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The Sunway TaihuLight is the first supercomputer built entirely with domestic processors in China. On Sunway Taihulight, the local data memory (LDM) of the slave core is limited, so data transmission with the main memory is frequent during calculation, and the memory access efficiency is low. On the other hand, for many scientific computing programs, how to solve the storage problem of irregular access data is the key to program optimization. Software cache (SWC) is one of the effective means to solve these problems. Based on the characteristics of Sunway TaihuLight structure and irregular access, this paper designs and implements a new software cache structure by using part of the space in LDM to simulate the cache function, which uses new cache address mapping and conflicts solution to solve high data access overhead and storage overhead in a traditional cache. At the same time, the SWC uses the register communication between the slave cores to share on the different slave core LDMs, increasing the capacity of the software cache and improving the hit rate. In addition, we adopt a double buffer strategy to access regular data in batches, which hides the communication overhead between the slave core and the main memory. The test results on the Sunway TaihuLight platform show that the software cache structure in this paper can effectively reduce the program running time, improve the software cache hit rate, and achieve a better optimization effect. [ABSTRACT FROM AUTHOR]

The application of wireless sensor network (WSN) technology promotes the modernization of forestry. WSN application technology in forest areas is an important research topic for the sustainable development of forestry in China and is also a research hotspot for forestry ecological monitoring at present. The application of wireless sensor networks in forest areas, first of all, solves the problem of limited energy supply and low-latency data transmission in the forest environment. Due to the large area of the forest environment and uneven tree density, dynamic changes in forest height, easy to block the signal, and other characteristics, the forest environment is prone to node energy depletion fast, the network life cycle is short, and data transmission delays large dilemma. Second, the application of wireless sensor networks is usually centered on maximum data acquisition, but the contradiction between high data acquisition rate and limited energy supply is inevitable, so it is necessary to construct a maximum data acquisition rate model with limited energy supply as a constraint to guarantee the optimal acquisition conditions for wireless sensor networks. In this paper, from the application of wireless sensor network technology in forest environment, the research on the application of wireless sensor network in forestry is carried out around the analysis of energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision-making fire danger warning process, so as to provide a solution to the overall problem of forest fire warning based on rechargeable wireless sensor network. In this paper, we analyze the dynamic replenishment of energy in rechargeable wireless sensor networks and propose an energy-based transmission control protocol that effectively improves data transmission efficiency. In the rechargeable wireless sensor network, the network E2E (end-to-end) average delay time is calculated based on the number of nodes on the data transmission link. The research idea of this paper starts from the application technology of wireless sensor network in the forest environment, and the design of the energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision fire danger warning process are realized vertically. [ABSTRACT FROM AUTHOR]

The development of big data and wireless communication technology has expanded the channels for Western culture to enter China. Diversified teaching forms make us dizzy, which has a great impact on traditional English teaching. This paper aims to study the dilemma and countermeasures of English teaching reform based on multiculturalism under the background of big data and wireless communication. It analyzes the connotation of multiculturalism, the characteristics of the era of big data, the problems existing in college English teaching, and the necessity of college English teaching reform. On the basis of feasibility, in order to understand the current situation of English teaching in colleges and universities, this paper takes teachers and students of a college in this province as the research object, conducts a questionnaire survey on them, and finds out how to better use the background of big data and wireless communication through data analysis. Combined with the multicultural trend of the times to carry out English teaching, the study concluded that under the current technological background, our English teaching must adhere to the student-centered approach and take the improvement of teachers' quality as an important means. [ABSTRACT FROM AUTHOR]

With the continuous improvement of China's scientific and technological level, the popularity of mobile network technology is becoming more and more widespread. Many big data technologies and wireless sensor technologies have brought new changes to people's lives. At present, the functions of communication technology and network transmission have moved from perfection to new innovation and development. 5G mobile network technology has played an important role in various fields. When China's economy and science and technology develop better and better, people pay more and more attention to children's education. The research on children's education has become a hot topic. From the above background, this paper studies the network transmission function and network transmission path of children's education app in 5G era mobile computing technology. First, starting from the development trend and main functions of 5G, this paper briefly describes the functional requirements of children's education app. The efficient data transmission in the 5G mobile wireless sensor network is applied to children's education app. Starting from the distance of network transmission nodes, the data transmission optimization algorithm is adopted, and the network transmission module is composed of the best transmission path of nodes. Combined with the energy-saving effect of mobile computing technology, the problem of excessive consumption of network transmission resources is optimized. Finally, the data transmission path is studied in the 5G mobile network. The results show that 5G mobile computing technology can optimize the network transmission performance, improve the operation efficiency of the server, and has a good effect in solving the problems of delay and low coverage. In the process of children's education app network transmission under 5G mobile computing technology, it can ensure the user's personal information and improve the security of system feedback. [ABSTRACT FROM AUTHOR]

