum group metal (PGM) and a third support material; and wherein either: (i) the third washcoat region is adjacent to the second washcoat region; or (ii) the second washcoat region is disposed or supported on the third washcoat region. Also described are uses and methods involving the oxidation catalyst.

Abstract: This oxidation catalyst for diesel engines is divided into an upstream-side catalyst layer and a downstream-side inner catalyst layer in the flow direction of the exhaust gas, and a downstream-side outer catalyst layer is additionally formed so as to cover the surface of the downstream-side inner catalyst layer. The upstream-side catalyst layer and the downstream-side inner catalyst layer contain Pd, and the downstream-side outer catalyst layer contains Pt. The amounts of Pt and Pd contained in the upstream-side catalyst layer and the amounts of Pt and Pd contained in the downstream-side inner catalyst layer are constantly set to certain values, while the amount of Pt contained in the downstream-side outer catalyst layer is set to a value which enables the oxidation efficiency to be at a predetermined value or higher.

Abstract: An oxidation catalyst is described for treating an exhaust gas from a diesel engine, which oxidation catalyst comprises: a substrate; a first washcoat region disposed on the substrate, wherein the first washcoat region comprises a first platinum group metal (PGM) and a first support material; a second washcoat region adjacent to the first washcoat region, wherein the second washcoat region comprises a second platinum group metal (PGM) and a second support material; a third washcoat region disposed on the substrate, wherein the third washcoat region comprises a third platinum group metal (PGM) and a third support material; and wherein either: (i) the third washcoat region is adjacent to the second washcoat region; or (ii) the second washcoat region is disposed or supported on the third washcoat region. Also described are uses and methods involving the oxidation catalyst.

Abstract: An oxidation catalyst is described for treating an exhaust gas from a diesel engine, which oxidation catalyst comprises: a substrate; a first washcoat region disposed on the substrate, wherein the first washcoat region comprises a first platinum group metal (PGM) and a first support material; a second washcoat region adjacent to the first washcoat region, wherein the second washcoat region comprises a second platinum group metal (PGM) and a second support material; a third washcoat region disposed on the substrate, wherein the third washcoat region comprises a third platinum group metal (PGM) and a third support material; and wherein either: (i) the third washcoat region is adjacent to the second washcoat region; or (ii) the second washcoat region is disposed or supported on the third washcoat region. Also described are uses and methods involving the oxidation catalyst.

Abstract: An oxidation catalyst is described for treating an exhaust gas from a diesel engine, which oxidation catalyst comprises: a substrate; a first washcoat region disposed on the substrate, wherein the first washcoat region comprises a first platinum group metal (PGM) and a first support material; a second washcoat region adjacent to the first washcoat region, wherein the second washcoat region comprises a second platinum group metal (PGM) and a second support material; a third washcoat region disposed on the substrate, wherein the third washcoat region comprises a third platinum group metal (PGM) and a third support material; and wherein either: (i) the third washcoat region is adjacent to the second washcoat region; or (ii) the second washcoat region is disposed or supported on the third washcoat region. Also described are uses and methods involving the oxidation catalyst.

Abstract: This oxidation catalyst for diesel engines is divided into an upstream-side catalyst layer and a downstream-side inner catalyst layer in the flow direction of the exhaust gas, and a downstream-side outer catalyst layer is additionally formed so as to cover the surface of the downstream-side inner catalyst layer. The upstream-side catalyst layer and the downstream-side inner catalyst layer contain Pd, and the downstream-side outer catalyst layer contains Pt. The amounts of Pt and Pd contained in the upstream-side catalyst layer and the amounts of Pt and Pd contained in the downstream-side inner catalyst layer are constantly set to certain values, while the amount of Pt contained in the downstream-side outer catalyst layer is set to a value which enables the oxidation efficiency to be at a predetermined value or higher.

