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Objectives: In the large-scale of virtual reality scene, it is difficult to add all graphics data into the video memory for rendering. Removing the occluded objects in advance by visible query technology can reduce the amount of data loaded on the display end to improve the rendering efficiency. Therefore, the research of visible query method for regional objects has important application value for real-time rendering of large-scale urban scene. Methods: We put forward a distributed visible query method based on Map-Reduce. In the map phase, we apply a hierarchical axis-aligned bounding box as viewpoint space partition. When the number of 3D objects in viewpoint space partition exceeds the threshold, the axis-aligned bounding box continues to be divided into sub- boxes. After the above process, the map tasks produce GeoTuples with the VSPID as key and visible query candidate set as value. In the reduce phase, a viewpoint is created for each leaf axis-aligned bounding box where the binary space partitioning trees are build and the visible set is calculated using real-time occlusion algorithm. Results: The experiment results with a building compound, containing more than 200 000 geometric solids, in Shenzhen, China show that: (1) There is no simple linear relationship between the running time of distributed visible query and the number of viewpoint space partitions. (2) Running time and parallelism are not simply inversely proportional. The computational efficiency of each process first increases and then decreases with the increase of parallelism. About 48 parallelism, the process has the highest efficiency. (3) Whether the distributed approach is better than the traditional approach depends on the number of 3D objects. After the amount of 3D objects reaches about 40 000, the distributed algorithm begins to be better than the traditional algorithm. Conclusions: The computational experiments reveal the proposed algorithms outperform competitors in terms of the processing efficiency and feasibility, which can meet the requirement of visible query in large-scale scenarios. [ABSTRACT FROM AUTHOR]

Taking 13 cities in Beijing, Tianjin and Hebei as the research objects, this paper constructed the urban smart development index system from three aspects: smart space construction, smart element allocation and smart welfare performance, measured the urban smart development level in Beijing, Tianjin and Hebei from 2008 to 2018, and used ArcGIS software to realize the temporal and spatial measurement performance of smart development level. The obstacle degree model was used to reveal the criterion-level factors that hinder the smart development of Beijing, Tianjin and Hebei cities. The main conclusions are as follows: (1) The smart development level in Beijing, Tianjin and Hebei is low, the research period shows a weak fluctuation and downward trend, and there is room for improvement. (2) From the spatial difference of smart development level, the double core trend with Beijing and Tianjin as the high level is obvious, showing a downward trend from the center to the surrounding. (3) From the overall barrier performance of study area, smart welfare performance accounts for the largest proportion, smart space construction takes the second place, and smart factor allocation is the lowest. (4) The obstacles to smart development in different cities vary. The obstacles in Beijing and Tianjin are mainly focused on smart welfare performance. As the main core area to undertake Beijing's noncapital functions, smart space construction and smart element allocation are the obstacles in most cities. [ABSTRACT FROM AUTHOR]

Objectives: Facing the demand for mobile intelligent services in the era of internet of everything, it is an urgent need to establish an aerial-ground collaborative intelligent service platform. Due to the limitations of core equipments and algorithms, the development of aerial-ground collaborative mobile intelligent service platform is relatively slow. Methods: Therefore, we break through the core technologies of realtime position and attitude measurement of sensors, develop the airborne and vehicle mounted aerial-ground multi-platform collaborative networking remote sensing observation system, and realize the quality improvement and intelligent and fine processing of multi-source remote sensing images, which can effectively support remote sensing mapping services, and improve the level of automatic processing of remote sensing information. Results: Thus, our research solves the problems of “accuracy, speed and flexibility” in the aerial-ground collaborative intelligent service platform, and realizes the global autonomous positioning of “BeiDou navigation satellite system with position and attitude measuring instrument”, rapid target searching under the aerial-ground collaborative networking, and automatic change checking under intelligent processing. Conclusions: The aerial-ground collaborative mobile intelligent service platform has been widely used in the monitoring of geographical conditions, smart city planning and construction, emergency mapping support and other industries. [ABSTRACT FROM AUTHOR]

