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 Artificial Intelligence. According to news reporting from Kafr El-Shaikh, Egypt, by NewsRx journalists, research stated, “Recently, Digital Twin (DT) has a growth revolution by increasing Artificial Intelligence (AI) techniques and relative technologies as the Internet of Things (IoT). They may be considered as the panacea for DT technology for various applications in the real world such as manufacturing, healthcare, and smart cities.” The news correspondents obtained a quote from the research from the Higher Institute of Engineering & Technology, “The integration of DT and AI is a new avenue for open research in the upcoming days. However, for exploring the issues of developing Digital Twins, there are interesting in identifying challenges with standardization ensures future developments in this innovative theme. This paper first presents the Digital Twins concept, challenges, and applications. Afterward, it discusses the incorporation of AI and DT for developing various IoT-based applications with exploring the challenges and opportunities in this innovative arena. Then, developing tools are presented for exploring the digital twins’ system implementation. Further, a review of recent DT-based AI approaches is presented.” According to the news reporters, the research concluded: “Finally, a discussion of open research direc- tions in this innovative theme is presented.” This research has been peer-reviewed.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting from Shenzhen, People’s Republic of China, by NewsRx journalists, research stated, “Laser powder bed fusion (LPBF) has proven to be an effective tool in fabricating heat transfer devices with improved efficiency. However, the accurate prediction of convective heat transfer in LPBF-fabricated fluid channels remains a challenge.” Funders for this research include Shenzhen Science & Technology Project, NTUT-SZU Joint Research Program. The news correspondents obtained a quote from the research from Shenzhen University, “The classical Gnielinski model is regarded as the most accurate correlation for predicting forced convective heat transfer in traditional pipes. However, whether it is applicable to LPBFfabricated pipes is yet to be determined. To address this challenge, in this study, pipe samples with diameters of 3 mm, 4 mm, and 5 mm were designed and fabricated using LPBF along the building angles of 0 degrees, 45 degrees, and 90 degrees. The pressure loss and heat transfer characteristics of these samples were experimentally measured. Results showed that there was a maximum prediction error of 72.1 % between the classical Gnielinski model and experimental results.”
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 is the subject of a report. According to news originating from Wuhan, People’s Republic of China, by NewsRx correspondents, research stated, “As a promising material, liquid metals (LMs) have gained considerable interest in the field of soft robotics due to their ability to move as designed routines or change their shape dramatically under external stimuli. Inspired by the science fiction film , tremendous efforts have been devoted to liquid robots with high compliance and intelligence.” Financial support for this research came from Wuhan Institute of Technology. Our news journalists obtained a quote from the research from the Wuhan Institute of Technology, “How to manipulate LM droplets is crucial to achieving this goal. Accordingly, this review is dedicated to presenting the principles driving LMs and summarizing the potential methods to develop LM actuators of high maneuverability. Moreover, the recent progress of LM robots based on these methods is overviewed.” According to the news editors, the research concluded: “The challenges and prospects of implementing autonomous robots have been proposed.” This research has been peer-reviewed.