Abstract: Described are a system, method, and computer program product for state compression in stateful machine learning models. The method includes receiving a transaction authorization request for a transaction and loading at least one encoded state of a recurrent neural network (RNN) model from a memory. The method further includes decoding the at least one encoded state by passing each encoded state through a decoder network to provide at least one decoded state. The method further includes generating at least one updated state and an output for the transaction by inputting at least a portion of the transaction authorization request and the at least one decoded state into the RNN model. The method further includes encoding the at least one updated state by passing each updated state through an encoder network to provide at least one encoded updated state, and storing the at least one encoded updated state in the memory.

Abstract: A parity checking method and apparatus for a qubit, a superconducting quantum chip, an electronic device, and a storage medium are provided. The method includes: configuring a measurement system for a qubit excited state measurement environment, the measurement system including: a first data qubit, a second data qubit, and an auxiliary qubit; determining a first operational frequency parameter of the first data qubit; determining a second operational frequency parameter of the second data qubit; determining a third operational frequency parameter of the auxiliary qubit; determining a logic gate matching the qubit excited state measurement environment based on the first operational frequency parameter, the second operational frequency parameter, and the third operational frequency parameter; and checking parity of a qubit in the qubit excited state measurement environment according to the logic gate.

Abstract: Disclosed is an electrode assembly, a battery, and a battery pack and a vehicle including the same. In the electrode assembly, a first electrode, a second electrode, and a separator interposed therebetween are wound based on a winding axis to define a core and an outer circumference. The first electrode includes a first active material portion coated with an active material layer and a first uncoated portion not coated with an active material layer along a winding direction. At least a part of the first uncoated portion is defined as an electrode tab by itself. The first uncoated portion includes a first portion adjacent to the core of the electrode assembly, a second portion adjacent to the outer circumference of the electrode assembly, and a third portion interposed between the first portion and the second portion. The first portion or the second portion has a smaller height than the third portion in the winding axis direction.

Abstract: A micro inverter having a plurality of independent inputs and a photovoltaic system are provided. The micro inverter includes multiple isolated DC-DC converters and a DC-AC converter. Each isolated DC-DC converter of the isolated DC-DC converters includes an inverter H-bridge, a transformer and a voltage-multiplying rectifier. An input terminal of the inverter H-bridges is configured to connect to a direct-current power supply. A secondary winding of the transformer is connected to an input terminal of the voltage-multiplying rectifier. An output terminal of the voltage-multiplying rectifier is connected to an input terminal of the DC-AC converter. A leakage inductor or an external inductor of the transformer forms series resonance along with a capacitor in the voltage-multiplying rectifier.

Abstract: A light-emitting element includes a pair of electrodes, a first light-emitting unit, a second light-emitting unit, and a charge generation layer. The first light-emitting unit, between the pair of electrodes, and the first light-emitting unit, includes a first light-emitting layer. The second light-emitting unit, between the pair of electrodes, includes a second light-emitting layer. A first luminescent layer includes a first main body material, a second main body material, a first guest material, and a first auxiliary material, and the first main body material forms a first excimer complex with the second main body material. A first excited triplet state energy level of the first auxiliary material is lower than a first excited triplet state energy level of the first excimer complex, and the first excited triplet state energy level of the first auxiliary material is higher than that of the first guest material.

Abstract: Disclosed is an electrode assembly, a battery, and a battery pack and a vehicle including the same. In the electrode assembly, a first electrode, a second electrode, and a separator interposed therebetween are wound based on an axis to define a core and an outer circumference. The first electrode includes an uncoated portion at a long side end thereof and exposed out of the separator along a winding axis direction of the electrode assembly. A part of the uncoated portion is bent in a radial direction of the electrode assembly to form a bending surface region that includes overlapping layers of the uncoated portion, and in a partial region of the bending surface region, the number of stacked layers of the uncoated portion is 10 or more in the winding axis direction of the electrode assembly.

