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    Systems Research Institute Researchers Highlight Recent Research in Machine Lear ning (Multimodal Image-Based Indoor Localization with Machine Learning-A Systema tic Review)

    77-77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 originating from Warszawa, Poland, by N ewsRx editors, the research stated, “Outdoor positioning has become a ubiquitous technology, leading to the proliferation of many location-based services such a s automotive navigation and asset tracking.” Funders for this research include Agh University of Krakow. The news journalists obtained a quote from the research from Systems Research In stitute: “Meanwhile, indoor positioning is an emerging technology with many pote ntial applications. Researchers are continuously working towards improving its a ccuracy, and one general approach to achieve this goal includes using machine le arning to combine input data from multiple available sources, such as camera ima gery. For this active research area, we conduct a systematic literature review a nd identify around 40 relevant research papers. We analyze contributions describ ing indoor positioning methods based on multimodal data, which involves combinat ions of images with motion sensors, radio interfaces, and LiDARs.”
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    Imperial College London Reports Findings in Artificial Intelligence (A radiograp hic artificial intelligence tool to identify candidates suitable for partial kne e arthroplasty)

    78-78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 Artificial Intelligenc e is the subject of a report. According to news originating from London, United Kingdom, by NewsRx correspondents, research stated, “Knee osteoarthritis is a pr evalent condition frequently necessitating knee replacement surgery, with demand projected to rise substantially. Partial knee arthroplasty (PKA) offers advanta ges over total knee arthroplasty (TKA), yet its utilisation remains low despite guidance recommending consideration alongside TKA in shared decision making.” Funders for this research include Wellcome Trust, National Institute for Health and Care Research. Our news journalists obtained a quote from the research from Imperial College Lo ndon, “Radiographic decision aids exist but are underutilised due to clinician t ime constraints. This research develops a novel radiographic artificial intellig ence (AI) tool using a dataset of knee radiographs and a panel of expert orthopa edic surgeons’ assessments. Six AI models were trained to identify PKA candidacy . 1241 labelled four-view radiograph series were included. Models achieved stati stically significant accuracies above random assignment, with EfficientNet-ES de monstrating the highest performance (AUC 95%, F1 score 83% and accuracy 80%). The AI decision tool shows promise in identifyin g PKA candidates, potentially addressing underutilisation of this procedure. Its integration into clinical practice could enhance shared decision making and imp rove patient outcomes.”
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    Researchers from Lanzhou University Report Recent Findings in Machine Learning ( The Reconstruction of FY-4A and FY-4B Cloudless Top-of-Atmosphere Radiation and Full-Coverage Particulate Matter Products Reveals the Influence of Meteorologica l ...)

    79-80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 originating from Lanzhou, Peop le’s Republic of China, by NewsRx editors, the research stated, “By utilizing to p-of-atmosphere radiation (TOAR) data from China’s new generation of geostationa ry satellites (FY-4A and FY-4B) along with interpretable machine learning models , near-surface particulate matter concentrations in China were estimated, achiev ing hourly temporal resolution, 4 km spatial resolution, and 100% spatial coverage.” Funders for this research include Fundamental Research Funds For The Central Uni versities; Gansu Provincial Science And Technology Plan; National Natural Scienc e Foundation of China.
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    Researcher’s Work from Universidad Carlos III de Madrid Focuses on Machine Learn ing (Improving Indoor WiFi Localization by Using Machine Learning Techniques)

    79-79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 Mad rid, Spain, by NewsRx correspondents, research stated, “Accurate and robust posi tioning has become increasingly essential for emerging applications and services .” The news journalists obtained a quote from the research from Universidad Carlos III de Madrid: “While GPS (global positioning system) is widely used for outdoor environments, indoor positioning remains a challenging task. This paper present s a novel architecture for indoor positioning, leveraging machine learning techn iques and a divide-and-conquer strategy to achieve low error estimates. The prop osed method achieves an MAE (mean absolute error) of approximately 1 m for latit ude and longitude.”
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    Research on Machine Learning Described by a Researcher at Faculty of Information Technology (Classification of Urea Content in Fish Using Absorbance Near-Infrar ed Spectroscopy and Machine Learning)

    80-81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 originating from Da Nang, Vietnam, by NewsRx correspondents, research stated, “Near-infrared (NIR) spectroscopy has become a popular technique for assessing food quality due to its advantages over complex chemical analysis methods.” Financial supporters for this research include Ministry of Science And Technolog y of Vietnam.
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    Reports Summarize Robotics and Automation Findings from University of Ljubljana (Center Direction Network for Grasping Point Localization On Cloths)

    81-82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 Robotics - Robotics and Automation is now available. According to news reporting from Ljubljana, Sloven ia, by NewsRx journalists, research stated, “Object grasping is a fundamental ch allenge in robotics and computer vision, critical for advancing robotic manipula tion capabilities. Deformable objects, like fabrics and cloths, pose additional challenges due to their non-rigid nature.” Financial support for this research came from ARIS. The news correspondents obtained a quote from the research from the University o f Ljubljana, “In this work, we introduce CeDiRNet-3DoF, a deep-learning model fo r grasp point detection, with a particular focus on cloth objects. CeDiRNet-3DoF employs center direction regression alongside a localization network, attaining first place in the perception task of ICRA 2023’s Cloth Manipulation Challenge. Recognizing the lack of standardized benchmarks in the literature that hinder e ffective method comparison, we present the ViCoS Towel Dataset. This extensive b enchmark dataset comprises 8,000 real and 12,000 synthetic images, serving as a robust resource for training and evaluating contemporary data-driven deep-learni ng approaches. Extensive evaluation revealed CeDiRNet-3DoF’s robustness in real- world performance, outperforming state-of-the-art methods, including the latest transformer-based models.”
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    Tianshui Normal University Researcher Releases New Study Findings on Robotics (R obot Manipulator Minimum Jerk Trajectory Planning Based on the Improved Dung Bee tle Optimizer Algorithm)