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting originating in Hangzhou, People’s Republic of China, by NewsRx journalists, research stated, “The bio-reduction of azo dyes is significantly dependent on the availability of electron donors and external redox mediators. In this study, the natural henna plant biomass was supplemented to promote the biological reduction of an azo dye of Acid Orange 7 (AO7).” The news reporters obtained a quote from the research from Hangzhou Dianzi University, “Besides, the machine learning (ML) approach was applied to decipher the intricate process of henna-assisted azo dye removal. The experimental results indicated that the hydrolysis and fermentation of henna plant biomass provided both electron donors such as volatile fatty acid (VFA) and redox mediator of lawsone to drive the bio-reduction of AO7 to sulfanilic acid (SA). The high henna dosage selectively enriched certain bacteria, such as Firmicutes phylum, Levilinea and Paludibacter genera, functioning in both the henna fermentation and AO7 reduction processes simultaneously. Among the three tested ML algorithms, eXtreme Gradient Boosting (XGBoost) presented exceptional accuracy and generalization ability in predicting the effluent AO7 concentrations with pH, oxidation-reduction potential (ORP), soluble chemical oxygen demand (SCOD), VFA, lawsone, henna dosage, and cumulative henna as input variables. The validating experiments with tailored optimal operating conditions and henna dosage (pH 7.5, henna dosage of 2 g/L, and cumulative henna of 14 g/L) confirmed that XGBoost was an effective ML model to predict the efficient AO7 removal (91.6%), with a negligible calculating error of 3.95%.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learning have been published. According to news originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “The population aging is a growing problem worldwide. Walking is one of the most important ways of self management of health for older adults, determined by many factors, such as neighborhood environment (NE) and socio-economic attributes.” Financial supporters for this research include National Social Science Fund, Shanghai Municipal Bureau of Planning and Natural Resources Fund. Our news journalists obtained a quote from the research from Shanghai Jiao Tong University, “Al- though the previous studies have typically predicted elderly walking behavior through NE, they are limited by the methodological system and data collection, resulting in low prediction accuracy. To this end, this study incorporates residents’ subjective perceptions of the environment and objective neighborhood envi- ronmental attributes into the evaluation system, uses human-machine adversarial framework and machine learning methods to predict elderly walking behavior, and assesses the nonlinear effects of each factor. The results show that (1) combining subjective and objective factors, the prediction accuracy of elderly walk- ing behavior has been effectively improved based on human-machine adversarial framework and machine learning methods. (2) The nonlinear and threshold effects of environmental and perceptual factors on the walking time of the elderly were revealed. (3) The neighborhood attributes were incorporated into the walking behavior prediction, and were found to be of comparable importance to the influence of the NE on the behavior of the elderly.”
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 is the subject of a report. According to news report- ing originating in Stuttgart, Germany, by NewsRx journalists, research stated, “This paper describes an optimization-based trajectory planning scheme for handing over an object between a quadrotor and a wheeled robot in a transportation scenario. Concretely, a quadrotor should pick up an object from a moving ground mobile robot and deliver it to its destination.” Financial support for this research came from German Research Foundation (DFG). The news reporters obtained a quote from the research from the University of Stuttgart, “An op- timization framework based on discrete mechanics and complementarity constraints is utilized here to jointly ensure dynamic feasibility and determine the position, timing, and coordination of the handover au- tonomously. Cooperative trajectories of the heterogeneous robot system can be generated simultaneously to satisfy different requirements by adjusting the objective function and constraints.” According to the news reporters, the research concluded: “The proposed planning scheme provides a novel paradigm combining trajectory planning and handover decision-making within an optimal control problem.” This research has been peer-reviewed.
