Information analysis of single photon emission computed tomography with count losses

An analysis is presented of the information transfer from emitter-space to detector-space in single photon emission computed tomography (SPECT) systems. The analysis takes into account the fact that count loss side information is generally not available at the detector. Side information corresponds to the number gamma-rays lost deleted due to lack of interaction with the detector data. It is shown that the information transfer depends on the structure of the likelihood function of the emitter locations associated with the detector data. This likelihood function is the average of a set of ideal-detection likelihood functions, each matched to a particular set of possible deleted gamma-ray paths. A lower bound is derived for the information gain due to incorporating the count loss side information at the detector. This is shown to be significant when the mean emission rate is small or when the gamma-ray deletion probability is strongly dependent on emitter location. Numerical evaluations of the mutual information, with and without side information, associated with information-optimal apertures and uniform parallel-hole collimators are presented.     

Data stream classification with novel class detection: a review,comparison and challenges

Knowledge and Information Systems - Developing effective and efficient data stream classifiers is challenging for the machine learning community because of the dynamic nature of data streams. As a...     

基于ZigBee的温室监测系统的低功耗设计

针对传统温室大棚有线监测系统存在施工复杂、线路多和维护难等缺陷,提出了一种基于ZigBee无线传感网络技术的低功耗温室监测系统的设计方案;通过对系统各部分的能耗进行分析,结合实际情况对传感器节点采用低功耗设计策略;硬件设计上采用低功耗射频芯片和智能开关芯片,软件编写上采用事件驱动方法延长节点休眠时间;该系统能够准确采集温室内光照度、空气温湿度、土壤水分和二氧化碳浓度等环境信息,并具有低功耗、低成本和易扩展等特点;测试结果验证了该方案的可行性。     

基于星敏感器的姿态优化估计算法

对于采用星敏感器的航天器姿态确定问题,提出了一种快速的姿态优化估计方法;首先,根据Rodrigues参数和观测向量之间的线性关系,引入四元数,构造了不同的非奇异的优化准则;其次,借助四元数,求解了基于该准则的姿态优化算法;误差协方差分析和数值仿真结果表明,该算法与著名的QUaternion ESTmation(QUEST)算法相比,在相同的操作系统环境下,具有相同的姿态估计精度,但计算速度更快,对两种算法选取间隔为2000次的仿真步长,统计数据长度为100个采样点,最后对结果加权求平均值,统计结果显示仅为QUEST的三分之一;这种姿态优化估计方法具有一定的工程应用价值。     

在CodeWarrior编译环境下运行μC／OS—Ⅲ

μC／OS-Ⅱ是面向8／16位及低端32位单片机应用的RTOS,而新近推出的μC／OS-Ⅲ则面向高性能32位单片机,如ARMCortex等。以Cortex—M4为内核的Kinetis系列单片机,不仅用于全国大学生飞思卡尔杯智能车竞赛,也用于诸多大学的嵌入式系统教学,官方提供的开发环境是CodeWarrior。本文介绍如何利用CodeWarrior开发环境,将μC／OS-Ⅲ在Kinetis单片机上运行起来,以便将μC／OS-Ⅲ引入教学、科研与应用。     

漫射红外技术的智能家居无线局域网设计

分析了红外技术在短距离无线通信中的优势,并将其应用在智能家居局域网中;结合安华高科技公司的HSDL-3020红外收发模块搭建了硬件电路,构成网络的主从节点;介绍了网络组建的过程,包括IrDA协议栈结构、数据编码格式、链路连接、网络管理机制等。本设计实现了对家居设备的统一管理,具有较高的应用价值。     

A new admissibility condition of discrete-time singular systems with time-varying delays

This paper gives a novel delay-dependent admissibility condition of discrete-time singular systems with time-varying delays. For convenience, the time-varying delay is assumed to be the sum of delay lower bound and the integral multiples of a constant delay. Specially, if the constant delay is of unit length, the delay is an interval-like time-varying delay. The proposed admissibility condition is presented and expressed in terms of linear matrix inequality (LMI) by Lyapunov approach. Generally, the uncertainty of time-varying delay would lead to conservatism. In this paper, this critical issue is tackled by accurately estimating the time-varying delay. Consequently, the proposed admissibility condition is less conservative than the existing results, which is demonstrated by a numerical example.     

Data preprocessing using hybrid general regression neural networks and particle swarm optimization for remote terminal units

Data corruption in SCADA systems refers to errors that occur during acquisition, processing, or transmission, introducing unintended changes to the original data. In SCADA-based power systems, the data gathered by remote terminal units (RTUs) is subject to data corruption due to noise interference or lack of calibration. In this study, an effective approach based on the fusion of the general regression neural network (GRNN) and the particle swarm optimization (PSO) technique is employed to deal with errors in RTU data. The proposed hybrid model, denoted as GRNN-PSO, is able to handle noisy data in a fast speed, which makes it feasible for practical applications. Experimental results show the GRNN-PSO model has better performance in removing the unintended changes to the original data compared with existing methods.     

Study on heat conduction and adsorption/desorption characteristic of MIL-101/few layer graphene composite

Journal of Porous Materials - Aiming at the poor heat conduction performance of porous MIL-101 applied in adsorption cooling process, few layer graphene (FLG) was selected as a promising thermal...     

基于U-Net的多尺度融合视网膜血管分割算法

针对眼底血管图像具有形状多样、分叉较多、曲度复杂的特点,提出了一种多尺度融合视网膜血管分割算法.该算法基于U-Net模型进行改进,首先在编码和解码部分使用短跳跃连接模块将网络浅层和深层的特征信息进行融合,通过增加浅层特征的权重,更多地保留了血管的边缘和细微结构信息.其次在编码部分采用空洞卷积构建空洞空间金字塔池化模块代替传统卷积块,来扩大算法的感受野,从而在不增加网络参数的同时进行多尺度特征融合,提取更丰富的空间信息.通过在DRIVE数据集上进行验证,实验结果表明:本算法的准确率和AUC值分别达到0.9572、0.9811,与U-Net等其他基于深度学习的算法相比分割效果更优,从而验证本算法在视网膜血管分割中更加有效.