    82-83页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on robotics are presented in a new rep ort. According to news originating from Gansu, People’s Republic of China, by Ne wsRx correspondents, research stated, “Trajectory planning of robotic manipulato rs in complex environments involves generating smooth and collision-free paths, and key aspects to consider include dynamic environment perception, path plannin g, trajectory smoothing and optimization, and obstacle avoidance.” Funders for this research include Malaysia Fundamental Research Grant Scheme; Ge ran Insentif Putra Siswazah; Tianshui Normal University Scientific Research Proj ect.
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    Studies from University of Michigan-Dearborn Update Current Data on Robotics (Au tomatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting)

    83-84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 originating from Dearborn, Michigan, by NewsRx editor s, the research stated, “This paper investigates the problem of optimal base pla cement in collaborative robotic car painting.” Financial supporters for this research include Ford Motor Company. Our news editors obtained a quote from the research from University of Michigan- Dearborn: “The objective of this problem is to find the optimal fixed base posit ions of a collection of given articulated robotic arms on the factory floor/ceil ing such that the possibility of vehicle paint coverage is maximized while the p ossibility of robot collision avoidance is minimized. Leveraging the inherent tw o-dimensional geometric features of robotic car painting, we construct two types of cost functions that formally capture the notions of paint coverage maximizat ion and collision avoidance minimization. Using these cost functions, we formula te a multi-objective optimization problem, which can be readily solved using any standard multi-objective optimizer. Our resulting optimal base placement algori thm decouples base placement from motion/trajectory planning. In particular, our computationally efficient algorithm does not require any information from motio n/trajectory planners a priori or during base placement computations.”
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    Fondazione Poliambulanza Istituto Ospedaliero Reports Findings in Liver Surgery (Is prolonged operative time associated with postoperative complications in live r surgery? An international multicentre cohort study of 5424 patients)

    84-85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 from Brescia, Italy, b y NewsRx journalists, research stated, “The relation between operative time and postoperative complications in liver surgery is unclear. The aim of this study i s to assess the impact of operative time on the development of postoperative com plications in patients who underwent minimally invasive or open liver resections of various anatomical extent and technical difficulty levels.” The news correspondents obtained a quote from the research from Fondazione Polia mbulanza Istituto Ospedaliero, “In this retrospective cohort study, patients tha t underwent a right hemihepatectomy (RH), technically major resection (anatomica lly minor resection in segment 1, 4a, 7 or 8; TMR) or left lateral sectionectomy (LLS) between 2000 and 2022 were extracted from a multicenter database comprisi ng the prospectively maintained databases of 31 centers in 13 countries. Minimal ly invasive procedures performed during the learning curve were omitted. Logisti c regression models, performed separately for 9 different groups based on strati fication by procedure type and allocated surgical approach, were used to assess the association between the fourth quartile of operative time (25% of patients with the longest operative time) and postoperative complications. Ov erall, 5424 patients were included: 1351 underwent RH (865 open, 373 laparoscopi c and 113 robotic), 2821 TMR (1398 open, 1225 laparoscopic and 198 robotic), and 1252 LLS (241 open, 822 laparoscopic and 189 robotic). After adjusting for pote ntial confounders (age, BMI, gender, ASA grade, previous abdominal surgery, dise ase type and extent, blood loss, Pringle, intraoperative transfusions and incide nts), the fourth quartile of operative time, compared to the first three quartil es, was associated with an increased risk of postoperative complications after o pen, laparoscopic and robotic TMR (aOR 1.35, p = 0.031; aOR 1.74, p = 0.001 and aOR 3.11, p = 0.014, respectively), laparoscopic and robotic RH (aOR 1.98, p = 0 .018 and aOR 3.28, p = 0.055, respectively) and solely laparoscopic LLS (aOR 1.6 9, p = 0.019).”
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    Research Findings from School of Computer Science and Technology Update Understa nding of Artificial Intelligence (Research on the application of artificial inte lligence technology in supply chain management)

    85-86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 originating fr om the School of Computer Science and Technology by NewsRx correspondents, resea rch stated, “As competition in the global market continues to intensify and cust omer needs become increasingly diverse, the importance of supply chain managemen t (SCM) has become increasingly prominent.” The news journalists obtained a quote from the research from School of Computer Science and Technology: “In recent years, the rapid development of artificial in telligence technology (AI) has provided new solutions for improving the efficien cy and accuracy of supply chain management. This article deeply explores the app lication of AI technology in supply chain management, including key aspects such as demand forecasting, inventory management, risk management and supply chain a utomation. Analyze the advantages of using artificial intelligence technology th rough case studies. Finally, the current research is summarized and future resea rch directions are proposed.”
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