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 out of Seropedica, Brazil, by News Rx editors, research stated, “This study presents two innovative machine learnin g-based models: one for daily electrical load forecasting in the State of Rio de Janeiro and another for monthly forecasting for each Light concessionaire subst ation in the Metropolitan Area of Rio de Janeiro (MARJ). The utilized data inclu de (1) daily electrical load data from the National System Operator (ONS) for th e State of Rio de Janeiro spanning four years (2017-2020); (2) monthly electrica l load data from 84 Light substations over 11 years (2010-2020); and (3) maximum , minimum, and mean air temperatures.” Financial support for this research came from Conselho Nacional de Desenvolvimen to Cientifico e Tecnologico (CNPQ).
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 out of Gainesville, Florida, by N ewsRx editors, research stated, “The purpose of this research study was to exami ne the overall effect of adaptive learning systems deployed using artificial int elligence technology across a range of relevant variables (e.g., duration, stude nt level, etc.).” Our news correspondents obtained a quote from the research from University of Fl orida: “Following a systematic procedure, this meta-analysis examined literature from 18 academic databases and identified N = 45 independent studies utilizing AI-enabled adaptive learning. This meta-analysis examined the overall effect of AI-enabled adaptive learning systems on students’ cognitive learning outcomes wh en compared with non-adaptive learning interventions and found that they have a medium to large positive effect size ( g = 0.70). The effect was significantly m oderated by publication type, origin of study, student classification level, stu dent discipline, duration, and research design. In addition, all three adaptive sources (cognitive, affective, and behavioral) and adaptive targets (navigation and assessment) were significant moderators.”
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 reporting originating in Nanjing, Peo ple’s Republic of China, by NewsRx journalists, research stated, “Evaluating the progressive collapse resistance of truss string structures (TSSs) in the contex t of key member failure presents a significant challenge, particularly when this indicator is crucial during structural design and performance evaluation proces ses. Fortunately, machine learning (ML) methods can establish complex and nonlin ear relationships between input and output variables during structural performan ce evaluation.” Financial supporters for this research include National Key Research and Develop ment Program of China, 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 Computation - Neural C omputation is the subject of a report. According to news reporting from Saclay, France, by NewsRx journalists, research stated, “Mean-field models are a class o f models used in computational neuroscience to study the behavior of large popul ations of neurons. These models are based on the idea of representing the activi ty of a large number of neurons as the average behavior of mean-field variables. ” The news correspondents obtained a quote from the research from Paris-Saclay Uni versity, “This abstraction allows the study of large-scale neural dynamics in a computationally efficient and mathematically tractable manner. One of these meth ods, based on a semianalytical approach, has previously been applied to differen t types of singleneuron models, but never to models based on a quadratic form. I n this work, we adapted this method to quadratic integrate-and-fire neuron model s with adaptation and conductancebased synaptic interactions. We validated the mean-field model by comparing it to the spiking network model.”
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 Tianjin, People’s Repu blic of China, by NewsRx correspondents, research stated, “Based on water qualit y conditions and management, developing an optimized and targeted design approac h for metal-modified biochar is achievable through machine learning. This study leveraged machine learning to analyze experimental data on phosphate adsorption by metal-modified biochar from literature published in Web of Science during 201 4-2023.”Our news journalists obtained a quote from the research from the Ministry of Agr iculture and Rural Affairs, “Using six machine learning models, phosphate adsorp tion capacity of biochar and residual phosphate concentration were predicted. Fo llowing hyperparameter optimization, gradient boosting model exhibited superior training performance (R > 0.96). Metal load quantity, so lid-liquid ratio, and pH are key factors influencing adsorption performance. Opt imal preparation parameters indicated that Mg-modified biochar achieved the high est adsorption capacity (387-396 mg/g), while La-modified biochar displayed the lowest residual phosphate concentration (0 mg/L). The results of verification ex periments based on optimized process parameters closely aligned with model predi ctions.”
