RETRACTED ARTICLE: Intelligent traffic monitoring and traffic diagnosis analysis based on neural network algorithm

Traffic sign recognition and lane detection play an important role in traffic flow planning, avoiding traffic accidents, and alleviating traffic chaos. At present, the traffic intelligent recognition rate still needs to be improved. In view of this, based on the neural network algorithm, this study constructs an intelligent transportation system based on neural network algorithm, and combines machine vision technology to carry out intelligent monitoring and intelligent diagnosis of traffic system. In addition, this study discusses in detail the core of the monitoring system: multi-target tracking algorithm, and introduces the complete implementation process and details of the system, and highlights the implementation and tracking effect of the multi-target tracker. Finally, this study uses case identification to analyze the effectiveness of the algorithm proposed by this paper. The research results show that the proposed method has certain practical effects and can be used as a reference for subsequent system construction.

     

Low‐voltage and high‐transmittance blue‐phase liquid‐crystal device with slanted electrodes

Abstract— A low‐voltage (～10 V_rms) and high‐transmittance (～90%) polymer‐stabilized blue‐phase liquid‐crystal (BPLC) device with a slanted‐electrodes structure is proposed. Unlike the vertical‐field‐switching (VFS) mode in which oblique incident light and a vertical field are employed, the proposed device utilizes normal incident light and an oblique field. The slanted electrodes generate a strong and uniform oblique electric field, which contributes in obtaining low voltage and high transmittance. Moreover, no couple films or prism sheets are needed, which helps to enhance the optical efficiency and simplify of the device structure. This device has great potential application for emerging BPLC displays and photonic devices.     

ANDES: efficient evaluation of NOT-twig queries in relational databases

Despite a large body of work on XPath query processing in relational environment, systematic study of queries containing not-predicates have received little attention in the literature. Particularly, several xml supports of industrial-strength commercial rdbms fail to efficiently evaluate such queries. In this paper, we present an efficient and novel strategy to evaluate not -twig queries in a tree-unaware relational environment. not -twig queries are XPath queries with ancestor–descendant and parent–child axis and contain one or more not-predicates. We propose a novel Dewey-based encoding scheme called Andes (ANcestor Dewey-based Encoding Scheme), which enables us to efficiently filter out elements satisfying a not-predicate by comparing their ancestor group identifiers. In this approach, a set of elements under the same common ancestor at a specific level in the xml tree is assigned same ancestor group identifier. Based on this scheme, we propose a novel sql translation algorithm for not-twig query evaluation. Experiments carried out confirm that our proposed approach built on top of an off-the-shelf commercial rdbms significantly outperforms state-of-the-art relational and native approaches. We also explore the query plans selected by a commercial relational optimizer to evaluate our translated queries in different input cardinality. Such exploration further validates the performance benefits of Andes.     

Optimal Performance in Tracking Stochastic Signal Under Disturbance Rejection

The analysis method of optimal tracking performance is proposed for multiple‐input multiple‐output (MIMO) linear time‐invariant (LTI) systems under disturbance rejection. An H₂ criterion of the error signal between the output of the plant and the reference signal is used as a measure for the tracking performance. Spectral factorization is applied to obtain the optimal solution of the system tracking error. The explicit expressions are derived for this minimal tracking error with respect to random reference signals under disturbance rejection. It is shown that the nonminimum phase zeros, the zero direction, the unstable poles, the pole direction of a given plant, statistical characteristics of the reference input signal, and disturbance signal have a negative effect on a feedback system's ability to reduce the system error with disturbance rejection. The results show that the optimal tracking performance will further be damaged because of disturbance rejection. Some typical examples are given to illustrate the theoretical results.     

基于转矩分析理论的功率振荡事故原因快速排查方法

电力系统功率振荡严重影响电力系统安全稳定运行,排查分析功率振荡事件发生的原因是避免类似功率振荡事件、提高电力系统安全稳定性能的前提条件。本文针对励磁系统异常导致功率振荡的情况,提出了一套快速排查方法,以一起电厂功率振荡事故的过程为例,应用基于转矩分析理论的功率振荡事故原因快速排查方法,确认了此次振荡事故的故障原因,为事故处理提供依据。     

A review of machine learning applications in IoT-integrated modern power systems

This paper aims to provide a systematic and comprehensive survey of state-of-the-art machine learning techniques and their potential applications in IoT-integrated power systems.     

机动车辆装载问题的一种混合遗传算法实现*

针对货物装载地和运送目的地均已确定情况下的车辆装载问题,给出了基于遗传算法求解的数学模型,并对基本遗传算法的各个算子针对问题的特点提出了改进方法,同时引入启发式策略,形成了一种混合遗传算法.该算法的特点是各个算子都以提高算法收敛速度和解的最优性为目标,同时种群大小是动态变化的,以求在保证群体多样性的同时加快收敛速度.实验结果表明,该算法对求解此类问题是有效的.     

一种基于事务规则树的高效关联规则挖掘算法*

提出了基于事务规则树改进的关联规则快速挖掘算法--FG算法.该算法不需要查找频繁项集,可直接求出所有无冗余的关联规则;将FG算法与其他算法进行实验比较,结果表明,FG算法在效率上优于其他算法,是有效的、可行的关联规则挖掘算法.     

有效的IPSec安全策略管理方案*

针对IPSec协议在安全策略管理存在的问题,引入信任管理的思想,介绍了一种基于信任管理的IPSec安全策略管理方案。该方案对分布式网络中的策略可以进行统一的描述,并通过一致性证明能够实现策略的委托授权管理,这样大大提高了IPSec安全策略管理效率和IPSec的灵活性。     

一种面向重构的工作流活动状态语义描述方法

工作流活动行为的精确描述是实现工作流过程控制的基础。基于状态的工作流活动行为描述方法在当前的工作流管理系统中被普遍采用。然而,非形式化的活动状态描述缺乏精确的语义并且不易扩充,导致系统适应性较差。针对业务过程管理需求的多样性和动态性,提出了一种支持快速重构的工作流活动状态语义的形式化描述方法。在分析工作流活动与工作项的状态关联基础上,定义了活动状态配置、活动状态配置全集等用于活动状态语义描述的基本概念。通过把活动状态映射为具有相同特征的活动状态配置的集合,建立了形式化的活动状态语义,研究了在此语义下活动状态的重构机制和基本实现步骤,并通过实例验证了该机制的有效性。应用本方法能够提高工作流管理系统适应企业业务过程管理需求快速变化的能力。