The problem of blind noise level estimation arises in many image processing applications, such as denoising, compression, and segmentation. In this paper, we propose a new noise level estimation method on the basis of principal component analysis of image blocks. We show that the noise variance can be estimated as the smallest eigenvalue of the image block covariance matrix. Compared with 13 existing methods, the proposed approach shows a good compromise between speed and accuracy. It is at least 15 times faster than methods with similar accuracy, and it is at least two times more accurate than other methods. Our method does not assume the existence of homogeneous areas in the input image and, hence, can successfully process images containing only textures.

In dense IEEE 802.11 networks, improving the efficiency of contention-based media access control is an important and challenging issue. Recently, the IEEE802.11ah Task Group has discussed a group-synchronized distributed coordination function (GS-DCF) for densely deployed wireless networks with a large number of stations. By using the restricted access window (RAW) and RAW slots, the GS-DCF is anticipated to improve the throughput substantially, primarily due to relieving the channel contention. However, optimizing the MAC configurations for the RAW, i.e., the number and duration of RAW slots, is still an open issue. In this paper, we first build an analytical model to track the performance of the GS-DCF in saturated 802.11 networks. Then, we study and compare the GS-DCF throughput using both centralized and decentralized grouping schemes. The accuracy of our model has been validated with simulation results. It is observed that the GS-DCF obtains a throughput gain of seven times or more over DCF in a network of 512 or more stations. Moreover, it is demonstrated that the decentralized grouping scheme can be implemented with a small throughput loss when compared with the centralized grouping scheme.

Measurements of complete and incomplete fusion cross sections for 6 Li+ 154 Sm have been performed at energies above the Coulomb barrier by the online γ -ray method, to investigate the effect of breakup and inelastic couplings on the complete fusion (CF) of this weakly bound system. We show that inelastic excitation couplings have non-negligible effects, when compared with the breakup effect, for deformed nuclei at energies very close to the Coulomb barrier. The average CF suppression corresponding to dynamic breakup effects was found to be around 35%. The total fusion cross section is not affected by the breakup coupling. A comparison between the 6 Li-induced CF suppression for three different samarium isotopes shows that the breakup effect is larger for the more spherical isotope.

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Abstract-This paper presents methodologies for deriving reliability performance of wireless communication networks to support demand response (DR) control. First, the impact of communication impairments on a direct DR control program is investigated. Second, the outage probability of a wireless link is modelled and quantified, considering the multipath fading, shadowing, and random path loss given the location distribution of smart meters. Third, the distributions of packet delivery ratio are derived for two wireless network architectures: the single-hop infrastructure-based network and the multi-hop mesh network. Simulation results verify the above reliability models and provide important insights on the coverage of wireless communication networks considering the reliability requirements of DR programs.

Back-streaming neutrons through the incoming proton channel at the spallation target station of China Spallation Neutron Source (CSNS) has been exploited as a white neutron beam line (so-called Back-n), and a number of spectrometers for nuclear data measurements have been planned. With a thick tungsten target and modest moderation by the cooling water through the target

Linear sensor networks (LSNs) have recently attracted increasing attention due to the vast requirements on the monitoring and surveillance of a structure or area with a linear topology. However, there is little work on the network modeling and analysis based on a duty-cycling MAC protocol for LSNs. In this paper, we model a duty-cycling MAC with a pipelinedscheduling feature for an LSN, where each node is responsible for monitoring a certain area and can generate packets according to its sensed results. Based on the model, we analyze the network performance in terms of the system throughput, active time ratio per cycle of each node, and packet delivery latency. Through the extensive OPNET-based simulations, we validate the model and reveal the dependency of the network performance on various system parameters. Besides enabling the effective estimation of the protocol performance by using our model, we believe that our model and analysis could provide an insightful understanding on the behavior of a duty-cycling MAC protocol and aid its design and optimization for a multi-hop LSN.

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