Abstract: A method for accurately positioning a navigation target point includes: selecting a navigation reference with a fixed position, acquiring positions of the navigation reference and the navigation target point in a navigation coordinate system respectively, and calculating a position of the navigation target point relative to the navigation reference, so as to further obtain a position of the navigation target point in a coordinate system of the navigation reference. As long as the navigation reference does not move, the coordinate system of the navigation reference will not change during the entire navigation process, and spatial position coordinates of the navigation target point in the coordinate system of the navigation reference will not be interfered by the navigation coordinate system.

Abstract: A stator assembly and stator for a motor is provided that directly installs in a conductor slot a slot wedge having a width approximately the same as the width of the conductor slot. The slot wedge is limited in three directions, circumferential, radial, and axial, by means of cooperation between a slot wedge pressing ring, a conductor, and a sidewall of the conductor slot, and at the same time, the slot wedge is capable of preventing the conductor from falling out of the conductor slot. In addition, in the stator assembly for a motor disclosed, when the slot wedge is installed, the slot wedge may not only be inserted and installed in the conductor slot along the axial direction, but may also be inserted and installed in the conductor slot along the radial direction, and thus, the installation mode is flexible, which may improve the installation efficiency.

Abstract: A method and device for smoke or fire recognition, a computer device and a storage medium are disclosed. The method includes: acquiring a to-be-recognized image in a smoke or fire monitoring region; recognizing a smoke or fire suspected region in the to-be-recognized image according to the to-be-recognized image, including recognizing a smoke or fire suspected region in a visible light image on the basis of colors, and recognizing a smoke or fire suspected region in an infrared image on the basis of brightness; and inputting the to-be-recognized image including the smoke or fire suspected region into a preset model, and recognizing a smoke or fire state in the to-be-recognized image according to an output result of the preset model, the preset model being obtained by training based on the visible light image pre-marked with a smoke or fire state or the infrared image pre-marked with a smoke or fire state.

Abstract: The present disclosure relates to the technical field of potential transformer (PT) ferromagnetic resonance elimination, in particular to a PT ferromagnetic resonance elimination method implemented by actively inputting resistance through an electronic load, including the following steps: setting up a PT, and determining a mapping relationship; constructing a resonance elimination control system; and designing the electronic load as an active resonance elimination device. The present disclosure overcomes a contradiction between a magnitude of resonance elimination resistance and winding overload in a PT open delta during single-phase-to-earth fault and fault clearance, and effectively avoids the technical problems of difficult distinguishing between single-phase-to-earth fault characteristics and power frequency resonance characteristics and causing resonance in a single-phase-to-earth fault process.

Abstract: The present disclosure provides a self-adaption faster-than-real-time method for estimating a working condition start-up state of a unit. Firstly, an event recording sequence, an analog measurement point ID, an analog measurement point first-level alarm value and a history scatter point distribution record are read from a time sequence event record table, an analog measurement point table, an alarm threshold table and a historical scatter record table. A measured value slope of the analog measurement point is calculated according to an event recording relative time. Then, an abnormal state estimated value is calculated based on the history scatter point distribution record, the analog measurement point first-level alarm value and the measured value slope of the analog measurement point. Finally, a pre-warning is sent to remind a watchman to perform a preventive operation when the abnormal state estimated value is above the threshold.

Abstract: An artificial neural network for data imbalanced regression and a method for training that network. A regression dataset is obtained that includes multiple pairs that respectively are made up of inputs and corresponding targets. The inputs are represented in a feature space and the targets are represented in a label space of continuous values. Label space similarities between the targets as represented in the label space are determined, and analogously feature space similarities between the inputs as represented in the feature space are determined. A loss may then be determined based on differences between rankings of the label space similarities and corresponding feature space similarities. That loss may be used to train an artificial neural network.

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

Abstract: Disclosed solutions for improved machine learning (ML) employ knowledge balancing self-distillation with adaptive mutual information (AMI). Examples include: for a neural network (NN) having a plurality of modules, determining a task objective for at least a final module of the plurality of modules; for the NN, determining a balancing objective using at least an output of the final module and an output of a first intermediate module of the plurality of modules; determining an overall objective, wherein determining the overall objective comprises combining the task objective with the balancing objective; and adjusting weights of the NN to minimize the overall objective. Balancing information may combine mutual information (between an intermediate module output and the output of the final module) with self-information (for the intermediate module output) to produce AMI. Adjusting weights of the NN during training, using the AMI, results in knowledge balancing self-distillation.

Abstract: A composition comprising a C2-C12 polyalphaolefin and a functionalized propylene-based elastomer comprising from about 4 to about 25 wt % units derived from one or more C2 or C4-C12 alpha-olefins; a triad tacticity greater than about 90%; a heat of fusion less than about 75 J/g; and a plurality of oxygen containing functional groups selected from carboxylic acids, anhydrides, ketones, carbonates, esters, ethers, lactones, and combinations thereof. Compositions containing the functionalized propylene-based elastomer and methods to produce the same are also disclosed.

