拉普拉斯加权聚类算法

 本文提出了一种用于聚类分析的加权聚类算法,通过利用拉普拉斯权,将聚类对象之间的结构信息自动转换为对象的权重.由于拉普拉斯权能够描述数据的邻域结构,从而能够更好的聚类.该加权聚类算法在性能上比经典聚类算法有较大改进,还具有对孤立点鲁棒、适合类别不平衡数据聚类、对聚类个数不敏感等优点.人工数据集以及UCI标准数据集上的实验证实了本文算法的可行性和有效性.     

Fast and effective Keypoint-based image copy-move forgery detection using complex-valued moment invariants

Copy-move forgery is one of the most common image tampering schemes, with the potential use for misleading the opinion of the general public. Keypoint-based detection methods exhibit remarkable performance in terms of computational cost and robustness. However, these methods are difficult to effectively deal with the cases when 1) forgery only involves small or smooth regions, 2) multiple clones are conducted or 3) duplicated regions undergo geometric transformations or signal corruptions. To overcome such limitations, we propose a fast and accurate copy-move forgery detection algorithm, based on complex-valued invariant features. First, dense and uniform keypoints are extracted from the whole image, even in small and smooth regions. Then, these keypoints are represented by robust and discriminative moment invariants, where a novel fast algorithm is designed especially for the computation of dense keypoint features. Next, an effective magnitude-phase hierarchical matching strategy is proposed for fast matching a massive number of keypoints while maintaining the accuracy. Finally, a reliable post-processing algorithm is developed, which can simultaneously reduce false negative rate and false positive rate. Extensive experimental results demonstrate the superior performance of our proposed scheme compared with existing state-of-the-art algorithms, with average pixel-level F-measure of 94.54% and average CPU-time of 36.25 s on four publicly available datasets.     

Direct Growth of Germanene at Interfaces between Van der Waals Materials and Ag(111)

Germanene, a 2D honeycomb germanium crystal, is grown at graphene/Ag(111) and hexagonal boron nitride (h-BN)/Ag(111) interfaces by segregating germanium atoms. A simple annealing process in N₂ or H₂/Ar at ambient pressure leads to the formation of germanene, indicating that an ultrahigh-vacuum condition is not necessary. The grown germanene is stable in air and uniform over the entire area covered with a van der Waals (vdW) material. As an important finding, it is necessary to use a vdW material as a cap layer for the present germanene growth method since the use of an Al₂O₃ cap layer results in no germanene formation. The present study also proves that Raman spectroscopy in air is a powerful tool for characterizing germanene at the interfaces, which is concluded by multiple analyses including first-principles density functional theory calculations. The direct growth of h-BN-capped germanene on Ag(111), which is demonstrated in the present study, is considered to be a promising technique for the fabrication of future germanene-based electronic devices.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

Public interest in continued use of Chinese government portals: A mixed methods study

Public adoption of policies detailed on government websites is an important topic in the field of e-government research, and researchers have mainly focused on the key factors that influence initial adoption. However, there has been much less discussion on factors influencing the continued use of government websites. This study identifies and tests a theoretical model that predicts consumers’ intentions to continue using government portals, using a mixed methods approach based on Grounded Theory. To construct a theoretical framework of public interest in continued use of government information portals, we interviewed 56 respondents and coded the interview data. Next, we tested the resulting model using data collected from a questionnaire-based survey of 354 users. The Structural Equation Modeling (SEM) results indicate that continued use is influenced by psychological perception, user characteristics, service parameters of the government portals and the government’s idea. Of these, psychological perception was found to have the strongest effect. These findings enrich the theoretical system of e-government public adoption of intention and have important practical significance for the development of Chinese government portals.     

FGWSO‐TAR: Fractional glowworm swarm optimization for traffic aware routing in urban VANET

In mobile distributed applications, such as traffic alert dissemination, dynamic route planning, file sharing, and so on, vehicular ad hoc network (VANET) has emerged as a feasible solution in recent years. However, the performance of the VANET depends on the routing protocol in accord with the delay and throughput requirements. Many of the routing protocols have been extensively studied in the literature. Although there are exemptions, they escalate research challenges in traffic aware routing (TAR) protocol of VANET. This paper introduces the fractional glowworm swarm optimization (FGWSO) for the TAR protocol of VANET in an urban scenario that can identify the optimal path for the vehicle with less traffic density and delay time. The proposed FGWSO searches the optimal routing path based on the fitness function formulated in this paper. Fractional glowworm swarm optimization is the combination of the GWSO and fractional theory. Moreover, exponential weighted moving average is utilized to predict the traffic density and the speed of the vehicle, which is utilized as the major constraints in the fitness function of the optimization algorithm to find the optimal traffic aware path. Simulation of FGWSO shows the significant improvement with a minimal end‐to‐end delay of 6.6395 seconds and distance of 17.3962 m, respectively, in comparison with the other existing routing approaches. The simulation also validates the optimality of the proposed TAR protocol.     

Clustering‐based resource discovery on Internet‐of‐Things

Resource discovery on Internet‐of‐Things paradigm is an eminent challenge due to data‐specific activities with respect to foraging and sense‐making loops. The prerequisite to deal with the challenge is to process and analyze the data that require resources to be indexed, ranked, and stored in an efficient manner. A novel clustering technique is proposed to resolve the specified challenge. The technique, namely, iterative k‐means clustering algorithm, targets concrete cluster formation using similarity coefficients of vector space model and performs efficient search against matching criteria with respect to complexity. It is simulated on MATLAB, and the obtained results are compared with fuzzy k‐means and fuzzy c‐means clustering algorithm with similarity coefficients of vector space model against exponential increase in the number of resources.     

Game theory-based attack and defense analysis in virtual wireless networks with jammers and eavesdroppers

Dynamic spectrum sharing and cognitive radio networks were proposed to enhance the Radio Frequency (RF) spectrum utilization. However, there are several challenges to realize them in real systems, such as sensing uncertainty causing issues to licensed users, business models for licensed service providers. Wireless virtualization is regarded as a technology that leverages service level agreements to sublease unused or underutilized RF spectrum that addresses aforementioned issues and helps to significantly enhance the utilization of the RF spectrum, offer improved coverage and capacity of networks, enhance network security and reduce energy consumption. With wireless virtualization, wireless networks' physical substrate is shared and reconfigured dynamically between virtual wireless networks through Mobile Virtual Network Operations (MVNOs). Wireless virtualization with dynamic configurable features of Wireless Infrastructure Providers (WIPs), virtualized wireless networks are vulnerable to a multitude of attacks, including jamming attacks and eavesdropping attacks. This paper investigates a means of defense through the employment of coalition game theory when jammers try to degrade the signal quality of legitimate users, and eavesdroppers aim to reduce secrecy rates. Specifically, we consider a virtual wireless network where MVNO users' job is to improve their Signal to Interference plus Noise Ratio (SINR) while the jammers target to collectively enhance their Jammer Received Signal Strength (JRSS), and an eavesdropper's goal is to reduce the overall secrecy rate. Numerical results have demonstrated that the proposed game strategies are effective (in terms of data rate, secrecy rate and latency) against such attackers compared to the traditional approaches.     

基于排队论的路由选择策略研究

针对局域网路由器配置的实际问题,利用排队论相关知识,比较不同方案下的信息传输的平均时间,优化路由设计。将信息传输过程中的路由器分别建模为开的Jackson网络、串联排队网络和取消中间路由的排队网络,比较三种传输网络方式下的信息传输时间,得到最佳的路由选择方案。利用matlab通过蒙特卡洛对传输过程进行仿真,仿真结果验证了理论分析的正确性。