Why Keep Silent Online? Voices from Stay-at-home Postgraduate Students

Online classroom silence is an overlooked site of research irrespective of the growing popularity of online teaching in today’s education. Against this background, this study showcases why a group of postgraduate students keep silent in their online classes through classroom observation, stimulated recall interviews and in-depth interviews. Reasons found are classified into three categories: the peculiarity of online class, the uniqueness of postgraduate academic lesson, and other general reasons resembling the ones in the traditional classroom. In addition, these factors are found to be interconnected and sometimes exerting both positive and negative effects; unexpectedly, the factor of ‘losing face’, contrary to previous studies, is trivial in contributing to postgraduate students’ online-classroom silence

Spectrum Sharing between Cooperative Relay and Ad-hoc Networks: Dynamic Transmissions under Computation and Signaling Limitations

This paper studies a spectrum sharing scenario between a cooperative relay network (CRN) and a nearby ad-hoc network. In particular, we consider a dynamic spectrum access and resource allocation problem of the CRN. Based on sensing and predicting the ad-hoc transmission behaviors, the ergodic traffic collision time between the CRN and ad-hoc network is minimized subject to an ergodic uplink throughput requirement for the CRN. We focus on real-time implementation of spectrum sharing policy under practical computation and signaling limitations. In our spectrum sharing policy, most computation tasks are accomplished off-line. Hence, little real-time calculation is required which fits the requirement of practical applications. Moreover, the signaling procedure and computation process are designed carefully to reduce the time delay between spectrum sensing and data transmission, which is crucial for enhancing the accuracy of traffic prediction and improving the performance of interference mitigation. The benefits of spectrum sensing and cooperative relay techniques are demonstrated by our numerical experiments.Comment: 5 pages, 3 figures, to appear in IEEE International Conference on Communications (ICC 2011

6,8-Di-tert-butyl-3-(4-nitro­phen­yl)-2H-chromen-2-one

The title compound, C23H25NO4, was synthesized by the reaction of 2-(4-nitro­phen­yl)acetonitrile and 3,5-di-tert-butyl-2-hydroxy­benzaldehyde. The dihedral angle formed by the benzene ring and the mean plane through the benzopyran­one ring system is 35.57 (5)°. The nitro group is almost coplanar with the attached benzene ring [dihedral angle = 5.19 (15)°]. The crystal packing is stabilized by an inter­molecular C—H⋯O hydrogen-bond inter­action

Optimal Distributed Resource Allocation for Decode-and-Forward Relay Networks

This paper presents a distributed resource allocation algorithm to jointly optimize the power allocation, channel allocation and relay selection for decode-and-forward (DF) relay networks with a large number of sources, relays, and destinations. The well-known dual decomposition technique cannot directly be applied to resolve this problem, because the achievable data rate of DF relaying is not strictly concave, and thus the local resource allocation subproblem may have non-unique solutions. We resolve this non-strict concavity problem by using the idea of the proximal point method, which adds quadratic terms to make the objective function strictly concave. However, the proximal solution adds an extra layer of iterations over typical duality based approaches, which can significantly slow down the speed of convergence. To address this key weakness, we devise a fast algorithm without the need for this additional layer of iterations, which converges to the optimal solution. Our algorithm only needs local information exchange, and can easily adapt to variations of network size and topology. We prove that our distributed resource allocation algorithm converges to the optimal solution. A channel resource adjustment method is further developed to provide more channel resources to the bottleneck links and realize traffic load balance. Numerical results are provided to illustrate the benefits of our algorithm