Abstract: A medical device includes a shaft. The shaft includes an integral tube defining a plurality of lumens. The integral tube is comprised of at least one of PTFE and ePTFE. A density of the at least one of PTFE and ePTFE varies along a length of the integral tube.

Abstract: The present invention relates to a method for processing data executed by a computing apparatus including at least a storage and a processor in a human-computer interface system using electroencephalography (EEG) data and eye tracking (ET) data, the method comprising following steps: representing through the control interface, a set of list of keys which is associated with user actions; collecting and processing the two EEG and ET dataset, to determine whether the user is looking at a certain key or not and the concentration state of the user while looking at that key, if yes then activating a time counting parameter t with an increasing rate of the time counting parameter ?>0 and an adjusting rate ?T; confirming whether the user wants to select that key or not, based on a time constraint defined as t?dwell, wherein dwell is a known parameter according to a conventional method corresponding to a required time duration that the user has to look at a key to select that key.

Abstract: An unmanned aerial vehicle aerial vehicle and a localization method for an unmanned aerial vehicle aerial vehicle are described. In an embodiment, an unmanned aerial vehicle comprises: a first ultra-wide band node; a second ultra-wide band node; and a localization processor configured to use signals received at the first ultra-wide band node and the second ultra-wide band node from a plurality of anchor nodes located within an environment to estimate a pose state of the unmanned aerial vehicle, wherein the first ultra-wide band node and the second ultra-wide band node are arranged on the unmanned aerial vehicle at positions offset from one another.

Abstract: A method includes training, by one or more processing devices, a plurality of machine learning predictive models, thereby generating a plurality of trained machine learning predictive models. The method further includes generating, by the one or more processing devices, a solved machine learning optimization model, based at least in part on the plurality of trained machine learning predictive models. The method further includes outputting, by the one or more processing devices, one or more control input and predicted outputs based at least in part on the solved machine learning optimization model.

Abstract: A surface cleaning apparatus, such as a carpet extractor, includes a base and a fluid recovery system for drawing dirty cleaning fluid from a surface to be cleaned. The fluid recovery system includes a suction nozzle in fluid communication with a recovery chamber. The suction nozzle is mounted to the base for vertical movement with respect to the base and is biased into contact with the surface to be cleaned.

Abstract: A surface cleaning apparatus having a suction source defining a portion of a working air path and a fluid delivery system includes at least one fluid distributor, a fluid supply path, a first pump in the fluid supply path, and a second pump in the fluid supply path. The pumps are operable to effect dispensing cleaning fluid at different volumetric flow rates.

Abstract: The present disclosure provides a surface cleaning apparatus that includes steam delivery. The apparatus includes a hand-carried body adapted to be hand-carried by a user, the hand-carried body including a supply tank, a recovery tank, a liquid supply pump, a steam supply pump, a heater, and a suction source including a vacuum motor. A flexible hose is mounted to the hand-carried body and a hand-held cleaning tool mounted to an end of the hose.

Abstract: In unsupervised interpretable machine learning, one or more datasets having multiple features can be received. A machine can be trained to jointly cluster and interpret resulting clusters of the dataset by at least jointly clustering the dataset into clusters and generating hyperplanes in a multi-dimensional feature space of the dataset, where the hyperplanes separate pairs of the clusters, where a hyperplane separates a pair of clusters. Jointly clustering the dataset into clusters and generating hyperplanes can repeat until convergence, where the clustering in a subsequent iteration uses the generated hyperplanes from a previous iteration to optimize performance of the clustering. The hyperplanes can be adjusted to further improve the performance of the clustering. The clusters and interpretation of the clusters can be provided, where a cluster's interpretation is provided based on hyperplanes that construct a polytope containing the cluster.

Abstract: The present disclosure provides a surface cleaning apparatus that includes a headlight or other light source that selectively illuminates upon the occurrence of a predetermined condition. The headlight turns on to emit light when the surface cleaning apparatus us turned on, and emits light in a different color when cleaning fluid is dispensed. Methods for operating a headlight or light source are also disclosed.

Abstract: A medical stent may include a tubular support structure including a plurality of struts defining a plurality of cells disposed between the plurality of struts. A polymeric coating may be disposed over the tubular support structure such that a first portion of the plurality of cells are closed by the polymeric coating in a first region of the tubular support structure and a second portion of the plurality of cells in a second region of the tubular support structure remain open to fluid flow and/or tissue ingrowth therethrough. The struts in the first region of the tubular support structure and the struts in the second region of the tubular support structure may be at least partially covered by the polymeric coating.

