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 Learn ing have been published. According to news originating from Besancon, France, by NewsRx correspondents, research stated, “Data -driven prognostics of systems ex ploit sensor measurements to predict the degradation evolution and anticipate fa ilures, corresponding to the estimation of the remaining useful life (RUL). This task uses feature engineering to build prognostic indicators (HI) and machine l earning (ML) to estimate the RUL.” Our news journalists obtained a quote from the research from the University of F ranche-Comte, “However, high variability in data coming from similar systems ope rating under different conditions negatively affects the RUL performance. Hence, this paper presents a new methodology that combines feature and ML engineering methods to provide an explainable RUL prediction. The key contributions lie in c onstructing efficient prognostic indicators that isolate distinct profile trajec tories, enabling adaptive RUL extraction for each system. An ensemble of heterog eneous ML predictors is also trained using these indicators and RUL trajectories , effectively addressing variability issues and enhancing RUL performance.”
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 Ma chine Learning. According to news reporting originating in Changsha, People’s Re public of China, by NewsRx journalists, research stated, “Particle size distribu tion (PSD) is an important index property of granular materials. The conventiona l mechanical sieve analysis for PSD determination is labor-intensive, time-consu ming, and inefficient.” Financial supporters for this research include National Science Fund for Disting uished Young Scholars, National Natural Science Foundation of China (NSFC), Nati onal Key R & D Program of China, Key R & D Program o f Chinese Academy of Railway Sciences, Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway (Central South University), Fundame ntal Research Funds for the Central Universities of Central South University, Ch ina.
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 Robotics is now availab le. According to news reporting from Anhui, People’s Republic of China, by NewsR x journalists, research stated, “Optically responsive liquid crystal elastomer ( LCE) devices have thriving potential to flourish in soft robots and microdrives, owing to their advantages of remote controllability, structural simplicity, and no power supply. In terms of illumination -driven modes, most research has focu sed on the dynamic response of LCE devices under continuous and periodic illumin ation, while the theoretical study of the dynamic response under moving illumina tion is limited.” Funders for this research include Open Project Program of Guangdong Provincial K ey Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, National Natural Science Foundation of China (NSFC).
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 th e subject of a report. According to news originating from Aachen, Germany, by Ne wsRx correspondents, research stated, “Demand side management (DSM) contributes to the industry’s transition to renewables by shifting electricity consumption i n time while maintaining feasible operations. Machine learning is promising for DSM with reasonable computation times and electricity price forecasting (EPF), w hich is paramount to obtaining the necessary data.” Financial supporters for this research include Federal Ministry of Education & Research (BMBF), Helmholtz Association of German Research Centers as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting out of Qingdao , People’s Republic of China, by NewsRx editors, research stated, “The Yellow Ri ver Delta wetlands in China belong to the coastal wetland ecosystem, which is on e of the youngest and most characteristic wetlands in the world.” Funders for this research include The Finance Science And Technology Project of Hainan Province.
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 th e subject of a report. According to news reporting originating from New York Cit y, New York, by NewsRx correspondents, research stated, “Digital diabetes preven tion programs (dDPPs) are effective ‘digital prescriptions’ but have high attrit ion rates and program noncompletion. To address this, we developed a personalize d automatic messaging system (PAMS) that leverages SMS text messaging and data i ntegration into clinical workflows to increase dDPP engagement via enhanced pati ent-provider communication.”
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. According to news reporting from Bologna, Italy, b y NewsRx journalists, research stated, “Rare cancers constitute over 20% of human neoplasms, often affecting patients with unmet medical needs. The devel opment of effective classification and prognostication systems is crucial to imp rove the decision-making process and drive innovative treatment strategies.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Robotics have been publi shed. According to news originating from Shenyang, People’s Republic of China, b y NewsRx correspondents, research stated, “With the development of robotics and Internet of Things, robot-assisted goods-to-person order picking systems become popular in smart warehouses. Order picking in such systems is a human-robot coll aborative process, where robots carry pods to a picking station with human picke rs who pick the demanded goods from them to fulfill orders.” Financial support for this research came from National Key Research and Developm ent Program of China.
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 intelligen ce have been presented. According to news reporting out of Zonguldak Bulent Ecev it University by NewsRx editors, research stated, “Forest aboveground biomass ( AGB) is one of the critical measures of forest resources. Therefore, it is cruci al to identify a reliable method to estimate the AGB, especially in the tropics, where forest ecosystems are exposed to several depleting factors, including def orestation, climate change and replacing natural forests with palm oil tree plan tations.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news originating from Goiania, Brazil, by N ewsRx correspondents, research stated, “In this research, a group of charging me ssages for the payment of taxes was investigated. Altogether 12 variations of bi lling messages (social norms, simplification, disclosure, previous engagement, r eminders and previous choices) were evaluated, and their effectiveness was teste d.” Our news journalists obtained a quote from the research from Federal University Goias, “The messages were transmitted to defaulting microentrepreneurs in four B razilian states. From a database containing information about defaulting micro e ntrepreneurs, 250 thousand text messages were sent making charges. The data were obtained from the Secretaria Especial da Micro e Pequena Empresa (Sempe). Tests were used to analyse the difference between means and Logistic Regression was u sed in sequence. The Random Forest, Logistic Regression and Na & i uml;ve Bayes widgets were used to indicate the robustness of the Machine Learnin g predictive model. The research findings indicated that the formats ‘simplifica tion’, ‘previous choices’ and ‘alert’, employees, did not have an effect in comb ating default. However, when aligned with social norms, messages in the form of ‘past options’ and ‘reminders’ increase the payment of debts. The widgets used i ndicated an excellent fit to the machine learning model. The Random Forest tool attested with superiority that the model is robust and suitable for the predicti ve function. The results of the research provide a contribution to public polici es when they present an effective action to reduce defaults in the payment of ta xes.”
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