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    Research Results from Universidad Cooperativa de Colombia Up- date Understanding of Machine Learning (Machine Learning Model for Primary Solar Resource Assessment in Colombia)

    67-67页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artificial intelligence. According to news originating from the Universidad Cooperativa de Colombia by NewsRx editors, the research stated, “This work introduces a Machine Learning (ML) model designed to predict solar radiation in diverse cities representing Colombia’s climatic variability. It is crucial to assert that the amount of solar energy received in a specific region is directly related to solar radiation and its availability, which is influenced by each area’s particular climatic and geographic conditions.”

    Study Data from Rutgers University - The State University of New Jersey Update Understanding of Machine Learning (Partial-physics- informed Multi-fidelity Modeling of Manufacturing Processes)

    68-69页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news originating from Piscataway, New Jersey, by NewsRx correspondents, research stated, “The design and control of manufacturing processes hinges on predictive modeling of its parametric effects. The deployability of Machine Learning (ML) models has made them of increasing interest for this purpose.” Financial support for this research came from National Science Foundation (NSF).

    New Artificial Intelligence Study Findings Have Been Reported from Otto-von-Guericke-University (A dynamic approach for visualizing and exploring concept hierarchies from textbooks)

    69-70页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – 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 Magdeburg, Germany, by NewsRx journalists, research stated, “In this study, we propose a visu- alization technique to explore and visualize concept hierarchies generated from a textbook in the legal domain. Through a human-centered design process, we developed a tool that allows users to effectively navigate through and explore complex hierarchical concepts in three kinds of traversal techniques: top- down, middle-out, and bottom-up.”

    Findings from Technical University Chemnitz (TU Chemnitz) Broaden Understanding of Robotics (Batteries for Small-scale Robotics)

    70-71页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Robotics. According to news reporting from Chemnitz, Germany, by NewsRx journalists, research stated, “The advent of small-scale robots holds immense potential for revolutionizing various industries, particularly in the domains of surgery and operations within confined spaces that are currently inaccessible to conventional tools. However, their tethered nature and dependence on external power sources impede their progress.” Financial supporters for this research include European Research Council (ERC), European Research Council (ERC).

    Findings from University of Miami Has Provided New Data on Machine Learning (Rexprt: a Machine Learning Tool To Predict Pathogenicity of Tandem Repeat Loci)

    71-72页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – 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 Miami, Florida, by NewsRx journalists, research stated, “Expansions of tandem repeats (TRs) cause approximately 60 monogenic diseases. We expect that the discovery of additional pathogenic repeat expansions will narrow the diagnostic gap in many diseases.” Financial support for this research came from American Heart Association.

    Tongji University Reports Findings in Artificial Intelligence [Applica- tion of artificial intelligence in (waste)water disinfection: Emphasiz- ing the regulation of disinfection by-products formation and residues prediction]

    72-73页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligence is the subject of a report. According to news reporting originating in Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “Water/wastewater ((waste)water) disinfection, as a critical process during drinking water or wastewater treatment, can simultaneously inactivate pathogens and remove emerging organic contaminants. Due to fluctuations of (waste)water quantity and quality during the disinfection process, conventional disinfection models cannot handle intricate nonlinear situations and provide immediate responses.”

    Findings from Columbia Business School Yields New Data on Ma- chine Learning (Machine-learning the Skill of Mutual Fund Man- agers)

    73-74页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting out of New York City, New York, by NewsRx editors, research stated, “We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, before and after fees. The outperformance persists for more than three years.” Our news journalists obtained a quote from the research from Columbia Business School, “Fund mo- mentum and fund flow are the most important predictors of future risk-adjusted fund performance, while characteristics of the stocks that funds hold are not predictive. Returns of predictive long-short portfolios are higher following a period of high sentiment.”

    Jinan University Reports Findings in Machine Learning (Use of ma- chine learning to identify key factors regulating volatilization of semi-volatile organic chemicals from soil to air)

    74-74页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – 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 report- ing from Guangzhou, People’s Republic of China, by NewsRx journalists, research stated, “Volatilization from soil to air is a key process driving the distribution and fate of semi-volatile organic contaminants. However, quantifying this process and the key environmental governing factors remains difficult.” The news correspondents obtained a quote from the research from Jinan University, “To address this issue, the volatilization fluxes of polybrominated diphenyl ethers (PBDEs) and organophosphate esters (OPEs) from soil were determined in 16 batch experiments orthogonally with six variables (chemical prop- erty, soil concentration, air velocity, ambient temperature, soil porosity, and soil moisture) and analyzed with machine learning methods. The results showed that gradient-boosting regression tree models satis- factorily predicted the volatilization fluxes of PBDEs (r = 0.82 ± 0.07) and OPEs (r = 0.62 ± 0.13). Permutation importance analysis showed that partitioning potential of chemicals between soil and air was the most important factor regulating the volatilization of the target compounds from soil. Temperature and soil porosity played a secondary role in controlling the migration of PBDEs and OPEs, respectively, due to higher volatilization enthalpies of PBDEs than those of OPEs and dominant adsorption of OPEs on mineral surface. The effect of soil moisture was negative and positive for the volatilization fluxes of PBDEs and OPEs, respectively.”

    New Findings Reported from Delft University of Technology De- scribe Advances in Machine Learning (Data-enhanced Design: En- gaging Designers In Exploratory Sensemaking With Multimodal Data)

    75-75页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – 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 Delft, Netherlands, by NewsRx journalists, research stated, “Research in the wild can reveal human behaviors, contexts, and needs around products that are difficult to observe in the lab. Telemetry data from the use of physical products can help facilitate in the wild research, in particular by suggesting hypotheses that can be explored through machine learning models.” Financial support for this research came from UK Research Councils/EPSRC under the New Industrial Systems theme through the Chatty Factories project.

    Reports from University of Agder Highlight Recent Findings in Arti- ficial Intelligence (Artificial Intelligence and Corporate Carbon Neu- trality: a Qualitative Exploration)

    76-76页
    查看更多>>摘要:2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Artificial Intelligence are discussed in a new report. According to news originating from Kristiansand, Norway, by NewsRx correspondents, research stated, “Many firms have established formal carbon neutrality (CN) targets in response to the increasing climate risk and related regulatory requirements. Subsequently, they have implemented various measures and adopted multiple approaches to attain these goals.” Our news journalists obtained a quote from the research from the University of Agder, “Academic research has given due attention to firms’ efforts in this direction. However, past studies have primarily focused on non-digital and process-oriented approaches to achieving CN, with the potential of digital technologies such as artificial intelligence (AI) remaining less explored.”