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    Findings on Robotics Discussed by Investigators at University of Padua (Task All ocation Model for Human-robot Collaboration With Variable Cobot Speed)

    68-68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 Vicenza, Italy, by NewsRx c orrespondents, research stated, “New technologies, such as collaborative robots, are an option to improve productivity and flexibility in assembly systems. Task allocation is fundamental to properly assign the available resources.” Financial support for this research came from Universita degli Studi diPadova wi thin the CRUI-CARE Agreement.

    Reports Summarize Robotics Study Results from University of Seoul (Energy effici ent robot operations by adaptive control schemes)

    68-69页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on robotics are presented i n a new report. According to news originating from the University of Seoul by Ne wsRx correspondents, research stated, “Energy efficiency is key to achieving the Sustainable Development Goals (SDGs) globally.”

    Data on Artificial Intelligence Discussed by Researchers at Free University Bolz ano (Artificial Intelligence In Supply Chain Management: a Systematic Literature Review of Empirical Studies and Research Directions)

    69-70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 from Bolzano, Italy, by NewsRx journalists, research stated, “This article presents a systematic lit erature review (SLR) of empirical studies concerning Artificial Intelligence (AI ) in the field of Supply Chain Management (SCM). Over the past decade, technolog ies belonging to AI have developed rapidly, reaching a sufficient level of matur ity to catalyze transformative changes in business and society.”

    Researchers from Jaypee University of Engineering & Technology Des cribe Findings in Machine Learning (Machine Learning for Predicting the Half Cel l Potential of Cathodically Protected Reinforced Cement Concrete Slabs Subjected To Chloride ...)

    70-71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 Machine Learning have been presented. According to news reporting originating in Guna, India, by News Rx journalists, research stated, “This research work predicts the Half Cell Pote ntial (HCP) values of cathodically protected concrete slabs subjected to chlorid e ingress using machine learning techniques. Six classes of cathodically protect ed slabs were cast using centrally placed pure Magnesium (Mg) anodes and AZ91D o f dimensions 1000 mm x 1000 mm x 100 mm.”

    Studies from Peking Union Medical College in the Area of Machine Learning Report ed (Functional Evaluation of tmem176b and Its Predictive Role for Severe Respira tory Viral Infection Through Integrated Analysis of Single-cell and Bulk ...)

    71-72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 Machine Learn ing have been published. According to news originating from Beijing, People’s Re public of China, by NewsRx correspondents, research stated, “Transmembrane prote in 176B (TMEM176B), localized mainly on the endosomal membrane, has been reporte d as an immune regulatory factor in malignant diseases. However, the biological function of this molecule remains undetermined during respiratory viral infectio ns.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), CAMS Institute of Respiratory Medicine Grant for Young Schol ars.

    Investigators at Nanjing Tech University Discuss Findings in Machine Learning (U se of Interpretable Machine Learning Approaches for Quantificationally Understan ding the Performance of Steel Fiber-reinforced Recycled Aggregate Concrete: From the ...)

    72-73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 in Nanjing, People’s Rep ublic of China, by NewsRx journalists, research stated, “In this study, four mac hine learning (ML) algorithms, namely Support Vector Machine (SVM), Back-propaga tion Artificial Neural Network (BP-ANN), Adaptive Boosting (AdaBoost), and Gradi ent Boosted Regression Tree (GBRT), were employed to conduct an in-depth analysi s of the global estimation model of the compressive strength and splitting tensi le strength of steel fiber recycled aggregate concrete (SFR-RAC). A database con taining 465 compressive strength sets and 339 splitting tensile strength sets wi th different mix proportions was established, and the ML model was trained and t ested in combination with Bayesian optimization.”

    Research Reports from War Studies University Provide New Insights into Artificia l Intelligence (Harnessing Artificial Intelligence for Enhanced Scientific Colla boration: Insights from Students and Educational Implications)

    73-74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 originating from War saw, Poland, by NewsRx correspondents, research stated, “This study aimed to exp lore students’ perspectives on integrating artificial intelligence (AI) into sci entific collaboration, specifically on writing academic articles and creating sc ientific posters.” Funders for this research include War Studies University.

    Research Conducted at AF Engineering University Has Updated Our Knowledge about Robotics and Automation (Gatr: Transformer Based On Guided Aggregation Decoder f or 3d Multi-modal Detection)

    74-75页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Robotics - Robotics and Automation are presented in a new report. According to news reporting from Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “In the automatic dri ving 3D object detection task, the multi-modal fusion method can realize the com plementarity of different modal information, especially the fusion algorithm of LiDAR point cloud and camera image has been widely used. Nowadays, most point cl oud-image fusion methods employ external projection matrix to achieve data align ment.”

    Study Results from University of Alberta in the Area of Robotics Reported (Criti cal Review of Virtual Reality Applications In Offsite Construction Research)

    75-76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 in Edmonton, Canada, by NewsRx journalists, research stated, “Offsite construction (OSC) techniques are argued to provide superior quality and shorter schedules compared with traditional tech niques. Nonetheless, the pace of OSC implementation has been slow due to the inf luence of several barriers.” Financial support for this research came from Natural Sciences and Engineering R esearch Council of Canada (NSERC).

    Studies from Nanjing University Further Understanding of Robotics and Automation (Cda: Covert Deception Attacks In Multi-agent Resource Scheduling)

    76-77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 Robotics - Ro botics and Automation have been published. According to news reporting from Nanj ing, People’s Republic of China, by NewsRx journalists, research stated, “In thi s letter, we address the critical security concerns in multi-agent systems, wher e illegal infiltration is commonly used to convert agents into malicious entitie s. Existing research predominantly focuses on explicit malicious attack patterns .”