International Arts Festivals Visitors＇ Motives and Profile Characteristics： The Case of Two Medium-Sized Greek Cities

This paper presents an analysis of two renowned international arts festivals visitors＇ motives and profilecharacteristics, in two medium-sized Greek cities： the Kalamata International Dance Festival （KIDF） and theDrama International Short Film Festival （DISFF）. The purpose of the study was to determine the reasons visitorsattend these festivals, which is necessary for building more concise marketing strategies and, therefore,more successful and sustainable events, with long-term benefits, ranging from the local to the national levels.The research addresses international arts festivals that share four main characteristics： （1） they host internationalprofessional artists; （2） they feature explicitly-stated artistic visions and objectives; （3） they are publicly funded;and （4） they have achieved a consecutive 23 years of successful presence in each city. These two case studiesrepresent two cultural events which have managed to maintain their popularity and high status, on the Europeanfestival map, as well as to raise their host cities＇ cultural and tourism standards, despite the serious economiccutback they have both faced. Due to limited available funds, the festivals lack marketing resources andspecifically data collection on visitor motivation, a gap which this study aims to remedy. Primary datawere collected with the aid of online structured questionnaires, distributed and collected during autumn2016. Altogether, 130 questionnaires were answered by visitors of the DISFF and 186 questionnaires wereanswered by visitors of the KIDF. Even though both festivals share similar characteristics regarding theirorganization and their aims, our analysis emphasized the heterogeneity of the motives of attendance in connectionwith the visitors＇ profile characteristics, for each event. While some similarities were found, especially betweendemographic sample characteristics and visitors＇ profiles, the general picture to emerge from the findingsindicates significant differences between the two cases. Arts festivals-goers do not appear to constitute a singlehomogeneous market; rather, each event appears to attract different audiences for different reasons. Theimplications of these findings, deriving from statistical analysis, are discussed and suggestions for further researchare outlined. This research aims to contribute to knowledge concerning the marketing strategies of internationalarts festivals in medium-sized cities, useful for research and academic purposes, as well as to local and nationalauthorities and other agencies and bodies, responsible for urban tourism and cultural city/town planning andmanagement.

Five-force Analysis and Market Strategies of Budget Hotels in Small and Medium-sized Cities --ake Xuchang Jinjiang INN for Example

Budget hotels, as an emerging hotel model, were started and attained a rapid development in China in the last ten years, and have proven to be important part of China抯 hotel industry. As competitions in the hotel industry become increasingly fiercer, budget hotel brands launch a fight for seizing more market share. Therefore, it is necessary for Xuchang Jinjiang INN as a famous hotel brand to be distinguished from the hotel product strategies of the developed economic areas in the development environment of the small and medium-sized tourism cities, so as to adapt to the characteristics of regional market.

Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

Smart cities make use of a variety of smart technology to improve societies in better ways.Such intelligent technologies,on the other hand,pose sig-nificant concerns in terms of power usage and emission of carbons.The suggested study is focused on technological networks for big data-driven systems.With the support of software-defined technologies,a transportation-aided multicast routing system is suggested.By using public transportation as another communication platform in a smart city,network communication is enhanced.The primary objec-tive is to use as little energy as possible while delivering as much data as possible.The Attribute Decision Making with Capacitated Vehicle(CV)Routing Problem(RP)and Half Open Multi-Depot Heterogeneous Vehicle Routing Problem is used in the proposed research.For the optimum network selection,a Multi-Attribute Decision Making(MADM)method is utilized.For the sake of reducing energy usage,the Capacitated Vehicle Routing Problem(CVRP)is employed.To reduce the transportation cost and risk,Half Open Multi-Depot Heterogeneous Vehicle Routing Problem is used.Moreover,a mixed-integer programming approach is used to deal with the problem.To produce Pareto optimal solutions,an intelligent algorithm based on the epsilon constraint approach and genetic algorithm is cre-ated.A scenario of Auckland Transport is being used to validate the concept of offloading the information onto the buses for energy-efficient and delay-tolerant data transfer.Therefore the experiments have demonstrated that the buses may be used effectively to carry out the data by customer requests while using 30%of less energy than the other systems.

