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Surface monitoring of microseismic monitoring events is generally challenging because microseismic data have a low signal-to-noise ratio (SNR). Traditional event-detection methods struggle to detect weak microseismic events. A variance fractal dimension (VFD) method for automatic microseismic event detection via multitrace energy envelope stacking (MTEES) is introduced. In the first stage, we propose a processing microseismic data method based on the MTEES method. It increases the energy of weak microseismic data to avoid missed and false microseismic detection. Furthermore, it can greatly improve computational efficiency to satisfy real-time processing requirements. In the second stage, the VFD algorithm is applied to the data processed in the first stage to improve the feasibility and validity of microseismic event detection. A simulation test with perforation data shows the reliability of the new method in the automatic detection of microseismic events. In addition, we demonstrate that analogous results can be obtained when perforation data are not available by introducing a novel approach based on synthetic correction time. The new approach is particularly useful when perforation data are not recorded, representing a significant advantage over previous approaches. We describe the application of the novel method to a real microseismic data example from monitoring hydraulic fracture treatments in Shanxi Province, China, with and without perforation data. The new method yields improvement in microseismic event detection for microseismic monitoring. Therefore, we find a wide range of applications requiring analysis of microseismic data. [ABSTRACT FROM AUTHOR]

Drivers have always been confronted with real-time parking difficulties when driving on urban roads, especially in crowded downtown or beauty spots. On the other hand, privacy leakage risks on users’ private parking preferences and the sensitive data of parking lots have triggered increasing worries. Some literatures endeavor to improve parking service qualities through multi-consideration parking decision optimization on edge sides or cloud computing based on outsourced data storage. And some other literatures propose a number of privacy-preserving methods, such as cryptography and authentication, but these privacy strategies are at the expense of other qualities of parking services, especially the real-time performance. In this paper, we propose a fuzzy skyline parking recommendation scheme for real-time parking recommendation based on roadside traffic facilities. Linguistic parking information instead of raw parking-related data is used in fuzzy skyline fusion. We evaluated our solution with real-world data sets collected from parking facilities in Wulin downtown, Hangzhou city, China. The evaluation results show that our approaches achieve an average accuracy of parking recommendation over 91%, low communication cost, and quick response time with privacy protection. [ABSTRACT FROM AUTHOR]

Steady-state analysis on production systems, especially serial lines with rigid production mode, have been carried out in a large amount of research literature. With the development of the advanced manufacturing technologies, as well as the national strategies, for example, Made in China 2025, real-time performance evaluation, prediction, production management, and efficient control of systems with flexible production mode are gradually becoming important issues. Under the assumption of assembly systems with small batch-based production tasks, we develop a mathematical model for the real-time performance analysis of such systems with the geometric machine reliability model, which is applicable in many manufacturing environments. The formulas for real-time performance analysis are derived first using the Markovian approach for three-machine assembly systems. Then, based on the idea of decomposition and aggregation, an algorithm with high accuracy and efficiency for system real-time performance approximation is proposed. Finally, the decomposition and aggregation-based real-time analysis approach is extended to the generalized assembly systems. Note to Practitioners—As the concept of manufacturing intelligence being proposed and promoted, system flexibility appears frequently in production in recent years. A flexible production refers to the implementation of small batch-based production with multitype of products on the same production line, by quick setup or machine adjustments. The steady-state analysis method that is traditionally used might be not applicable in this case since most of the production process is in transient state. An approximation-based analytical method, for real-time performance evaluation of assembly systems with small batch-based production tasks and with machines having the geometric reliability model, is proposed. The algorithm developed in this article can be utilized by production managers and engineers, with which the real-time performance of the systems can be predicted with high accuracy. It can also provide assistance for decision-making on activities of production control. [ABSTRACT FROM AUTHOR]

With the rapid growth of China’s high-speed railway mileage, relevant safety technologies of railway operation are very urgent at present. One of the crucial parts is the pantograph–catenary system, which is directly related to the power supply safety of trains in high-speed railways. To ensure the safe operation of the pantograph–catenary system and eliminate the hidden danger during the power supply of trains, from 2011 in China, an automatic detection and monitoring system (called 6C system) of pantograph–catenary in high-speed railways was gradually established to timely discover and report all the potential defects and evaluate the performance of the pantograph–catenary system. The 6C system can measure the dynamic and static geometry parameters of the catenary and detect the defective working states of components and the operation conditions of the pantograph–catenary system. Considering the feedbacks from railway administrations, the 6C system can also realize a fine-grained detection and diagnosis of the pantograph–catenary and significantly improve the detection efficiency. In this article, the whole architecture of the 6C system is presented in detail, including six relatively independent parts for the detection and monitoring of pantograph–catenary systems and a data processing center with a three-level structure. Especially, some critical technologies for automatic detection and monitoring of pantograph–catenary systems are introduced. In the end, some new techniques of detection and monitoring are discussed, and suggestions are made for the future development of detection and monitoring systems of pantograph–catenary in high-speed railways. [ABSTRACT FROM AUTHOR]

