大型精密机械设备的验收与管理

对学院使用的大型精密机械设备——五轴加工中心和数控铣床等设备的安装条件、验收指标、技术管理和日常维护进行了阐述,确保设备到位后及时安装和有效使用。     

The implications of serial correlation and time-lag effects for the impact study of climate change on vegetation dynamics – a case study with Hulunber meadow steppe,Inner Mongolia

Ecological time series data are widely used in ecological research thanks to the development of remote-sensing technologies and fixed ecological research stations. However, the serial correlation issue with time series, which violates the fundamental assumption of independence for traditional statistical models or analysis, is rarely considered by ecologists in vegetation–climate relationship research. In addition, the issue of time lags between climate change and vegetation response is also often ignored. Inadequate consideration of these issues produces misleading results in some cases. In this article, we propose an approach based on the Autoregressive Integrated Moving Average (ARIMA) model and the nonparametric test to address serial correlation issue and distribution requirements for the valid statistical analysis of time series data. With Hulunber meadow steppe as a case, we applied this approach to analyse the role of climate factors in vegetation dynamics based on leaf area index (LAI) data and climatic data. The results showed that the LAI dynamics of Hulunber meadow steppe were mainly related to temperature with the time lag of zero, whereas the impact of precipitation on LAI dynamics was not statistically obvious. The comparison of regression models that deal with serial correlation and residual normality to different extents showed that ignoring the serial correlation issue with time series data likely produces misleading results, highlighting the importance of serial correlation removal. The combination of nonparametric correlation tests with ARIMA-based cross-correlation analysis also proved quite useful in reducing the chance of spurious correlation and time lags resulting from outlier values in ARIMA-based cross-correlation.     

基于P2P网络的机顶盒VoD系统条件接收机制

近年来,基于对等网络(Peer-to-Peer,P2P)的视频点播(Video-on-Demand,VoD)作为付费网络电视业务的一种新趋势受到了越来越多的关注,然而对等网络自身存在的不稳定性、异构性等缺陷,导致这种系统存在较大的信息安全隐患,从而严重阻碍了其推广使用.基于P2P网络的机顶盒VoD系统条件接收机制分析了现有系统的不安全因素及问题症结,提出了一种适用于P2P网络的VoD系统动态双向条件接收(Conditional Access,CA)机制,通过采用双向认证协议来保证通信双方身份的可靠性.同时在身份认证中可以结合密钥协商,生成用于传输控制字的业务密钥.另外,在简化设计的同时,也进一步提高了系统的安全性.     

Controller design and analysis for singularly perturbed switched systems with actuator saturation

This paper investigates the problems of controller design and stability analysis for singularly perturbed switched systems subject to actuator saturation. A set of well‐defined sufficient conditions for the existence of state feedback controllers is proposed, under which the closed‐loop system is locally asymptotically stable for arbitrary switching law as long as the singular perturbation parameter is sufficiently small. With the obtained controller, the estimation problem of stability bound and basin of attraction of the closed‐loop system is reduced to solving a convex optimization problem. A numerical example and a hydraulic servo position system are used to illustrate the obtained results. Copyright © 2016 John Wiley & Sons, Ltd.     

Topology optimization of a coupled thermal-fluid system under a tangential thermal gradient constraint

This paper presents a continuous adjoint approach for topology optimization of a coupled heat transfer and laminar fluid flow system under tangential thermal gradient (TTG) constraints. In this system, the thermal gradient along the boundary of multiple heat sources needs to be controlled. The design goals are to minimize the temperature of the domain, the fluid power dissipation and the TTG along the boundary of the heat sources. The first two goals are combined into a single cost function with weight variables. The TTG is constrained in one of two forms, an integral form where the integral of TTG squares along the boundaries of heat sources is constrained, or a point-wise form where TTG is constrained point-wise. A gradient-based approach is developed to obtain the optimized designs. A salient feature of our approach is the use of the continuous adjoint approach to derive gradients of both the cost function and two forms of TTG constraints. Numerical examples demonstrate that the continuous adjoint approach leads to successful topological optimization of the constrained thermal-fluid system. The use of TTG constraint is effective in lowering the TTG along the heat source boundaries. The resulting designs exhibit clear black/white contrast.     

