查看更多>>摘要：The development of a new theory is typically associated with the greats of physics. You might think of Isaac Newton or Albert Einstein, for example. Many Nobel Prizes have already been awarded for new theories. Researchers at Forschungszentrum Julich have now programmed an artificial intelligence that has also mastered this feat. Their AI is able to recognize patterns in complex data sets and to formulate them in a physical theory. The development of a new theory is typically associated with the greats of physics. You might think of Isaac Newton or Albert Einstein, for example. Many Nobel Prizes have already been awarded for new theories. Researchers at Forschungszentrum Julich have now programmed an artificial intelligence that has also mastered this feat. Their AI is able to recognize patterns in complex data sets and to formulate them in a physical theory.
查看更多>>摘要：Investigators publish new report on robotics. According to news reporting from Tianjin University of Science and Technology by NewsRx journalists, research stated, "Unmanned mobile robots have broad application prospects in industrial production. With the continuous deepening of Industry 4.0, the complexity of manufacturing workflows has skyrocketed, and researching robots suitable for flexible production is becoming a focus of development." Our news reporters obtained a quote from the research from Tianjin University of Science and Technology: "With the rapid development of computer technology and sensor technology, the ability of robots to obtain their own state and environmental information has also been greatly expanded. Studying the work, path planning, and obstacle avoidance of robots has important practical significance. This article designs a flexible production robot that integrates Automated Guided Vehicle (AGV) with industrial robots. It has the ability to perceive the environment, make optimal decisions, and operate independently. It can achieve functions such as mobile transportation, flexible operation, and human-machine interaction and cooperation in the production line. This article uses Gazebo to construct a production environment and simulate robot movement."
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting from Rotterdam, Netherlands, by NewsRx journalists, research stated, "To provide a comprehensive framework for value assessment of artificial intelligence (AI) in radiology. This paper presents the RADAR framework, which has been adapted from Fryback and Thornbury's imaging efficacy framework to facilitate the valuation of radiology AI from conception to local implementation." The news correspondents obtained a quote from the research from Erasmus University Medical Center, "Local efficacy has been newly introduced to underscore the importance of appraising an AI technology within its local environment. Furthermore, the RADAR framework is illustrated through a myriad of study designs that help assess value. RADAR presents a seven-level hierarchy, providing radiologists, researchers, and policymakers with a structured approach to the comprehensive assessment of value in radiology AI. RADAR is designed to be dynamic and meet the different valuation needs throughout the AI's lifecycle. Initial phases like technical and diagnostic efficacy (RADAR-1 and RADAR-2) are assessed pre-clinical deployment via in silico clinical trials and cross-sectional studies. Subsequent stages, spanning from diagnostic thinking to patient outcome efficacy (RADAR-3 to RADAR-5), require clinical integration and are explored via randomized controlled trials and cohort studies. Cost-effectiveness efficacy (RADAR- 6) takes a societal perspective on financial feasibility, addressed via health-economic evaluations. The final level, RADAR-7, determines how prior valuations translate locally, evaluated through budget impact analysis, multi-criteria decision analyses, and prospective monitoring. The RADAR framework offers a comprehensive framework for valuing radiology AI. Its layered, hierarchical structure, combined with a focus on local relevance, aligns RADAR seamlessly with the principles of value-based radiology."
查看更多>>摘要：A new study on robotics is now available. According to news reporting originating from Hangzhou, People's Republic of China, by NewsRx correspondents, research stated, "Currently, most service robots typically receive and execute commands in a passive manner, which is unsuitable for more meaningful Human-Robot Interaction (HRI)." Financial supporters for this research include The Key Research And Development Project of Zhejiang Province; The Fundamental Research Funds For The Provincial Universities of Zhejiang.
