查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Researchers detail new data in Machine Learning. According to news reporting originating in Birmingham, United Kingdom, by NewsRx journalists, research stated, "Most European countries have been committed to r educing their carbon footprint, combating climate change, and reducing the air p ollution typical in large cities over the past decade. Among current solutions t hat can be adopted are the replacement of fuel-powered means of transport with e lectric ones, as well as the introduction of car sharing, bike sharing and elect ric scooters." The news reporters obtained a quote from the research from the University of Bir mingham, "The postpandemic phase was characterized by a greater propensity to u se these means of transport as they were perceived as a healthier choice (for a greater possibility of implementing social distancing) and cheaper (for the diff usion of shared services). The study of modal choice depends on socio-economic s tructures. The present work analyses data related to socio-economic factors (wor k, income and other) to examine the tendency to use electric scooters in the met ropolis of Palermo, Sicily, through machine learning algorithms. The comparison of different algorithms allowed us to underline how the multilayer perceptron al gorithm obtained the best classification among the minimal sequential optimizati on algorithms. The findings also highlight middle-income and freelancer people a s being more likely to use micro-mobility than others. Contrary to what was thou ght, these findings revealed that micro-mobility is not just a preferred mode of transport for low-income people or students."
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 originating from Ames, Iowa, by NewsRx correspondents, research stated, "Spatial adjustments are used to impr ove the estimate of plot seed yield across crops and geographies. Moving means ( MM) and P-Spline are examples of spatial adjustment methods used in plant breedi ng trials to deal with field heterogeneity." Financial support for this research came from North Central Soybean Research Pro gram. Our news editors obtained a quote from the research from Iowa State University, "Within the trial, spatial variability primarily comes from soil feature gradien ts, such as nutrients, but a study of the importance of various soil factors inc luding nutrients is lacking. We analyzed plant breeding progeny row (PR) and pre liminary yield trial (PYT) data of a public soybean breeding program across 3 ye ars consisting of 43,545 plots. We compared several spatial adjustment methods: unadjusted (as a control), MM adjustment, P-spline adjustment, and a machine lea rning-based method called XGBoost. XGBoost modeled soil features at: (a) the loc al field scale for each generation and per year, and (b) all inclusive field sca le spanning all generations and years. We report the usefulness of spatial adjus tments at both PR and PYT stages of field testing and additionally provide ways to utilize interpretability insights of soil features in spatial adjustments. Ou r work shows that using soil features for spatial adjustments increased the rela tive efficiency by 81%, reduced the similarity of selection by 30%,and reduced the Moran's I from 0.13 to 0.01 on average across all experiments. These results empower breeders to further refine selection criteria to make mor e accurate selections and select for macro- and micro-nutrients stress tolerance . Spatial adjustments utilizing soil maps perform better than traditional method s for spatial adjustments of trials. Soil-based spatial adjustments can be used to better understand the spatial variability in breeding trials. Site-specific m achine learning models for spatial adjustments perform better than large general ized models. Plant breeding trials are a key component of crop improvement for y ield, quality, and stress resistance. Breeding trials typically are grown on sma ll plots of land and are highly affected by the area in the field where they are planted due to field trends. We investigated if using the soil features in a fi eld could explain some of the variability in the early stages of a breeding prog ram and used machine learning techniques to estimate the soil effects on observe d yields. We found that by using the soil features for spatial adjustments, we c ould increase the accuracy of selections and improve the outcomes of decisions m ade by a breeder."
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 Brescia, Italy, by NewsRx corresp ondents, research stated, "An e-nose is built on a single graphene field effect transistor (GFET), based on a graphene/Si3N4/p-Si stack of layers. Multichannel data acquisition, enabling to mimic the architecture of a sensor array, is achie ved by steering the gate potential, thus yielding a virtual array of 2D chemires istors on a single sensing layer." Financial support for this research came from Universita Cattolica del Sacro Cuo re-KU Leuven Joint PhD Project within the School of Doctorate in Science.
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 originating from Shanghai, People's Republic of China,by NewsRx correspondents, research stated, "Accurate collaborative positioning by dual robots is crucial for achieving high precision in dual-robot mirror mil ling operations. However, the tool frames constructed in conventional dual-robot coordinate calibration approaches need to be substituted by a new set designate d for the mirror milling, which may induce a notable reduction of collaborative positioning accuracy." Funders for this research include National Natural Science Foundation of China ( NSFC), Natural Science Foundation of Shanghai, National Natural Science Foundati on 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 originating in Rouen, France, by Ne wsRx journalists, research stated, "The comprehensive integration of machine lea rning healthcare models within clinical practice remains suboptimal, notwithstan ding the proliferation of high -performing solutions reported in the literature. A predominant factor hindering widespread adoption pertains to an insufficiency of evidence affirming the reliability of the aforementioned models." Financial supporters for this research include National University of Singapore, NUS-JSPS Joint Research Project, Agency for Science Technology & Research (A*STAR), CISCO Systems (USA) Pte. Ltd.