Abstract: An oxidation catalyst is described for treating an exhaust gas from a diesel engine, which oxidation catalyst comprises: a substrate; a first washcoat region disposed on the substrate, wherein the first washcoat region comprises a first platinum group metal (PGM) and a first support material; a second washcoat region adjacent to the first washcoat region, wherein the second washcoat region comprises a second platinum group metal (PGM) and a second support material; a third washcoat region disposed on the substrate, wherein the third washcoat region comprises a third platinum group metal (PGM) and a third support material; and wherein either: (i) the third washcoat region is adjacent to the second washcoat region; or (ii) the second washcoat region is disposed or supported on the third washcoat region. Also described are uses and methods involving the oxidation catalyst.

Abstract: An oxidation catalyst is described for treating an exhaust gas from a diesel engine, which oxidation catalyst comprises: a substrate; a first washcoat region disposed on the substrate, wherein the first washcoat region comprises a first platinum group metal (PGM) and a first support material; a second washcoat region adjacent to the first washcoat region, wherein the second washcoat region comprises a second platinum group metal (PGM) and a second support material; a third washcoat region disposed on the substrate, wherein the third washcoat region comprises a third platinum group metal (PGM) and a third support material; and wherein either: (i) the third washcoat region is adjacent to the second washcoat region; or (ii) the second washcoat region is disposed or supported on the third washcoat region. Also described are uses and methods involving the oxidation catalyst.

Abstract: A semiconductor device (and method thereof) includes an LSI chip, a package substrate, an optical element chip, and a flexible optical waveguide substrate. The LSI chip and the optical element chip are mounted on an upper surface of the package substrate. The optical element chip is electrically connected to the LSI chip through the package substrate. One end of the flexible optical waveguide substrate is optically coupled to the optical element chip, and the other end is arranged on a bottom surface side of the package substrate.

Abstract: A nondestructive inspection apparatus includes a sensor unit for detecting vibrations transmitted through a test object from a vibration generator and a signal input unit for extracting a target signal from an electric signal outputted from the sensor unit. An amount of characteristics extracting unit is also included for extracting multiple frequency components from the test signal as an amount of characteristics. Further, a decision unit has a competitive learning neural network for determining whether the amount of the characteristics belongs to a category, wherein the competitive learning neural network has been trained by using training samples belong to the category representing an internal state of the test object, wherein distributions of membership degrees of the training samples are set in the decision unit.

Abstract: A method of the present invention is processed by a selector. The selector selects each member constituting a learning data set from a data set source. Each member of the source is feature data extracted through a transducer and assigned to any one of categories in advance. The selector calculates each member's divergence degree of the source to obtain an average divergence degree. If an output neuron of the output layer of a neural network is related to different categories of all the categories represented by the output layer, the selector includes every member of the source corresponding to the category of the minimum average divergence degree in the selection from the source to the learning data set. The selector also excludes, from the selection, every member of the source corresponding to every remaining category of the different categories.

Abstract: An anomaly monitoring device includes two neural networks which are switchable between a training mode by using training samples and a checking mode for classifying, based on a training result, whether an amount of characteristics obtained by an operation of an apparatus indicates that the operation of an apparatus is normal and a mode switching unit controlling one of the neural networks to operate in training mode and the other neural network to operate in the checking mode. Further, the anomaly monitoring device includes a switching determining unit computing a judgment evaluation value serving to evaluate reliability of a judgment result of the other neural network operating in the checking mode, and for instructing the mode switching unit to have the one of the neural networks operate in the checking mode and the other neural network operate in training mode when the judgment evaluation value does not meet evaluation criteria.

Abstract: A method of the present invention is processed by a selector. The selector selects each member constituting a learning data set from a data set source. Each member of the source is feature data extracted through a transducer and assigned to any one of categories in advance. The selector calculates each member's divergence degree of the source to obtain an average divergence degree. If an output neuron of the output layer of a neural network is related to different categories of all the categories represented by the output layer, the selector includes every member of the source corresponding to the category of the minimum average divergence degree in the selection from the source to the learning data set. The selector also excludes, from the selection, every member of the source corresponding to every remaining category of the different categories.

Abstract: An anomaly monitoring device includes: a signal input unit for receiving a periodic target signal generated by an operating apparatus; a storage unit for storing therein segmented target signals provided from the target signal in a form of a queue; a dividing unit for providing comparing portions of each segmented target signal; a power calculating unit for calculating a power of each comparing portion in each segmented target signal. The device further includes an anomalous input detecting unit which judges that a comparing portion of a latest segmented target signal is abnormal if a power of the comparing portion is in a range of abnormal values when compared with a corresponding comparing portion in a previous segmented target signal, and determines that the signal input unit is abnormal if the number of abnormal comparing portions in the latest segmented target signal exceeds a threshold.

