Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mo...Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless chan- nels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First （SMSEF） algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.展开更多
In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation...In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation results show that the performance of our presented mechanism in this paper is greatly improved, much better than that of the other three mechanisms： earliest deadline first （EDF）, highest value first （HVF） and highest density first （HDF）, under the same conditions of all nominal loads and task type proportions.展开更多
The purpose of the paper is to study retention of vocabulary acquired incidentally on task-induced involvement by senior middle school students. Grade two of senior middle students participated in the experiments, tes...The purpose of the paper is to study retention of vocabulary acquired incidentally on task-induced involvement by senior middle school students. Grade two of senior middle students participated in the experiments, testing whether retention of vocabulary acquired incidentally is contingent on amount of task-induced involvement.Using short-and long term, namely immediate posttest and delayed posttest, retention of twelve unfamiliar words was investigated in three learning tasks (reading, reading plus fill-in and writing) with varying degrees of “involvement load”- various combinations of need, search and evaluation. The results of the experiment partially support the Involvement Load Hypothesis: retention in the writing group was higher than that in the reading plus fill-in group; retention in the reading plus fill-in group was higher than that in the reading group. The results are discussed in light of the construct of task-induced involvement.展开更多
Subjective scales have different kinds of applicability in diverse fields.This study intends to implement a quantitative approach to determine the applicability of subjective scales in manual as-sembly work and evalua...Subjective scales have different kinds of applicability in diverse fields.This study intends to implement a quantitative approach to determine the applicability of subjective scales in manual as-sembly work and evaluate the cognitive load of assembly workers.A multi-scale research paradigm based on subjective evaluation method is proposed.Three typical task stages are extracted from the process of assembly work.The National Aeronautics and Space Administration Task Load Index(NASA-TLX)scale,PAAS scale and Workload Profile Index Ratings(WP)scale are selected for the design of 3×3 multi-factor mixed experiment.The power spectrum density(PSD)characteris-tics of electroencephalogram(EEG)are utilized to identify the difficulty levels of the three task sta-ges.The relevant indicators of scale applicability are assessed.The results show that in terms of sensitivity,NASA-TLX scale reaches the highest sensitivity(F=999.137,P=0<0.05).In terms of validity,NASA-TLX scale possesses the best concurrent validity(P=0.0255<0.05).In terms of diagnosticity,NASA-TLX scale based on 6 dimensions takes on the best diagnostic performance.In terms of subject acceptability,WP scale performs the worst.According to the analytic hierarchy process(AHP)model,the applicability scores of NASA-TLX scale,PAAS scale and WP scale are determined as 3,2.55 and 1.6714,respectively.Therefore,NASA-TLX scale is regarded as the most suitable subjective evaluation questionnaire for assembly workers,which is also an effective quantitative evaluation method for the cognitive load of assembly workers.展开更多
Fault tolerance has become an important issue in parallel computing. It is often addressed at system level, but application-level approaches receive increasing attention. We consider a parallel programming pattern, th...Fault tolerance has become an important issue in parallel computing. It is often addressed at system level, but application-level approaches receive increasing attention. We consider a parallel programming pattern, the task pool, and provide a fault-tolerant implementation in a library. Specifically, our work refers to lifeline-based global load balancing, which is an advanced task pool variant that is implemented in the GLB framework of the parallel programming language X10. The variant considers side effect-free tasks whose results are combined into a final result by reduction. Our algorithm is able to recover from multiple fail-stop failures. If recovery is not possible, it halts with an error message. In the algorithm, each worker regularly saves its local task pool contents in the main memory of a backup partner. Backups are updated for steals. After failures, the backup partner takes over saved copies and collects others. In case of multiple failures, invocations of the restore protocol are nested. We have implemented the algorithm by extending the source code of the GLB library. In performance measurements on up to 256 places, we observed an overhead between 0.5% and 30%. The particular value depends on the application’s steal rate and task pool size. Sources of performance overhead have been further analyzed with a logging component.展开更多
