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    Study Findings on Artificial Intelligence Described by Researchers at German Aer ospace Center (In Situ Enhancement of Heliostat Calibration Using Differentiable Ray Tracing and Artificial Intelligence)

    19-20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 artificial intelligen ce have been presented. According to news reporting originating from the German Aerospace Center by NewsRx correspondents, research stated, “The camera target m ethod is the most commonly used calibration method for heliostats at solar tower power plants to minimize their sun tracking errors. In this method, individual heliostats are moved to a white surface and their deviation from the targeted po sition is measured.” Financial supporters for this research include Deutsches Zentrum Fur Luft- Und R aumfahrt.
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    New Robotics Study Findings Have Been Reported by Researchers at Harbin Institut e of Technology (Hierarchical Control for Partially Feasible Tasks With Arbitrar y Dimensions: Stability Analysis for the Tracking Case)

    20-21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 in Harbin, People’s Republic of China, by NewsRx journalists, research stated, “Hierarchical impedance-based tra cking control has attracted much interest recently due to its advantages of no e xternal forces/torques feedback and inertia reshaping. Desired trajectories on e ach hierarchy level can be asymptotically tracked following the order of priorit ies.” Funders for this research include National Natural Science Foundation of China ( NSFC), Major Scientific and Technological Research Project of Ningbo, New Corner stone Science Foundation through the XPLORER PRIZE.
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    Research on Machine Learning Detailed by Researchers at Xi’an Jiaotong Universit y (The relationship between attribute performance and customer satisfaction: an interpretable machine learning approach)

    21-21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 out of Xi’an, People’s Republic of China, by NewsRx editors, research stated, “Understanding the relationship betw een attribute performance (AP) and customer satisfaction (CS) is crucial for the hospitality industry.” Financial supporters for this research include National Key Research And Develop ment Program of China; National Natural Science Foundation of China. Our news journalists obtained a quote from the research from Xi’an Jiaotong Univ ersity: “However, accurately modeling this relationship remains challenging. To address this issue, we propose an interpretable machine learning-based dynamic a symmetric analysis (IML-DAA) approach that leverages interpretable machine learn ing (IML) to improve traditional relationship analysis methods. The IML-DAA empl oys extreme gradient boosting (XGBoost) and SHapley Additive exPlanations (SHAP) to construct relationships and explain the significance of each attribute. Foll owing this, an improved version of penalty-reward contrast analysis (PRCA) is us ed to classify attributes, whereas asymmetric impact-performance analysis (AIPA) is employed to determine the attribute improvement priority order. A total of 2 9,724 user ratings in New York City collected from TripAdvisor were investigated . The results suggest that IML-DAA can effectively capture non-linear relationsh ips and that there is a dynamic asymmetric effect between AP and CS, as identifi ed by the dynamic AIPA model.”
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    Reports Outline Robotics Study Findings from Swiss Federal Institute of Technolo gy (Enhancing Dexterity In Confined Spaces: Real-time Motion Planning for Multif ingered In-hand Manipulation)

    22-22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 have been published. According to news originating from Lausanne, Switzerland, by Ne wsRx correspondents, research stated, “Dexterous in-hand manipulation in robotic s, particularly with multifingered robotic hands, poses significant challenges d ue to the intricate avoidance of collisions among fingers and the object being m anipulated. Collision-free paths for all fingers must be generated in real time, as the rapid changes in hand and finger positions necessitate instantaneous rec alculations to prevent collisions and ensure undisturbed movement.” Financial support for this research came from European Research Council (ERC).
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    Sichuan University Reports Findings in Liver Surgery (Trend of robot-assisted su rgery system in gastrointestinal and liver surgery: A bibliometric analysis)

    23-23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 - Liver Surger y is the subject of a report. According to news reporting out of Chengdu, People ’s Republic of China, by NewsRx editors, research stated, “Robot-assisted gastro intestinal and liver surgery has been an important development direction in the field of surgery in recent years and it is also one of the fastest developing an d most concerning fields in surgical operations. To illustrate the major areas o f research and forward-looking directions over the past twenty-six years.” Our news journalists obtained a quote from the research from Sichuan University, “Using the Web of Science Core Collection database, a comprehensive review of s cholarly articles pertaining to robot-assisted gastrointestinal and liver surger y was researched out between 2000 and 2023. We used Citespace (Version 6.2.4) an d Bibliometrix package (Version 4.3.0) to visualize the analysis of all publicat ions including country, institutional affiliations, authors, and keywords. In to tal, 346 articles were retrieved. had with the largest number of publications an d was cited in this field. The United States was a core research country in this field. Yonsei University was the most productive institution. The current focus of this field is on rectal surgery, long-term prognosis, perioperative manageme nt, previous surgical experience, and the learning curve. The scientific interes t in robot-assisted gastrointestinal and liver surgery has experienced a signifi cant rise since 1997.”
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    Researcher from Kyung Hee University Reports Details of New Studies and Findings in the Area of Robotics (Human-to-Robot Handover Based on Reinforcement Learnin g)

