137 results about "Task level" patented technology

A multi-dimensional imaging device and method for automated exposure control that implement two distinct modules to control the exposure and gain settings in the imager so that processing can occur in a multi-tasking single CPU environment. The first module, referred to herein as the imager control module, controls the exposure and gain settings in the imager. The first module is typically implemented in a high priority routine, such as an interrupt service routine, to insure that module is executed on every captured frame. The second module, referred to herein as the histogram processing module, calculates a target contrast (the product of the targeted exposure and gain settings) based on feedback data from the first module and image data from memory. The second module is typically implemented in a low priority routine, such as a task level routine, to allow for the routine to be executed systematically in accordance with priority.

In certain embodiments, a Service Deployment Infrastructure (SDI) request engine is disclosed. The SDI request engine performs the tracking, management and provisioning of services subscribed to by customers of the cloud infrastructure system. The SDI request engine is deployed to process large volumes of provisioning requests and deliver time critical applications for customers. The SDI request engine translates each request into a list of tasks of various sizes based on the requirement and configuration of the request. In some embodiments, the SDI request engine imposes control and management on both request and task levels in order to execute, rollback, retry or fail a task automatically and accurately.

Methods and apparatuses are disclosed for use in network-centric computing for scripting user-interface components together on an as-needed basis for purposes of executing a software application preferably stored on a server. The application may be called from a container / desktop of a client which in turn launches a script. The script may be stored on a server, on the desktop, or on a removable media, such as an optical or magnetic diskette. The script determines each task to be performed in the application and calls each node associated with the tasks. The script further verifies the policies of the container / desktop with respect to invoking, initializing, and executing the node. Once a task has been performed on the client, the script determines the next node, if any, and may discard the previous node in accordance with the policy framework of the container / desktop. In this way, applications can be performed in a myriad of computing devices, some having little or no memory, by downloading to the client only those user-interface components needed for a particular task to be performed.

The invention relates to a method for scheduling the processing of tasks and to the associated device, the processing of a task comprising a step for configuring resources required for executing the task and a step for executing the task on the thereby configured resources, the method comprising a selection (1) of at least one level of independent tasks to be processed in accordance with an order of precedence and a step for sorting (2) out the tasks of the level of tasks to be processed in order to define, an order of priority in the processing of the tasks, depending on the number of resources required for processing the tasks on the one hand and on a time characteristic of the tasks on the other hand.

An improved operating system and architecture, particularly useful for aircraft, provides a schedule for multiple tasks that ensures that each task has sufficient execution time and does not interfere with any other tasks. In the operating system, each task is scheduled to a deadline monotonic algorithm. The algorithm creates a schedule for the tasks in which the tasks are time partitioned by task, not by task level. The APIs in the operating system are provided by the services. Thus, changing a service, e.g. because of a change in hardware, is facilitated, since the service will provide the proper API.

The invention provides a virtual container based big data storage and management system and method. The system comprises a metadata server, a scheduler and a slaver server, wherein the metadata server is used for maintaining tenant information and user information and performing authority authentication when a user accesses metadata and a container; the scheduler comprises two layers of scheduling; the upper-layer scheduling is container-layer scheduling; the lower-layer scheduling is task-layer scheduling; the upper-layer scheduling is used for receiving a request of the user and assigning and configuring the corresponding container for the user; the lower-layer scheduling is completed by a master node of a big data computing framework; the scheduler implements scheduling of the container; and the slave server controls start and stop of the container on a physical machine, monitors resources of the physical machine and feeds back the resources and a task operation condition to the scheduler. According to the system, a virtual container technology is adopted to isolate the resources from the environment, adopts a double-layer scheduling architecture to reduce a load of an upper-layer scheduler and a coupling degree between a distributed application and the scheduler, and provides support for real-time scheduling on a storage system.

