13 results about "Sequential selection" patented technology

The invention provides a memory block management method and a controller. The method comprises the following steps: acquiring a configuration file in a Linux kernel, analyzing the configuration file to obtain a memory size interval, determining a use state of a memory block in the memory size interval, and setting a bit flag of the use state in a flag bit corresponding to each memory block; whether the memory size of a target memory block of the current allocation request is in a memory size interval or not is judged, if yes, whether a first idle linked list in the SLUB allocator is empty or not is judged, and the first idle linked list is used for storing the flag bit of the memory block with the bit marked as idle; and if not, sequentially selecting a flag bit of a target memory block of a linked list from a first idle linked list of the SLUB allocator, and determining the target memory block for the current allocation request according to the flag bit of the target memory block. According to the method and the device, the problems of too high memory block metadata occupation and low allocation efficiency in the SLUB allocator can be solved.

The application discloses an algorithm electricity collaborative demand response bidding decision method and system based on large model training tasks, and relates to the technical field of power system dispatching. First, the power grid invitation signal is received and analyzed to construct an invitation signal feature set. Then, the state of the intelligent algorithm center is collected, and the computing power shadow price of each large model training task is calculated; the state space and action space are constructed according to the distribution characteristics of the invitation signal feature set and the computing power shadow price, the PPO algorithm is used to solve the optimal bid, and the optimal bidding strategy is output. If the bidding is successful, the adjusted task set is selected in the order from low to high according to the computing power shadow price of each large model training task, and hierarchical control is performed as needed. Through the hierarchical response mechanism and cost consideration, when interruption must be performed, the large model training task that has just completed the "checkpoint saving" is automatically locked and suspended through the computing power shadow price sorting, the impact on the training progress is minimized, and the safety of the model parameters is ensured.

One aspect of the present invention is an information processing system that comprises at least one processor. The processor is configured to execute a program to accomplish the following steps: a management step for managing a plurality of keywords and degrees of priority that respectively correspond to the keywords, the plurality of keywords being at least one preset term that indicates a behavior related to wellbeing and having been determined by sequential selection by a user; and a first display control step for displaying the plurality of keywords selected by the user in a manner that allows the user to ascertain the corresponding degrees of priority.

The invention belongs to the technical field of programming teaching, and particularly relates to a programming thinking triple recruitment-based children programming teaching method, which comprises the steps of sequence, selection and circulation, and comprises the following steps: step 1, introducing the concept of programming thinking triple recruitment to children; 2, theoretical explanation, instance demonstration and programming practice operation are carried out on the sequence, selection and circulation; and step 3, integrating the application of the three recruitments through a comprehensive programming project. According to the method, the programming core concept is abstracted into three major thinking modes of sequence, selection and circulation, namely programming thinking triple recruitment, a progressive teaching process of concept introduction, sub-item teaching and comprehensive application is established, and by analogy of abstraction concepts through living examples, children can visually understand the programming essence, the cognition threshold is reduced, meanwhile, all program logics are covered, and the programming effect is improved. Students can autonomously dismantle complex problems after mastering, systematic thinking cultivation is improved, step-by-step teaching ensures internalization of each thinking mode, contusion caused by knowledge jumping is reduced, and teaching efficiency is improved.

To maintain a user's sense of expectation for a long time in a process of progress of a game.SOLUTION: A game system comprises: a lottery section for successively selecting one of multiple lottery elements by a lottery; and a control section for controlling a game utilizing multiple blocks. One of multiple attributes and one or more lottery elements among multiple lottery elements are allocated to each of the multiple blocks. The control section erases a first block to which a lottery element selected by the lottery section among the multiple blocks is allocated for each selection of a lottery element by the lottery section, moves a second block to a space generated by the erasure of the first block, and generates a fourth block with the attribute concerned by mutually connecting the second block and the third block when an attribute of the second block is common to an attribute of a third block adjacent to the second block after movement.SELECTED DRAWING: Figure 5

A method and system for generating product arrangement information by using product volume information is proposed. The proposed relates to a method for generating arrangement information when products are loaded into a box by using volume information of the products, and a system for executing the method. The method includes an initial solution set creation step of generating a plurality of first sample objects having randomly generated loading order information and rotation direction information from product specification data including product size information and product rotation direction count information and an arrangement information generation step of crossing a pair of the first sample objects with each other to generate a plurality of second sample objects, and selecting the plurality of first or second sample objects in order of priority so as to be reset as the first sample objects.

