浅析龙脉、龙穴在故宫风水中的运用

中国是一个有着悠久历史和灿烂文化的文明古国,北京城便是我们伟大祖国的首都,它有着三千多年的历史,优越的地理位置使它成为历代建都最佳的风水之城——天、地、人合一之城,它保留有我国最大、最完整的古建筑群——故宫。它建造时的严整规划和辉煌壮丽的宫殿,深受中国传统文化和风水术的影响,无处不深深地打上了风水操作的烙印。     

传统文化在城市印象招贴设计中的运用

研究传统文化在城市印象招贴设计当中的运用,目的旨在于发掘传统文化,将传统文化与招贴设计相结合,利用招贴是传达信息的载体这一功能来对城市文化进行宣传,塑造城市的文化品牌。论文通过对传统文化在城市印象主题招贴设计当中运用的调研和分析,发现传统图形、色彩和文字在城市印象招贴设计当中的重要意义。     

城市街区空间引导系统的设计思考

城市街区空间引导系统与人们的日常生活息息相关,为人们的出行提供了便捷的标识引导,同时它也是城市形象的重要组成部分之一。本文分析总结了该系统的设计原则,并从视觉传达学科入手分析其视觉元素的设计。为了设计无语言障碍和有个性、地域化的城市街区空间引导系统,从符号、文字、色彩三方面对其进行设计思考。     

重庆旧城改造中的历史文化保护研究

重庆旧城是经过漫长的历史发展而逐渐演化形成的,旧城改造"一刀切"的做法会产生多方面的问题,只有对其社会、经济、文化形态有清醒而深刻的认识基础上,才能实现可持续发展的目标。历史文脉的保护与传承是重庆旧城改造的重要组成部分,本文在对其历史文化分类归纳基础上,提出了相应保护措施,力图为重庆旧城改造提供借鉴。     

模拟退火粒子群算法在新交通控制模型中的应用

城市交通系统是个随机性很强、复杂的巨型系统,为了获得良好的通行效率,提出了一种基于模拟退火温度的自适应粒子群优化算法,同时给出了一种城市区域交通协调控制信号配时模型,然后将提出的方法应用于此模型。仿真结果表明：这种算法不仅能够克服基本粒子群算法陷入局部寻优的缺点,而且算法的收敛性和稳定性都很好,同时也表明该模型是可行的、有效的。     

Network Intrusion Detection in Internet of Blended Environment Using Ensemble of Heterogeneous Autoencoders (E-HAE)

Contemporary attackers, mainly motivated by financial gain, consistently devise sophisticated penetration techniques to access important information or data. The growing use of Internet of Things (IoT) technology in the contemporary convergence environment to connect to corporate networks and cloud-based applications only worsens this situation, as it facilitates multiple new attack vectors to emerge effortlessly. As such, existing intrusion detection systems suffer from performance degradation mainly because of insufficient considerations and poorly modeled detection systems. To address this problem, we designed a blended threat detection approach, considering the possible impact and dimensionality of new attack surfaces due to the aforementioned convergence. We collectively refer to the convergence of different technology sectors as the internet of blended environment. The proposed approach encompasses an ensemble of heterogeneous probabilistic autoencoders that leverage the corresponding advantages of a convolutional variational autoencoder and long short-term memory variational autoencoder. An extensive experimental analysis conducted on the TON_IoT dataset demonstrated 96.02% detection accuracy. Furthermore, performance of the proposed approach was compared with various single model (autoencoder)-based network intrusion detection approaches: autoencoder, variational autoencoder, convolutional variational autoencoder, and long short-term memory variational autoencoder. The proposed model outperformed all compared models, demonstrating F1-score improvements of 4.99%, 2.25%, 1.92%, and 3.69%, respectively.     

沿海城市暴雨-高潮位复合致涝区划研究北大核心CSCD

由于暴雨和高潮位的共同影响,沿海城市更容易遭受内涝灾害。暴雨和高潮位影响区域致灾因子划分是减灾措施布设的重要因素。本文提出了致灾因子区划方法,并进行了区划方法的效果分析。以海口市主城区为例,基于城市暴雨污水及流域雨洪管理建模软件构建一二维耦合城市内涝模型,计算不同组合工况下的淹没水深和淹没范围,将内涝区域划分为降雨影响区、潮汐影响区和共同影响区,并对三个区域进行了减灾措施优化分析。结果表明,潮汐影响区、共同影响区和降雨影响区距海岸线逐渐变远;降雨影响区布设蓄水池的效益要明显优于潮汐影响区,而潮汐影响区布设止回阀的效益要优于降雨影响区。因此,通过内涝区域划分可以更高效地布设防涝措施。     

宁夏城市形象宣传招贴设计应用研究

目的研究以《印象·宁夏》为主题的宁夏城市形象宣传招贴设计。方法分析国内关于城市形象宣传设计的发展现状,以《印象·宁夏》为主题案例分析城市形象招贴的设计方法。结论城市形象宣传招贴的设计应从城市的形象定位、城市文化的提炼、城市形象招贴的创意思路3个方面入手,结合招贴设计的基本原则,将提炼出的信息符号进行视觉化的创意设计实践。     

低影响开发(LID)透水砖铺装系统的研究进展

透水砖铺装系统是现阶段我国海绵城市建设中重要的透水铺装系统技术之一。为了充分认识该领域已有的应用和研究成果,开展更深入的透水铺装系统技术探索和应用研究,对透水砖铺装系统的国内外应用和研究现状进行了分析总结。简述了透水铺装材料的分类和特点,分析了国内外应用情况,分别对混凝土透水砖、陶瓷透水砖、砂基透水砖的国内外研究现状进行了评述。最后指出现阶段研究存在的问题,并提出了建议和展望。     

The Role of Deep Learning in Parking Space Identification andPredictionSystems

In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement in parking identification and prediction systems. However, no work reviews DL approaches applied to solve parking identification and prediction problems. Inspired by this gap, the purpose of this work is to investigate, highlight, and report on recent advances in DL approaches applied to predict and identify the availability of parking spaces. A taxonomy of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature, and by doing so, the salient and supportive features of different DL techniques for providing parking solutions are presented. Moreover, several open research challenges are outlined. This work identifies that there are various DL architectures, datasets, and performance measures used to address parking identification and prediction problems. Moreover, there are some open-source implementations available that can be used directly either to extend existing works or explore a new domain. This is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart cities. This study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits, the convergence of these two types of systems and DL brings about new issues that must be resolved in the near future.