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on artificial intelligence are presented in a new report. According to news reporting originating from Ulsa n, South Korea, by NewsRx correspondents, research stated, "Corrosion reduces th e thickness of a structure, making it less safe and reducing its lifespan." Funders for this research include Ministry of Education-Singapore; National Re search Foundation of Korea; Korea Ministry of Small And Medium Enterprises And S tartups. Our news editors obtained a quote from the research from University of Ulsan: "I n particular, ships are vulnerable to corrosion because they are always submerge d in seawater. This corrosion is identified through regular inspections of the s hip structure, and gradually increases in scope if no action is taken at an earl y stage. In this study, we developed a model to detect the corrosion areas and p redict the depth of corrosion in the detected areas. The corrosion area detectio n model used a machine learning model based on Mask R-CNN. The 35,753 images wer e used to map corrosion images and measured corrosion depths. Four different col or maps and regression algorithm were used to predict corrosion depths and their performance was compared."
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 from Kunming, People's Republic of China, by NewsRx journalists, research stated, "Cruising ride-hailing vehicles exacerb ate traffic congestion by generating negative externalities. In contrast, reserv ed ride-hailing services leverage precise information regarding the departure ti mes and originsdestinations of future trips." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Yunnan Fundamental Research Projects, Yunnan Xing Dian Talen ts Plan Young Program (2023). The news correspondents obtained a quote from the research from Kunming Universi ty, "Platforms can use this data to dispatch and route drivers more efficiently, thereby reducing the need for cruising. Although previous research has largely concentrated on real-time ride-hailing services, the impact of the built environ ment on reserved ride-hailing remains unexplored with empirical data. This study integrates multi-source data from Haikou City in China and utilizes the gradien t boosting decision tree model, which is an interpretable machine learning appro ach, to investigate potential relationships between reserved ridehailing trip d emand and the built environment. The rankings of relative importance reveal that factors such as the density of food services, education institutions, accessibi lity to town centers, and proximity to transportation hubs significantly influen ce the demand for reserved ride-hailing. Furthermore, the study demonstrates that the aforementioned factors exhibit non-linear effects on the demand for reserv ed ride-hailing."
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 from Zhejiang University by NewsRx journalis ts, research stated, "Hydraulic actuated quadruped robots have bright applicatio n prospects and significant research values in unmanned area investigation, disa ster rescue and other scenarios, due to the advantages of high payload and high power to weight ratio." Funders for this research include National Natural Science Foundation of China; Postdoctoral Research Foundation of China; Key Research And Development Program of Zhejiang Province. The news correspondents obtained a quote from the research from Zhejiang Univers ity: "Among these fields, inevitable collision of robots may occur when contact with unknown objects, step on empty objects, or collapse, all of which have an i mpact on the working hydraulic system. To overcome the unknown external disturba nces, this paper proposes an active disturbance rejection control (ADRC) strateg y of double vane hydraulic rotary actuators for the hip joints of the quadruped robots. Considering the order of the valve-controlled actuator model, a three-st age tracking differentiator, a four-stage extended state observer, and a state e rror feedback controller are designed relatively, and the extended state observe r is adopted to observe and compensate the uncertainty of external load torque o f the system. The effectiveness of the ADRC method is verified in simulation env ironment and a single joint experimental platform."
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 Duisburg, Germany, by NewsRx correspondents, research stated, "The technique of differential impedance analys is (DIA) has shown promising results in identifying appropriate model orders whe n applied to electrochemical impedance spectroscopy (EIS) measurements of a give n medium. However, even with this method it remains challenging to reliably dedu ce general material properties of the medium from impedance data alone." Financial support for this research came from German Bundesministerium fur Wirts chaft und Klimaschutz. Our news journalists obtained a quote from the research from the University of D uisburg-Essen, "Here, we discuss a number of possible extensions and modificatio ns of the technique and, in particular, an extension of the process from mere mo del order identification to a complete modelling approach. In addition, the comb ination of DIA and machine learning methods to predict material properties is ex plored."
查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on artificial intelligen ce have been presented. According to news reporting originating from North Carol ina State University by NewsRx correspondents, research stated, "This review foc uses on the transformative applications of deep learning and artificial intellig ence in textile dyeing, printing, and finishing." The news reporters obtained a quote from the research from North Carolina State University: "In textile dyeing, the topics span color prediction, color-based cl assification, dyeing recipe prediction, dyeing pattern recognition, and the nuan ced domain of color fabric defect detection. In textile printing, applications o f artificial intelligence and machine learning center around pattern detection i n printed fabrics, the generation of novel patterns, and the critical task of de tecting defects in printed textiles. In textile finishing the prediction of fabr ic thermosetting parameters is discussed. Artificial neural networks, diverse co nvolutional neural network variations like AlexNet, traditional machine learning approaches including support vector regression, principal component analysis, X GBoost, and generative artificial intelligence such as generative adversarial ne tworks, as well as genetic algorithms all find application in this multifaceted exploration. At its core, the interest to use these methodologies is because of the need to minimize repetitive and time-consuming manual tasks, curtail prototy ping costs, and promote process automation. The review unravels a plethora of in novative architectures and frameworks, each tailored to address specific challen ges."