Optimal jamming attack schedule for remote state estimation with two sensors

In cyber-physical systems (CPS), cyber threats emerge in many ways which can cause significant destruction to the system operation. In wireless CPS, adversaries can block the communications of useful information by channel jamming, incurring the so-called denial of service (DoS) attacks. In this paper, we investigate the problem of optimal jamming attack scheduling against remote state estimation wireless network. Specifically, we consider that two wireless sensors report data to a remote estimator through two wireless communication channels lying in two unoverlapping frequency bands, respectively. Meanwhile, an adversary can select one and only one channel at a time to execute jamming attack. We prove that the optimal attack schedule is continuously launching attack on one channel determined based on the system dynamics matrix. The theoretical results are validated by numerical simulations.     

A cognitive TV white space-broadband power line MIMO system for indoor communication networks

Broadband power line communication (BPLC) is a promising solution to satisfy the growing data rate demands for broadband indoor communication networks. However, the BPLC transmission power spectral density (PSD) is restricted in the very high frequency (VHF) band to avoid harmful interference to the existing wireless services. In this paper, a new hybrid system is proposed utilizing BPLC and cognitive radio over TV white space (TVWS) to enhance the system capacity over BPLC in VHF, forming a VHF TVWS BPLC multiple-input multiple-output (MIMO) system. An iterative precoding algorithm is proposed to satisfy the interference limit at the TV primary user (PU) receiver (Rx) and enhance the ergodic capacity. Moreover, a power allocation algorithm is developed for the MIMO system to achieve the maximum ergodic capacity subject to the average total power constraint and limit of interference to TV PU. Simulation results demonstrate the significant enhancement in the achieved capacity by our proposed system in the VHF band compared to both previous cognitive and hybrid BPLC systems.     

A new sensor selection scheme for Bayesian learning based sparse signal recovery in WSNs

In this paper, we address the issue of sparse signal recovery in wireless sensor networks (WSNs) based on Bayesian learning. We first formulate a compressed sensing (CS)-based signal recovery problem for the detection of sparse event in WSNs. Then, from the perspective of energy saving and communication overhead reduction of the WSNs, we develop an optimal sensor selection algorithm by employing a lower-bound of the mean square error (MSE) for the MMSE estimator. To tackle the nonconvex difficulty of the optimum sensor selection problem, a convex relaxation is introduced to achieve a suboptimal solution. Both uncorrelated and correlated noises are considered and a low-complexity realization of the sensor selection algorithm is also suggested. Based on the selected subset of sensors, the sparse Bayesian learning (SBL) is utilized to reconstruct the sparse signal. Simulation results illustrate that our proposed approaches lead to a superior performance over the reference methods in comparison.     

Combined state and parameter estimation for a bilinear state space system with moving average noise

This paper considers the identification problem of bilinear systems with measurement noise in the form of the moving average model. In particular, we present an interactive estimation algorithm for unmeasurable states and parameters based on the hierarchical identification principle. For unknown states, we formulate a novel bilinear state observer from input-output measurements using the Kalman filter. Then a bilinear state observer based multi-innovation extended stochastic gradient (BSO-MI-ESG) algorithm is proposed to estimate the unknown system parameters. A linear filter is utilized to improve the parameter estimation accuracy and a filtering based BSO-MI-ESG algorithm is presented using the data filtering technique. In the numerical example, we illustrate the effectiveness of the proposed identification methods.     

New insights in stability analysis of delayed Lotka–Volterra systems

Most of the reported Lotka–Volterra examples have at most one stability interval for the delay parameters. Furthermore, the existing methods fall short in treating more general case studies. Inspired by some recent results for analyzing the stability of time-delay systems, this paper focuses on a deeper characterization of the stability of Lotka–Volterra systems w.r.t. the delay parameters. More precisely, we will introduce the recently-proposed frequency-sweeping approach to study the complete stability problem for a broad class of linearized Lotka–Volterra systems. As a result, the whole stability delay-set can be analytically determined. Moreover, as a significant byproduct of the proposed approach, some Lotka–Volterra examples are found to have multiple stability delay-intervals. To the best of the authors’ knowledge, such a characterization represents a novelty for having some insights in the population dynamics: in some situations, a longer maturation period of species is helpful for the stability of a population system.     

