Autonomous wind turbine inspection using a quadrotor

There has been explosive growth of wind farm installations in recent years due to the fact that wind energy is gaining worldwide popularity. However, the maintenance of these offshore or onshore wind turbines, especially in remote areas, remains a challenging task. In this work, vision-based autonomous wind turbine inspection using a quadrotor is designed based on realistic assumptions. Both simulation and Hardware-In-the-Loop (HIL) testing results have shown the effectiveness of the proposed approach

The Sihailongwan Maar Lake, northeastern China as a candidate Global Boundary Stratotype Section and Point for the Anthropocene Series

Sihailongwan Maar Lake, located in Northeast China, is a candidate Global boundary Stratotype Section and Point (GSSP) for demarcation of the Anthropocene. The lake’s varved sediments are formed by alternating allogenic atmospheric inputs and authigenic lake processes and store a record of environmental and human impacts at a continental-global scale. Varve counting and radiometric dating provided a precise annual-resolution sediment chronology for the site. Time series records of radioactive (239,240Pu, 129I and soot 14C), chemical (spheroidal carbonaceous particles, polycyclic aromatic hydrocarbons, soot, heavy metals, δ13C, etc), physical (magnetic susceptibility and grayscale) and biological (environmental DNA) indicators all show rapid changes in the mid-20th century, coincident with clear lithological changes of the sediments. Statistical analyses of these proxies show a tipping point in 1954 CE. 239,240Pu activities follow a typical unimodal globally-distributed profile, and are proposed as the primary marker for the Anthropocene. A rapid increase in 239,240Pu activities at 88 mm depth in core SHLW21-Fr-13 (1953 CE) is synchronous with rapid changes of other anthropogenic proxies and the Great Acceleration, marking the onset of the Anthropocene. The results indicate that Sihailongwan Maar Lake is an ideal site for the Anthropocene GSSP

Facial kinship verification:a comprehensive review and outlook

Abstract The goal of Facial Kinship Verification (FKV) is to automatically determine whether two individuals have a kin relationship or not from their given facial images or videos. It is an emerging and challenging problem that has attracted increasing attention due to its practical applications. Over the past decade, significant progress has been achieved in this new field. Handcrafted features and deep learning techniques have been widely studied in FKV. The goal of this paper is to conduct a comprehensive review of the problem of FKV. We cover different aspects of the research, including problem definition, challenges, applications, benchmark datasets, a taxonomy of existing methods, and state-of-the-art performance. In retrospect of what has been achieved so far, we identify gaps in current research and discuss potential future research directions