Abstract: A request to configure a connect cluster including one or more connectors for a cloud computing system is received. The request include a desired connector state. A connector specification file is automatically generated based on the desired connector state for the connect cluster via a declarative application programming interface (API). Application resources associated with the connect cluster are automatically configured based on the specification file.

Abstract: A deployment request is received for a plurality of clusters within a plurality cloud computing environments. The deployment request relates to one or more operational actions for computing devices associated with the plurality of clusters. The plurality of clusters is associated with a single application programming interface (API). A set of standards are received for the plurality of clusters from the API. The plurality of clusters is configured according to the set of standards to create a configured plurality of clusters. The configured plurality of clusters are deployed within the plurality of cloud computing environments.

Abstract: Provided are a database processing method and apparatus, and a computer readable storage medium. The database processing method comprises: after a lock wait is generated, writing lock wait related information into a lock wait log.

Abstract: The invention discloses a method, a system, a device, and a medium for detecting a battery state of health. The method includes extracting a target curve segment from a first charging characteristic curve of a battery under test; and determining, according to a corresponding relation between characteristic parameters of the target curve segment and the battery state of health, the battery state of health matching the characteristic parameters of the target curve segment, and determining the battery state of health as the battery state of health of the battery under test. By utilizing said corresponding relation as the calculation basis, the invention improves the reliability and accuracy of the detection of battery state of health detection. The invention also tracks instances of abusive conditions that accelerate battery aging, assessing whether such conditions accelerate battery degradation and issuing warnings accordingly.

Abstract: The invention discloses a method, a system, an electronic device, and a storage medium for determining performance of a power battery. The method includes the following steps: acquiring historical data of the power battery in at least two charging processes; determining, according to historical data in one charging process, a dQ/dV curve and a direct current internal resistance corresponding to said charging process; calculating a relative change rate of internal resistance capacity in any two charging processes; and determining the performance of the power battery according to the relative change rate of internal resistance capacity and a relative change rate of internal resistance capacity range corresponding to fault type. The invention can effectively determine whether the performance of the power battery is abnormal by combining, in the two charging processes, the target peak value of a dQ/dV curve of the power battery and the change in direct current internal resistance.

Abstract: The disclosure provides a nanolaser based on a depth-subwavelength graphene-dielectric hyperbolic dispersive cavity, comprising a pumping light source and the depth-subwavelength graphene-dielectric hyperbolic dispersive cavity; wherein the depth-subwavelength graphene-dielectric hyperbolic dispersive cavity is a spherical or hemispherical hyperbolic dispersive microcavity formed by alternately wrapping a dielectric core with graphene layers and dielectric layers.

Abstract: The disclosure provides a nanolaser based on a depth-subwavelength graphene-dielectric hyperbolic dispersive cavity, comprising a pumping light source and the depth-subwavelength graphene-dielectric hyperbolic dispersive cavity; wherein the depth-subwavelength graphene-dielectric hyperbolic dispersive cavity is a spherical or hemispherical hyperbolic dispersive microcavity formed by alternately wrapping a dielectric core with graphene layers and dielectric layers.

Abstract: According to one embodiment, an apparatus for training a neural network acoustic model includes a calculating unit, a clustering unit, and a sharing unit. The calculating unit calculates, based on training data including a training speech and a labeled phoneme state, scores of phoneme states different from the labeled phoneme state. The clustering unit clusters a phoneme state whose score is larger than a predetermined threshold and the labeled phoneme state. The sharing unit shares probability of the labeled phoneme state by the clustered phoneme states. The training unit trains the neural network acoustic model based on the training speech and the clustered phoneme states.

Abstract: According to one embodiment, an apparatus trains a neural network language model. The apparatus includes a calculating unit and a training unit. The calculating unit calculates probabilities of n-gram entries based on a training corpus. The training unit trains the neural network language model based on the n-gram entries and the probabilities of the n-gram entries.

Abstract: According to one embodiment, an apparatus trains a neural network auxiliary model used to calculate a normalization factor of a neural network language model. The apparatus includes a calculating unit and a training unit. The calculating unit calculates a vector of at least one hidden layer and a normalization factor by using the neural network language model and a training corpus. The training unit trains the neural network auxiliary model by using the vector of the at least one hidden layer and the normalization factor as an input and an output respectively.

Abstract: According to one embodiment, an apparatus for training a neural network acoustic model includes a calculating unit, a clustering unit, and a sharing unit. The calculating unit calculates, based on training data including a training speech and a labeled phoneme state, scores of phoneme states different from the labeled phoneme state. The clustering unit clusters a phoneme state whose score is larger than a predetermined threshold and the labeled phoneme state. he sharing unit shares probability of the labeled phoneme state by the clustered phoneme states. The training unit trains the neural network acoustic model based on the training speech and the clustered phoneme states.

