EPA控制网络中GSM接入点的设计

针对无线EPA接入设备中蓝牙、ZigBee等无线通信技术传输距离短、不利于远程监控的缺点,设计了基于GSM功能的无线EPA接入设备。考虑到移动通信网络实时性不高的特点,提出了在EPA控制网络的L2网段设计GSM接入点的方案。分别从硬件设计、报文转换、地址映射等角度,对GSM接入点的设计流程进行了研究。测试结果表明,GSM接入点能够较好地满足EPA微网段远程监控的需要,商用无线通信技术也必将引领未来无线控制网络的发展方向。     

入侵检测的进化神经网络研究

针对传统入侵检测系统漏报率和误报率高的问题,提出基于遗传神经网络的入侵检测系统。该系统将遗传算法和BP算法有机结合,利用遗传算法较强的宏观搜索能力和全局寻优特点,优化BP网络的初始权值和阈值,并在此基础上进行神经网络学习,从而建立入侵检测系统的优化分析模型。实验结果表明,该算法可以有效地运用于入侵检测系统中。     

移动终端的设施农业物联网环境监控系统设计

通过使用物联网(IOT)传输协议—消息队列遥测传输(MQTT)协议,将前端硬件、服务器端及移动端连接在一起,完成对设施农业环境的远程实时监控.在系统中,前端硬件以STM32微处理器为核心,由传感器模块、设备控制模块、GPRS模块和电源模块组成,实现数据的采集和传输;服务器端有数据接收、存储、分析的能力,并担任MQTT消息协议中消息生产者和消息管理者的角色;移动终端软件则以Android操作系统为基础开发了应用软件,用户在装有Android系统的移动终端上安装该应用软件,即可查看实时环境情况,发送控制设备指令等.经过测试,整个系统运行稳定、使用简单、实时性高,用户能有效地对设施农业环境进行远程实时监控.     

结合优化3D-SIFT与Gist特征的运动目标识别

目标识别和场景理解是图像处理高级任务中近几年的研究热点。结合局部特征和全局特征,利用累计差分图像分割出的目标提取优化3D-SIFT特征。结合Gist提取的图像全局特征,建立特征向量。通过SVM支持向量机训练,将其应用在运动目标识别和场景理解上。实验结果表明,与现有算法相比,该算法在目标识别和场景理解上的效果有显著的提高。     

Visualizing Waypoints‐Constrained Origin‐Destination Patterns for Massive Transportation Data

Origin‐destination (OD) pattern is a highly useful means for transportation research since it summarizes urban dynamics and human mobility. However, existing visual analytics are insufficient for certain OD analytical tasks needed in transport research. For example, transport researchers are interested in path‐related movements across congested roads, besides global patterns over the entire domain. Driven by this need, we propose waypoints‐constrained OD visual analytics, a new approach for exploring path‐related OD patterns in an urban transportation network. First, we use hashing‐based query to support interactive filtering of trajectories through user‐specified waypoints. Second, we elaborate a set of design principles and rules, and derive a novel unified visual representation called the waypoints‐constrained OD view by carefully considering the OD flow presentation, the temporal variation, spatial layout and user interaction. Finally, we demonstrate the effectiveness of our interface with two case studies and expert interviews with five transportation experts.     

Structure‐adaptive Shape Editing for Man‐made Objects

One of the challenging problems for shape editing is to adapt shapes with diversified structures for various editing needs. In this paper we introduce a shape editing approach that automatically adapts the structure of a shape being edited with respect to user inputs. Given a category of shapes, our approach first classifies them into groups based on the constituent parts. The group‐sensitive priors, including both inter‐group and intra‐group priors, are then learned through statistical structure analysis and multivariate regression. By using these priors, the inherent characteristics and typical variations of shape structures can be well captured. Based on such group‐sensitive priors, we propose a framework for real‐time shape editing, which adapts the structure of shape to continuous user editing operations. Experimental results show that the proposed approach is capable of both structure‐preserving and structure‐varying shape editing.     

Development of a Rotorcraft Micro air Vehicle for Indoor Flight Research

Autonomous flight of micro air vehicles (MAVs) in hostile indoor environments poses significant challenges in terms of control and navigation. In order to support navigation and control research for indoor micro air vehicles, a four-wing tail-sitter type rotorcraft MAV weighing less than 350g has been designed in this paper. In an effort to achieve autonomous indoor flight, an embedded integrated avionic system has been developed. The modeling process has been conducted to obtain accurate six degrees of freedom dynamical model for the designed rotorcraft MAV. In addition, aerodynamic coefficients are evaluated from the results of Computational Fluid Dynamics A PI-ADRC double loop controller with inner-loop outer-loop control scheme has been proposed which takes into account the system’s nonlinearities and uncertainties. The proposed flight controller was implemented on the designed rotorcraft MAV that has undergone various simulation and indoor flight tests. Experimental results that demonstrate robustness of the proposed controller with respect to external disturbances and the capabilities of the designed rotorcraft MAV are presented.     

Assessment of drivers' visual perception of information displayed in LED traffic signs at road construction sites

This study investigated drivers' visual perception of information displayed in LED traffic signs under different levels of environmental luminance. Concerning the information displayed, the environmental luminance comprised four luminance contrasts, two arrow types, and three environmental luminances, which were used to identify the visibility of traffic signs at the reading distance. Regarding visible distance, visibility involved reading starting and end points, extent of glare, comfortable distance, and glare distance. According to the study results obtained by using a highly reliable glare assessment method and studying the LED traffic signs, the lower the luminance contrast of traffic signs was the higher glare the participants perceived. A luminance contrast of 6200:2066 cd/m² provided the farthest comfortable and glare distances, enabling drivers to notice the signs comparatively earlier and have sufficient time to react accordingly. Overall, arrow type “<<<” outperformed “←” because the former was easier for drivers to read and created less glare. Regarding environmental luminance, traffic signs displayed in high and medium luminance environments (i.e., extremely sunny and cloudy days, respectively) each featured their own advantage, whereas those displayed in low luminance environments (nights) have to be further improved.     

An AR based fast mode decision for H.265/HEVC intra coding

As a critical technique to raise coding efficiency in H.265/HEVC (H.265/High Efficiency Video Coding), the number of prediction modes for intra coding is much larger than that in H.264/AVC. However, the large number of prediction modes also leads to high complexity. In this paper, an AR (Auto Regression) based fast mode decision method for H.265/HEVC intra coding is proposed, including an AR based fast mode selection and an MPM (Most Probable Mode) joint fast mode selection method. Considering the correlation between SATD (Sum of Absolute Transformed Differences) cost and RD (Rate-Distortion) cost, we establish a selective function controlled by an adaptive parameter which is acquired by an AR model. According to the distribution of the SATD cost, the selective function can decide which modes can be discarded and which modes can be used for the FMD (Fine Mode Decision). In addition, in order to further reduce the number of candidate modes for FMD, an MPM joint fast mode selection method is presented based on the relationship between MPMs and candidate modes. Experimental results show that just in PU layer, the proposed AR based fast intra mode decision method can save encoding time by 32 % with negligible coding loss in all-intra main configuration compared to the intra mode decision of HM13.0.