Abstract: A semiconductor structure and a method for forming same. The structure includes: a base substrate; a gate structure, located on the base substrate; a drift region, located in the base substrate on one side of the gate structure; a body region, located in the base substrate on the other side of the gate structure; a drain region, located in the drift region on one side of the gate structure; a source region, located in the body region on the other side of the gate structure; and a floating field plate, located on the drift region between the gate structure and the drain region, where the floating field plate has notches arranged at intervals along a width direction of the gate structure, and the floating field plate also has notches arranged at intervals along a length direction of the gate structure.

Abstract: Disclosed is a system for assessing quality of a singing voice singing a song. The system comprises memory and at least one processor. The memory stores instructions that, when executed by the at least one processor, cause the at least one processor to receive a plurality of inputs comprising a first input and one or more further inputs, each input comprising a recording of a singing voice singing the song, to determine, for the first input, one or more relative measures of quality of the singing voice by comparing the first input to each further input; and to assess quality of the singing voice of the first input based on the one or more relative measures. Also disclosed is a method implemented on such a system.

Abstract: Technologies for suppressing effects of crosstalk in a quantum circuit of a quantum computing system are disclosed. A pair of target qubits on which to perform a quantum gate operation is selected. The quantum gate operation is performed. A rotation is induced on the target qubits such that crosstalk between any of the target qubits and any of the neighboring qubits in the quantum circuit is canceled out.

Abstract: Disclosed is a resonant filter, which includes a housing including an input hole and an output hole, an input resonator including an input resonant body and an input port extending from the input resonant body and out of the housing through the input hole, and an output resonator including an output resonant body and an output port extending from the output resonant body and out of the housing through the output hole. The input resonator and the output resonator are fixed in the housing. The input resonator body and the output resonator body, which are sheets with a metal surface or metal sheets, respectively include a resonant rod with an upright segment, an extension segment extending from the upright segment and one end of which away from the extension segment is connected to the housing, and a first branch extending from the extension segment away from the upright segment.

Abstract: For online audio/video conferencing applications deployed in an open office environment, using shared conference devices, it can be advantageous to define an acoustic fence. A non-participant audio received from outside the acoustic fence can be considered noise and filtered out before transmission of an audio signal to a far end recipient. Three suppression stages are used to filter the non-participant audio. The first suppression stage uses beamformers for suppression. The second suppression stage is mask-based, and the third suppression stage is reference-based. The three suppression stages filter out non-participant audio signals, having a wide range of frequencies.

Abstract: Methods, systems, and computer-readable media for generating a statistically covaried machine learning model for performance measurement of service providers. The method receives a configuration file that includes one or more parameters associated with a plurality of individuals and parses it to generate and executing the database query on input data to generate sets of tabulated data of individuals of the plurality of individuals. The method next determines one or more measures of service providers listed in the configuration file using two or more tabulated data of individuals from the sets of tabulated data of individuals. The method finally generates a covaried machine learning model by training a machine learning model by statistically covarying measures and using them as training data.

Abstract: A system for fusion of Wi-Fi measurements from multiple frequency bands to monitor indoor and outdoor space is provided. The system includes a multi-band wireless network comprising a set of radio devices to provide coverage in an environment, wherein the set of radio devices are configured to establish wireless communication or sensing links over multi-band wireless channels, wherein the multi-band wireless channels use a first radio band at a millimeter wavelength and a second radio band at a centimeter wavelength. The system further includes a computing processor communicatively coupled to the set of radio devices and a data storage, wherein the data storage has data comprising a parameterized model, modules and executable programs.

Abstract: Provided are a coaxial filter and a communication radio frequency device. The communication radio frequency device includes the coaxial filter. The coaxial filter includes a housing having a resonant cavity, a cover plate, and a resonator. The cover plate corresponds to the resonant cavity and covers the housing. The resonator includes plurality of elastic pieces, a connection portion, and a body portion which are sequentially connected from one end to another end. The connection portion is connected to a bottom of the resonant cavity.