查看更多>>摘要：Research findings on Machine Learning are discussed in a new report. According to news reporting originating in London, United Kingdom, by NewsRx journalists, research stated, "Thermal spraying, an important industrial surface manufacturing process in sectors such as aerospace, energy and biomedical, remains a skill intensive process often involving multiple trial runs impacting the yield. The core research challenge in digitalisation of thermal spraying process lies in instrumenting the manufacturing platform as the process includes harsh conditions, including UV Rays, high-plasma temperature, dusty chemical environment, and spray booth inaccessibility." Financial supporters for this research include UK Research & Innovation (UKRI), Hubert Curien Partnership award 2022 from the British Council, International exchange Cost Share award by the Royal Society, Royal Academy, Eusko Jaurlaritza.
查看更多>>摘要：Fresh data on Robotics are presented in a new report. According to news reporting from Ghent, Belgium, by NewsRx journalists, research stated, "Estimating the execution time of assembly task sequences of a new geometric model is an essential prerequisite for task allocation and resource planning decisions in smart multi-robotic assembly cells. This paper discusses an optimization-based method to estimate the execution time of a full sequence of assembly tasks, including picking, aligning, and insertion." Financial support for this research came from Higher Education Commision, Pakistan.
查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating from Harbin, People's Republic of China, by NewsRx correspondents, research stated, "In this paper, we investigated the diffusion migration behavior of single atoms in an aluminum matrix using a machine-learning (ML)-accelerated first-principles calculation method. Initially, we used density functional theory to investigate the diffusion migration behavior of 30 individual atoms within the aluminum matrix." Financial support for this research came from Science Foundation of National Key Laboratory of Science and Technology on Advanced Composites in Special Environments.
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Dublin, Ireland, by NewsRx correspondents, research stated, "Lower extremity open revascularization is a treatment option for peripheral artery disease that carries significant peri-operative risks; however, outcome prediction tools remain limited. Using machine learning (ML), we developed automated algorithms that predict 30-day outcomes following lower extremity open revascularization." Financial supporters for this research include Ontario Ministry of Health and Long-Term Care, Physicians' Services Incorporated Foundation, Canadian Institutes of Health Research, Brigham and Women's Hospital Heart and Vascular Center.
查看更多>>摘要：New research on Adenomas is the subject of a report. According to news reporting originating from Kocaeli, Turkey, by NewsRx correspondents, research stated, "To evaluate the performances of machine learning using semantic and radiomic features from magnetic resonance imaging data to distinguish cystic pituitary adenomas (CPA) from Rathke's cleft cysts (RCCs). The study involved 65 patients diagnosed with either CPA or RCCs." Our news editors obtained a quote from the research from Kocaeli University, "Multiple observers independently assessed the semantic features of the tumors on the magnetic resonance images. Radiomics features were extracted from T2-weighted, T1-weighted, and T1-contrast-enhanced images. Machine learning models, including Support Vector Machines (SVM), Logistic Regression (LR), and Light Gradient Boosting (LGB), were then trained and validated using semantic features only and a combination of semantic and radiomic features. Statistical analyses were carried out to compare the performance of these various models. Machine learning models that combined semantic and radiomic features achieved higher levels of accuracy than models with semantic features only. Models with combined semantic and T2- weighted radiomics features achieved the highest test accuracies (93.8%, 92.3%, and 90.8% for LR, SVM, and LGB, respectively). The SVM model combined semantic features with T2-weighted radiomics features had statistically significantly better performance than semantic features only ( = 0.019)."
查看更多>>摘要：Fresh data on Robotics are presented in a new report. According to news reporting out of Beijing, People's Republic of China, by NewsRx editors, research stated, "Tracking-and-inserting a moving peg using a robot manipulator is a challenging task in manufacturing. In the past decades, various visual-based methods have been proposed for robotic manipulating static targets, which usually ignore the time delay in robot command transmission and image processing." Financial supporters for this research include National Natural Science Foundation of China (NSFC), Beijing Natural Science Foundation, key laboratory of spaceflight dynamics technology Foundation.
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