The intelligent sensing and communication technology in the airports' grid information system provides a multidimensional big data set for analyzing flight delays. These data from air traffic control, weather, and multiple determinants will cause initial flight delays. Due to the influence of adjacent flight time correlation, the initial delay causes the delay of subsequent flights, discovered by mining information sensing data, forming the phenomenon of flight delay diffusion. Different determinants will lead to the delay diffusion form of different regions, and more seriously, it will lead to "disaster area" delay in the whole regional grid information structure. To analyze the spatial impact of each factor on flight delay and explore the regional distribution of delay determinants, this paper combined the spatial regression model and determined the key explanatory variables by statistical and processing of the aviation system data. The case study showed the spatial airport delay characteristics in terms of aircraft movements in China. After processing intelligent sensing and communication data, the results show that there is a spatial effect between airports in terms of delay and determinants. The high-delay clusters of delay constraints principally occurred in the Beijing-Tianjin-Hebe and Yangtze River Delta urban agglomerations. Direct flights, weather, new flight routes, take-off, and landing capacity have a more critical impact on spatial airport delays. The use of Internet of Things technology to perceive, analyze, and integrate multiple information of airport delay and combine spatial analysis models can accurately mine delay characteristics and effectively achieve digital and intelligent flight delay management. [ABSTRACT FROM AUTHOR]

The continuous development of information technology and various electronic devices has accelerated the process of informatization and digitization, enabling the development and application of the emerging technology of wireless communication and the Internet of Things. Since the continuous occurrence of vicious bridge collapse accidents in China in recent years, the problem of bridge inspection has become a hot topic among the people. At the same time, how to apply wireless communication and the Internet of Things technology to bridge inspection systems has also become a new research topic. This article mainly studies the design and analysis of bridge detection systems based on wireless communication and Internet of Things technology. In order to expand the field of bridge detection and standard management and improve the credibility and reliability of safety problem prediction and evaluation, the bridge detection system will integrate IoT sensing, internet, remote communication, digital signal analysis and processing, big data knowledge mining, big data prediction and other technologies, design and analysis of the main structure of roads and bridges, and other multifaceted knowledge fields and build a professional intelligent digital network based on bridge inspection data collection, monitoring, analysis, evaluation, and early warning. From design to use and maintenance of the bridge, a digital neural network spanning time and space throughout the life cycle is constructed to construct a digital brain with bridge sensing points as neurons. This paper uses high-power infrared sensor equipment, satellite positioning systems, sensor equipment, and other technical equipment to achieve the purpose of data communication and exchange and realize intelligent positioning, identification, supervision, tracking, and other functions, making the wireless communication and Internet of Things reliable transmission, comprehensive perception, intelligent processing, and other capabilities very effective in the field of bridge inspection. Through the research and analysis of this article, there are more and more bridge inspection systems developed by the Internet of Things and wireless communication technology in China, and the percentage of related equipment used can reach more than 90%. The functions of the bridge inspection system are becoming more and more complete, and the results of the inspection data are also increasing. [ABSTRACT FROM AUTHOR]

In the field of modern bidding, electronic bidding leads a new trend of development, convenience and efficiency and other significant advantages effectively promote the reform and innovation of China's bidding field. Nowadays, most systems require a strong and trusted third party to guarantee the integrity and security of the system. However, with the development of blockchain technology and the rise of privacy protection, researchers has begun to emphasize the core concept of decentralization. This paper introduces a decentralized electronic bidding system based on blockchain and smart contract. The system uses blockchain to replace the traditional database and uses chaincode to process business logic. In data interaction, encryption techniques such as zero-knowledge proof based on graph isomorphism are used to improve privacy protection, which improves the anonymity of participants, the privacy of data transmission, and the traceability and verifiable of data. Compared with other electronic bidding systems, this system is more secure and efficient, and has the nature of anonymous operation, which fully protects the privacy information in the bidding process. [ABSTRACT FROM AUTHOR]

With the development of wireless mobile communication technology, the demand for wireless communication rate and frequency increases year by year. Existing wireless mobile communication frequency tends to be saturated, which demands for new solutions. Terahertz (THz) communication has great potential for the future mobile communications (Beyond 5G), and is also an important technique for the high data rate transmission in spatial information network. THz communication has great application prospects in military-civilian integration and coordinated development. In China, important breakthroughs have been achieved for the key techniques of THz high data rate communications, which is practically keeping up with the most advanced technological level in the world. Therefore, further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G. This paper analyzes the performance of the MIMO channel in the Terahertz (THz) band and a discrete mathematical method is used to propose a novel channel model. Then, a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver. Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel. [ABSTRACT FROM AUTHOR]

With the increasing trend of economic globalization and the continuous evolution of economic forms, the role of science and technology in promoting the development of human civilization has become more and more obvious. With the improvement of comprehensive national strength, the knowledge economy has brought new opportunities and challenges. With the increasing internationalization of higher education, it has not only driven the economic exchanges between countries but also led to the exchange of educational resources among transnational countries. However, China's international education talent cultivation started late, with poor teaching awareness, imperfect discipline construction, and low quality of international education talents. A series of problems have seriously hindered the establishment of the talent training mechanism. In order to establish a reasonable and perfect talent training mechanism, optimize the international education talent training mechanism, make the international education talent training mechanism keep up with the development trend of science, technology, and education in the contemporary world, promote the internationalization of international education talent training, and strengthen the exchange of educational resources among countries. This paper uses various algorithms of fusion algorithms to accurately calculate the talent data. The algorithm results show that the optimized grouped quadratic combined Kalman filter has a shorter running time than the traditional Kalman filter, which decreased about 20%. The S-LEACH algorithm outperforms the traditional algorithm in the simulation results of the number of surviving nodes, relative energy consumption, and data transmission. In response to the national strategy of rejuvenating the country through science and education, cultivating international talents and building a modern talent training mechanism are particularly important. [ABSTRACT FROM AUTHOR]

