查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on androids are presented i n a new report. According to news reporting from the Department of Architecture by NewsRx journalists, research stated, “During the last 15 years, an increasing amount of works have investigated proactive robotic behavior in relation to Hum an-Robot Interaction (HRI).” The news reporters obtained a quote from the research from Department of Archite cture: “The works engage with a variety of research topics and technical challen ges. In this paper a review of the related literature identified through a struc tured block search is performed. Variations in the corpus are investigated, and a definition of Proactive HRI is provided.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Nanotechnology - Nanoplastics is the subject of a report. According to news reporting from Wuxi, People’s Republi c of China, by NewsRx journalists, research stated, “Nanoplastics (NPs) aggregat ion determines their bioavailability and risks in natural aquatic environments, which is driven by multiple environmental and polymer factors. The back propagat ion artificial neural network (BP-ANN) model in machine learning (R = 0.814) can fit the complex NPs aggregation, and the feature importance was in the order of surface charge of NPs > dissolved organic matter (DOM) > functional group of NPs > ioni c strength and pH > concentration of NPs.” The news correspondents obtained a quote from the research from Jiangnan Univers ity, “Meta-analysis results specified low surface charge (0 |z| <10 mV) of NPs, low concentration (<1 mg/L) and low molecu lar weight (<10 kg/mol) of DOM, NPs with amino groups, hig h ionic strength (IS > 700 mM) and acidic solution, and high concentration ( 20 mg/L) of NPs with smaller size (<1 00 nm) contribute to NPs aggregation, which is consistent with the prediction in machine learning. Feature interaction synergistically (e.g., DOM and pH) or ant agonistically (e.g., DOM and cation potential) changed NPs aggregation. Therefor e, NPs were predicted to aggregate in the dry period and estuary of Poyang Lake. Research on aggregation of NPs with different particle size,shapes, and functio nal groups, heteroaggregation of NPs with coexisting particles and aging effects should be strengthened in the future.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting originating from Tucson, Arizona, by New sRx correspondents, research stated, “Coal and gas outbursts are a major cause o f fatalities in underground coal mines and pose a threat to coal power generatio n worldwide. Among the current mitigation efforts include monitoring methane gas levels using sen-sors, employing geophysical surveys to identify geological str uctures and zones prone to outbursts, and using empirical modeling for outburst predictions.” Our news editors obtained a quote from the research from the University of Arizo na, “However, in the wake of industry 4.0 technologies, several studies have bee n conducted on applying artificial intelligence methods to predict outbursts. Th e proposed models and their results vary significantly in the literature. This s tudy reviews the application of machine learning (ML) to predict coal and gas ou tbursts in underground mines using a mixed-method approach. Most of the availabl e literature, with a focus on ML applications in coal and gas outburst predictio n, was investigated in China. Findings indicate that researchers proposed divers e ML models mostly combined with different optimization algorithms, including pa rticle swarm optimization (PSO), genetic algorithm (GA), rough set (RS), and fru it fly optimization algorithm (IFOA) for outburst prediction. The number and typ e of input parameters used for prediction differed significantly, with initial g as velocity being the most dominant parameter for gas outbursts, and coal seam d epth as the dominant parameter for coal outbursts. The datasets for training and testing the proposed ML models in the literature varied significantly but were mostly insufficient - which questions the reliability of some of the applied ML models.”
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 Punjab, Pakistan, by N ewsRx editors, the research stated, “The prevalence of cyberbullying has reached an alarming rate, affecting approximately 54% of teenagers who ex perience various forms of cyberbullying, including offensive hate speech, threat s, and racism.” Our news journalists obtained a quote from the research from University of Engin eering and Technology Lahore: “This research introduces a comprehensive dataset and system for cyberbullying detection in Urdu tweets, leveraging a spectrum of machine learning approaches including traditional models and advanced deep learn ing techniques. The objectives of this study are threefold. Firstly, a dataset c onsisting of 12,500 annotated tweets in Urdu is created, and it is made publicly available to the research community. Secondly, annotation guidelines for Urdu t ext with appropriate labels for cyberbullying detection are developed. Finally, a series of experiments is conducted to assess the performance of machine learni ng and deep learning techniques in detecting cyberbullying.”