The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic l...The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.展开更多
This study mainly discussed the effects of three tasks of translating authentic business report on L2 vocabulary learning.160 students were chosen from different majors by a pre-task proficiency test.The findings reve...This study mainly discussed the effects of three tasks of translating authentic business report on L2 vocabulary learning.160 students were chosen from different majors by a pre-task proficiency test.The findings revealed that task 3 was the optimum task in vo-cabulary gain and direct vocabulary learning had a more facilitated power than incidental vocabulary learning in this translation task forthe learners with the lowest level of vocabulary.This study also suggested that the caution of need and evaluation needed to be adjustedand paid for the learners with the lowest vocabulary level.展开更多
Task scheduling is a key problem for the distributed computation. This thesis analyzes receiver initiated(RI) task scheduling algorithm, finds its weakness and presents an improved algorithm PRI algorithm. This algo...Task scheduling is a key problem for the distributed computation. This thesis analyzes receiver initiated(RI) task scheduling algorithm, finds its weakness and presents an improved algorithm PRI algorithm. This algorithm schedules the concurrent tasks onto network of workstation dynamically at runtime, and initiates task scheduling by the node of low load. The threshold on each node can be modified according to the system information which is periodically detected. Meanwhile, the detecting period can be adjusted in terms of the change of the system state. The result of the experiments shows that the PRI algorithm is superior to the RI algorithm.展开更多
负荷预测是综合能源系统(integrated energy system,IES)高效运行的前提,面对综合能源系统多元负荷强耦合相关性、强随机性的特点,单一模型在运行负荷特征提取方面存在不足。为充分利用负荷间的相关性、降低负荷数据的非平稳性、弥补单...负荷预测是综合能源系统(integrated energy system,IES)高效运行的前提,面对综合能源系统多元负荷强耦合相关性、强随机性的特点,单一模型在运行负荷特征提取方面存在不足。为充分利用负荷间的相关性、降低负荷数据的非平稳性、弥补单一模型的不足,提出一种基于TCN-TPABiLSTM组合模型和多任务学习框架的IES多元负荷超短期协同预测方法。首先对负荷间耦合相关性、负荷时间相关性和负荷影响因素进行分析以构建模型输入,再通过变分模态分解将负荷数据分解为一定数量的模态以降低非平稳性,最后以TCN-TPA-BiLSTM组合模型作为多任务学习框架的共享层进行预测。通过实际数据进行验证和对比,结果表明该方法能够充分发挥模型各部分优势,相较于其他模型也获得了更优的结果。展开更多
基金supported by NSFC(No. 61571055)fund of SKL of MMW (No. K201815)Important National Science & Technology Specific Projects(2017ZX03001028)
文摘Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless chan- nels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First （SMSEF） algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.
基金supported by the Shanghai Applied Materials Foundation (Grant No.06SA18)
文摘In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation results show that the performance of our presented mechanism in this paper is greatly improved, much better than that of the other three mechanisms： earliest deadline first （EDF）, highest value first （HVF） and highest density first （HDF）, under the same conditions of all nominal loads and task type proportions.
文摘The purpose of the paper is to study retention of vocabulary acquired incidentally on task-induced involvement by senior middle school students. Grade two of senior middle students participated in the experiments, testing whether retention of vocabulary acquired incidentally is contingent on amount of task-induced involvement.Using short-and long term, namely immediate posttest and delayed posttest, retention of twelve unfamiliar words was investigated in three learning tasks (reading, reading plus fill-in and writing) with varying degrees of “involvement load”- various combinations of need, search and evaluation. The results of the experiment partially support the Involvement Load Hypothesis: retention in the writing group was higher than that in the reading plus fill-in group; retention in the reading plus fill-in group was higher than that in the reading group. The results are discussed in light of the construct of task-induced involvement.
基金the National Natural Science Foundation of China(No.51775325)the Joint Funds of the National Natural Science Foundation of China(No.U21A20121)+1 种基金the Key Research and Development Program of Ningbo(No.2023Z218)the Young Eastern Scholars Program of Shanghai(No.QD2016033).