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China's maritime communication regulatory departments have issued some corresponding regulatory policies to ensure the sound development of China's maritime communication, but the evaluation of the regulatory performance of these policies has not been taken seriously, and some existing studies still lack a set of performance evaluation models verified by empirical studies. Based on this, this paper first uses principal component analysis method to establish an exploratory model of China's maritime communication regulation performance evaluation based on the maritime communication data of 31 provinces, municipalities and autonomous regions in China. On this basis, it uses BP neural network algorithm to verify the model and finally establishes a model of China's maritime communication regulation performance evaluation, thus providing a useful reference for China's maritime communication regulation. [ABSTRACT FROM AUTHOR]

To provide the generic clock, trigger, and control function and fulfill the data transmission performance requirement in high-energy physics experiments, a microtelecommunications computing architecture fast control board (uFC) was developed based on the advanced mezzanine card specification. Built around the Xilinx Kintex-7 field-programmable gate array (FPGA), the uFC provides users with a platform with a data memory, reference clock, trigger, and SFP+ (small form-factor pluggable) connections that are required in general experiments. In addition, it has access to two on-board FPGA mezzanine card sockets with a large array of configurable input/ouput and high-speed links up to 10 Gb/s. This paper presents test results from the first set of preproduction prototypes and reports on the application in high-energy photon source in China. [ABSTRACT FROM AUTHOR]

Data infrastructure systems such as the National Aeronautics and Space Administration (NASA) Planetary Data System (PDS), European Space Agency (ESA) Planetary Data Archive (PSA)and Japan Aerospace Exploration Agency (JAXA) Data Archive and Transmission System (DARTS) archive large amounts of scientific data obtained through dozens of planetary exploration missions and have made great contributions to studies of lunar and planetary science. Since China started lunar exploration activities in 2007, the Ground Research and Application System (GRAS), one of the five systems developed as part of China's Lunar Exploration Program (CLEP) and the Planetary Exploration of China (PEC), has gradually established China's Lunar and Planetary Data System (CLPDS), which involves the archiving, management and long-term preservation of scientific data from China's lunar and planetary missions; additionally, data are released according to the policies established by the China National Space Administration (CNSA). The scientific data archived by the CLPDS are among the most important achievements of the CLEP and PEC and provide a resource for the international planetary science community. The system plays a key and important role in helping scientists obtain fundamental and original research results, advancing studies of lunar and planetary science in China, and improving China's international influence in the field of lunar and planetary exploration. This paper, starting from CLEP and PEC mission planning, explains the sources, classification, format and content of the lunar and Mars exploration data archived in the CLPDS. Additionally, the system framework and core functions of the system, such as data archiving, management and release, are described. The system can be used by the international planetary science community to comprehensively understand the data obtained in the CLEP and PEC, help scientists easily access and better use the available data resources, and contribute to fundamental studies of international lunar and planetary science. Moreover, since China has not yet systematically introduced the CLPDS, through this article, international data organizations could learn about this advanced system. Therefore, opportunities for international data cooperation can be created, and the data service capability of the CLPDS can be improved, thus promoting global data sharing and application for all humankind. [ABSTRACT FROM AUTHOR]

The advent of the digital era has put forward an urgent demand for the digitization of units of measurement, and the construction of unit ontology is an important method to realize the digitization of units of measurement. However, the existing unit ontology is at the preliminary research stage, especially the bilingual unit of measurement suitable for the construction of Digital China. Based on the Web Ontology Language (OWL), a bilingual unit of measurement ontology, vim, is designed and constructed using the Seven Steps to Ontology Development approach. vim provides a standardized, interoperable, and unified architecture to realize the bilingual digital representation of units in the International Vocabulary of Metrology—Basic and general concepts (VIM) and from the Chinese metrological technical specification JJF 1001-2011 General Terms in Metrology and Their Definitions. The ontology was verified for machine readability, knowledge reasoning capability, and semantic retrieval and applied. The experimental results show that the vim ontology can achieve machine readability with correct syntax, logical consistency, and validity, and can facilitate data communication and sharing. Furthermore, a comparison between vim, OM, and QUDT was conducted. OM and QUDT serve as representative instances in the field of ontology for units. The construction of this ontology lays the foundation for realizing the digitization and standardization of China's unit of measurement, as well as the machine-readability, interoperability, and sharing of domestic and foreign metrology test data and metrology certificates. [ABSTRACT FROM AUTHOR]

This paper presents a single-carrier multiuser receiver in underwater acoustic communications with strong multiple access interference (MAI) combining passive time-reversal (PTR) and direct-adaptation-based turbo equalization. The receiver works in an iterative block by block manner. In the first iteration, when the symbols of all users are detected by successive interference cancellation (SIC) in the block, the channel impulse response (CIR) of each user is then updated by post-SIC signal to achieve more accurate MAI reconstruction and PTR combination for the next block. In the following iterations, the a priori mean of symbol in the current block is available and used to further improve the accuracy of reconstructed MAI and the updated CIR. The proposed receiver is demonstrated using experimental data collected at Songhua Lake, China, in 2019. The results show that single-carrier nine-user communication data with quadrature phase-shift keying can be successfully recovered, with an average data rate of 1.67 kbps for each user. [ABSTRACT FROM AUTHOR]

