19 results about "Sequence selection" patented technology

The invention discloses an alloy specific strength optimization method combining uncertainty and heuristic algorithms. The alloy specific strength optimization method comprises the steps that a high-entropy alloy component and a strength data set of the high-entropy alloy component at a high temperature are constructed; calculating physicochemical properties based on components, and selecting and screening key feature subsets by adopting correlation analysis and forward sequence selection; comparing the prediction performance and uncertainty of each machine learning model, and determining an optimal model; selecting a target system, performing performance prediction on a candidate system by using an optimal model, estimating uncertainty in combination with a folding knife method, and constructing an upper confidence boundary as an evaluation index; the upper confidence boundary serves as a fitness function of a heuristic algorithm, and optimized alloy components and fitness values are output; the performance of the optimized components is verified through experiments, if the requirements are not met, the result is fed back, and optimization continues until the components with the performance meeting the requirements are obtained. According to the alloy specific strength optimization method combining uncertainty and heuristic algorithms, the problems of high cost and long period caused by dependence on a trial and error method in the prior art are solved.

A method for encoding data includes: selecting a sequence of pivot candidate positions from a sequence of g encoded vectors to encode blocks of g data symbols in a round of encoding by the following steps: providing a set of g pivot candidate positions; selecting pivot candidate positions for the sequence from the set of pivot candidate positions; removing the selected pivot candidate positions from the set of pivot candidate positions; and repeating until the set of pivot candidate positions is empty and the sequence of selected pivot candidate positions in the round is non-linear. A set of encoded vectors is generated based on the sequence of selected pivot candidate positions, each encoded vector including zero-valued coefficients at positions within the encoded vector preceding the pivot candidate positions and non-zero-valued coefficients at least at the pivot candidate positions.

The present invention discloses a stateful protocol differential fuzz testing method and system based on behavioral difference guidance. In the test preparation stage, the method compiles a data model and a state model as the input of the fuzzifier according to the protocol specification of the protocol to be tested. In the target state selection stage, an optimal state to be tested is selected according to the behavioral difference information. In the message sequence selection stage, the message sequence that can best trigger the behavioral difference between programs under the current target state is selected and mutated. In the behavioral difference guidance stage, the behavioral difference information generated by all the programs to be tested executing the test case is collected and synchronized to the target state selection and message sequence selection. The present invention effectively solves the problems that the existing network protocol differential testing work cannot effectively realize automated testing of the complete state space of the protocol, as well as the existing blind selection of state and message sequences, thereby improving testing efficiency.

The embodiment of the present application provides a kind of power system transient stability key feature selection method, device and product, belong to information processing technical field.In the embodiment of the present application, the operation data not carried out in power grid safety and stability evaluation is considered, and the manifold structure of operation data sample of unlabeled data is reserved by local linear embedding;In the embodiment of the present application, the forward sequence selection method based on Fisher Score is used, and unlabeled data is processed by local linear embedding, and the variance cumulative contribution rate is calculated by principal component analysis method to reduce the dimension of feature;After dimension reduction, efficient incremental feature selection is carried out, so that the key feature affecting power system transient stability is selected.The embodiment of the present application can comprehensively utilize the operation data not subjected to safety and stability evaluation generated in the process of power system operation, and improve the classification accuracy of the selected key feature on test set.

The invention discloses a dynamic game-based immediacy decision-making method, which specifically comprises the following steps of: establishing a combat action dynamic game selection model, and determining a red-blue action set of the combat action selection model; determining a battlefield state transition probability of the battlefield action selection model; obtaining a red-blue confrontation strategy according to the red-blue action set and the state transition probability; constructing a state utility function in the battle action selection model; and determining the optimal strategy of the red and blue parties through the zero-sum game. Compared with the prior art, the method not only can dynamically evaluate the advantages and disadvantages of different tactical selections, but also can preferably select an appropriate action sequence and select an optimal action decision in a complex game environment of friend or foe in combination with intelligence update and battlefield feedback.

To make it possible to realize batch process control that can achieve the target control performance.SOLUTION: A control support device according to one aspect of the present disclosure is a control support device that supports control of an object that executes a batch process, and includes: an acquisition unit that acquires a control quantity output from the object and a target value for the control quantity; a prediction unit that calculates a first control quantity prediction time series that represents a time series of a future control quantity later than the control quantity, based on the control quantity, a model that represents a relation between an operation quantity and a control quantity of the object, and an operation pattern that represents the time series of the operation quantity; a selection unit that selects a best operation pattern from the plurality of operation patterns, based on the first control quantity prediction time series and the target value; and a correction unit that selects a best corrected operation pattern from among one or more corrected operation patterns obtained by correcting the best operation pattern by one or more correction methods, based on the target value.SELECTED DRAWING: Figure 2

