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    Findings from University of Brescia Provide New Insights into Machine Learning ( Enabling End-User Development in Smart Homes: A Machine Learning-Powered Digital Twin for Energy Efficient Management)

    135-135页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news originating from Brescia, Italy, b y NewsRx correspondents, research stated, “End-User Development has been propose d over the years to allow end users to control and manage their Internet of Thin gs-based environments, such as smart homes.” Financial supporters for this research include Italian Mur Prin 2022 Pnrr; Europ ean Union-next Generation Eu. The news editors obtained a quote from the research from University of Brescia: “With End-User Development, end users are able to create trigger-action rules or routines to tailor the behavior of their smart homes. However, the scientific r esearch proposed to date does not encompass methods that evaluate the suitabilit y of user-created routines in terms of energy consumption. This paper proposes u sing Machine Learning to build a Digital Twin of a smart home that can predict t he energy consumption of smart appliances.”
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    Studies from Federal University Add New Findings in the Area of Robotics (Dynami cs analysis and chatter control of a polishing and milling nonideal flexible man ipulator)

    136-136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 Parana, Brazil, by NewsRx c orrespondents, research stated, “Some robots are designed to be lightweight and flexible, enabling them to access small and challenging paths in various applica tions.” The news editors obtained a quote from the research from Federal University: “Th ese features enable robots to collaborate with humans in performing specific pro duction tasks. However,the movement of the flexible manipulator can become self- excited when handling a cutting tool on a workpiece, which can lead to a control problem. This article presents a control solution for lightweight robotic manip ulators with rotating tools, such as polishing and milling, using smart actuator s. The control discretization method is also introduced to facilitate integratio n into digital controllers. The paper starts by describing the governing equatio ns of the non-ideal flexible manipulator for polishing and milling and analysing its dynamic behavior. Subsequently, models for the controllers of the DC motor- only actuators and the hybrid (shape memory alloy and DC motors) actuators were formulated using shape memory alloy and a suboptimal control scheme known as the discrete state-dependent Riccati equation.”
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    Data on Machine Learning Described by Researchers at Shahjalal University of Sci ence and Technology (Advanced machine learning approaches for predicting permeab ility in reservoir pay zones based on core analyses)

    137-137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 artificial intell igence are discussed in a new report. According to news reporting from Sylhet, B angladesh, by NewsRx journalists, research stated, “Permeability is the most imp ortant petrophysical characteristic for determining how fluids pass through rese rvoir rocks. This study aims to develop and assess intelligent computer-based mo dels for predicting permeability.” Our news correspondents obtained a quote from the research from Shahjalal Univer sity of Science and Technology: “The research focuses on three novel models-Deci sion Tree, Bagging Tree, and Extra Trees-while also investigating previously app lied techniques such as random forest, support vector regressor (SVR), and multi ple variable regression (MVR). The primary dataset consists of 197 data points f rom a heterogeneous petroleum reservoir in the Jeanne d’Arc Basin, including lab oratory-derived permeability (K), oil saturation (SO), water saturation (SW), gr ain density (rgr), porosity (ph), and depth. The most effective machine learning models are identified by a thorough analysis that makes use of a variety of sta tistical metrics, such as the coefficient of the determinant (R2), mean squared error (MSE), mean absolute error (MAE), root mean square error (RMSE), mean abso lute percentage error (MAPE), maximum error (maxE), and minimum error (minE). Ad ditionally, core features are ranked based on their importance in permeability m odeling. This study deviates from conventional approaches by proposing an effici ent means of forecasting permeability, reducing reliance on labor-intensive and time-consuming laboratory work. The findings reveal that MVR is unsuitable for p ermeability prediction, with all developed models outperforming it. Extra Trees emerges as the most accurate model, with an R2 of 0.976, while random forest and bagging tree exhibit slightly lower R2 values of 0.961 and 0.964, respectively. The ranking of these algorithms based on performance criteria is as follows: ex tra trees, bagging tree, random forest, SVR, decision tree, and MVR. The study a lso presents a detailed analysis of the impact of input parameters, highlighting porosity (ph) and water saturation (SW) as the most influential, while grain de nsity (rgr), oil saturation (SO), and depth are considered less important.”
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    Research from West Anhui University in the Area of Pattern Recognition and Artif icial Intelligence Described (The Classification Algorithm of Nano Targets Based on Millimeter Wave Radar)