The displacement of the cross section directly reflects the stress state and stability of the surrounding rock and structure, so the monitoring of it is essential during the construction and operation of the tunnel and underground engineering, particularly under the conditions of earthquake and other geological disasters. This paper introduces a new contact tunnel profile monitoring system (TPMS) in detail that uses a tilt sensor and a displacement sensor as data acquisition devices. According to the relation between the sensing physical quantity and displacement change, the displacement calculation formulas of the tunnel cross section measuring points based on the two-dimensional plane coordinate system were deduced, and in order to eliminate the actual installation and positioning deviation of the monitoring system, the method of obtaining the optimal monitoring plane and converting coordinates of the measuring points was proposed, thus establishing the theoretical basis for the application of the TPMS. With the Beishan exploration tunnel (BET) in China as the test platform, the TPMS was successfully applied for long-term monitoring. The application experience showed that the TPMS can realize continuous monitoring, automatic collection and transmission of the monitoring data, remote access whenever necessary, without affecting the transportation in the tunnel, and high accuracy, which reaches 0.01 mm. This system provides a new simple and effective method with good generality and applicability for the deformation monitoring of the tunnel and underground engineering. [ABSTRACT FROM AUTHOR]

This paper uses both Chinese aggregate and dis-aggregate level data to investigate the transmission mechanisms of spillover effects of US economic policy uncertainty on the Chinese macroeconomy activities. We find that different industries of China respond quite differently by using quasi-exogenous variation across industries. More specifically, increasing uncertainty reduces the Chinese stock market return, especially those industries closely connected to the US investors. FDI in China is positively associated with increased US policy uncertainties, and industries intensively depending on foreign investment would be affected more. Lastly, the export from China to US would decrease, and industries whose exports heavily relying on the US market would drop more in response to increases in the US policy uncertainties. [ABSTRACT FROM AUTHOR]

The GIS-based water quantity and water quality model is widely used to provide decision-making supports for water resource and water quality management. However, the existing integration patterns of GIS and model system mainly depend on data communication between themselves which may lead to low operating efficiency and time-consuming model setup. In this paper, a generalized data structure (dual object structure (DOS)) which can store the data of GIS objects and model objects together is proposed and realized for the first time, avoiding frequent data communication during the period of numerical simulation and result expression, realizing the fusion of GIS objects and model objects at the data structure level, improving the operating efficiency of the system. Finally, the water quantity and water quality modeling software (digital basin simulation system (DBSS)) based on DOS was developed by using C++ language. The software has been applied successfully in large-scale river basins of China, and one of the cases was demonstrated to show the application process and the outstanding results. [ABSTRACT FROM AUTHOR]

The heterogeneous network formed by the deployment and interconnection of various network devices (e.g., sensors) has attracted widespread attention. P M 2.5 forecasting on the entire industrial region throughout mainland China is an important application of heterogeneous networks, which has great significance to factory management and human health travel. In recent times, Large Language Models (LLMs) have exhibited notability in terms of time series prediction. However, existing LLMs tend to forecast nationwide industry P M 2.5 , which encounters two issues. First, most LLM-based models use centralized training, which requires uploading large amounts of data from sensors to a central cloud. This entire transmission process can lead to security risks of data leakage. Second, LLMs fail to extract spatiotemporal correlations in the nationwide sensor network (heterogeneous network). To tackle these issues, we present a novel framework entitled Spatio-Temporal Large Language Model with Edge Computing Servers (STLLM-ECS) to securely predict nationwide industry P M 2.5 in China. In particular, We initially partition the entire sensor network, located in the national industrial region, into several subgraphs. Each subgraph is allocated an edge computing server (ECS) for training and inference, avoiding the security risks caused by data transmission. Additionally, a novel LLM-based approach named Spatio-Temporal Large Language Model (STLLM) is developed to extract spatiotemporal correlations and infer prediction sequences. Experimental results prove the effectiveness of our proposed model. [ABSTRACT FROM AUTHOR]

The goal of deepening institutional reforms was to bring transparency and accountability, address corruption, and establish a clean government (CG) in China. The first step toward this transparency is considered to be the free development and transmission of Open Data (OD). In this regard, China has set up open data centers in provincial governments. Considering that OD can have an impact on CG and bring new ideas for CG construction, ODs of 31 provincial governments have been analyzed through fsQCA3.0 to test these assumptions. To see how much it can contribute to the development of the Technology Organization Environment Framework (TOE). To this end, between 2019 and 2021, 31 provincial government data have been clustered into low, medium, and high corruption case enrollment areas to determine the impact of OD. The study mentioned that improvements in ODs in 31 provinces could strengthen cooperation with the disciplinary inspection department in the fight against corruption. The study, on the other hand, made two assumptions that environmental barriers and internal pressures could affect data’s reliability. [ABSTRACT FROM AUTHOR]

Dynamic behaviour and its evolution are concerns for those operating high-speed trains. In this paper, a cloud server is applied to establish a connection between the vehicle-mounted equipment and users to decrease the influence of network instability. To ensure the accuracy and consistency of data transmission, MQTT (Message Queue Telemetry Transport) protocol is used to transfer data measured from the vehicle. The paper discovers the vibration transfer characteristic and the evolution of the dynamic behaviour of several types of high-speed trains, along with wheel wear under several operation conditions, over time. The turbulence caused by high-order wheel polygonalization formed during long-term service, which cannot be weakened by the suspended system sufficiently, is harmful to the ride quality of high-speed trains. The results confirm the operational reliability of the high-speed trains in China and provide useful references for the optimisation and maintenance of high-speed trains. [ABSTRACT FROM AUTHOR]

