The Scholar\u27s Robe : Material Culture and Political Power in Early Modern China

「心身 / 身心」と「環境」の哲学 : 東アジアの伝統的概念の再検討とその普遍化の試み, 国際日本文化研究センター, 2016年2月19日-21

Research on Online Engagement in the MOOC Context

Online engagement had become the key measure of leaning performance and satisfaction(Gaojie 2016,). Jiao Jianli (2013).indicated that how to enhance effective online engagement was the key to improve the quality of online learning. Scholars have done lots of researches on the online engagement form the perspectives of teaching resources, technology, interaction and emotion, etc. However, how do learners regulate themselves and implement self regulated strategies to adapt to the online setting, is seldom explored. Do those self regulative strategies enhance the online engagement effectively? Which strategies are indeed helpful? The research explores the underlying mechanism how self regulated strategies impact online engagement based on the questionnaire of 387 college students. Online engagement, a second-order construct , composes of behavioral engagement, cognitive engagement and emotional engagement. Thorough SEM and hypotheses testing, the research finds that time management and peer learning exert the strongest influence on online engagement; rehearsal, organization and metacognitive strategies do produce a direct influence on online engagement, but they cannot enhance the learners’ self efficacy; elaboration, critical thinking and help strategies do not exert direct influence on online engagement. self efficacy fully mediates the relations among them. The research indicates that resource management strategies produce positive and direct influence on online engagement. Online learners shall pay great attention to time management and peer learning to enhance the online learning efficiency while focusing on the traditional cognitive strategies. Keywords: online engagement, cognitive strategy, metacognitve strategy, resource management strategy, self efficacy DOI: 10.7176/JEP/10-6-1

A Dynamic Competition Control Strategy for Freeway Merging Region Balancing Individual Behaviour and Traffic Efficiency

An integrated control strategy is considered in this paper with the aim of solving congestion in freeway merging regions during peak hours. Merging regions discussed in this paper include the mainline and on-ramp. Traditional research mainly focuses on the efficiency of traffic, ignoring the experience of on-ramp drivers and passengers. Accordingly, a dynamic competition control strategy is proposed to balance individual behaviour and traffic efficiency. First, the concept of the congestion index is introduced, which is expressed by the queue length and the speed parameter of the merging region. The congestion index is used to balance the priorities of the vehicles from the mainline and on-ramp into the merging region in order to avoid poor individual behaviour of on-ramp drivers due to the long-time waiting. Additionally, a nonlinear optimal control approach integrating variable speed limits control and ramp metering is proposed to minimize the total time spent and the maximum traffic flow. The integrated control approach proposed in this paper is tested by simulation which is calibrated using field data. The results indicate that the integrated control approach can effectively shorten the total delay and enhance the traffic service level.</p

Research on dynamic load characteristics and active control strategy of electro-mechanical coupling powertrain of drum shearer cutting unit under impact load

In order to extend the service life of the long-chain gear transmission system of a drum shearer, an electro-mechanical coupling model of a drum shearer cutting unit is established. The model considers the dynamic characteristics of the motor, time-varying meshing stiffness, as well as the drum load characteristics. Additionally, the dynamic characteristics and control strategy for suppressing the dynamic load of the gear transmission system under impact load are investigated based on this model. Firstly, the influence of the gear transmission system of the drum shearer cutting unit under impact load is analyzed. Then, on that basis, the active control strategy based on motor torque compensation is proposed to suppress the dynamic load of the gear transmission system caused by mutational external load. Finally, the suppression effect on the dynamic load of the gear transmission system is analyzed. Research results indicate that this control strategy has good control effects to suppress the dynamic load caused by a mutational external load, which confirms the effectiveness of the proposed control strategy

Straggler Mitigation and Latency Optimization in Blockchain-based Hierarchical Federated Learning

Cloud-edge-device hierarchical federated learning (HFL) has been recently proposed to achieve communication-efficient and privacy-preserving distributed learning. However, there exist several critical challenges, such as the single point of failure and potential stragglers in both edge servers and local devices. To resolve these issues, we propose a decentralized and straggler-tolerant blockchain-based HFL (BHFL) framework. Specifically, a Raft-based consortium blockchain is deployed on edge servers to provide a distributed and trusted computing environment for global model aggregation in BHFL. To mitigate the influence of stragglers on learning, we propose a novel aggregation method, HieAvg, which utilizes the historical weights of stragglers to estimate the missing submissions. Furthermore, we optimize the overall latency of BHFL by jointly considering the constraints of global model convergence and blockchain consensus delay. Theoretical analysis and experimental evaluation show that our proposed BHFL based on HieAvg can converge in the presence of stragglers, which performs better than the traditional methods even when the loss function is non-convex and the data on local devices are non-independent and identically distributed (non-IID)