113 results about "Task Performances" patented technology

The present invention relates to a method and apparatus to objectively measure stress and fatigue using measurement tools, record stress and fatigue related data in a standardized database, create automated prompts and alerts based upon pre-defined stress and fatigue thresholds (which are derived based upon individual end-user and task performance), provide a number of interventions (which can be preferentially selected by the individual end-user), create data-driven best practice guidelines though meta-analysis of the database, and provide an objective tool for comparative technology assessment.

Methods are disclosed that dynamically improve soft real-time task performance in virtualized computing environments under the management of an enhanced hypervisor comprising a credit scheduler. The enhanced hypervisor analyzes the on-going performance of the domains of interest and of the virtualized data-processing system. Based on the performance metrics disclosed herein, some of the governing parameters of the credit scheduler are adjusted. Adjustments are typically performed cyclically, wherein the performance metrics of an execution cycle are analyzed and, if need be, adjustments are applied in a later execution cycle. In alternative embodiments, some of the analysis and tuning functions are in a separate application that resides outside the hypervisor. The performance metrics disclosed herein include: a “total-time” metric; a “timeslice” metric; a number of “latency” metrics; and a “count” metric. In contrast to prior art, the present invention enables on-going monitoring of a virtualized data-processing system accompanied by dynamic adjustments based on objective metrics.

The invention provides a task scheduling method based on a distributed scheduling system, a server and a memory medium. The method comprises the steps of receiving mass task scheduling requests, establishing timed tasks in batches according to the requests, and storing related information of each task to a message queue; receiving the tasks from the message queue, issuing each task to a corresponding host for performance according to a preset mode, and monitoring a performance state of each task in real time; automatically triggering the host which performs the task to reperform the task according to a preset task restart rule if certain task is performed unsuccessfully, writing performance state identification information to the task by a load balancing device if the task is still reperformed unsuccessful, forwarding the task to the other host for performance, until the task is performed successfully, and storing a task performance result to a database in a log form. Through application of the method, the server and the memory medium, the scheduling of mass distributed scheduling tasks can be realized, and the throughput of the distributed system is improved.

Disclosed herein is a system and method for determining a sequence for a plurality of tasks, such as tasks assigned to an employee by an employer. The system associates a location identifier to each task, and generates a proposed sequence for the plurality of tasks. The disclosed system receives task performance data that provides information on the actual sequence that was used to perform the plurality of tasks. The task performance data is used to determine a performed sequence—the sequence used by the employee to perform the plurality of tasks. The system compares the performed sequence to the proposed sequence. The system may score the proposed sequence and the performed sequence using a plurality of weighted factors. The system for determining a sequence for a plurality of tasks uses the proposed sequence and the performed sequence to generate proposed sequences for future pluralities of tasks.

The system and method of the present invention enable the user to build and/or use an interactive visual instrument panel for monitoring and/or managing one or more target systems locally or remotely in real-time, with the instrument panel being configured based on the user-defined requirements and based on the attributes of the target system(s) being monitored and/or managed. In one embodiment of the present invention a novel data handling system is provided for ensuring that the target system is able to continuously transmit real-time data without any data loss and without interrupting its operation.

A method and related computer system that allow recalling at least one memory pooling profile, in response to user input, and pooling data processing system memory devices in response to the at least one memory pooling profile.

The invention discloses a MapReduce short job optimization system and method based on resource reuse. The system comprises a master node, a primary slave node and a plurality of secondary slave nodes, wherein the master node is connected with the primary slave node; the primary slave node is connected with the plurality of secondary slave nodes; a resource manager and a primary scheduler are deployed on the master node; an application manager, a task performance estimator and a sub-scheduler are deployed on the primary slave node; the sub-scheduler is connected with the task performance estimator; the sub-scheduler is further connected with the master node; and node managers are deployed on the secondary slave nodes. Through adoption of the MapReduce short job optimization system and method, short job running performance is optimized from the aspect of increase of the effective resource utilization ratio; the resource allocation and recovery frequency is lowered; the resource allocation and recovery time is used for running short jobs; and the short job execution performance is improved in a way of shortening resource waiting time of jobs.

