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 Qinhuangdao, People's Republic of Chi na, by NewsRx correspondents, research stated, "This brief is concerned with the prescribed-time tracking control problem for mobile robot systems subject to pe rformance constraints. In contrast to existing results on mobile robotic systems , which fail to achieve precise tracking, this brief focuses on achieving error- free tracking control within a specific time interval, which is independent of s ystem initial conditions as well as control parameters." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from Yanshan University, "Then, a novel state transformation is proposed to achieve global performance c onstrains control. Additionally, based on the Lyapunov's theory, it is proved th at the designed controller can make system states accurately track the given sig nal within a prescribed-time interval, while guaranteeing the boundedness of clo se-loop systems." According to the news editors, the research concluded: "Finally, the effectivene ss of proposed control algorithm is verified by a simulation example." This research has been peer-reviewed.
查看更多>>摘要：The news correspondents obtained a quote from the research from the Grenoble Sch ool of Management, "The lack of transparency related to AI algorithms and their categorization methods make practical insights into effective management of the risks associated to their utilization of crucial importance. We address these is sues through two field tests aimed at mitigating biases in online science, techn ology, engineering, and mathematics (STEM) education-related ads targeting teena gers. We conducted online ad campaigns involving gender-unspecific, women-specif ic, and gender-neutral ads targeted at young social network users. Our findings show that inclusion in the ad of a gender-oriented message tends to alleviate al gorithmic gender bias but also reduced overall ad visibility." According to the news reporters, the research concluded: "Our research shows als o that text length has a significant impact on ad visibility, and that gender-or iented messages influence the display of the ad based on gender." This research has been peer-reviewed.
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 reporting originating in Ottawa, Canada, by New sRx journalists, research stated, "We develop a fast, recursive, and parameteriz ation-free formulation for the dynamics of soft robots. Such systems are modelle d as multi -body systems, composed of rigid and flexible bodies connected with d iscrete joints." Funders for this research include CGIAR, Canada Research Chairs. The news reporters obtained a quote from the research from Carleton University, "We couple the recursive Newton-Euler equation for rigid bodies and the Partial Differential Equations (PDEs) on the Special Euclidean group SE(3) modelling dyn amic Cosserat rods to capture the system's dynamics. Our proposed inverse dynami cs recursively determines the system's response and the joint torques, given a j oint-space trajectory; while subject to known joint torques and external forces, the forward dynamics determines the system's motion. Unlike rigid systems, the inclusion of flexible bodies necessitates solving a coupled set of PDEs with sep arated Boundary Conditions (BCs). We develop a shootingmethod-based BC solver to move BCs to one point and a numerical framework based on a finite difference me thod to spatially integrate these equations using a geometrically exact integrat or on SE(3)."
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 and Machine L earning is the subject of a report. According to news reporting from Surabaya, I ndonesia, by NewsRx journalists, research stated, "Variations in muscular contra ction are known to significantly impact the quality of the generated EMG signal and the output decision of a proposed classifier. This is an issue when the clas sifier is further implemented in prosthetic hand design." The news correspondents obtained a quote from the research, "Therefore, this stu dy aims to develop a deep learning classifier to improve the classification of h and motion gestures and investigate the effect of force variations on their accu racy on amputees. The contribution of this study showed that the resulting deep learning architecture based on DNN (deep neural network) could recognize the six gestures and robust against different force levels (18 combinations). Additiona lly, this study recommended several channels that most contribute to the classif ier's accuracy. Also, the selected time domain features were used for a classifi er to recognize 18 combinations of EMG signal patterns (6 gestures and three for ces). The average accuracy of the proposed method (DNN) was also observed at 92. 0 ± 6.1 %. Moreover, several other classifiers were used as compari sons, such as support vector machine (SVM), decision tree (DT), K-nearest neighb ors, and Linear Discriminant Analysis (LDA). The increase in the mean accuracy o f the proposed method compared to other conventional classifiers (SVM, DT, KNN, and LDA), was 17.86 %." According to the news reporters, the research concluded: "Also, the study's impl ication stated that the proposed method should be applied to developing prosthet ic hands for amputees that recognize multi-force gestures."