Traffic flow prediction is an important and challenging task in building smart city. Accurate forecasting requires consideration of spatio-temporal characteristics consisting of multiple influences such as holiday, similar node, and weather. In order to accurately capture the spatio-temporal characteristics of road network intersections, this paper proposed a prediction model based on graph convolutional neural network, temporal algorithm Prophet and Pearson correlation coefficient to achieve accurate prediction of intersection traffic considering spatial structure, similar nodes, holidays and other influencing factors. Firstly, it introduced pearson correlation coefficient to reduce the influence of similar nodes to improve the temporal algorithm for capturing temporal features. Secondly, it used the graph convolution neural network to capture spatial features; Finally, it determined the fusion weights of the graph convolutional network and the temporal algorithm by linear regression to obtain the results of spatio-temporal fusion prediction. This paper finally extracted the intersection traffic data based on the analysis of Chengdu taxi trajectory data and conducted traffic prediction experiments. The results show that the accuracy of the model proposed in this paper is better than that of most existing baseline methods, compared with the T-GCN, ASTGCN, and AGCRN models, the MAE is reduced by 1.623, 0.724, 0.161, respectively, and the accuracy is improved by 0. 144, 0. 068, and 0. 021, respectively, which verifies the effectiveness of the model in traffic intersection flow prediction. [ABSTRACT FROM AUTHOR]

Objectives: With the rapid development of the reality acquisition technologies, such as laser scanning and structured light scanning, point cloud has become a high-precision three-dimensional holographic representation for the physics world. As the third important data source, point cloud is very suitable for presenting 3D model and geographic and spatial information, and pushes forward an immense influence on smart city, autonomous driving application and augmented reality. However, the massive, unstructured, and uneven density of point cloud data brings challenges to onboard and offboard storage as well as real-time transmission. Hence, efficient compression methods, which balance between bit rate and quality, are mandatory for ensuring the storage and transmission of such data. Methods: Firstly, we describe different families of approaches in details and summarize the basic technologies that are usually used in 3D point cloud compression. Secondly, we provide detailed description of three open source point cloud codec algorithms and their coding performances. Finally, the promising development tendency of the static point cloud compression is summarized. Results: This paper summarizes the state-of-the-art of domestic and foreign static point cloud compression algorithms, the standard specifications released by moving picture experts group and evaluation metrics for point cloud compression. Conclusions: The purpose is to open up a vision for the further research on the static point cloud compression technology to a certain extent, boost the advancement of theoretical research significance and practical application value in this technical area. [ABSTRACT FROM AUTHOR]

Objectives: The k nearest neighbor query method under the road network environment plays an important role in geographic information system, point of interest discovery, smart city, data mining and material distribution. The existing methods mainly deal with the query problem that the query object and data object are single data type. However, in reality, the data object type of the target object set is often not single, and the query problem will become more complex. The existing nearest neighbor query methods in road network cannot directly solve the neighbor query problem in which the query object is a point and the data object includes the data mixed with points and line segments. In order to make up for the shortcomings of the existing methods, the nearest neighbor query algorithm of mixed complex data in the road network is proposed. Methods: The query process is divided into three parts: Preprocessing, data set reduction and data set refining. Firstly, the data set is preprocessed, the line segments are transformed into points. A mapping relationship is formed between the intersection of line segments in the road network and line segments, and the corresponding line segments are found by querying the location of the points. The query points, data points and Hilbert values are stored using arrays. Secondly, the data object set is refined preliminarily by pruning method and shortest path theorem to reduce the number of data objects, and the data set filtering algorithm is given. Finally, the points in the data set are further pruned to calculate the shortest path network distance from the query point to the points in the candidate set. Compared with these distances, the shortest path distance can be determined, and then the nearest neighbor is accurately found. Results: Experimental results show that the proposed algorithm effectively reduces the data set and the amount of calculation in the query process, further refines the nearest neighbor candidate set and reduces the query scope and the query time. There is no need to store the distance information between all boundary nodes in the road network, so a large amount of redundant distance information is eliminated. The data points and road network data that meet the pruning conditions around the query points are pruned. Therefore, the increase of road network scale has little impact on the time cost of the algorithm. Conclusions: The proposed algorithm can directly deal with the nearest neighbor query of mixed data in the road network environment. When the number of data objects and the scale of the road network are large, the algorithm has obvious advantages in central processing unit running time and input/output cost. [ABSTRACT FROM AUTHOR]

