Abstract: A device configured to receive a first encoded vector and receive one or more feature descriptors for a first object. The device is further configured to remove one or more encoded vectors from an encoded vector library that are not associated with the one or more feature descriptors and to identify a second encoded vector in the encoded vector library that most closely matches the first encoded vector based on the numerical values within the first encoded vector. The device is further configured to identify a first item identifier in the encoded vector library that is associated with the second encoded vector and to output the first item identifier.

Abstract: A system for capturing images for training an item identification model obtains an identifier of an item. The system detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system causes the platform to rotate. The system causes at least one camera to capture an image of the item while the platform is rotating. The system extracts a set of features associated with the item from the image. The system associates the item to the identifier and the set of features. The system adds a new entry to a training dataset of the item identification model, where the new entry represents the item labeled with the identifier and the set of features.

Abstract: A system for updating a training dataset of an item identification model determines that an item is not included in a training dataset. In response to determining that the item is not included in the training dataset, the system obtains an identifier of the item. The system detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system captures images of the item. The system extracts a set of features associated with the item from the images. The system associates the item to the identifier and the set of features. The system adds a new entry to the training dataset, where the new entry represents the item labeled with the identifier and the set of features.

Abstract: A transmission includes a drive element, a first output element, a primary transmission unit, a reversing unit, and an intermediate gearbox. At least three of the at least seven shifting elements of the primary transmission unit, at least one of the at least two shifting elements of the reversing unit, and at least one of the at least two shifting elements of the intermediate gearbox are activatable in combinations of at least five shifting elements so as to establish at least eighteen forward gears between the drive element and the first output element.

Abstract: A transmission includes a drive element, a first output element, a primary transmission unit, a reversing unit, and an intermediate gearbox. At least two of the at least five shifting elements of the primary transmission unit, at least one of the at least two shifting elements of the reversing unit, and at least one of the at least two shifting elements of the intermediate gearbox are activatable in combinations of at least four shifting elements so as to establish at least twelve forward gears between the drive element and the first output element.

Abstract: A transmission includes a drive element, a first output element, a primary transmission unit, a reversing unit, and an intermediate gearbox. At least three of the at least eight shifting elements of the primary transmission unit, at least one of the at least two shifting elements of the reversing unit, and at least one of the at least two shifting elements of the intermediate gearbox are activatable in combinations of at least five shifting elements so as to establish at least twenty-eight forward gears between the drive element and the first output element.

Abstract: A transmission includes a drive element, a first output element, a primary transmission unit, a reversing unit, and an intermediate gearbox. At least two of the at least nine shifting elements of the primary transmission unit, at least one of the at least two shifting elements of the reversing unit, and at least one of the at least two shifting elements of the intermediate gearbox are activatable in combinations of at least four shifting elements so as to establish at least twenty-eight forward gears between the drive element and the first output element.

Abstract: A transmission includes a drive element, a first output element, a primary transmission unit, a reversing unit, and an intermediate gearbox. At least two of the at least five shifting elements of the primary transmission unit, at least one of the at least two shifting elements of the reversing unit, and at least one of the at least two shifting elements of the intermediate gearbox are activatable in combinations of at least four shifting elements so as to establish at least twelve forward gears between the drive element and the first output element.

Abstract: In a gaming machine, a first display area displays a plurality of wager options. A wager selection mechanism is operable by a player to select more than one of the wager options to be activated concurrently and to individually select wager amounts to apply to each selected wager option. A second display area displays a game outcome of a spinning reel game of chance. A game outcome evaluator evaluates the game outcome based on each of the concurrently activated wager options and respective ones of the individually selected wager amounts.

Abstract: A method includes providing a jig including a predetermined center and a magnetron installed on the jig; rotating the magnetron and obtaining a measured first magnetic flux density at the predetermined center of the jig; defining a first area of the magnetron based on the measured first magnetic flux density; rotating the magnetron and measuring a plurality of second magnetic flux densities within the first area of the magnetron; deriving a measured second magnetic flux density among the plurality of second magnetic flux densities; comparing the measured second magnetic flux density with a predetermined threshold; and performing an operation based on the comparison.

Abstract: A circuit is provided. The circuit includes a first master stage, a second master stage, a first slave stage, a first slave stage, and a second slave stage. The first master stage includes a data input line. The second master stage includes an inverse data input line. The first slave stage is coupled to an output of the first master stage. The second slave stage is coupled to an output of the second master stage. The first slave stage generates an output signal during a rising edge of a clock cycle. The second slave stage generates an inverted output signal during the rising edge of the clock cycle. The output signal and the inverted output signal are available concurrently.