Abstract: An image recognizing method is provided, which includes the capability of efficiently recognizing characters such as letters and numerical characters included in an original image with accuracy when at least one of the characters is composed of plural elements. In this method, the elements in the original image are extracted to obtain a second image, in which each of the elements is enclosed by a rectangular frame. Then, a composite image is prepared with respect to a combination of the rectangular frames in the second image. After calculating a characteristic amount of the elements included in the composite image, the characteristic amount is input in a back-propagation network, in which learning about a reference character(s) to be included in the image has already finished, so that a degree of agreement between the characteristic amount of the composite image and the reference character is obtained.

Abstract: A nondestructive inspection apparatus includes a sensor unit for detecting vibrations transmitted through a test object from a vibration generator and a signal input unit for extracting a target signal from an electric signal outputted from the sensor unit. An amount of characteristics extracting unit is also included for extracting multiple frequency components from the test signal as an amount of characteristics. Further, a decision unit has a competitive learning neural network for determining whether the amount of the characteristics belongs to a category, wherein the competitive learning neural network has been trained by using training samples belong to the category representing an internal state of the test object, wherein distributions of membership degrees of the training samples are set in the decision unit.

Abstract: An anomaly monitoring device includes: a signal input unit for receiving a periodic target signal generated by an operating apparatus; a storage unit for storing therein segmented target signals provided from the target signal in a form of a queue; a dividing unit for providing comparing portions of each segmented target signal; a power calculating unit for calculating a power of each comparing portion in each segmented target signal. The device further includes an anomalous input detecting unit which judges that a comparing portion of a latest segmented target signal is abnormal if a power of the comparing portion is in a range of abnormal values when compared with a corresponding comparing portion in a previous segmented target signal, and determines that the signal input unit is abnormal if the number of abnormal comparing portions in the latest segmented target signal exceeds a threshold.

Abstract: An anomaly monitoring device includes two neural networks which are switchable between a training mode by using training samples and a checking mode for classifying, based on a training result, whether an amount of characteristics obtained by an operation of an apparatus indicates that the operation of an apparatus is normal and a mode switching unit controlling one of the neural networks to operate in training mode and the other neural network to operate in the checking mode. Further, the anomaly monitoring device includes a switching determining unit computing a judgment evaluation value serving to evaluate reliability of a judgment result of the other neural network operating in the checking mode, and for instructing the mode switching unit to have the one of the neural networks operate in the checking mode and the other neural network operate in training mode when the judgment evaluation value does not meet evaluation criteria.

Abstract: An image processor for generating, from a surface image of an object having a pattern, a processed image having a distinct contrast between the pattern and a background, is provided. This image processor comprises a first smoothing filter for generating a first smoothed image; a second smoothing filter for generating a second smoothed image; a weighting unit for multiplying each of pixel values of the first smoothed image by a weight coefficient of 1 or more to determine a weighted pixel value; a differential image generator for subtracting each of weighted pixel values provided by the weighting unit from a pixel value of a corresponding pixel of the second smoothed image to generate a differential image; and an image extracting unit for extracting pixel values having the positive sign from the differential image to obtain the processed image. For example, this image processor can be utilized in a pattern recognition apparatus.

Abstract: A method for appearance inspection utilizes a reference image and an object image. Before determining a final reference image for direct comparison with the object image, the outlines of the reference and object images are extracted and processed in accordance with an error function indicative of linear or quadric deformation of the object image in order to derive error parameters including a position, a rotation angle, and a scale of the object image relative to reference image. The resulting error parameters are applied to transform the reference outline. The step of updating the error parameters and transforming the reference outline is repeated until the updated error parameters satisfy a predetermined criterion with respect to a linear or quadric transformation factor of the object image. Thereafter, the last updated parameters are applied to transform the reference image into the final reference image for direct comparison with the object image.