High Performance Priority Packets Scheduling Mechanism for Big Data in Smart Cities

Today,Internet of Things(IoT)is a technology paradigm which convinces many researchers for the purpose of achieving high performance of packets delivery in IoT applications such as smart cities.Interconnecting various physical devices such as sensors or actuators with the Internet may causes different constraints on the network resources such as packets delivery ratio,energy efficiency,end-to-end delays etc.However,traditional scheduling methodologies in large-scale environments such as big data smart cities cannot meet the requirements for high performance network metrics.In big data smart cities applications which need fast packets transmission ratio such as sending priority packets to hospitals for an emergency case,an efficient schedulingmechanism ismandatory which is the main concern of this paper.In this paper,we overcome the shortcoming issues of the traditional scheduling algorithms that are utilized in big data smart cities emergency applications.Transmission information about the priority packets between the source nodes(i.e.,people with emergency cases)and the destination nodes(i.e.,hospitals)is performed before sending the packets in order to reserve transmission channels and prepare the sequence of transmission of theses priority packets between the two parties.In our proposed mechanism,Software Defined Networking(SDN)with centralized communication controller will be responsible for determining the scheduling and processing sequences for priority packets in big data smart cities environments.In this paper,we compare between our proposed Priority Packets Deadline First scheduling scheme(PPDF)with existing and traditional scheduling algorithms that can be used in urgent smart cities applications in order to illustrate the outstanding network performance parameters of our scheme such as the average waiting time,packets loss rates,priority packets end-to-end delay,and efficient energy consumption.

On the Development Principles and Models of Recreational Belt around Small and Middle Cities

The definition and type of recreational belt around metropolis were introduced,the development principles of recreational spot around small and middle cities were analyzed.With Baoding City as an example,the empirical analysis was conducted,and the development models of recreational spot around metropolis in Baoding City were put forward.

Sustainable Development Research in Chinese Medium-Sized City Based on SLEUTH

Compared with megacity, the medium-sized city is playing a more and more important part in the rapid urbanization process in China. Due to the expanding scale of the medium-sized city, urban growth is sprawl and this way leads to ecological, social and environment problems that are unsustainable. To measure the urban growth of the medium sized city, cellular automata (CA) model is employed. CA has proven to be a popular and effective modeling approach to investigate dynamic urban growth systems and for evaluating the impacts of possible policy options. We use the SLEUTH model, which is a well known CA model, to simulate the future urban growth of Huaian, Jiangsu province of China. The results confirm the value of SLEUTH which provides a rich exploratory of knowledge for evaluating the effects of possible decision-making in local government.

A Case Study of Affordable Housing in a Medium-Sized City in Central China

The main task of this paper is to explore the housing condition and housing policy in the vast but long-neglected middle-sized cities in China. Under the requirement of ＂Construction of 10 Million Units in 2011＂ from the central government, the affordable housing has started its nationwide building. Medium-sized cities are facing different developing periods but applying same housing policy as big cities. The paper examines the economic and social condition of the case city to find out the housing problems. It concludes that houses are affordable in these medium-sized cities, but housing policies are not implemented well. The paper proposed that housing affordability in medium-sized city is not about quantity but about quality. To keep houses affordable in these medium-sized cities, housing market, legislation, urban planning, public participation and intensive developments are all important.

北京市职住失衡驱动因素研究及其对雄安新区规划的启示

职住失衡是近年来国内城市治理领域常见的“大城市病”之一,北京市尤为典型与严重,其成因与治理经验对新城规划有重要借鉴意义。我们采用“昼夜人口比”作为职住失衡水平的测度,发现由于城市产业结构的空间布局由核心城区向外围郊区扩散的速度暂未能跟上人口向外围转移的速度,考察期内北京市整体职住失衡程度趋于加剧,核心城区越来越偏向工作区,而外围郊区尤其是近郊区县则愈加偏重居住功能。基于2005—2021年北京市16区县面板数据模型的一系列实证研究发现:区县房价收入比越高,该区县越倾向成为常住人口流出的工作区;而地铁开通以及教育、医疗、零售市场的发展则会吸引居住人口流入,使之更偏向于居住而非工作的“睡城”,且该影响在去除了密云、延庆、平谷三个远郊区县后更为显著;各因素对核心城区与近郊区职住比的影响存在显著差异。雄安新区等国内新城规划时应注意借鉴北京经验,通过在城市区域内多点均衡配置优质产业、平衡区域间房价与房租差距、设置网格状交通系统等措施预防严重职住失衡现象。

站城一体化视角下高铁新城演变效应实证研究——以杭州东站城东新城为例

以高铁站点为核心,综合发展居住、商业、办公等功能的高铁新城建设模式逐渐被规划开发者所接受。高铁新城的发展是否达到规划预期,高铁站对城市的影响强度是研究的目标。文章以杭州东站所在的城东新城为对象,通过多年卫星地图、空间句法和大数据3种方法,揭示了城东新城12年的发展与站城融合发展预期目标的协同情况。从道路网络构成、房地产开发、商业建设情况、乘客微观感知4个考察维度建立高铁新城演变效应研究体系,证实了该体系对研究站与城关系的科学性和理论性。研究旨在通过综合多种数据采集方法,从城市设计和微观感知角度获得高铁站点对城市的具体发展效应,对我国高铁新城的城市规划评估体系和开发模式提供实证借鉴。

