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 out of Parma, Italy, by News Rx editors, research stated, "This paper works on detecting a person in bed for sleep routine and sleep pattern monitoring based on the Micro-Electro-Mechanical Systems (MEMS) accelerometer and Internet of Things (IoT) embedded system board ." Funders for this research include Ministry of University And Research in The Fra mework of Pnc "daredigital Lifelong Prevention Project". The news reporters obtained a quote from the research from University of Parma: "This work provides sleep information, patient assessment, and elderly care for patients who live alone via tele-distance to doctors or family members. About 21 6,000 pieces of acceleration data were collected, including three classes: no pe rson in bed, a static laying position, and a moving state for Artificial Intelli gence (AI) application. Six well-known Machine-Learning (ML) algorithms were eva luated with precision, recall, F1- score, and accuracy in the workstation before implementing in the STM32-microcontroller for real-time state classification. Th e four best algorithms were selected to be programmed into the IoT board and app lied for real-time testing."
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 from Liverpool, United Kingd om, by NewsRx journalists, research stated, "We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way -type galaxies from those that were formed externally and later accreted." Our news reporters obtained a quote from the research from Liverpool John Moores University: "These models, which include examples from artificial neural networ ks, decision trees and dimensionality reduction techniques, are trained on a sam ple of disc-like, Milky Way-mass galaxies drawn from the ARTEMIS cosmological hy drodynamical zoom-in simulations. We find that the input parameters which provid e an optimal performance for these models consist of a combination of stellar po sitions, kinematics, chemical abundances ([Fe/H] and [a/Fe]) and photometric properties. Mo dels from all categories perform similarly well, with area under the precision-r ecall curve (PR-AUC) scores of 0.6. Beyond a galactocentric radius of 5 kpc, mod els retrieve $>90 {{ \%}}$ of accreted stars, with a sample purity close to 60%, however the p urity can be increased by adjusting the classification threshold. For one model, we also include host galaxy-specific properties in the training, to account for the variability of accretion histories of the hosts, however this does not lead to an improvement in performance."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news originating from Milan, Italy, by NewsRx correspondents, research stated, "In this study, a novel Machine learning -based method for the joint State of Charge and State of Health estimation of Li thium Batteries that tackle real-world applications and with Bayesian Hyperparam eter optimization is proposed." Financial supporters for this research include Piano Nazionale Di Ripresa E Resi lienza (Pnrr) ? Missione 4 Componente 2, Investimento 1.4. Our news editors obtained a quote from the research from Polytechnic University Milan: "The estimated State of Health is used as an input for State of Charge es timation, considering battery degradation. The accuracy and computational cost o f the proposed method are compared with the other state-of-the-art Machine Learn ing models. For the most promising solutions, an in-depth analysis on factors af fecting the estimation accuracy is performed. To facilitate further research, a new battery dataset was created using extended dynamic driving cycles, encompass ing a wide range of temperature conditions and aging stages. This dataset is pub licly available online to support model development and comparative testing by t he scientific community."
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 artific ial intelligence. According to news reporting originating from Montreal, Canada, by NewsRx correspondents, research stated, "This study explores the progress of chatbot technology, focusing on the aspect of error correction to enhance these smart conversational tools." Our news correspondents obtained a quote from the research from Ecole de Technol ogie Superieure: "Chatbots, powered by artificial intelligence (AI), are increas ingly prevalent across industries such as customer service, healthcare, e-commer ce, and education. Despite their use and increasing complexity, chatbots are pro ne to errors like misunderstandings, inappropriate responses, and factual inaccu racies. These issues can have an impact on user satisfaction and trust. This res earch provides an overview of chatbots, conducts an analysis of errors they enco unter, and examines different approaches to rectifying these errors. These appro aches include using data-driven feedback loops, involving humans in the learning process, and adjusting through learning methods like reinforcement learning, su pervised learning, unsupervised learning, semi-supervised learning, and meta-lea rning. Through real life examples and case studies in different fields, we explo re how these strategies are implemented."