Aiming at saving energy and maximizing the network life cycle, the multi-node cooperative image acquisition and compression technology in Wireless Multimedia Sensor Networks (WMSNs) is studied deeply. The Minimum Energy Image Collection (MEIC) problem for multiple target domains in a certain period of time in the monitoring area is proposed, the integer linear programming for Minimum Energy Image Collection (MEIC) problem is described and proved to be NP complete; then combined with the features of image acquisition of camera node, the Local Camera Coordinative Energy-saving Strategy (LCCES) is proposed, and the performance of the Local Camera Coordinative Energy-saving Strategy (LCCES) is evaluated through a lot of simulation experiments; finally, the LBT-based Multi-node Cooperative Image Compression Scheme (LBT-MCIC) is proposed. The results show that this strategy can effectively reduce the number of active camera nodes in the process of image acquisition, thus reducing the energy consumption of image acquisition. At the same time, it also plays a role in balancing the energy consumption of camera nodes in the network, effectively solves the problem of high cost of common nodes in the image transmission scheme of two-hop cluster structure and has the characteristics of low computational complexity and high quality of reconstructed image. [ABSTRACT FROM AUTHOR]

Smartphone location data provide the most direct field disaster distribution data with low cost and high coverage. The large-scale continuous sampling of mobile device location data provides a new way to estimate the distribution of disasters with high temporal–spatial resolution. On September 5, 2022, a magnitude 6.8 earthquake struck Luding County, Sichuan Province, China. We quantitatively analyzed the Ms 6.8 earthquake from both temporal and geographic dimensions by combining 1,806,100 smartphone location records and 4,856 spatial grid locations collected through communication big data with the smartphone data under 24-hour continuous positioning. In this study, the deviation of multidimensional mobile terminal location data is estimated, and a methodology to estimate the distribution of out-of-service communication base stations in the disaster area by excluding micro error data users is explored. Finally, the mathematical relationship between the seismic intensity and the corresponding out-of-service rate of communication base stations is established, which provides a new technical concept and means for the rapid assessment of post-earthquake disaster distribution. [ABSTRACT FROM AUTHOR]

Li, D. and Zhang, Y., 2019. Maritime communication regulation: A model for evaluating the performance. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 997–1001. Coconut Creek (Florida), ISSN 0749-0208. China's maritime communication regulatory departments have issued some corresponding regulatory policies to ensure the sound development of China's maritime communication, but the evaluation of the regulatory performance of these policies has not been taken seriously, and some existing studies still lack a set of performance evaluation models verified by empirical studies. Based on this, this paper first uses principal component analysis method to establish an exploratory model of China's maritime communication regulation performance evaluation based on the maritime communication data of 31 provinces, municipalities and autonomous regions in China. On this basis, it uses BP neural network algorithm to verify the model and finally establishes a model of China's maritime communication regulation performance evaluation, thus providing a useful reference for China's maritime communication regulation. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to compare and evaluate the personal cloud storage products (PCSPs) in China and find the gap among them for promoting their service level. There are five representative products including Baidu cloud, Tencent cloud, Qihoo 360-cloud, Kingsoft cloud and Huawei DBank.Design/methodology/approach This study, first, extracts corresponding indicators based on the extant literature to evaluate PCSPs, and then collects the data about each index by investigation and the performance test, finally proposes a model to rank PCSPs, which applies analytic hierarchy process (AHP) to determine the indexed weights and the technique for order preference by similarity to ideal solution-grey relational analysis calculate evaluation score of each PCSP.Findings Among them, Qihoo 360-cloud gets the highest evaluation score contributed by large space, file editing and fast transmission speed. The rest are Kingsoft cloud, Baidu cloud, Huawei DBank and Tencent cloud in order. These storage products are all want of the addition or improvement of the online editing service similar as Google Docs.Research limitations/implications AHP method is subjective, some of the data is incomplete, and some accidental error and systematic error exist in the actual testing process.Practical implications The findings can assist users in selecting more suitable products and offer cloud storage providers (CSPs) a general direction of improving their product performance.Social implications Contributing to improve the overall level of the cloud storage services in China.Originality/value The study perfects the evaluation index system of the PCSP and fills the research gap in studying PCSPs in China, and expands the application field of the multiple criteria decision-making problems. This evaluation process and results have implied that CSPs in China should provide good services of large capacity, cooperation and security with the good internet environment of economical, high and stable speed by institutions and internet access providers. [ABSTRACT FROM AUTHOR]

