Abstract: A method of cleaning a bottom plate, including: providing an adjacent bottom plate with at least one soldering lug, filling a liquid material between the adjacent bottom plate and the soldering lug to cover the substance to be cleaned, and placing the adjacent bottom plate in a chamber, controlling a temperature of the chamber to 25-200° C., generating intermittent pressure increasing and reducing and/or intermittent vacuum pumping for a gas in the chamber using a pressure increasing and reducing device and/or a vacuum generator, causing a fluctuation change of the liquid material using a fluctuation change of the gas, rubbing and scrubbing the liquid material by the fluctuation using the fluctuation change of the gas, and taking the substance to be cleaned attached to the adjacent bottom plate away from the adjacent bottom plate.

Abstract: A method of cleaning a bottom plate, including: providing an adjacent bottom plate with at least one soldering lug, filling a liquid material between the adjacent bottom plate and the soldering lug to cover the substance to be cleaned, and placing the adjacent bottom plate in a chamber, controlling a temperature of the chamber to 25-200° C., generating oscillating pressure increasing and reducing and/or oscillating vacuum pumping for a gas in the chamber using a pressure increasing and reducing device and/or a vacuum generator, causing a variation of the liquid material using differential pressure variation of the gas, rubbing and scrubbing the liquid material by the differential pressure variation using the differential pressure variation of the gas, and taking the substance to be cleaned attached to the adjacent bottom plate away from the adjacent bottom plate.

Abstract: Disclosed are methods, systems, apparatus, and computer programs for self-learning geofences is disclosed. In one aspect, a method involves gathering a plurality of data points associated with one or more Citizens Broadband Radio Service (CBRS) deployers; determining respective identifiers of the one or more CBRS deployers associated with the plurality of data points; clustering, based on the respective identifiers of the one or more CBRS deployers, the plurality of data points into one or more clusters, where each cluster is associated with one of the one or more CBRS deployers, and where each cluster is associated with a geofence of a network of the one or more CBRS deployers; identifying an opportunity for uploading the one or more clusters to a central server; and uploading the one or more clusters to the central server during the identified opportunity.

Abstract: A performance match method of memory, a memory storage device and a memory control circuit unit are disclosed. The method includes: receiving a performance match command from a host system; in response to the performance match command, adjusting an operation setting of a memory storage device to match a performance of the memory storage device with a performance requirement of the host system; and interacting with the host system based on the adjusted operation setting.

Abstract: A mapping table updating method, a memory storage device and a memory control circuit unit are disclosed. The method includes: receiving, a plurality of operation commands from a host system; performing a first table updating operation according to a first operation command and a third operation command among the operation commands to read and update a first sub-mapping table and a third sub-mapping table from a rewritable non-volatile memory module; and after the first table updating operation is finished, performing a second table updating operation according to a second operation command among the operation commands to read and update a second sub-mapping table from the rewritable non-volatile memory module.

Abstract: A performance match method of memory, a memory storage device and a memory control circuit unit are disclosed. The method includes: receiving a performance match command from a host system; in response to the performance match command, adjusting an operation setting of a memory storage device to match a performance of the memory storage device with a performance requirement of the host system; and interacting with the host system based on the adjusted operation setting.

Abstract: A mapping table updating method, a memory storage device and a memory control circuit unit are disclosed. The method includes: receiving, a plurality of operation commands from a host system; performing a first table updating operation according to a first operation command and a third operation command among the operation commands to read and update a first sub-mapping table and a third sub-mapping table from a rewritable non-volatile memory module; and after the first table updating operation is finished, performing a second table updating operation according to a second operation command among the operation commands to read and update a second sub-mapping table from the rewritable non-volatile memory module.

Abstract: A feedback control circuit of a pulse-frequency modulation (PFM) converter includes a multiplexer circuit and a detection circuit. The multiplexer circuit is arranged to receive a plurality of candidate peak current values, and output one of the plurality of candidate peak current values as a target peak current value according to a selection control signal, wherein a peak current value of an inductor current pulse of the PFM converter is subject to the target peak current value. The detection circuit is arranged to adaptively adjust the selection control signal according to a pulse interval between two successive inductor current pulses of the PFM converter.

Abstract: A mosquito repelling device is disclosed. The mosquito repelling device comprises: a microphone, configured to receive surrounding sounds; a power supply, configured to receive power; a first output device, configured to repel mosquitoes; and a processor, configured to process the received surrounding sounds from the microphone, determine whether there are mosquitoes present, and instruct the output device to repel mosquitoes if the processor determines there are mosquitoes present.

Abstract: A wearable electromyography device includes a garment, a plurality of fabric electrodes, and an insulating film. The garment has a plurality of anchor structures disposed on a first surface of the garment and a plurality of holes penetrating the garment. The fabric electrodes are disposed on the first surface of the garment. The insulating film is disposed on the first surface of the garment and seals peripherals of the fabric electrodes. A segment of the garment without being covered by the insulating film has a first elastic extension rate, a segment of the garment being covered by the insulating film has a second elastic extension rate, and the first elastic extension rate is greater than the second elastic extension rate.

Abstract: Disclosed are methods, systems, apparatus, and computer programs for self-learning geofences is disclosed. In one aspect, a method involves gathering a plurality of data points associated with one or more Citizens Broadband Radio Service (CBRS) deployers; determining respective identifiers of the one or more CBRS deployers associated with the plurality of data points; clustering, based on the respective identifiers of the one or more CBRS deployers, the plurality of data points into one or more clusters, where each cluster is associated with one of the one or more CBRS deployers, and where each cluster is associated with a geofence of a network of the one or more CBRS deployers; identifying an opportunity for uploading the one or more clusters to a central server; and uploading the one or more clusters to the central server during the identified opportunity.

Abstract: Disclosed are methods, systems, apparatus, and computer programs for self-learning geofences is disclosed. In one aspect, a method involves gathering a plurality of data points associated with one or more Citizens Broadband Radio Service (CBRS) deployers; determining respective identifiers of the one or more CBRS deployers associated with the plurality of data points; clustering, based on the respective identifiers of the one or more CBRS deployers, the plurality of data points into one or more clusters, where each cluster is associated with one of the one or more CBRS deployers, and where each cluster is associated with a geofence of a network of the one or more CBRS deployers; identifying an opportunity for uploading the one or more clusters to a central server; and uploading the one or more clusters to the central server during the identified opportunity.

Abstract: Electronic design automation (EDA) of the present disclosure logically places components of the electronic circuitry onto an electronic design real estate to determine an architectural design placement for the electronic circuitry. The EDA evaluates a metaheuristic algorithm starting with an initial placement of components of the electronic circuitry onto the electronic design real estate to provide multiple possible placements for placing these components of the electronic circuitry onto the electronic design real estate. The EDA utilizes the multiple possible placements of the metaheuristic algorithm to train one or more probabilistic functions of a model-based reinforcement learning (RL) algorithm. The EDA evaluates the model-based RL algorithm utilizing the one or more probabilistic functions to determine the architectural design placement.

Abstract: Various techniques are provided to generate a list of node names that cause a node in a machine vision camera to be locked. In one example, a method includes receiving a file identifying a plurality of nodes corresponding to associated features of a device, wherein each of the nodes has an associated plurality of settings and each of the nodes is configured to be in either an unlocked state to permit adjustment of its associated settings by a user or a locked state to prevent adjustment of its associated settings by the user; receiving a request by the user that identifies a first one of the nodes in the locked state; parsing at least a portion of the file to identify a second one of the nodes having associated settings on which the locked state of the first node is contingent; and presenting the associated settings of the second node to the user. Additional methods and systems are also provided.

Abstract: A prediction model training apparatus and method are provided. The apparatus classifies a plurality of data into a normal situation data set and a non-normal situation data set, wherein each of the data comprises a plurality of first features. The apparatus trains a first prediction model based on the normal situation data set and a plurality of third features among the first features. The apparatus inputs the non-normal situation data set to the first prediction model to generate a first stage prediction value. The apparatus adds the first stage prediction value to the non-normal situation data set. The apparatus trains a second prediction model based on the non-normal situation data set and the first features.

Abstract: Disclosed are methods, systems, apparatus, and computer programs for self-learning geofences is disclosed. In one aspect, a method involves gathering a plurality of data points associated with one or more Citizens Broadband Radio Service (CBRS) deployers; determining respective identifiers of the one or more CBRS deployers associated with the plurality of data points; clustering, based on the respective identifiers of the one or more CBRS deployers, the plurality of data points into one or more clusters, where each cluster is associated with one of the one or more CBRS deployers, and where each cluster is associated with a geofence of a network of the one or more CBRS deployers; identifying an opportunity for uploading the one or more clusters to a central server; and uploading the one or more clusters to the central server during the identified opportunity.

Abstract: Apparatuses, systems, and methods for network interface management for Citizens Broadband Radio Service (CBRS) deployments, e.g., in LTE and/or 5G NR systems and beyond, including methods for coarse selection of CBRS networks and fine selection of CBRS networks as well as support for multiple CBRS networks. Coarse selection of CBRS networks may include various triggers for automatic CBRS profile enabling and/or disabling, user management and overriding of system selections, tiered hierarchy for CBRS network enabling and/or disabling, as well as mechanisms to avoid ping-ponging between network selection. Fine selection of CBRS networks may include data slot switching between mobile network operators (MNOs, e.g., LTE/NR macro cells) and CBRS eSIM as well as prioritization of CBRS networks over Wi-Fi networks. Multiple CBRS networks support may include CBRS network identifier (NID) matching for unique identification as well as user-ranked CBRS priority.

Abstract: Abdomen scanning techniques are disclosed. The techniques include acquiring a current abdomen positioning image; inputting the current abdomen positioning image into a pre-trained liver outline acquisition model, and obtaining current liver outline information outputted by the liver outline acquisition model; the liver outline acquisition model being obtained by training, using a first quantity of historical abdomen positioning images as an input set, and using a first quantity of historical liver outline information respectively corresponding to the first quantity of historical abdomen positioning images as an output set; based on the current liver outline information, calculating an abdomen scanning range and a scanning center position, and applying the scanning range and scanning center position in a current scanning protocol; and using the scanning protocol to perform a magnetic resonance scan of an abdomen.

Abstract: A system performs the operations of a neural network agent and a circuit simulator for analog circuit sizing. The system receives an input indicating a specification of an analog circuit and design parameters. The system iteratively searches a design space until a circuit size is found to satisfy the specification and the design parameters. In each iteration, the neural network agent calculates measurement estimates for random sample generated in a trust region, which is a portion of the design space. Based on the measurement estimate, the system identifies a candidate size that optimizes a value metric. The circuit simulator receives the candidate size and generates a simulation measurement. The system calculates updates to weights of the neural network agent and the trust region for a next iteration based on, at least in part, the simulation measurement.