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 originating in Ankara, Turkey, by NewsRx journalists, research stated, "Although artificial intelligen ce technologies are still in their infancy, it is seen that they can bring toget her both hope and anxiety for the future. In the research, it is focused on exam ining the ChatGPT-4 version, which is one of the most well-known artificial inte lligence applications and claimed to have self-learning feature, within the scop e of business establishment processes." The news reporters obtained a quote from the research from National Defence Univ ersity, "In this direction, the assessment questions in the Entrepreneurship Han dbook, published as open access by the Small and Medium Enterprises Development Organization of Turkey, which focuses on guiding the entrepreneurial processes i n Turkey and creating the perception of entrepreneurship, were combined with the artificial intelligence model ChatGPT-4 and analysed within three stages. The w ay of solving the questions of artificial intelligence modelling and the answers it provides have the opportunity to be compared with the entrepreneurship liter ature. It has been seen that the artificial intelligence modelling ChatGPT-4, be ing an outstanding entrepreneurship example itself, has succeeded in answering t he questions posed in the context of 16 modules in the entrepreneurship handbook in an original way by analysing deeply. It has also been concluded that it is q uite creative in developing new alternatives to the correct answers specified in the entrepreneurship handbook."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Kidney Diseases and Co nditions - Chronic Kidney Disease is the subject of a report. According to news reporting from Beijing, People's Republic of China, by NewsRx journalists, resea rch stated, "Cardiovascular disease (CVD) is the leading cause of death in patie nts with chronic kidney disease (CKD). This study aimed to develop CVD risk pred iction models using machine learning to support clinical decision making and imp rove patient prognosis." Financial support for this research came from National Outstanding Youth Science Fund Project of National Natural Science Foundation of China.
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 Nanjing, Pe ople's Republic of China, by NewsRx correspondents, research stated, "The inspec tion of broken wires in prestressed concrete cylinder pipes is crucial for ensur ing the safety and reliability of the pipeline. Traditional point detection tech niques always require labor-intensive periodic inspections and cannot deployed a long the entire pipeline, significantly limiting the development of the industry ." 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-Data detailed on Machine Learning have been presented. According to news reporting originating in Shanghai, People's R epublic of China, by NewsRx journalists, research stated, "Waterabsorbing expan ded elastomers hold significant importance in the fields of engineering and cons truction. However, traditional expanded elastomers exhibit common characteristic s such as slow swelling rates, leakage after water absorption, and low strength. " Financial supporters for this research include Shanghai Municipal Education Comm ission (SHMEC), Class III Peak Discipline of Shanghai-Materials Science and Engi neering (High-Energy Beam Intelligent Processing and Green Manufacturing).
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 Catanzaro, Italy, by New sRx journalists, research stated, "Distinguishing tremor-dominant Parkinson's di sease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data." The news correspondents obtained a quote from the research from University Magna Graecia, "We enrolled 72 patients including 40 tPD patients and 32 rET patients , and 45 control subjects (HC). RT electrophysiological features (frequency, amp litude, and phase) were calculated using surface electromyography (sEMG). Severa l MRI morphometric variables (cortical thickness, surface area, cortical/subcort ical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a treebased classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET pati ents. Both structural MRI and sEMG data showed acceptable performance in disting uishing the two patient groups. Models based on electrophysiological data perfor med slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; = 0.0071). The top-performing model used a combination of sEMG fea tures (amplitude and phase) and MRI data (cortical volumes, surface area, and me an curvature), reaching AUC: 0.97 ? 0.03 and outperforming models using separate ly either MRI ( = 0.0001) or EMG data ( = 0.0231). In the best model, the most i mportant feature was the RT phase."
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 originating from Guangzhou, People' s Republic of China, by NewsRx correspondents, research stated, "Environmental m apping and robot navigation are the basis for realizing robot automation in mode rn agricultural production." The news journalists obtained a quote from the research from South China Agricul ture University: "This study proposes a new autonomous mapping and navigation me thod for gardening scene robots. First, a new LiDAR slam-based semantic mapping algorithm is proposed to enable the robots to analyze structural information fro m point cloud images and generate roadmaps from them. Secondly, a general robot navigation framework is proposed to enable the robot to generate the shortest gl obal path according to the road map, and consider the local terrain information to find the optimal local path to achieve safe and efficient trajectory tracking ; this method is equipped in apple orchards. The LiDAR was evaluated on a differ ential drive robotic platform. Experimental results show that this method can ef fectively process orchard environmental information. Compared with vnf and point net++, the semantic information extraction efficiency and time are greatly impro ved."
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