"任务型语言教学"(Task-based Language Teaching)是一种基于任务的教学途径。这种教学方法与教育部2009年最新提出的《高等职业教育英语课程教学要求(试行)(讨论稿)》中的教学目的天然契合,试图以《希望英语》第1册第6单元Tr..."任务型语言教学"(Task-based Language Teaching)是一种基于任务的教学途径。这种教学方法与教育部2009年最新提出的《高等职业教育英语课程教学要求(试行)(讨论稿)》中的教学目的天然契合,试图以《希望英语》第1册第6单元Travel(旅游)为例,探讨笔者在使用Willis的三阶段任务型语言教学框架时从形式到话语的教学过程。展开更多
In order to solve the problem of efficiently assigning tasks in an ad-hoc mobile cloud( AMC),a task assignment algorithm based on the heuristic algorithm is proposed. The proposed task assignment algorithm based on pa...In order to solve the problem of efficiently assigning tasks in an ad-hoc mobile cloud( AMC),a task assignment algorithm based on the heuristic algorithm is proposed. The proposed task assignment algorithm based on particle swarm optimization and simulated annealing( PSO-SA) transforms the dependencies between tasks into a directed acyclic graph( DAG) model. The number in each node represents the computation workload of each task and the number on each edge represents the workload produced by the transmission. In order to simulate the environment of task assignment in AMC,mathematical models are developed to describe the dependencies between tasks and the costs of each task are defined. PSO-SA is used to make the decision for task assignment and for minimizing the cost of all devices,which includes the energy consumption and time delay of all devices.PSO-SA also takes the advantage of both particle swarm optimization and simulated annealing by selecting an optimal solution with a certain probability to avoid falling into local optimal solution and to guarantee the convergence speed. The simulation results show that compared with other existing algorithms,the PSO-SA has a smaller cost and the result of PSO-SA can be very close to the optimal solution.展开更多
A checkpointing scheme for relevant distributed real-time tasks which can be scheduled as a DAG is proposed. A typical algorithm, OSA, is selected for DAG scheduling. A new methods based a new structure, Scheduled Clu...A checkpointing scheme for relevant distributed real-time tasks which can be scheduled as a DAG is proposed. A typical algorithm, OSA, is selected for DAG scheduling. A new methods based a new structure, Scheduled Cluster Tree, is presented to calculate the slack time of each task in the task cluster. In the checkpointing scheme, the optimal checkpoint intervals which minimize the approximated failure probability are derived formally and validated experimentally. The complexity of approximated failure probability is quite small compared with that of the exact probability. Meanwhile, the consistency of the checkpointing is discussed also.展开更多
This work is to observe the performance of PC based robot manipulator under general purpose （Windows）, Soft （Linux） and Hard （RT Linux） Real Time Operating Systems （OS）. The same open loop control system is ob...This work is to observe the performance of PC based robot manipulator under general purpose （Windows）, Soft （Linux） and Hard （RT Linux） Real Time Operating Systems （OS）. The same open loop control system is observed in different operating systems with and without multitasking environment. The Data Acquisition （DAQ, PLC-812PG） card is used as a hardware interface. From the experiment, it could be seen that in the non real time operating system （Windows）, the delay of the control system is larger than the Soft Real Time OS （Linux）. Further, the authors observed the same control system under Hard Real Time OS （RT-Linux）. At this point, the experiment showed that the real time error （jitter） is minimum in RT-Linux OS than the both of the previous OS. It is because the RT-Linux OS kernel can set the priority level and the control system was given the highest priority. The same experiment was observed under multitasking environment and the comparison of delay was similar to the preceding evaluation.展开更多
The task assignment problem of robots in a smart warehouse environment （TARSWE） based on cargo-to-person is investigated. Firstly, the sites of warehouse robots and the order picking tasks are given and the task ass...The task assignment problem of robots in a smart warehouse environment （TARSWE） based on cargo-to-person is investigated. Firstly, the sites of warehouse robots and the order picking tasks are given and the task assignment problem for picking one order is formulated into a mathematical model to minimize the total operation cost. Then a heuristic algorithm is designed to solve the task assignment problem for picking multiple orders. Finally, simulations are done by using the orders data of online bookstore A. The results show that using the heuristic algorithm of this paper to assign robots, the cost was reduced by 2% and it can effectively avoid far route and unbalanced workload of robots. The feasibility and validity of the model and algorithm are verified. The model and algorithm in this paper provide a theoretical basis to solve the TARSWE.展开更多
In order to reduce the scheduling makespan of a workflow,three list scheduling algorithms,namely,level and out-degree earliest-finish-time(LOEFT),level heterogeneous selection value(LHSV),and heterogeneous priority ea...In order to reduce the scheduling makespan of a workflow,three list scheduling algorithms,namely,level and out-degree earliest-finish-time(LOEFT),level heterogeneous selection value(LHSV),and heterogeneous priority earliest-finish-time(HPEFT)are proposed.The main idea hidden behind these algorithms is to adopt task depth,combined with task out-degree for the accurate analysis of task prioritization and precise processor allocation to achieve time optimization.Each algorithm is divided into three stages:task levelization,task prioritization,and processor allocation.In task levelization,the workflow is divided into several independent task sets on the basis of task depth.In task prioritization,the heterogeneous priority ranking value(HPRV)of the task is calculated using task out-degree,and a non-increasing ranking queue is generated on the basis of HPRV.In processor allocation,the sorted tasks are assigned one by one to the processor to minimize makespan and complete the task-processor mapping.Simulation experiments through practical applications and stochastic workflows confirm that the three algorithms can effectively shorten the workflow makespan,and the LOEFT algorithm performs the best,and it can be concluded that task depth combined with out-degree is an effective means of reducing completion time.展开更多