The relative change of in-situ stress is an inevitable outcome of differential movement among the crust plates. Conversely, changes of in-situ stress can also lead to deformation and instability of crustal rock mass, trigger activity of faults, and induce earthquakes. Hence, monitoring real-time change of in-situ stress is of great significance. Piezomagnetic in-situ stress monitoring has good and longtime applications in large engineering constructions and geoscience study fields in China. In this paper, the new piezomagnetic in-situ stress monitoring system is introduced and it not only has overall improvements in measuring cell's structure and property, stressing and orienting way, but also enhances integration and intelligence of control and data transmission system, in general, which greatly promotes installing efficiency of measuring probe and quality of monitoring data. This paper also discusses the responses of new piezomagnetic system in large earthquake events of in-situ stress monitoring station at Qiaoqi of Baoxing and Wenxian of Gansu. The monitoring data reflect adjustments and changes of tectonic stress field at the southwestern segment of and the northern area near the Longmenshan fault zone, which shows that the new system has a good performance and application prospect in the geoscience field. Data of the Qiaoqi stress-monitoring station manifest that the Lushan Earthquake did not release stress of the southwestern segment of the Longmenshan fault zone adequately and there still probably exists seismic risk in this region in the future. Combined with absolute in-situ stress measurement, carrying out long-term in-situ stress monitoring in typical tectonic position of important regions is of great importance for researchers to assess and study regional crust stability. [ABSTRACT FROM AUTHOR]

Satellite establishes a satellite ground station to satellite link with a ground station to complete data transmission. However, in China, satellite ground stations only exist within the country. With the rapid increase in the number of satellites, effectively dispatching satellite communications and maximizing the performance of ground stations are necessary. We propose a heuristic adaptive large neighborhood search algorithm (H-ALNS) to solve the satellite data transmission scheduling (SDTS) problem. The algorithm includes two heuristic rules for generating the initial scheme and the conflict reduction process after updating the neighborhood. A heuristic task assignment method is used to select the execution time window and position for the task sequence. The adaptive operator is used to update the delete operator and insert operator weights into the H-ALNS. The quality of the generated planning scheme improved through continuous neighborhood destruction and repair. Through experimental analysis, the algorithm we propose is feasible for solving SDTS problems and surpasses the planning results acquired using other comparison algorithms. The H-ALNS has good prospects for practical engineering applications. [ABSTRACT FROM AUTHOR]

With the rapid development of rail transit in China, the TCN-based train network can no longer meet the needs of train data transmission services. The TCSN emerges as the times require. This paper studied a train service communication network based on the integrated service model for the train data transmission business, and established the traffic flow model for the four trains. It analyzed the weighted fairness queue scheduling ( WFQ) algorithm for network grouping and designed service classification and bandwidth allocation based on WFQ scheduling ( SCBAWFQ ) algorithm. And it used simulation software to simulate and analyze the time delays of constant data stream and burst data stream under WFQ and SCBAWFQ respectively. The simulation results prove that the improved algorithm can reduce the latency of real-time service stream. It has a good effect, so that the SCBAWFQ algorithm realizes the need to maintain both the fairness of the WFQ algorithm and the quality of service for real-time services [ABSTRACT FROM AUTHOR]

Color is one of the three major elements of print advertising, and different color combinations can trigger different emotional experiences of human beings. At present, the application of color in advertising in China is relatively mature, but it is limited to the traditional application method and has not been combined with big data technology. From the perspective of business needs, this research analyzes the process of visual creativity from the perspective of business value-added, and analyzes the role of big data in it. Then it introduces the semantics of common colors and how to incorporate color semantics into advertising design. And a sequence mining-based advertising click-through rate prediction model is proposed. The Criteo dataset is used as the training set. The AUC value of the model is 0.702 and the loss value is 0.415. Compared with other models, AUC values increased by 10.16%, 4.70%, 2.69% and 2.30%, respectively. Losses decreased by 10.17%, 9.19%, 6.11% and 7.57%, respectively. Finally, the online shopping data of 20 consumers was used as the test set to predict their color preferences, and the prediction accuracy was about 70%. Among them, the prediction accuracy of the group with stable shopping habits was 72.76%, and that of the group who liked to try new things was 70.60%, both meeting the expectation. Through experiments, it is concluded that the model has good performance and stability, and can more accurately judge consumers' consumption preferences. [ABSTRACT FROM AUTHOR]

This article aims to summarize the development and challenges of real-world data (RWD) and real-world evidence (RWE) in China and introduce a unique opportunity for medical devices to gain accelerated regulatory approval in China by utilizing RWE generated in a free trade pilot zone "Boao Lecheng" in Hainan Province. In 2020, the National Medical Products Administration (NMPA) issued a draft guideline on the "Use of real-world data to support clinical evaluation for medical devices", suggesting that RWE derived from RWD could support clinical evaluation throughout the life cycle of a medical device. Meanwhile, the Chinese government has allowed qualified RWD collected in Boao Lecheng to support registration application of innovative medical devices and drugs in China. These medical devices and drugs should have been approved abroad, but not in China yet, and met urgent and unmet medical needs in China. The article also presents the successful story of an innovative Glaucoma drainage tube as the first medical device approved in China using RWE generated in Boao Lecheng in 2020. Although we are witnessing an increased interest in RWE, a few challenges remain, e.g., limited data accessibility and data sharing, concerns on data quality, etc. Collaborations among relevant stakeholders in the RWE research are vital to address the challenges. [ABSTRACT FROM AUTHOR]

