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    Findings from Sichuan Agriculture University Broaden Understanding of Machine Learning (The Rapid Non-Destructive Differentiation of Different Varieties of Rice by Fluorescence Hyperspectral Technology Combined with Machine Learning)

    19-20页
    查看更多>>摘要：Investigators discuss new findings in artificial intelligence. According to news reporting from Sichuan Agriculture University by NewsRx journalists, research stated, “A rice classification method for the fast and non-destructive differentiation of different varieties is significant in research at present.” Financial supporters for this research include Sichuan Agricultural University. The news journalists obtained a quote from the research from Sichuan Agriculture University: “In this study, fluorescence hyperspectral technology combined with machine learning techniques was used to distinguish five rice varieties by analyzing the fluorescence hyperspectral features of Thai jasmine rice and four rice varieties with a similar appearance to Thai jasmine rice in the wavelength range of 475-1000 nm. The fluorescence hyperspectral data were preprocessed by a first-order derivative (FD) to reduce the background and baseline drift effects of the rice samples. Then, a principal component analysis (PCA) and t-distributed stochastic neighborhood embedding (t-SNE) were used for feature reduction and 3D visualization display. A partial least squares discriminant analysis (PLS-DA), BP neural network (BP), and random forest (RF) were used to build the rice classification models. The RF classification model parameters were optimized using the gray wolf algorithm (GWO).”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Research Findings from Ruhr-Universitat Bochum Update Understanding of Machine Learning (Influence of Sampling Methods on the Accuracy of Machine Learning Predictions Used for Strain- Dependent Slope Stability)

    20-21页
    查看更多>>摘要：Current study results on artificial intelligence have been published. According to news reporting out of Bochum, Germany, by NewsRx editors, research stated, “Supervised machine learning (ML) techniques have been widely used in various geotechnical applications.” The news reporters obtained a quote from the research from Ruhr-Universitat Bochum: “While much attention is given to the ML techniques and the specific geotechnical problem being addressed, the influence of sampling methods on ML performance has received relatively less scrutiny. This study applies supervised ML to the strain-dependent slope stability (SDSS) method for the prediction of the factor of safety (FoS) using hypoplasticity. It delves into different sampling strategies for training the ML model, emphasizing predictions of soil behavior in lower stress ranges. A novel sampling method is introduced to ensure a more representative distribution of samples in these ranges, which is challenging to achieve through traditional sampling approaches. The ML models were trained using traditional and modified sampling methods. Subsequently, slope stability analyses using SDSS were conducted with ML models trained from six different sampling methods.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    National Research Council of Canada Reports Findings in Machine Learning (Novel machine learning insights into the QM7b and QM9 quantum mechanics datasets)

    21-22页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating in Ottawa, Canada, by NewsRx journalists, research stated, “This paper (i) explores the internal structure of two quantum mechanics datasets (QM7b, QM9), composed of several thousands of organic molecules and described in terms of electronic properties, and (ⅱ) further explores an inverse design approach to molecular design consisting of using machine learning methods to approximate the atomic composition of molecules, using QM9 data. Understanding the structure and characteristics of this kind of data is important when predicting the atomic composition from physical-chemical properties in inverse molecular designs.” The news reporters obtained a quote from the research from the National Research Council of Canada, “Intrinsic dimension analysis, clustering, and outlier detection methods were used in the study. They revealed that for both datasets the intrinsic dimensionality is several times smaller than the descriptive dimensions. The QM7b data is composed of well-defined clusters related to atomic composition. The QM9 data consists of an outer region predominantly composed of outliers, and an inner, core region that concentrates clustered inliner objects. A significant relationship exists between the number of atoms in the molecule and its outlier/inliner nature. The spatial structure exhibits a relationship with molecular weight. Despite the structural differences between the two datasets, the predictability of variables of interest for inverse molecular design is high. This is exemplified by models estimating the number of atoms of the molecule from both the original properties and from lower dimensional embedding spaces. In the generative approach the input is given by a set of desired properties of the molecule and the output is an approximation of the atomic composition in terms of its constituent chemical elements. This could serve as the starting region for further search in the huge space determined by the set of possible chemical compounds. The quantum mechanic’s dataset QM9 is used in the study, composed of 133,885 small organic molecules and 19 electronic properties. Different multi-target regression approaches were considered for predicting the atomic composition from the properties, including feature engineering techniques in an auto-machine learning framework. High-quality models were found that predict the atomic composition of the molecules from their electronic properties, as well as from a subset of only 52.6% size. Feature selection worked better than feature generation.”
      原文链接:
    • NETL
    • NSTL

