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    Recent Research from University of Namur Highlight Findings in Machine Learning (Constrained Tiny Machine Learning for Predicting Gas Concentration With I4.0 Lo w-cost Sensors)

    58-59页
    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 originating from Namu r, Belgium, by NewsRx correspondents, research stated, "Lowcost gas sensors (LC S) often produce inaccurate measurements due to varying environmental conditions that are not consistent with laboratory settings, leading to inadequate product ivity levels compared to highquality sensors. To address this issue, we propose the use of Machine Learning (ML) to predict accurate concentrations of pollutant gases acquired by LCS integrated into an embedded Internet of Things platform." Funders for this research include Belgian Walloon region - Win2WAL program of th e Public Service of Wallonia Research (SMARTSENS project), CeREF-Technique Cente r of the HELHa college.
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    Study Findings on Machine Learning Are Outlined in Reports from Swiss Federal In stitute of Technology Zurich (ETH Zurich) (Ddml: Double/debiased Machine Learnin g In Stata)

    59-60页
    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 originating from Zurich, Switze rland, by NewsRx correspondents, research stated, "In this article, we introduce a package, ddml, for double/debiased machine learning in Stata." Our news journalists obtained a quote from the research from the Swiss Federal I nstitute of Technology Zurich (ETH Zurich), "Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimati on of causal effects of endogenous variables in settings with unknown functional forms or many exogenous variables. ddml is compatible with many existing superv ised machine learning programs in Stata. We recommend using double/debiased mach ine learning in combination with stacking estimation, which combines multiple ma chine learners into a final predictor." According to the news editors, the research concluded: "We provide Monte Carlo e vidence to support our recommendation."
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    Researcher at Nantes Universite Publishes New Study Findings on Robotics (Coacti vation in Symmetric Four-Bar Mechanisms Antagonistically Actuated by Cables)

    60-61页
    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 reporting originating from Nantes, France, by NewsRx c orrespondents, research stated, "In biological systems, the joints are actuated antagonistically by muscles that can be moved coherently to achieve the desired displacement and coactivated with appropriate forces to vary joint stiffness. In spired by this, there is an interest in developing bio-inspired robots suitable for low- and high-stiffness tasks." The news journalists obtained a quote from the research from Nantes Universite: "Mechanisms actuated by antagonist cables can be a reasonable approximation of b iological joints. A study on the anti-parallelogram mechanism showed that the an tagonistic forces (>0) positively influence its stiffnes s, similar to the biological joints. This work investigates more general symmetr ic four-bar mechanisms with crossed/non-crossed limbs and top and base bars of u nequal lengths for this property. First, the cables are attached between the two unconnected pivot pairs in the four-bar mechanism, and their limits of movement are presented. Inside these limits, we show that the cable forces have a positi ve (resp. negative) influence on the stiffness of the mechanism when its limbs a re crossed (resp. non-crossed). These results are validated experimentally in al l cases."
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    Studies from University of Wisconsin Madison Add New Findings in the Area of Art ificial Intelligence (Explainable Artificial Intelligence and Multi-stage Transf er Learning for Injection Molding Quality Prediction)

    61-62页
    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 Artific ial Intelligence. According to news reporting from Madison, Wisconsin, by NewsRx journalists, research stated, "High-precision optical products made of polymeri c materials have been surging in recent years due to the prevalence of smartphon es and their camera modules. Manufacturing fast-changing generations of high-pre cision optical lenses with accurately predicted qualities is a challenging task. " Financial supporters for this research include Wisconsin Alumni Research Foundat ion, University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education (VCRGE), Wisconsin Alumni Research Foundation (WARF) - Aj ou University, Consolidated Papers Foundation Chair Professorship by the Mead Wi tter Foundation.
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    Recent Studies from Anhui University of Technology Add New Data to Machine Learn ing (A Machine-learning Based Framework for Design and Characterization of Honey combs With Partial Selfsimilar Hierarchical Architectures)

    62-63页
    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 from Anhui, People's Republic of China, by NewsRx journalists, research stated, "Honeycomb structures with hi erarchical topology are widely used in engineering fields for their excellent me chanical properties. Multiphase topology is proved to possess a larger design sp ace than the traditional hierarchical topology." Funders for this research include National Natural Science Foundation of China ( NSFC), Education Committee of Anhui Province of China.
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    New Intelligent Systems Research Has Been Reported by a Researcher at Hebei Univ ersity of Architecture (Application of online teaching-based classroom behavior capture and analysis system in student management)

