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 originating from Manchester, United Kin gdom, by NewsRx correspondents, research stated, "Post-operative length of hospi tal stay (LOS) is a valuable measure for monitoring quality of care provision, p atient recovery, and guiding hospital resource management. But the impact of pat ient ethnicity, socio-economic deprivation as measured by the indices of multipl e deprivation (IMD), and pre-existing health conditions on LOS post-anterior cer vical decompression and fusion (ACDF) is under-researched in public healthcare s ettings."
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 University Park, Penns ylvania, by NewsRx editors, research stated, "Materials characterization remains a labor-intensive process, with a large amount of expert time required to post- process and analyze micrographs. As a result, machine learning has become an ess ential tool in materials science, including for materials characterization." Financial support for this research came from National Science Foundation (NSF). Our news journalists obtained a quote from the research from Pennsylvania State University (Penn State), "In this study, we perform an in-depth analysis of the prediction of crystal coverage in WSe 2 thin film atomic force microscopy (AFM) height maps with supervised regression and segmentation models. Regression model s were trained from scratch and through transfer learning from a ResNet pretrain ed on ImageNet and MicroNet to predict monolayer crystal coverage. Models traine d from scratch outperformed those using features extracted from pretrained model s, but fine-tuning yielded the best performance, with an impressive 0.99 R 2 val ue on a diverse set of held-out test micrographs. Notably, features extracted fr om MicroNet showed significantly better performance than those from ImageNet, bu t fine-tuning on ImageNet demonstrated the reverse. As the problem is natively a segmentation task, the segmentation models excelled in determining crystal cove rage on image patches. However, when applied to full images rather than patches, the performance of segmentation models degraded considerably, while the regress ors did not, suggesting that regression models may be more robust to scale and d imension changes compared to segmentation models."
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 originating from Changsha, People's Republic of Chin a, by NewsRx correspondents, research stated, "It is challenging to automaticall y explore an unknown 3D environment with a robot only equipped with depth sensor s due to the limited field of view. We introduce THP, a tensor field-based frame work for efficient environment exploration which can better utilize the encoded depth information through the geometric characteristics of tensor fields." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Young Elite Scientists Sponsorship Program by CAST, Natural Science Foundation of Hunan Province.
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 Jiangsu, People's Republic of China, by NewsRx correspondents, research stated, "Since the 21st century, China has be en vigorously developing urban construction, and now the rise of artificial inte lligence (AI) has brought new opportunities for urban design and management. Mes o-scale cities are the most developed cities in China and play an important role in economic and social development." The news reporters obtained a quote from the research from Southeast University: "The current robot technology is mainly divided into industrial robots and serv ice robots, which can play an important role in the development of cities. This paper aims to apply AI robotics technology to the analysis and intelligent manag ement of mesoscale urban design genealogy. Firstly, the development pedigree of the mesoscale city was analyzed, from which the characteristics of previous desi gns could be clearly understood. Then, the urban management and control system i s intelligently designed from many aspects, the characteristics of the robot are analyzed, and the application of the intelligent robot in urban design is intro duced. After that, four developing meso-scale cities in a province were selected as the evaluation objects, and an Analytic Hierarchy Process (AHP) was proposed to evaluate the application effect of robotics technology in meso-scale cities. The results showed that the overall score of the robot in urban traffic design was greater than 70 points, and the overall score of urban architectural design was greater than 65 points, which was in the acceptable range. In the applicatio n score of urban environment design, the influence was about 70 to 80 points, an d the aesthetics was more than 75 points. The cultural aspect of the design impa ct score was no more than 75 points, while the cultural support aspect score was around 80 points. After the weight calculation, the final overall score was 489 points, and the comprehensive average score was 36 points."
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 Ecully, Fra nce, by NewsRx correspondents, research stated, "With increasing popularity of r ide -hailing services, it becomes important to build transparent and explainable pricing models using artificial intelligence (AI). While the literature on this domain is growing steadily, the application of AI in pricing prediction is rela tively new." Our news editors obtained a quote from the research from EMLYON Business School, "We drew upon the New York City Taxi dataset to build pricing prediction models to bridge this gap. Our contributions are as follows. First, we created unique clusters for yellow and app -based cabs, leading to a dynamic pricing mechanism across different zones in New York City. Second, we converted a prediction probl em into a classification problem by transforming the prices into four distinct q uartiles. Third, we applied variable importance schemes to generate top predicto rs in each cluster. Fourth, our study reveals that differential effects of each predictor for cab -pricing across different clusters exist. Fifth, the ‘ congest ion surcharge ‘ is significant for only a few clusters, and imposing such surcha rges could hurt the overall taxicab industry."
