先进的城市停车诱导系统的研究

针对目前我国城市中停车难、难停车的问题，分析了目前停车诱导存在的问题以及建立先进的停车诱导系统的必要性，提出了一种比较先进且经济实用的停车管理系统方案，并分析了系统的结构，同时分析了系统各部分的功能及建立系统时应注意的问题。该方案把城市的停车资源看成一个整体，对改善城市交通具有积极作用。     

基于OpenMV的共享单车规范停车检测

为了解决城市中共享单车乱停乱放的问题,提出了一种基于OpenMV的共享单车规范停车系统。系统主要由OpenMV开发板、BC20通信定位模块以及OneNET云服务器等组成。其中OpenMV完成对停车状态的检测与识别,借助BC20内置的网络模块与OneNET云服务器进行数据交互,并将检测结果反馈至小程序客户端,从而实现对共享单车的停车检测和控制。系统通过大量的测试,实验结果表明系统运行稳定,识别准确率为94.1%,可以实现共享单车的规范停车自动检测,具有良好的市场应用前景与价值。     

REST架构下的智能共享停车位系统

为了有效缓解城市停车一位难求与大量车位利用率低下两者之间的矛盾,本文从物联网的角度给出了智能分时停车位系统解决方案,采用REST架构将用户手机app、信息存储服务器和智能车位锁等独立设备有机连接,支持停车位的实时发现、分时共享、在线预约、智能导航和无人监管,形成又一个良好的共享经济案例.     

基于物联网的智慧停车管理系统设计

随着国民经济水平的不断提高,我国汽车保有量持续增加,停车难、停车乱、部分区域车位闲置等问题,不仅影响城市交通通行效率,而且会造成一定的社会资源浪费,因此基于物联网技术设计了智慧停车管理系统。通过智慧化的停车管理系统实现停车场车位和路况的智慧规划及合理分配,形成停车引导、车位自主查询、智慧结算以及路线规划等完善服务体系,以提高车辆出行效率和停车便捷性。     

扩展的信牌驱动模型中配对结构之研究

在分层的工作流模型研究的基础上，指出了WPDL中AND-JOIN的语义问题，并在扩展的信牌驱动模型层，对配对结构进行了系统、深入的研究．形式地定义了最宽泛的配对概念和严格的正则配对的概念，分析了它们各自的优缺点．然后定义了一个既有严格语义、性能可以确定，但要求相对宽泛、相对比较实用的扩展正则配对的概念．利用此概念，严格地定义了扩展的信牌驱动模型．     

一种智能共享车位系统架构的研究

汽车数量的快速增长,导致停车位短缺的问题日益突出。针对此问题,基于互联网+共享经济理念,提出了一个智能共享车位系统设想：由智能共享地锁、前端用户App和后台管理系统组成。智能地锁对车位进行管理,由微控制器、电机和电池等硬件组成,其控制系统包括通信定位、蓄电池电量检测、报警系统等软件功能模块。前端用户App用于车位出租管理,包括用户信息、车位信息和车位使用子模块。后台管理系统是运营管理云服务器端,主要有服务器管理、用户管理和车位管理3个子模块。该智能共享车位平台系统架构的设计基于定位技术,实现停车位的精准定位,为用户节约寻找车位时间,合理充分利用空闲车位,缓解停车交通压力。     

基于智能手机的停车导航系统设计

为了应对当前城市交通迫切的停车问题,充分利用停车场车位资源,提高车主出行体验和满意度,降低停车场内部的拥堵和安全隐患,文中利用无线通信、电子地图、GIS技术和室内定位技术设计了一套具备车位预约、车位导航、在线支付和反向寻车功能的智能停车导航系统。该系统充分发挥车主随身携带的智能终端的作用,利用智能终端的无线接入信号,在室内部署的蓝牙标签的辅助下完成高精度的定位与导航,有效解决当前室内定位与导航中存在的定位不准确等难题,提升停车场车位使用率,进而增加停车场收入。     

手机与ZigBee结合的城市停车系统

为解决现有城市智能停车系统普遍存在的建设及运营成本高、缺乏与停车用户交互等问题,提出一种用户智能手机与停车场ZigBee网络相结合的架构。介绍该架构的组成、硬件方框图、软件流程图和设计的停车场、停车位寻优算法,给出系统的实物展示及测试结果。测试结果表明,将选用的传感器用于车位检测准确可靠,设计的停车场、停车位寻优算法的运行结果符合人们的生活习惯,开发的ZigBee网络与智能手机软件之间能够良好地通信,该架构的可行性得到验证。     