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

Abstract: The present invention relates to a wound covering with prominent biocompatible and accelerated wound-healing and its preparation method thereof. The wound covering comprises a film prepared from collagen and Dopa-containing protein—mussel adhesive protein, which is immobilized on collagen by chemical cross-linking, thus enhances the stability of protein structure and maintains the activity of collagen and mussel adhesive protein. The wound covering has excellent mechanical strength and can be trimmed into any shape; it accelerates tissue epithelisation and promotes wound healing with good biocompatibility, non-adhesive to the wound and no further wound damages.

Abstract: The present disclosure provides a self-adaption faster-than-real-time method for estimating a working condition start-up state of a unit. Firstly, an event recording sequence, an analog measurement point ID, an analog measurement point first-level alarm value and a history scatter point distribution record are read from a time sequence event record table, an analog measurement point table, an alarm threshold table and a historical scatter record table. A measured value slope of the analog measurement point is calculated according to an event recording relative time. Then, an abnormal state estimated value is calculated based on the history scatter point distribution record, the analog measurement point first-level alarm value and the measured value slope of the analog measurement point. Finally, a pre-warning is sent to remind a watchman to perform a preventive operation when the abnormal state estimated value is above the threshold.

Abstract: The present disclosure provides a self-adaptive test method for an intelligent prediction algorithm of analog measured values. Firstly, an event recording sequence, an analog measurement point ID and an analog measurement point alarm value are read from a time sequence event record table, an analog measurement point table and an alarm threshold table. Next, operation records of a normal operation state of a unit within a statistical cycle are acquired to form historical statistics of measured values of the analog measurement point based on switching value signals. Then, simulated measured values of the analog measurement point with time scales are calculated based on the historical statistics, the analog measurement point alarm value and an analog measurement point current measured value. Finally, sensitivity is calculated; and an alarm is sent to remind a technician to adjust the algorithm when the sensitivity is greater than a threshold.

Abstract: A stator assembly and stator for a motor is provided that directly installs in a conductor slot a slot wedge having a width approximately the same as the width of the conductor slot. The slot wedge is limited in three directions, circumferential, radial, and axial, by means of cooperation between a slot wedge pressing ring, a conductor, and a sidewall of the conductor slot, and at the same time, the slot wedge is capable of preventing the conductor from falling out of the conductor slot. In addition, in the stator assembly for a motor disclosed, when the slot wedge is installed, the slot wedge may not only be inserted and installed in the conductor slot along the axial direction, but may also be inserted and installed in the conductor slot along the radial direction, and thus, the installation mode is flexible, which may improve the installation efficiency.

Abstract: The disclosure describes one or more embodiments of a structured text summary system that generates structured text summaries of digital documents based on an interactive graphical user interface. For example, the structured text summary system can collaborate with users to create structured text summaries of a digital document based on automatically generating document tags corresponding to the digital document, determining segments of the digital document that correspond to a selected document tag, and generating structured text summaries for those document segments.

Abstract: In an example embodiment, position bias and other types of bias may be compensated for by using two-phase training of a machine-learned model. In a first phase, the machine-learned model is trained using non-randomized training data. Since certain types of machine-learned models, such as those involving deep learning (e.g., neural networks) require a lot of training data, this allows the bulk of the training to be devoted to training using non-randomized training data. However, since this non-randomized training data may be biased, a second training phase is then used to revise the machine-learned model based on randomized training data to remove the bias from the machine-learned model. Since this randomized training data may be less plentiful, this allows the deep learning machine-learned model to be trained to operate in an unbiased manner without the need to generate additional randomized training data.

Abstract: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for techniques for identifying textual similarity and performing answer selection. A textual-similarity computing model can use a pre-trained language model to generate vector representations of a question and a candidate answer from a target corpus. The target corpus can be clustered into latent topics (or other latent groupings), and probabilities of a question or candidate answer being in each of the latent topics can be calculated and condensed (e.g., downsampled) to improve performance and focus on the most relevant topics. The condensed probabilities can be aggregated and combined with a downstream vector representation of the question (or answer) so the model can use focused topical and other categorical information as auxiliary information in a similarity computation.

Abstract: A base film for a light diffusion film includes a transparent polymer layer, which comprises a plurality of nanopores, and liquid crystal filled in the plurality of nanopores. A light diffusion film, a display device, and production methods thereof are also disclosed.

Abstract: The disclosure describes one or more embodiments of a structured text summary system that generates structured text summaries of digital documents based on an interactive graphical user interface. For example, the structured text summary system can collaborate with users to create structured text summaries of a digital document based on automatically generating document tags corresponding to the digital document, determining segments of the digital document that correspond to a selected document tag, and generating structured text summaries for those document segments.