Abstract: Systems and methods for deep technology innovation management by cross-pollinating innovations dataset are disclosed. A system extracts context-based keyword from an innovation dataset by transforming the innovation dataset to a vector. Further, the system searches semantically relevant keywords for the extracted context-based keyword, by extracting an entity and a key phrase from the extracted a context-based keyword. Furthermore, system clusters the vector, by identifying frequent keywords in the semantically relevant keywords to obtain cluster centroids of the frequent keywords. Thereafter, the system determines weighted keywords in each cluster using the obtained cluster centroids, and classifies the weighted keywords to identify emerging innovation trends relevant to the innovation in the innovation dataset. The system forms cohorts of innovators to explore the reuse of innovations, assets, code, and build focused monetization model.

Abstract: Systems, methods, and software program products for dispensing chemical solutions. A controller receives a signal from a pressure sensor indicative of a pressure of a diluent. The controller determines an expected flow rate of the diluent through an eductor based at least in part on the pressure of the diluent. The controller may further determine an expected concentration of a chemical product in the solution dispensed from a discharge port of the eductor. Based on the expected flow rated and concentration of the chemical product, the controller determines a duration of a dispense stage of a dispensing operation required to dispense a predetermined dose of the chemical product. The controller then causes the diluent to flow through the eductor for the determined duration of the dispense stage. A check valve on the output of the eductor prevents dissimilar chemicals from mixing and reduces a response time of the eductor.

Abstract: A micro-electro-mechanical-systems (MEMS) device is disclosed that is configured to operate as a reservoir computer including performing sensing and computing co-locally. The MEMS device includes circuitry for: generating a modulated input signal based on an input signal; generating a MEMS deflection signal based on the modulated input signal and a time-delayed MEMS deflection signal; sampling the MEMS deflection signal N times during a time internal T to generate a MEMS deflection matrix, wherein MEMS deflection matrix has a size M×N, wherein N corresponds to a number of virtual nodes of the reservoir computer and M is a number of time steps of time interval T; receiving a trained weight matrix, wherein the trained weight matrix is trained by linear regression; and multiplying the MEMS deflection matrix by the trained weight matrix to generate an output signal that classifies the input signal.

Abstract: A method for decoding an encoded audio bitstream in an audio processing system is disclosed. The method includes extracting from the encoded audio bitstream a first waveform-coded signal comprising spectral coefficients corresponding to frequencies up to a first cross-over frequency for a time frame and performing parametric decoding at a second cross-over frequency for the time frame to generate a reconstructed signal. The second cross-over frequency is above the first cross-over frequency and the parametric decoding uses reconstruction parameters derived from the encoded audio bitstream to generate the reconstructed signal. The method also includes extracting from the encoded audio bitstream a second waveform-coded signal comprising spectral coefficients corresponding to a subset of frequencies above the first cross-over frequency for the time frame and interleaving the second waveform-coded signal with the reconstructed signal to produce an interleaved signal for the time frame.

Abstract: A container includes a container main body and a cushioning. The container main body is configured with an accommodation space that is to accommodate a to-be-accommodated object with a flat plate shape. The container main body includes a base, a side wall, and a recess. The recess is formed in a peripheral part of the base and recessed from a surface of the base. The cushioning is to be set in the recess in multiple different postures. The cushioning has a first surface including a first receiving surface and a second receiving surface. In a state in which the cushioning in a first posture or a second posture is set in the recess, the first receiving surface or the second receiving surface faces the accommodation space and the second receiving surface or the first receiving surface is buried in the recess.

Abstract: An opening is formed at an end portion of a stack case that houses a fuel cell stack. A unit cell constituting a fuel cell stack is provided with a cell voltage detection terminal at a position facing an opening. A conductor extends from the cell voltage detection terminal. The opening is covered with a porous cover that is formed with a plurality of through-holes. The porous cover is formed with an annular protrusion on an end face facing the cell voltage detection terminal. The annular protrusion is located among the plurality of through-holes.

Abstract: There is provided an information processing device including a display control unit configured to display pieces of content at a first position of a screen, a condition setting unit configured to set a clustering condition for the pieces of content in accordance with a user operation, and a clustering unit configured to classify the pieces of content into a cluster in accordance with the clustering condition. The display control unit moves a display of the pieces of content from the first position toward a second position corresponding to the cluster.

Abstract: A children's accessory including a frame and a containment portion supported by the frame. In some example forms, the frame is adjustable between a lower first height and a higher second height relative to a supporting surface. In some example forms, the containment portion is adjustable between a shallower first depth and a deeper second depth. In some example forms, the containment portion further comprises a bedside sleeper flap configured to be opened or closed for side access to the containment portion. In some example forms, the accessory is reconfigurable between two or more configurations, such as for example a bassinet configuration, a bedside sleeper configuration and a playard configuration. In some example forms, the frame includes at least one modular frame component.

Abstract: In one example, an active variable reactance rectifier circuit includes an active variable reactance rectifier circuit input port and an output port. A power splitter circuit includes an input port coupled to the active variable reactance rectifier circuit input port and a pair of output ports. A first rectifier circuit includes an input port is coupled to the first power splitter circuit output port. A second rectifier circuit includes an input port coupled to the second power splitter circuit output port. A power combiner circuit includes a first input port, a second input port and an output port. The first power combiner circuit input port is coupled to the first rectifier circuit output port, the second power combiner circuit input port is coupled to the second rectifier circuit output port and the power combiner circuit output port is coupled to the active variable reactance rectifier circuit output port.

Abstract: A set condition determining method for manufacturing facilities includes: inputting, into a trained model, a manufacturing condition for a target product and a setup condition that is for a product manufactured in same manufacturing facilities before manufacture of the target product and that reflects setup condition modification by an operator's manual manipulation; and obtaining a setup condition for the target product. The trained model has been trained with input being: manufacturing conditions for the target product; and setup conditions that are for the product manufactured in the same manufacturing facilities before the manufacture of the target product and that reflect setup condition modification by an operator's manual manipulation, and output being setup conditions for the target product.

Abstract: Systems and methods for managing airflow for cooling computing devices (e.g. in a data center) in normal and cold environments are disclosed. In one embodiment, the method comprises positioning the computing devices on a plurality of racks with air barriers to create hot and cold aisles. The computing devices may be configured in a first mode to draw in cool air the cold aisles and exhaust heated air into the hot aisles. Temperatures in the cold aisles may be periodically measured. In response to temperatures below a predetermined threshold, one or more of the cold aisles may be converted into a temporary hot aisle by adjusting ventilation openings and configuring a subset of the computing devices to temporarily draw in warm air from the temporary hot aisle.

Abstract: A bassinet includes a base, a column assembly rotatably connected to the base at a first end of the column assembly, an arm rotatably connected to a second end of the column assembly, a tub frame pivotably connected to the arm, an infant tub retained within the tub frame, the infant tub including a front wall, a back wall, and two side walls and having areas of reduced height along the front wall and at least one of the side walls to provide enhanced access to the infant located within the infant tub, and an insert configured to reversibly fit within an interior of the infant tub.

Abstract: Improvement is made in performance of a trained neural network that uses positional information indicating a position at which each token included in an input sequence is present in the input sequence.

Abstract: An analysis device according to the present disclosure is provided with: a data acquisition unit that acquires data detected by an industrial machine; an operation state extraction unit that extracts, from the data, data detected during operation of the industrial machine; an annotation unit that creates a plurality of data set groups by giving, on the basis of a predetermined standard, annotations indicating motion states of the industrial machine to a plurality of data sets segmented by a predetermined standard from the extracted data during the operation; a feature amount extraction unit that extracts a feature amount of data included in each of the data sets; a learning unit that generates decision tree models respectively for the plurality of data set groups; and a display unit that ranks the generated decision tree models on the basis of correct answer rates regarding prediction of the annotations based on predetermined training data and that displays the decision tree models.

Abstract: The present disclosure relates to a package for one or more delivery systems. The package includes a container and a lid hingedly connected to the container about a hinge line 5. The package further includes an inner frame comprising a side wall having a portion which extends from the container and which is received in the lid when the lid is closed. The portion of the side wall extending from the container includes at least two regions having different coefficients of friction.

Abstract: A method for using a processor unit of an autonomously movable vehicle involves making a computing power of the processor unit available to at least one external computer network and/or to a computer cluster during a process of charging an electrical energy storage unit of the vehicle.

Abstract: A method includes determining queue times associated with operations of a sequence recipe. The operations are associated with production of substrates in a substrate processing system. The method further includes generating a schedule based on the queue times. The method further includes transmitting the schedule to a controller of the substrate processing system. The controller is to control the substrate processing system to produce the substrates based on the schedule.

Abstract: A power system includes: power converters, each including a power conversion unit configured to convert an input power, and output the converted power, a controller configured to execute a primary control for controlling the output by controlling the power conversion unit based on: a reference function having a drooping characteristic defined according to an input value and a voltage of the bus or a power of the power converter to which the power conversion unit is connected, and an update unit configured to update a control method on the output; a central control device configured to execute a secondary control of controlling the power converter; the bus connected to the power conversion unit; and a power element connected to the power converter and configured to supply, consume and charge power. The central control device performs the secondary control on the power converter according to an update instruction to update the control method.

Abstract: A stirring device is provided. The stirring device includes a stirring component and a base. the stirring component comprises a stirring portion and a holding portion, the stirring portion and the holding portion are connected to each other. The base defines an accommodating groove having an upper opening, at least one draining hole for communicating the accommodating groove with the outside is defined on a groove bottom wall of the accommodating groove, and the stirring portion is at least partially disposed in the accommodating groove. The stirring device that is capable of being properly placed and well protected.

Abstract: Described herein is an Autonomous Conversational AI system, which does not require any human configuration or annotation, and is used to have multi-turn dialogs with a user. A typical Conversational AI system consists of three main models: Natural Language Understanding (NLU), Dialog Manager (DM) and Natural Language Generation (NLG), which requires human provided data and configuration. The system proposed herein leverages novel Conversational AI methods which automatically generates conversational AI configuration from any historical conversation logs. The automatically generated configuration contains Auto-Topics, Auto-Subtopics, Auto-Intents, Auto-Responses and Auto-Flows which are used to automatically train NLU, DM and NLG models. Once these models are trained for given conversation logs, the system can be used to have dialog with any user.