Abstract: Method for obtaining at least one significant feature in a series of components of the same type on the basis of data sets by non-destructive testing. The method includes examining a classified random sample of components which have a known production sequence, by a non-destructive testing. A three-dimensional data set for each component is obtained, and components of the sample are divided by good and rejected parts. Defect-free component regions from all of the components of the random sample are extracted. At least one feature which is characteristic of the type of component and production process which, over a predetermined time of component production, exhibits considerable characteristic differences between the good and rejected parts is determined. The determination can be accomplished using neural networks, machine learning approaches, or statistics from the field of data analytics. The at least one feature and its characteristic is defined as a trained classifier.

Abstract: A defrosting system includes an RF signal source, two electrodes proximate to a cavity within which a load to be defrosted is positioned, a transmission path between the RF signal source and the electrodes, and an impedance matching network electrically coupled along the transmission path between the output of the RF signal source and the electrodes. The system also includes power detection circuitry coupled to the transmission path and configured to detect reflected signal power along the transmission path. A system controller is configured to modify, based on the reflected signal power, values of variable capacitors of the impedance matching network to reduce the reflected signal power. The impedance matching network may be a single-ended network or a double-ended network.

Abstract: Method for obtaining information from short-fibre-reinforced plastic components sequentially produced by an X-ray computed tomography. A learning phase includes: generating CT data sets for a random sample of plastic components from a production process; extracting at least one defect-free region of the plastic components; determining characteristic feature(s) in the extracted regions, relevance of individual features, and regions which are characteristic of the plastic component type and production process thereof, over a predetermined period of the plastic components productions, which exhibit considerable characteristic differences between good parts and reject parts; and defining the feature(s) with its characteristic as trained classifier.

Abstract: Method for obtaining information from short-fibre-reinforced plastic components sequentially produced by an X-ray computed tomography. A learning phase includes: generating CT data sets for a random sample of plastic components from a production process; extracting at least one defect-free region of the plastic components; determining characteristic feature(s) in the extracted regions, relevance of individual features, and regions which are characteristic of the plastic component type and production process thereof, over a predetermined period of the plastic components productions, which exhibit considerable characteristic differences between good parts and reject parts; and defining the feature(s) with its characteristic as trained classifier.

Abstract: Method for obtaining at least one significant feature in a series of components of the same type on the basis of data sets by non-destructive testing. The method includes examining a classified random sample of components which have a known production sequence, by a non-destructive testing. A three-dimensional data set for each component is obtained, and components of the sample are divided by good and rejected parts. Defect-free component regions from all of the components of the random sample are extracted. At least one feature which is characteristic of the type of component and production process which, over a predetermined time of component production, exhibits considerable characteristic differences between the good and rejected parts is determined. The determination can be accomplished using neural networks, machine learning approaches, or statistics from the field of data analytics. The at least one feature and its characteristic is defined as a trained classifier.

Abstract: A defrosting system includes an RF signal source, two electrodes proximate to a cavity within which a load to be defrosted is positioned, a transmission path between the RF signal source and the electrodes, and an impedance matching network electrically coupled along the transmission path between the output of the RF signal source and the electrodes. The system also includes power detection circuitry coupled to the transmission path and configured to detect reflected signal power along the transmission path. A system controller is configured to modify, based on the reflected signal power, values of variable capacitors of the impedance matching network to reduce the reflected signal power. The impedance matching network may be a single-ended network or a double-ended network.

Abstract: The present invention provides an exercise device for use in non-surgical treatment of tennis elbow or lateral epicondylopathy (LE) and for post-surgical rehabilitation and other upper limb rehabilitation. The exercise device comprising a main body, and at least one gripping means provided on the main body, wherein each gripping means comprises a rotatable hand grip and a mode selector means, wherein the mode selector means is operable to move the gripping means from a first configuration in which the rotatable hand grip is rotatable relative the main body and a second configuration in which the rotatable hand grip is in a fixed position and not rotatable relative the main body, and wherein a static grip is provided on the main body such that a user may hold the exercise device with both hands, one hand holding the rotatable hand grip, the other hand holding the static grip to perform exercises.

Abstract: A plaster-based board includes a plaster-based core positioned between two sheets of paper or nonwoven fabric, wherein the core contains at least one polymer selected from polyvinyl butyral (PVB), copolymers of vinyl acetate and an olefin, which copolymers have a glass transition temperature that varies from ?10° C. to +25° C., terpolymers of vinyl acetate, an olefin and a vinyl ester monomer, terpolymers of vinyl acetate, a vinyl ester monomer and a (meth)acrylate monomer, and copolymers of vinyl acetate and an acrylic monomer.

Abstract: The present invention provides an exercise device for use in non-surgical treatment of tennis elbow or lateral epicondylopathy (LE) and for post-surgical rehabilitation and other upper limb rehabilitation. The exercise device comprising a main body, and at least one gripping means provided on the main body, wherein each gripping means comprises a rotatable hand grip and a mode selector means, wherein the mode selector means is operable to move the gripping means from a first configuration in which the rotatable hand grip is rotatable relative the main body and a second configuration in which the rotatable hand grip is in a fixed position and not rotatable relative the main body, and wherein a static grip is provided on the main body such that a user may hold the exercise device with both hands, one hand holding the rotatable hand grip, the other hand holding the static grip to perform exercises.

Abstract: Methods of identifying individuals are presented.

Abstract: The invention provides a method for stimulating the regeneration of a neuronal cell, said method comprising exposing the cell to the osteonectin protein or a functional equivalent thereof in an amount that is effective to stimulate the regeneration of the cell.