The invention discloses an annular shuttle vehicle task scheduling method and device, computer equipment and a storage medium, and the method comprises the steps: collecting the real-time operation data of an annular shuttle line, and generating a system state snapshot; carrying out multi-round random pairing on the idle trolleys and the to-be-transported goods to generate n groups of initial matching sequences; randomly selecting two groups for fragment interception, and mixing and recombining to form a new sequence until all initial sequences are updated into brand new matching sequences; calculating the total running time of each group of brand new matching sequences; sorting the matching sequences according to the total operation time length, selecting the first n groups, and randomly extracting parts from the first n groups to mix and recombine again; determining n groups of optimal matching sequences; and the group with the shortest total running time is selected to be issued to the corresponding annular shuttle vehicles to execute the scheduling task. By implementing the method, the operation efficiency and the logistics processing capacity of the annular shuttle vehicle system can be improved, and an advanced technical solution is provided for a logistics system in an intelligent manufacturing scene.

The invention relates to a memory allocation system for automatic parallel data processing and a method thereof. The system comprises: a topology sequence selection component for selecting a specific topology sequence for a computational graph; the simulation execution component simulates an execution operator according to the selected topological sequence and generates an output data block; the memory and calculation component is used for adding the memory required by the generated data block to the sum of the memories of the survived data blocks in the process of simulating and executing the operator; the data block marking component is used for marking all the current survival data blocks as support data blocks when the memory sum of the current survival data blocks is equal to a preset memory peak value; the supporting memory calculation component is used for summing the memories of all the supporting data blocks to obtain a supporting memory; the memory peak value lower bound calculation component is used for summing the supporting memory, the full-period data block memory, the transmission memory and the data processing system starting memory to obtain a memory peak value lower bound for the selected specific topological sequence; and the memory allocation component is used for allocating the memory of which the redundancy is greater than the preset redundancy of the lower bound of the memory peak value to the computational graph of the selected parallel scheme as an estimated memory.

A self-checkout device is disclosed. The self-checkout device comprises a detection plate adapted to allow placement of product(s) thereon, and one or more cameras positioned to have a Field-of-View encompassing the detection plate, the one or more cameras configured to provide a video footage. The self-checkout device further comprises a motion detection module configured to detect presence of motion in the video footage; a sequence selection module configured to select a sequence of video frames over a time interval corresponding to the detection of the presence of motion in the video footage; an appearance interpretation module configured to register one or more products present in the sequence of video frames; a billing module configured to fetch prices of the registered one or more products, generate a total bill based on the fetched prices, and process a payment for the total bill; and a controller module facilitating communications therebetween.

The application discloses a kind of neural network-based Internet of Things equipment vulnerability mining method, it is related to Internet of Things equipment vulnerability detection technical field, including the following steps: step 1, collection Internet of Things equipment message sequence and pre-processing and annotation;Step 2, determine a message from all messages to be mutated for variation operation;Step 3, determine the variable segment of the message to be mutated, and execute multiple variation strategies;Step 4, fuzzy testing is carried out on Internet of Things equipment using the variable segment, and the feedback information of the fuzzy testing module is obtained by classifying the response of Internet of Things equipment.The application can generate more effective variable sequences through the variable sequence selection based on attention mechanism, and the device response classification based on improved clustering algorithm can reduce the number of mutations, and compared with several popular black-box testing tools, the number of mined vulnerabilities and the number of discovered program coverage paths are improved.

A wireless transmit / receive unit (WTRU) may include a transceiver and a processor. The WTRU may be configured to receive one or more downlink signals. The WTRU may be configured to receive configuration information indicating time and frequency resources for transmission of hybrid automatic repeat request (HARQ) acknowledgement (ACK). The configuration information may indicate a first sequence. The WTRU may be configured to determine a set of sequences to be used in response to the receipt of the one or more downlink signals. The set of sequences may be determined based on the indicated first sequence. The WTRU may be configured to send a second sequence from the set of sequences in the time and frequency resources to indicate HARQ-ACK. The second sequence may be selected based on a number of physical downlink control channel (PDCCH) monitoring occasions associated with the indicated HARQ-ACK.

The invention relates to the technical field of computers, in particular to a multi-core and multi-core particle verification method and device and electronic equipment. The method comprises the following steps: acquiring a reset signal corresponding to a target engine in a target core particle in a core particle set under the condition that each core particle in the core particle set is interconnected; under the condition that the reset signal meets the signal requirement, controlling the target engine to send a first test excitation sequence to an access address space corresponding to the target engine; and when a second reset signal is received in the process of sending the first test excitation sequence by the target engine and the reset signal is determined to be completed, sending a second test excitation sequence according to a test excitation sequence selection mode corresponding to the target engine, and obtaining a verification result of the target engine according to the test end information, a first test result of the first test excitation sequence and a second test result of the second test excitation sequence. According to the invention, the verification accuracy and verification efficiency of the core particles can be improved.

