视频检测式违章自动监测管理系统的设计

本文概述了几种违章自动监测管理系统的特点、重点介绍了利用摄像机为前端设备的视频检测式道路交叉口违章自动监测管理系统的设计、组成以及可能存在的技术难点和解决办法。     

视频检测测试违章自动监测管理系统的设计

本文概念了几种违章自动监测管理系统的特点、重点介绍了利用摄像机为前端设备的视频检测式道路交叉口违章自动监测管理系统的设计、组成以及可能存在的技术难点和解决办法。     

违章停车智能监控系统设计

介绍了违章停车智能监控系统的设计。它综合利用网络技术、图像处理和计算机视觉等技术，实现了对违章停车的自动监测和对违章车辆信息的相关管理，而且成本低、智能化程度高、可行性强。     

电子警察系统中的图像传输方案设计

就电子警察系统中的违章图像传输的几种技术方案进行了讨论.重点论述了在MODEM通信串口编程的基础上,针对交通十字路口的实际情况利用电话线进行违章图像自动传输的系统.通过长时间的测试,正常情况下效果很好;对突发的异常情况,如停电等,也能及时处理,有效地证明了本方案的可行性和实用性.     

交通信号灯状态判别

介绍了机动车违章闯红灯视频自动监测系统的基本原理和实现框架,分析了其中的关键技术,并提出了一个视频交通信号灯状态判别模型以解决交通信号灯状态判别这个关键问题。该模型在闯红灯视频自动监测系统中得到应用。实际结果表明该模型准确、可靠、实用、鲁棒性强。     

电子警察系统中的图像传输方案设计

就电子警察系统中的违章图像传输的几种技术方案进行了讨论。重点论述了在MODEM通信串口编程的基础上，针对交通十字路口的实际情况利用电话线进行违章图像自动传输的系统。通过长时间的调试，正常情况下效果很好；对突发的异常情况，如停电等，也能及时处理，有效地证明了本方案的可行性和实用性。     

违章逆行智能视频监控系统设计

设计了一个对交通车辆违章逆行行为进行智能视频监控的方案.综合利用图像处理、模式识别、计算机视觉和网络通讯等技术,在对交通视频流进行实时采集的基础上,首先成功地识别出交通车辆目标,然后实现了对违章逆行的自动识别以及对违章现场的自动抓拍,并完成对违章车辆信息的传输和相关管理工作.     

基于CORBA的油库在线监测与管理系统

结合油库在线监测与管理系统的实际需求,采用CORBA技术实现分布式异构系统中不同硬件设备之间的相互通信和不同应用之间的信息共享,增强了设备的通用性,提高了在线监测与管理系统的实时性和可移植性,实现了对油库安全的自动监测和业务的统一管理.此设计方案真正解决了油库在线监测与管理系统构建和扩容时面临的不同通信协议、编程语言和网络平台和设备的兼容问题.     

便携式违章车辆网络管理系统设计

结合我国违章车辆管理现状,本文阐述了车辆违章管理便携化和网络智能化的必要性,然后从便携式违章车辆网络管理系统结构出发,逐次讲述了系统的硬件设计、操作系统裁剪、系统引导、内核OAL和驱动程序开发以及应用程序的开发技术,最后针对嵌入式系统资源紧缺的特点提出了一些新的解决方案。     

改进的灰度帧差统计法对车辆违章压黄线的检测

现阶段国内外在基于视频的车辆违章检测领域研究比较多,算法较成熟的包括:车辆闯红灯违章检测、车辆超速违章检测、车辆逆行违章检测等;而目前在基于视频的车辆压双黄线违章检测方面的研究与开发应用,可发现的文献相对较少。针对车辆违章压双黄线在此提出了一种基于彩色检测线的线间差分与灰度帧差统计法相结合的改进混合型方法,该方法有效解决了阴影对车辆违章压双黄线检测的影响,对准确判定车辆是否违章具有良好的效果。     

A hybrid metaheuristic case-based reasoning system for nurse rostering

In this paper we present a novel Case-Based Reasoning (CBR) system called CABAROST (CAsed-BAsed ROSTering) which was developed for personnel scheduling problems. CBR is used to capture and store examples of personnel manager behaviour which are then used to solve future problems. Previous examples of constraint violations in schedules and the repairs that were used to solve the violations are stored as cases. The sequence in which violations are repaired can have a great impact on schedule quality. A novel memetic algorithm is proposed which evolves good quality sequences of repairs generated by CABAROST. The algorithm was tested on instances of the real-world nurse rostering problem at the Queens Medical Centre NHS Trust in Nottingham.     

Updating one's knowledge about the current status of vehicles in a freight system simulation

The use of simulations of real-world settings can provide data relevant to ergonomics problems in a wide range of similar settings. This paper reports on a simulation of a freight service operation. It examines the effect of manipulating the type and format of information representation on the ability to update knowledge about the status of three vehicles. In addition, the effects of display type and the detection of violations of pre-learned rules on the ability to update are examined. The display format proved not to be a critical factor but the requirement to detect rule violations of a specific vehicle resulted in better memory-updating performance for that vehicle. The results are discussed in terms of a human memory mechanism, which is analogous to a computer operating system, involved in updating memory and detecting violations. Finally, the value of using this tool to examine complex cognitive processes relevant to the workplace is discussed.     

