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 originating from Xianning, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Lonicerae japonicae flos (LJF) and Lonicerae flos (LF) are traditional Chinese herbs that are common ly used and widely known for their medicinal properties and edibility. Although they may have a similar appearance and vary slightly in chemical composition, th eir effectiveness as medicine and their use in clinical settings vary significan tly, making them unsuitable for substitution.” Financial supporters for this research include Young and Middle-Aged Talent Proj ect of Hubei Provincial Department of Education, Xianning Science and Technology Plan Project, Hubei University of Science and Technology Cultivation Project.
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 Ma chine Learning. According to news originating from Bangi, Malaysia, by NewsRx co rrespondents, research stated, “This article presents the results of our investi gation into a machine learning (ML) method for 6G MIMO antenna performance impro vement in the THz band. Regarding the lowest frequency, the MIMO antenna is deve loped on a polyimide substrate with dimensions of 0.614 lambda 0 in length and 0 .614 lambda 0 in width.” Financial support for this research came from King Saud University.
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 Bydgoszcz University o f Science and Technology by NewsRx editors, research stated, “The main challenge s when managing a fleet of unmanned aerial vehicles are to ensure the relative s tability of its formation and to minimise disorganisation, specifically when und ergoing an intrusion.” The news editors obtained a quote from the research from Bydgoszcz University of Science and Technology: “When planning the mission it is beneficial for the ope rator to set the parameters of the formation to balance the needs of the mission with the disorganisation that an intruder may cause. The model developed in thi s research predicts the anticipated disturbance as a function of the parameters of the formation. The effectiveness of six machine learning methods are compared with a previously established baseline, using data obtained from simulations. C atBoost (categorical boosting) delivered the best results, with an $ $R∧2$$ R 2 (coefficie nt of determination) value of 83.3%, representing an improvement of 80 % over the baseline.”
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 reporting out of Reduit, Mauritius, b y NewsRx editors, research stated, “This study sheds light on the determinants o f consumers’ adoption of artificial intelligence-driven drone food delivery serv ice (AI-driven DFDS) using a mixed-methods approach. Interviews with hospitality industry professionals revealed several drivers and inhibitors of AI-driven DFD S adoption.” Our news journalists obtained a quote from the research from the University of M auritius, “Using these findings, we developed a theoretical model AI-driven DFDS adoption based on the premise of the behavioral reasoning theory and innovation resistance theory. The model was tested using data collected from 1240 consumer s. The results suggest that drones’ relative advantage, perceived ubiquity, soci al influence, and green image positively influence attitudes and adoption. Risk, usage, and experience barriers have an adverse influence on attitudes and adopt ion. Consumers’ openness to new technology has a positive influence on ‘reasons for’ using AI-driven DFDS. The research makes an important theoretical contribut ion to research on the adoption of AI-driven DFDS.”
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 originating from Yamaguchi, Japan, by NewsRx correspon dents, research stated, “The controlled actuation of hydraulic and pneumatic act uators has unveiled fresh and thrilling opportunities for designing mobile robot s with adaptable structures.” The news editors obtained a quote from the research from Yamaguchi University: “ Previously reported rolling robots, which were powered by fluidic systems, often relied on complex principles, cumbersome pump and valve systems, and intricate control strategies, limiting their applicability in other fields. In this invest igation, we employed a distinct category of functional fluid identified as Elect rohydrodynamic (EHD) fluid, serving as the pivotal element within the ring-shape d actuator. A short stream of functional fluid is placed within a fluidic channe l and is then actuated by applying a direct current voltage aiming at shifting t he center of mass of the robot and finally pushed the actuator to roll. We desig ned a ring-shaped fluidic robot, manufactured it using digital machining methods , and evaluated the robot’s characteristics.”
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 out of Shanghai, People’s Republi c of China, by NewsRx editors, research stated, “Millions of lives are lost in r oad accidents annually, underscoring the severity of traffic incidents.” Financial supporters for this research include Article Processing Charge (Apc) T hrough Prince Sultan University, Riyadh, Saudi Arabia.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Cirrhosis is the subje ct of a report. According to news reporting originating from Tianjin, People’s R epublic of China, by NewsRx correspondents, research stated, “We sought to devel op and validate a machine learning (ML) model for predicting multidimensional fr ailty based on clinical and laboratory data. Moreover, an explainable ML model u tilizing SHapley Additive exPlanations (SHAP) was constructed.” Our news editors obtained a quote from the research from the Department of Geria trics, “This study enrolled 622 patients hospitalized due to decompensating epis odes at a tertiary hospital. The cohort data were randomly divided into training and test sets. External validation was carried out using 131 patients from othe r tertiary hospitals. The frail phenotype was defined according to a self-report ed questionnaire (Frailty Index). The area under the receiver operating characte ristics curve was adopted to compare the performance of five ML models. The impo rtance of the features and interpretation of the ML models were determined using the SHAP method. The proportions of cirrhotic patients with nonfrail and frail phenotypes in combined training and test sets were 87.8% and 12.2% , respectively, while they were 88.5 % and 11.5% in t he external validation dataset. Five ML algorithms were used, and the random for est (RF) model exhibited substantially predictive performance. Regarding the ext ernal validation, the RF algorithm outperformed other ML models. Moreover, the S HAP method demonstrated that neutrophil-tolymphocyte ratio, age, lymphocyte-to- monocyte ratio, ascites, and albumin served as the most important predictors for frailty. At the patient level, the SHAP force plot and decision plot exhibited a clinically meaningful explanation of the RF algorithm. We constructed an ML mo del (RF) providing accurate prediction of frail phenotype in decompensated cirrh osis.”
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 Nanjing , People’s Republic of China, by NewsRx editors, the research stated, “This stud y utilizes six years of hourly meteorological data from seven observation statio ns in the Beibu Gulf- Qinzhou (QZ), Fangcheng (FC), Beihai (BH), Fangchenggang (F CG), Dongxing (DX), Weizhou Island (WZ), and Hepu (HP)-over the period from 2016 to 2021.” Financial supporters for this research include Guangxi Transportation (Railway) Intelligent Integrated Service Technology; Guangxi Key Research And Development Program; National Natural Science Foundation of China.
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 reporting originating in Beijing, People’s Re public of China, by NewsRx journalists, research stated, “More and more robots a re required to adsorb or crawl on the 3D curved surface in order to assist human s in some dangerous or tedious tasks. Existing methods on curved surface are mer ely able to plan in 2.5D environment at best, limiting the applications of the r obots.” Funders for this research include National Natural Science Foundation of China ( NSFC), Beijing Natural Science Foundation. The news reporters obtained a quote from the research from the Beijing Institute of Technology, “In this letter, we propose an effective trajectory generation m ethod on general 3D curved surface. We utilize a pose projection strategy to eli minate terrain contact constraint such that it allows to address the 3D curved s urface path planning problem with current optimization solvers. We develop a rat ional terrain assessment approach based on the local terrain geometry, enabling a direct correlation with the robotic hardware properties. The smoothness and sa fety of the trajectory on 3D curved surface are significantly improved by optimi zing the projected state of the robots. We thoroughly validate our method in var ious scenarios.”
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 reporting out of Macau, People’s Repu blic of China, by NewsRx editors, research stated, “This work introduces advance d computational techniques for modeling the time evolution of compact binary sys tems using machine learning.” Financial supporters for this research include Most | National Natural Science F oundation of China; Moe | Fundamental Research Funds For The Central Universitie s; Sun Yat-sen University.
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