A method and system for modifying an existing user interface at the user task level, such that the existing user interface is contained within the data-processing system. Initially, user tasks that enable particular user interface functions are identified within the existing user interface. Each identified user task is then abstracted into a grouping of objects such that the grouping of objects includes a task object which provides a non-interface specific abstraction of the user task, and a view object which provides a user interface abstraction of the task object. Thereafter the user interface of an identified user task is modified by altering only the view object of the plurality of objects maintained within the user task, such that an alteration of the view object allows a user to effect specific changes to selected portions of the existing user interface without globally altering the existing user interface. The grouping of objects further includes a window object associated with the view object, such that a modification of the window object also does not globally effect specific changes to selecting portions of the existing user interface.

The invention discloses a method and a system used for searching for entities in the internet of things. The method comprises the steps of processing a query statement of a user and generating an unambiguous intermediate language; analyzing the intermediate language into a system internal query statement through a knowledge graph; constructing a knowledge tree in a self-learning or manual training mode through a construction method; and performing distributed query on the system internal query statement through servers and a sensing network through distributed query method and protocol. The system comprises a search service system for performing analysis and result feedback on user query, an artificial intelligence system for maintaining the knowledge graph and providing analysis, and a server cluster and a sensing network system for retrieving the entities according to the system internal query statement. Through the method and the system, the user can search for the entities in the internet of things by using a natural language; the abstractness and divergence of the knowledge graph ensure that a search target can be any describable objective entity or virtual object; and the sensing network system and the protocol described in the system split a search task level by level and perform delegation, so that the system has the characteristics of high concurrency and strong compatibility.

This invention increases the available instruction level parallelism (IPC) of CABAC encoding by decoupling the re-normalization loop and the bit-insertion task required to create the encoded bit-stream. This makes all software implementations of CABAC based encoding significantly faster on digital signal processors that can exploit instruction level parallelism such as very long instruction word (VLIW) digital signal processors. In a joint hardware / software implementation, this invention employs existing Huffman variable length encoding hardware with minimum modifications. The de-coupling of these two tasks of this invention exposes previously hidden underlying instruction level parallelism and task level parallelism.

The invention relates to a multi-task management method based on an embedded system, the method of the invention divides the limited duty of the embedded system into different task levels beforehand: most for a real-time interrupt level, next for a clock interrupt level, once more for a high priority duty inquiry level, finally for a low priority duty inquiry level, the higher the priority is, the performability is higher, the task can be guaranteed more to complete, the lower the priority is, the performability is lower, therefore the duty with high real-time request is arranged in a higher duty level, the duty with low backstage real-time is arranged in a lower duty level. The invention has the advantages of fully guaranteeing the real-time of executing partial task, saving the system resources, and having brief and clear task management.

The invention discloses a task allocating method, device, and system based on location service. The method comprises steps of: releasing a task position, a task type, and task grade information; acquiring the real-time position information of a person and searching people within a task range according to the task position; searching people capable of executing a task according to the task type and the task grade; sending a task instruction to the people capable of executing the task. The method, the device, and the system may automatically record and determine the skill proficiency degrees of the people, automatically allocate the task according to the specific positions, the operating states, and the skill proficiency degrees of the people, and greatly reduce task allocation time cost and intermediate communication cost.

A compiler for multiple processor and distributed memory architectures is described. The compiler uses a high-level language to represent a task-level network of behaviors that describes an embedded system. The compiler maps a plurality of tasks and data onto a multiple processor, distributed memory hardware architecture. The mapping includes describing a task-level network of behaviors, each of the task-level network of behaviors being related through control and data flow. The mapping further includes predicting a schedule of tasks for the task-level network of behaviors and allocating the plurality of tasks and data to at least one of the multiple processors and to at least one of distributed memory, respectively, in response to the predicted schedule of tasks.

The invention discloses a multilevel distributed task processing system which comprises a plurality of computer nodes in intercommunication with each other, wherein all the computer nodes are connected with a same node server; the node server comprises a task level scheduling module, a sub-task level cutting module and a task managing module; the task level scheduling module is used for storing a task in a 'first in, first out' mode and distributing the task to a corresponding computer node according to a 'least recently used' principle when a user task request is received; the sub-task level cutting module is used for cutting the task into a plurality of sub-tasks and calling the task level scheduling module for distributing the cut sub-tasks to different computer nodes when a treating task is received; the task managing module is used for recycling a computed result of each sub-task from different computer nodes and assembling the computed result of each sub-task into a complete task result; each of the computer nodes comprises an OpenMP inner core level module. The multilevel distributed task processing system is used for increasing the parallel processing efficiency of each task.

An embodiment of the invention discloses a method and a device for quality guarantee on task-level-oriented large data distribution. The method includes the steps of establishing a task distribution request by processing of a data distribution coordination server; partitioning and adjusting aggregate bandwidth according to currently running tasks to be distributed; transmitting a bandwidth adjustment instruction for the tasks to a bandwidth control server which is responsible for the tasks to be distributed; adjusting task data receiving rate to set bandwidth required by the instruction; transmitting a task establishment instruction to the task-assigned bandwidth control server; transmitting a task completion instruction to the data distribution coordination server; modifying the state of the tasks into the state of being completed, and re-calculating bandwidth occupied by the running tasks to be distributed. By the method and the device, bandwidth resources for the tasks in different priority levels for distribution can be customized and distributed when large data are distributed through network. Dynamic adjustment is available, so that task distribution bandwidth resources and transmission rate are guaranteed.

The invention discloses a full-electronic security computer interlocking system. The full-electronic security computer interlocking system comprises a special railway security computer, an interlocker, a control and display machine and an electronic executing unit subsystem, wherein the special railway security computer comprises two security computers as a master computer and a spare computer; each security computer comprises a CPU (central processing unit) board and multiple communication boards; data transmission and data synchronization between a first CPU module and a second CPU module of the CPU board are finished through a two-port RAM (random access memory) and interrupt operation; the CPU board and the communication boards in a same system exchange data through the two-port RAM and the interrupt operation; during system operation, the first CPU module and the second CPU module output control signals for driving a master relay; and a normally open contact of the master relay is used for controlling acting power of onboard safety relays of all the communication boards. By a working method of the full-electronic security computer interlocking system, the special railway security computer can achieve functional safety of a double 2-vote-2 platform, can achieve short-period task-level synchronization of a single computer and two computers, and can achieve seamless handover under fault conditions.

Systems and methods for improved power profiling of embedded applications are presented. These inventions provide the ability to measure the power consumption of an embedded application at the task level as the application is executing on the target hardware. Methods and apparatus are provided to permit such measurements in both real-time and non-real-time.

An interrupt controller specifies and outputs the most highly prioritized one of a plurality of interrupt signal requested for output. A CPU executes a process corresponding to an interrupt signal from the interrupt controller and executes OS-provided programs. Based on reception of a request to execute a task level process, the CPU requests the interrupt controller to output an interrupt signal corresponding to the task level process.

The invention belongs to the field of robot technology and application and relates to a man, machine and object interaction mechanical arm teaching system based on an RGB-D image. The teaching systemrecognizes an objected on the basis of the RGB-D image. By means of tf tree and Kinect V2 point cloud information in an ROS system, the object and a mechanical arm are unified to the same coordinate to locate the object. According to the human behavior habit, the high level actions of the mechanical arm are planned on the basis of MoveIt. In the teaching process, by selecting the object in an operation interface, the type and pose of the object can be obtained, then one action is selected from the high level actions in a centralized manner, the mechanical arm is controlled to operate the corresponding object in the actual space, and multi-step interaction forms the teaching track. The teaching system can achieve man, machine and object intelligent interaction facing the task level, can replace an actual robot system to carry out teaching study, and the system has the characteristics of being high in efficiency, convenient, safe and the like.

The invention proposes a task-level parallel scheduling method and system for a dynamically reconfigurable processor. The system comprises a main controller, a plurality of reconfigurable processing units, a main memory, a direct memory access device and a system bus, wherein each reconfigurable processing unit consists of a co-controller, a plurality of reconfigurable processing element arrays in charge of reconfigurable calculation and a plurality of shared memories used for data storage; the reconfigurable processing element arrays and the shared memories are adjacently arranged; and the shared memories can be read and written by the two connected reconfigurable processing element arrays around. According to the task-level parallel scheduling method and system for the dynamically reconfigurable processor, different scheduling modes can be executed for different tasks by adjusting the scheduling method, and basically all parallel tasks can be well accelerated in parallel in the reconfigurable processor.

The invention discloses a task management method for quantifying task value. The method includes the steps that task content and task levels are acquired and informed to a task executor and a task supervisor; the task content is sent to the task executor; task beginning time is recorded; the task execution progress is acquired regularly and sent to the task supervisor; task completion time is recorded; the evaluation of the task supervisor is acquired; task value is acquired through calculation. The invention further discloses a task management device for quantifying the task value. The device comprises a task management module, a task analysis module, a task tracking module and a timer module. According to the task management method and device for quantifying the task value, the task value of unstructured tasks can be quantified.

The invention relates to a data processing task relation setting method and system. The method includes the steps of obtaining at least one SQL script in a data processing task, carrying out morphology analysis and semantic analysis on SQL sentences in each SQL script in the at least one SQL script to build a data lineage relation of the SQL sentences, building a data lineage relation of the SQL scripts according to the data lineage relation of the SQL sentences, building a data lineage relation of the data processing task according to the data lineage relation of the SQL scripts in the at least one SQL script, determining data input and output of a data level and a task level of the data processing task, and determining and setting the relation between the data processing task and another data processing task according to the data lineage relation and the data level of the data processing task. Intelligent analysis and setting of the relation of the SQL data processing tasks can be achieved, the automation degree of data task scheduling configuration is improved and accuracy and efficiency of data operation and maintenance are achieved.

The invention discloses a hot redundancy interlocking subsystem. The hot redundancy interlocking subsystem comprises a first system and a second system which are identical and are connected, wherein each of the first system and the second system comprises two heterogeneous hardware and two CPUs synchronizing at task level. The two sets of different software run on two CPUs respectively. The first system and the second system obtain inputs from track sides and synchronize preset time for one time, and operations of the two systems are compared and then output simultaneously. The hot redundancy interlocking subsystem achieves a hot redundancy double 2-vote-2 hot standby switching mechanism.

The invention discloses a character interaction-oriented network weight generation few-sample image classification method. Considering the problem of long tails in a character interaction image data set, a meta-learning framework and an episodic training strategy are used to simulate the situation of less sample image data in a real scene, reduce the image data distribution difference, improve thegeneralization ability, and effectively solve the problem of uneven image distribution in a character interaction task. Introducing semantic information of nouns and verbs of the labels, and generating task-level feature extraction network function parameters to reinforce visual features. TRAINING PROCESS, different small sample tasks are continuously obtained; task data is expressed as a task feature by using semantic and visual fusion information of a category contained in a task, a parameter of a corresponding layer of a target network for the current task is sampled through a parameter generator based on the task feature, and actions and object areas of characters in related images are concerned, so that the image classification capability can be improved.

The invention relates to a dual-redundant unmanned ship ship-borne control system and method based on an ARM. The system comprises an information collection system, a first arbitration switching system, a second arbitration switching system, an execution mechanism, a first ARM processor, a second ARM processor, a communication system and a power supply. The task level synchronization is realized by the two ARM processors. The dual-redundant designs of all sensors are made. The data of two paths of sensors are transmitted to two ARM processors at the same time to carry out comparison, correct data is selected to carry out task operation, and a comparison point is set in the task operation. The corresponding data is subjected to consistency judgment, if the corresponding data is inconsistent, the arbitration switching systems carry out fault diagnosis on the two ARM processors, a failed ARM processor is isolated, and at the same time an ARM processor with normal operation is selected to control output. According to the dual-redundant unmanned ship ship-borne control system and method, with hardware redundancy as a basis, with software redundancy, information redundancy and time redundancy as a supplement, the reliability, stability and safety of the unmanned ship ship-borne control system are effectively improved, the safe and stable operation of an unmanned ship is ensured, and various complex tasks are smoothly completed.

