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 reporting originating from Suzhou, People’s Republic o f China, by NewsRx correspondents, research stated, “This paper investigates the issue of observer-based dual-dynamic event-triggered scheme into networked cont rol systems, focusing on its application to motion robots. Firstly, it establish es a mathematical model of the motion robot system based on Newtonian mechanics. ” Our news editors obtained a quote from the research from the Suzhou University o f Science and Technology, “Secondly, it introduces a dynamic event-triggering me chanism coupled with observer design to minimize data transmission and enhance c ommunication efficiency. Thirdly, it implements a second dynamic event-triggerin g protocol for controller design, ensuring a positive lower bound for triggering event intervals, thus avoiding Zeno behavior. Fourthly, it constructs a Lyapuno v function with internal dynamic variables for stability analysis using linear m atrix inequalities.”
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 reporting out of Chengdu, People’s Republic of China, by NewsRx editors, research stated, “In welding tasks, the repeated positioning precision of robots can generally reach the micron level, but the data of each a xis during each operation may vary.” Funders for this research include The Technology Development Project of Swjtu. Our news editors obtained a quote from the research from Southwest Jiaotong Univ ersity: “There may even be out-of-control situations where the robot does not ru n according to the set welding trajectory, which may cause the robot and equipme nt to collide and be damaged. Therefore, a real-time judgment method for the wel ding robot trajectory is proposed. Firstly, multiple sets of axis data are obtai ned by running the welding robot, and the phase of the data is aligned by using a proposed algorithm, and then the Kendall correlation coefficient is used to id entify and remove weak axis data. Secondly, the mean of multiple sets of axis da ta with strong correlation is calculated as the standard trajectory, and the tra jectory threshold of the robot is set using the m ± ns method based on the traje ctory deviation judgment sensitivity. Finally, the absolute difference between t he real-time axis trajectory and the standard trajectory is used to determine th e deviation of the running trajectory. When the deviation reaches the threshold, a forewarning starts.”
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 Dhahran, Saudi Arabia, by N ewsRx editors, the research stated, “Drilling through shale formations can be ex pensive and time-consuming due to the instability of the wellbore. Further, ther e is a need to develop inhibitors that are environmentally friendly.” Our news reporters obtained a quote from the research from King Fahd University of Petroleum and Minerals: “Our study discovered a cost-effective solution to th is problem using Gum Arabic (ArG). We evaluated the inhibition potential of an A rG clay swelling inhibitor and fluid loss controller in water-based mud (WBM) by conducting a linear swelling test, capillary suction timer test, and zeta poten tial, fluid loss, and rheology tests. Our results displayed a significant reduct ion in linear swelling of bentonite clay (Na-Ben) by up to 36.1% a t a concentration of 1.0 wt. % ArG. The capillary suction timer (C ST) showed that capillary suction time also increased with the increase in the c oncentration of ArG, which indicates the fluid-loss-controlling potential of ArG . Adding ArG to the drilling mud prominently decreased fluid loss by up to 50% . Further, ArG reduced the shear stresses of the base mud, showing its inhibitio n and friction-reducing effect. These findings suggest that ArG is a strong cand idate for an alternate green swelling inhibitor and fluid loss controller in WBM .”
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 reporting out of Jiangsu, People’s Republic of China, by NewsRx editors, research stated, “Supernumerary robotic limbs (SRLs) have gr eat potentials to assist human in daily activities and industrial manufacturing by providing extra limbs. However, current SRLs have heavy and rigid structures that may threaten the operator safety; moreover, their limited degrees of freedo m and movement modes are not suitable for complicated tasks.” Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Natural Science Foun dation of Jiangsu Province, State Key Laboratory of Robotics and Systems (HIT), Fundamental Research Funds for the Central Universities, Nanjing Overseas Schola rs Science and Technology Innovation Project, Scientific Research Foundation of Nanjing University of Aeronautics and Astronautics.
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 reporting out of Maceio, Brazil, by NewsRx edi tors, research stated, “Protected areas (PAs) play a vital role in the conservat ion of natural and cultural heritage while supporting local livelihoods. However , in Brazil, where limited resources and poor effectiveness lead to negative sen timents and are leveraged as criticism towards PAs, it is necessary to better co mprehend public perceptions of Brazilian PAs and identify the key factors contri buting to negative sentiments.” Funders for this research include Fundo Brasileiro para a Biodiversidade (FUNBIO ), Instituto Humanize, Conselho Nacional de Desenvolvimento Cientifico e Tecnolo gico (CNPQ), European Union (EU), Conselho Nacional de Desenvolvimento Cientific o e Tecnologico (CNPQ), Research Council of Finland, KONE Foundation.
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 is now availab le. According to news reporting out of Beijing, People’s Republic of China, by N ewsRx editors, research stated, “Medical imaging robots typically use technologi es, such as X-ray, magnetic resonance imaging (MRI), and computed tomography (CT ), to generate images of the human body interior. These generated images are com plex and contain a large amount of noise and interference, which requires high-p recision and real -time fast image analysis algorithms to extract significant in formation, including tumour area, tumour location, organ and tissue, and blood v essel information.” Our news journalists obtained a quote from the research from Beijing Jiaotong Un iversity, “This paper proposes a novel lightweight neural network to perform tum our segmentation in brain MRI images, which could realize the high-accuracy and fast execution. To meet the real -time requirements, a lightweight module based on channel attention mechanism is presented, which constitutes an encoder-deco d er architecture for the segmentation task. To enrich the feature map information , this paper designs a spatial attention mechanism to concatenate the output fea ture maps of the encoder and decoder correspondingly, which could realize the be tter fusion of high-level and low-level semantic features extracted by the netwo rk. The comparison experiments and ablation studies are conducted to improve the effectiveness of the proposed model, which could represent a higher performance .”
