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    Researchers at Karlsruhe University of Applied Sciences Target Robotics (Facets of Trust and Distrust In Collaborative Robots At the Workplace: Towards a Multidimensional and Relational Con- ceptualisation)

    20-20页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news reporting originating in Karlsruhe, Germany, by NewsRx editors, the research stated, “The relevance of trust on the road to successful human-robot interaction is widely acknowledged. Thereby, trust is commonly understood as a monolithic concept characterising dyadic relations between a human and a robot.” Financial support for this research came from Hochschule Karlsruhe HKA (3386).
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Spanish National Research Council (CSIC) Reports Findings in Ma- chine Learning [A kernel-based machine learning potential and quan- tum vibrational state analysis of the cationic Ar hydride (Ar2H+)]

    21-21页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news report- ing from Madrid, Spain, by NewsRx journalists, research stated, “One of the most fascinating discoveries in recent years, in the cold and low pressure regions of the universe, was the detection of ArH and HeH species. The identification of such noble gas-containing molecules in space is the key to understanding noble gas chemistry.” Financial supporters for this research include European Cooperation in Science and Technology, Min- isterio de Ciencia e Innovacion, Universidad Nacional de Colombia, Direccion General de Universidades e Investigacion.
      原文链接:
    • NETL
    • NSTL
    • Royal Soc Chemistry

    Studies from Carnegie Mellon University Add New Findings in the Area of Androids (The Importance of Being Humanoid)

    22-22页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Robotics - Androids. According to news reporting from Kigali, Rwanda, by NewsRx journalists, research stated, “A humanoid robot is a particular form of embodied agent. The form that an agent takes has a major impact on how that agent interacts with its environment and how it develops an understanding of that environment through its interactions.” The news correspondents obtained a quote from the research from Carnegie Mellon University, “In this paper, we explore the importance of humanoid embodiment and we argue that humanoids occupy a special niche in the spectrum of robot forms. In doing so, we highlight the implications for the way a humanoid robot can interact with its environment, including humans, for the manner in which humans interact with humanoid robots, and for a humanoid robot’s capacity to develop cognitive abilities. We also consider the degree to which humanoid robots should approximate humans, addressing robot morphology, appearance, and movement. We emphasize the dual role of humanoid robots as engineering artifacts that can provide services for humans, and as platforms for scientific enquiry into the nature of human cognition.”
      原文链接:
    • NETL
    • NSTL
    • World Scientific

    Mohammed Ⅵ Polytechnic University (UM6P) Researchers Update Current Data on Machine Learning (Are raw satellite bands and machine learning all you need to retrieve actual evapotranspiration?)

    22-23页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligence is the subject of a new report. According to news reporting originating from Mohammed Ⅵ Polytechnic University (UM6P) by NewsRx correspondents, research stated, “Accurately estimating latent heat flux (LE) is crucial for achieving efficiency in irrigation. It is a fundamental component in determining the actual evapotranspiration (ETa), which in turn, quantifies the amount of water lost that needs to be adequately compensated through irrigation.”
      原文链接:
    • NETL
    • NSTL

    Findings from Xi'an Jiaotong University Yields New Data on Machine Learning (Predictive Control of Reactor Network Model Using Machine Learning for Hydrogen-rich Gas and Biochar Polygeneration By Biomass Waste Gasification In Supercritical ...)

    23-24页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting origi- nating in Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “Supercritical water gasification (SCWG) technology can convert biomass into hydrogen rich gas and biochar. Fluidized bed reactor is promising for the industrialization of this technology, and the reactor dynamic perfor-mance study is of great significance for its scaling up.” Funders for this research include National Natural Science Foundation of China (NSFC), Shaanxi Science & Technology Co-ordination & Innovation Project, Youth Innovation Team of Shaanxi Universities, NUS Start-up.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Data on Sepsis Reported by Fei Ye and Colleagues (A customised down-sampling machine learning approach for sepsis prediction)