Objectives: Nowadays, a vast number of sensors and observation platforms bring a significant challenge for city perception. In the study, we focus on developing of a smart city tempo‑spatial perception system. The concept of smart city awareness base station (SCABS) is proposed in this study, and the SCABS architecture considers the above problems. Methods: Firstly, we systematically reviewed the requirements and the complexity of smart city perception and summarized the development process and network architecture of smart city perception technology systems. On this basis, the challenges of ubiquitous access, trusted perception and intelligent management in future smart city perception are addressed. Then, this paper sorted out the demand for future city perception services and constructed the architecture of SCABS. Finally, we standardized the technical indicators and service capabilities of SCABS. Results: We constructed the prototype of SCABS. According to the qualitative analysis and experiments based on real environment, we found that SCABS with unified access, integrated management, and edge intelligence can meet the access and management ability of multi‑platform and high‑density sensing resources. Conclusions: SCABS would act an essential role in the smart city perception in the future. As a cyber‑physical infrastructure, it expects to cover various scenarios in the city with multiple heterogeneous perception access and hybrid access of multi‑protocols, and to automatically support the multi‑platform coordinated control. The SCABS meets global, accurate, heterogeneous, and multiple sensory perception. The SCABS is expected to be one of the critical infrastructures of the future smart city. [ABSTRACT FROM AUTHOR]

BACKGROUND: 3D bioprinting has become a crucial research field of tissue engineering with the unceasing development of science and technology. Nevertheless, some limitations cannot be resolved. 4D bioprinting is the most emerging technology, and has become the major solution for the next generation of tissue engineering. OBJECTIVE: To introduce the materials and methods of 4D bioprinting in accordance with various shape transformation principles, and to explore the application of 4D bioprinting to tissue engineering and the current challenges. METHODS: “4D bioprinting, 4D biofabriation, printing, smart materials, smart scaffold, shape memory polymers, tissue engineering” in Chinese and English were utilized as search terms. A total of 127 related articles published from January 1, 2016 to January 1, 2021 were retrieved from CNKI, PubMed, and SCIE databases. After screening out by the first author and adding high-quality references, 106 articles were included for review. RESULTS AND CONCLUSION: (1) 4D bioprinting, the latest emerging technology, combines the concept of time with 3D bioprinting as the fourth dimension. 4D bioprinting can create complex and functional structures. (2) 4D bioprinting can make dynamic 3D biological structures by using smart materials. These structures can alter shape under various stimuli. (3) The functional transformation and maturation of printed cell structures are also considered a form of 4D bioprinting. (4) This technology provides an unprecedented potential for tissue engineering. In the field of biomedicine, although this technology has attracted great attention, more research and development are needed to realize clinical application, because it is still in the emerging stage. [ABSTRACT FROM AUTHOR]

How to realize safety data sharing and promote the integration of multi-source data is one of the important technical challenges faced by academic and industrial circles. In recent years,federated learning has received widespread attention, which is a new technology to deal with this challenge. Federated learning has been applied in fields such as smart healthcare and smart city construction, but there is little research in the field of potential trajectory data mining. To solve this problem, this paper proposed a distributed and secure framework named federated spectral clustering( FSC), and applied it to the spectral clustering of ship AIS trajectory data. In the FSC framework, it used the encrypted sample alignment technology and a homomorphic encryption scheme as building blocks for the clustering algorithm, guaranteeing the security of the data in the process offederal training executed by multi-participants. To illustrate the effect of this algorithm, this paper conducted the experiments on both synthetic datasets and ships AIS trajectory datasets. The comparisons of experiments results with other similar clustering algorithms demonstrate that, besides its security advantage, this algorithm performs well in terms of clustering effect. The results indicate that the FSC can obtain the main route in the marine navigation area, which can provide specialized support for the intelligence of maritime supervision systems. [ABSTRACT FROM AUTHOR]

