Abstract: An asset manager controls power distribution within an aggregated distributed energy resources system (“DERs system”) having a plurality of assets. The asset manager is configured to operate with a given asset. As such, the asset manager has 1) an interface to receive asset information relating to the given asset and to communicate with another asset manager in the DERs system, and 2) a function generator configured to produce a local cost function using data relating to the given asset only. The local cost function represents a portion of a system cost function for the DERs system. The asset manager also has 3) a controller configured to use the local cost function for the given asset to manage operation of the given asset in the DERs system. In addition, the controller also is configured to determine, using the local cost function, an operating point for the given asset.

Abstract: A method of treating a subject having been diagnosed as having cancer with an immunotherapy is described. The method comprises targeting one or more clonal neoantigens selected using a method comprising determining whether a tumour-specific mutation is likely to be clonal in a subject. The method comprises providing sequence data from one or more samples from the subject comprising tumour genetic material, the sequence data comprising for each of the one or more samples, and determining the likelihood that the tumour-specific mutation is clonal as a posterior probability depending on: a prior probability of the mutation being clonal, and the probabilities of observing the sequence data if the tumour-specific mutation is (i) clonal and (ii) non-clonal, in view of a tumour fraction for each of the one or more samples and one or more candidate joint genotypes.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to generate embeddings of inputs to the machine learning model, the machine learning model having an encoder that generates the embeddings from the inputs and a decoder that generates outputs from the generated embeddings, wherein the embedding is partitioned into a sequence of embedding partitions that each includes one or more dimensions of the embedding, the operations comprising: for a first embedding partition in the sequence of embedding partitions: performing initial training to train the encoder and a decoder replica corresponding to the first embedding partition; for each particular embedding partition that is after the first embedding partition in the sequence of embedding partitions: performing incremental training to train the encoder and a decoder replica corresponding to the particular partition.

Abstract: A method includes receiving an input text utterance to be synthesized into expressive speech having an intended prosody and a target voice and generating, using a first text-to-speech (TTS) model, an intermediate synthesized speech representation for the input text utterance. The intermediate synthesized speech representation possesses the intended prosody. The method also includes providing the intermediate synthesized speech representation to a second TTS model that includes an encoder portion and a decoder portion. The encoder portion is configured to encode the intermediate synthesized speech representation into an utterance embedding that specifies the intended prosody. The decoder portion is configured to process the input text utterance and the utterance embedding to generate an output audio signal of expressive speech that has the intended prosody specified by the utterance embedding and speaker characteristics of the target voice.

Abstract: A system and method for monitoring an elevator operating environment. The system for monitoring the elevator operating environment includes at least one local monitoring device, a cloud computing platform, and at least one alarm module associated with the local monitoring device, wherein, each of the local monitoring devices is arranged in an operating area and is configured to: determine heat index based on temperature data and humidity data of the operating area, and output a first warning message locally; and transmit the temperature data and humidity data to the cloud computing platform regularly or irregularly, the cloud computing platform is configured to send the temperature data and humidity data to the alarm module regularly or irregularly, and the alarm module is configured to generate a third warning message based on the temperature data and humidity data and present the third warning message.

Abstract: A method includes obtaining training data including a plurality of training audio signals and corresponding transcripts. Each training audio signal is spoken by a target speaker in a first accent/dialect. For each training audio signal of the training data, the method includes generating a training synthesized speech representation spoken by the target speaker in a second accent/dialect different than the first accent/dialect and training a text-to-speech (TTS) system based on the corresponding transcript and the training synthesized speech representation. The method also includes receiving an input text utterance to be synthesized into speech in the second accent/dialect. The method also includes obtaining conditioning inputs that include a speaker embedding and an accent/dialect identifier that identifies the second accent/dialect.

Abstract: A method (400) for representing an intended prosody in synthesized speech includes receiving a text utterance (310) having at least one word (240), and selecting an utterance embedding (204) for the text utterance. Each word in the text utterance has at least one syllable (230) and each syllable has at least one phoneme (220). The utterance embedding represents an intended prosody. For each syllable, using the selected utterance embedding, the method also includes: predicting a duration (238) of the syllable by decoding a prosodic syllable embedding (232, 234) for the syllable based on attention by an attention mechanism (340) to linguistic features (222) of each phoneme of the syllable and generating a plurality of fixed-length predicted frames (260) based on the predicted duration for the syllable.

Abstract: A method determines the topology of a DERs system having a plurality of assets, where at least one of the assets is a controllable asset. The method injects a power signal at a given frequency from a controllable asset into the DERs system. The voltage at each of the plurality of assets is measured, and the magnitude of perturbation of the voltage at the given frequency is determined for each of the plurality of assets. The method then constructs the topology of the DERs system as a function of the differences of the magnitude of perturbations of each of the plurality of assets.

Abstract: A method includes receiving an input text utterance to be synthesized into expressive speech having an intended prosody and a target voice and generating, using a first text-to-speech (TTS) model, an intermediate synthesized speech representation tor the input text utterance. The intermediate synthesized speech representation possesses the intended prosody. The method also includes providing the intermediate synthesized speech representation to a second TTS model that includes an encoder portion and a decoder portion. The encoder portion is configured to encode the intermediate synthesized speech representation into an utterance embedding that specifies the intended prosody. The decoder portion is configured to process the input text utterance and the utterance embedding to generate an output audio signal of expressive speech that has the intended prosody specified by the utterance embedding and speaker characteristics of the target voice.