Technology adoption,consumer inattention and heuristic decision-making: Evidence from a UK district heating scheme

This paper contributes to the debate on the energy efficiency paradox according to which consumers fail to adopt cost-effective, energy efficient technologies over less efficient technologies and therefore fail to reduce energy consumption. Both traditional and behavioural theories are used to investigate the decision-making process of residential consumers with empirical evidence based upon a specially designed quasi-experimental survey of 784 households on the decision to connect to a district-heating system, a more energy efficient alternative to individual heating systems. The results suggest an internal discount rate of around 36 per cent for homeowners, a signal that consumers undervalue future energy costs. We also find the household’s decision to be negatively affected by years of payback up to around 7–8 years. Our findings suggest that neglecting consumer inattention and heuristics can lead to biases which cast doubt on the existence of the energy efficiency paradox. We believe that these results help to explain why some consumers are unlikely to invest in energy efficient technology, particularly those on low incomes.     

矩阵方程组异类约束解的MCG1-3-5算法

借鉴求线性矩阵方程组同类约束解的MCG算法（修正共轭梯度法）,建立了求多个未知矩阵的线性矩阵方程组的一种异类约束解的MCG1-3-5算法,证明了该算法的收敛性。该算法不仅可以判断矩阵方程组的异类约束解是否存在,而且在有异类约束解,且不考虑舍入误差时,可在有限步计算后求得矩阵方程组的一组异类约束解;选取特殊初始矩阵时,求得矩阵方程组的极小范数异类约束解。同时还能求取指定矩阵在该矩阵方程组异类约束解集合中的最佳逼近。算例表明,该算法有效。     

Novice mathematics teachers create themselves

This study presents a qualitative research based on three narratives written by novice mathematics teachers. We examine their unique professional world during their first year of work. The methodology of narrative framework, on which this article is based, helps to gain better understanding of the need for novice mathematics teachers to have pedagogical knowledge. Findings reveal three themes of pedagogical knowledge: the attitude of novice teachers toward students with difficulties in mathematics; parents’ expectations of and involvement with novice mathematics teachers; teacher–student relations. The implications of the findings show that novice mathematics teachers are required to have not only content knowledge of mathematics but also, and above all, pedagogical knowledge. The implications of this study enable reassessment of emphases required in training mathematics teachers, as well as the assistance and support they need, especially as they launch their careers.     

长期冰川学观测引领大陆性和干旱区冰川变化与影响研究

中国是中纬度山地冰川大国,冰川科学研究十分重要。冰川还是我国西部干旱区重要的水资源——我国及周边国家大江大河的源头,由冰川变化引发的水文、水资源变化对于我国西北干旱区山盆地理结构的生态系统具有决定性意义。中国科学院天山冰川观测试验站(以下简称"天山冰川站")建立于中国冰川学开创之初的1959年,围绕乌鲁木齐河源1号冰川(以下简称"1号冰川")的研究,对中国冰川科学理论的形成和发展起着关键性作用,亦是对国际冰川学的重要发展和贡献。以乌鲁木齐河山区流域综合观测试验为基础的水文学研究,奠定了我国内陆河流域水文研究基础。60年来,作为中国冰川学观测、试验、研究和人才培养的基地,对外开放交流的平台,天山冰川站在冰川物理学、冰川对气候变化的响应、冰川水文、雪冰物理化学过程、第四纪冰川、冰缘植被与生态等研究方向取得系统性创新成果,为中国的冰川学事业作出了卓越贡献。世界冰川监测服务中心(WGMS)将1号冰川列为全球10条重点观测研究的参照冰川之一,即作为中国和中亚干旱区的参照冰川,其长期、系统的观测研究成为许多国家冰川学研究的参照和典范。