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
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
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
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。
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.