Abstract: The present disclosure provides a method and a system for training a neural network suitable for localization of a device within an environment based on signals received by the device. The method comprises training a bi-regressor neural network to identify locations from labeled data, wherein the bi-regressor neural network includes a feature extractor and a bi-regressor including two regressors; training parameters of the bi-regressor using the labeled data and unlabeled data, such that each of the two regressors identifies the same labeled locations while processing the labeled data and identifies different locations while processing the unlabeled data; and training parameters of the feature extractor using an adversarial discriminator to extract domain invariant features from the unlabeled data with statistical properties of the labeled data according to the adversarial discriminator such that each of the two regressors identifies the same locations while processing the domain invariant features.

Abstract: A cavity filter includes a housing, an input resonator and an output resonator. The input resonator includes a first sheet-like resonant body, an input end extending outward from one side of the first sheet-like resonance body and a first branch extending outward from the first sheet-like resonance body and/or the input end, and the input end extends out of the housing through the input through hole. The output resonator includes a second sheet-like resonant body, an output end extending outward from one side of the second sheet-like resonance body, and a second branch extending outward from the second sheet-like resonance body and/or the output end, and the output end extends out of the housing through the output through hole. The lengths of the first branch and the second branch are both a quarter wavelength of a resonant frequency of the cavity filter.

Abstract: An orbital sander (10) comprises a housing (14) and a drive unit (50) in the housing (14). The drive unit (50) includes an electric motor (58) and a drive shaft (68). The electric motor (58) has a motor output shaft defining a rotational axis (62). The drive shaft (68) is coupled for co-rotation with the motor output shaft about the rotational axis (62). The drive shaft (68) has an eccentric portion (70) configured to orbit about the rotational axis (62). A sanding pad (100) is coupled to the eccentric portion (70). A handle (16) extends from the housing (14) at an oblique angle greater than 90 degrees relative to the rotational axis (62). A battery pack (26) is coupled to the handle (16) for providing power to the electric motor (58). The orbital sander (10) is convenient for users to grasp.

Abstract: A system and method for automated construction of a stochastic deep neural network (DNN) architecture is provided. The framework of invention automatically searches for most relevant stochastic modes underlaying datasets for variational Bayesian inference. The invention provides a way to use heterogenous, irregular, and mismatched beliefs in stochastic sampling for intermediate representation in DNNs with a capability of an automatically tuning mechanism of posterior, prior, and likelihood models to enable accurate generative models and uncertainty models for machine learning tasks. The system further allows adjustable discrepancy measure to regularize intermediate representation by variants of divergence metrics including Renyi's alpha, beta, and gamma divergences. The invention enables diverse mixture combinations of stochastic models for misspecified and unspecified probabilistic relations in an automatic fashion.

Abstract: A system and a computer-implemented method using physics-informed neural network (PINN) are provided for data communications. At a transmitter, the method is configured to acquire source data to be transmitted, encode the source data to codewords based on forward error correction (FEC) codes, map the codewords to amplitude symbols, modify the mapped amplitude symbols to pre-equalized symbols including pre-distort channel impairments symbols based on a predetermined physical model, and transmit digital data of the pre-equalized symbols over a channel as channel data.

Abstract: An anomaly detector for detecting anomaly in input data comprises an auto-encoder trained to encode the input data and decode the encoded input data to reconstruct the input data. Further, the anomaly detector comprises a classifier trained to determine a reconstruction loss indicative of a difference between the accepted input data and the reconstructed input data, where the reconstruction loss includes a weighted combination of a plurality of loss functions evaluating reconstruction losses of a plurality of parts of the reconstructed input data, different types of loss functions, or both. The classifier is further configured to detect an anomaly in the reconstructed input data when the reconstruction loss is above a threshold.

