查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Italian Institute of Technology) in collaboration with the University of Freiburg have developed a biohybrid robot, which consist s of a flour-based capsule created using 3D microfabrication techniques, and two natural appendages from oat fruit capable of moving in response to air humidity . Named HybriBot, this new device can accommodate natural seeds from different p lants, serving as a biodegradable vector for reforestation. The research group h as already conducted positive tests with tomato, chicory, and willow herb seeds, the latter being one of bees' favorite flowers, from which the plants germinate d. A patent application has been filed for the invention. HybriBot has been described in a paper recently published in the international s cientific journal Advanced Materials; it is born within the framework of the Eur opean project i-Seed coordinated by Barbara Mazzolai, Associate Director for Rob otics at the IIT, and the innovation ecosystem RAISE (Robotics and AI for Socio- economic Empowerment) funded by the National Recovery and Resilience Plan in Ita ly.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on artificial intelligence is now ava ilable. According to news originating from Jazan, Saudi Arabia, by NewsRx corres pondents, research stated, "The nuclear reactor control unit employs human facto r engineering to ensure efficient operations and prevent any catastrophic incide nts. This sector is of utmost importance for public safety."Funders for this research include Jazan University. Our news journalists obtained a quote from the research from Jazan University: " This study focuses on simulated analysis of specific areas of nuclear reactor co ntrol, specifically administration, operation, and maintenance, using artificial intelligence software. The investigation yields effective artificial intelligen ce algorithms that capture the essential and non-essential components of numerou s parameters to be monitored in nuclear reactor control. The investigation furth er examines the interdependencies between various parameters and validates the s tatistical outputs of the model through attribution analysis. Furthermore, a Mul tivariant ANOVA analysis is conducted to identify the interactive plots and mean plots of crucial parameters interactions. The artificial intelligence algorithm s demonstrate the correlation between the number of vacant staff jobs and both t he frequency of license event reports each year and the ratio of contract employ ees to regular employees in the administrative domain. An AI method uncovers the relationships between the operator failing rate (OFR), operator processed error s (OEE), and operations at limited time frames (OLC)."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in artificial intelligence. According to news originating from Charles University b y NewsRx correspondents, research stated, "An intrinsic limitation of empirical models of the magnetopause location is a predefined magnetopause shape and assum ed functional dependences on relevant parameters."Our news reporters obtained a quote from the research from Charles University: " We overcome this limitation using a machine learning approach (artificial neural networks), allowing us to incorporate general, purely data-driven dependences. For the training and testing of the developed neural network model, a data set o f about 15,000 magnetopause crossings identified in the THEMIS A-E, Magion 4, Ge otail, and Interball-1 satellite data in the subsolar region is used. A cylindri cal symmetry around the direction of the impinging solar wind is assumed, and so lar wind dynamic pressure, interplanetary magnetic field magnitude, cone angle, clock angle, tilt angle, and corrected Dst index are considered as parameters. T he effect of these parameters on the magnetopause location is revealed. The perf ormance of the developed model is compared with other empirical magnetopause mod els. Finally, we demonstrate and discuss the inaccuracy of magnetopause models d ue to the inaccurate information about the impinging solar wind parameters based on measurements near the L1 point."
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 artificial intelligence is now available. According to news reporting originating from Bergen, Norway, by NewsRx correspondents, research stated, "This paper explores machine learning methods for exercise-induced laryngeal obstruction (EILO) diagnostics."Our news journalists obtained a quote from the research from Western Norway Univ ersity of Applied Sciences: "Traditional diagnostic approaches like CLE scoring face subjectivity, limiting precise objective assessments. Machine learning is i ntroduced as a theoretical solution to potentially overcome these limitations an d improve diagnostic precision. A narrative review was conducted to explore the integration of machine learning techniques in the diagnostics of EILO. Three mac hine learning methods for the segmentation of laryngeal images were discovered: fully convolutional network, Mask R-CNN, and 3D VOSNet. Our findings reveal that the integration of machine learning with EILO diagnostics remains a largely unt apped research domain, providing significant room for further exploration."
