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    Data on Machine Learning Reported by Researchers at Johns Hopkins University (Ma chine Learning Guided Analysis and Rapid Design of a 3d-printed Bio-inspired Str ucture for Energy Absorption)

    115-115页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 originating from Baltimore, Maryland, by NewsR x correspondents, research stated, "Mantis shrimps employ their telson, or tail plate, to mitigate the impact with hard surfaces, thanks to its unique double-si ne shaped microstructures that absorb energy through deformation. Inspired by th is natural impactresistant design, similar lightweight energy absorbers have bee n developed for applications in transportation systems and personal protective e quipment." Financial support for this research came from Hopkins Extreme Materials Institut e (HEMI).
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    Researchers from State University of New York (SUNY) Binghamton Report Details o f New Studies and Findings in the Area of Robotics (Integrating Action Knowledge and Llms for Task Planning and Situation Handling In Open Worlds)

    116-116页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 report. According to news reporting from Binghamton, New York, by NewsRx journalists, research stated, "Task planning systems have been developed to help robots use human knowledge (about actions) to complete long-horizon tasks. Most of them have been developed for ‘closed worlds' while assuming the robot is pro vided with complete world knowledge." Financial supporters for this research include National Science Foundation (NSF) , Ford Motor Company, SUNY Research Foundation, OPPO.
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    Investigators from Beihang University Release New Data on Robotics (Efficientnet -eca: a Lightweight Network Based On Efficient Channel Attention for Class-imbal anced Welding Defects Classification)

    117-117页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 reporting from Beijing, People's Republic of C hina, by NewsRx journalists, research stated, "Welding defects recognition is cr ucial for ensuring weldment quality in robot arc welding. Nevertheless, due to u nbalanced data distributions, limited computing resources in factory, as well as intraclass variability and interclass similarity among different welding defect s, it is difficult to extract the most discriminative defect features from weldi ng molten pool images on site, resulting in weak class-imbalanced defect recogni tion performance." The news correspondents obtained a quote from the research from Beihang Universi ty, "To address the above issue, a novel lightweight network named EfficientNet- ECA is proposed for recognizing and classifying welding defects according to mol ten pool images of robot arc welding. Firstly, the EfficientNet- ECA network base d on Efficient Channel Attention (ECA) is designed to extract the most discrimin ative features of different defects from molten pool images, where ECA is employ ed to enhance cross-channel information interactions. Secondly, a dynamic equali zed focal loss function is proposed to both rebalance the loss contribution of c lass-imbalanced data of different defects and improve defects recognition accura cy. Subsequently, a class-imbalanced dataset containing eight typical welding de fects is constructed to evaluate the EfficientNet-ECA model. Finally, the propos ed model is comprehensively analyzed through ablation studies and compared with the existing state-of-the-art lightweight models, and results show that the prop osed method exhibits better effectiveness and generalizability in classifying cl ass-imbalanced defects across different welding scenarios, achieving the highest accuracy of 95.84% on a self-constructed AL5083 dataset and 96.50 % on a publicly available SS304 dataset."
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    New Artificial Intelligence Study Findings Recently Were Reported by Researchers at Shanghai International Studies University [English Speaki ng With Artificial Intelligence (Ai): the Roles of Enjoyment, Willingness To Com municate With Ai, and ...]

    118-118页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 in Shang hai, People's Republic of China, by NewsRx journalists, research stated, "The pe rvasive use of artificial intelligence (AI) among educational stakeholders has i nevitably led to discussion around its influence on learning as well as users' c ontinuance adoption. There is a dearth of studies that contextualize the use of AI in the English-speaking learning setting, and even fewer studies examined the roles of learners' emotions generated from AI usage in influencing their speaki ng practice." Funders for this research include Shanghai International Studies University, Xi' an Jiongtong Liverpool University, CCCS, XJTLU.
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    Researchers' Work from Xiamen University Focuses on Robotics (Cooperative Roboti cs Visible Light Positioning: an Intelligent Compressed Sensing and Gan-enabled Framework)

