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 out of Hangzhou, Peop le’s Republic of China, by NewsRx editors, research stated, “Machine learning (M L) has been universally adopted for automated decisions in a variety of fields, including recognition and classification applications, recommendation systems, n atural language processing, and so on. However, in light of high expenses on tra ining data and computing resources, recent years have witnessed a rapid increase in outsourced ML training, either partially or completely, which provides vulne rabilities for adversaries to exploit.” Funders for this research include National Key R&D Program of China , National Natural Science Foundation of China (NSFC), Key R&D Prog ram of Zhejiang.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Machine Learning have be en published. According to news originating from Vicenza, Italy, by NewsRx corre spondents, research stated, “This paper proposes a method for cable failure dete ction in cable-driven parallel robots (CDPRs) with arbitrary architecture, which is based on the estimates of the motor load torques, together with machine lear ning algorithms. By just exploiting the dynamic model of each actuator in the co nditions of no load, an open-loop load torque observer is designed for each moto r to estimate the presence of a load coupled through a cable.” Funders for this research include Universita degli Studi di Padova within the CR UI-CARE Agreement, Ministry of Education, Universities and Research (MIUR), Euro pean Union (EU).
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 Lisbon, Portugal, by N ewsRx journalists, research stated, “The aim of this study was to assess the sho rt-term outcomes of robotic colorectal surgery implemented through a structured, standardized training pathway in five colorectal centres in the United Kingdom. A multicentre retrospective observational study was conducted, involving 523 co nsecutive patients who underwent robotic colorectal resection between 2015 and 2 019.” The news reporters obtained a quote from the research from Champalimaud Clinical Center, “All participating centres followed the European Academy of Robotic Col orectal Surgery training pathway. Patient data, including demographics, operativ e details, postoperative outcomes and pathology results, were collected and anal ysed. The study included 447 rectal resections and 76 colonic operations. The me dian age of the patients was 64.7 years, with the majority of patients (70% ) being men. The mean body mass index was 27.4 kg/m, and 89.7% of the patients underwent surgery for malignancy. The overall conversion rate to op en surgery was 4.2%. The median length of stay was 6 days and there was no 30-day mortality. The readmission and reoperation rates were 8.8% and 7.3%, respectively. The anastomotic leak rate was 4.1% for rectal resections and 3.9% for colonic resections. Pathologica l examination showed a positive circumferential resection margin rate of 2.6% . Through the implementation of a structured, standardized training pathway, the participating colorectal centres in the UK achieved safe and effective robotic colorectal surgery pathways with favourable short-term oncological and clinical outcomes.”
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 - Computational Intelligence. According to news reporting originating from Guiyang, People’s Republic of China, by NewsRx correspondents, research sta ted, “Long-tailed (LT) classification is an unavoidable and challenging problem in the real world. Most existing long-tailed classification methods focus only o n solving the class-wise imbalance while ignoring the attribute-wise imbalance.” Funders for this research include National Key Research & Developm ent Program of China, National Natural Science Foundation of China (NSFC), Guizh ou Provincia Basic Research Program (Natural Science), Youth Science And Technol ogy Talent Growth Project of Guizhou Education Department.
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 originating from Rijeka, Croatia, by Ne wsRx correspondents, research stated, “In this paper, the dataset is collected f rom the fluidic muscle datasheet.” Funders for this research include Ceepus Network; Erasmus+ Projects Wict; Erasmu s+ Aise; University of Rijeka. The news journalists obtained a quote from the research from University of Rijek a: “This dataset is then used to train models predicting the pressure, force, an d contraction length of the fluidic muscle, as three separate outputs. This mode ling is performed with four algorithms-extreme gradient boosted trees (XGB), Ela sticNet (ENet), support vector regressor (SVR), and multilayer perceptron (MLP) artificial neural network. Each of the four models of fluidic muscles (5-100N, 1 0-100N, 20-200N, 40-400N) is modeled separately: First, for a later comparison. Then, the combined dataset consisting of data from all the listed datasets is us ed for training.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Tangshan, Peopl e’s Republic of China, by NewsRx editors, research stated, “At present, as the p roblem of water shortage and pollution is growing serious, it is particularly im portant to understand the recycling and treatment of wastewater. Artificial inte lligence (AI) technology is characterized by reliable mapping of nonlinear behav iors between input and output of experimental data, and thus single/integrated A I model algorithms for predicting different pollutants or water quality paramete rs have become a popular method for simulating the process of wastewater treatme nt.” Our news journalists obtained a quote from the research from the North China Uni versity of Science and Technology, “Many AI models have successfully predicted t he removal effects of pollutants in different wastewater treatment processes. Th erefore, this paper reviews the applications of artificial intelligence technolo gies such as artificial neural networks (ANN), adaptive network-based fuzzy infe rence system (ANFIS) and support vector machine (SVM). Meanwhile, this review ma inly introduces the effectiveness and limitations of artificial intelligence tec hnology in predicting different pollutants (dyes, heavy metal ions, antibiotics, etc.) and different water quality parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (T P) in wastewater treatment process, involving single AI model and integrated AI model.”