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 originating from Calgary , Canada, by NewsRx correspondents, research stated, "For high-precision positio ning applications, various GNSS errors need to be mitigated, including the tropo spheric error, which remains a significant error source as it can reach up to a few meters."Financial supporters for this research include Natural Sciences And Engineering Research Council of Canada.
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 Machine Learning is now available. According to news reporting originating in Chongqing, People's Repub lic of China, by NewsRx journalists, research stated, "Ball-sealer diversion has been proven to be an effective and economical way to increase fractures and fra cturing volume in multistage hydraulic fracturing and matrix acidizing treatment s. However, designing and implementing a successful ball-sealer diversion treatm ent is still challenging."Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Digestive System Disea ses and Conditions - Crohn's Disease is the subject of a report. According to ne ws originating from Chengdu, People's Republic of China, by NewsRx correspondent s, research stated, "The simplified endoscopic score of Crohn's disease (SES-CD) is the gold standard for quantitatively evaluating Crohn's disease (CD) activit y but is invasive. This study aimed to develop and validate a machine learning ( ML) model based on dual-energy CT enterography (DECTE) to noninvasively evaluate CD activity."
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 report. According to news originating from Santander, Spain, by NewsRx co rrespondents, research stated, "The increasing number of robotic urological proc edures observed in recent years highlights the need to expand training opportuni ties in robotic surgery. Our objective is to investigate the state of robotic tr aining during urology residency in Spain in order to identify significant defici encies."Our news journalists obtained a quote from the research from Hospital Universita rio Marques de Valdecilla, "A 20-item online survey was conducted among urology residents in Spain who were registered in the database of the Residents and Youn g Urologists Group of the Spanish Association of Urology. The survey assessed su bjective opinions, institutional aspects, training resources, and experience reg arding robotic surgery. A total of 455 email invitations were sent throughout th e year 2021. Descriptive analysis of the responses was performed. The participat ion rate reached 30%, with a total of 135 residents. 52% of respondents lacked access to a robotic system in their institution, of which only 48% could compensate for this deficiency through external rot ations. Among those with access to a robotic system, 25% and 23% reported having access to theoretical and practical training, respectively. The existence of a formal training program was low (13%). 85% of the respondents considered robotic surgery training in Spain to be deficient. "
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 originating from the Mor occan Foundation for Advanced Science by NewsRx correspondents, research stated, "Energy management systems allow the Smart Grids industry to track, improve, an d regulate energy use."Financial supporters for this research include Institut De Recherche En Energie Solaire Et 'energies Nouvelles; The Portuguese National Funds Through Fct, Funda ccao Para A Ciencia E A Tecnologia. The news correspondents obtained a quote from the research from Moroccan Foundat ion for Advanced Science: "Particularly, demand-side management is regarded as a crucial component of the entire Smart Grids system. Therefore, by aligning util ity offers with customer demand, anticipating future energy demands is essential for regulating consumption. An updated examination of several forecasting techn iques for projecting energy short-term load forecasts is provided in this articl e. Each class of algorithms, including statistical techniques, Machine Learning, Deep Learning, and hybrid combinations, are comparatively evaluated and critica lly analyzed, based on three real consumption datasets from Spain, Germany, and the United States of America. To increase the size of tiny training datasets, th is paper also proposes a data augmentation technique based on Generative Adversa rial Networks. The results show that the Deep Learning-hybrid model is more accu rate than traditional statistical methods and basic Machine Learning procedures. "
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Henan, Peopl e's Republic of China, by NewsRx correspondents, research stated, "The (re)hemor rhage in patients with sporadic cerebral cavernous malformations (CCM) was the p rimary aim for CCM management. However, accurately identifying the potential (re )hemorrhage among sporadic CCM patients in advance remains a challenge."Financial support for this research came from Kaifeng Science and Technology Dev elopment Plan Project, CN.
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