站城融合背景下的高铁站域空间利用一体化评价——以武汉市为例

在站城融合的背景下,交通枢纽站成为承载多种功能的重要的复合型公共空间,为使高铁站域空间成为城市发展中具有吸引力的核心部分,对新一代高速铁路枢纽提出了站城一体化的要求,以更好地满足人们对交通、娱乐、休闲的需求。该文以武汉市三个主要高铁站为例,依托地理信息科学(GIS)技术,结合多源大数据,通过借鉴日本站城一体化的发展模式,从交通可达性、设施便利性、功能混合度和土地开发强度四个维度建立高速铁路枢纽空间利用一体化评价指标体系,对铁路枢纽一体化水平进行了综合系统的评价。相关结果对高铁站的建设与完善提供了借鉴。

基于物联网大数据的智慧城市可持续建设研究

文中针对智慧城市建设可持续发展与规划的重要意义和重大影响,利用物联网和大数据分析技术,提出了一种以物联网和大数据分析为基础的智慧城市可持续发展规划与建设框架。首先,设计了一种基于物联网的异构聚合智慧城市架构;然后,对框架进行了大数据分析与探讨;最后,利用HadoopEco系统,对数据吞吐率曲线与数据量大小进行了评估,验证了所提框架的实用性和先进性。

智慧城市时空大数据平台建设与实践——以宜兴市为例

在新一代信息技术与城市现代化的深度融合下,智慧城市的建设显得尤为重要。城市时空大数据平台是智慧城市的基础支撑。目前的智慧城市普遍存在时空数据单一、数据更新周期长、信息孤岛现象严重等问题。智慧宜兴时空大数据平台建设项目构建统一的时空基准,将各类信息资源集中于一体,引入基于HMM模型的中文地名地址引擎构建技术,并提出一种基于深度学习的电子地图快速更新方法。该平台可为用户提供大量的时空数据和分析服务,具有明显的社会效益和推广价值,为创建“智慧宜兴”奠定了坚实的基础。

基于大数据的智慧城市空间规划与城市建设方法研究

为促进城市现代化管理水平提升,促进新型智慧城市建设与发展,引入大数据技术,开展智慧城市空间规划与城市建设方法研究。文章从智慧城市空间规划与发展战略制定、智慧城市空间质量评价、智慧城市空间规模预测等方面提出一种全新的智慧城市空间规划思路。在此基础上,基于大数据,提出打通智慧城市数据通道、加强智慧城市大数据规范化管理的城市建设方法。

生态水文系统支撑城市韧性安全建设的若干思考

近40年城市生态水文学应用研究的重要进展,特别是区域水循环要素的优化调控,有效地支撑了韧性安全城市建设。在城市生态水文系统理念的指导下,北美、欧洲和中国相继出现了低影响开发、水框架指令、海绵城市与气候适应型城市建设。全球变化和人为活动相互作用产生了复杂的城市生态水文过程,自然水循环模式已转变为“自然-社会”相互作用的二元水循环模式。面对全球变化,韧性安全城市的建设更加关注对气候变化的减缓和适应,特别是对极端天气气候事件的适应能力。我国长期持续大规模的城市开发建设,强烈影响和改变着区域水循环关键要素,城市地下空间开发利用和地面沉降面临着极端天气气候情境下的灾害风险。因此,地学基础条件及其韧性构成了城市韧性安全底座的基础。基于二元水循环关键要素调控设计的减缓和适应对策,在新一轮气候适应型城市建设中发挥了重要作用。“气候变化—区域二元水循环—水平衡调控—灾害风险”“遥感大数据—台站网小数据—传递函数—云孪生”,可作为一种地球大数据支撑韧性城市建设与可持续发展的技术框架和方法组合。上海作为长江流域的龙头和海陆交互敏感区域,城市韧性安全还面临着海平面上升的考验。在气候变化情景下区域二元水循环关键要素调控,可作为地学服务上海地下空间安全及城市韧性安全的一个策略。

