Coverage optimization algorithm based on VF-CS in mobile sensor network

A random placement of large-scale sensor network in the outdoor environment often causes low coverage.An area coverage optimization algorithm of mobile sensor network (MSN) based on virtual force perturbation and Cuckoo search (VF-CS) was proposed.Firstly,the virtual force of the sensor nodes within the Thiessen polygon was analyzed based on the partitioning of Voronoi diagram of the monitoring area.Secondly,the force of polygon vertices and neighbor nodes was taken as the perturbation factor for updating the node’s location of the Cuckoo search (CS).Finally,the VF-CS guided the node to move so as to achieve the optimal coverage.The simulation results demonstrate that the proposed algorithm has higher coverage and shorter average moving distance of nodes than the Voronoi diagram based algorithms in literatures.     

面向多源数据融合的稀疏表示目标跟踪

传统的基于稀疏表示的目标跟踪方法主要利用目标的灰度特征构建稀疏表示模型。由于灰度特征对光照变化敏感，这会影响目标跟踪在复杂场景下的鲁棒性。基于多源数据融合的目标跟踪可以明显提升目标跟踪鲁棒性，但如何有效融合不同维度，不同类型的多源目标特征成为基于多源数据融合的目标跟踪所要解决的关键问题。提出了一个基于目标状态以及灰度特征的稀疏表示目标跟踪方法。所提出的方法可通过基于核函数表示的稀疏表示模型，在探究目标状态以及灰度特征相关性的基础上，将两种不同维度的特征进行有效融合，提升目标跟踪在复杂场景下的鲁棒性。     

Shape transformer nets: Generating viewpoint-invariant 3D shapes from a single image

Single-view 3D shapes generation has achieved great success in recent years. However, current methods always blind the learning of shapes and viewpoints. The generated shape only fit the observed viewpoints and would not be optimal from unknown viewpoints. In this paper, we propose a novel encoder–decoder based network which contains a disentangled transformer to generate the viewpoint-invariant 3D shapes. The differentiable and parametric Non-uniform B-spline (NURBS) surface generation and 3D-to-3D viewpoint transformation are incorporated to learn the viewpoint-invariant shape and the camera viewpoint, respectively. Our new framework allows us to learn the latent geometric parameters of shapes and viewpoints without knowing the ground truth viewpoint. That can simultaneously generate camera-viewpoint and viewpoint-invariant 3D shapes of the object. We analyze the effects of disentanglement and show both quantitative and qualitative results of shapes generated at various unknown viewpoints.     

增强现实中基于位置安全性的LBS位置隐私保护方法

为了解决基于位置的服务(LBS)和增强现实(AR)技术快速发展带来的用户位置隐私泄露的隐患,分析了现有的位置隐私保护方法的优缺点,提出基于位置安全性的位置隐私保护方法。将区域安全度和伪装区域引入该方法中,将提示某区域是否需要保护这一度量标准定义为区域安全度,非安全区域(即需要给予保护的区域)的区域安全度设置为1,安全区域(即不需要保护的区域)设置为0,通过扩大区域安全度和识别等级来计算位置安全度。实验结果表明,该方法与未引入位置安全性的方法相比降低了平均定位误差,提高了平均安全性,从而有效地保护了用户的位置隐私,提高了LBS的服务质量。     

Energy efficiency optimization for HCNs based on small base station transmission power allocation

In the research of green communication, considering the base station (BS) power allocation from the perspective of energy efficiency (EE) is meaningful for heterogeneous cellular networks (HCNs) optimization. The EE of two-tier HCNs was analyzed and a new method for the network EE optimization was proposed by adjusting the small BS transmitting power. First, the HCNs ware modeled by homogeneous Poisson point processes (PPPs), and the coverage probability of BSs in each tier was derived. Second, according to the definition of EE, and the closed-form of EE was given by deriving the total power consumption and total throughput of HCNs respectively. At last, the analytical performance of the EE of HCNs on the small BS transmission power was analyzed, and a small BS power optimization algorithm was proposed to maximize the EE. Simulation results show that, the transmission power of small BS has a significant impact on the EE of HCNs. Furthermore, by optimizing the transmission power of small BS, the EE of HCNs can be improved effectively.     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.     

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.     

Thermal reliabilities of Sn-0.5Ag-0.7Cu-0.1Al2O3/Cu solder joint

The effects of trace addition of Al₂O₃ nanoparticles (NPs) on thermal reliabilities of Sn-0.5Ag-0.7Cu/Cu solder joints were investigated. Experimental results showed that trace addition of Al₂O₃ NPs could increase the isotheraml aging (IA) and thermal cyclic (TC) lifetimes of Sn-0.5Ag-0.7Cu/Cu joint from 662 to 787 h, and from 1597 to 1824 cycles, respectively. Also, trace addition of Al₂O₃ NPs could slow down the shear force reduction of solder joint during thermal services, which was attributed to the pinning effect of Al₂O₃ NPs on hindering the growth of grains and interfacial intermetallic compounds (IMCs). Theoretically, the growth coefficients of interfacial IMCs in IA process were calculated to be decreased from 1.61×10^-10 to 0.79×10^-10 cm²/h in IA process, and from 0.92×10^-10 to 0.53×10^-10 cm²/h in TC process. This indicated that trace addition of Al₂O₃ NPs can improve both IA and TC reliabilities of Sn-0.5Ag- 0.7Cu/Cu joint, and a little more obvious in IA reliability.