    24-25页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Blood Diseases and Conditions - Sepsis is the subject of a report. According to news reporting out of Eindhoven, Netherlands, by NewsRx editors, research stated, “Sepsis is a life-threatening condition in the ICU and requires treatment in time. Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing alarms could worsen alarm fatigue and desensitisation in ICUs, potentially compromising patient safety.” Our news journalists obtained a quote from the research, “In this retrospective study, we aim to develop an accurate, robust, and readily deployable method in ICUs, only based on the vital signs and laboratory tests. Our method consists of a customised down-sampling process and a specific dynamic sliding window and XGBoost to offer sepsis prediction. The down-sampling process was applied to the retrospective data for training the XGBoost model. During the testing stage, the dynamic sliding window and the trained XGBoost were used to predict sepsis on the retrospective datasets, PhysioNet and FHC. With the filtered data from PhysioNet, our method achieved 80.74% accuracy (77.90% sensitivity and 84.42% specificity) and 83.95% (84.82% sensitivity and 82.00% specificity) on the test set of PhysioNet-A and PhysioNet-B, respectively. The AUC score was 0.89 for both datasets. On the FHC dataset, our method achieved 92.38% accuracy (88.37% sensitivity and 95.16% specificity) and 0.98 AUC score on the test set of FHC. Our results indicate that the down-sampling process and the dynamic sliding window with XGBoost brought robust and accurate performance to give sepsis prediction under various hospital settings.”
      原文链接:
    • NETL
    • NSTL

    New Robotics Study Results from University of Grenoble-Alpes Described (Variational Meta Reinforcement Learning for Social Robotics)

    25-26页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Robotics. According to news originating from Montbonnot St. Martin, France, by NewsRx correspondents, research stated, “With the increasing presence of robots in our everyday environments, improving their social skills is of utmost importance. Nonetheless, social robotics still faces many challenges.” Funders for this research include Agence Nationale de la Recherche (ANR), H2020 SPRING, Agence Nationale de la Recherche (ANR).
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Findings from University of Bath Has Provided New Data on Robotics (Leveraging In-store Technology and Ai: Increasing Cus- tomer and Employee Efficiency and Enhancing Their Experiences)

    26-27页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics are presented in a new report. According to news originating from Bath, United Kingdom, by NewsRx correspondents, research stated, “Due to digital innovations, retailing is undergoing radical changes. Scholars have proposed frameworks to address outcomes of im- plementing technology e.g., an increased customer experience, efficiency gains, consumer or employee acceptance.” Our news journalists obtained a quote from the research from the University of Bath, “Existing frame- works concentrate primarily on the consumer perspective, focus on specific technologies (e.g., AI) and covering the customer journey. In contrast, this paper also focuses on the employee perspective, and how technology influences the employee journey. Since the convenience offered by online retailers puts offline retailers under pressure, this research focuses on in-store technology. Based on a comprehensive review of managerial and academic literature and expert interviews, we propose a framework covering customers and employees, and technology’s function (increasing efficiency or experience), as also including more tra- ditional and newer technologies, such as robots and AI. We identify and showcase technologies increasing efficiency for customers (quadrant 1, e.g., checkout options or autonomous stores) or for employees (quad- rant 2, e.g., in-store robots), and enhancing the experience for customers (quadrant 3, e.g., retailer apps or communication) or for employees (quadrant 4, e.g., exoskeletons or smart wearables).”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    First Affiliated Hospital of Sun Yat-Sen University Reports Findings in Asthma (Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and ...)

    27-28页
    查看更多>>摘要：2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Lung Diseases and Conditions - Asthma is the subject of a report. According to news originating from Guangdong, People’s Republic of China, by NewsRx correspondents, research stated, “Asthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood.” Our news journalists obtained a quote from the research from the First Affiliated Hospital of Sun Yat- Sen University, “This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease. The gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma. A total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631-0.904, p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = - 0.3268, p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = - 0.3472, p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960, p = 0.0071) and FEV/forced vital capacity (r = 0.3213, p = 0.0314) in asthmatic patients.” According to the news editors, the research concluded: “Decreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Studies Conducted at Autonomous University Barcelona on Ma- chine Learning Recently Reported (Deep Machine Learning for Me- teor Monitoring: Advances With Transfer Learning and Gradient- weighted Class Activation Mapping)

    28-29页
    查看更多>>摘要：2024 FEB 27 (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 from Catalonia, Spain, by NewsRx journalists, research stated, “In recent decades, the use of optical detection systems for meteor studies has increased dramatically, resulting in huge amounts of data being analyzed. Automated meteor detection tools are essential for studying the continuous meteoroid incoming flux, recovering fresh meteorites, and achieving a better understanding of our Solar System.” Funders for this research include Spanish Government, MCIN/AEI, Spanish Government, Program Unidad de Excelencia Maria de Maeztu.
      原文链接:
    • NETL
    • NSTL
    • Elsevier