Simple Summary: Since PCV2 is currently the primary viral agent in intensive pigs, the cost of immune suppression and preventative measures has resulted in severe economic losses. It has been claimed that PCVs infect wild pigs in a number of nations, including South Korea, Germany, and Italy. Jiangxi province in China is a heavily populated area with an extremely intensive pig production industry, but data on the transmission of PCVs in wild boar are poor. In order to ascertain the incidence of PCV1/2/3 and the genetic characteristics of PCV2 circulating in wild boar in Jiangxi province, an epidemiological investigation was conducted. We discovered a medium prevalence of PCVs, notably PCV2, which indicated that wild boar in Jiangxi province were exposed to PCVs. Our findings highlight the need for the pig sector to actively prevent the contact between livestock and wild boar, which have a high risk of PCVs infection. A number of disorders that harm pig production are linked to porcine circoviruses, including PCV2. PCV2 infection is a substantial contributor to porcine-circovirus-associated illnesses (PCAS) and the post-weaning multi-systemic wasting syndrome (PMWS), which have a significant negative economic impact on pig production. Additionally, PCV infection has been labeled as a global concern to cattle and wildlife. This study's objectives were to examine the prevalence of PCV1/2/3 in Jiangxi Province, China, and to clarify the epidemiological significance of wild boar in PCV epidemiology. The 2020 hunting seasons resulted in the collection of 138 wild boar samples for PCV1/2/3 detection, which was followed by the genetic clarification of PCV2 strains. According to our data, 21.7% (30/138) of the population had PCV1 positivity, 22.5% (31/138) had PCV2 positivity, and 5.8% (8/138) had PCV3 positivity. Additionally, 10 out of 138 wild boar samples had PCV1 and PCV2 co-infections, while 5 out of 138 wild boar samples had PCV2 and PC3 co-infections. Nineteen full-length PCV2 genomes measuring 1767 nt were recovered from various animal tissues using conventional PCR. Eighteen out of nineteen PCV2 strains were identified as PCV2b by phylogenetic tree analysis, which was completed by the reference strain HLJ2015 obtained from domestic pigs in 2015. Additionally, one genotype of PCV2d JX11-2020 (MW889021) shared a sub-branch with the referenced strain TJ (AY181946), which was isolated in domestic pigs in 2002. This finding raises the possibility that domestic pigs could contract PCV2 strains from wild boar, posing a serious threat to the Jiangxi province of China's pig production industry. [ABSTRACT FROM AUTHOR]

With the rapid development of communication technology and automation technology, sensors are becoming more and more intelligent. This study proposes an environmental accounting system model based on artificial intelligence blockchain and embedded sensors. A high-precision sensor system based on embedded technology is first built, which not only avoids the shortcomings of analog data transmission, but also has high performance and price advantages. At the same time, it can be easily combined into a simple sensor network, and array measurement can be realized through the development of blockchain technology. However, the current blockchain system has the disadvantage of storage limitation. The problem is particularly serious when a large amount of data needs to be stored in the blockchain, especially when the blockchain is combined with big data. As a comprehensive field of accounting, ecology, and environmental science, environmental accounting has made great contributions to sustainable development in the field of accounting. The theoretical research in the field of environmental accounting in China started late, and a unified environmental accounting system has not actually been established. Under the conditions of immature theoretical and policy basis, companies have almost no actual surveys on environmental accounting. The characteristics of blockchain technology, such as decentralization, transparency, and changes in information unavailability, can fully solve the problem that the current accounting information system cannot consolidate transaction information and the accounting process. The reliability assurance mechanism of the accounting information system based on blockchain technology can greatly ensure the reliability of the accounting information system, effectively suppress accounting fraud, and improve the transparency of information. [ABSTRACT FROM AUTHOR]

Urban economic development is not linear, but it always exhibits certain volatility. If the economic fluctuation exceeds a certain range, it may damage the urban economic development. In order to solve the economic damage caused by the excessive fluctuation of the urban economy in the development process, this article is based on the current situation of China's macroeconomic monitoring and early warning and data warehouse-related technologies, analyzed, explained the role of IoT sensors in the macroeconomic early warning system, reviewed the development process of economic monitoring and early warning, sorted out and compared several common economic monitoring methods, and proposed the application of IoT sensors to urban economic monitoring, the idea of early warning, and the construction of an urban economic data monitoring and early warning model. The urban economic data monitoring and early warning model is based on IoT sensors and has carried out research on data transmission, monitoring, forecasting, processing and display. After simulating the model, the results of the simulation experiment show that the accuracy rate of the economic volatility prediction of the model reaches 80%, which has certain practical value. [ABSTRACT FROM AUTHOR]

In recent years, the coal industry has been expanding the scale and output of coal mining in China, yet the safety in production is faced with great challenge. Communication system in coal mines plays a significant role in production safety, and wireless narrowband data communication network technology is a new-type advantageous measure to construct wireless network security monitoring system for coal mining. Here, a coal mine monitoring signal transmission method based on bus technology and wireless data transmission technology suitable for coal mines is proposed. The corresponding monitoring system is designed, and the system is able to collect the gas concentration and mechanical operation status of the mines. Wireless sensor network nodes are used for the RF communication module. The communication performance of this system in coal and rock medium and the roadway along the goaf is simulated, and the quantitative relationship between the attenuation coefficient of different communication frequencies and the effective communication distance is obtained. Hence, the results show that the protocol has good performance in terms of route establishment, maintenance, and data transmission hop count for the positioning of coal mine employees. [ABSTRACT FROM AUTHOR]

