安徽省风化花岗岩资源的开发与利用

介绍了安徽省风化花岗岩资源,通过提取钾长石矿物原料,生产免烧砖的改良土壤等途径,更好地解决开发利用风化花岗岩资源的问题,提出合理开发和保护风化花岗岩资源的建议。     

顾及地理-语义动态的城市热点预测框架

城市热点时空预测是城市管理和智慧城市建设的一项长期而富有挑战性的任务。准确地进行城市热点时空预测可以提高城市规划、调度和安全保障能力并降低资源消耗。现有的区域级深度时空预测方法主要利用基于地理网格的图像、给定的网络结构或额外的数据来获取时空动态。通过从原始数据中挖掘出潜在的自语义信息,并将其与基于地理空间的网格图像融合,也可以提高时空预测的性能,基于此,本文提出了一种新的深度学习方法地理语义集成神经网络(GSEN),将地理预测神经网络和语义预测神经网络相叠加。GSEN模型综合了预测递归神经网络(PredRNN)、图卷积预测递归神经网络(GCPredRNN)和集成层的结构,从不同的角度捕捉时空动态。并且该模型还可以与现实世界中一些潜在的高层动态进行关联,而不需要任何额外的数据。最终在3个不同领域的实际数据集上对本文提出的模型进行了评估,均取得了很好的预测效果,实验结果表明GSEN模型在不同城市热点时空预测任务中的推广性和有效性,利用该模型可以更好地进行城市热点时空预测,解决一系列如犯罪、火灾、网约车预订等等现代城市发展中亟需解决的相关问题。     

煤矸石制作轻质莫来石砖研究

本文研究了利用煤矸石生产高档轻质莫来石砖的可行性，实验研究表明，在煅烧后的煤矸石中加入部分工业氧化铝粉，一起混磨至８００目筛余小于５％，再经加有机质成型和１５５０℃×５小时煅烧，可制成物相及各种性能指标达到从德国进口轻质莫来石砖的制品。     

基于云计算的智慧唐山时空信息平台数据库构建

随着云计算技术的不断发展,大数据与信息化时代的优势越来越突出,应用越来越广泛。时空信息平台作为智慧城市建设的重要内容,管理海量基础地理信息数据,是智慧城市建设的基础。因此,海量数据的管理成为时空信息平台设计的关键。以智慧唐山建设为例,结合云计算技术,探讨时空信息平台数据库的构建,针对云平台基础地理信息数据体系、云平台数据库体系架构以及云平台数据库管理系统等方面进行设计,明确基于云计算时空信息平台数据库建设内容,探讨适用于智慧城市建设的时空信息云平台解决方案。     

基于众包模式的智慧城市时空信息云平台构建研究

智慧城市建设是拓展城市综合承载能力、促进城市转型升级发展的重要途径,时空信息云平台是智慧城市建设的重要基础设施,为城市大数据的发掘、应用提供时空化承载。借鉴互联网商业的众包理念建设智慧城市时空信息云平台,将有助于满足城市发展的现实需求,解决城市治理的主要问题。     

Technologies of austerity urbanism: the “smart city” agenda in Italy (2011–2013)

In the heyday of the late 2000s financial crisis, austerity urbanism became a dominant practice of state financial restructuring—an intensification in the encroachment of the neoliberal project into the agendas of local governments. In the specific case of Italy, which faced political and economic distress between 2011 and 2013, “smart city” policies became one of the foundational political technologies for the implementation of austerity measures. In this paper, I analyse how the smart city provided a lexicon for urban austerity through a series of different sites and vehicles of policymaking, from practitioners to companies and other institutions. I argue that smart city discourses and practices functioned as a political technology that was effective in justifying cost containment measures and supporting the shift to pro-innovation public expenditures. Yet, at the same time, the smart city techno-utopian vocabulary created spaces where other meanings and, potentially, alternative political outcomes were made possible by diverse alignments of knowledge and expertise.     