Abstract: Provided is a system that includes at least one processor programmed or configured to receive an XML data file, wherein the XML data file includes data associated with one or more input parameters of a machine learning model, generate a code generation template based on the data associated with one or more input parameters of the machine learning model included in the XML file, where the code generation template includes one or more keys associated with one or more parameters of a transaction aggregate for an account of a user, and generate a file of executable code based on the code generation template, wherein the file of executable code includes instructions that, when executed by at least one processor, causes at least one processor to retrieve transaction aggregate data associated with the transaction aggregate for the account of the user. A method and computer program product are also provided.

Abstract: A cutting fluid digital monitoring and management system and method are provided, applicable to a computer numerical control (CNC) machining device. The CNC machining device has a cutting fluid tank configured to accommodate a cutting fluid. The cutting fluid digital monitoring and management system includes: a detection tank, configured to extract a cutting fluid from the cutting fluid tank through a motor and an electrically controlled water valve; a concentration sensing module, a pH sensing module, a water hardness sensing module, and a temperature sensing module, respectively configured to obtain a concentration, a pH value, a hardness, and a temperature of the cutting fluid; a processing module, configured to generate a monitoring integration value, compare the monitoring integration value with a standard model, and generate an adjustment signal; and an adjustment module, configured to actively adjust a variable parameter of the cutting fluid according to the adjustment signal.

Abstract: The present disclosure provides a method for producing a composite crystal, the method is performed in a multi-chamber growth device, and the multi-chamber growth device includes a plurality of chambers. The method includes conveying and processing at least one substrate between a plurality of chambers and obtaining at least one composite crystal by growing a target crystal through vapor deposition in one of the plurality of chambers, the at least one composite crystal including the at least one substrate and the target crystal.

Abstract: Provided is a system for testing a machine learning (ML) model based on simulations in an offline environment that includes at least one processor programmed or configured to receive historical transaction data, generate online simulation data, wherein generating the online simulation data includes modifying the historical timestamp of each data record to provide online simulation data. The processor is further programmed or configured to determine a timeline for a plurality of data insertion actions and a plurality of data request actions based on the online simulation data, perform a simulation of online activities involving a stateful ML model using the timeline for the plurality of data insertion actions and the plurality of data request actions, and validate the stateful ML model based on the simulation of online activities. Methods and computer program products are also provided.

Abstract: A single-stage multi-path direct current access converter and a control method thereof are provided. The single-stage multi-path direct current access converter includes an AC-side conversion circuit; at least two DC-side conversion circuits; and transformers corresponding to the at least two DC-side conversion circuits. AC sides of the at least two DC-side conversion circuits are respectively connected to primary windings of the corresponding transformers; secondary windings of the transformers are connected in parallel to a first side of the AC-side conversion circuit; each of the at least two DC-side conversion circuits is configured to invert DC power received by the DC-side conversion circuit, or to rectify AC power received by the DC-side conversion circuit; and the AC-side conversion circuit is configured to perform AC frequency conversion.

Abstract: This document describes techniques and systems of multiple-target, simultaneous beamforming for four-dimensional (4D) radar systems for efficient angle estimation in two dimensions with a high dynamic range. For example, a processor can use electromagnetic (EM) energy received by a two-dimensional (2D) array to determine first angles in a first dimension associated with one or more objects. The processor can then determine a subspace projection matrix using the first angles without an estimate of the power of noise or interference signals in the received EM energy. Using the subspace projection matrix, the processor can determine an interference-orthogonal subspace projection-based beamformer. With the interference-orthogonal subspace projection-based beamformer, the processor can determine the desired signal output from an adaptive beamformer for the EM energy and second angles corresponding to respective first angles for the objects.