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 from Khulna University by New sRx journalists, research stated, "This research aims to assess the rheological and mechanical characteristics of Self-compacting concrete (SCC) incorporating w aste tire rubber aggregates (WRTA) as an interim substitute for coarse aggregate s. However, the standard experimental modeling approach has significant obstacle s when it comes to overcoming the nonlinearity and environmental susceptibility of concrete parts." Our news editors obtained a quote from the research from Khulna University: "The refore, linear regression (LR) and extreme gradient boosting (XGBoost) were used as two standard single machine learning (ML) models to predict the aforemention ed rubberized SCC features. In this study, conventional coarse aggregates were s upplanted with WRTA at 0%, 5%, 10%, and 2 0% to uncover the optimal proportion of coarse aggregates substitu ting rubber. To find the optimum amount of WRTA to use as a substitute, the stud y follows the impacts of rubber on the self-compacting rubberized concrete's (SC RC) rheological and mechanical characteristics. The consequences on fresh proper ties were investigated by the slump flow, J-ring, and V-funnel tests, while comp ressive and splitting tensile strengths tests were conducted to assess mechanica l properties. Increasing WRTA test outputs indicated a deterioration in workabil ity and hardened qualities. While a 10% swapping ratio is deemed f easible for producing SCRC, optimal results were achieved by reducing environmen tal impacts and efficiently managing a significant volume of rubber tire waste w ith a 5% substitution of rubber within the coarse aggregates. The research findings indicated a noticeable decrease in fresh properties as the WRT A content increased."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news reporting from Ningbo, People's Republic of China, by NewsRx journalists, research stated, "A highly selective and sensitive fluorescence sensor, using the decision tree (DT) machine learning , was successfully fabricated for the quantitative detection of Cu2+, which is b ased on near-infrared carbonized polymer dots (r-CPDs). Using o-phenylenediamine and 1,3,5-benzene tricarboxylic acid as raw materials first to synthesize the r -CPDs (quantum yield of 32.9%), which pyrrole NH ring can specifica lly form metal chelates with Cu2+ hiding the electron leap result in the fluores cence burst, by a one-step hydrothermal synthesis method." Funders for this research include Public Welfare Research Project of Ningbo, Nin gbo Science and Technology Bureau, Pioneer and Leading Goose R & D Program of Zhejiang. The news correspondents obtained a quote from the research from Ningbo Universit y, "Furthermore, the fluorescence sensor based on the r-CPDs was fabricated for ultra-sensitively detect Cu2+ in the range of 0.5-80.0 nM (R2 =0.9986) in aqueou s environments and aquatic products with relative standard deviation (RSD) below 4.4% and a limit of detection (LOD) of 0.24 nM. Combined with the machine learning algorithm model, the r-CPDs fluorescence color changes accompa nied by different Cu2+ concentrations were classified. A self-developed smartpho ne application equipped with 3D printing technology to prepare portable cartridg es successfully applied to rapid real-time detection of trace Cu2+ in various pr actical samples. The experimental results show that the method has not only conv enient for calculating but also accurate."
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 Machine Learning. According to news reporting originating in Ottawa, Canada, by NewsRx journalists, research stated, "Coring or destructive testing is typically the de fault choice for the evaluation of concrete compressive strength in reinforced c oncrete (RC) structures. However, it can be impractical and/ or not representati ve of all areas of interest in a structure." Funders for this research include FPrimeC Solutions Inc., Mitacs. The news reporters obtained a quote from the research from the University of Ott awa, "While various non-destructive test (NDT) methods can be correlated to conc rete strength, the accuracy of any single NDT used for this purpose is generally low. The SonReb method, which combines ultrasonic pulse velocity readings and r ebound number, has been shown to have improved accuracy over single test methods . However, empirical SonReb equations, calibrated to specific datasets using reg ression analysis, cannot necessarily be applied to concrete from other sources w ithout introducing significant errors. This study presents a practical machine l earning (ML) model for on-site concrete strength prediction. A large database wa s created from available literature along with new experimental test data. Three different ML models based on an adaptive neuro-fuzzy inference system (ANFIS) w ere developed along with a graphical user interface application to facilitate it s use in the field. In addition to the ML models, linear and non-linear regressi on analyses were also conducted and compared with existing equations in the lite rature. The accuracy of each model was subsequently validated against core sampl es extracted from a reinforced concrete slab. The results show that the proposed ML model and non-linear regression provided the most reliable predictions of co ncrete strength of the validation specimen with a mean absolute error of less th an 10 % compared with twelve core samples."