Abstract: Software that performs the following operations: (i) receiving a set of graph predictions corresponding to an input text, where graph predictions of the set of graph predictions are generated by different respective machine learning models; (ii) blending the graph predictions of the set of graph predictions to generate a plurality of candidate blended graphs, where nodes and edges of the candidate blended graphs have respective selection metric values, generated using a selection metric function, that meet a minimum threshold; and (iii) selecting as an output blended graph a candidate blended graph of the plurality of candidate blended graphs having a highest total combination of selection metric values among the plurality of candidate blended graphs.

Abstract: A method includes: receiving, by a computing device, data from sensors in a manufacturing environment; mapping, by the computing device, the data into a deep learning network; learning, by the computing device, correlations between inputs and outputs of the manufacturing environment using the data; pruning, by the computing device, the deep learning network; predicting, by the computing device and using the pruned network, an output of the pruned network from the inputs of the manufacturing environment; linearizing, by the computing device, the pruned network; optimizing, by the computing device, the output of the linearized pruned network to calculate predicted inputs for the manufacturing environment; and changing, by the computing device, operation inputs in the manufacturing environment to match the predicted inputs.

Abstract: Aspects of the disclosure relate to a dynamic event securitization and neural network analysis system. A dynamic event inspection and securitization computing platform comprising at least one processor, a communication interface, and memory storing computer-readable instructions may securitize event data prior to authorizing execution of the event. A neural network event analysis computing platform comprising at least one processor, a communication interface, and memory storing computer-readable instructions may utilize a plurality of event analysis modules, a neural network, and a decision engine to analyze the risk level values of data sharing events. The dynamic event inspection and securitization computing platform may interface with the neural network event analysis computing platform by generating data securitization flags that may be utilized by the neural network event analysis computing platform to modify event analysis results generated by the event analysis modules.

Abstract: Bias supplies and plasma processing systems are disclosed. One bias supply comprises an output node, a return node, and a switch network and at least one power supply coupled to the output node and the return node. The switch network and the at least one power supply configured, in combination, to apply an asymmetric periodic voltage waveform and provide a corresponding current waveform at the output node relative to the return node. A timing parameter estimator receives a digital representation of a full cycle of the voltage and current waveforms, and generates a pulse width control signal based on a crossing time that the current waveform crosses a threshold current value after falling from a positive peak current value to control the switch network.

Abstract: This document describes a framework for measuring and improving the performance of applications, such as distributed applications and web applications. In one aspect, a method includes performing a test on an application. The test includes executing the application on one or more computers and, while executing the application, simulating a set of workload scenarios for which performance of the application is measured during the test. While performing the test, a set of performance metrics that indicate performance of individual components involved in executing the application during the test is obtained. A knowledge graph is queried using the set of performance metrics. The knowledge graph links the individual components to corresponding performance metrics and defines a set of hotspot conditions that are each based on one or more of the corresponding performance metrics for the individual components. A given hotspot condition is detected based on the set of performance metrics.

Abstract: A surface cleaning apparatus having an upright assembly, a power source, and a coiled electrical cable. The upright assembly including a frame and a telescoping handle at last partially extending from the frame and movable between an extended position and a contracted position. The coiled electrical cable being provided within a portion of the telescoping handle and configured to uncoil or coil when the telescoping handle is moved between the extended position and the contracted position.

Abstract: A method for driving an electromechanical sliding door in a transportation vehicle, wherein the sliding door has an adjusting mechanism with a rolling carriage guided in a guide rail and a first electric drive motor. A fixing mechanism with a second electric drive motor and also a locking mechanism is also provided, which locking mechanism allows the rolling carriage to be arrested in any desired position. Here, the locking mechanism is driven by the second electric drive motor. The method may include driving the second electric drive motor with an input voltage which lies below a threshold voltage for tripping the locking mechanism, continuously increasing the input voltage for the second electric drive motor, and locking the locking mechanism when the input voltage for the second electric drive motor exceeds the threshold voltage for tripping the locking mechanism.

Abstract: The present disclosure provides a surface cleaning apparatus that includes steam delivery. The apparatus includes a hand-carried body adapted to be hand carried by a user, the hand-carried body having a main housing, a supply tank, and a heater. A flexible hose is mounted to the hand-carried body and a hand-held cleaning tool mounted to an end of the hose. The tool has a liquid distributor to deliver liquid cleaning fluid and a steam distributor to deliver steam. Various features for controlling the operation of electrical component of the extraction cleaner are disclosed.