Practical Block-wise Neural Network Architecture Generation

Convolutional neural networks have gained a remarkable success in computer vision. However, most usable network architectures are hand-crafted and usually require expertise and elaborate design. In this paper, we provide a block-wise network generation pipeline called BlockQNN which automatically builds high-performance networks using the Q-Learning paradigm with epsilon-greedy exploration strategy. The optimal network block is constructed by the learning agent which is trained sequentially to choose component layers. We stack the block to construct the whole auto-generated network. To accelerate the generation process, we also propose a distributed asynchronous framework and an early stop strategy. The block-wise generation brings unique advantages: (1) it performs competitive results in comparison to the hand-crafted state-of-the-art networks on image classification, additionally, the best network generated by BlockQNN achieves 3.54% top-1 error rate on CIFAR-10 which beats all existing auto-generate networks. (2) in the meanwhile, it offers tremendous reduction of the search space in designing networks which only spends 3 days with 32 GPUs, and (3) moreover, it has strong generalizability that the network built on CIFAR also performs well on a larger-scale ImageNet dataset.Comment: Accepted to CVPR 201

Online auction-based relay selection for cooperative communication in CR networks

Cognitive radio and cooperative communication are two new network technologies. So, the combination of these two new technologies is a novel solution to solve the problem of spectrum scarcity. Two main challenges exist in the integration of cognitive radio and cooperative communication. First, there is a lack of incentives for the participating wireless devices to serve as relay nodes. Second, there is not an effective relay selection policy. In this paper, we propose an online auction-based relay selection scheme for cooperative communication in cognitive radio (CR) networks. Specifically, we design an auction scheme through adopting stopping theory. The proposed scheme ensures that the primary user (PU) can effectively select a CR relay to transmit its packets in a given time bound. In addition, we have analytically proven the truthfulness and the individual rationality of our online auction scheme. Extensive simulations demonstrate that the proposed relay selection scheme can always successfully and efficiently select a proper relay for a PU and can achieve a higher cooperative communication throughput compared with the conventional schemes

Re-flaring of a Post-Flare Loop System Driven by Flux Rope Emergence and Twisting

In this letter, we study in detail the evolution of the post-flare loops on 2005 January 15 that occurred between two consecutive solar eruption events, both of which generated a fast halo CME and a major flare. The post-flare loop system, formed after the first CME/flare eruption, evolved rapidly, as manifested by the unusual accelerating rise motion of the loops. Through nonlinear force-free field (NLFFF) models, we obtain the magnetic structure over the active region. It clearly shows that the flux rope below the loops also kept rising accompanied with increasing twist and length. Finally, the post-flare magnetic configuration evolved to a state that resulted in the second CME/flare eruption. This is an event in which the post-flare loops can re-flare in a short period of $\sim$16 hr following the first CME/flare eruption. The observed re-flaring at the same location is likely driven by the rapid evolution of the flux rope caused by the magnetic flux emergence and the rotation of the sunspot. This observation provides valuable information on CME/flare models and their prediction.Comment: 11 pages, 4 figures, 1 table, accepted for publication in ApJ Lette

Enabling smartphone-based HD video chats by cooperative transmissions in CRNs

Smartphones have been equipped with the cameras that can shoot HD videos, and the video chat apps such as Skype are becoming popular. We can, therefore, intuitively predict the trend that users are expecting to enjoy HD video chats via utilizing their smartphones. Most of the current Internet services, however, cannot support the live HD video transmissions because of their low uplink rate. In order to overcome this limit, we propose to offload the uplink transmissions to cooperative users via cognitive radio networks. Specifically, we first divide the video stream into several substreams according to the H.264/SVC standard and the cooperative users’ uplink rates. Then, the cooperative users are selected by employing our proposed optimal multiple stopping method. Finally, the substreams are assigned to the selected cooperative users by a 0-1 Knapsack-based allocation algorithm. The simulation results demonstrate that our proposed scheme can successfully support 720P HD video chats

Subway Fire Cause Analysis Model Based on System Dynamics: A Preliminary Model Framework

AbstractThis paper collects typical major subway fire cases in nearly 20 years. Through analysis of these cases, the causes of the fire accidents are summed up. And further the influence factors of these reasons are extracted, including four aspects namely equipment, human, environment and emergency management. On this basis, combined with the relevant principles of system dynamics, the influence of various factors on the happening, spreading and controlling of subway fires are considered. Then, a simulation model of subway fire accident rate is constructed by Vensim. The equations of relevant variables and parameters of the system are given preliminarily