China’s Beidou-3 global satellite navigation system, short for Beidou system（BDS）, was fully operational on July 31, 2020, which has become the basis of the interconnection and intelligence of all things in the information society. Based on the analysis of the architecture and key technologies of Internet of Things （IoT）, the service types of BDS, and the main mode of BDS applications in IoT, this paper proposes a BDSIoT technology architecture, which takes BDS’s positioning and timing as the main perception information, takes the short message and other characteristic services as the main information transmission means, and integrates Internet and artificial intelligence technology. Then, the typical application of BDS services in the IoT field is further analyzed, and the application mode of“IoT + BDS”is put forward. Finally, taking smart city, intelligent transportation and other applications as examples, the challenge of BDS is analyzed, the development advice is given, and the new driving force of BDS for innovation driven development is proved. [ABSTRACT FROM AUTHOR]

As long-standing goals and all-round development practices of agricultural and rural modernization of China, the rural revitalization strategy provides huge opportunities and spaces for the disciplinary innovation and development of all agricultural related disciplines. The purpose of this paper was aimed to analyze special requirements, objectives, tasks and implementation environment raised by the rural revitalization strategy, based on reviewing the references and development history of agricultural engineering, and to analyze impacts of the rural revitalization strategies on and demand for the adjustment of agricultural engineering innovation, so that to figure out the ways, means and measures for new round disciplinary adjustments and restructuring of agricultural engineering. In recent years, the disciplinary renovation and restructuring for all subjects have been encouraged and launched by the Ministry of Education, China. The new round adjustment of the discipline layout marked by the innovation and construction of new disciplines such as new engineering and new agriculture were given more attention on introducing new technological and industrial revolution achievements, and transforming and upgrading traditional engineering and agricultural science with information technology, digital technology and artificial intelligence. But it’s worth noting that insufficient attention had been paid to the expansion of agricultural and rural modernization roads and changes in development patterns caused by the rural revitalization in this important adjustment process. Agricultural engineering takes multiple and wide range responsibilities in offering scientific and technological support and talent training and cultivation, so that it plays a special and key role in the modernization of agricultural and rural areas. Information, communication, intelligent and smart technologies, and all new breaking through technologies should be introduced into agricultural engineering to equip and empower it more updated and effectively. Under such a background, more efforts should also be made in such important development consequences brought by the rural revitalization strategy. The disciplinary adjustment of agricultural engineering should be restructured and optimized according to the instructions of the national development strategies and its new application areas required by agricultural and rural modernization. The more attention should be paid to the influence of social and economic development mode and structural adjustment and upgrading on innovation and its correspondence. Great attentions should be paid to following key issues: 1) The implementation of the rural revitalization strategy has opened up some new development spaces for the disciplinary innovation of agricultural engineering and proposed new development requirements. 2) The development and extension of the agricultural engineering technology systems will extend from the agricultural production to rural multi-industrial integration, relying on all agricultural and rural resources. 3) The cultivation of agricultural engineering talents and the construction of educational scientific research systems should aim at the requirements of the whole process for all rural productions, as well for the construction of rural ecological systems. 4) The systematic construction and management of agricultural and rural industries in different regions should meet the needs of the urban-rural integration development and the modernization of new rural communities’ governance system. Currently, more reform, renovations and adjustments should be made to reshape the agricultural engineering to meet new needs of the rural revitalization, the new development fields and directions of agricultural engineering disciplinary innovation currently are more practical in rural e-commerce engineering, rural landscape construction and maintenance engineering, rural new industrial development space construction, rural ecological environment engineering, and rural social and economic management and governance system engineering. [ABSTRACT FROM AUTHOR]

