查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - A new study on Machine Learning is now available. According to news reporting from Fairbanks, Alaska, by NewsRx journa lists, research stated, “We introduce a new framework called Machine Learning (M L) based Auroral Ionospheric electrodynamics Model (ML-AIM). ML-solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kund uri et al. (2020, ), the FAC-derived auroral conductance model of Robinson et al . (2020, ), and the solar irradiance conductance model of Moen and Brekke (1993, ). The ML-inputs are 60-min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. ”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - New research on Artificial Intelligenc e is the subject of a report. Study 1 investigates the effect of immersive AI (vs traditional hospitality) on custo mers’ behavioral intentions and the need for differentiation using virtual-assis ted reality.” Financial support for this research came from Fundacao para a Ciencia e a Tecnol ogia (FCT).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Research findings on Machine Learning are discussed in a new report. According to news reporting from Graz, Austria, b y NewsRx journalists, research stated, “Mesh degeneration is a bottleneck for fl uid-structure interaction (FSI) simulations and for shapeoptimization via the me thod of mappings. In both cases, an appropriate mesh motion techniqueis required .” The news correspondents obtained a quote from the research from Karl-Franzens-Un iversity, “The choice is typically based on heuristics, e.g., the solution opera tors of partialdifferential equations (PDE), such as the Laplace or biharmonic e quation. Especially the latter,which shows good numerical performance for large displacements, is expensive. Moreover,from a continuous perspective, choosing th e mesh motion technique is to a certain extentarbitrary and has no influence on the physically relevant quantities. Therefore, we considerapproaches inspired by machine learning. We present a hybrid PDE-NN approach, where theneural network (NN) serves as parameterization of a coefficient in a second order nonlinearPDE. We ensure existence of solutions for the nonlinear PDE by the choice of the neu ralnetwork architecture. Moreover, we present an approach where a neural network corrects theharmonic extension such that the boundary displacement is not chang ed. In order to avoidtechnical difficulties in coupling finite element and machi ne learning software, we work witha splitting of the monolithic FSI system into three smaller subsystems. This allows to solve themesh motion equation in a sepa rate step. We assess the quality of the learned mesh motiontechnique by applying it to a FSI benchmark problem.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - New study results on artificial intell igence have been published. According to news reporting from Islamabad, Pakistan , by NewsRx journalists, research stated, “Electrical load forecasting remains a n ongoing challenge due to various factors, such as temperature and weather, whi ch change day by day. In this age of Big Data, efficient handling of data and ob taining valuable information from raw data is crucial.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Investigators publish new report on . According to news originating from the University of Malaya by NewsRx correspond ents, research stated, “As climate change increases the risk of extreme rainfall events, concerns over flood management have also increased.” Our news correspondents obtained a quote from the research from University of Ma laya: “To recover quickly from flood damage and prevent further consequential da mage, flood waste prediction is of utmost importance. Therefore, developing a ra pid and accurate prediction of flood waste generation is important in order to r educe disaster. Several approaches of flood waste classification have been propo sed by various researchers, however only a few focus on prediction of flood wast e. In this study, a Long Short-Term Memory (LSTM) and Support Vector Machine (SV M) approach is adapted to address these challenges. Two different raw datasets w ere obtained from the ‘Advancing Sustainable Materials Management: Facts and Fig ures 2015’ source. The datasets were for 9 years (1960, 1970, 1980, 1990, 2000, 2005, 2010, 2014, 2015), and are labelled as the materials generated in the Muni cipal Waste Stream from 1960 to 2015 and the materials Recycled and Composted in Municipal Solid Waste from 1960 to 2015.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - New study results on artificial intell igence have been published. According to news originating from the Universidad T ecnica Estatal de Quevedo by NewsRx correspondents, research stated, “College co ntext and academic performance are important determinants of academic success; u sing students’ prior experience with machine learning techniques to predict acad emic success before the end of the first year reinforces college self-efficacy.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - New research on Robotics - Androids is the subject of a report. According to news reporting originating in Beijing, Pe ople’s Republic of China, by NewsRx journalists, research stated, “Various cogni tive systems have been designed to model the position and stiffness profiles of human behavior and then to drive robots by mimicking the human’s behavior to acc omplish physical humanrobot interaction tasks through a properly designed imped ance controller. However, some studies have shown that variable stiffness parame ters of the impedance controller can cause the violation of the passivity constr aint of the robot states, and make the robot’s stored energy exceed the external energy injected from the human user, thus leading to the unsafe human-robot int eraction.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Data detailed on Robotics have been pr esented. According to news reporting from Changchun, People’s Republic of China, by NewsRx journalists, research stated, “For the application background of phys ical human robot interaction (pHRI), a novel decentralized position/torque contr ol scheme of modular robot manipulators (MRMs) is developed based on the human m otion intention identification in this investigation. Different from traditional control schemes which are oriented to pHRI tasks depending on the biological si gnal or the multisensory, the developed decentralized position/torque control is realized by utilizing only position measurements of each joint module in this p aper.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Investigators publish new report on ro botics. According to news originating from Birmingham, United Kingdom, by NewsRx correspondents, research stated, “This paper showcases the integration of the I nterfacing Toolbox for Robotic Arms (ITRA) with our newly developed hybrid Visua l Servoing (VS) methods to automate the disassembly of electric vehicle batterie s, thereby advancing sustainability and fostering a circular economy.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - A new study on artificial intelligence is now available. According to news reporting originating from the Universiti T enaga Nasional by NewsRx correspondents, research stated, “Land use and land cov er (LULC) analysis is crucial for understanding societal development and assessi ng changes during the Anthropocene era. Conventional LULC mapping faces challeng es in capturing changes under cloud cover and limited ground truth data.”
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