The application of fabricated segmental lining in deeply buried inclined shafts in complex strata has been significantly increased in recent years. However, the structural safety of the fabricated lining is vulnerable to high ground stress and high water pressure, as well as the vibration of mechanical equipment and ground disturbance caused by coal mining. Thus, applying an automatic load-monitoring system to the inclined shaft in coal mines has great engineering importance in evaluating structural safety. In this study, an automatic monitoring and data transmission system for the inclined shaft was developed. In addition, by considering the non-linear characteristics of segment joints and different working states of concrete segments, a more functional assessment method was proposed based on the limit state assessment theory. According to the in situ monitoring project in the number 2 inclined shaft of Bulianta coal mine in China, the calculated internal forces are in good agreement with the monitored data, and the proposed assessment method shows reliable results during the operation period. [ABSTRACT FROM AUTHOR]

It is essential to provide disaster relief assistance after coal mine explosions. Often, it is life‐threatening for rescuers to enter an accident scene blindly; therefore, a coal mine rescue robot (CMRR) has been developed. However, the application of the CMRR has not proven satisfactory after decades of development. To solve this problem, we summarize the reasons for this disappointing state and address the technical challenges of the CMRR. Based on these reasons and the associated technical challenges, two generations of tracked robots have been developed. The China University of Mining Technology‐V (CUMT‐V) (A) robot was first developed and its walking system, body support system, communication system, environmental awareness system, and control system are described in detail. A performance test was performed on the CUMT‐V (A) robot and some problems were encountered. To address these problems, we designed the CUMT‐V (B) robot. The field test was conducted in Shanxi province, China, in August 2016. The application results show that the robot has good adaptability to complex terrain and high reliability in terms of environmental awareness and data transmission. In conclusion, the robot is nearing practical applications. [ABSTRACT FROM AUTHOR]

Global spread of Zika virus in 2015 and 2016 highlighted the importance of surveillance to rapidly detect, report, and respond to emerging infections. We describe the lessons learned from the development and deployment of a web-based surveillance reporting system for Zika virus and other acute febrile illnesses (AFI) in Guangdong and Yunnan provinces, China. In less than 2 months, we customized the China Epidemiologic Dynamic Data Collection (EDDC) platform to collect, manage, and visualize data in close to real time. According to provincial and sentinel hospital staff requirements, the customized platform provided specific user authorization management, online/offline data collection, data quality control, and secure data transmission and protection and visualization tools. AFI case data and laboratory test results were entered through a web-based interface by hospital and provincial-level staff and saved on a China CDC server in Beijing. The dashboard visualized aggregate data by hospital, age, onset date, and laboratory test results. From June 2017 to December 2018, data from 768 patients with AFI were entered into the web-based surveillance system and visualized by hospital and provincial-level decision makers. Input from provincial and hospital staff was essential for developing the AFI case-reporting and feedback tools appropriate for specific settings and decision-making requirements. Web-based systems (eg, EDDC, data collection, and visualization tools that can be easily adapted to meet local surveillance needs) can help shorten time for system deployment, thereby strengthening global health security to rapidly detect and respond to emerging infections and outbreaks. [ABSTRACT FROM AUTHOR]

The application of wireless sensor network can achieve real-time monitoring of the underwater environment. Nodes must be effectively deployed in the targeted monitoring area to gain full coverage of the resources in a monitored area of water. However, the variability of flowing water is likely to cause a delay in the transmission of the resource data. Node mobility also requires the use of a more advanced algorithm in the coverage control method of the WSN. What type of methods or measures should be used to deploy mobile sensor nodes to effectively meet the requirement of water resource monitoring tasks and realize the full coverage of water resources, thereby improving the monitoring quality? Moreover, how can the coverage capacity of mobile sensor nodes be improved in water resource monitoring? These are pressing research issues to resolve. This study proposes the deployment of an algorithm for an improved sensor network k-coverage based on probabilistic sensing; maximum weight matching is introduced to realize a centralized allocation strategy, which can effectively reduce the energy consumed in node allocation. The coverage results obtained in a simulation were higher than those of the event probability and the energy-efficient coverage algorithms. The energy consumed during sensor node movement was lower than that with the latter two approaches, indicating that the network node coverage algorithm based on probabilistic sensing that is proposed in this study can effectively meet the requirements for the application of WSNs in water resource monitoring. [ABSTRACT FROM AUTHOR]

There are mainly two types of data modulation methods used for enhanced LOng-RAnge Navigation (eLORAN) systems: pulse position modulation (PPM) and supernumerary interpulse modulation (SIM). The typical application for PPM is tri-state PPM (3S-PPM), also known as Eurofix. The typical application for SIM is ninth pulse modulation. Both of these methods are phase modulation methods. Phase modulation coding, a very mature technology, is used at present. To achieve a better demodulation success rate of eLORAN digital modulation signals at longer distances, a method of using the transmitting station duplex mode to transmit a digital modulation pulse group after LORAN-C transmitting a pulse group is proposed to realize modulation pulse on–off modulation. In this method, a broadcasting experiment was performed on the BPL (The call sign of eLORAN time service system in China) broadcaster station. After monitoring, a good receiving demodulation effect was initially obtained. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government. Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic's epicenter. Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China. Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports. Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases. Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang. Our 10-day forecasts across the three models predict an additional 65–81 cases (upper bounds: 169–507) in Guangdong and an additional 44–354 (upper bounds: 141–875) cases in Zhejiang by February 23, 2020. In the best-case scenario, current data suggest that transmission in both provinces is slowing down. [ABSTRACT FROM AUTHOR]