License plate recognition is a significant technology to build a smart city transportation system. The current license plate recognition systems have achieved a good recognition and application effect for single-row license plates, nonetheless, these can’t satisfy the recognition need for license plates which contain stacked characters. Based on this problem, this paper proposed a method based on deep learning and independent of character segmentation to identify the license plates containing stacked characters. Firstly, the method corrected the tilted or distorted license plate, and used MobileNet-SSD algorithm to detect single-row characters and stacked characters in the license plate. Then, it sent stacked characters to the stacked character recognition network based on CTC loss and conducted the end-to-end identification without character segmentation. Result of the experiment indicates that this algorithm not only has high recognition accuracy for the license plate with stacked characters, but also adapts to the license plate under the complex environment such as tilt and distortion, greatly improves the generality of the license plate recognition system. [ABSTRACT FROM AUTHOR]

Objectives: Because of the fast growing acquisition of real‑time spatiotemporal data for various applications such as smart city or real‑time air‑quality monitoring, the traditional database technologies can‑ not satisfy the higher standards for large‑scale data indexing, querying, and storing operations. As the viable alternative, NoSQL databases that are scalable and possess fast input/output capabilities offer potential solutions to accommodate the needs. Methods: We propose a Hilbert curve and Cassandra technologies based approach for efficient indexing and storing of large‑scale spatiotemporal datasets aiming to provide an effective framework for processing, querying, and analyzing large amount of data with spatial and temporal features. For example, the dataset of vehicle trajectories contains valuable spatial and temporal features those are being employed in the real world. The collected spatiotemporal datasets are preprocessed in order to fit the proposed structures for different applications. Specifically, two types of query applications commonly used in the real world are the spatiotemporal range query and query upon vehicle IDs respectively. Two corresponding indexing structures are designed and implemented in order to accommodate the requests. S2 Geometry Library open sourced by Google is utilized to divide the earth surface into grids, and data points fall in grids are assigned with the specific IDs as the keys. The keys and columns are so designed by applying the Hilbert curve and Cassandra techniques that the resultant structures will physically store the spatially neighboring data points close to each other, and they are more suitable for large‑scale spatiotemporal data querying and analyzing applications. Results: The datasets acquired from the real applications are used to conduct the computational experiments to validate the efficiency of the proposed approach. The query efficiency and the time consumed to store large amount of spatiotemporal data are investigated and bench‑ marked against some existing database technologies. Conclusions: The computational experiments reveal the superiority of the proposed approach comparing to the existing methodologies, the required time to store (insert) data in the database is reduced by 6 times while the time needed to query data is decreased by at least 10 times. The efficiency of the proposed methodology is validate further by applying it to query the vehicle trajectories gathering the real‑time air quality data. [ABSTRACT FROM AUTHOR]

Software defined network(SDN) has attracted much attention in recent years.Some scholars have integrated it with smart city construction.In view of the current situation of decentralized traffic management and combined with the characteristics of SDN forwarding and control separation and centralized control,this paper introduced it into intelligent transport system(ITS),and proposed a collaborative management architecture to achieve collaborative management and improve traffic.Firstly,it expounded the characteristics of SDN,and proposed an intelligent traffic architecture based on SDN by using ITS characteristics and combining with ITS.Secondly,it built a collaborative management strategy model combining factors such as dynamic speed limit,path guidance and weather and compared with a single control strategy.Finally,through simulation experiments,it verified and analyzed the proposed architecture strategy.The experimental results show that compared with the single control strategy,the management under this architecture smooths the traffic flow,reduces the average delay at the intersection by 20.7%,reduces the average queue length by 35%. [ABSTRACT FROM AUTHOR]

Currently, China's big cities have a high degree of concentration and three-dimensional development. Traditional TOD theories can well explain the current TOD development model of China. In the context of developing a smart city and highly concentrated cities, this paper proposes a three-dimensional TOD (3D TOD) urban design model for the core area of an urban central railway station. The paper studies the theoretical basis for three-dimensional urban development and practical projects. Based on the characteristics of land use and urban functions in the core area of railway stations, six development types of the three-dimensional TOD model are studied: "Business + Commerce, Commerce + Public Hub, Business + Public Hub, Convention & Exhibition + Business, Commerce + Education, and Commerce + Historic District." Additionally, the technical framework for the intelligent three-dimensional TOD urban design method in the urban central railway station's core area is developed. Also, the core area's three-dimensional agglomeration development mechanism of the urban central railway station is studied to optimize the TOD theory and provide a reference for intelligent urban design. [ABSTRACT FROM AUTHOR]