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 Espoo, Finland, by NewsRx journalist s, research stated, “This article presents a novel data augmentation method that generates feature values for unmeasured loading levels based on limited measure d and simulated loading level data. The incorporation of offline simulated data in the augmentation framework and the mapping of the error distribution over the loading levels greatly reduce the dependency on including a large number of loa ding levels in the curve fitting process.” Financial support for this research came from Academy of Finland Consortium. The news correspondents obtained a quote from the research from Aalto University , “Furthermore, the proposed method shows high potential to minimize the deviati on between measured and simulated data at the feature level. The method is appli ed to the induction machine (IM) to generate feature values at 25% and 50% loading levels for healthy, one, two, and three broken rot or bars (BRBs) conditions. An excellent agreement is observed between the augmen ted and actual feature values calculated from the measured data at 25% and 50% loading levels.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Machine Learning - Intellige nt Systems are discussed in a new report. According to news originating from Sha nghai, People’s Republic of China, by NewsRx correspondents, research stated, “W e present VoxelPlane-Reloc, a novel indoor plane relocalization system based on voxel point clouds, designed for use with depth cameras. First, we propose an ad aptive weighted plane extraction model that allows for dynamic adjustment of the correlation between points and plane accuracy.” 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 – Investigators publish new report on ar tificial intelligence. According to news reporting originating from Taiyuan, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “Accurate me dium- and long-term runoff prediction models play crucial guiding roles in regio nal water resources planning and management. However, due to the significant var iation in and limited amount of annual runoff sequence samples, it is difficult for the conventional machine learning models to capture its features, resulting in inadequate prediction accuracy.” Funders for this research include National Natural Science Foundation of China; Basic Research Programs of Shanxi Province; Open Research Fund of Henan Key Labo ratory of Water Resources Conservation And Intensive Utilization in The Yellow R iver Basin.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics are presented i n a new report. According to news reporting originating in Shanghai, People’s Re public of China, by NewsRx journalists, research stated, “Facing the system unce rtainties caused by unmodeled dynamics and unpredictable external disturbances, the robot position control for meeting the high-performance control requirements on higher accuracy and faster beat is vital for many industrial applications, s uch as welding and laser cutting tasks. This work aims to cope with the problem of precise and fast position tracking for robot manipulators with an effective a nd safe control scheme.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), 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 Daily News – Investigators publish new report on ro botics. According to news reporting originating from Wuhan, People’s Republic of China, by NewsRx correspondents, research stated, “Fastener screws are critical components of rail fasteners.” Our news editors obtained a quote from the research from Hubei University of Tec hnology: “For the fastener screw maintenance robot, an image-based fast fastener screw detection method is urgently needed. In this paper, we propose a light-we ight model named FSS-YOLO based on YOLOv5n for rail fastener screw detection. Th e C3Fast module is presented to replace the C3 module in the backbone and neck t o reduce Params and FLOPs. Then, the SIoU loss is introduced to enhance the conv ergence speed and recognition accuracy. Finally, for the enhancement of the scre w detail feature fusion, the shuffle attention (SA) is incorporated into the bot tom-up process in the neck part.”
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 from Bergamo, Italy, b y NewsRx journalists, research stated, “Overall survival (OS)-predictive models to clinically stratify patients with stage I Non-Small Cell Lung Cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) are still unavailable. The aim of this work was to build a predictive model of OS in this setting.” The news correspondents obtained a quote from the research from Radiation Oncolo gy Department, “Clinical variables of patients treated in three Institutions wit h SBRT for stage I NSCLC were retrospectively collected into a reference cohort A (107 patients) and 2 comparative cohorts B1 (32 patients) and B2 (38 patients) . A predictive model was built using Cox regression (CR) and artificial neural n etworks (ANN) on reference cohort A and then tested on comparative cohorts. Coho rt B1 patients were older and with worse chronic obstructive pulmonary disease ( COPD) than cohort A. Cohort B2 patients were heavier smokers but had lower Charl son Comorbidity Index (CCI). At CR analysis for cohort A, only ECOG Performance Status 0-1 and absence of previous neoplasms correlated with better OS. The mode l was enhanced combining ANN and CR findings. The reference cohort was divided i nto prognostic Group 1 (0-2 score) and Group 2 (3-9 score) to assess model’s pre dictions on OS: grouping was close to statistical significance (p=0.081). One an d 2-year OS resulted higher for Group 1, lower for Group 2. In comparative cohor ts, the model successfully predicted two groups of patients with divergent OS tr ends: higher for Group 1 and lower for Group 2. The produced model is a relevant tool to clinically stratify SBRT candidates into prognostic groups, even when a pplied to different cohorts.”
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