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 originating from Maharashtra, India, b y NewsRx editors, the research stated, “The state of cutting tools profoundly in fluences the efficiency of the machining processes within the manufacturing indu stry. Cutting tool faults are highly undesirable and can adversely impact the pe rformance of machine tools, leading to a shortened operational lifespan.” Financial supporters for this research include Deanship of Scientific Research, King Saud University.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Prostate Ca ncer is the subject of a report. According to news reporting originating in Aach en, Germany, by NewsRx journalists, research stated, “The treatment with Lutetiu m PSMA (Lu-PSMA) in patients with metastatic castration-resistant prostate cance r (mCRPC) has recently been approved by the FDA and EMA. Since treatment success is highly variable between patients, the prediction of treatment response and i dentification of short- and long-term survivors after treatment could help tailo r mCRPC diagnosis and treatment accordingly.” The news reporters obtained a quote from the research from RWTH Aachen Universit y, “The aim of this study is to investigate the value of radiomic parameters ext racted from pretreatment Ga-PSMA PET images for the prediction of treatment resp onse. A total of 45 mCRPC patients treated with Lu-PSMA- 617 from two university hospital centers were retrospectively reviewed for this study. Radiomic features were extracted from the volumetric segmentations of metastases in the bone. A r andom forest model was trained and validated to predict treatment response based on age and conventionally used PET parameters, radiomic features and combinatio ns thereof. Further, overall survival was predicted by using the identified radi omic signature and compared to a Cox regression model based on age and PET param eters. The machine learning model based on a combined radiomic signature of thre e features and patient age achieved an AUC of 0.82 in 5-fold cross-validation an d outperformed models based on age and PET parameters or radiomic features (AUC, 0.75 and 0.76, respectively). A Cox regression model based on this radiomic sig nature showed the best performance to predict overall survival (C-index, 0.67). Our results demonstrate that a machine learning model to predict response to Lu- PSMA treatment based on a combination of radiomics and patient age outperforms a model based on age and PET parameters.”
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 have been published. According to news reporting out of Punjab, India, by Ne wsRx editors, research stated, “Bone drilling is a mechanical, thermal coupling process utilized in orthopedics for provision of rigid internal fixation and tre atment of fractured bone. Rotary ultrasonic-assisted bone drilling (RUABD) has a chieved noteworthy interest in orthopedic practice due to its ability to enhance biomechanical pullout strength.” Financial support for this research came from SERB SURE grant.
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 originating from Nantong, People’s Republic o f China, by NewsRx correspondents, research stated, “With the development of aut omation and intelligent technologies, the demand for autonomous mobile robots in the industry has surged to alleviate labor-intensive tasks and mitigate labor s hortages.” The news correspondents obtained a quote from the research from Nantong Universi ty: “However, conventional industrial mobile robots’ route-tracking algorithms t ypically rely on passive markers, leading to issues such as inflexibility in cha nging routes and high deployment costs. To address these challenges, this study proposes a novel approach utilizing active landmarks-battery-powered luminous la ndmarks that enable robots to recognize and adapt to flexible navigation require ments. However, the reliance on batteries necessitates frequent recharging, prom pting the development of an automatic power supply system. This system integrate s omnidirectional contact electrodes on mobile robots, allowing to recharge acti ve landmarks without precise positional alignment. Despite these advancements, c hallenges such as the large size of electrodes and non-adaptive battery charging across landmarks persist, affecting system efficiency. To mitigate these issues , this research focuses on miniaturizing active landmarks and optimizing power d istribution among landmarks.”