    King Faisal University Researcher Describes Advances in Machine Learning [Machine Learning Backpropagation Prediction and Analysis of the Thermal Degradation of Poly (Vinyl Alcohol)]

    22-23页
    查看更多>>摘要：Research findings on artificial intelligence are discussed in a new report. According to news reporting originating from Al Ahsa, Saudi Arabia, by NewsRx correspondents, research stated, “Thermogravimetric analysis (TGA) is crucial for describing polymer materials’ thermal behavior as a result of temperature changes.” Funders for this research include King Faisal University. The news correspondents obtained a quote from the research from King Faisal University: “While available TGA data substantiated in the literature significantly focus attention on TGA performed at higher heating rates, this study focuses on the machine learning backpropagation analysis of the thermal degradation of poly (vinyl alcohol), or PVA, at low heating rates, typically 2, 5 and 10 K/min, at temperatures between 25 and 600 °C. Initial TGA analysis showed that a consistent increase in heating rate resulted in an increase in degradation temperature as the resulting thermograms shifted toward a temperature maxima. At degradation temperatures between 205 and 405 °C, significant depths in the characterization of weight losses were reached, which may be attributed to the decomposition and loss of material content. Artificial neural network backpropagation of machine learning algorithms were used for developing mathematical descriptions of the percentage weight loss (output) by these PVA materials as a function of the heating rate (input 1) and degradation temperature (input 2) used in TGA analysis.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Researchers from Tsinghua University Report Recent Findings in Robotics (Elasto-geometrical Calibration of a Hybrid Mobile Robot Considering Gravity Deformation and Stiffness Parameter Errors)

    23-24页
    查看更多>>摘要：Data detailed on Robotics have been presented. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “Hybrid mobile robots, which combine the advantages of serial and parallel robots and have the ability to realize processing in situ, have considerable application potential in the field of processing and manufacturing. In this paper, a hybrid mobile robot used for wind turbine blade polishing is presented.” Financial supporters for this research include National Key R&D Program of China, National Natural Science Foundation of China (NSFC). Our news journalists obtained a quote from the research from Tsinghua University, “The robot combines an automated guided vehicle, a 2-DoF robotic arm, and a 3-RCU parallel module. To improve the accuracy, investigating the elasto-geometrical calibration of the robot is necessary. Considering that the 3-RCU parallel module has weak stiffness along the gravitational direction, the stiffness model was established to estimate the deformation caused by the gravity of the mobile platform, ball screws, and motors. Subsequently, a rigid-flexible coupling error model considering structural and stiffness parameter errors is established. Based on these, a parameter identification method for the simultaneous identification of structural and stiffness parameter errors is proposed herein. For the 2-DoF robotic arm with parallelogram mechanisms, an intuitive error model considering the posture error caused by the parallelogram mechanism errors is established. The regularized nonlinear least squares method was adopted for parameter identifica-tion. Thereafter, a compensation strategy for the hybrid mobile robot that comprehensively considers the pose errors of the 3-RCU parallel module and 2-DoF robotic arm is proposed. Finally, a verification experiment was performed on the prototype, and the results indicated that after elasto-geometrical calibration, the maximum/mean of the position and posture errors of the hybrid mobile robot decreased from 3.738 mm/2.573 mm to 0.109 mm/0.063 mm and 0.236 degrees/0.179 degrees to 0.030 degrees/0.013 degrees, respectively. Owing to the decrease in the robot pose errors, the quality of the polished surface was more uniform.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Research from Ming Chuan University Provides New Data on Pattern Recognition and Artificial Intelligence (All-Day Object Detection and Recognition for Blind Zones of Vehicles Using Deep Learning)

    24-25页
    查看更多>>摘要：Data detailed on pattern recognition and artificial intelligence have been presented. According to news reporting out of Ming Chuan University by NewsRx editors, research stated, “The neglect of perception ability to the surrounding traffic conditions has always been the major cause of traffic accidents and the inattention to blind spots is the most important factor during driving. Existing solutions are facing the problems of using expensive equipment, wrong classification of the target object type, not suitable for nighttime, and incorrectly determining if the target object is in the blind zones.” The news journalists obtained a quote from the research from Ming Chuan University: “This paper aims to improve driving perception ability by developing an all-day object detection and recognition system with more accurate performance for blind zones. The proposed method uses a general-purpose camera as a single input and a two-stage deep network architecture for object detection and recognition. The proposed system is based on a two-stage cascaded network structure. At first, the style conversion process is performed to convert the daytime and nighttime images with different brightness into consistent brightness. Then the objects in the visual blind zones are detected and identified. Therefore, the accuracy of object detection can be significantly improved.”
      原文链接:
    • NETL
    • NSTL
    • World Scientific