The invention relates to a multi-touch input device with orientation sensing. The multi-touch orientation sensing input device may enhance task performance efficiency. The multi-touch orientation sensing input device may include a device body that is partially enclosed or completely enclosed by a multi-touch sensor. The multi-touch orientation sensing input device may further include an inertia measurement unit that is disposed on the device body, The inertia measurement unit may measures a tilt angle of the device body with respect to a horizontal surface, as well as a roll angle of the device body along a length-wise axis of the device body with respect to an initial point on the device body.

The invention consists of a method of real-time tracking of production schedules and timetables for one or more homebuilding developments, comprising: a) assigning one or more mobile devices to one or more users associated with projects and lots, the mobile devices providing access to project and lot information, including: lots for completion for each project, tasks for completion for each lot, assignment of suppliers and material to specific tasks, projected and actual times for completion of tasks, contact information for suppliers and invoicing information for payment of purchase orders upon task completion; and each mobile device capable of operating independently without a continuous connection to a central system; b) tracking performance of production tasks for each project via real-time monitoring by the users; c) reporting task performance data to a central ERP system and comparing real-time performance of the production tasks to scheduled timetables for the production tasks; d) enabling modification and updating of scheduled timetables for production tasks based on performance data for the production tasks and additional real-time input from the individuals; e) coordinating compensation for production activities with the performance data, including enabling payment for completed tasks from the mobile devices via purchase orders; f) synchronizing, on a sequential basis, updates to scheduled timetables and other information between the mobile devices and the ERP system.

The invention discloses a self-learning load prediction based cluster on-demand starting method, which includes the following steps of receiving a task from a user by management nodes and predicting load of the task according to historic load information; computing increased CPU (central processing unit) utilization rate after the task is dispatched to any one of computing nodes; searching and selecting an underloading computing node in the computing nodes; selecting a dormant computing node to wake up if the underloading computing node is not found; dispatching the task on the selected computing node; building a new thread to execute the task after the computing node receives the task; feeding back execution results of the task to the management nodes after the task is completed, feeding load information of the task back to the management nodes to be stored in historic load information; and setting the computing nodes without loading tasks in a certain time into dormancy by the management nodes at regular intervals. Power consumption of the integral cluster is reduced without affecting task performances by the self-learning load prediction based cluster on-demand starting method.

A robotic machine assembly includes a movable robotic arm configured to perform an assigned task that involves moving toward, engaging, and manipulating a target object of a vehicle. The assembly also includes a communication circuit configured to receive manipulation parameters for the target object from a remote database. The manipulation parameters are specific to at least one of the vehicle or a vehicle class in which the vehicle belongs. The assembly also includes one or more processors configured to generate a task performance plan for the robotic arm based on the manipulation parameters. The task performance plan includes prescribed forces to be exerted by the robotic arm on the target object to manipulate the target object. The one or more processors also are configured to drive movement of the robotic arm during performance of the assigned task according to the task performance plan.

The invention relates to a four-rotor multipurpose flying robot which comprises rotorcrafts and a control device, wherein each rotorcraft comprises a base plate, propellers, a wireless signal transceiver, a driving device, a controller and an electric energy storage device; the propellers are in transmission connection with the driving devices through transmission mechanisms; the driving devices and the wireless signal transceivers are electrically connected with the controllers; the controllers are electrically connected with the electric energy storage devices; an anti-collision ring is arranged on the outer side of the propellers of each rotorcraft; the anti-collision rings are fixedly connected to the upper sides of the four corners of the corresponding base plate; an ultrasonic sensor is arranged on the outer wall of one side, away from each base plate, of the corresponding anti-collision ring; the ultrasonic sensors are electrically connected with the controllers; support legs are fixedly arranged on the lower sides of the four corners of each base plate. According to the four-rotor multipurpose flying robot, the ultrasonic sensors are arranged on conventional rotorcrafts, so that the probability of collision of the flying robot in a flying process is reduced, the controllability of the flying robot s improved, meanwhile, flying of the flying robot in a narrow passage is facilitated, and task performance efficiency is improved.

The invention discloses an embedded type control system based on upper limb exoskeleton assisting robots. Each upper limb exoskeleton assisting robot is mainly composed of two single-arm components same in structure and a back support, and the single-arm components are formed by elbow joints and shoulder joints in sequence from bottom to top. The embedded type control system further comprises an ARM microprocessor module, a DSP microcontroller module, an ARM signal conditioning module, a DSP signal conditioning module, a power module, two operator movement intention detection sensors, four angular displacement sensors and four driving units same in structure. The ARM microprocessor module is connected with the DSP microcontroller module through a CAN bus, and the four driving units are connected with exoskeleton mechanisms and drive the exoskeleton mechanisms to move. The embedded type control system based on the upper limb exoskeleton assisting robots is an exoskeleton assisting robot embedded type control platform which is complete in function and easy to develop and maintain, and has the advantages of being high in real-time response speed, high in real-time multi-task performance, high in driving capacity, low in power dissipation, good in universal expandability, small and the like.

The present invention is directed to system and process for inputting, tracking, monitoring, and displaying the progress and status of the tasks within a project. The system is comprised of an application server, having a team directory and a project database, in communication with a member client and a manager client over a network. A manager client is configured with a plurality of interfaces to input users, create an adaptive, group based permission structure, select team members, and input tasks. The permissions structure allows a team member to be assigned to multiple groups with differing permission for different project functions. The system determines an effective permission based on the multiple group membership. The member client is configured with a plurality of interfaces to create and update task information. The manager client is further configured with a plurality of interfaces to monitor and input project information in response to project events and information. Specifically, the system allows a client to input a dependency hold status, which is visible to the project manager, the person creating the dependency, and other team members, reducing interference with task performance for redundant communication.

Disclosed is a method of efficiently allocating resources in a cloud computing system of the High-Throughput Computing (HTC) field. In more detail, a cloud resource allocation model is proposed in which accumulated job histories are analyzed, a correlation between a performance factor and the job properties is extracted, a factor which is greatly influential in a task performance is identified based on the result of the analyzing and the extracting and is applied to subsequent resource allocations, and reanalysis is performed adaptively.

A novel method of using task fingerprinting to predict outcome measures such quality, errors, and the likelihood of cheating, particularly as applied to crowd sourced tasks. The technique focuses on the way workers work rather than the products they produce. The technique captures behavioral traces from online crowd workers and uses them to build predictive models of task performance. The effectiveness of the approach is evaluated across three contexts including classification, generation, and comprehension tasks.

Techniques to facilitate task performance in an industrial automation environment are disclosed herein. In at least one implementation, an organizational role of a user of a computing system is identified. A set of tasks for the user is determined based on the organizational role of the user. Relative display sizes are assigned to each task in the set of tasks based on a frequency of use of each task. Each task in the set of tasks is displayed according to their relative display sizes on a display system of the computing system.

The invention discloses a complete-vehicle control method and a complete-vehicle controller of an intelligent vehicle. The method includes the steps that after a BSP is initialized and a system is initialized, a main task of the system is created; after system parameters are initialized, unit sub-tasks are created in the main task of the system; according to the priorities of the unit sub-tasks, time slice round-robin scheduling is performed; a time slice comprises a preset mode and/or a user-defined mode. Different task priorities can be distributed among the unit sub-tasks of the vehicle according to the importance of events, time slice round-robin scheduling is adopted for circulation, operation time of all the tasks is reasonably distributed, the requirement for real-time performance is met, in addition, the multi-task performance can be used for integrating part of intelligent unit modules into the complete-vehicle controller, in this way, the cost of each unit module is lowered, space inside the vehicle is saved, and communication faults among the modules are reduced.

Described is a technique for managing a workflow of human intelligence tasks based on task performance. When a large batch of tasks is performed continuously by a worker, task performance may decline. To lessen these consequences and improve overall task performance, the techniques described herein may adjust the type of tasks provided during a workflow. These adjustments may include providing a workflow interruption in the form of a different type of task or a break activity. These interruptions may switch between conceptual and perceptual activities in order to refresh the user and aid in alleviating the negative consequences of repetitive tasks such as physical and cognitive fatigue.

The present application discloses a location based task management method. A computational device obtains first location information concerning one or more geographical locations where a first client device has been located, and assigns a task to the first client device based on the one or more geographical locations. The task includes a task performance location. The computational device then receives from the first client device a first message that includes second location information corresponding to the task performance location and at least one additional information item. The at least one additional information item is captured by first client device at or near the task performance location after completing the task. The progress of the task is then managed based on the second location information, the at least one additional information item and a time difference between the assignment of the task and the receipt of the first message.

A task to be performed using an industrial vehicle is defined and segmented into segments including a start segment and an end segment. The performance of the industrial vehicle while the industrial vehicle performs the segments is measured, and a target score for the task based on an extrinsic factor that is in effect at least one time during performance of the task is defined. The measured performance of the industrial vehicle during the segments is aggregated to create a task performance score, which is evaluated to the target score to create a task evaluation.

The invention discloses a method and a device for testing the performance of electronic equipment. The method for testing the performance of the electronic equipment comprises the steps of obtaining a test beginning instruction, responding to the test beginning instruction and respectively testing items to be tested, wherein the items to be tested at least comprise the virtual machine performance and the multi-task performance. Testing of the items to be tested comprises the steps of executing testing of the virtual machine performance, obtaining a first execution result, determining a first testing result corresponding to the virtual machine performance according to the first execution result, executing testing of the multi-task performance after the first execution result is obtained, obtaining a second execution result, and determining a second testing result corresponding to the multi-task performance according to the second execution result. According to the scheme, through the reasonable item testing sequences, the testing accuracy of the electronic equipment can be improved.

The invention discloses a feature subdivision method for call center customer service staff in mass data. The feature subdivision method includes: acquiring a preset number of workers; determining a cluster index, and determining data corresponding to the cluster index, of each worker as cluster index data of the worker; performing clustering through a K-Means algorithm according to the cluster index data of each worker so as to obtain a cluster result; and dividing the workers into different classes according to the cluster result to obtain a group result. A call center work management method can automatically adapt worker subdivision work in the mass data, is high in accuracy, and can avoid the situations that classification based on subjective experience does not confirm with actual task performance of the workers.

The invention discloses a feature map enhancement method and device of a convolutional neural network, equipment and a medium. The method comprises the following steps of performing convolution operation on an input original image; obtaining a corresponding multi-layer feature map; feature maps for a layer, grouping the data according to channel dimensions; obtaining multiple sub-feature maps, targeting each sub-feature map, performing global average pooling and global maximum pooling parallel processing by using an embedded spatial grouping enhanced SGE module; obtaining two corresponding channel dimension vectors; obtaining two corresponding channel dimension vectors according to the two corresponding channel dimension vectors; obtaining an attention enhancement factor of each channel inthe corresponding sub-feature map; according to the attention enhancement factor and the corresponding sub-feature map, obtaining the attention feature map obtaining the enhanced feature map corresponding to a certain layer of feature map according to all enhanced sub-feature maps, thereby better expressing the semantic information of the importance degree between sub-feature map channels, and improving the task performances of image classification, segmentation and detection of the convolutional neural network.

The invention discloses a self-adapting automation method based on brain function state. The self-adapting automation method comprises the steps of: determining the arrangement of an encephalogram electrode, a near infrared optical spectrum light source and a near infrared optical spectrum probe; establishing an artificial neural network model according to a linear characteristic parameter, a non-linear characteristic parameter, an oxyhemoglobin saturation index and a simulative task performance index, and optimizing the artificial neural network model through a genetic algorithm to obtain a cognitive function state detecting model; determining whether adjusting the task distribution mode of a person and an automatic system and early warning an operator according to a real-time cognitive function state index, a task demand index, a cognitive function state index warning threshold value and a state duration threshold value; and if so, adjusting the task distribution mode of the person and the automatic system, early warning the operator, and ending the process. Compared with the traditional automatic man-machine system, the self-adapting automation method disclosed by the invention distributes the tasks in a self-adapting manner to reduce the occurrence rate of human errors and effectively improve the working efficiency and safety of the man-machine system.