    63-63页
    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 intelli gent systems. According to news originating from Zhangjiakou, People's Republic of China, by NewsRx correspondents, research stated, "Analyzing online learning behavior helps to understand students' progress, difficulties, and needs during the learning process, making it easier for teachers to provide timely feedback a nd personalized guidance." The news reporters obtained a quote from the research from Hebei University of A rchitecture: "However, the classroom behavior (CB) of online teaching is complex and variable, and relying on traditional classroom supervision methods, teacher s find it difficult to comprehensively pay attention to the learning behavior of each student. In this regard, a dual stream network was designed to capture and analyze CB by integrating AlphaPose human keypoint detection method and image d ata method. The experimental results show that when the learning rate of the mod el parameters is set to 0.001, the accuracy of the model is as high as 92.3% . When the batch size is 8, the accuracy of the model is as high as 90.8% . The accuracy of the fusion model in capturing upright sitting behavior reached 97.3%, but the accuracy in capturing hand raising behavior decreas ed to only 74.8%. The fusion model performs well in terms of accura cy and recall, with recall rates of 88.3, 86.2, and 85.1% for capt uring standing up, raising hands, and sitting upright behaviors, respectively."
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    New Machine Learning Study Findings Have Been Published by a Researcher at Unive rsity of Paris Saclay (Machine learning for determination of activity of water a nd activity coefficients of electrolytes in binary solutions)

    64-64页
    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 artificial in telligence have been published. According to news reporting out of Gif-sur-Yvett e, France, by NewsRx editors, research stated, "Activity of water and electrolyt es in aqueous solutions is of utmost importance for multiple industrial applicat ions. However, experimental determination of such values is time-consuming, whil e calculation of activity coefficients using numerical methods is challenging." Financial supporters for this research include Agence Nationale De La Recherche. Our news journalists obtained a quote from the research from University of Paris Saclay: "By training neural networks models on literature data, one could predi ct activity of water and electrolytes easily, without requiring any experiment. In this paper, multiple descriptors (or features) are compared to predict activi ty coefficients of electrolytes and activity of water in electrolyte solutions. A neural network based on the Levenberg-Marquardt algorithm (LM-NN) showed high accuracy to calculate values, despite the small size of the training datasets. B oth activity coefficients of electrolytes and activity of water in electrolyte s olutions can be predicted accurately even on unseen data, using simple descripto rs such as electrolyte concentration, ion sizes and charges. However, some discr epancies were observed due to the lack of representativeness of the training dat aset. This could be solved by selecting training data sets that are similar (e.g . same group of the periodic table) to the unknown values, or by including avail able experimental data for the salt considered."
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    Findings from Nantong University in Machine Learning Reported (Machine Learning: an Accelerator for the Exploration and Application of Advanced Metal-organic Fr ameworks)

    65-65页
    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 reporting out of Nantong, People's Republic of Chin a, by NewsRx editors, research stated, "Metal-organic framework (MOF) materials have the advantages of high specific surface area, large pore volume and adjusta ble organizational structure. It has received widespread attention in gas storag e, adsorption separation, catalysis and other fields." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Zhejiang Province. Our news journalists obtained a quote from the research from Nantong University, "The quantity of MOFs has shown an explosive growth trend in recent years. In a ddition, as a branch of artificial intelligence, the powerful adaptability, scal ability, and automation of machine learning (ML) provide a powerful tool for com prehensively evaluating the application performance of MOFs in various scenarios . This makes up for the shortcomings of complex, time-consuming and safety hazar ds in the preparation and design of traditional porous materials. By building mo dels using ML algorithms such as linear regression, random forests, and neural n etworks, it is able to predict high-performance MOFs with adsorption properties, electrical properties, catalytic properties, mechanical properties, and thermod ynamics. It promotes the joint development of ML and MOFs. This review provides an overview of the general implementation methods and processes for ML assisted MOF design, including data collection, feature selection, algorithm design, and evaluation. In addition, a summary of the classic algorithms of ML and their app lications in the classification and prediction for MOFs are summarized."
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    Studies from Zhejiang University in the Area of Machine Learning Reported (Ident ifying Drivers of County-level Industrial Carbon Intensity By a Generic Machine Learning Framework)

    66-66页
    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 from Hangzhou, People's Republic of China, by NewsRx correspondents, research stated, "Carbon intensity has been recognized as a measure of the relative change between carbon emissions and economic development in numerous policy documents at multiple levels. Count ies as the basic governmental units for policy formulation and implementation re main largely unexplored in climate governance." Financial supporters for this research include Zhejiang Provincial Science and T echnology Program Project of China, Natural Science Foundation of Zhejiang Provi nce, National Natural Science Foundation of China (NSFC), Major Project of Natio nal Social Science Fund of China.
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    Xidian University Researcher Details New Studies and Findings in the Area of Mac hine Learning (Analysis the approaches and applications for jazz music composing based on machine learning)

    67-68页
    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 artificial in telligence have been published. According to news reporting out of Xi'an, People 's Republic of China, by NewsRx editors, research stated, "As a matter of fact, computer composing is a hot topic for study in recent years."Our news reporters obtained a quote from the research from Xidian University: "T o be specific, Jazz, one of the essential music genres, has a complex and irregu lar musical structure. Current researchers are focusing on how to use models to generate expressive and innovative jazz. This study first summarizes in detail t he characteristics of the musical structure of jazz and the unique structures of jazz music that are the difficulties of model training."
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