文摘"任务型语言教学"(Task-based Language Teaching)是一种基于任务的教学途径。这种教学方法与教育部2009年最新提出的《高等职业教育英语课程教学要求(试行)(讨论稿)》中的教学目的天然契合,试图以《希望英语》第1册第6单元Travel(旅游)为例,探讨笔者在使用Willis的三阶段任务型语言教学框架时从形式到话语的教学过程。
基金The National Natural Science Foundation of China(No.61741102,61471164,61601122)the Fundamental Research Funds for the Central Universities(No.SJLX_160040)
文摘In order to solve the problem of efficiently assigning tasks in an ad-hoc mobile cloud( AMC),a task assignment algorithm based on the heuristic algorithm is proposed. The proposed task assignment algorithm based on particle swarm optimization and simulated annealing( PSO-SA) transforms the dependencies between tasks into a directed acyclic graph( DAG) model. The number in each node represents the computation workload of each task and the number on each edge represents the workload produced by the transmission. In order to simulate the environment of task assignment in AMC,mathematical models are developed to describe the dependencies between tasks and the costs of each task are defined. PSO-SA is used to make the decision for task assignment and for minimizing the cost of all devices,which includes the energy consumption and time delay of all devices.PSO-SA also takes the advantage of both particle swarm optimization and simulated annealing by selecting an optimal solution with a certain probability to avoid falling into local optimal solution and to guarantee the convergence speed. The simulation results show that compared with other existing algorithms,the PSO-SA has a smaller cost and the result of PSO-SA can be very close to the optimal solution.
文摘A checkpointing scheme for relevant distributed real-time tasks which can be scheduled as a DAG is proposed. A typical algorithm, OSA, is selected for DAG scheduling. A new methods based a new structure, Scheduled Cluster Tree, is presented to calculate the slack time of each task in the task cluster. In the checkpointing scheme, the optimal checkpoint intervals which minimize the approximated failure probability are derived formally and validated experimentally. The complexity of approximated failure probability is quite small compared with that of the exact probability. Meanwhile, the consistency of the checkpointing is discussed also.
文摘This work is to observe the performance of PC based robot manipulator under general purpose （Windows）, Soft （Linux） and Hard （RT Linux） Real Time Operating Systems （OS）. The same open loop control system is observed in different operating systems with and without multitasking environment. The Data Acquisition （DAQ, PLC-812PG） card is used as a hardware interface. From the experiment, it could be seen that in the non real time operating system （Windows）, the delay of the control system is larger than the Soft Real Time OS （Linux）. Further, the authors observed the same control system under Hard Real Time OS （RT-Linux）. At this point, the experiment showed that the real time error （jitter） is minimum in RT-Linux OS than the both of the previous OS. It is because the RT-Linux OS kernel can set the priority level and the control system was given the highest priority. The same experiment was observed under multitasking environment and the comparison of delay was similar to the preceding evaluation.
基金Project Supported： National Natural Science Foundation of China （11131009, 71540028, F012408）, Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality （CIT＆TCD20130327）, and major research project of Beijing Wuzi University.
文摘The task assignment problem of robots in a smart warehouse environment （TARSWE） based on cargo-to-person is investigated. Firstly, the sites of warehouse robots and the order picking tasks are given and the task assignment problem for picking one order is formulated into a mathematical model to minimize the total operation cost. Then a heuristic algorithm is designed to solve the task assignment problem for picking multiple orders. Finally, simulations are done by using the orders data of online bookstore A. The results show that using the heuristic algorithm of this paper to assign robots, the cost was reduced by 2% and it can effectively avoid far route and unbalanced workload of robots. The feasibility and validity of the model and algorithm are verified. The model and algorithm in this paper provide a theoretical basis to solve the TARSWE.
基金The Natural Science Foundation of Hunan Province(No.2018JJ2153)the Scientific Research Fund of Hunan Provincial Education Department(No.18B356)+1 种基金the Foundation of the Research Center of Hunan Emergency Communication Engineering Technology(No.2018TP2022)the Innovation Foundation for Postgraduate of the Hunan Institute of Science and Technology(No.YCX2018A06).
文摘In order to reduce the scheduling makespan of a workflow,three list scheduling algorithms,namely,level and out-degree earliest-finish-time(LOEFT),level heterogeneous selection value(LHSV),and heterogeneous priority earliest-finish-time(HPEFT)are proposed.The main idea hidden behind these algorithms is to adopt task depth,combined with task out-degree for the accurate analysis of task prioritization and precise processor allocation to achieve time optimization.Each algorithm is divided into three stages:task levelization,task prioritization,and processor allocation.In task levelization,the workflow is divided into several independent task sets on the basis of task depth.In task prioritization,the heterogeneous priority ranking value(HPRV)of the task is calculated using task out-degree,and a non-increasing ranking queue is generated on the basis of HPRV.In processor allocation,the sorted tasks are assigned one by one to the processor to minimize makespan and complete the task-processor mapping.Simulation experiments through practical applications and stochastic workflows confirm that the three algorithms can effectively shorten the workflow makespan,and the LOEFT algorithm performs the best,and it can be concluded that task depth combined with out-degree is an effective means of reducing completion time.