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 in Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Shaft sleeve is a kind of usual component in industrial manufacturing, and its assembly is also a common task. The sizes of shaft sleeves are usually diverse due to the various application sc enarios.” 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 – New research on Technology - Blockchai n Technology is the subject of a report. According to news reporting from Vilniu s, Lithuania, by NewsRx journalists, research stated, “Like other disciplines, m achine learning is currently facing a reproducibility crisis that hinders the ad vancement of scientific research. Researchers face difficulties reproducing key results due to the lack of critical details, including the disconnection between publications and associated models, data, parameter settings, and experimental results.” Financial support for this research came from Research Council of Lithuania (LMT LT).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in robotics. A ccording to news reporting out of New Delhi, India, by NewsRx editors, research stated, “In industrial environments, efficient indoor transportation is a corner stone of streamlined operations. However, the availability of high-end robotic t ransportation systems often poses a challenge for small-scale manufacturers due to their prohibitive costs.” The news correspondents obtained a quote from the research from Indian Council o f Agricultural Research (ICAR) Indian Agricultural Statistics Research Institute : “Addressing this disparity, this research introduces ‘Pony’, an innovative and cost-effective semi-autonomous self-driven robotic system tailored for indoor t ransportation purposes. Built upon a microcontroller-based platform, Pony harnes ses low-cost technology to create and store m-graphs effectively, facilitating s eamless navigation within indoor facilities. Moreover, the study presents a nove l Pruned-BFS (P-BFS) algorithm designed to efficiently traverse mgraphs, outper forming conventional graph-traversal approaches. Furthermore, the experimental v alidation in the study encompasses a comprehensive evaluation of Pony’s performa nce across a range of scenarios. Randomly generated graphs, varying in complexit y from 26 to 200 nodes, serve as the testing ground. Notably, four distinct algo rithms-Breadth First Seach (BFS), Depth First Search (DFS), Iterative DFS (ID), and P-BFS are put through their paces during numerous random walks on each graph .”
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 out of Xi’an, People’s Republ ic of China, by NewsRx editors, research stated, “Offline reinforcement learning (RL) aims to learn the possible policy from a fixed dataset without real-time i nteractions with the environment. By avoiding the risky exploration of the robot , this approach is expected to significantly improve the robot’s learning effici ency and safety.” 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 – A new study on Machine Learning is now available. According to news reporting from Beijing, People’s Republic of China , by NewsRx journalists, research stated, “The Silicon cold source field-effect transistor (CSFET) offers a compelling solution for low-power logic devices due to its ability to achieve sub-60 mV/dec steep-slope switching with innovative so urce engineering, while maintaining compatibility with Silicon CMOS technology. Developing a compact model for CSFETs is crucial for advancing our understanding of these novel devices and enabling advanced design and simulation based on CSF ETs.” Funders for this research include Spanish Government, National Natural Science F oundation of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on RNA Viruses - Influenz a A Virus is the subject of a report. According to news reporting out of Guelph, Canada, by NewsRx editors, research stated, “Influenza is a disease that repres ents both a public health and agricultural risk with pandemic potential. Among t he subtypes of influenza A virus, H3 influenza virus can infect many avian and m ammalian species and is therefore a virus of interest to human and veterinary pu blic health.” Our news journalists obtained a quote from the research from the University of G uelph, “The primary goal of this study was to train and validate classifiers for the identification of the most likely host species using the hemagglutinin gene segment of H3 viruses. A five-step process was implemented, which included trai ning four machine learning classifiers, testing the classifiers on the validatio n dataset, and further exploration of the best-performing model on three additio nal datasets. The gradient boosting machine classifier showed the highest host-c lassification accuracy with a 98.0 % (95 % CI [97.01, 98.73]) correct classification rate on an independent validation dataset. The classifications were further analyzed using the predicte d probability score which highlighted sequences of particular interest. These se quences were both correctly and incorrectly classified sequences that showed con siderable predicted probability for multiple hosts. This showed the potential of using these classifiers for rapid sequence classification and highlighting sequ ences of interest. Additionally, the classifiers were tested on a separate swine dataset composed of H3N2 sequences from 1998 to 2003 from the United States of America, and a separate canine dataset composed of canine H3N2 sequences of avia n origin. These two datasets were utilized to look at the applications of predic ted probability and host convergence over time. Lastly, the classifiers were use d on an independent dataset of environmental sequences to explore the host ident ification of environmental sequences.”
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