基于GPRS的油井远程监控系统设计

针对当今油井现场作业情况监控的缺陷,研究、设计并实现了基于GPRS模块的油井远程监控系统。系统综合应用了先进MCGS工控组态软件、GPRS模块、信号检测与处理等技术对油井现场进行了有效地监控,能对各种数据进行方便地统计和查询。通过模拟调试验证了结合上位机和下位机对油井大钩负荷、原油油管压力和油管内原油温度的远程监测和现场监控。     

嵌入式疲劳驾驶监测系统的设计与实现

疲劳驾驶是引发恶性交通事故的重要原因之一,驾驶员疲劳监测技术近年来已逐步成为图像处理领域的一个研究热点。基于改进的和提出的新算法,设计了一个嵌入式驾驶员疲劳监测系统。由可见光/近红外摄像头采集视频,首先采用Haar特征的级联分类器从图像中检测出人脸区域,并用钻石搜索法跟踪人脸区域;然后提取一个新的图像差分统计特征,并结合3个准则判断疲劳状态;最后采用全变分模型消除图像中的非均匀光照,以便实现鲁棒的人眼定位和人脸识别。实验测试结果表明,本系统的疲劳状态监测准确率达到95%以上。     

水下定位系统传感器安装误差标定技术研究

提出了一种基于非线性参数估计的水下定位系统传感器安装误差标定技术.水下定位系统由声学传感器,GPS和船体姿态传感器组成,各传感器的坐标系并不能完全重合,需要对传感器之间的误差标定后进行修正才能够获得高精度的定位效果.已有的标定方法多基于高斯-牛顿迭代法,而当非线性系统模型线性化带来较大误差时,常规的基于高斯-牛顿迭代法的标定方法已无法达到高精度的要求,而非线性模型参数估的直接解法则掺人了三阶量,有效减小线性化的模型误差,提高了各传感器安装误差的标定精度.海试数据处理表明:定位精度可由1 m提高到0.7 m.     

MIMO多跳无线网络

综述了多跳无线网络MIMO(multiple-input multiple-output)技术的研究进展,分析了MIMO技术的引入对多跳无线网络各层及整体设计的影响.以跨层协议设计为重点,详细介绍了当前典型的基于MIMO的多跳无线网络协议算法的核心机制,并比较分析了这些算法的特点和性能差异与存在的缺陷.最后,结合本领域内的研究现状,指出了基于MIMO的多跳无线网络走向实际工程应用环境所亟待解决的关键问题,指出了基于MIMO技术设计自适应调整、高性能多跳无线网络跨层模型及协议的重要性.     

基于FPGA的射频热疗系统的设计

采用高精度数字温度传感器DS18B20与可编程逻辑器件FPGA实现温度测量与控制,并进行温度场的测量与控制实验.实验表明,一维控制器控制精度不够,温度超调比较大(1℃),而二维控制器的温度超调就比较小(0.5℃).因此,所设计的射频温度场温度测量与控制的方法满足热疗要求.与传统方法相比,该系统具有设计灵活、现场可编程、调试简单和体积小等特点.     

取代酚对日本长腿蛙蝌蚪急性毒性的QSAR研究

用Hartree-Fock(HF)和DFT-B3LYP方法,分别在较高基组6-31G**和6.311G**水平下,全优化计算了21种取代酚化合物.从中获得分予最高占用和最低空轨道能(EHOMO和ELUMO)、前线轨道能级差(△E＝EHOMO-ELUMO)、分子总能量(ET)、氧原了所带的最高正电荷(QH+)、最负原子的静电荷(Q-)、分子偶极矩(μ)和分子体积(V)等描述符.结合文献中标题化合物对日本长腿蛙蝌蚪的毒性值(-logLC50)和辛醇/水分配系数(logKow),由线性同归方法成功建立包含10gKow、ELUMO和Q-的三参数QSAR模型.其中,模型(5)的复相关系数R2=0.944 8,交叉验证系数Q2=0.920 5,标准偏差SE=0.187,Fisher检验值F=98.390,故其预测能力较好.由此推断,标题物对日本长腿蛙蝌蚪的毒性作用分为2步,首先穿过细胞壁在细胞内富集,以logKow和Q-描述;其次与亲核试剂发生亲电反应,以风ELUMO表示.     

Building strength models for high-performance concrete at different ages using genetic operation trees, nonlinear regression, and neural networks

Because the behavior of HPC at early age may be rather different at late age, this study proposed to establish the strength models of HPC at different ages, and to explore the difference between these models. A large number of experimental data were used to compare accuracy of the three model building techniques, nonlinear regression analysis (NLRA), back-propagation networks (BPN), and genetic operation trees (GOT). The results showed: (1) when NLRA was employed to establish the prediction model, the approach to establish HPC strength models based on the three separate data sets was more accurate than that used to establish HPC strength models for the total data set. (2) If an explicit formula is necessary, GOT is the best choice to build concrete strength models at medium and late ages (i.e., more than 14 days), while NLRA provides greater accuracy at early ages (i.e., less than 14 days); otherwise, BPN is the best choice.     

Real-time foveation filtering using nonlinear Mipmap interpolation

In recent years, several techniques have been proposed to simulate the gaze effect of the Human Visual System (HVS). It is believed that this effect is due to the foveation filtering. Current techniques to simulate the foveation filtering in computer graphics are either slow or suffer from artifacts and limitations. In this paper, we present a new approach of foveation filtering based on the Mipmap Pyramid of the current view by considering the relationship between the Gaussian kernel and Mipmap level. Due to the nonlinear Mipmap interpolation under the Bilateral Filtering scheme, we are able to simulate the foveation filtering more naturally and efficiently than in previous work. Moreover, a detail enhancement method based on the Cornsweet illusion is proposed to augment the gazing effect. We demonstrate our new approach with a variety of examples and provide comparisons with recent approaches.     

Moving People Segmentation from Zoomed Dynamic Scenes Containing a Door

The challenge of segmenting the moving object is harder when the background is dynamic and the camera used can change its zoom dynamically. Here, in this paper, we propose a method to detect and segment moving object from a dynamic background, which contains moving multiple-leaf doors. In addition, the proposed algorithm also takes care of dynamic zoom changes that can occur while shooting a scene. The proposed method uses background-rebuilding with discrete door’s position to tackle moving multiple-leaf door backgrounds and image feature comparison to tackle changes in zoom. The experiment results show satisfying segmentation results with high processing speed.     

Will the experience of playing a violent role in a video game influence people’s judgments of violent crimes?

The present study investigates the impact of the experience of role playing a violent character in a video game on attitudes towards violent crimes and criminals. People who played the violent game were found to be more acceptable of crimes and criminals compared to people who did not play the violent game. More importantly, interaction effects were found such that people were more acceptable of crimes and criminals outside the game if the criminals were matched with the role they played in the game and the criminal actions were similar to the activities they perpetrated during the game. The results indicate that people’s virtual experience through role-playing games can influence their attitudes and judgments of similar real-life crimes, especially if the crimes are similar to what they conducted while playing games. Theoretical and practical implications are discussed.