Abstract: A measuring method is provided. A probe and a first sensor are disposed over a jig including a bar protruding from the jig. The probe is moved until a first surface of the probe is laterally aligned with a second surface of the bar facing the jig. A first distance between the second surface of the bar and the first sensor is obtained by the first sensor. The probe and the first sensor are disposed over a magnetron. Magnetic field intensities at different elevations above the magnetron are measured by the probe. A method for forming a semiconductor structure is also provided.

Abstract: The disclosure herein relates to methods and systems for enabling human-robot interaction (HRI) to resolve task ambiguity. Conventional techniques that initiates continuous dialogue with the human to ask a suitable question based on the observed scene until resolving the ambiguity are limited. The present disclosure use the concept of Talk-to-Resolve (TTR) which initiates a continuous dialogue with the user based on visual uncertainty analysis and by asking a suitable question that convey the veracity of the problem to the user and seek guidance until all the ambiguities are resolved. The suitable question is formulated based on the scene understanding and the argument spans present in the natural language instruction. The present disclosure asks questions in a natural way that not only ensures that the user can understand the type of confusion, the robot is facing; but also ensures minimal and relevant questioning to resolve the ambiguities.

Abstract: A method includes providing a jig including a predetermined center and a magnetron installed on the jig; rotating the magnetron and obtaining a measured first magnetic flux density at the predetermined center of the jig; defining a first area of the magnetron based on the measured first magnetic flux density; rotating the magnetron and measuring a plurality of second magnetic flux densities within the first area of the magnetron; deriving a measured second magnetic flux density among the plurality of second magnetic flux densities; comparing the measured second magnetic flux density with a predetermined threshold; and performing an operation based on the comparison.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a grant indicating a modulation and coding scheme (MCS) that indicates that the grant is for a retransmission of an initial communication. The UE may decode, based at least in part on the grant indicating the MCS that indicates that the grant is for the retransmission and using a transport block size (TBS) of a prior communication, a communication scheduled by the grant, wherein the prior communication is prior to the initial communication. Numerous other aspects are described.

Abstract: Embodiments described herein relate to detectors and their method of use for sensing electromagnetic fields, electromagnetic signals, biochemical analytes, and/or other conditions in subjects. The device may include an inductively-coupled implantable coil-based transducer that converts electrical, photonic, biochemical signals, and/or other appropriate signals and/or conditions originating in tissues and/or transplanted tissue grafts into changes in a property of the transducer, such as a resonance frequency, that may be detected using an alternating magnetic field that may be provided by a magnetic resonance imaging (MRI) signal and/or other appropriate source. In some embodiments, the detector comprises a FET that changes state upon detection of a subject condition of interest. The change in the FET may change the resonance frequency of an associated LC or RLC circuit.

Abstract: This disclosure provides systems and methods for robotic task planning when a complex task instruction is provided in natural language. Conventionally robotic task planning relies on a single task or multiple independent or serialized tasks in the task instruction. Alternatively, constraints on space of linguistic variations, ambiguity and complexity of the language may be imposed. In the present disclosure, firstly dependencies between multiple tasks are identified. The tasks are then ordered such that a dependent task is always scheduled for planning after a task it is dependent upon. Moreover, repeated tasks are masked. Thus, resolving task dependencies and ordering dependencies, a complex instruction with multiple interdependent tasks in natural language facilitates generation of a viable task execution plan. Systems and methods of the present disclosure finds application in human-robot interactions.

Abstract: Systems are provided for compressing portfolios of open option positions. Market participants may provide constraints, such as net delta and gamma values within a specific tolerance. A compression engine uses a linear, integer and/or linear-quadratic programming solver to analyze portfolios of multiple market participants and identify multilateral option spread trades that result in portfolios that are compressed subject to the constraints.

Abstract: Embodiments relate to an input-encoding technique in conjunction with federation. Participating entities are arranged in a collaborative relationship. Each participating entity trains a machine learning model with an encoder on a training data set. The performance of each of the models is measured and at least one of the models is selectively identified based on the measured performance. An encoder of the selectively identified machine learning model is shared with each of the participating entities. The shared encoder is configured to be applied by the participating entities to train the first and second machine learning models, which are configured to be merged and shared in the federated learning environment.