Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication

Smart Contract Vulnerability Detection Based on Hybrid Attention Mechanism Model

A smart contract, as an important part of blockchain technology, has attracted considerable interest from both industry and academia. It provides the basis for the realization of a variety of practical blockchain applications and plays a crucial role in the blockchain ecosystem. While it also holds a large number of digital assets, the frequent occurrence of smart contract vulnerabilities have caused huge economic losses and destroyed the blockchain-based credit system. Currently, the security and reliability of smart contracts have become a new focus of research, and there are a number of smart contract vulnerability detection methods, such as traditional detection tools based on static or dynamic analysis. However, most of them often rely on expert rules, and therefore have poor scalability and high false negative and false positive rates. Recent deep learning methods alleviate this issue, but without considering the semantic information and context of source code. To this end, we propose a hybrid attention mechanism (HAM) model to detect security vulnerabilities in smart contracts. We extract code fragments from the source code, which focus on key points of vulnerability. We conduct extensive experiments on two public smart contract datasets (a total of 24,957 contracts). Empirical results show remarkable accuracy improvement over the state-of-the art methods on five kinds of vulnerabilities, where the detection accuracy could achieve 93.36%, 80.85%, 82.56%, 85.62%, and 82.19% for reentrancy, arithmetic vulnerability, unchecked return value, timestamp dependency, and tx.origin, respectively

Location monitoring approach of underground pipelines using time-sequential images

The location monitoring of underground pipelines is of utmost significance as it helps the effective management and maintenance of the pipelines, and facilitates the planning of nearby projects, preventing damage to the pipelines. However, currently there is a serious lack of data on the locations of underground pipelines. This paper proposes an image-based approach for monitoring the locations of underground pipelines by combing deep learning and visual-based reconstruction. The proposed approach can build the monitoring model for underground pipelines and characterize their locations through their centroid curve. Its advantages are: (1) simplicity: it only requires time-sequential images of the inner walls of underground pipelines; (2) clarity: the location model and the location curve of underground pipelines can be provided quickly; (3) robustness: it can cope with some existing problems in underground pipelines, such as light variations and small viewing angles. A lightweight approach for monitoring the locations of underground pipelines is achieved. The proposed approach’s effectiveness has been validated through laboratory simulation experiments, demonstrating accuracy at the millimeter level

Analysis on the evolution trend of water resources and water environment in Xiangjiang River basin

According to the daily flow data collected by three representative hydrological stations in the Xiangjiang River basin which are the Guiyang station in the upstream section, the Hengshan station in the midstream section, and the Xiangtan station in the downstream section, and the water environment data collected from the Hunan Water Resources Bulletin, Mann-Kendal method was used to analyze the changes of the annual average flow of the Xiangjiang River basin in the past 20 years as well as the variation of water environment quality in the whole year, flood season and non-flood season. Based on these analysis, the evolution trend of water resources and water environment in the Xiangjiang River basin is further forecasted. The results show that the annual runoff of the upper reaches of the Xiangjiang River basin tends to be stable, and the runoff of the middle and lower reaches is decreasing. The water quality of the Xiangjiang River basin got deteriorated from 1996 to 2010. A sudden change occurred around 2012, and the water quality of the basin gradually improved

Analysis on the evolution trend of water resources and water environment in Xiangjiang River basin

According to the daily flow data collected by three representative hydrological stations in the Xiangjiang River basin which are the Guiyang station in the upstream section, the Hengshan station in the midstream section, and the Xiangtan station in the downstream section, and the water environment data collected from the Hunan Water Resources Bulletin, Mann-Kendal method was used to analyze the changes of the annual average flow of the Xiangjiang River basin in the past 20 years as well as the variation of water environment quality in the whole year, flood season and non-flood season. Based on these analysis, the evolution trend of water resources and water environment in the Xiangjiang River basin is further forecasted. The results show that the annual runoff of the upper reaches of the Xiangjiang River basin tends to be stable, and the runoff of the middle and lower reaches is decreasing. The water quality of the Xiangjiang River basin got deteriorated from 1996 to 2010. A sudden change occurred around 2012, and the water quality of the basin gradually improved

Lunar rock investigation and tri-aspect characterization of lunar farside regolith by a digital twin

Abstract Yutu-2 rover conducted an exciting expedition on the 41st lunar day to investigate a fin-shaped rock at Longji site (45.44°S, 177.56°E) by extending its locomotion margin on perilous peaks. The varied locomotion encountered, especially multi-form wheel slippage, during the journey to the target rock, established unique conditions for a fin-grained lunar regolith analysis regarding bearing, shear and lateral properties based on terramechanics. Here, we show a tri-aspect characterization of lunar regolith and infer the rock’s origin using a digital twin. We estimate internal friction angle within 21.5°−42.0° and associated cohesion of 520-3154 Pa in the Chang’E-4 operational site. These findings suggest shear characteristics similar to Apollo 12 mission samples but notably higher cohesion compared to regolith investigated on most nearside lunar missions. We estimate external friction angle in lateral properties to be within 8.3°−16.5°, which fills the gaps of the lateral property estimation of the lunar farside regolith and serves as a foundational parameter for subsequent engineering verifications. Our in-situ spectral investigations of the target rock unveil its composition of iron/magnesium-rich low-calcium pyroxene, linking it to the Zhinyu crater (45.34°S, 176.15°E) ejecta. Our results indicate that the combination of in-situ measurements with robotics technology in planetary exploration reveal the possibility of additional source regions contributing to the local materials at the Chang’E-4 site, implying a more complicated geological history in the vicinity

Digital twin enabled risky rock investigation and tri-aspect characterization of lunar farside regolith

Source Data of Fig. 4 (Excel format): Parameters of terrestrial soil samples; Parameters of lunar soil obtained in other lunar exploration missions; Mechanical properties of Apollo samples and simulants; The physical and mechanical parameters of the lunar soil simulant and HIT-LSS2 Source Data of Fig. 5 (Excel format): The 1 and 2 μm band center positions of rocks investigated in the CE-4 mission with pyroxenes measured by Adams (1974) Source Data of Supplementary Fig. 5 (Excel format): Simulation results of the outboard traverse conditioned on φ=25°, Ky=40 mm Source Data of Supplementary Fig. 6 (Excel format): Wheel slip ratios of predicted traverses under different internal friction angles; Wheel side slip angles of the predicted traverse under different lateral shearing deformation modulus Source Data of Supplementary Fig. 9 (Excel format): Spectra data of the six rocks investigated in the CE-4 missio