自动代客泊车背景下的共享停车供需匹配模型及对应禁忌搜索算法

为了减少自动代客泊车车辆在停车场或指定停车区域内的车辆移位次数和距离,从而降低相关的成本和潜在事故风险,在满足共享停车需求的条件下构建了相应的车辆和泊位匹配优化模型.考虑到无人驾驶车辆停车中可自由移位的特征,将共享停车的需求和供给在时间上加以细分,与决策变量和可行解对应定义了匹配、匹配条和匹配图的概念;通过概念转换将求解匹配图的有效邻居转换为经典指派问题,并利用匈牙利算法加以求解;针对匹配模型的NP-hard特征,设计了对应的禁忌搜索算法.数值分析不仅验证了模型的合理性和求解算法的有效性,也证实模型与方法可处理有人驾驶的共享停车匹配问题.结果表明,利用自动代客泊车可以进一步提升共享泊位利用率,增加可停放的共享车辆数.     

基于量子反应均衡的政府与共享单车企业停车管理博弈分析

共享单车停车问题是城市交通治理中最主要的问题之一,其表面为共享单车用户停车行为不规范、共享单车企业管理调度不及时所致,究其本质实为共享单车各利益主体缺乏有效协同治理机制、停车权责划分不清晰、成本分担失衡的结果.考虑政府与共享单车企业的有限理性,建立扩展式博弈的量子反应均衡(QRE)模型分析双方停车管理博弈机理,并利用Gambit软件进行算例仿真分析.研究表明:双方博弈结果随理性程度增加逐渐趋向于基于完全理性的子博弈精炼纳什均衡,政府掌握更多企业运营信息有利于达到社会效用最大化的博弈结果;政府引入有效处罚措施或主导负责停车管理可以降低自身的财政支出和社会总成本,建立量化的处罚标准能够促进企业主动承担停车管理责任;有限理性程度、违停数量、激励机制和科技手段运行效率会影响企业的停车管理策略选择.     

"数字流域"中数据共享机制研究与实现

“数字流域”是一个复杂的巨系统，“数字流域”需解决的核心问题是海量数据的共享。采用层次模型设计“数字流域”中的数据共享模型，并对其实现方法进行了详细的分析，力图为“数字流域”提供一种高效的数据共享途径。     

Permutation test for incomplete paired data with application to cDNA microarray data

A paired data set is common in microarray experiments, where the data are often incompletely observed for some pairs due to various technical reasons. In microarray paired data sets, it is of main interest to detect differentially expressed genes, which are usually identified by testing the equality of means of expressions within a pair. While much attention has been paid to testing mean equality with incomplete paired data in previous literature, the existing methods commonly assume the normality of data or rely on the large sample theory. In this paper, we propose a new test based on permutations, which is free from the normality assumption and large sample theory. We consider permutation statistics with linear mixtures of paired and unpaired samples as test statistics, and propose a procedure to find the optimal mixture that minimizes the conditional variances of the test statistics, given the observations. Simulations are conducted for numerical power comparisons between the proposed permutation tests and other existing methods. We apply the proposed method to find differentially expressed genes for a colorectal cancer study.     

Adaptive scheduling for shared window joins over data streams

Recently a few Continuous Query systems have been developed to cope with applications involving continuous data streams. At the same time, numerous algorithms are proposed for better performance. A recent work on this subject was to define scheduling strategies on shared window joins over data streams from multiple query expressions. In these strategies, a tuple with the highest priority is selected to process from multiple candidates. However, the performance of these static strategies is deeply influenced when data are bursting, because the priority is determined only by static information, such as the query windows, arriving order, etc. In this paper, we propose a novel adaptive strategy where the priority of a tuple is integrated with realtime information. A thorough experimental evaluation has demonstrated that this new strategy can outperform the existing strategies.     

Risk assessment of parking lot management based on occupational injuries data

This study is concerned with the characteristics of occupational injuries and sick leaves for the workers doing parking lot management. Possible incidents and sick leaves have been identified and analyzed for 470 occupational accidents in the parking lot management process. Management level of accidents for prioritizing prevention measures is induced for the combination of the accident types and parking lot management processes. Accidents occurring during the specific parking lot management process showed different characteristics, depending on the type of accident and agency of accident. Most critical accidents that required corrective actions for prevention were being struck by an object in the “guide” process and slipping in the “valet parking” process. And, possible incidents predicted also as high level of management were slips in the “fee collection” and “cleaning” processes and falls to lower level in the “operating lift” and “repair” processes. Also, traffic accidents in the “guide” process, overexertion and bodily reaction and posture in the “patrol” process were ranked ‘high. The findings of this study can be used to develop more effective accident prevention policies to reduce occupational accidents in parking lot management.     