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 originating from Beijing, People's Republic o f China, by NewsRx correspondents, research stated, "An impedance control scheme is proposed for a Stewart-structure-based wheel-legged robotic system to streng then the dynamic attitude adjustment stability in wheel motion. The wheel-leg, w hich is driven by electrical cylinders in the Stewart structure, is analyzed in kinematics and dynamics." Financial supporters for this research include National Key Research and Develop ment Project of China, National Natural Science Foundation of China (NSFC), Chin a Postdoctoral Science Foundation. Our news journalists obtained a quote from the research from the Beijing Institu te of Technology, "The rotation in the axial direction of every electric cylinde r is calculated to improve the accuracy of the kinematic model. To fulfill the i mpedance demands, a passive structure with 6 degrees of freedom (DOF) is modeled . The mass of the mechanism has a coupling effect on the impedance model for eac h DOF, which is a nonlinear function. As motion decoupling in the workspace has been completed for the Stewart structure, an impedance control strategy with inn er-loop position tracking is employed. An extended state observer (ESO) is desig ned to estimate the disturbances arising from the nonlinear coupling effects. Ba sed on the ESO observation outputs, an active disturbance rejection control that explicitly handles the workspace limit is designed with guaranteed practical st ability. By reducing force interaction and body vibration, the wheel-legged robo tic system keeps wheel motion stability on uneven roads."
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 in Padua, Italy, by NewsRx journ alists, research stated, "Differentially flat under-actuated robots are characte rized by more degrees of freedom (DOF) than actuators: this makes possible the d esign of lightweight cheap robots with high dexterity. The main issue of such ro bots is the control of the passive joint, which requires accurate dynamic modeli ng of the robot.Friction is usually discarded to simplify the models, especially in the case of low-speed trajectories." The news reporters obtained a quote from the research from the University of Pad ua, "However, this simplification leads to oscillations of the end-effector abou t the final position, which are incompatible with fast and accurate motions.This paper focuses on planar $n$ -DOF serial robotic arms with $n-1$ actuated rotational joints plus one final passive rotational joint with stiffness and friction properties. These robots, if properly balanced, are differentially flat. When the non-actuated joint can b e considered frictionless, differentially flat robots can be controlled in open loop, calculating the motor torques demanded by pointto- point motions. This pap er extends the open-loop control to robots with a passive joint with viscous fri ction adopting a Laplace transform method. This method can be adopted by exploit ing the particular structure of the equations of motion of differentially flat u nder-actuated robots in which the last equations are linear. Analytical expressi ons of the motor torques are obtained."
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 originating from Hangzhou, People's Republic of Ch ina, by NewsRx correspondents, research stated, "Thick frost on the evaporators of air-source heat pumps and refrigeration systems can degrade system performanc e. Defrosting in time based on precise frosting state recognition method is of g reat importance." Financial supporters for this research include Key R & D project o f Zhejiang Province, Research Project of Zhejiang University of Technology. Our news journalists obtained a quote from the research from the Zhejiang Univer sity of Technology, "Indirect measuring recognition method with low accuracy is widely used in commercial systems, for cheapness and simpleness, needing improve ment urgently. While accurate direct measuring methods are usually expensive and complicated. Therefore, a novel frosting state recognition method with high acc uracy is proposed, which can be realized with a simple current sensor. The metho d is based on the micro fluctuation in the evaporator fan current (rather than c urrent amplitude) caused by the perturbed air due to frost. An experimental setu p is built to obtain fan current samples. Combining three feature extraction app roaches and three classifiers, four frost state recognition methods using fan cu rrent fluctuation are merged. They are compared and studied based on the experim ental samples. Results show original signal + 1D-CNN method has the best identif ication performance, reaching 95.74 +/- N; 1.73 % accuracy at -10 C evaporator air temperature. It reveals 94.53 +/- 1.06 % accuracy in a temperature range of - 5 -20 C-degrees, and 94.73 +/- 1.00 % accuracy for another fan with the same model."
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