Abstract: An electrode assembly, a battery, a battery pack and a vehicle including the same are provided. In the electrode assembly, the uncoated portion of an electrode includes a segment region divided into a plurality of segments, and the segment region includes a plurality of segment groups separated by a group separation pitch along a winding direction. One end of the electrode assembly includes a plurality of segment alignments. In winding turns corresponding to the plurality of segment alignments, group separation pitches of segment groups disposed in a same winding turn are substantially identical, and separation pitches of the segment groups is greater in a winding turn of a region adjacent to the outer circumference of the electrode assembly than in a winding turn of a region adjacent to the core of the electrode assembly.

Abstract: Described are a method, system, and computer program product for operating dynamic shadow testing environments for machine-learning models. The method includes generating a shadow testing environment operating at least two transaction services. The method also includes receiving a plurality of transaction authorization requests. The method further includes determining a first percentage associated with a first testing policy of the first transaction service and a second percentage associated with a second testing policy of the second transaction service. The method further includes replicating in the shadow testing environment, in real-time with processing the payment transactions, a first portion of the plurality of transaction authorization requests and a second portion of the plurality of transaction authorization requests.

Abstract: The present invention discloses a Fe—Al-based metal porous membrane and a preparation method thereof, which relate to the technical field of industrial gas-solid and liquid-solid separation and purification, and mainly address problems in the prior art, such as cracking-prone and peeling of a membrane layer of an existing Fe—Al-based metal porous membrane during its preparation and use. The preparation method of the present invention comprises the steps of: adding a Fe—Al-based metal powder and a metal fiber powder into an organic-additive-added water-based solvent, and mixing them into a slurry; casting the slurry, through a casting machine, to form a membrane green body on a metal substrate layer, and letting it dry; and placing the dried membrane green body in a sintering furnace, to remove organic substances and perform high-temperature sintering and predetermined-temperature reaction synthesis.

Abstract: Systems and methods of reconfiguring machine learning models are disclosed. A method includes receiving, by a server computer, external data and determining, by the server computer, a machine learning model from a plurality of machine learning models, based on the external data. The plurality of machine learning models are in standby mode. The server computer configures an AI engine with the machine learning model. The method also includes receiving, by the server computer, a prediction request from a client computer, processing the prediction request with the AI engine to form a prediction response, and sending the prediction response to the client computer.

Abstract: A booting method is provided, applied to a computer system. The computer system includes a transmission interface, a power key, and a trigger element. The transmission interface includes a transmission specification and is electrically connected to a graphics card, and the power key is used for driving the computer system to perform a booting procedure. The booting method includes: detecting, in the booting procedure, whether the trigger element is triggered or not; and lowering the transmission specification and restarting the computer system when the trigger element is triggered. A computer system adopting the booting method is further provided.

Abstract: A plurality of wireless charging systems may be employed within a network at a venue or other physical area to precisely locate a battery-operated node of the network. The location of the node may then be used to manage a transaction between that node and another node within the network when the transaction is associated with that precise location.

Abstract: Provided is a system for generating an inference based on real-time selection of a machine learning model using a machine learning model framework that includes at least one processor programmed or configured to receive a request for inference, wherein the request includes a payload, select a machine learning model of a plurality of machine learning models based on the request for inference, determine an aggregation of data based on the machine learning model and the payload of the request, transform the aggregation of data into inference data, wherein the inference data has a configuration that is capable of being processed by the machine learning model, and generate an inference based on the inference data using the machine learning model. Methods and computer program products are also provided.

Abstract: A method, system, and computer program product for dynamically scheduling machine learning inference jobs receive or determine a plurality of performance profiles associated with a plurality of system resources, wherein each performance profile is associated with a machine learning model; receive a request for system resources for an inference job associated with the machine learning model; determine a system resource of the plurality of system resources for processing the inference job associated with the machine learning model based on the plurality of performance profiles and a quality of service requirement associated with the inference job; assign the system resource to the inference job for processing the inference job; receive result data associated with processing of the inference job with the system resource; and update based on the result data, a performance profile of the plurality of the performance profiles associated with the system resource and the machine learning model.