There is provided a method of managing a data memory in order to improve the processing of memory allocation requests. Memory segments are associated with different levels according to their size. A different granule size to the power of two is defined for each level. The granule size defines the range of segment sizes associated with each level. A multiple-stage bitmap is provided which indicates which of the levels contains free segments and the size of free segments. The bitmap is updated each time a memory segment is freed or allocated. Thereby, a deterministic ''Best Fit'' approach is provided which permits the allocation and release of memory segments at both task and interrupt level and which reduces memory fragmentation.

The invention relates to the technical field of data processing, in particular to a task allocation method and device, a storage medium and terminal equipment. The task allocation method comprises thesteps of obtaining each first attribute feature corresponding to a to-be-allocated task; inputting each first attribute feature into a preset decision tree model to obtain a first task level corresponding to the to-be-allocated task output by the preset decision tree model, the preset decision tree model being a model taking the attribute features as nodes and taking the task level as a decisionresult; determining a candidate employee group corresponding to the first task level according to a preset corresponding relationship between the task level and the employee group; and selecting a corresponding target employee from the candidate employee group based on a preset selection mode, and sending the to-be-allocated task to a terminal corresponding to the target employee, so as to comprehensively analyze each first attribute feature of the to-be-allocated task through the preset decision tree model to accurately determine the task level of the to-be-allocated task, thereby performingreasonable and accurate task allocation according to the task level.

The invention provides a computer interlocking system and a redundancy switching method thereof. The system includes an interlocking subsystem. The interlocking subsystem contains an interlocking I system and an interlocking II system which are the same and are interconnected. Each of the interlocking I system and the interlocking II system includes two CPUs which are the same in hardware and adopt task-level synchronization. The two CPUs respectively run executable files generated by compiling the same program code by different compilers. According to the system, heterogeneous software / hardware and program running starting times with a fixed difference are adopted to reduce occurrence probability of common-mode faults, development difficulty is reduced while the common-mode faults are reduced, production efficiency is improved, and reducing of requirements of debugging and maintenance is realized.

The invention discloses a SDSIN-based multi-task routing method. The method comprises the following steps: establishing a reasonable network model; carrying out spatial task level division; establishing a mathematical model based on an SDSIN multi-task routing method; making a link parameter decision; and carrying out weight updating. On the basis of the machine learning algorithm, the method considers a plurality of factors such as link state parameters and spatial tasks fully to realize optimal path selection, so that the utilization rate of network resources is increased and a congestion phenomenon of local links is avoided. Meanwhile, QoS requirements of various spatial tasks are met. With full consideration of link characteristics like transmission delay, a packet loss rate and a remaining bandwidth, a training set is trained based on the parameters; the link parameter weights are updated; and thus the multi-tasking routes are selected and recorded. Therefore, the utilization rateof the underlying resources is increased and the load balancing across the entire network is realized.

The invention relates to a task data processing method and device, computer equipment and a storage medium. The method comprises the steps of intercepting a service request sent by a first terminal based on a preset statistical task to obtain task data; determining a task level of a pre-configured statistical task; according to the shunting configuration information of the task level, storing thetask data into a memory for real-time processing, storing a real-time processing result into the memory, or storing the real-time processing result into a database for batch processing, and storing abatch processing result into the database; and when a data query request sent by a second terminal is received, reading the result of the real-time processing in the memory, or reading the result of the batch processing in the database. By adopting the method, the task data processing timeliness can be improved.

The present invention relates to an intelligent service scheduling method, which is used for realizing the scheduling of a plurality of tasks on a server cluster. There is no time-sequence relationship among the plurality of tasks. The tasks comprise a plurality of subtasks having a time-sequence relationship. The method comprises: gathering a plurality of tasks into different task groups, and in each of the task groups, gathering subtasks which are at the same level in a time sequence into one new subtask; and taking the new subtask as a minimum scheduling unit to conduct parallel subtask scheduling in a server cluster. The present invention takes account of the problem of scheduling a plurality of subtasks, having a time-sequence dependency, contained inside one task and conducts task gathering at a subtask level, thereby obtaining the minimum scheduling unit of a suitable particle size. In addition, in the aspect of the selection of performance indexes, two performance indexes, i.e. timeliness and energy consumption, are comprehensively taken into account.