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 - Art ificial Intelligence is the subject of a report. According to news originating f rom Saskatoon, Canada, by NewsRx correspondents, research stated, “Recent advanc es in generative Artificial Intelligence (AI) and Natural Language Processing (N LP) have led to the development of Large Language Models (LLMs) and AI-powered c hatbots like ChatGPT, which have numerous practical applications. Notably, these models assist programmers with coding queries, debugging, solution suggestions, and providing guidance on software development tasks.” Our news journalists obtained a quote from the research from the University of S askatchewan, “Despite known issues with the accuracy of ChatGPT’s responses, its comprehensive and articulate language continues to attract frequent use. This i ndicates potential for ChatGPT to support educators and serve as a virtual tutor for students. To explore this potential, we conducted a comprehensive analysis comparing the emotional content in responses from ChatGPT and human answers to 2 000 questions sourced from Stack Overflow (SO). The emotional aspects of the ans wers were examined to understand how the emotional tone of AI responses compares to that of human responses. Our analysis revealed that ChatGPT’s answers are ge nerally more positive compared to human responses. In contrast, human answers of ten exhibit emotions such as anger and disgust. Significant differences were obs erved in emotional expressions between ChatGPT and human responses, particularly in the emotions of anger, disgust, and joy. Human responses displayed a broader emotional spectrum compared to ChatGPT, suggesting greater emotional variabilit y among humans. The findings highlight a distinct emotional divergence between C hatGPT and human responses, with ChatGPT exhibiting a more uniformly positive to ne and humans displaying a wider range of emotions.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on robotics are discussed in a new report. According to news reporting from Chengdu Technological University by NewsRx journalists, research stated, “In the past, manual inspection was often used for equipment inspection in indoor environments such as substation rooms an d chemical plant rooms.” Financial supporters for this research include International Joint Research Cent er of Robots And Intelligence Program Under Grant.
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 out of Kocaeli University by NewsRx editors, research stated, “Swarm Robotics (SR) is an interdisciplinary field tha t is rapidly advancing to address complex industrial challenges.” Our news correspondents obtained a quote from the research from Kocaeli Universi ty: “This paper provides a comprehensive review of recent advancements and emerg ing trends in SR, with a specific focus on the coordination and control of Swarm Flying Robots (SFRs). The motivation behind this review is to explore scalable and robust solutions for SFRs to enhance their performance and adaptability acro ss various applications. Key objectives include examining the characteristics an d essential behaviors of SR, analyzing the challenges and so lutions for impleme nting SR in Flying Robots (FRs), and highlighting current and future research di rections. The review delves into critical areas such as multiple robot path plan ning, Swarm Intelligence (SI), combinatorial optimization, and formation flying using SFR. Special attention is given to coordination and control techniques, in cluding formation control in GPS-denied environments, to underscore their signif icance in advancing SR. The paper also addresses ethical, privacy, and security considerations, emphasizing the importance of responsible practices in SR develo pment.”
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 in Fuzhou, People ’s Republic of China, by NewsRx journalists, research stated, “This study examin es the impact of Generative Artificial Intelligence (GenAI) resources on entrepr eneurial performance in China, focusing on internal integration and external col laboration mediating roles. Drawing upon Resource-Based Theory (RBT), this study proposes a theoretical model that outlines how tangible, intangible, and human resources related to GenAI affect entrepreneurial performance.” Financial support for this research came from Major Humanities and Social Scienc es Research Projects in Zhejiang higher education institutions.
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 Kavala, Greece, by Ne wsRx editors, the research stated, “In modern industry, anomaly detection is an important part of safety and productivity management.” Our news reporters obtained a quote from the research from Democritus University of Thrace: “Early anomaly detection could allow for timely interventions, preve nting malfunctions and reducing risks for human workers and machines. This work aims to deliver an overview of the use of machine learning for anomaly detection in industrial environments, highlight the state-of-the-art, and discuss challen ges and prospects for future research. Existing approaches, methodologies, and r esults related to anomaly detection are summarized, focusing on the application of machine learning for different types of industrial anomalies.”
