25 results about "Digital computer" patented technology

A method for solving an optimization problem inputted by a user may include: (a) using an interface of a digital computer to receive an indication of (i) said optimization problem, (ii) one or more optimization problem specifications of a plurality of optimization problem specifications, (iii) at least one generation method and at least one evaluation method, (iv) one or more algorithms of a plurality of algorithms, wherein said one or more algorithms is configured to solve said optimization problem subject to at least said one or more optimization problem specifications using said at least one generation method and said at least one evaluation method, and (v) one or more computational platforms of a plurality of computational platforms, wherein said one or more computational platforms is configured to execute said one or more algorithms; (b) using said one or more computational platforms to execute said one or more algorithms to yield a solution to said optimization problem; and (c) providing said solution to said optimization problem from said computational platform at said interface.

The invention relates to the technical field of digital computer combination processing, in particular to an edge computing node cooperative processing system based on load awareness, which comprises a task density construction module, a current sequence extraction module, a state transition identification module, a synchronous trigger generation module and a processing chain construction module. According to the method, task features are mapped to system load distribution in a task number construction and merging mode, dynamic features of task execution are extracted by combining a splicing and alignment mechanism of node current disturbance, and state transition boundaries are constructed according to current head and tail differences between tasks to identify key change points. The inter-node serial number consistency identification mechanism extracts synchronous trigger positions to ensure execution collaboration, an execution chain is constructed based on task sequence rearrangement and serial number binding, perception of task scheduling on node operation states and load changes is achieved, and the task identification precision, the execution time sequence management capability and the collaborative organization efficiency are improved.

Drone-Assisted Digital Computer Device for Structural Health Monitoring

A system and method for seasonal energy consumption determination using verified energy loads with the aid of a digital computer are provided. A digital computer is operated, including: obtaining energy loads for a building measured over a seasonal time period; obtaining outdoor temperatures for the building as measured over the seasonal time period; verifying stability of the energy loads, including: evaluating the energy loads over time; and identifying at least one of one or more discontinuities and one or more irregularities in the energy loads based on the evaluation. Operating the computer further includes: determining a baseload energy consumption using at least some of those of the energy loads; calculating seasonal fuel consumption rates and balance point temperatures; and disaggregating seasonal fuel consumption based on the baseload energy consumption, seasonal fuel consumption rates, balance point temperatures, and at least some of the outdoor temperatures into component loads of consumption.

The invention provides a WiFi network digital down-conversion system which comprises a multi-phase mixer and a resampling filter. The multi-phase mixer is used for converting a high-speed digital band-pass signal into a low-speed mode so as to realize digital down-conversion (DDC) on an FPGA (Field Programmable Gate Array) platform; and the resampling filter is used for reducing the sampling rate and removing unwanted frequency spectrum components to generate a complex baseband frequency spectrum. The multi-phase mixer PM of the present invention employs a parallel coordinate rotation digital computer (CORDIC) processor and a low pass filter array to reduce high speed data rates while minimizing resource utilization. The resampling filter comprises a cascade integral combination (CIC) filter and a multi-channel pulse finite impulse response (FIR) filter, optimal hardware cost is achieved, a floating point data type is converted into a fixed point data type, and resources are remarkably saved.

A system and method for determining a balance point of a building that has undergone or is about to undergo modifications (such as shell improvements) are provided. A balance point of the building before the modifications can be determined using empirical data. Total thermal conductivity of the building before and after the modifications is determined and compared. Indoor temperature of the building is obtained. The balance point temperature after the modifications can be determined using a result of the comparison, the temperature inside the building, and the pre-modification balance point temperature. Knowing post-modification balance point temperature allows power grid operators to take into account fuel consumption by that building when planning for power production and distribution. Knowing the post-improvement balance point temperature also provides owners of the building information on which they can base the decision whether to implement the improvements.

System and method for inferring photovoltaic (PV) system specifications are described. A consumer PV system's location and net load data recorded through net metering are retrieved. For each discrete period, a time of peak PV production and a magnitude of minimum net load for a representative day are found, and base loads are estimated. Plane-of-array irradiance (POAI) using clear sky global horizontal irradiance for azimuth and tilt combinations is produced. Azimuth, tilt, and system rating combinations based on the magnitude of minimum net load and the base load over each discrete period are created. A lowest error metric among the azimuth, tilt and system rating combinations is found, by finding the minimum of the combined residual errors in the time of peak PV production and the time of maximum POAI and residual errors in the magnitude of minimum net load plus the base load and magnitude of maximum POAI.

The invention relates to the technical field of medical monitoring equipment, in particular to a cardiac pacemaker pocket pressure intelligent remote monitoring device which comprises a fixing device, the fixing device is a treatment type pressurization vest, and the treatment type pressurization vest is made of medical hypoallergenic pinhole breathable diving materials and is integrally formed through a digital computer knitting technology; the treatment type pressurizing vest body is provided with a double-layer elastic breathable knitted net bag structure, the joints of the vest body are provided with adjustable three-point buckles made of medical-grade ABS materials, the inner-layer net bag is used for fixing the pressurizing device, and the edge of the inner-layer net bag is provided with an anti-skid elastic band. According to the heart pacemaker bag pressure intelligent remote monitoring device, a non-target area is prevented from being pressed by matching the shape of a medical high-strength TPU air bag with a skin projection area outside a pacemaker bag body, and air backflow and leakage can be effectively prevented by matching with a pressure one-way valve and a rotary buckle type IP67-level sealing pipeline which are arranged in a handheld inflation ball; and the set pressure is stably kept.

A system for increasing the speed and reducing the time to obtain a required amount of data, from a secondary storage device, for a digital computer, based upon measures to improve the time efficiency of I / O request processing by improving the timing and sequence of transfers to improve the efficiency of mass storage devices.

This invention relates to an unconditional data generation method and a hybrid computer system. In this hybrid computer system, a digital computer transforms the sampling problem of the unconditional data generation model (which can be mapped to an energy network type of optical quantum computer) into a problem of solving for the ground state of a quantum Hamiltonian. The optical quantum computer then solves for the quantum Hamiltonian to achieve rapid sampling. This invention solves for the low sampling efficiency of existing deep learning-based unconditional data generation models, thereby improving the sampling efficiency of unconditional data generation models.

A computer-implemented system for creation, matching, and trading of private-asset derivative instruments (synthetic or standard) for portfolio management and risk transfer is provided. The system include one or more databases organized into logical subdivisions associated with users of different qualifications, the databases storing digital identities representing private assets, private-asset derivative instruments and derivatives archetypes. Processors, which can be cloud-deployed, are configured to receive user preferences for risk, return, and exposure; determine user access rights; identify or create a derivatives archetype that satisfies those preferences; and generate or return a corresponding private-asset derivative instrument for portfolio management, risk transfer, or trading. Archetypes are associated through machine-readable references with digital identities of corresponding instruments or their underlyings. The processors may employ quantitative or machine-learning models to convert user preferences into statistical descriptors, select private-asset representatives, project cash flows, and match users on a trading platform for execution or restructuring of transactions.

A computer implemented method for solving a classical optimization problem of integer factorization implemented on a digital computer system is described. The method is implemented on a classical processor adapted to execute a time evolving block decimation algorithm. The method comprises in a first step an inputting a lattice basis and a target lattice vector to an input device of the classical processor followed by an implementing a lattice basis reduction algorithm on the lattice basis in an implementation module, thereby obtaining a reduced orthogonal lattice basis. The method further comprises a projecting the target lattice vector on the reduced orthogonal lattice basis followed by a building a closest vector to the target lattice vector and optimizing the closest vector using a tropical time-evolving block decimation algorithm by the classical processor and finally outputting an integer vector.

Control loop latency can be accounted for in predicting positions of micro-objects being moved by using a hybrid model that includes both at least one physics-based model and machine-learning models. The models are combined using gradient boosting, with a model created during at least one of the stages being fitted based on residuals calculated during a previous stage based on comparison to training data. The loss function for each stage is selected based on the model being created. The hybrid model is evaluated with data extrapolated and interpolated from the training data to prevent overfitting and ensure the hybrid model has sufficient predictive ability. By including both physics-based and machine-learning models, the hybrid model can account for both deterministic and stochastic components involved in the movement of the micro-objects, thus increasing the accuracy and throughput of the micro-assembly.

The invention relates to a method for communication between a human user and a digital AI-supported computer system, in which the system can generate suggestions, particularly regarding job offers and career paths, by recognizing data collected from a user. The system comprises video and audio sensors and communicates on the computer side via an AI-supported avatar.

This invention relates to a method for generating conditional data and a hybrid computer system. In this hybrid computer system, a digital computer transforms the sampling problem of the variables to be sampled in a conditional data generation model of an energy network type, which can be mapped to a quantum computer, into a problem of solving the Ising model. The quantum computer then solves the Ising model to achieve rapid sampling. This invention solves the technical problem of low sampling efficiency in existing deep learning-based conditional data generation models, thereby improving the sampling efficiency of conditional data generation models.

Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.

This invention belongs to the field of digital computer control technology, specifically relating to a method and system for monitoring the operating status of an ore centrifuge. The method includes: acquiring the original vibration signal sequence of the main shaft, the original current signal sequence of the motor, and the original speed signal sequence of the rotor of the ore centrifuge and performing low-pass filtering; acquiring the main shaft vibration amplitude, motor current, and rotor speed, and obtaining the load vibration deviation based on these parameters; obtaining the eccentric wear degradation index using the sliding reference deviation and time interval; obtaining the critical risk value by combining parameters such as the critical wear amount for structural failure; comparing the critical risk value with a set threshold, and sending control commands to the ore feed valve or the drive motor frequency converter based on the comparison results. This invention reduces false alarm interference caused by slurry load fluctuations and the hidden dangers caused by delayed manual response, improving the stability of continuous centrifuge operation.

An analog-digital hybrid computer including an analog part and a digital part that are connected to each other and are capable of mutually exchanging signals, the hybrid computer comprises at least one component for analog calculations, and analog-to-digital (AD) and / or digital-to-analog (DA) converters. The hybrid computer further comprises at least one analog circuit for signal processing as a smart AD interface within the analog part of the hybrid computer, which is used for tasks other than analog calculation of the hybrid computer. The smart AD interface is configured for performing analyzing the signals and / or extracting information from the signals, filtering signals and reducing the amount of data before AD conversion, measuring and digitizing characteristic data of at least one of frequency, periodicity and duration of a process, extracting one or more spectral components from a signal by frequency response filtering or demodulation, processing the signals for enabling use of sub-Nyquist rate AD converter, and digitizing the obtained information and transmitting the digitized information to the digital computer.

This invention relates to a training method and hybrid computer system for a conditional data generation model. In this hybrid computer system, a digital computer transforms the sampling problem of the variables to be sampled in an energy network-type conditional data generation model that can be mapped to an optical quantum computer into a problem of solving the Ising model. The optical quantum computer then solves the Ising model to achieve rapid sampling. This invention solves the technical problem of low sampling efficiency in existing deep learning-based conditional data generation models, thereby improving the sampling efficiency of conditional data generation models.

A system and method for personal energy-related changes payback evaluation with the aid of a digital computer are provided. An overall thermal performance of a building is estimated. One or more proposed replacements for existing equipment associated with an individual associated with the building is received. An annual electric consumption associated with the existing equipment is determined. The consumption associated the existing equipment is converted into a time series that includes a plurality of values that are each associated with a time interval. Renewable energy production data associated with the building is obtained. The time series is combined with the photovoltaic production data to obtain time series net consumption data. A cost associated with the time series net consumption data is determined. A payback associated with replacing the existing equipment is estimated using the cost.

The application relates to the technical field of digital signal processing, in particular to a non-scaling reconfigurable CORDIC calculation method based on a lookup table and a micro-rotation angle set, which comprises the following steps: input angle and a mode selection signal are acquired; based on the mode selection signal, a first-stage rotation operation is performed on the input angle through the lookup table, the input angle is mapped to a small-angle region, and a first-rotation-vector value and a first residual angle after the first-stage rotation operation are output; a multi-stage iterative micro-rotation operation is performed on the first residual angle by using the micro-rotation angle set, and a final-rotation-vector value is output; wherein the circular rotation and the hyperbolic rotation share the address of the lookup table, the micro-rotation angle set and the rotation operation hardware resources, and the mode switching is performed through the mode selection signal, so that the high reconfigurability of the hardware resources is realized. The method can solve the technical problem that the existing CORDIC architecture is difficult to balance among the convergence range, the hardware resources, the calculation accuracy and the reconfigurability.

The application discloses a CORDIC method and a communication device. The method comprises: calculating and storing a first parameter value λ, determining a target rotation direction d according to an input first angle θ and the first parameter value λ θ , and performing iterative calculation through a CORDIC algorithm according to the target rotation direction d θ . The first parameter value λ is determined by a sum θ cp of rotation angles of multiple iterations and the input angle θ. In other words, all rotation directions can be predicted before iteration according to the calculated d θ . Through the CORDIC method, rotation iteration can be converted into at least three-level iteration or equal multi-level iteration. The rotation direction of each iteration does not need to wait for the completion of the last iteration, the number of iterations can be reduced, and the calculation time delay can be reduced.

HYBRID ANALOG DIGITAL COMPUTER FOR DEMONSTRATING NONLINEAR MATHEMATICAL ELECTRICAL BEHAVIOUR