Abstract: One or more computer processors encode a plurality of time sequenced global position system (GPS) datapoints onto a grided dimensional area; determine a general trajectory between each time sequenced GPS datapoint in the plurality of encoded time sequenced GPS datapoints and a subsequent encoded time sequenced GPS datapoint; cluster the encoded time sequenced GPS datapoints based on a respective determined trajectory with a plurality of encoded historical GPS datapoints; calculate an azimuth for each encoded time sequenced GPS datapoint in the plurality of time sequenced GPS datapoints utilizing a plurality of adjacent historical GPS datapoints contained within a respective cluster; generate a plurality of interpolated GPS datapoints utilizing calculated azimuths, determined general trajectories, and historical GPS datapoints; and aggregate the generated interpolated GPS datapoints with the plurality of time sequenced GPS datapoints into an interpolated route, wherein each GPS datapoint in the interpolated ro

Abstract: A compatible method for a self-service printing background includes: background configuration interface is presented in response to acquired background configuration event, herein background configuration interface is at least configured to configure interaction parameters between biometric feature recognition device and background of biometric feature recognition device and between biometric feature recognition device and printing device; user configuration event is received on background configuration interface; background configuration information of printing device and address of background of biometric feature recognition device are acquired based on user configuration event, herein background configuration information of printing device includes printing parameters of printing device and address of printing device; and configurations between biometric feature recognition device and background of the biometric feature recognition device and between biometric feature recognition device and printing device

Abstract: A reconfigurable device is provided for splitting optical beams. The device includes an input port configured to receive an input beam including at least two primary wavelengths, a tunable splitter configured to separate the input beam into at least two beams via at least two routes corresponding to the at least two primary wavelengths, wherein each of the at least two routes is configured to propagate one of the at least two primary wavelengths of the input beam, wherein the tunable splitter includes a bottom electrode, a substrate on the bottom electrode, core segments arranged on the substrate, a top layer, support segments to connect the substrate and the top layer, a top electrode on the top layer, a controllable refractive index layer arranged to fill gaps between the substrate, the support segments, and the top layer; and at least two output ports configured to transmit the at least two beams propagated via the at least two routes.

Abstract: Communication-capable devices such as commercial Wi-Fi devices can be used for integrated sensing and communications (ISAC) systems to jointly exchange data and monitor environment. Such devices typically require diverse signal processing such as machine learning inference that demands high-power operations for real-time sensing and computing. The present invention provides a way to realize energy-efficient computing by exploiting the capability of data communications to access distributed computing resources including classical computers and quantum computers over networks. The system and method are based on the realization that computationally intensive processing is offloaded to networked hybrid classical-quantum computing to build dynamic computing graphs. Some embodiments use automated classical-quantum machine learning whose circuits and hyperparameters are automatically adjusted via gradient or heuristic optimization for Wi-Fi indoor monitoring and human tracking.

Abstract: The present invention discloses an LED straight tube lamp with an end face switch for a tone adjustment and a power adjustment, which belongs to the technical field of LED lamps, comprising a lamp tube, wherein an inside of the lamp tube is provided with a light source board, one end of the lamp tube is provided with a first plug, another end of the lamp tube is provided with a second plug, the first plug is provided with a first driving board, the second plug is provided with a second driving board, both the first driving board and the second driving board are connected to the light source board, a switch is provided on the second driver board, an end face of the second plug is provided with an oblique groove, and an interior of the oblique groove is provided with a notch for extending a handle of the switch. In the present invention, the handle of the switch is arranged at the end face of the second plug, and an end of the handle of the switch is flush with the end face of the second plug.

Abstract: Disclosed are a metal aluminum nano-adjuvant, a vaccine composition and a preparation method therefor and a use thereof. The vaccine adjuvant comprises metal aluminum nanoparticles, and can be used as a candidate adjuvant for preventive vaccines and therapeutic vaccines for various diseases such as infections, autoimmune diseases and tumors. The combined use of the vaccine adjuvant provided by the present disclosure and antigen can effectively enhance the humoral immune response and the cellular immune response of the vaccine, and the enhancement effect is significantly better than that of the commercially available aluminum hydroxide adjuvant.