City is the place aggregated massive human activities. City is the exchange hub of population flow, goods flow, information flow and currency flow, which is highly dynamic and complex. Smart city provides various tools to acquire spatiotemporal big data, such as satellite and drone remote sensing, mobile sensing, social sensing, crowdsourcing sensing, etc., which enable us to sense urban dynamics. This paper introduces the framework of urban dynamic sensing, describes the typical applications of spatial dynamics, human behavior dynamics and space behavior interaction dynamics, and discusses the problems, such as the uncertainty in spatiotemporal big data, the multi ⁃view ensemble learning in urban sensing, the verification of the urban dynamic results and the cascading influence of multi⁃urban factors. Outlooking the future, the study of urban dynamics should combine with real⁃time Internet of things data to sense multi⁃dimensional, multi⁃spatiotemporal resolution urban dynamic to enable refined urban governance and to effectively solve urban problems. [ABSTRACT FROM AUTHOR]

Physical space and social space constitute the dual space of human society. With the rapid de⁃ velopment and popularization of information and communication technology (ICT), information space has grown into the third space, which constitutes the ternary space of human society together with physical space and social space. Smart cities are the intelligent transformation of cities under the condition of ternary space. Its basic engineering logic is to establish the mapping from physical space and social space to informa⁃ tion space, and then feedback physical space and social space through information space to optimize the ur⁃ ban system and solve the urban problems. Geographic information system (GIS) is a technical science that depicts and expresses physical space and social space from the perspective of space. Establishing the intrin⁃ sic relationship of ternary space through GIS will be the logical basis for the construction of smart cities. Firstly, the GIS technology requirements of smart cities is analyzed from four aspects: Digitization, intelli⁃ gence, visualization and openness. Then, a GIS framework for smart cities is proposed, the core of which is shielding complex heterogeneous data downwards and enabling diverse applications upwards. Finally, the key research contents that need to be focused on is discussed, including unified urban data platform con⁃ struction, digital twins and visualization, two⁃way synchronized spatial intelligence, and open platform ser⁃ vices. [ABSTRACT FROM AUTHOR]

The pole-like objects are the impontant infrastructure in cities, and their automatic extraction is important for fast updating of smart city data. The vehicle-borne mobile measurement system can quickly acquire high-precision point cloud data of the objects in both roadsides. An automatic extraction method for pole-like objects from vehicle-borne laser point cloud data based on circular arc characteristic is proposed. Firstly, according to the target distribution morphology in single and adjacent scanning lines, the non-pole column part in original point cloud is filtered by clustering and denoising. Then, the circular arc point set is searched by constraint random sample consensus (RANSAC) operator, and the 3D statistical regularity of the circular arc are used to identify the column part of pole-like object accurately. Finally, according to the spatial morphology of the target point cloud, the condition of region growing is dynamically determined, and the complete point cloud of different pole-like objects is searched. Experimental results show that this method can effectively reduce noise interference of non-pole-like objects nearby in pole-like objects extraction and has better adaptive ability. [ABSTRACT FROM AUTHOR]

In the context of the Trump administration’s escalating strategic competition with China, US strategic experts have a negative perception of the Digital Silk Road, believing that it poses challenges to US economic interests, technology development, military and intelligence security, international standards and ideologies. The US’ concern about the Digital Silk Road is to counter the Belt and Road Initiative, and also closely related to its China policy featuring the blocking of technology transfer, reflecting that US strategic experts are viewing its China policy from the perspective of “digital geopolitics”. In response to the Digital Silk Road, the US has increased investment in digital infrastructure, intensified crackdown against Chinese companies and deepened cooperation with its allies and partners. Besides, in order to contain China’s “digital influence”, the US has coped with economic issues with security thinking and stirred up ideological differences. The US regards Southeast Asia as the primary region in counterbalancing the Digital Silk Road, constantly improves the mechanisms and measures under the framework of the “Indo- Pacific Strategy” and strengthens cooperation with Japan and other countries on digital economy, smart cities, cyber security and other fields to compete with China. [ABSTRACT FROM AUTHOR]