    24-24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 robotics is the subjec t of a new report. According to news reporting out of Seoul, South Korea, by New sRx editors, research stated, “This study explores manipulator control using rei nforcement learning, specifically targeting anthropomorphic gripper-equipped rob ots, with the objective of enhancing the robots’ ability to safely exchange dive rse objects with humans during humanrobot interactions (HRIs).” Financial supporters for this research include Ministry of Science And Ict (Msit ), Korea; Ministry of Education of Korea; Korea Government; Ministry of Trade, I ndustry And Energy (Motie), South Korea.
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    King Abdulaziz University Researcher Focuses on Machine Learning (Detection of G PS Spoofing Attacks in UAVs Based on Adversarial Machine Learning Model)

    25-25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 originating from Jeddah, Saudi Arabia, by NewsRx correspondents, research stated, “Advancements in wirel ess communication and automation have revolutionized mobility systems, notably t hrough autonomous vehicles and unmanned aerial vehicles (UAVs).” Funders for this research include King Abdulaziz University (Kau), Jeddah, Saudi Arabia.
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    Researchers from University of Toronto Describe Research in Machine Learning (Ma chine-learning-derived thermal conductivity of two-dimensional TiS2/MoS2 van der Waals heterostructures)

    26-26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 ar tificial intelligence. According to news reporting out of Toronto, Canada, by Ne wsRx editors, research stated, “Predicting the thermal conductivity of twodimen sional (2D) heterostructures is challenging and cannot be adequately resolved us ing conventional computational approaches.” Funders for this research include Natural Sciences And Engineering Research Coun cil of Canada; New Frontiers in Research Fund-exploration.
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    First Affiliated Hospital Reports Findings in Breast Cancer (Predicting gene sig nature in breast cancer patients with multiple machine learning models)

    27-27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 Oncology - Breast Canc er is the subject of a report. According to news reporting originating from Zhej iang, People’s Republic of China, by NewsRx correspondents, research stated, “Th e aim of this study was to predict gene signatures in breast cancer patients usi ng multiple machine learning models. In this study, we first collated and merged the datasets GSE54002 and GSE22820, obtaining a gene expression matrix comprisi ng 16,820 genes (including 593 breast cancer (BC) samples and 26 normal control (NC) samples).” Our news editors obtained a quote from the research from First Affiliated Hospit al, “Subsequently, we performed enrichment analyses using Gene Ontology (GO), Ky oto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO). We iden tified 177 differentially expressed genes (DEGs), including 40 up-regulated and 137 down-regulated genes, through differential expression analysis. The GO enric hment results indicated that these genes are primarily involved in extracellular matrix organization, positive regulation of nervous system development, collage n-containing extracellular matrix, heparin binding, glycosaminoglycan binding, a nd Wnt protein binding, among others. KEGG enrichment analysis revealed that the DEGs were primarily associated with pathways such as focal adhesion, the PI3K-A kt signaling pathway, and human papillomavirus infection. DO enrichment analysis showed that the DEGs play a significant role in regulating diseases such as int estinal disorders, nephritis, and dermatitis. Further, through LASSO regression analysis and SVM-RFE algorithm analysis, we identified 9 key feature DEGs (CF-DE Gs): ANGPTL7, TSHZ2, SDPR, CLCA4, PAMR1, MME, CXCL2, ADAMTS5, and KIT. Additiona lly, ROC curve analysis demonstrated that these CF-DEGs serve as a reliable diag nostic index. Finally, using the CIBERSORT algorithm, we analyzed the infiltrati on of immune cells and the associations between CF-DEGs and immune cell infiltra tion across all samples.”
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    Reports from Yunnan University of Finance and Economics Add New Data to Findings in Robotics (A Robot Ground Medium Classification Algorithm Based On Feature Fu sion and Adaptive Spatiotemporal Cascade Networks)

    28-29页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Robotics are discussed in a new report. According to news reporting originating in Yunnan, People’s Republic of China, by NewsRx journalists, research stated, “With technological advanceme nts and scientific progress, mobile robots have found widespread applications ac ross various fields. To enable robots to perform tasks safely and effectively in diverse and unknown environments, this paper proposes a ground medium classific ation algorithm for robots based on feature fusion and an adaptive spatio-tempor al cascade network.” Funders for this research include Major Science and Technology Special Project o f Yunnan Province, Key Research and Development Program of Yunnan Province, Nati onal College Students’ Innovation and Entrepreneurship Training Program of 2023, The 2023 Yunnan Provincial Student Innovation and Entrepreneurship Training Pro gram, The 2022 Yunnan Provincial Student Innovation and Entrepreneurship Trainin g Program, National Natural Science Foundation of China (NSFC).
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