Abstract: A method of treating a subject having been diagnosed as having cancer with an immunotherapy is described. The method comprises targeting one or more clonal neoantigens selected using a method comprising determining whether a tumour-specific mutation is likely to be clonal in a subject. The method comprises providing sequence data from one or more samples from the subject comprising tumour genetic material, the sequence data comprising for each of the one or more samples, and determining the likelihood that the tumour-specific mutation is clonal as a posterior probability depending on: a prior probability of the mutation being clonal, and the probabilities of observing the sequence data if the tumour-specific mutation is (i) clonal and (ii) non-clonal, in view of a tumour fraction for each of the one or more samples and one or more candidate joint genotypes.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to generate embeddings of inputs to the machine learning model, the machine learning model having an encoder that generates the embeddings from the inputs and a decoder that generates outputs from the generated embeddings, wherein the embedding is partitioned into a sequence of embedding partitions that each includes one or more dimensions of the embedding, the operations comprising: for a first embedding partition in the sequence of embedding partitions: performing initial training to train the encoder and a decoder replica corresponding to the first embedding partition; for each particular embedding partition that is after the first embedding partition in the sequence of embedding partitions: performing incremental training to train the encoder and a decoder replica corresponding to the particular partition.

Abstract: A method of treating a subject having been diagnosed as having cancer with an immunotherapy is described. The method comprises targeting one or more clonal neoantigens selected using a method comprising determining whether a tumour-specific mutation is likely to be clonal in a subject. The method comprises providing sequence data from one or more samples from the subject comprising tumour genetic material, the sequence data comprising for each of the one or more samples, and determining the likelihood that the tumour-specific mutation is clonal as a posterior probability depending on: a prior probability of the mutation being clonal, and the probabilities of observing the sequence data if the tumour-specific mutation is (i) clonal and (ii) non-clonal, in view of a tumour fraction for each of the one or more samples and one or more candidate joint genotypes.

Abstract: A method for performing glitch power analysis of a circuit, comprising receiving no-timing waveform simulation data for the circuit, the waveform simulation data including a first signal, and identifying a delayed stimulus injection point (DSIP) for the first signal. The method further comprises determining a total delay for the first signal and performing waveform replay simulation including injecting the first signal at the DSIP at a time based on the total delay for the first signal.

Abstract: A method determines the topology of a DERs system having a plurality of assets, where at least one of the assets is a controllable asset. The method injects a power signal at a given frequency from a controllable asset into the DERs system. The voltage at each of the plurality of assets is measured, and the magnitude of perturbation of the voltage at the given frequency is determined for each of the plurality of assets. The method then constructs the topology of the DERs system as a function of the differences of the magnitude of perturbations of each of the plurality of assets.

Abstract: The present disclosure relates to a low-light autofocus technique. One example embodiment includes a method. The method includes receiving an indication of a low-light condition for a camera system. The method also includes determining an extended exposure time for a low-light autofocus procedure of the camera system. Further, the method includes capturing, by the camera system, an extended frame for the low-light autofocus procedure. The extended frame is captured by die camera system using the determined extended exposure time. In addition, the method includes determining, based on the captured extended frame, an in-focus lens setting for a lens of the camera system.

Abstract: An HEMT includes a gallium nitride layer. An aluminum gallium nitride layer is disposed on the gallium nitride layer. A gate is disposed on the aluminum gallium nitride layer. The gate includes a P-type gallium nitride and a schottky contact layer. The P-type gallium nitride contacts the schottky contact layer, and a top surface of the P-type gallium nitride entirely overlaps a bottom surface of the schottky contact layer. A protective layer covers the aluminum gallium nitride layer and the gate. A source electrode is disposed at one side of the gate, penetrates the protective layer and contacts the aluminum gallium nitride layer. A drain electrode is disposed at another side of the gate, penetrates the protective layer and contacts the aluminum gallium nitride layer. A gate electrode is disposed directly on the gate, penetrates the protective layer and contacts the schottky contact layer.

Abstract: A method for representing an intended prosody in synthesized speech includes receiving a text utterance having at least one word, and selecting an utterance embedding for the text utterance. Each word in the text utterance has at least one syllable and each syllable has at least one phoneme. The utterance embedding represents an intended prosody. For each syllable, using the selected utterance embedding, the method also includes: predicting a duration of the syllable by encoding linguistic features of each phoneme of the syllable with a corresponding prosodic syllable embedding for the syllable; predicting a pitch contour of the syllable based on the predicted duration for the syllable; and generating a plurality of fixed-length predicted pitch frames based on the predicted duration for the syllable. Each fixed-length predicted pitch frame represents part of the predicted pitch contour of the syllable.

Abstract: A method for providing a frame-based mel spectral representation of speech includes receiving a text utterance having at least one word, and selecting a mel spectral embedding for the text utterance. Each word in the text utterance has at least one syllable and each syllable has at least one phoneme. For each phoneme, using the selected mel spectral embedding, the method also includes: predicting a duration of the corresponding phoneme by encoding linguistic features of the corresponding phoneme with a corresponding syllable embedding for the syllable that includes the corresponding phoneme; and generating a plurality of fixed-length predicted mel-frequency spectrogram frames based on the predicted duration for the corresponding phoneme. Each fixed-length predicted mel-frequency spectrogram frame representing mel-spectral information of the corresponding phoneme.

Abstract: A method for managing connections associated with multiple subscriber numbers is provided. The method includes the following steps: using a first subscriber number and a second subscriber number to establish two data connections with two mobile communication networks; receiving a QoS update notification from one of the wireless transceivers in response to the first data connection being used for data transfer of an application; and enabling the data transfer of the application to switch from the first data connection to the second data connection in response to the QoS update notification indicating that the QoS of the first data connection fails to support the application and the QoS of the second data connection is capable of supporting the application. Advantageously, the performance requirement of the application may be maintained after switching to the second data connection, thereby ensuring smooth operation of the application.