The invention discloses a heterogeneous multi-core system hybrid task allocation method and device, and the method comprises the steps: carrying out the instruction cycle according to the hierarchy of each task and the worst case of the task, and sorting the tasks, and obtaining the allocation priority of each task; selecting to-be-allocated tasks according to the allocation priority sequence, and allocating the selected task forcing part to a processor core which meets the task deadline and system energy consumption requirements of the tasks and has the highest task execution efficiency; according to the total energy consumption of the distributed task forcing parts and the total energy consumption budget of the system, sequentially carrying out energy consumption extension on the task forcing parts according to the task distribution priority; and selecting the tasks to be distributed according to the distribution priority sequence, and distributing the selectable parts of the selected tasks to the processor core which meets the task deadline of the tasks and has the highest task execution efficiency. According to the technical scheme, system resources are fully utilized to improve the service quality of the system, and collaborative optimization of hybrid task scheduling is achieved.

To provide a game system or the like that can enhance the enjoyment of competitive games using game media.SOLUTION: A game system is for a competitive game played using a placement object on which game media is placed and a storage object in which the placement object is stored. The game system includes a placement object selection unit that sequentially selects placement objects stored in the storage object on the basis of parameters set for at least one of the game media, the placement object, and the storage object, and a game progression control unit that controls the game media placed in the selected placement object to progress the competitive game.SELECTED DRAWING: Figure 3

Clock throttler architecture including clock throttler circuitry, related methods and state machine, where the clock throttler circuitry includes: first selection circuitry to select a first pattern of a plurality of patterns in storage, where each pattern of the plurality of patterns comprises a plurality of bits; second selection circuitry to sequentially select bits of the first pattern and to provide the selected bits to clock gate circuitry in a successive manner; where the clock gate circuitry is to receive a clock input signal and to pass or gate pulses of the clock input signal responsive to applying the selected bits to generate a clock output signal.

The invention discloses a scheduling method and device of an artificial intelligence processor, a terminal and a storage medium, and the scheduling method comprises the steps: obtaining target task information, the target task information comprises the type, size and delay demand of a target task; obtaining task data volume information based on the target task information; based on the task data volume information, the first transmission rate and the second transmission rate, obtaining independent processing delay and / or combined processing delay of the AI processing module, judging whether the delay demand is met or not, and if yes, generating an execution scheme of the target task. According to the scheduling method, the independent processing time delay and the combined processing time delay of the AI processing module are calculated, the scheme which can meet the time delay requirement and has the lowest power consumption is selected based on the time sequence requirement and the priority sequence of the target task, the execution scheme of the target task is generated, power consumption can be minimized on the premise that the time delay requirement is met, and the scheduling efficiency is improved. And the power consumption when the terminal executes the AI task is obviously reduced.

To provide a new method for estimating the number of passengers on a train, based on the premise that each passenger's train selection tendencies are not the same. [Solution] From the trains included in the train timetable 310, multiple candidate trains corresponding to each passenger based on passenger demand data 312 are set. For each of the multiple candidate trains corresponding to each passenger based on passenger demand data 312, the following are calculated: 1) the probability of selection of the candidate train based on a simultaneous selection model, and 2) the probability of selection of the candidate train based on a sequential selection model. Based on the selection probabilities of 1) and 2), the probability of adoption of the candidate train is calculated, and the estimated number of passengers for each train in the train timetable 310 is estimated based on the aggregated adoption probabilities for each passenger and each candidate train.

The controller executes a method (200) for configuring a capping machine to engage a threaded cap with a threaded neck of a container. In the method, angular positions AP are sequentially selected (201) from a predefined set of APs for the cap, each AP corresponding to an orientation of the cap relative to the neck. For each AP, a capping test is performed (100), and the capping machine is operated to engage multiple caps placed at the selected APs with the respective necks of the containers. The capping operations are evaluated for consistent capping performance (202). The method is performed for a sequence of adjacent APs corresponding to a sequence of spatially adjacent cap orientations until consistent capping performance is detected. The capping machine is then configured (204) by setting its operating AP in relation to the sequence of adjacent APs.

The invention discloses a dynamically reconfigurable machine learning acceleration system, which ensures the structural correctness of a processing flow and no data loss by checking the sequence exchange consistency and queue / storage conservation in a running process in a cloud edge collaborative environment. The system includes a plurality of seat modules, referred to as EDGE, NODE, CORE, FIN, and GOV, and a cross-seat exchange interconnect structure connecting these modules. During operation, the system performs continuous consistency check on a key service link, and once an inconsistency or tearing fault is detected, the system only allows to adopt a single repair action once, and selects repair measures according to a priority sequence of topology / path priority, secondary format / protocol and secondary time sequence / window, so that the repair efficiency is improved. And it is ensured that one inconsistency can be eliminated only through one-time repair each time. The process converges in a unit stepping mode, and each iteration enables the inconsistent count mu to be reduced by 1 (delta mu = 1) until the system reaches a consistent state of sealing.