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    Reports from Purdue University Provide New Insights into Robotics (Enhanced Visual Slam for Construction Robots By Efficient Integration of Dynamic Object Segmentation and Scene Semantics)

    20-20页
    查看更多>>摘要:Current study results on Robotics have been published. According to news reporting from West Lafayette, Indiana, by NewsRx journalists, research stated, "With the increasing adoption of autonomous mobile robots in the construction industry, accurate localization and mapping in dynamic construction environments have become paramount. This is typically tackled via Simultaneous Localization and Mapping (SLAM) techniques." The news correspondents obtained a quote from the research from Purdue University, "Primarily designed for static environments, traditional SLAM systems struggle to maintain robustness and accuracy in dynamic settings. To address this challenge, this study presents an enhanced visual SLAM system specifically tailored for dynamic construction environments. The proposed system, named vSLAM-Con, introduces an adaptive dynamic object segmentation method, utilizing an innovative AD-keyframes selection mechanism grounded on optical flow magnitude to diminish computational overhead while preserving competitive tracking accuracy. Additionally, a semantic-based feature update process is developed, leveraging scene understanding and continuous observation to augment the reliability of tracking features. This system's performance, evaluated on both an established public benchmark and a custom construction dataset, shows substantial improvements over the baseline and competitive results with the state-of-theart algorithms. More importantly, it largely reduces the processing time compared to state-of-the-arts, demonstrating robust tracking performance even under highly dynamic conditions."

    China Academy of Building Research Researcher Reveals New Findings on Machine Learning (Machine Learning Prediction Model for Boundary Transverse Reinforcement of Shear Walls)

    21-21页
    查看更多>>摘要:New study results on artificial intelligence have been published. According to news originating from Beijing, People's Republic of China, by NewsRx editors, the research stated, "Due to their roles as efficient lateral force-resisting systems, reinforced concrete shear walls exert a tremendous degree of influence on the overall seismic performance of buildings." Funders for this research include Beijing Natural Science Foundation; Special Funding of China Academy of Building Research. Our news journalists obtained a quote from the research from China Academy of Building Research: "The ability to predict the boundary transverse reinforcement of shear walls is critical to the seismic design process, as well as in the overall evaluation and retrofitting of existing buildings. Contemporary empirical models attain low predictive accuracy, with an inability to capture nonlinearity between boundary transverse reinforcement and different influencing variables. This study proposes a boundary transverse reinforcement prediction model for shear walls with boundary elements based on the demand of ductility. Using the extreme gradient boosting machine learning algorithm and 501 samples, some 52 input variables are considered, and a subset with six features is selected, monitored, and analyzed using both internal methods (gain and cover) and external methods. The results (R2=0.884) display superior predictive capacity compared with existing models. Interpretation and error analysis are performed."

    People's Hospital of Guangxi Zhuang Autonomous Region Reports Findings in Machine Learning (An early screening model for preeclampsia: utilizing zero-cost maternal predictors exclusively)

    22-22页
    查看更多>>摘要:New research on Machine Learning is the subject of a report. According to news reporting originating in Nanning, People's Republic of China, by NewsRx journalists, research stated, "To provide a reliable, low-cost screening model for preeclampsia, this study developed an early screening model in a retrospective cohort (25,709 pregnancies) and validated in a validation cohort (1760 pregnancies). A data augmentation method (a-inverse weighted-GMM + RUS) was applied to a retrospective cohort before 10 machine learning models were simultaneously trained on augmented data, and the optimal model was chosen via sensitivity (at a false positive rate of 10%)."

    University of Novi Sad Researcher Furthers Understanding of Machine Learning (Vineyard Zoning and Vine Detection Using Machine Learning in Unmanned Aerial Vehicle Imagery)

    23-24页
    查看更多>>摘要:Investigators publish new report on artificial intelligence. According to news reporting originating from Novi Sad, Serbia, by NewsRx correspondents, research stated, "Precision viticulture systems are essential for enhancing traditional intensive viticulture, achieving high-quality results, and minimizing costs." The news journalists obtained a quote from the research from University of Novi Sad: "This study explores the integration of Unmanned Aerial Vehicles (UAVs) and artificial intelligence in precision viticulture, focusing on vine detection and vineyard zoning. Vine detection employs the YOLO (You Only Look Once) deep learning algorithm, achieving a remarkable 90% accuracy by analysing UAV imagery with various spectral ranges from various phenological stages. Vineyard zoning, achieved through the application of the K-means algorithm, incorporates geospatial data such as the Normalized Difference Vegetation Index (NDVI) and the assessment of nitrogen, phosphorus, and potassium content in leaf blades and petioles. This approach enables efficient resource management tailored to each zone's specific needs. The research aims to develop a decision-support model for precision viticulture. The proposed model demonstrates a high vine detection accuracy and defines management zones with variable weighting factors assigned to each variable while preserving location information, revealing significant differences in variables."