    119-119页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news originating from Xiamen, People's Republic of China, by Ne wsRx correspondents, research stated, "This article presents a compressed sensin g (CS) based framework for visible light positioning (VLP), designed to achieve simultaneous and precise localization of multiple intelligent robots within an i ndoor factory. The framework leverages lightemitting diodes (LEDs) originally i ntended for illumination purposes as anchors, repurposing them for the localizat ion of robots equipped with photodetectors." Funders for this research include Natural Science Foundation of Fujian Province, Open Research Fund of National Mobile Communications Research Laboratory,Southe ast University, Basic and Applied Basic Research Foundation of Guangdong Provinc e, National Natural Science Foundation of China (NSFC), Science and Technology K ey Project of Fujian Province, China, Science and Technology Key Project of Xiam en, National Science Foundation (NSF), US Department of Transportation, Toyota, Amazon, JST ASPIRE.
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    Findings from Georgia Institute of Technology Update Understanding of Robotics ( Learning Prehensile Dexterity By Imitating and Emulating State-only Observations )

    120-120页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 from Atlanta, Georgia, by NewsRx journalists , research stated, "When human acquire physical skills (e.g., tool use) from exp erts, we tend to first learn from merely observing the expert. But this is often insufficient." The news correspondents obtained a quote from the research from the Georgia Inst itute of Technology, "We then engage in practice, where we try to emulate the ex pert and ensure that our actions produce similar effects on our environment. Ins pired by this observation, we introduce Combining IMitation and Emulation for Mo tion Refinement (CIMER) - a two-stage framework to learn dexterous prehensile ma nipulation skills from state-only observations. CIMER's first stage involves imi tation: simultaneously encode the complex interdependent motions of the robot ha nd and the object in a structured dynamical system. This results in a reactive m otion generation policy that provides a reasonable motion prior, but lacks the a bility to reason about contact effects due to the lack of action labels. The sec ond stage involves emulation: learn a motion refinement policy via reinforcement that adjusts the robot hand's motion prior such that the learned object motion is reenacted. CIMER is both task-agnostic (no task-specific reward design or sha ping) and intervention-free (no additional teleoperated or labeled demonstration s)."
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    Researchers from National Institute of Technology Warangal Report New Studies an d Findings in the Area of Machine Learning (Machine Learning-assisted Wire Arc A dditive Manufacturing and Heat Input Effect On Mechanical and Corrosion Behaviou r of ...)

    121-122页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 out of Warangal, India, by NewsRx e ditors, research stated, "Predicting the track forming factor or height-to-width ratio (H/W) in wire arc additive manufacturing is crucial for optimal path plan ning, heat distribution, structural integrity, distortion control, process effic iency, and defect prevention, ensuring high-quality and reliable components. Dif ferent analytical and numerical modeling methods have been introduced to predict the H/W ratio." Financial supporters for this research include Aeronautics Research and Developm ent Board of the Government of India, NIT-Warangal.
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    Urological Research Institute Reports Findings in Robotics (Learning Curve for S ingle-port Robot-assisted Urological Surgery: Singlecenter Experience and Impli cations for Adoption)

    122-123页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 report. According to news reporting originating from Milan, Italy, by New sRx correspondents, research stated, "Understanding the learning curve for the d a Vinci single-port (SP) surgical robot is crucial for adoption, training, and e nhancement of surgical safety and efficiency. Our aim was to assess the impact o f both overall experience (O-EXP) and procedure-specific experience (PS-EXP) on perioperative outcomes across various SP surgeries." Our news editors obtained a quote from the research from Urological Research Ins titute, "We analyzed data for 387 consecutive SP surgeries conducted by a high-v olume surgeon from December 2018 to July 2023. These included SP robot-assisted radical prostatectomy (SP-RARP), robot-assisted simple prostatectomy (SP-RASP), and robot-assisted nephrectomy (SP-RANP). We used multivariable logistic regress ion to evaluate the relationship between surgeon experience and outcomes, and lo cally weighted scatterplot smoothing analysis to graphically explore the risk of postoperative complications according to O-EXP. The 387 SP procedures assessed included 172 (44%) SP-RARP, 53 (14%) SP-RASP, and 162 (42 %) SP-RANP cases. Overall, 17% of patients had a c omplication of any grade, 6% experienced severe complications (Cla vien-Dindo grade 3), and 8% required readmission. Both O-EXP and P S-EXP were associated with a lower risk of complications. The odds ratios for th e incidence of complications per increment of 10 procedures were 0.83 (95% confidence interval [CI] 0.76-0.89) for PS -EXP and 0.93 (95% CI 0.90-0.96) for O-EXP. PS-EXP was also associ ated with a shorter operative time (b = -3.9, 95% CI -4.9 to -2.9) . The risk of complications reached a minimum at 30 SP-RASP, 70 SP-RANP, and 150 SP-RARP cases. Our study is limited by its retrospective design, single-surgeon experience, and lack of functional outcome assessment. Robot-assisted surgery w ith the da Vinci SP robot has a distinctive learning curve that is influenced by the platform and procedure-specific characteristics. For surgeons new to SP sur gery, RASP and renal procedures had the earliest learning curve success and shou ld be approached first, with RARP attempted only when the surgeon has become acc ustomed to the SP platform. We investigated the learning curve for a surgical ro bot that uses just one keyhole incision. We found that the time to reach profici ency for urological surgeries with this specific robot, measured as the rate of complications, is faster for some procedures than for more complex operations."
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    Findings from Shenzhen University in the Area of Machine Learning Described (Nov el Machine Learning-driven Multi-objective Optimization Method for Edm Trajector y Planning of Distorted Closed Surfaces)