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 new report. According to news originating from the Institute of Mechanica l Engineering by NewsRx editors, the research stated, “A method of trajectory pl anning with regards to joint velocity and acceleration constraints for industria l 6 DOF manipulator is presented.” The news journalists obtained a quote from the research from Institute of Mechan ical Engineering: “The task of the robot is to move to specified location in the workspace passing through intermediate waypoints. The proposed algorithm can be used to plan the task of the robot by autonomous systems in smart factories eli minating human participation in the robot programing process. Opposite to simila r approaches it does not assume the type of function describing the motion of th e robot. The trajectories generated using the proposed approach are smooth and p rovide smooth velocities and continuous joint accelerations. The motion is plann ed in such a way to fulfill joint velocity and acceleration constraints. Fulfill ment of velocity limitations is accomplished by perturbing the manipulator motio n close to velocity limits.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Machine Learning have been prese nted. According to news originating from Shanghai, People’s Republic of China, b y NewsRx correspondents, research stated, “Accurate numerical analysis in geotec hnical engineering heavily relies on the constitutive model and its parameters. The advanced constitutive model can describe the complex mechanical behaviors of soil that may involve a number of parameters.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Science & Technology Commission of Shanghai Mu nicipality (STCSM). Our news journalists obtained a quote from the research from Shanghai Jiao Tong University, “However, determining the values of constitutive parameters always r elies on manual trial-and-error, which can be a time-consuming process and not c onducive to widespread application. This paper presents an identification method that combines machine learning with search algorithm based on the laboratory an d in-situ testing. Initially, the sensitivity of constitutive parameters was ana lyzed by investigating the effects of variations in soil overconsolidation and s tructural parameters on the results of triaxial and pressuremeter tests. Subsequ ently, the initial state parameter values and material control parameter ranges of the soil can be identified from the triaxial tests, this is achieved by using the neural network model. In order to accurately determine the parameters value , the numerical model was established based on in-situ pressuremeter test, and t raversal algorithm was implemented to search for the optimal fit values within t he range of material control parameters. Finally, the proposed identification me thod was applied to layers 3 - 5 of Shanghai clay, and the inverted parameters e xhibited a good fit with the outcomes of triaxial tests and pressuremeter tests. ”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Immune System Diseases and Conditions - Allergies is the subject of a report. According to news report ing out of Guangzhou, People’s Republic of China, by NewsRx editors, research st ated, “The prevalence of pollen allergies is a pressing global issue, with proje ctions suggesting that half of the world’s population will be affected by 2050 a ccording to the estimation of the World Health Organization (WHO). Accurately fo recasting pollen allergy risks requires identifying key factors and their thresh olds for aerosol pollen.” Our news journalists obtained a quote from the research from the Guangdong Unive rsity of Technology, “To address this, we developed a technical framework combin ing advanced machine learning and SHapley Additive exPlanations (SHAP) technolog y, focusing on Beijing. By analyzing meteorological data and vegetation phenolog y, we identified the factors influencing next-day’s pollen concentration (NDP) i n Beijing and their thresholds. Our results highlight vegetation phenology data from Synthetic Aperture Radar (SAR), temperature, wind speed, and atmospheric pr essure as crucial factors in spring. In contrast, the Normalized Difference Vege tation Index (NDVI), air temperature, and wind speed are significant in autumn. Leveraging SHAP technology, we established season-specific thresholds for these factors. Our study not only confirms previous research but also unveils seasonal variations in the relationship between radar-derived vegetation phenology data and NDP. Additionally, we observe seasonal fluctuations in the influence pattern s and threshold values of daily air temperatures on NDP.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Lung Cancer is the subject of a report. According to news originating from Hangzhou, People ’s Republic of China, by NewsRx correspondents, research stated, “This study aim ed to develop models for predicting prolonged postoperative length of stay (PPOL OS) in lung cancer patients undergoing video-assisted thoracoscopic surgery (VAT S) by utilizing machine-learning techniques. These models aim to offer valuable insights for clinical decision-making.” Our news journalists obtained a quote from the research from the Department of I ndustrial Design, “This retrospective cohort study analyzed a dataset of lung ca ncer patients who underwent VATS, identifying 25 numerical features and 45 textu al features. Three classification machine-learning models were developed: XGBoos t, random forest, and neural network. The performance of these models was evalua ted based on accuracy (ACC) and area under the receiver operating characteristic curve, whereas the importance of variables was assessed using the feature impor tance parameter from the random forest model. Of the 6767 lung cancer patients, 1481 patients (21.9%) experienced a postoperative length of stay of > 4 days. The majority were male (4111, 60.8% ), married (6246, 92.3%), and diagnosed with adenocarcinoma (4145, 61.3%). The Random Forest classifier exhibited superior prediction performance with an area under the curve (AUC) of 0.792 and ACC of 0.804. The ca libration plot revealed that all three classifiers were in close alignment with the ideal calibration line, indicating high calibration reliability. The five mo st critical features identified were the following: surgical duration (0.116), a ge (0.066), creatinine (0.062), hemoglobin (0.058), and total protein (0.054). T his study developed and evaluated three machine-learning models for predicting P POLOS in lung cancer patients undergoing VATS. The findings revealed that the Ra ndom Forest model is most accurately predicting the PPOLOS.”
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