Except for its known aspects of positioning, navigation, and timing (PNT), the Global Navigation Satellite System (GNSS) has extended its application to the rainfall forecasting. GNSS-derived zenith total delay (ZTD) or precipitable water vapor (PWV) has been used as a single factor to predict the occurrence of rainfall; however, the rainfall is highly correlated with myriad atmospheric parameters, which cannot be perfectly reflected by a single predictor. In this article, an improved rainfall forecasting model (IRFM) is proposed to forecast the rainfall. The IRFM considers five predictors: monthly PWV value, seasonal PWV/ZTD variations, and their first derivatives: it can forecast rainfall using a single predicator or an arbitrary combination of those predicators. The merit of IRFM is reducing the false forecasted rainfall (FFR) events and missed detected rainfall (MDR) events as much as possible while guaranteeing the true detected rainfall (TDR) events. An optimized selecting principle of predictors’ threshold has been determined using the percentile method. The test experiment has been performed using five GNSS stations derived from continuously operating reference system (CORS) network of Zhejiang province, China. The analysis reveals that the IRFM considering five predictors provides a better performance than that only using a single predictor or a combination of arbitrary predictors. The statistical result shows the average TDR value of more than 95%, FFR value of less than 30%, and MDR of less than 5%, respectively. Compared to the existing rainfall forecasting methods using ZTD or PWV, the IRFM reduces the FFR and MDR, respectively, with the lowest values, while the TDR value is the highest. [ABSTRACT FROM AUTHOR]

Current Online Video Services (OVSs) usually optimize service strategies based on future video popularity to improve efficiency, making popularity prediction highly important. Existing models generally infer a video’s future views from its early views, and maintain performance by updating themselves with the real target views of past predictions. However, for real-time of OVSs, the revealing of past prediction targets cannot keep up with the new round of prediction, making existing models fail to achieve their promise. Thus, a reliable and timely indication of videos’ future views is critical for popularity prediction in OVSs. Recent studies show that the average watched percentage of a video’s content is correlated with the video’s views in the same period and is predictable through time series models. Inspired by these studies, we propose a model to infer videos’ popularity through prediction of the videos’ average watched percentage. Specially, through large-scale analysis of OVS data, we discover that a video age varying relation exists between the average watched percentage and the future views of videos. We then model the relation between the average watched percentage and the future views of videos through a video age-sensitive function, making the feature’s indication of future views reliable for different aged videos. Meanwhile, by restricting the temporal range of average watched percentage prediction, we are able to promptly update the feature’s prediction model, further stabilizing the performance of popularity prediction. We evaluate the proposed model on a real-world data set of iQIYI, one of the most popular OVS providers in China. The experimental results demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization and industrialization in China, more and more children are studying and living in cities, which presents some safety challenges. To help guardians better monitor their children, the authors present ChildGuard, a child safety system based on mobile devices. ChildGuard provides an in-path safety function that monitors the real-time movement of children walking on the road. It also provides a region safety function that sets designated areas in which children can play. Children can be warned about potential risks, and their guardians can be informed of location or activity abnormities. Experiments show that ChildGuard has higher positioning accuracy and better real-time communication than similar systems. This article is part of a special issue on cybersecurity. [ABSTRACT FROM AUTHOR]

In China, two modular multilevel converter (MMC) projects were recently commissioned, and another two are currently under construction. The real-time hardware-in-the-loop (HIL) test bench played an important role in validating the manufacturer's controllers. The full detail MMC model does not fit with the HIL test bench, which has to solve the circuit containing numerous switches and handles a large amount of inputs and outputs at a small time step for real-time simulation. The main challenge is to find a method to model and simulate the MMC systems with sufficient detail, accuracy, and speed. This paper presents an equivalent circuit method for the HIL test bench. The circuit inside the submodule is represented by mathematical equations, implemented in CPU or a field-programmable gate array, and solved in parallel to achieve real-time performance. This method-based test bench is used in those MMC projects in China and connected to the manufacturer's controllers for HIL tests. The model accuracy and simulation speed achieved by this method met the requirements of the HIL tests. In this paper, various scenarios are tested in an MMC HVDC study system. The results achieved by the proposed method have high agreement with those of a reference model in EMTP-RV. [ABSTRACT FROM PUBLISHER]