Secure Transmission for Relay Wiretap Channels in the Presence of Spatially Random Eavesdroppers

We propose a secure transmission scheme for a relay wiretap channel, where a source communicates with a destination via a decode-and-forward relay in the presence of spatially random-distributed eavesdroppers. We assume that the source is equipped with multiple antennas, whereas the relay, the destination, and the eavesdroppers are equipped with a single antenna each. In the proposed scheme, in addition to information signals, the source transmits artificial noise signals in order to confuse the eavesdroppers. With the target of maximizing the secrecy throughput of the relay wiretap channel, we derive a closed-form expression for the transmission outage probability and an easy-to-compute expression for the secrecy outage probability. Using these expressions, we determine the optimal power allocation factor and wiretap code rates that guarantee the maximum secrecy throughput, while satisfying a secrecy outage probability constraint. Furthermore, we examine the impact of source antenna number on the secrecy throughput, showing that adding extra transmit antennas at the source brings about a significant increase in the secrecy throughput.Comment: 7 pages, 5 figures, accepted by IEEE Globecom 2015 Workshop on Trusted Communications with Physical Layer Securit

Recurrent Multimodal Interaction for Referring Image Segmentation

In this paper we are interested in the problem of image segmentation given natural language descriptions, i.e. referring expressions. Existing works tackle this problem by first modeling images and sentences independently and then segment images by combining these two types of representations. We argue that learning word-to-image interaction is more native in the sense of jointly modeling two modalities for the image segmentation task, and we propose convolutional multimodal LSTM to encode the sequential interactions between individual words, visual information, and spatial information. We show that our proposed model outperforms the baseline model on benchmark datasets. In addition, we analyze the intermediate output of the proposed multimodal LSTM approach and empirically explain how this approach enforces a more effective word-to-image interaction.Comment: To appear in ICCV 2017. See http://www.cs.jhu.edu/~cxliu/ for code and supplementary materia

Training and Validation of the Fast PCRTM_Solar Model

In this work, we extended PCRTM to including the contribution from solar radiation, including the nonlocal thermal equilibrium (NLTE) effect

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available

Spatio-temporal variations and influencing factors of polycyclic aromatic hydrocarbons in atmospheric bulk deposition along a plain-mountain transect in western China

Ten atmospheric bulk deposition (the sum of wet and dry deposition) samplers for polycyclic aromatic hydrocarbons (PAHs) were deployed at a plain-mountain transect (namely PMT transect, from Daying to Qingping) in Chengdu Plain, West China from June 2007 to June 2008 in four consecutive seasons (about every three months). The bulk deposition fluxes of ∑15-PAHs ranged from 169.19 μg m−2 yr−1 to 978.58 μg m−2 yr−1 with geometric mean of 354.22 μg m−2 yr−1. The most prevalent PAHs were 4-ring (39.65%) and 3-ring (35.56%) PAHs. The flux values were comparable to those in rural areas. Higher fluxes of total PAHs were observed in the middle of PMT transect (SL, YX and JY, which were more urbanized than other sites). The seasonal deposition fluxes in the sampling profile indicated seasonality of the contaminant source was an important factor in controlling deposition fluxes. PAHs bulk deposition was negatively correlated with meteorological parameters (temperature, wind speed, humidity, and precipitation). No significant correlations between soil concentrations and atmospheric deposition were found along this transect. PAHs in soil samples had combined sources of coal, wood and petroleum combustion, while a simple source of coal, wood and grass combustion for bulk deposition. There were significant positive correlation relationship (p < 0.05) between annual atmospheric bulk deposition and local PAHs emission, with biomass burning as the major contribution to the total emission of PAHs. This transect acts as an important PAHs source rather than being a sink according to the ratio of deposition/emission. Mountain cold trap effect existed in this transect where the altitude was higher than 1000 m. Long-range transport had an impact on the bulk deposition in summer. And this transect was a source to Tibetan only in summer. The forward trajectory analysis showed most air masses did not undergo long-range transport due to the blocking effect of surrounding mountains. Only a few air masses (<10%) arrived at the eastern and northern region of China or farther regions via long-range transport

A New Dynamic Path Planning Approach for Unmanned Aerial Vehicles

Dynamic path planning is one of the key procedures for unmanned aerial vehicles (UAV) to successfully fulfill the diversified missions. In this paper, we propose a new algorithm for path planning based on ant colony optimization (ACO) and artificial potential field. In the proposed algorithm, both dynamic threats and static obstacles are taken into account to generate an artificial field representing the environment for collision free path planning. To enhance the path searching efficiency, a coordinate transformation is applied to move the origin of the map to the starting point of the path and in line with the source-destination direction. Cost functions are established to represent the dynamically changing threats, and the cost value is considered as a scalar value of mobile threats which are vectors actually. In the process of searching for an optimal moving direction for UAV, the cost values of path, mobile threats, and total cost are optimized using ant optimization algorithm. The experimental results demonstrated the performance of the new proposed algorithm, which showed that a smoother planning path with the lowest cost for UAVs can be obtained through our algorithm. (PDF) A New Dynamic Path Planning Approach for Unmanned Aerial Vehicles. Available from: https://www.researchgate.net/publication/328765418_A_New_Dynamic_Path_Planning_Approach_for_Unmanned_Aerial_Vehicles [accessed Nov 20 2018]

Extremal oriented graphs avoiding 1-subdivision of an in-star

An oriented graph is a digraph obtained from an undirected graph by choosing an orientation for each edge. Given a positive integer $n$ and an oriented graph $F$, the oriented Tur$\acute{\rm a}$n number $ex_{ori}(n,F)$ is the maximum number of arcs in an $F$-free oriented graph of order $n$. In this paper, we investigate the oriented Tur$\acute{\rm a}$n number $ex_{ori}(n, \overrightarrow{S_{k,1}} )$, where $\overrightarrow{S_{k,1}}$ is the $1$-subdivision of the in-star of order $k+1$. We determine $ex_{ori}(n,\overrightarrow{S_{k,1}})$ for $k=2,3$ as well as the extremal oriented graphs. For $k\ge 4$, we establish a lower bound and an upper bound on $ex_{ori}(n,\overrightarrow{S_{k,1}})$