    Reports from Technical University of Moldova Describe Recent Advances in Artificial Intelligence (Decentralised Autonomous Society Through Large Language Models’ Based Agents: A Pathway To Empower Small Communities)

    25-26页
    查看更多>>摘要：Researchers detail new data in artificial intelligence. According to news reporting from Chisinau, Moldova, by NewsRx journalists, research stated, “This paper explores the concept of Decentralized Autonomous Society through the lens of Large Language Models focusing on the transformative potential of integrating these technologies.” The news reporters obtained a quote from the research from Technical University of Moldova: “The paper on the role of Large Language Models based agents in providing a versatile, responsive, and contextually intelligent resource within a Decentralized Autonomous Society, fostering intellectual exploration, assisting in complex tasks, and aiding real-time problem solving. One delves into their integration with Decentralized Autonomous Society infrastructures, including robotic and automated systems. While promising, the integration of Large Language Models and their agents into a Decentralized Autonomous Society poses several challenges, including infrastructure and connectivity limitations, information accuracy, artificial intelligence bias, privacy and data security, and ethical concerns. This paper critically discusses these issues and proposes potential solutions.”
      原文链接:
    • NETL
    • NSTL

    New Machine Learning Study Results from CGG Described (A new exploration tool in the search for native hydrogen and helium)

    26-27页
    查看更多>>摘要：A new study on artificial intelligence is now available. According to news reporting out of CGG by NewsRx editors, research stated, “Native hydrogen and helium have been considered important resources in assisting the energy transition.” Our news journalists obtained a quote from the research from CGG: “Hydrogen and helium seeps have been reported worldwide, which may indicate large reserves within the subsurface. However, generation of hydrogen and helium is complex; poorly understood and constrained for both generation processes and migration. One source of native hydrogen is ultramafic rocks, which have experienced serpentinization together with water radiolysis. In contrast, helium generation occurs as the result of the radioactive decay of uranium and thorium present within radiogenically enriched basement. An exploration tool, dedicated to identifying areas with the geological settings and conditions favourable for native hydrogen and helium generation, has been developed and tested. Several databases have been created and integrated as part of this study (geological and geochemical generation models) to support and focus the search for both hydrogen and helium.”
      原文链接:
    • NETL
    • NSTL

    New Robotics Study Findings Have Been Reported by Researchers at Chongqing University of Education (Enhancing Machine Vision: the Impact of a Novel Innovative Technology On Video Questionanswering)

    27-27页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting out of Chongqing, People’s Republic of China, by NewsRx editors, research stated, “The robot video questionanswering system is an artificial intelligence application that integrates computer vision and natural language processing technologies. Recently, it has received widespread attention, especially with the rapid development of large language models (LLMs).” Financial supporters for this research include Scientific and Technological Research Program of Chongqing Municipal Education Commission, Chongqing Engineering Laboratory of Children’s Big Data, Chongqing Engineering Research Center for Interactive Education Electronics, Chongqing Key Discipline of Electronic Information.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Researchers at Belgorod State Technological University Named after V.G. Shukhov Publish New Data on Robotics (Optimal Design of Lower Limb Rehabilitation System Based on Parallel and Serial Mechanisms)

    28-28页
    查看更多>>摘要：Fresh data on robotics are presented in a new report. According to news reporting out of Belgorod, Russia, by NewsRx editors, research stated, “This paper presents the structure and model of a hybrid modular structure of a robotic system for lower limb rehabilitation.” Funders for this research include State Assignment of Ministry of Science And Higher Education of The Russian Federation. The news correspondents obtained a quote from the research from Belgorod State Technological University Named after V.G. Shukhov: “It is made of two modules identical in structure, including an active 3-PRRR manipulator for moving the patient’s foot and a passive orthosis based on the RRR mechanism for supporting the lower limb. A mathematical model has been developed to describe the positions for the links of the active and passive mechanisms of two modules, as a function of the angles in the joints of the passive orthosis, considering constraints for attaching the active manipulators to the moving platform and their configurations. A method has been formulated for a parametric synthesis of the hybrid robotic system proposed with modular structure, taking into account the generated levels of parametric constraints depending on the ergonomic and manufacturability features.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi