无线传感器网络中一种自适应的退避算法

802.15.4协议中CSMA/CA信道接入方式为了避免再次碰撞使用BEB退避算法,在重负载的情况下网络性能较差。提出一种自适应的退避算法,它用报文的冲突概率来预测节点附近信道的争用状况,在不同的网络状况下,竞争窗口的取值采用相应的退避策略,动态地控制节点的退避范围,以达到改善网络性能的目的。分析与仿真结果表明,新的算法与传统的退避算法BEB算法相比,在网络负载重的情况下,有效地降低了数据包的冲突概率,减少了时延,提高了网络的吞吐量,同时对信道的公平性也有所改善。     

传感器网络中一种基于多元回归模型的缺失值估计算法

在无线传感器网络中,感知数据的缺失问题不可避免,并且给无线传感器网络的各种应用带来了巨大困难.解决该问题的最好办法是对缺失数据进行准确估计.提出了一种基于多元回归模型的缺失值估计算法.该算法首先依感知数据的时间相关性和空间相关性分别采用多元线性回归模型对缺失数据进行估计,然后根据回归模型的拟合优度对基于时间维和空间维求出的两个估计值分别赋予相应的权值系数,并将其加权平均值作为缺失数据的最后估计值.由于该算法在对缺失值进行估计时,同时考察多个邻居节点并联合地用其感知数据来共同估计缺失值,因此该算法具有可靠、稳定的估计性能.在两个真实的数据集合上对该算法进行了测试,实验结果表明提出的缺失值估计算法能够有效估计无线传感器网络中的缺失数据.     

The influence of goal clarity,curiosity, and enjoyment on intention to code

The purpose of this study is to examine the influence of goal clarity, curiosity, and enjoyment – dimensions of flow theory – on the intention to write programming code. This research refines and extends previous information systems (IS) research in two significant ways: first, this research is focused specifically on systems development behaviour; second; this is the first research that isolates specific flow theory constructs associated with systems development behaviour. We used SmartPLS to test our model, as partial least squares is the appropriate statistical methodology for theory building and model testing. Findings are based on survey data from computer IS classes at two different universities. Goal clarity and curiosity independently and significantly contributed to enjoyment when programming, which significantly and positively influenced a future intention to code. Recommendations for practitioners and faculty include testing for curiosity characteristics, providing clear goals, and providing stimuli to pique curiosity.     

Multiple kernel ensemble learning for software defect prediction

Software defect prediction aims to predict the defect proneness of new software modules with the historical defect data so as to improve the quality of a software system. Software historical defect data has a complicated structure and a marked characteristic of class-imbalance; how to fully analyze and utilize the existing historical defect data and build more precise and effective classifiers has attracted considerable researchers’ interest from both academia and industry. Multiple kernel learning and ensemble learning are effective techniques in the field of machine learning. Multiple kernel learning can map the historical defect data to a higher-dimensional feature space and make them express better, and ensemble learning can use a series of weak classifiers to reduce the bias generated by the majority class and obtain better predictive performance. In this paper, we propose to use the multiple kernel learning to predict software defect. By using the characteristics of the metrics mined from the open source software, we get a multiple kernel classifier through ensemble learning method, which has the advantages of both multiple kernel learning and ensemble learning. We thus propose a multiple kernel ensemble learning (MKEL) approach for software defect classification and prediction. Considering the cost of risk in software defect prediction, we design a new sample weight vector updating strategy to reduce the cost of risk caused by misclassifying defective modules as non-defective ones. We employ the widely used NASA MDP datasets as test data to evaluate the performance of all compared methods; experimental results show that MKEL outperforms several representative state-of-the-art defect prediction methods.     

Investigation of fused silica glass etching using C4F8/Ar inductively coupled plasmas for through glass via (TGV) applications

Through glass via (TGV) technology is considered to be a cost effective enabler for the integration of micro electromechanical systems and radio frequency devices. Inductively coupled plasma and Bosch etching process comprise one of the most pervasive methods for through silicon via (TSV) formation. Unfortunately an equivalent process for glass etching remains elusive. In this paper, the influence of plasma etching for fused silica glass were investigated to find the best tradeoff between etch rate and profile of TGVs. The process parameters including bias power, gas flow rate, ratio of etching gases and reaction chamber pressure using Ar/C₄F₈ inductively coupled plasmas were studied. The etching results show that all these three parameters have a significant impact on the etch rate. Furthermore, the adjustment including total flow rate and ratio of Ar/C₄F₈ and chamber pressure can be used to control the via profile. Constant fused silica glass etch rate greater than 1 μm/min was obtained when chiller temperature was 40 °C with etching time of 60 min. The profile angle of TGVs with nearly 90° was also achieved.     

Hybrid fire detection using hidden Markov model and luminance map

Recently, fire detection is a hot research topic. Although many detection methods have been proposed, there exist high false alarms because of the interference of fire-colored moving object in the complex environments. In this paper, a hybrid method is proposed. First, we get the set of candidate fire regions. Then these candidate fire regions are analyzed to exclude the fire-colored moving object. Our contributions are using the hidden Markov model (HMM) based on spatio-temporal feature and the variance of luminance map motivated by visual attention, and combining both for fire detection. The wrong detection can be reduced greatly. Experiment results show our proposed method has a good performance and it is robust to be used in complex environment compared with previous algorithms.     

智能家居照明控制无线开关系统

设计了一种用于智能家居照明控制的可编程四路无线开关系统。该系统利用芯片组PT2262／2272实现编码一发射和接收一解码,采用AT89S52单片机对接收信号进行控制。此方案电路设计灵活,能充分利用系统软硬件资源,系统扩展性好,提供了一种廉价的智能家居照明控制解决方案。     

协议一致性测试平台的设计和实现

简要介绍了协议一致性测试平台的基本要求和设计思想,给出了整体的设计框架,并且详细讨论了在平台实现过程中涉及到的5部分工作,包括测试例的生成、选择和执行,同时给出了一些简单的实例。     

面向数值模拟数据的HDF5性能优化

大规模数值模拟数据对可视化分析提出了挑战,I/O是影响可视化交互性能的重要因素.HDF5是科学计算领域广泛采用的存储格式,介绍了HDF5的抽象数据模型、数据读写流程,并使用典型数值模拟数据测试了HDF5的读性能.测试发现HDF5的数据集定位开销较大.根据数值模拟数据的数据块以整数有规律编号的特点,通过在HDF5中增加数据块视图对象来提高读性能.测试表明,该方法可显著加速数据的读取性能.