基于英飞凌TC275的整车控制器CCP协议底层驱动开发

针对以英飞凌TC275单片机为平台的整车控制器,进行控制器局域网络标定协议(controller area network calibration protocol,CCP)底层驱动程序的开发。依据CCP的需求开发了英飞凌TC275的控制器局域网络(controller area network,CAN)模块、系统定时器(system timer,STM)模块和FLASH模块的底层驱动程序,实现CCP标定系统的通信连接、数据上传、数据下载、数据存储等功能。为验证系统的性能,进行整车控制器的实际测试,测试结果表明:所开发的基于TC275单片机的CCP底层驱动程序能够实现CCP的功能要求。     

A low power and low phase-noise 91~96 GHz VCO in 90 nm CMOS

This paper reports a 94 GHz CMOS voltage-controlled oscillator (VCO) using both the negative capacitance (NC) technique and series-peaking output power and phase noise (PN) enhancement technique. NC is achieved by adding two variable LC networks to the source nodes of the active circuit of the VCO. NMOSFET varicaps are adopted as the required capacitors of the LC networks. In comparison with the conventional one, the proposed active circuit substantially decreases the input capacitance (C_in) to zero or even a negative value. This leads to operation (or oscillation) frequency (OF) increase and tuning range (TR) enhancement of the VCO. The VCO dissipates 8.3 mW at 1 V supply. The measured TR of the VCO is 91~96 GHz, close to the simulated (92.1~96.7 GHz) and the calculated one (92.2~98.2 GHz). In addition, at 1 MHz offset from 95.16 GHz, the VCO attains an excellent PN of – 98.3 dBc/Hz. This leads to a figure-of-merit (FOM) of ?188.5 dBc/Hz, a remarkable result for a V- or W-band CMOS VCO. The chip size of the VCO is 0.75 × 0.42 mm², i.e. 0.315 mm².     

工程建设标准客观优先度评价研究

在工程建设标准的制定和修订过程中，如何科学地确定编制顺序一直是困扰标准管理部门的难题，采用传统方式“按需制标”，具有盲目性、主观性，容易造成标准在制定和修订过程中的互相重复、滞后与矛盾。为了保证标准制定和修订工作的协调性，指导标准体系中各标准的制修订顺序，引入复杂网络拓扑结构，将同一标准类型下的标准构成功能团，根据相互之间的关系形成复杂网络，采用剥落算法对其网络节点重要性排序，进而确定标准制修订的优先度。通过对建筑给水排水工程规范标准修订的实证分析，总结工程建设标准的网络拓扑优先度评价的算法模型，实现制定和修订顺序的自动计算，从而更加科学地指导标准的制定和修订工作     

Stochastic geometry of network of randomly distributed moving vehicles on a highway

Vehicular ad hoc networks (VANETs) have become an extensively studied topic in contemporary research. One of the fundamental problems that has arisen in such research is understanding the network statistical properties, such as the cluster number distribution and the cluster size distribution. In this paper, we analyze these characteristics in the case in which vehicles are located on a straight road. Assuming the Rayleigh fading model and a probabilistic model of intervehicle distance, we derive probabilistic distributions of the aforementioned connectivity characteristics, as well as distributions of the biggest cluster and the number of disconnected vehicles. All of the results are confirmed by simulations carried out for the realistic values of parameters.     

Supply chain network design under the risk of uncertain disruptions

Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.     

Deploy Efficiency Driven k-Barrier Construction Scheme Based on Target Circle in Directional Sensor Network

Journal of Computer Science and Technology - With the increasing demand for security, building strong barrier coverage in directional sensor networks is important for effectively detecting...     

改进Elman神经网络在短期热负荷预测中的应用

热电厂的短期热负荷预测在城市集中供暖中起着至关重要的作用,直接影响热电厂的经济效益和热能利用率。电厂的短期热负荷一般采用神经网络预测模型进行预测,而BP神经网络应用最为广泛。Elman神经网络算法在BP神经网络基础上加入了承接层,作为一步延时算子,实现记忆能力,使系统具备适应时变能力,增强系统全局稳定性。但Elman神经网络算法模型的构造依然需要大量样本的支撑,而且输入层的变量多,导致预测时间依然很长,收敛速度慢。该文在Elman神经网络预测前,进行了相关系数预处理和对样本中异常值的平均化预处理,通过数据归一化运算,使Elman神经网络输入层变量大幅减少。仿真实验表明,改进的Elman神经网络算法使预测模型快速寻优,减少预测时间的同时明显提高预测精度。     

人工监督神经网络在煤层裂缝发育区识别中的应用

针对在地震属性应用中难以精细识别煤层裂缝发育区边界的难题,开展了基于人工监督神经网络技术的煤层裂缝发育区应用研究。从地震资料中获取倾角导向体以提取高质量的地震属性,以多属性为指导进行人工拾取样点,并基于多层感知器进行神经网络机器训练学习,建立裂缝的最优属性集,拓展整体数据后获得裂缝概率体,从而识别划分出煤层裂缝发育区。该技术在山西阳泉新元矿区进行了应用,煤层裂缝发育区的识别结果明显优于属性直接识别,但勘探区内暂无钻井资料,预测效果还有待进一步验证。     

基于双层修正无迹卡尔曼的水下节点定位算法* .txt

摘要：针对水下无线传感网络中运动节点定位精度低的问题，提出了一种新的基于双层修正无迹卡尔曼的水下节点定位算法(DLMUKF)。该算法利用下层无迹卡尔曼滤波算法对节点状态进行预测，根据各信标节点的测距传播时延对预测的节点状态进行修正。运用上层无迹卡尔曼滤波算法对修正后的状态进行新的预测与修正。仿真实验中，DLMUKF算法的平均定位误差约为传统多边定位算法的15%，约为基于无迹卡尔曼滤波（UKF）定位算法的16%，受节点运动时间与速度的影响最小。通过实验证明DLMUKF算法能更充分利用实际距离值，可以有效减小运动节点的定位误差。 .txt