基于共享知识的不完整大数据填充方法

针对传统大数据填充方法相似度度量方法单一,且通常只考虑原数据集内部联系,使得填充数据容易被原数据集限制、失去自身原有特点、填充结果不客观等问题.提出一种新的概念——共享知识,该方法首先基于共享知识构建不完整数据集与异源相似完整数据集的共享关系,并建立共享信息系统;其次通过新的相似度度量方法建立它们对象间的相似关系,从而用异源相似完整数据集对象对不完整的数据集对象进行相似填充.实验结果表明,新的相似度度量方法比单一的数值型相似度度量方法填充精度更高.与其他填补算法相比,该方法对缺失值的填充精度值能够稳定地保持在0.85以上,均方根误差稳定在0.15之下,充分保留了填充值的客观性,填充效果更好.     

基于共享数据库的数据集成方案的改进

共享数据库在数据集成中用的比较多,但是它本身也有一些局限性,比如说保密数据容易泄露,数据传输的速度不够快等.分析比较了目前已有的基于共享数据库的集成方案以及基于数据交换中心的数据交换方案的优劣性,并在比较的基础上提出了一种新的将数据交换中心加到共享数据库体系中的改进型数据集成方案,其中数据交换中心采用了JMS数据交换技术.     

基于共享数据中心的学分制收费模型的研究与应用

通过分析现有财务管理信息系统和教务管理信息系统的异构性,结合Web服务跨平台的技术优势,提出了基于Web服务的"共享数据中心"学分制实时收费模型.该模型充分利用现有资源,有效整合已有系统,较好地解决了学年制到学分制收费改革所带来的软件升级问题,提出的基于角色的Web服务访问权限控制和基于Web服务调用日志的数据库恢复策略,提高了系统的安全性和可靠性.     

Towards implementation of a novel scheme for data prefetching on distributed shared memory systems

High speed networks and rapidly improving microprocessor performance make the network of workstations an extremely important tool for parallel computing in order to speedup the execution of scientific applications. Shared memory is an attractive programming model for designing parallel and distributed applications, where the programmer can focus on algorithmic development rather than data partition and communication. Based on this important characteristic, the design of systems to provide the shared memory abstraction on physically distributed memory machines has been developed, known as Distributed Shared Memory (DSM). DSM is built using specific software to combine a number of computer hardware resources into one computing environment. Such an environment not only provides an easy way to execute parallel applications, but also combines available computational resources with the purpose of speeding up execution of these applications. DSM systems need to maintain data consistency in memory, which usually leads to communication overhead. Therefore, there exists a number of strategies that can be used to overcome this overhead issue and improve overall performance. Strategies as prefetching have been proven to show great performance in DSM systems, since they can reduce data access communication latencies from remote nodes. On the other hand, these strategies also transfer unnecessary prefetching pages to remote nodes. In this research paper, we focus on the access pattern during execution of a parallel application, and then analyze the data type and behavior of parallel applications. We propose an adaptive data classification scheme to improve prefetching strategy with the goal to improve overall performance. Adaptive data classification scheme classifies data according to the accessing sequence of pages, so that the home node uses past history access patterns of remote nodes to decide whether it needs to transfer related pages to remote nodes. From experimental results, we can observe that our proposed method can increase the accuracy of data access in effective prefetch strategy by reducing the number of page faults and misprefetching. Experimental results using our proposed classification scheme show a performance improvement of about 9–25% over the same benchmark applications running on top of an original JIAJIA DSM system.

基于统计分析的地磁车位探测器在线标定方法

针对地磁车位探测器的标定值不稳定的问题,研究了地磁车位探测器标定值的变化特点,提出了一种地磁车位探测器的在线标定方法。该方法可实现在线自动标定,并可以提高车位状态判断的准确率。这种在线标定方法使用统计学方法对标定值的变化范围进行分析,可跟踪标定值的变化,并对其进行定期修正。文章最后用一个实际应用案例验证了该在线标定方法的可行性。