Current Issue : April - June Volume : 2019 Issue Number : 2 Articles : 5 Articles
Existing object trackers are mostly based on correlation filtering and neural network\nframeworks. Correlation filtering is fast but has poor accuracy. Although a neural network can\nachieve high precision, a large amount of computation increases the tracking time. To address this\nproblem, we utilize a convolutional neural network (CNN) to learn object direction. We propose a\ntarget direction classification network based on CNNs that has a directional shortcut to the tracking\ntarget, unlike the particle filter that randomly finds the target. Our network uses an end-to-end\napproach to determine scale variation that has good robustness to scale variation sequences. In the\npretraining stage, the Visual Object Tracking Challenges (VOT) dataset is used to train the network for\nlearning positive and negative sample classification and direction classification. In the online tracking\nstage, the sliding window operation is performed by using the obtained directional information\nto determine the exact position of the object. The network only calculates a single sample, which\nguarantees a low computational burden. The positive and negative sample redetection strategies can\nsuccessfully ensure that the samples are not lost. The one-pass evaluation (OPE) evaluation results of\nthe object tracking benchmark (OTB) demonstrate that the algorithm is very robust and is also faster\nthan several deep trackers....
In this paper,we examine the influence of intercell interference (ICI) on the system outage behaviorwith important derived results in\nthe proposed model of simultaneous wireless information and power transfer (SWIPT) together with the nonorthogonal multiple\naccess (NOMA) using the amplify-and-forward protocol. We derive the closed-form expression of coverage probability for two\nNOMA users as a function of the signal-to-interference-plus-noise ratio (SINR). To fully take into account the effect of ICI, we\nadoptmore practical parameters to evaluate the optimal power splitting coefficient regarding energy harvesting system performance\nanalysis. Furthermore, to consider a more practical scenario, based on the fact that the number of ICI sources can affect wireless\npowered relays, we investigate the average outage probability by considering impacts of the reasonable number of participating ICI....
Weighted priority queueing is a modification of priority queueing that eliminates\nthe possibility of blocking lower priority traffic. The weights assigned to\npriority classes determine the fractions of the bandwith that are guaranteed\nfor individual traffic classes, similarly as in weighted fair queueing. The paper\ndescribes a timed Petri net model of weighted priority queueing and uses discrete-\nevent simulation of this model to obtain performance characteristics of\nsimple queueing systems. The model is also used to analyze the effects of finite\nqueue capacity on the performance of queueing systems....
Due to the high density ofWi-Fi networks, especially in the unlicensed 2.4GHz frequency band, channel assignment has become\na critical duty for achieving a satisfactory user experience. Probably, the main peculiarity of Wi-Fi networks is the partial overlap\nof the radio channels that can be used by access points. For that reason, a number of works avoid cochannel interferences by using\nonly channels which are far enough from each other to have no interferences, the so-called orthogonal channels.However, there is\na range of choices between using the whole spectrum and using only orthogonal channels. In this work we evaluate the influence\nof the choice of channel set in realistic settings, using both optimization and heuristic approaches. Results show that the optimizer\nis not able to achieve better results when using the whole spectrum instead of restricting to only the orthogonal channels. In fact,\nthe optimizer uses mainly the orthogonal channelswhen they are available, while the heuristics considered lose performance when\nmore channels are available.We believe this insight will be useful to design new heuristics forWi-Fi channel assignment....
Several works by the authors have shown that energy consumption in communication\nnetworks does not only depend on the traffic load but on all\nconnected equipment in the network. We have contributed a new mathematical\nmodel and a new energy saving strategy with Software Defined Network\n(SDN) technology [1]. Our Model solution is based on the Modified SPRING\nProtocol (MSP). In this paper, we simulated our work and compared it to that\nof the authors [2] and [3]. The OMNET++ simulator was used for our work.\nThus, the results of the simulations gave a delay that tends to zero, a packet\nloss of the order of 10% and a constant jitter of 4% better than the previous\nauthors....
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