文摘Subjective scales have different kinds of applicability in diverse fields.This study intends to implement a quantitative approach to determine the applicability of subjective scales in manual as-sembly work and evaluate the cognitive load of assembly workers.A multi-scale research paradigm based on subjective evaluation method is proposed.Three typical task stages are extracted from the process of assembly work.The National Aeronautics and Space Administration Task Load Index(NASA-TLX)scale,PAAS scale and Workload Profile Index Ratings(WP)scale are selected for the design of 3×3 multi-factor mixed experiment.The power spectrum density(PSD)characteris-tics of electroencephalogram(EEG)are utilized to identify the difficulty levels of the three task sta-ges.The relevant indicators of scale applicability are assessed.The results show that in terms of sensitivity,NASA-TLX scale reaches the highest sensitivity(F=999.137,P=0<0.05).In terms of validity,NASA-TLX scale possesses the best concurrent validity(P=0.0255<0.05).In terms of diagnosticity,NASA-TLX scale based on 6 dimensions takes on the best diagnostic performance.In terms of subject acceptability,WP scale performs the worst.According to the analytic hierarchy process(AHP)model,the applicability scores of NASA-TLX scale,PAAS scale and WP scale are determined as 3,2.55 and 1.6714,respectively.Therefore,NASA-TLX scale is regarded as the most suitable subjective evaluation questionnaire for assembly workers,which is also an effective quantitative evaluation method for the cognitive load of assembly workers.
文摘Fault tolerance has become an important issue in parallel computing. It is often addressed at system level, but application-level approaches receive increasing attention. We consider a parallel programming pattern, the task pool, and provide a fault-tolerant implementation in a library. Specifically, our work refers to lifeline-based global load balancing, which is an advanced task pool variant that is implemented in the GLB framework of the parallel programming language X10. The variant considers side effect-free tasks whose results are combined into a final result by reduction. Our algorithm is able to recover from multiple fail-stop failures. If recovery is not possible, it halts with an error message. In the algorithm, each worker regularly saves its local task pool contents in the main memory of a backup partner. Backups are updated for steals. After failures, the backup partner takes over saved copies and collects others. In case of multiple failures, invocations of the restore protocol are nested. We have implemented the algorithm by extending the source code of the GLB library. In performance measurements on up to 256 places, we observed an overhead between 0.5% and 30%. The particular value depends on the application’s steal rate and task pool size. Sources of performance overhead have been further analyzed with a logging component.
基金Natural Science Foundation of China (No.60 173 0 3 1)
文摘The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.
文摘This study mainly discussed the effects of three tasks of translating authentic business report on L2 vocabulary learning.160 students were chosen from different majors by a pre-task proficiency test.The findings revealed that task 3 was the optimum task in vo-cabulary gain and direct vocabulary learning had a more facilitated power than incidental vocabulary learning in this translation task forthe learners with the lowest level of vocabulary.This study also suggested that the caution of need and evaluation needed to be adjustedand paid for the learners with the lowest vocabulary level.
文摘Task scheduling is a key problem for the distributed computation. This thesis analyzes receiver initiated(RI) task scheduling algorithm, finds its weakness and presents an improved algorithm PRI algorithm. This algorithm schedules the concurrent tasks onto network of workstation dynamically at runtime, and initiates task scheduling by the node of low load. The threshold on each node can be modified according to the system information which is periodically detected. Meanwhile, the detecting period can be adjusted in terms of the change of the system state. The result of the experiments shows that the PRI algorithm is superior to the RI algorithm.
文摘负荷预测是综合能源系统(integrated energy system,IES)高效运行的前提,面对综合能源系统多元负荷强耦合相关性、强随机性的特点,单一模型在运行负荷特征提取方面存在不足。为充分利用负荷间的相关性、降低负荷数据的非平稳性、弥补单一模型的不足,提出一种基于TCN-TPABiLSTM组合模型和多任务学习框架的IES多元负荷超短期协同预测方法。首先对负荷间耦合相关性、负荷时间相关性和负荷影响因素进行分析以构建模型输入,再通过变分模态分解将负荷数据分解为一定数量的模态以降低非平稳性,最后以TCN-TPA-BiLSTM组合模型作为多任务学习框架的共享层进行预测。通过实际数据进行验证和对比,结果表明该方法能够充分发挥模型各部分优势,相较于其他模型也获得了更优的结果。