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 ar tificial intelligence. According to news reporting from the University of Hambur g by NewsRx journalists, research stated, “At the CMS experiment, a growing reli ance on the fast Monte Carlo application (FastSim) will accompany the high lumin osity and detector granularity expected in Phase 2.” The news editors obtained a quote from the research from University of Hamburg: “The FastSim chain is roughly 10 times faster than the application based on the Geant4 detector simulation and full reconstruction referred to as FullSim. Howev er, this advantage comes at the price of decreased accuracy in some of the final analysis observables. In this contribution, a machine learning-based technique to refine those observables is presented. We employ a regression neural network trained with a sophisticated combination of multiple loss functions to provide p ost-hoc corrections to samples produced by the FastSim chain. The results show c onsiderably improved agreement with the FullSim output and an improvement in cor relations among output observables and external parameters.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Drugs and Therapies - Antifungals is the subject of a report. According to news reporting originating from Erzurum, Turkey, by NewsRx correspondents, research stated, “Antifungal med ications are important due to their potential application in cancer treatment ei ther on their own or with traditional treatments. The mechanisms that prevent th e effects of these medications and restrict their usage in cancer treatment are not completely understood.” Our news editors obtained a quote from the research from Ataturk University, “Th e evaluation and discrimination of the possible protective effects of the anti-a poptotic members of the Bcl-2 family of proteins, critical regulators of mitocho ndrial apoptosis, against antifungal drug-induced cell death has still scientifi c uncertainties that must be considered. Novel, simple, and reliable strategies are highly demanded to identify the biochemical signature of this phenomenon. Ho wever, the complex nature of cells poses challenges for the analysis of cellular biochemical changes or classification. In this study, for the first time,we in vestigated the probable protective activities of Bcl-2 and Mcl-1 proteins agains t cell damage induced by ketoconazole (KET) and fluconazole (FLU) antifungal dru gs in a yeast model through surface-enhanced Raman spectroscopy (SERS) approach. The proposed SERS platform created robust Raman spectra with a high signal-to-n oise ratio. The analysis of SERS spectral data via advanced unsupervised and sup ervised machine learning methods enabled unquestionable differentiation (100 % ) in samples and biomolecular identification. Various SERS bands related to lipi ds and proteins observed in the analyses suggest that the expression of these an ti-apoptotic proteins reduces oxidative biomolecule damage induced by the antifu ngals. Also, cell viability assay, Annexin V-FITC/PI double staining, and total oxidant and antioxidant status analyses were performed to support Raman measurem ents.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Machine Learning are presented in a new report. According to news reporting out of Guangzhou, People’s Republic of China, by NewsRx editors, research stated, “This paper presents a surrogate mode ling approach for predicting ground surface settlement caused by synchronous gro uting during shield tunneling process. The proposed method combines finite eleme nt simulations with machine learning algorithms and introduces an intelligent op timization algorithm to invert geological parameters and synchronous grouting va riables, thereby predicting ground surface settlement without conducting numerou s finite element analyses.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Science and Technology Program of Guangzhou, China.
查看更多>>摘要：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 originating from Columbus, Ohio, by NewsRx correspo ndents, research stated, “Stomatal conductance (gs) is a key leaflevel function controlling water, carbon, and energy exchange between vegetation and the surro unding environment. Conventionally, semi-empirical models have been used to mode l gs, but these models require re-parameterization as ecosystems undergo phenolo gical changes over the growing season.” Funders for this research include National Science Foundation (NSF), National Ae ronautics & Space Administration (NASA), College of Food, Agricult ural and Environmental Sciences at Ohio State University.
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 Robotics - Ro botics and Automation have been published. According to news reporting originati ng from Zhejiang, People’s Republic of China, by NewsRx correspondents, research stated, “Reaching in unknown environments is one of the essential tasks in robo t applications. Large-scale perception and long-horizon decision-making are the keys to solving this task as the operation scope expands or complexity rises.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).Our news editors obtained a quote from the research from Zhejiang University, “E xisting navigation methods may suffer from degraded performance in complicated e nvironments induced by scalabilitylimited map representation or greedy decision strategy. We propose the path-extended graph as a compact map representation pr oviding sufficient structural information within a reasonable receptive field an d incorporate it into a hierarchical policy for higher efficiency and generaliza bility. The path-extended graph contains the concise topology of environment str ucture and frontier layout for large-scale perception, avoiding the impact of re dundant information. The hierarchical policy solves long-horizon non-myopic deci sion-making through a high-level frontier selection policy using deep reinforcem ent learning (DRL) and a low-level motion controller that handles path planning and collision avoidance.”
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