Abstract: According to one embodiment, an apparatus for optimizing a speech recognition result comprising: a receiving unit configured to receive a speech recognition result; a calculating unit configured to calculate a pronunciation similarity between a segment of the speech recognition result and a key word in a key word list; and a replacing unit configured to replace the segment with the key word in a case that the pronunciation similarity is higher than a first threshold.

Abstract: According to one embodiment, an apparatus for improving a neural network language model of a speech recognition system includes a word classifying unit, a language model training unit and a vector incorporating unit. The word classifying unit classifies words in a lexicon of the speech recognition system. The language model training unit trains a class-based language model based on the classified result. The vector incorporating unit incorporates an output vector of the class-based language model into a position index vector of the neural network language model and use the incorporated vector as an input vector of the neural network language model.

Abstract: According to one embodiment, an apparatus for improving a language model of a speech recognition system includes an extracting unit, a classifying unit, and a setting unit. The extracting unit extracts user words from a user document provided by a user. The classifying unit classifies the user words based on a system lexicon of the speech recognition system. The setting unit sets weighting factor of a probability of the language model for at least one of the user words based on the classified result.

Abstract: According to one embodiment, an apparatus for optimizing a speech recognition result comprising: a receiving unit configured to receive a speech recognition result; a calculating unit configured to calculate a pronunciation similarity between a segment of the speech recognition result and a key word in a key word list; and a replacing unit configured to replace the segment with the key word in a case that the pronunciation similarity is higher than a first threshold.

Abstract: According to one embodiment, an apparatus for applying pitch features in automatic speech recognition is provided. The apparatus includes a distribution evaluation module, normalization module, and random value adjusting module. The distribution evaluation module evaluates the global distribution of pitch features of voiced frames in speech signals, and the global distribution of random values for unvoiced frames in speech signals. The normalization module normalizes the global distribution of random values for unvoiced frames based on the global distribution of pitch features of voiced frames. The random value adjusting module adjusts random values for unvoiced frames based on the normalized global distribution, so that the adjusted random values can be assigned to unvoiced frames in speech signals as pitch features of the unvoiced frames.

Abstract: According to one embodiment, an apparatus for applying pitch features in automatic speech recognition is provided. The apparatus includes a distribution evaluation module, normalization module, and random value adjusting module. The distribution evaluation module evaluates the global distribution of pitch features of voiced frames in speech signals, and the global distribution of random values for unvoiced frames in speech signals. The normalization module normalizes the global distribution of random values for unvoiced frames based on the global distribution of pitch features of voiced frames. The random value adjusting module adjusts random values for unvoiced frames based on the normalized global distribution, so that the adjusted random values can be assigned to unvoiced frames in speech signals as pitch features of the unvoiced frames.

Abstract: A flat type heat pipe device includes a packaging unit and a bonding member. The packaging unit further includes a first shell member and a second shell member. The first shell member has a work zone, a first joining part surrounding the work zone and an upright stop part disposed between the work zone and the joining part. The second shell member provides a shape corresponding to the first shell member to cover the first shell member and has a shell lid part spacing apart from the work zone and a second joining part disposed on the first joining part. The bonding member is disposed between the first joining part and the second joining part to adhere the first joining part to the second joining part. When the first shell member is pressingly fit with second shell member, the stop part is capable of preventing the bonding member from entering the packaging unit.

Abstract: The present invention provides a method and apparatus for enrollment and verification of speaker authentication. The method for enrollment of speaker authentication, comprising: extracting an acoustic feature vector sequence from an enrollment utterance of a speaker; and generating a speaker template using the acoustic feature vector sequence; wherein said step of extracting an acoustic feature vector sequence comprises: generating a filter-bank for the enrollment utterance of the speaker for filtering locations and energies of formants in the spectrum of the enrollment utterance based on the enrollment utterance; filtering the spectrum of the enrollment utterance by the generated filter-bank; and generating the acoustic feature vector sequence from the filtered enrollment utterance.

Abstract: A manufacturing system for processing a container body into a heat dissipating device includes: a support for supporting the container body thereon; an elastically deformable member covering a periphery of an opening in an upper wall of the container body and defining a cavity in fluid communication with interior of the container body through the opening; a vacuuming device connected to the elastically deformable member for vacuuming the inner space; a working fluid-loading device connected to the elastically deformable member for filling a predetermined amount of the working fluid into the container body; a depressing device including opposite upper and lower pressing members; and a driving mechanism for driving movement of at least one of the upper and lower pressing members.