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 Weihai, People's Republic of China, b y NewsRx editors, research stated, "Three-wheeled omnidirectional mobile robots (TOMRs) are widely used to accomplish precise transportation tasks in narrow env ironments owing to their stability, flexible operation, and heavy loads." Financial supporters for this research include Natural Science Foundation of Sha ndong Province. The news journalists obtained a quote from the research from Shandong University : "However, these robots are susceptible to slippage. For wheeled robots, almost all faults and slippage will directly affect the power consumption. Thus, using the energy consumption model data and encoder data in the healthy condition as a reference to diagnose robot slippage and other system faults is the main issue considered in this paper. We constructed an energy model for the TOMR and analy zed the factors that affect the power consumption in detail, such as the positio n of the gravity center. The study primarily focuses on the characteristic relat ionship between power consumption and speed when the robot experiences slippage or common faults, including control system faults."
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 from Yunnan, People's Republic of China, b y NewsRx journalists, research stated, "Aiming at the problem of poor autonomous adaptability of mobile robots to dynamic environments, this paper propose a YOL ACT++ based semantic visual SLAM for autonomous adaptation to dynamic environmen ts of mobile robots. First, a light-weight YOLACT++ is utilized to detect and se gment potential dynamic objects, and Mahalanobis distance is combined to remove feature points on active dynamic objects, also, epipolar constraint and clusteri ng are employed to eliminate feature points on passive dynamic objects." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from Yunnan Normal Un iversity, "Then, in terms of the semantic labels of dynamic and static component s, the global semantic map is divided into three parts for construction. The sem antic overlap and uniform motion model are chose to track moving objects and the dynamic components are added to the background map. Finally, a 3D semantic octr ee map is constructed that is consistent with the real environment and updated i n real time."
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 artificial in telligence have been published. According to news originating from Osaka Univers ity by NewsRx correspondents, research stated, "Located in the heart of Mainland Southeast Asia, Thailand is associated with high biomass burning (BB) activitie s from local and neighbouring countries." The news editors obtained a quote from the research from Osaka University: "The seasonal pattern of BB manifests itself as a potential predictor for PM2.5 conce ntration. Consequently, we enhanced machine learning based PM2.5 prediction by s egregating BB factor from the Community Multiscale Air Quality (CMAQ). Two Light Gradient Boosting Machine (LightGBM) models with different CMAQ predictors were developed: the BB-integrated model, which incorporated CMAQ-simulated PM2.5 fro m all emission sources and the BB-segregated model, which incorporated CMAQ-simu lated PM2.5 from sources other than BB (CMAQ_PM25_Othr ) and CMAQ-simulated PM2.5 from BB emissions (CMAQ_PM25_ BB). The two models had shared control predictors, which included simulated mete orological variables from WRF model, population, elevation, and land-use variabl es, and they were evaluated using a crossvalidation (CV). The BB-segregated mode l outperformed the BB-integrated model, achieving overall-CV R2 values of 0.86 a nd 0.82, respectively. The analysis of feature importance for the BB-segregated model indicates that CMAQ_PM25_Othr and CMAQ_ PM25_BB are the two most significant predictors."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators publish new report on Nanotechnolog y - Nanoparticles. According to news reporting originating from Shanghai, People 's Republic of China, by NewsRx correspondents, research stated, "Dielectric ela stomer actuators (DEAs) with reversible large electrically actuated strains can be used to build lightweight and flexible crawling robots. Silicone rubber (SR) has become a research hotspot for dielectric elastomer (DE) materials due to its stable performance and fast response speed (ms), but it has the problems of a s mall actuation strain, a low dielectric constant, and a large driving electric f ield, which seriously limit the actuation performance of DEAs." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Key Research Project of Zhejiang Laboratory, Project of Heta o Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone, Nationa l Natural Science Foundation of China (NSFC).
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 from College Park, Maryland, by News Rx journalists, research stated, "Building precise machine learning and deep lea rning models has traditionally required a combination of mathematical skills and hands-on experience to meticulously adjust hyperparameters that significantly i mpact the learning process. As datasets continue to expand across various engine ering domains, researchers increasingly turn to machine learning methods to unco ver hidden insights that may elude classic regression techniques." The news correspondents obtained a quote from the research from the University o f Maryland, "This surge in adoption raises concerns about the adequacy of result ant meta-models and the interpretation of findings. In response to these challen ges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. This paper benchmarks AutoML solutions by providing an overview of their principles and applying them to predict the most important mechanical p roperties of different concrete datasets, i.e., compressive strength. Nine datas ets from various concrete types, sample sizes, and features are utilized, with a detailed discussion on the benchmark dataset from high-performance concrete, ap plying best practices to the other eight datasets. For each case, the importance of hyperparameter tuning is discussed, alongside the ensemble and stacking mode ls. Tree-based models are employed for each dataset to develop SHAP plots, inter pret results, and understand the contribution of each component in the mix desig n to the overall strength of the concrete."
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