针对有向图的局部扩展的重叠社区发现算法

当前社区发现算法主要是针对无向图研究社区结构,但在实际复杂网络中,链接关系时常表现出非对称性或方向性,比如Twitter的用户关注关系,文献网络的引 用关系,网页之间的超链接关系等应用网络。因此,本文依据信息在复杂网络中的传播规律和流动方向性,提出了k-Path共社区邻近相似性概念及计算方法,用于衡量结点在同一社区的相似性程度,并给出了把有向图转换为带方向权值的无向图的方法。基于带权无向图提出了一种从局部扩展来探测社区的重叠社区发现算法(Local and wave-like extension algorithm of detecting overlapping community, LWS-OCD)。在真实数据集上的实验表明,共社区邻近相似性概念实现了有向到无向的合理转换,而且提高了社区结点的聚集效果,LWS-OCD算法能够有效地发现带权无向图中的重叠社区。     

Efficient link scheduling with joint power control and successive interference cancellation in wireless networks无线网络中联合功率控制和串行干扰消除的高效链路调度算法

Existing works have addressed the interference mitigation by any two of the three approaches: link scheduling, power control, and successive interference cancellation (SIC). In this paper, we integrate the above approaches to further improve the spectral efficiency of the wireless networks and consider the max-min fairness to guarantee the transmission demand of the worst-case link. We formulate the link scheduling with joint power control and SIC (PCSIC) problem as a mixed-integer non-linear programming (MINLP), which has been proven to be NP-complete. Consequently, we propose an iterative algorithm to tackle the problem by decomposing it into a series of linear subproblems, and then the analysis shows that the algorithm has high complexity in the worst case. In order to reduce the computational complexity, we have further devised a two-stage algorithm with polynomial-time complexity. Numerical results show the performance improvements of our proposed algorithms in terms of the network throughput and power consumption compared with the link scheduling scheme only with SIC.     

A yield-enhanced global optimization methodology for analog circuit based on extreme value theory

The challenge in variation-aware circuit optimization with consideration of yield is the trade-off between optimized performance, yield and optimization runtime. This paper presents a practical variationaware circuit global optimization framework named GOYE, which shows the advantages on performance, yield and runtime. It uses an approach called constraint violation elimination (CVE) in global search phase to prune initial starting points and uses the gradient-based method in local search to locate optimum. The worst-case analysis (WCA), which is necessary for variation-aware circuit optimization, is nested in the local optimization process. The efficiency is significantly improved by a novel method based on extreme value theory (EVT). Our EVT-based method is also the first one that allows users to control the target yield such that under-design or over-design can be avoided. A design example in TSMC 65 nm technology is illustrated in the paper where all performance achieves three-sigma yield with consideration of environmental and inter-die/intra-die process variations.     

Building 3D semantic maps for mobile robots using RGB-D camera

The wide availability of affordable RGB-D sensors changes the landscape of indoor scene analysis. Years of research on simultaneous localization and mapping (SLAM) have made it possible to merge multiple RGB-D images into a single point cloud and provide a 3D model for a complete indoor scene. However, these reconstructed models only have geometry information, not including semantic knowledge. The advancements in robot autonomy and capabilities for carrying out more complex tasks in unstructured environments can be greatly enhanced by endowing environment models with semantic knowledge. Towards this goal, we propose a novel approach to generate 3D semantic maps for an indoor scene. Our approach creates a 3D reconstructed map from a RGB-D image sequence firstly, then we jointly infer the semantic object category and structural class for each point of the global map. 12 object categories (e.g. walls, tables, chairs) and 4 structural classes (ground, structure, furniture and props) are labeled in the global map. In this way, we can totally understand both the object and structure information. In order to get semantic information, we compute semantic segmentation for each RGB-D image and merge the labeling results by a Dense Conditional Random Field. Different from previous techniques, we use temporal information and higher-order cliques to enforce the label consistency for each image labeling result. Our experiments demonstrate that temporal information and higher-order cliques are significant for the semantic mapping procedure and can improve the precision of the semantic mapping results.     

Fast two-dimensional weighted least squares techniques for the design of two-dimensional finite impulse response filters

This paper focuses on the design of two-dimensional (2D) quadrantally symmetric finite impulse response (FIR) filters, and presents three very efficient algorithms for the weighted least squares (WLS) design with a weight matrix that assigns four different weights to four different frequency bands. The first algorithm seeks for iterative solutions to the matrix equation describing the optimality condition of the design problem. The second algorithm aims at the limit solution of the solution sequence to the first algorithm, analytically obtained by using matrix diagonalization techniques. The third algorithm belongs to the category of iterative reweighting techniques. It uses the second algorithm as its iteration core, and aims at reducing the maximum magnitude error of the filter by iteratively adjusting the four entry values of the weight matrix. Design examples are provided to demonstrate the performance of the proposed algorithms.