    138-138页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on pattern recognition and artificia l intelligence is the subject of a new report. According to news originating fro m West Anhui University by NewsRx correspondents, research stated, “Nanodrones a re insect-sized drones that could fly in complex environments and confined space s, and act as an emerging tool for covert surveillance and intelligence attacks, which would become a potential threat to national security.” Financial supporters for this research include Research Start-up Fund of West An hui University; Provincial Natural Science Research Project of Anhui University; The Fund of Generic Technology Research Center For Anhui Traditional Chinese Me dicine Industry; The Open Fund of Anhui Undergrowth Crop Intelligent Equipment E ngineering Research Center; High-level Talents Research Startup Fund of West Anh ui University.
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    McMaster University Reports Findings in Prostatectomy (Predictors of failed same -day discharge in patients undergoing robot-assisted radical prostatectomy in a Canadian universal healthcare system)

    139-140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 Surgery - Prostatectom y is the subject of a report. According to news reporting from Hamilton, Canada, by NewsRx journalists, research stated, “Same-day discharge (SDD) after robot-a ssisted radical prostatectomy (RARP) has been shown to be feasible and safe. In order to improve uptake of this ambulatory model in Canada, we aimed to update o ur experience of SDD after RARP and identify reasons for SDD pathway non-initiat ion and failure in a universal healthcare system.”
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    Findings on Machine Learning Detailed by Investigators at Aalto University (Mach ine Learning the Kondo Entanglement Cloud From Local Measurements)

    139-139页
    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 Machine Learning is now available. According to news reporting out of Espoo, Finland, by NewsRx editors , research stated, “A quantum coherent screening cloud around a magnetic impurit y in metallic systems is the hallmark of the antiferromagnetic Kondo effect. Des pite the central role of the Kondo effect in quantum materials, the structure of quantum correlations of the screening cloud has defied direct observations.” Financial supporters for this research include Magnus Ehrnrooth Foundation, Rese arch Council of Finland, Jane and Aatos Erkko Foundation, Aalto Science -IT proj ect.
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    New Findings from Warsaw University of Technology Update Understanding of Machin e Learning (Predicting Detonation Cell Size of Biogas-oxygen Mixtures Using Mach ine Learning Models)

    140-141页
    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 Machine Learning is now available. According to news reporting out of Warsaw, Poland, by NewsRx editors , research stated, “Detonation cell size is a very important parameter describin g the detonation process, used both for explosion safety analysis and for the de sign of detonation combustion chambers. Typically it has been studied either exp erimentally or by CFD simulations; both options are costly in terms of money and time.” Financial support for this research came from Politechnika Warszawska.
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    Data from South China University of Technology Provide New Insights into Robotic s and Automation (Event-triggered Adaptive Fault-tolerant Boundary Control for F lexible Bionic Fish Tail With Output Constraint)

    141-142页
    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 Robotics - Robotics and Automation. According to news reporting originating from Guangzhou, People’s Republic of China, by NewsRx correspondents, research state d, “The article focuses on the tracking issue of a flexible bionic fish tail sys tem under boundary control. The flexible bionic fish tail system is modeled as a n Euler-Bernoulli beam with nonuniform parameters, where its actuator is a DC m otor located at the front end of the tail.” Financial support for this research came from National Key R&D Prog ram of China.
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    Study Findings from Zhejiang University of Technology Update Knowledge in Machin e Learning (Prediction of free chloride concentration in fly ash concrete by mac hine learning methods SVR, MLP and CNN)

    142-143页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting from Hangzhou, People’s Republic of China, by NewsRx journalists, research stated, “Free chloride concen tration distribution is important for assessing the corrosion risk of steel bars in reinforced concrete structures under chloride environment.” Our news reporters obtained a quote from the research from Zhejiang University o f Technology: “In this study, a group of 3150 free chloride concentration data s ets were obtained. Afterwards, three machine learning methods, including Support Vector Regression (SVR), Multilayer Perceptron (MLP) and One- Dimensional Convol utional Neural Network (1D-CNN) were adopted to construct models to predict chlo ride concentration distribution. Results show that 1D-CNN and MLP models are bet ter at predicting the chloride concentration in fly ash concrete, whereas the pr ediction capability of SVR is relatively poor. Moreover, free chloride concentra tion prediction based on unmeasured parameters was conducted. Results show that the 1D-CNN and MLP models both have high prediction abilities, i.e., predicted r esults are consistent with experimental measurements, performing generally bette r than the time-varying model constructed based on Fick’s second law.”
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    New Robotics Research from Nantes Universite Discussed (Comparison Analysis of B io-Inspired Tendon-Driven Manipulators Based on Their Tension-Feasible Workspace )

    143-144页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on robotics have been pr esented. According to news reporting originating from Nantes, France, by NewsRx correspondents, research stated, “Bio-inspiration can be used in the development of novel dextrous and energy-efficient manipulators. This paper focuses on plan ar manipulators inspired by the bird neck, built upon stacking a series of tense grity X-joints.”
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