For the multi-attribute group decision-making problem in Pythagoras environment, firstly, this paper combined the Pythagorean fuzzy number and the power-average operator to creatively expand a new improved weighted support, then based on this, it proposed a Pythagorean fuzzy interaction power-average operator with improved weighted support, and discussed the properties of the operator. Then it established a decision-making method that could reflect the interaction between decision attributes under Pythagoras fuzzy background. Finally, it was applied to the evaluation of smart cities. The case study shows that the method can solve the problem of actual multi-attribute group decision-making and can be further applied to the fields of intelligent logistics, pattern recognition and artificial intelligence. [ABSTRACT FROM AUTHOR]

Smart cities cannot be separated from spatiotemporal location big data. This paper summarizes the needs of spatiotemporal location big data for public epidemic events at home and abroad, investigates the specific services that current spatiotemporal location big data can provide in public epidemic events, and discusses the current stage of spatiotemporal location big data services that cannot meet the requirements of public epidemic events. This paper also focuses on how to improve the spatiotemporal location big data services in the next stage to better serve the public epidemic prevention and control, and gives advice on spatio-temporal location service construction at ordinary times and data sharing mechanism in “wartime”. This paper aims to take scientific measures to improve the spatiotemporal big data services, strives to establish a technical support system for public epidemic prevention and control at ordinary times, and introduces a “wartime” spatiotemporal location big data sharing mechanism for epidemic prevention and control. [ABSTRACT FROM AUTHOR]

In the Report uring the 18th National Congress of the Communist Party of China in 2012, President Xi Jinping proposed that we should speed up the construction of an ecological civilization system and resolutely fight the battle against pollution, which is presented in the new round of ecological civilization construction work in Guangdong Province. According to the carrying capacity of regional resources and environment, we should incorporate environmental damage, ecological benefits and other indicators into the comprehensive evaluation system of development, and build a green ecological urban agglomeration in the Pearl River Delta. In this paper, through the construction of development intensity and bearing capacity index system, nine cities in the Pearl River Delta were selected as the research object, and the coupling coordination model was used to quantify the level of sustainable development, and the role of each subsystem was revealed through driving force analysis. The results show that: (1) The contrast of regional development intensity is obvious, and the characteristics of metropolitan area are becoming increasingly prominent. Among them, Shenzhen has the strongest degree of development and Zhaoqing was the weakest; (2) According to the driving factors, the carrying capacity of resources and environment in the region can be divided into natural pulled type and economic pulled type. The comprehensive carrying capacity can be consolidated through natural advantages and socio-economic input, respectively; (3) More than half of the urban eco- economic systems in the region are on the verge of being out of tune. Driven by economic factors, Guangzhou and Shenzhen are relatively more coordinated; (4) We should cope with three coordinated development states in the region, and formulate ecological restoration plans for local cities. [ABSTRACT FROM AUTHOR]

