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 from Trappes, France, by New sRx correspondents, research stated, “Infiltration-based sustainable urban drain age systems (i-SUDS) often turn out to be simple and effective solutions for on- site runoff and pollution control. Their ability to limit the discharge to sewer networks or receiving waters can be broadly assessed in terms of (pluri)annual stormwater volume reduction.” Funders for this research include French Ministry of the Environment, Seine Norm andie Water Agency, OPUR partners (Seine-Normandy Water Agency, Val-de-Marne Dep artmental Council, Seine-Saint-Denis Departmental Council), Hauts-de-Seine Depar tmental Council, Seine-et-Marne Departmental Council.
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 out of Beijing, People’s Repu blic of China, by NewsRx editors, research stated, “With the increasing uncertai nty caused by the complexity of the world’s energy environment and the increasin g penetration rate of renewable energy, it is significant to estimate the future operation of power markets in advance. Forecasting individual bids in spot elec tricity markets is a promising new method for achieving so, but it has not been fully studied due to the difficulty of forecasting a bid function.” 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 – Research findings on Machine Learning are discussed in a new report. According to news reporting originating in Tianji n, People’s Republic of China, by NewsRx journalists, research stated, “The shor tage of annotated ECG data presents a significant impediment, hampering the over all generalization capabilities of machine learning models tailored for automate d ECG classification. The collective integration of multisource datasets present s a potential remedy for this challenge.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from Tianjin University, “ However, it is crucial to underscore that the mere addition of supplementary dat a does not automatically guarantee performance enhancement, given the unresolved challenges associated with multisource data. In this research, we address one s uch challenge, namely, the issue of incomplete labels arising from the diversity of annotations within multi -source ECG datasets. First, we identified three di stinct types of label missing: dataset-related label missing, supertype missing, and subtype missing. To address the supertype missing effectively, we introduce a novel approach known as offline category mapping which leverages the hierarch ical relationships inherent within the categories to recover the missing superty pe labels. Additionally, two complementary strategies, referred to as prediction masking and online category mapping, are proposed to mitigating the adverse eff ects of subtype and dataset-related label missing on model optimization. These s trategies enhance the model’s ability to identify missing subtypes under conditi ons of weak supervision. These pioneering methodologies are integrated into a de ep learning -based framework designed for multilabel ECG classification. The per formance of our proposed framework is rigorously evaluated using realistic multi -source datasets obtained from the PhysioNet/CinC challenge 2020/2021. The prop osed learning framework exhibits a notable improvement in macro -average precisi on, surpassing the corresponding baseline model by more than 25 % on the test datasets.”
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 out of Karnataka, India, by NewsRx edito rs, research stated, “The accumulation of microplastics (MPs) resulting from dis posal of plastic waste into water sources, poses a significant threat to aquatic organisms. These are readily ingested by organisms, leading to the accumulation of harmful substances, disrupting their biological processes.” Our news journalists obtained a quote from the research from the Manipal Academy of Higher Education, “Current methods for identifying microplastics have notabl e drawbacks, including low resolution, extended imaging time, and restricted par ticle size analysis. Integrating Raman spectroscopy with machine learning (ML) p roves to be an effective approach for identifying and classifying MPs, especiall y in scenarios where they are found in environmental media or mixed with various types. Machine learning (ML) can be vital tool in assisting Raman analysis, owi ng to its robust feature extraction capabilities. This comprehensive review outl ined the utilization of various machine learning techniques in conjunction with Raman spectral features for diverse investigations related to microplastics.”
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 reporting out of Nanjing, People’s Republic of China, by NewsRx editors, research stated, “This paper introduces a soft, ca ble-driven parallel robot for minimally invasive surgeries. The robot comprises a pneumatic inflatable scaffold, six hydraulic, folded pouch actuators, and a ho llow, cylindrical end-effector offering five degrees of freedom.” Financial supporters for this research include National Natural Science Foundati on of China; Fundamental Research Funds For The Central Universities.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on robotics is now available. Accordi ng to news originating from Hefei, People’s Republic of China, by NewsRx editors , the research stated, “Multi-robot Simultaneous Localization and Mapping (SLAM) systems employing 2D lidar scans are effective for exploration and navigation w ithin GNSS-limited environments.” Financial supporters for this research include National Natural Science Foundati on of China; Key Program of Natural Science Foundation of Anhui Higher Education Institutions of China.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on artificial intelligence are present ed in a new report. According to news originating from Ahvaz, Iran, by NewsRx co rrespondents, research stated, “Scale deposition, a form of formation damage, no t only affects the reservoir but also damages the well and equipment. This pheno menon occurs due to changes in temperature, pressure, and the injection of incom patible salt water, leading to ionic reactions.” Our news journalists obtained a quote from the research from Petroleum Universit y of Technology: “This study investigated permeability reduction due to scale de position and examined how parameters such as temperature, pressure drop, and ion concentration affect the prediction accuracy. The scale deposits investigated i n this study include CaSO4, BaSO4, and SrSO4. This paper uses Python to employ d ifferent machine-learning algorithms to predict the results. Each machine learni ng model has certain hyper-parameters that need adjustment. Failure to do so wil l result in reduced accuracy and incomplete interpretation of input data. The ac curacy of the support vector regression (SVR) algorithm was significantly affect ed by the variation of the epsilon parameter in the dataset used. Therefore, bef ore hyperparameter optimization, SVR had the lowest accuracy at 0.575. After adj usting the hyperparameters, our findings show that SVR had the highest increase in R-squared value, which was 0.900, and the most minor growth in KNN, which we nt from 0.995 to 0.996.”
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 Robotics. According to news reporting originating from Xi’an, People’s Republic of China, by NewsRx correspondents, research stated, “In the realm of semi-auton omous mobile robots designed for remote operation with humans, current variable autonomy approaches struggle to reconcile conflicting intents while ensuring com pliance, autonomy, and safety. To address this challenge, we propose a bidirecti onal trust-based variable autonomy (BTVA) control approach.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from Northwestern Polytechni c University, “By incorporating diverse trust factors and leveraging Kalman filt ering techniques, we establish a core abstraction layer to construct the state-s pace model of bidirectional computational trust. This bidirectional trust is int egrated into the variable autonomy control loop. Real-time modulation of the deg ree of automation is achieved through variable weight receding horizon optimizat ion. Through a within-group experimental study with twenty participants in a sem i-autonomous navigation task, we validate the effectiveness of our method in goa l transfer and assisted teleoperation. Statistical analysis reveals that our met hod achieves a balance between rapid response and trajectory smoothness.”
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 Machine Learn ing - Intelligent Systems have been published. According to news originating fro m Beijing, People’s Republic of China, by NewsRx correspondents, research stated , “With the development of deep learning, a higher level of perception of the en vironment such as the semantic level can be achieved in the simultaneous localiz ation and mapping (SLAM) domain. However, previous works did not achieve a natur al-language level of perception.” 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 – Data detailed on Machine Learning have been presented. According to news reporting out of Xi’an, People’s Republic of China, by NewsRx editors, research stated, “With the widespread data collection and processing, privacy -preserving machine learning has become increasingly imp ortant in addressing privacy risks related to individuals. Support vector machin e (SVM) is one of the most elementary learning models of machine learning.” Funders for this research include National Natural Science Foundation of China ( NSFC), Natural Science Basic Research Program of Shaanxi, Shaanxi Distinguished Youth Project, Shaanxi Provincial Education Department, Distinguished Youth Tale nts of Shaanxi Universities, Youth Innovation Team of Shaanxi Universities.
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