A Fast and Effective Multiple Kernel Clustering Method on Incomplete Data

Multiple kernel clustering is an unsupervised data analysis method that has been used in various scenarios where data is easy to be collected but hard to be labeled.However,multiple kernel clustering for incomplete data is a critical yet challenging task.Although the existing absent multiple kernel clustering methods have achieved remarkable performance on this task,they may fail when data has a high value-missing rate,and they may easily fall into a local optimum.To address these problems,in this paper,we propose an absent multiple kernel clustering(AMKC)method on incomplete data.The AMKC method rst clusters the initialized incomplete data.Then,it constructs a new multiple-kernel-based data space,referred to as K-space,from multiple sources to learn kernel combination coefcients.Finally,it seamlessly integrates an incomplete-kernel-imputation objective,a multiple-kernel-learning objective,and a kernel-clustering objective in order to achieve absent multiple kernel clustering.The three stages in this process are carried out simultaneously until the convergence condition is met.Experiments on six datasets with various characteristics demonstrate that the kernel imputation and clustering performance of the proposed method is signicantly better than state-of-the-art competitors.Meanwhile,the proposed method gains fast convergence speed.

Optimal Power Allocation with Limited Feedback of Channel State Information in Multi-User MIMO Systems

In this paper,an expression for the user’s achievable data rate in the multi-user multiple-input multiple-output(MU-MIMO)system with limited feedback(LF)of channel state information(CSI)is derived.The energy efficiency(EE)is optimized through power allocation under quality of service(QoS)constraints.Based on mathematical equivalence and Lagrange multiplier approach,an energy-efficient unequal power allocation(EEUPA)with LF of CSI scheme is proposed.The simulation results show that as the number of transmitting antennas increases,the EE also increases which is promising for the next generation wireless communication networks.Moreover,it can be seen that the QoS requirement has an effect on the EE of the system.Ultimately,the proposed EEUPA with LF of CSI algorithm performs better than the existing energy-efficient equal power allocation(EEEPA)with LF of CSI schemes.

Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents

Considering dynamical disease spreading network consisting of moving individuals,a new double-layer network is constructed,one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves.On the basis of Markov chains theory,a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment.Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence spreading dynamics.Simulation results show that the increasing of information transmission rate can reduce the scale of disease spreading in some degree.Shortening infection period and strengthening consciousness for self-protection by decreasing individual’s scope of activity both can effectively reduce the final refractory density for the disease but have less effect on the information dissemination.In addition,the increasing of vaccination rate or decreasing of long-range travel can also reduce the scale of disease spreading.

High Performance Electrically Small Huygens Rectennas Enable Wirelessly Powered Internet of Things Sensing Applications:A Review

Far-field wireless power transfer(WPT)is a major breakthrough technology that will enable the many anticipated ubiquitous Internet of Things(IoT)applications associated with fifth generation(5G),sixth generation(6G),and beyond wireless ecosystems.Rectennas,which are the combination of rectifying circuits and antennas,are the most critical components in far-field WPT systems.However,compact application devices require even smaller integrated rectennas that simultaneously have large electromagnetic wave capture capabilities,high alternating current(AC)-to-direct current(DC)(AC-to-DC)conversion efficiencies,and facilitate a multifunctional wireless performance.This paper reviews various rectenna miniaturization techniques such as meandered planar inverted-F antenna(PIFA)rectennas;miniaturized monopole-and dipole-based rectennas;fractal loop and patch rectennas;dielectric-loaded rectennas;and electrically small near-field resonant parasitic rectennas.Their performance characteristics are summarized and then compared with our previously developed electrically small Huygens rectennas that are proven to be more suitable for IoT applications.They have been tailored,for example,to achieve batteryfree IoT sensors as is demonstrated in this paper.Battery-free,wirelessly powered devices are smaller and lighter in weight in comparison to battery-powered devices.Moreover,they are environmentally friendly and,hence,have a significant societal benefit.A series of high-performance electrically small Huygens rectennas are presented including Huygens linearly-polarized(HLP)and circularly-polarized(HCP)rectennas;wirelessly powered IoT sensors based on these designs;and a dual-functional HLP rectenna and antenna system.Finally,two linear uniform HLP rectenna array systems are considered for significantly larger wireless power capture.Example arrays illustrate how they can be integrated advantageously with DC or radio frequency(RF)power-combining schemes for practical IoT applications.

Generating Cartoon Images from Face Photos with Cycle-Consistent Adversarial Networks

The generative adversarial network(GAN)is first proposed in 2014,and this kind of network model is machine learning systems that can learn to measure a given distribution of data,one of the most important applications is style transfer.Style transfer is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image.CYCLE-GAN is a classic GAN model,which has a wide range of scenarios in style transfer.Considering its unsupervised learning characteristics,the mapping is easy to be learned between an input image and an output image.However,it is difficult for CYCLE-GAN to converge and generate high-quality images.In order to solve this problem,spectral normalization is introduced into each convolutional kernel of the discriminator.Every convolutional kernel reaches Lipschitz stability constraint with adding spectral normalization and the value of the convolutional kernel is limited to[0,1],which promotes the training process of the proposed model.Besides,we use pretrained model(VGG16)to control the loss of image content in the position of l1 regularization.To avoid overfitting,l1 regularization term and l2 regularization term are both used in the object loss function.In terms of Frechet Inception Distance(FID)score evaluation,our proposed model achieves outstanding performance and preserves more discriminative features.Experimental results show that the proposed model converges faster and achieves better FID scores than the state of the art.

A Polarization Programmable Antenna Array

Reconfigurable antennas are becoming a major antenna technology for future wireless communications and sensing systems.It is known that,with a single linear polarization(LP)reconfigurable antenna element,a preferred polarization can be produced from a set of multiple polarization states,thus improving the quality of the communication link.This paper presents a new concept of a polarization programmable reconfigurable antenna array that consists of a number of polarization reconfigurable antenna elements with a finite number of possible polarization states.By employing a new optimization strategy and programming the polarization states of all the array elements,we demonstrate that it is possible to realize any desired LP in the vectorial array radiation pattern with accurate control of sidelobe and crosspolarization levels(XPLs),thereby achieving the desired polarization to perfectly match that of the required communications signal.Both numerical and experimental results are provided to prove the concept,and they agree well with each other.

无人机网络中的安全连通性分析（英文）

无人机网络的独特特征包括高动态网络拓扑、高移动性以及野外无线环境可能使得无人机网络容易受到攻击和威胁。本文基于无人机行为、运动模式和无人机之间的信道特征,为无人机网络提出一种新颖的信任模型。该信任模型由直接信任、间接信任、信任集成和信任更新4部分组成。基于信任模型,提出一种无人机网络中安全链路的概念,该概念仅在两个无人机之间既有物理链路又有信任链路时存在。此外,利用两架无人机之间的物理连通概率和安全连通概率,分析无人机网络的连通性。通过随机几何方法,推导得到考虑和不考虑多普勒频偏情况下的物理连通概率和安全连通概率的解析表达式。仿真结果表明,与具有和不具有恶意攻击的物理连接概率相比,提出的信任模型可以保证无人机之间的安全通信和可靠连接,并在无人机网络面临恶意攻击和其他安全隐患时提高网络性能。

Recent Advances in Reconfigurable Antennas at University of Technology Sydney

This paper presents an overview of the recent advances in reconfigurable antennas for wireless communications at University of Technology Sydney.In particular,it reports our latest progress in this research field,including a multi-linear polarization reconfigurable antenna,a pattern reconfigurable antenna with multiple switchable beams,and a combined pattern and polarization reconfigurable antenna.