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 Nanjing Agricultural University by N ewsRx editors, research stated, “Greenhouse technology is crucial for combating climate change and enhancing off-season produce and crop yield.” The news reporters obtained a quote from the research from Nanjing Agricultural University: “Dust build-up on greenhouse roofs remains a significant problem, si gnificantly reducing light transmission and affecting plant growth. Therefore, t his study aims to classify dust build-up on greenhouse roofs and to address it b y designing, manufacturing, operating, and evaluating a solar-powered cleaning r obot system. Water and cement removal agent (CRA) with different mixing ratios w ere selected to clean the greenhouse roof. The initial findings demonstrate the greenhouse cover’s ability to allow light to pass through can differentiate betw een different levels of dust accumulation. This study reveals that 88 % -93 % of transmittance levels indicate a clean roof, 82 % -87 % reveal minor dust accumulation, 81 %-75 % denote moderate dust accumulation, and below 75 % signify major du st accumulation. This increased the efficiency of the light intensity for minor dust roofs from 39,285 to 41,731 lux ((CRA) 1:3 water), moderate dust roofs from 36,777 to 39,383 lux ((CRA) 1:1 water), and major dust roofs from 30,585 to 35, 525 lux (CRA).”
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 from Lanzhou, People’s Republic of China, by NewsRx journalists, research stated, “Stimuli-responsive layered hydro gel actuators are highly attractive for broad applications in soft robots, intel ligent devices, etc., owing to their softness, asymmetric responsiveness and def ormability. However, current layered hydrogel actuators suffer from serious chal lenges such as tedious preparation, uncontrollable layer thickness and weak inte rfacial bonding force.” Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Outstanding Youth Fu nd of Gansu Province, Gansu Youth Science and Technology Fund.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics are disc ussed in a new report. According to news reporting from Hangzhou, People’s Repub lic of China, by NewsRx journalists, research stated, “The shape estimation tech nique can help solve the end positioning or grasping control of soft robots. How ever, there is a lack of sensing and modeling techniques for accurate deformatio n estimation and soft robots with axial elongation, e.g., pneumatic soft actuato rs (PSAs).” The news correspondents obtained a quote from the research from Zhejiang Science Technical University, “This paper presents a shape-self-sensing pneumatic soft actuator (SPSA) with integrated liquid-metal piecewise curvature sensors (LMCSs) . Two types of LM composite (Ga-In-Sn/Ga2O3 composites for the sensor and Ga-In- Sn/NdFeB/Ni for the electronic wire) were used to build the strain sensor networ k. Furthermore, a piecewise variable curvature (PVC) model was developed to pred ict the bending deformation of the soft actuator. A two-SPSAs-based gripper was built to test the identification performance of LMCSs. The results indicate that SPSA could perform contact and size identification using the PVC model. In addi tion, the K-nearest neighbors (KNN) algorithm was used to classify the shape of the targets. Finally, the circular, triangular, and square targets were identifi ed with an accuracy rate of 93.3%.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Guangdong, People’s Repu blic of China, by NewsRx journalists, research stated, “Collective flow has been found to be similar between small colliding systems (p + p and p + A collisions ) and large colliding systems (peripheral A + A collisions) at the CERN Large Ha dron Collider. In order to study the differences of collective flow between smal l and large colliding systems, we employ a point-cloud network to identify p + P b collisions and peripheral Pb + Pb collisions at root sNN = 5.02 TeV generated from a multiphase transport model.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Key Research & Development Program of China, Chinese Academy of Sciences, Guangdong Major Project of Basic and Applie d Basic Research, CUHK-Shenzhen university development fund, Federal Ministry of Education & Research (BMBF).
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