    123-124页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 reporting originating in Shenzhen, Pe ople's Republic of China, by NewsRx journalists, research stated, "Highly distor ted closed surfaces pose significant challenges for machining trajectory plannin g due to their intricate surface constraints and closed structures. Despite thes e challenges, components with such features are prevalent in industries like aer ospace." Financial support for this research came from Shenzhen Natural Science Fund (the Stable Support Plan Program).
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    North Sichuan Medical College Reports Findings in Prostate Cancer (Precision mol ecular insights for prostate cancer prognosis: tumor immune microenvironment and cell death analysis of senescencerelated genes by machine learning and single- cell ...)

    124-125页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Prostate Ca ncer is the subject of a report. According to news reporting originating from Na nchong, People's Republic of China, by NewsRx correspondents, research stated, " Prostate cancer (PCa) is a prevalent malignancy among men, primarily originating from the prostate epithelium. It ranks first in global cancer incidence and sec ond in mortality rates, with a rising trend in China." Our news editors obtained a quote from the research from North Sichuan Medical C ollege, "PCa's subtle initial symptoms, such as urinary issues, necessitate diag nostic measures like digital rectal examination, prostate-specific antigen (PSA) testing, and tissue biopsy. Advanced PCa management typically involves a multif aceted approach encompassing surgery, radiation, chemotherapy, and hormonal ther apy. The involvement of aging genes in PCa development and progression, particul arly through the mTOR pathway, has garnered increasing attention. This study aim ed to explore the association between aging genes and biochemical PCa recurrence and construct predictive models. Utilizing public gene expression datasets (GSE 70768, GSE116918, and TCGA), we conducted extensive analyses, including Cox regr ession, functional enrichment, immune cell infiltration estimation, and drug sen sitivity assessments. The constructed risk score model, based on aging-related g enes (ARGs), demonstrated superior predictive capability for PCa prognosis compa red to conventional clinical features. High-risk genes positively correlated wit h risk, while low-risk genes displayed a negative correlation. An ARGs-based ris k score model was developed and validated for predicting prognosis in prostate a denocarcinoma (PRAD) patients. LASSO regression analysis and cross-validation pl ots were employed to select ARGs with prognostic significance. The risk score ou tperformed traditional clinicopathological features in predicting PRAD prognosis , as evidenced by its high AUC (0.787). The model demonstrated good sensitivity and specificity, with AUC values of 0.67, 0.675, 0.696, and 0.696 at 1, 3, 5, an d 8 years, respectively, in the GEO cohort. Similar AUC values were observed in the TCGA cohort at 1, 3, and 5 years (0.67, 0.659, 0.667, and 0.743). The model included 12 genes, with high-risk genes positively correlated with risk and low- risk genes negatively correlated. This study presents a robust ARGs-based risk s core model for predicting biochemical recurrence in PCa patients, highlighting t he potential significance of aging genes in PCa prognosis and offering enhanced predictive accuracy compared to traditional clinical parameters."
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