Embodiments described herein provide systems and methods for training a sequential recommendation model. Methods include determining a difficulty and quality (DQ) score associated with user behavior sequences from a training dataset. User behavior sequences are sampled during training based on their DQ scores. A meta-extrapolator may also be trained based on user behavior sequences sampled according to DQ score. The meta-extrapolator may be trained with high quality low difficulty sequences. The meta-extrapolator may then be used with an input of high quality high difficulty sequences to generate synthetic user behavior sequences. The synthetic user behavior sequences may be used to augment the training dataset to fine-tune the sequential recommendation model, while continuing to sample user behavior sequences based on DQ score. As the DQ score is based on current model predictions, DQ scores iteratively update during the training process.

Various aspects of the present disclosure relate to techniques for preventing dimension reduction attacks. A user equipment (UE) is configured to receive, from a network entity, a configuration comprising a set of time-domain orthogonal cover code sequences, each time-domain orthogonal cover code sequence of the set of time-domain orthogonal cover code sequences comprising a sequence length that is different from sequence lengths of other time-domain orthogonal cover code sequences of the set of time-domain orthogonal cover code sequences; select, from the set of time-domain orthogonal cover code sequences, at least one time-domain orthogonal cover code sequence; multiplex uplink (UL) data associated with the UE in accordance with the selected at least one time-domain orthogonal cover code sequence; transmit, via a physical UL shared channel (PUSCH), a waveform carrying the multiplexed uplink data associated with the UE.

The application discloses a ring-shaped shuttle task scheduling method and device, computer equipment and a storage medium. The method comprises the following steps: collecting real-time running data of a ring-shaped shuttle line to generate a system state snapshot; performing multi-round random pairing on an idle trolley and a to-be-transported cargo to generate n groups of initial matching sequences; randomly selecting two groups to perform fragment interception and mixed recombination to form new sequences until all the initial sequences are updated into new matching sequences; calculating the total running time of each group of new matching sequences; sorting the matching sequences according to the total running time, selecting the first n groups and randomly extracting part of them for mixed recombination again; determining the optimal n groups of matching sequences; and selecting a group with the shortest total running time to issue to a corresponding ring-shaped shuttle vehicle to execute a scheduling task. The method can improve the running efficiency and logistics processing capacity of the ring-shaped shuttle system, and provides an advanced technical solution for a logistics system in an intelligent manufacturing scene.

Embodiments of the present disclosure include systems and methods for training masked language models based on partial sequences of tokens. A sequence of tokens for training a transformer model is received. A defined proportion of the sequence of tokens is selected. Each value of the defined proportion of the sequence of tokens is replaced with a defined value. The transformer model is trained by using the sequence of tokens to train the transformer model during a forward pass and using a subset of the sequence of tokens that includes the defined the proportion of the sequence of tokens to train the transformer model during a backward pass.

The present application provides a communication method and a communication apparatus. The method comprises: on the basis of sequences in a first sequence set, spreading a first modulation symbol to obtain a first spread symbol; and sending the first spread symbol, wherein the first sequence set is determined on the basis of Nset,2 second sequence sets, and Nset,2 is an integer greater than 1; each second sequence set comprises one or more second sequences, and the second sequences in each second sequence set are orthogonal; there are at least two sequence sets among Nset,2 second sequence sets, and the lengths of the second sequences comprised therein are different; and the sequences comprised in the first sequence set are orthogonal. Sequences in a first sequence set are used as spreading sequences to spread a first modulation symbol, thereby improving the flexibility of orthogonal spreading sequence selection.

The invention discloses a power grid secondary equipment remote operation and maintenance management method based on cloud edge collaboration, and relates to the technical field of power control, and the method comprises the steps: carrying out the impact evaluation of the operation instruction list and execution power flow sensitivity of power grid secondary equipment, and obtaining a minimum risk path; on the basis of the minimum risk path, micro time window slicing is implemented through an evidence fingerprinting sequence slicing algorithm, mirror image anchoring is carried out on station end operation data, and a zero-trust release credential is generated; a controlled session is established according to the zero-trust release credential, and execution record summarization is generated through context mirroring; and based on the execution record summarization, carrying out consistency survey and verification according to the zero-trust release credentials, and generating a verification receipt report. According to the method, the power flow sensitivity evaluation is carried out on the operation instruction list of the power grid secondary equipment, and the minimum risk path is selected through step-by-step short circuit judgment, so that the effects of explainability of sequence selection, cross-station consistency and plan one-time passing rate improvement are improved.