Taking urban agglomeration as the main object to optimize the spatial layout of urbanization is an important part of constructing the national land spatial planning system, and the essence of spatial optimization is to promote the coordinated development of large, medium and small cities within the urban agglomeration. Based on the measurement of urbanization coordination level of 26 cities in the Yangtze River Delta Urban Agglomeration from 2001 to 2016, this paper analyses and identifies the urban coordination relationship by using the methods of social network and multi- dimensional- scaling, and explores its internal evolution mechanism. The results show that: (1) With the improvement of the urbanization coordination level of the cities in the Yangtze River Delta Urban Agglomeration, the internal space of the urban agglomeration is obviously changed. The high coordination cities gradually show a Zshaped distribution with Shanghai as the core, and the low coordination cities were stably distributed in the expanded area of the urban agglomeration. (2) According to the correlation strength of the coordination level of the Yangtze River Delta Urban Agglomeration, the cohesive subgroups were divided. The values of weighted average centrality and the contact density of the cohesive subgroups of the urbanization coordination relationship increased, and the polarization effect of Shanghai was more obvious. (3) The coordination structure of the urban agglomeration was identified from two dimensions of space and time. The Yangtze River Delta Urban Agglomeration has transformed from the "circle layer" structure centered on the provincial capital cities under the influence of spatial distance into the structure of "coreperiphery" under the influence of temporal distance. (4) The evolution of spatial structure of the urban agglomeration was influenced by the change of coordination level of population, land and economy urbanization. Compared with population and economy urbanization, land urbanization has a significant role in promoting the level of urban coordination. The optimizing policies of the Yangtze River Delta Urban Agglomeration were proposed from the perspective of coordination after analyses of its spatial structure. This is conducive to the realization of the integration of urban agglomeration and the efficient use of space resources under the conditions of China's existing resource and environmental carrying capacity. [ABSTRACT FROM AUTHOR]

The lightweight block ciphers could be widely used in various applications, such as smart cities, internet of things and cloud computation and so on, in order to protect data and information secure. Midori was a lightweight block cipher proposed in ASIACRYPT 2015. Its block size had two scenarios, i. e, 64 bit and 128 bit, denoted by Midori 64 and Midori 128 respectively. Up to now, there were no results about meet-in-the-middle attacks on Midori 128. This paper developed a meet-inthe-middle attack on 10-round Midori 128 for the first time. Specifically, studying the basic construction and key schedule of Midori 128, this paper constructed a 7-round distinguisher on Midori 128 by using the differential enumeration and key-dependent sieve techniques. Through appending one round at its top and two rounds at its bottom, this paper mounted a meet-in-themiddle attack on 10-round Midori 128. In the attack, time-memory tradeoff technique and some weak subkeys were considered so as to reduce the time complexity of online phase. Finally, the data, time and memory complexities of our attack are 2125 chosen plaintexts, 2126. 510-round encryptions and 2105128-bit blocks, respectively. [ABSTRACT FROM AUTHOR]

Cities continue to serve as shining beacons of hope and opportunity, and people in every corner of the world flock to them to experience a higher standard of living, start families, and found businesses, in a migration trend known as urbanization. This trend has made of cities intellectual hubs and cultural and financial centers. But cities also have congestion, pollution, and public safety issues. Continued globalization and urbanization have tested the limits of the city’s health, power, safety, and transport infrastructures. With globalization came rapid change in technology, trade liberalization, and in the relationship between production, sales, and consumption. Cities must become smarter to be able to compete globally. Building smart cities with local characteristics is an important factor in cities’ ability to secure a place in the competition of globalization. [ABSTRACT FROM AUTHOR]

Based on a comprehensive survey on smart city definitions across the world and a series of public consultations, we first provide a definition of “Smart Macao.” Then we address the basic principles, development goals and strategies, and the main themes of Smart Macao. Next, we identify the potential bottlenecks in developing Smart Macao by inspecting Macao’s current situation. Finally, we argue that the building of Smart Macao must follow the laws of urban development, gather the insights of the public, grasp the opportunity of Greater Bay Area construction, and provide opportunities for young talents. [ABSTRACT FROM AUTHOR]

In recent years, leading cities around the world have been striving to develop smart cities. Each city sets its goals and measures on smart city development having regard to its own circumstances, background and priorities. Hong Kong has been maintaining its leading position globally in terms of economic performance and digital competitiveness. With the staunch national support for I&T development, its fast-growing start-up ecosystem and fervid I&T atmosphere gradually created, Hong Kong is well-positioned to pursue smart city development. The Government published the “Smart City Blueprint for Hong Kong” in December 2017. The development plans cover six major areas with more than 70 initiatives so as to drive the smart city development in Hong Kong. [ABSTRACT FROM AUTHOR]