基于CIM的智慧园区技术探索与落地实践

城市信息模型(CIM)是我国智慧城市建设及城市数字化转型的重要抓手之一。其核心技术主要包括物联感知技术、GIS与新型测绘技术、孪生建模技术、可视化渲染技术、仿真推演技术和交互控制技术等。本文以独角兽岛智慧园区项目为例,探讨CIM技术、物联网技术、大数据技术及可视化渲染技术的交汇与融合应用,设计并建设应用场景支撑产业园区全生命周期的规划、建设、管理、运营以及园区空间价值提升,形成园区、产业、市场和社会的数字化运行理念和方式,并提炼出项目中展现出的特色与亮点,为推动我国智慧园区及智慧城市的建设提供基础支撑和建设经验。

基于本体和知识图谱的城市空间数字底座架构及应用

为支撑城市数字化转型,解决目前智慧城市数据不能满足多领域兼容覆盖的需要、数据孤岛等问题,本文提出融合城市动静态多源数据、城市数据运算方案和数据组织管理方案的城市空间数字底座的概念,进而提出一种依托本体框架的城市空间数字底座架构,以多源多模知识图谱为核心来管理城市治理的数据模块、数据运算模块、数据可视化模块和城市服务模块,使得所有数据和事件、行为都在同一框架与协议下运作。本架构有三个特点:①依托本体框架,构建语义解释器覆盖领域全要素,保证数据结构完整和质量可靠;②数据与业务脱钩,原始数据从具体事物中抽象出来,重构为知识单元,适度脱敏推动数据融合;③空间运算升级为知识运算,利用知识图谱通过知识推理、知识发现等来优化传统计算,拓展服务边界及节省运算资源。通过知识图谱的管理架构,可以保证城市空间数字底座的数据质量可靠性、完整性、可解释性和共享性,确保了空间数字底座对城市空间信息服务的支撑能力。

基于新型探测资料对西安一次弱降水预报失误的原因分析

利用微波辐射计、激光测风雷达、多普勒雷达、相控阵雷达等新型探测资料、地面加密观测资料、ERA5再分析及多模式数值预报结果对2022年4月24日西安城区一次弱降水预报出现明显失误的原因进行分析,结果表明:①全球数值预报模式和中尺度数值预报模式对本次过程西安城区均报有明显降水,主要原因为模式对低层相对湿度预报明显偏大;②多种新型探测数据分析认为近地层湿度条件较差及中层的绝对水汽含量低,中层的干暖空气不利于成云致雨,垂直上升运动不强,且由于低层非常干燥,使水滴在下沉过程中蒸发,从而无法形成雨滴下落,这些原因共同造成西安城区无降水,低层相对湿度预报偏大是造成这次西安城区降水预报失误的主要原因之一;③造成西安城区近地层湿度条件差的原因是城市干热岛效应和低层干暖平流输送,且降水云团翻越秦岭后其湿空气绝热下沉至城区后出现增温降湿,使得城区形成较为深厚的干层,即使有雨滴在下落过程中也会造成更强的蒸发,这也是城区没有降水的重要原因之一;④预报员主观预报订正出现空报主要是源于对边界层水汽、抬升条件等关键降水要素缺乏订正能力,且对大城市的干热岛效应和秦岭山区地形影响研究不足。

城市大数据认知计算研究与应用进展

城市大数据为城市运行状态估计与综合决策提供理论与行动支撑,而其多源异构、耦合度低及动态变化等特点给传统的集成分析带来极大挑战。认知计算适用于时变多维、复杂多样数据的分析与挖掘,并可对问题进行自适应学习与进化,是解决城市大数据问题的重要途径。文中以城市大数据为背景,根据城市大数据的不同类型结构等特点,针对性地按照认知流程的4个环节对相应处理方法进行归纳,并进一步从知识驱动、数据驱动以及知识与数据协同驱动的角度,对上述具体方法进行概念级分类。最终形成城市大数据认知流程中不同驱动方式的方法间有机协同,从感知理解到决策行为的城市大数据认知闭环。同时从应用领域多角度综述了城市大数据认知计算的研究与发展现状。最后讨论了认知计算在城市大数据建设领域面临的挑战,并对未来发展趋势和研究方向进行了思考和展望。

基于现代测绘技术的基础地理空间数据生产——以智慧滕州时空大数据平台建设为例

智慧城市时空大数据平台建设是构建数字中国的重要组成部分,而基础地理空间数据的生产是建设智慧城市时空大数据平台的关键步骤。以智慧滕州时空大数据平台建设项目为例,阐述了利用先进的现代测绘技术进行基础地理空间数据生产的技术方法和具体流程,包括实景三维模型数据生产、矢量数据生产和更新、地理实体数据生产、街景数据生产和地名地址数据更新等方面,为智慧城市的建设提供了科学、实用的技术方法,并积累了宝贵的经验。