Governing a city of unicorns: technology capital and the urban politics of San Francisco

San Francisco is now widely considered to be the most important city in the world for the location of new technology start-up firms, especially high valuation “unicorns,” and is increasingly seen as both a locational and metaphorical extension of Silicon Valley. In this paper, I trace some of the political strategies and tensions that have accompanied the city’s prominence in this area, and in particular the distinctive role of technology and venture capital in the political economy of urban development. The paper has four empirical sections. It describes (1) the political machinations surrounding the 2011 and 2015 municipal elections, which saw the election of Ed Lee as Mayor with significant support from individual technology investors such as Ron Conway and Marc Benioff, and accompanied by various “tech-friendly” policy shifts; (2) the foundation of the “tech chamber of commerce” sf.citi as a means of enhancing the policy influence of the tech industry in San Francisco; (3) the introduction of a low taxation regime in the city’s Central Market area that has attracted technology companies such as Twitter as tenants; and (4) the urban policy tensions associated with the evolution of new “sharing economy” firms such as Uber and Airbnb, which have aggressively challenged municipal regulations in the taxi and property rental fields. Throughout these machinations, we can see a reshaping of capital fractions, with venture and angel capital increasingly involved in reengineering the labor, housing, and public transport markets of the city in order to circumvent the accumulation problems that tech investors had suffered in the earlier dot.com failures.     

基于智慧管网的高性能通信前置系统的研究与应用

针对在智慧管网环境下,大量多元化智能终端设备或传感设备接入前置机时,如何统一入口进行海量数据的高效能通信,提出了一种可行的解决方案。依据该方案开发的智慧管网通信前置系统,可以实现多台前置机高效协同通信与负载均衡,能实时获取海量的城市管线设施传感数据,是一种通信能力可扩展的高性能通信前置系统。     

公共服务共享平台设计与研究——以白银市为例

实现对智慧城市大数据中公共服务类的多尺度、非结构化、多源化、海量数据共享与应用是智慧城市建设所面临的巨大挑战。本文以白银市公共服务实体为研究对象,研究并设计了白银市公共服务共享平台。分析了公共服务数据内容,按照空间数据和属性数据两大类进行采集、处理以及数据建库。最后设计了共享平台总体结构框架和公共服务数据显示、编辑、检索和空间分析等功能。     

智慧旅游城市旅游竞争力评价

提升旅游竞争力是智慧旅游城市建设的核心目标。在借鉴前人研究的基础上,建立包括5个一级指标、14个二级指标和33个三级指标的智慧旅游城市旅游竞争力评价指标体系,选取北京、南京、武汉、成都、大连、厦门等12个首批国家智慧旅游试点城市,通过模拟仿真运算构建智慧旅游城市旅游竞争力评价BP神经网络模型,并运用该模型对上述智慧旅游城市旅游竞争力进行评价和分析。结果表明：① 旅游科技创新竞争力是影响智慧旅游城市旅游竞争力最关键的一级指标,其他一级指标按重要性排序依次为旅游经济发展竞争力、旅游发展保障竞争力、旅游发展潜力竞争力和旅游环境支撑竞争力;② 中国智慧旅游城市旅游竞争力整体水平不高且极不均衡,根据评价等级和竞争态势分为5类。第一类北京市是中国智慧旅游城市旅游竞争力的标杆,5项一级指标评价值均领先于其他城市,总评价值高达0.887,评价等级AA、竞争态势“优势”;第二类南京市旅游环境支撑竞争力评价值与北京市并列第1,旅游经济发展竞争力、旅游科技创新竞争力和旅游发展保障竞争力评价值均位列第2,总评价值0.536,明显高于除北京市外的其他智慧旅游城市,评价等级BB、竞争态势“较强”;第三类武汉、大连、成都、厦门、镇江、温州、烟台7市代表目前中国智慧旅游城市旅游竞争力的普遍水平,5项一级指标评价值偏低且差距不明显,总评价值在0.3~0.4之间,评价等级B、竞争态势“一般”;第四类福州、洛阳2市绝大多数一级指标评价值较低,总评价值在0.2~0.3之间,评价等级CC、竞争态势“较弱”;第五类黄山市总评价值仅0.176,评价等级C、竞争态势“弱势”;③ 构建的智慧旅游城市旅游竞争力评价BP神经网络模型具有较好的科学性、普适性和可操作性,根据评价值的大小判断智慧旅游城市旅游竞争力的优劣,比照指标体系寻找差距并加以完善,同时对评价指标进行动态监测,将是智慧旅游城市旅游竞争力研究的重要发展方向。