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 Genoa, Italy, by News Rx editors, research stated, “Monitoring rainfall is becoming increasingly impor tant due to the impacts of climate change.” Financial supporters for this research include Artificial Intelligence For A Sma rt Rainfall System (Ai4srs) Horizon 2020 Framework Programme of The European Uni on.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting out of Mansour a, Egypt, by NewsRx editors, research stated, “The DC microgrids possess numerou s pros, including enhanced reliability, increased efficiency, and a less complic ated control system. Further, they provide a simplified system that facilitates the incorporation of renewable energy sources (RES), battery storage systems, an d DC loads.” Our news reporters obtained a quote from the research from Mansoura University: “DC microgrids improve resource coordination and utilization, thus offering a po tential alternative to modern energy systems. DC power systems have unique featu res that make protecting DC microgrids from different types of faults very hard. These include large DC capacitors, low-impedance DC cables, no natural zero-cro ssing points, and significant transient current and voltage changes that happen very quickly. Also, solid-toground faults could result in a rapid increase in D C fault current. Therefore, a cost-effective and reliable system protection mech anism capable of detecting, locating, and isolating faults is crucial to prevent ing DC microgrids from experiencing power outages and failures. This paper prese nts a machine-learningbased protection approach for DC microgrids. The proposed methodology relies solely on measuring the current passing through the positive terminal at bus_1 in the modified IEEE 14-bus configuration. Durin g the measurement, the DC microgrid encountered several fault scenarios. The gat hered data is analyzed to train a supervised machine-learning method that uses m edium-gaussian support vector machines and bagged tree classification algorithms . The effectiveness of this method was evaluated by conducting tests on a partic ular subset of the collected data using the trained model. The proposed protecti on technique was verified using MATLAB/Simulink software under several pole-pole (P-P) and pole-ground (P-G) fault conditions.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting from Herlev, Denmark, by NewsRx journ alists, research stated, “To explore surgical, functional, and symptomatic outco mes in a series of patients who underwent robot-assisted laparoscopic Anderson-H ynes pyeloplasty (RALP) for ureteropelvic junction obstruction using the DaVinci Si surgical robotic system. Retrospective study including patients aged 16 year s or older who underwent RALP from June 2016 to December2021.” Financial support for this research came from Copenhagen University.
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 out of Dehradun, India, by NewsRx editors, research stated, “Soil moisture is a critical factor that supports plan t growth, improves crop yields, and reduces erosion. Therefore, obtaining accura te and timely information about soil moisture across large regions is crucial.” The news correspondents obtained a quote from the research from Indian Institute of Remote Sensing: “Remote sensing techniques, such as microwave remote sensing , have emerged as powerful tools for monitoring and mapping soil moisture. Synth etic aperture radar (SAR) is beneficial for estimating soil moisture at both glo bal and local levels. This study aimed to assess soil moisture and dielectric co nstant retrieval over agricultural land using machine learning (ML) algorithms a nd decomposition techniques. Three polarimetric decomposition models were used t o extract features from simulated NASA-ISRO SAR (NISAR) L-Band radar images. Mac hine learning techniques such as random forest regression, decision tree regress ion, stochastic gradient descent (SGD), XGBoost, K-nearest neighbors (KNN) regre ssion, neural network regression, and multilinear regression were used to retrie ve soil moisture from three different crop fields: wheat, soybean, and corn. The study found that the random forest regression technique produced the most preci se soil moisture estimations for soybean fields, with an R2 of 0.89 and RMSE of 0.050 without considering vegetation effects and an R2 of 0.92 and RMSE of 0.042 considering vegetation effects. The results for real dielectric constant retrieval for the soybean field were an R2 of 0.89 and RMSE of 6.79 without considering vegetation effects and an R2 of 0.89 and RMSE of 6.78 with considering vegetation effects.”
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 - Liver Cance r is the subject of a report. According to news reporting originating from Jiaxi ng, People’s Republic of China, by NewsRx correspondents, research stated, “The effectiveness of radiofrequency ablation (RFA) in improving long-term survival o utcomes for patients with a solitary hepatocellular carcinoma (HCC) measuring 5 cm or less remains uncertain. This study was designed to elucidate the impact of RFA therapy on the survival outcomes of these patients and to construct a progn ostic model for patients following RFA.”
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