    Findings from Kazimierz Wielki University Yields New Findings on Artificial Intelligence (Internet of Things and Ai-based Optimization Within Industry 4.0 Paradigm)

    23-23页
    查看更多>>摘要:New research on Artificial Intelligence is the subject of a report. According to news originating from Bydgoszcz, Poland, by NewsRx correspondents, research stated, "By reviewing the current state of the art, this article opens a Special Section titled ‘The Internet of Things and AIdriven optimization in the Industry 4.0 paradigm'. The topics of this section are part of the broader issues of integration of IoT devices, cloud computing, big data analytics, and artificial intelligence to optimize industrial processes and increase efficiency." Financial support for this research came from Kazimierz Wielki University.

    University of Lisbon Faculty of Sciences Reports Findings in Artificial Intelligence (Explaining protein-protein interactions with knowledge graph-based semantic similarity)

    24-25页
    查看更多>>摘要:New research on Artificial Intelligence is the subject of a report. According to news originating from Lisbon, Portugal, by NewsRx correspondents, research stated, "The application of artificial intelligence and machine learning methods for several biomedical applications, such as protein-protein interaction prediction, has gained significant traction in recent decades. However, explainability is a key aspect of using machine learning as a tool for scientific discovery."

    Arizona State University Reports Findings in Lyme Disease (Highly heterogenous humoral immune response in Lyme disease patients revealed by broad machine learning-assisted antibody binding profiling with random peptide arrays)

    25-26页
    查看更多>>摘要:New research on Tick-Borne Diseases and Conditions - Lyme Disease is the subject of a report. According to news reporting originating from Tempe, Arizona, by NewsRx correspondents, research stated, "Lyme disease (LD), a rapidly growing public health problem in the US, represents a formidable challenge due to the lack of detailed understanding about how the human immune system responds to its pathogen, the bacterium. Despite significant advances in gaining deeper insight into mechanisms the pathogen uses to evade immune response, substantial gaps remain."

    Studies from University of Economics Update Current Data on Robotics (Adaptive Control For Mobile Robots Based On Inteligent Controller)

    26-27页
    查看更多>>摘要:A new study on robotics is now available. According to news reporting originating from the University of Economics by NewsRx correspondents, research stated, "The paper presents three position controller designs for a mobile robot. The first is a position controller using a classic PID controller." Our news correspondents obtained a quote from the research from University of Economics: "The second is the position controller is designed based on optimal three coefficients for PID controller by fuzzy logic control (FLC). The last, the mobile robot is moved according to the trajectories set by the FLC controller. All three controllers have two state variables (position error and position deviation derivative and one output variable, velocity) and one velocity output variable of the robot. The robot is moved according to the trajectories set based on the PID-FLC controller flow fuzzy rules with a 7x7 matrix to the optimal three coefficients of the PID controller. Meanwhile, the FLC controller is done by a 9x9 matrix rule. Evaluated the efficiency of PID-FLC and FLC controllers are compared to classical PID controllers."

    Nanjing University of Information Science and Technology (NUIST) Researcher Reports on Findings in Artificial Intelligence (Impact of Artificial Intelligence on Manufacturing Industry Global Value Chain Position)

    27-28页
    查看更多>>摘要:Fresh data on artificial intelligence are presented in a new report. According to news originating from Nanjing, People's Republic of China, by NewsRx correspondents, research stated, "Using transnational panel data from 61 nations and regions from 2000 to 2019, this article empirically examines both the influence of artificial intelligence on the Global Value Chain as it pertains to the manufacturing industry and its mechanism of action." Financial supporters for this research include Humanities And Social Sciences Research Planning Foundation of China's Ministry of Education.

    Investigators at Beijing Institute of Technology Report Findings in Robotics (Risk Assessment Based On a Stpa-fmea Method: a Case Study of a Sweeping Robot)

    28-29页
    查看更多>>摘要:Investigators publish new report on Robotics. According to news reporting originating from Beijing, People's Republic of China, by NewsRx correspondents, research stated, "Despite rapid developments in the quality and safety of consumer products, the rise of intelligent household appliances, such as sweeping robots, has introduced new safety concerns. Considering ‘person-product-environment' elements and the complex systems of emerging consumer products, this study presents a new method of risk assessment for consumer products: systems theoretic process analysis (STPA)-failure mode and effects analysis (FMEA)."