自动修复短时序违反路径的FPGA布线算法

为了解决寄存器保持时间不满足而引起的短路径问题, 提出一种自动修复短时序违反路径的FPGA布线算法。在VPR时序布线算法整体布线布通之后, 调用短路径时序分析来获取违反短时序约束的布线连接, 然后通过修改代价函数, 对每条违反短时序约束的连接进行增量布线, 使每条连接的路径延时尽可能达到满足短时序约束所需的延时。实验结果表明, 本算法与VPR时序驱动布线算法相比, 能够平均修复94. 7%的短时序违反路径, 而运行时间仅增加了6. 8%。     

Architecture compliance checking at run-time

In this paper, we report on our experiences with architecture compliance checking – the process of checking whether the planned or specified software architecture is obeyed by the running system – of an OSGi-based, dynamically evolving application in the office domain. To that end, we first show how to dynamically instrument a running system in the context of OSGi in order to collect run-time traces. Second, we explain how to bridge the abstraction gap between run-time traces and software architectures, through the construction of hierarchical Colored Petri nets (CP-nets). In addition, we demonstrate how to design reusable hierarchical CP-nets. In an industry example, we were able to extract views that helped us to identify a number of architecturally relevant issues (e.g., architectural style violations, behavior violations) that would not have been detected otherwise, and could have caused serious problems like system malfunctioning or unauthorized access to sensitive data. Finally, we package valuable experiences and lessons learned from this endeavor.     

A fast iterative nearest point algorithm for support vector machineclassifier design

In this paper we give a new fast iterative algorithm for support vector machine (SVM) classifier design. The basic problem treated is one that does not allow classification violations. The problem is converted to a problem of computing the nearest point between two convex polytopes. The suitability of two classical nearest point algorithms, due to Gilbert, and Mitchell et al., is studied. Ideas from both these algorithms are combined and modified to derive our fast algorithm. For problems which require classification violations to be allowed, the violations are quadratically penalized and an idea due to Cortes and Vapnik and Friess is used to convert it to a problem in which there are no classification violations. Comparative computational evaluation of our algorithm against powerful SVM methods such as Platt's sequential minimal optimization shows that our algorithm is very competitive.     

Genericity in Java: persistent and database systems implications

Lack of parametric polymorphism has been a major obstacle for making Java a viable database programming language. Regrettably, a recently accepted solution for genericity in Java 5.0 has far-reaching negative implications for persistent and database systems because of static and dynamic type violations. Severe implications occur in typical database transactions when processing a variety of database collections. Well-known approaches to persistence in Java, including Java’s own persistence mechanism, do not perform correctly due to incorrect dynamic type information that gets promoted to persistence along with objects. Dynamic checking of types of objects fetched from the persistent store may now lead to unexpected type violations. Further problems occur in reflective transactions as Java Core Reflection now allows dynamic type violations without detecting them or throwing standard exceptions. All of this shows that extending Java with parametric polymorphism has not made Java a more viable database programming language. Both legacy systems, such as those based on the Java binding of the ODMG or JDO, and future Java-related persistent and database technologies will be affected. The source of these problems is in an implementation idiom called type erasure. This paper provides formal proofs of the above implications of type erasure along with specific samples of code in Java 5.0 illustrating these violations. The limitations of the virtual platform and extensions required for persistent systems to solve this problem are also elaborated.     

Self-adaptation and secure information flow in multiparty communications

We present a comprehensive model of structured communications in which self-adaptation and security concerns are jointly addressed. More specifically, we propose a model of multiparty, self-adaptive communications with access control and secure information flow guarantees. In our model, multiparty protocols (choreographies) are described as global types; security violations occur when process implementations of protocol participants attempt to read or write messages of inappropriate security levels within directed exchanges. Such violations trigger adaptation mechanisms that prevent the violations to occur and/or to propagate their effect in the choreography. Our model is equipped with local and global adaptation mechanisms for reacting to security violations of different gravity; type soundness results ensure that the overall multiparty protocol is still correctly executed while the system adapts itself to preserve the participants’ security.     

TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data

Maintaining a fluid and safe traffic is a major challenge for human societies because of its social and economic impacts. Various technologies have considerably paved the way for the elimination of traffic problems and have been able to effectively detect drivers’ violations. However, the high volume of the real-time data collected from surveillance cameras and traffic sensors along with the data obtained from individuals have made the use of traditional methods ineffective. Therefore, using Hadoop for processing large-scale structured and unstructured data as well as multimedia data can be of great help. In this paper, the TVD-MRDL system based on the MapReduce techniques and deep learning was employed to discover effective solutions. The Distributed Deep Learning System was implemented to analyze traffic big data and to detect driver violations in Hadoop. The results indicated that more accurate monitoring automatically creates the power of deterrence and behavior change in drivers and it prevents drivers from committing unusual behaviors in society. So, if the offending driver is identified quickly after committing the violation and is punished with the appropriate punishment and dealt with decisively and without negligence, we will surely see a decrease in violations at the community level. Also, the efficiency of the TVD-MRDL performance increased by more than 75% as the number of data nodes increased.