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 is the subject of a report. According to news report- ing originating in Stuttgart, Germany, by NewsRx journalists, research stated, “This paper describes an optimization-based trajectory planning scheme for handing over an object between a quadrotor and a wheeled robot in a transportation scenario. Concretely, a quadrotor should pick up an object from a moving ground mobile robot and deliver it to its destination.” Financial support for this research came from German Research Foundation (DFG). The news reporters obtained a quote from the research from the University of Stuttgart, “An op- timization framework based on discrete mechanics and complementarity constraints is utilized here to jointly ensure dynamic feasibility and determine the position, timing, and coordination of the handover au- tonomously. Cooperative trajectories of the heterogeneous robot system can be generated simultaneously to satisfy different requirements by adjusting the objective function and constraints.” According to the news reporters, the research concluded: “The proposed planning scheme provides a novel paradigm combining trajectory planning and handover decision-making within an optimal control problem.” This research has been peer-reviewed.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Artificial Intelligence have been presented. According to news originating from Rome, Italy, by NewsRx correspondents, research stated, “Organizations are increasingly leveraging the ability of artificial intelligence to analyze and resolve complex problems. This can potentially reshape the interdependencies and interactions of complex systems, leading to our research question: To what extent and in which direction is the literature on Artificial Intelligence (AI) and System Dynamics (SD) converging within the business and management landscape? We conducted an extensive literature review using bibliometric and topic modeling methods to address this question.” Our news journalists obtained a quote from the research from the Sapienza University of Rome, “Through a bibliometric analysis, we identified the areas in which academic papers referred to both SD and AI literature. However, bibliometrics do not show a clear path towards convergence. The top modeling analysis highlights more details on how convergence is structured, providing insights into how SD and AI may be integrated. Two trajectories are identified. In the ‘soft convergence,’ AI supports system dynamics analysis and modeling more deeply characterized by social interaction. In the ‘hard convergence,’ AI shapes innovative ways of rethinking system design, dynamics, and interdependencies.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learning have been published. According to news originating from Singapore, Singapore, by NewsRx correspondents, research stated, “The transition to a low-carbon economy requires the implementation of effective carbon capture and sequestration (CCS) strategies. One of the potential CCS strategies is to capture industrial CO2 emissions and inject them into the oceanic sediments to be stored as CO2 hydrates.” Funders for this research include Agency for Science Technology & Research (A*STAR), Guangdong Foreign Talent professorship, Shenzhen Science and Technology Committee, Tsinghua Shenzhen Interna- tional Graduate School.Our news journalists obtained a quote from the research from the National University of Singapore, “However, the success of this technique depends on a few key factors such as the type of sediments where CO2 is injected, the kinetics of CO2 hydrate formation and dissociation, the accuracy of the models for prediction of formation kinetics, and the CO2 hydrates morphology. So, in this first-gen work, a highly complex set of experiments was carried out to examine the CO2 hydrate formation and dissociation processes by injecting CO2 via injection tube into different size wet sediments, i.e., coarse (diameter: 0.5- 1.5 mm), granules (diameter:1.5-3.0 mm) and dual-layered sand (coarse + granules), embedded inside high-pressure reactor as the artificial seabed. The experiments were carried out at 3.5 MPa at T = 1.5-2.0 degrees C with 500 ppm of the eco-friendly hydrate promotor (l-tryptophan). The images of morphological changes during hydrate formation/dissociation, the Scanning Electron Microscope analysis of the sediments, and the estimated water-to-hydrate conversations have been reported in this work. A novel mathematical four-parameter-based CO2 hydrate kinetics model was also developed. A set of 32,843 experimental data points was used to train a supervised machine learning algorithm using two parameters with the other two taken from published literature. The water-to-hydrate conversion was estimated and follows the order of dual-layered sand [88.26 (+/- 4.62) %] >coarse [77.77 (+/- 5.72) %] >granules [65.36 (+/- 2.3) %].”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Support Vector Machines have been presented. According to news reporting out of Florianopolis, Brazil, by NewsRx editors, research stated, “Glasses are widely known for their unique properties, but improper disposal poses several environmental challenges. Laser-Induced Breakdown Spectroscopy (LIBS) has emerged as a promising tool for glass characterization.”Financial supporters for this research include Fundo de Defesa de Direitos Difusos-MJSP, Brazil, Con- selho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ). Our news journalists obtained a quote from the research from Federal University Santa Catarina, “This study explored the performance of LIBS, associated with machine learning methods and spectral angle mapper, to overcome the matrix effect in glass waste analysis. Using 10-fold cross-validation, an accuracy of 99.04% was achieved in color differentiation, 98.82% in the differentiation of flint glasses from the other glasses, 96.75% in differentiating particle sizes. When particle size and color were analyzed simultaneously, the accuracy remained high at 97.64%. The analytical accuracy was further improved using the spectral angle mapper method, which allowed us to achieve lower standard deviations, particularly for samples of larger particle sizes.”
NETL
NSTL
Springer Nature
Royal Soc Chemistry
Elsevier
Walter De Gruyter