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    Studies from Massachusetts Institute of Technology Further Understanding of Robo tics and Automation (Indoor and Outdoor 3d Scene Graph Generation Via Language-e nabled Spatial Ontologies)

    33-34页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Robotics - Roboti cs and Automation are discussed in a new report. According to news reporting ori ginating from Cambridge, Massachusetts, by NewsRx correspondents, research state d, "This letter proposes an approach to build 3D scene graphs in arbitrary indoo r and outdoor environments. Such extension is challenging; the hierarchy of conc epts that describe an outdoor environment is more complex than for indoors, and manually defining such hierarchy is time-consuming and does not scale." Financial support for this research came from ARL DCIST Program. Our news editors obtained a quote from the research from the Massachusetts Insti tute of Technology, "Furthermore, the lack of training data prevents the straigh tforward application of learning-based tools used in indoor settings. To address these challenges, we propose two novel extensions. First, we develop methods to build a spatial ontology defining concepts and relations relevant for indoor an d outdoor robot operation. In particular, we use a Large Language Model (LLM) to build such an ontology, thus largely reducing the amount of manual effort requi red. Second, we leverage the spatial ontology for 3D scene graph construction us ing Logic Tensor Networks (LTN) to add logical rules, or axioms (e.g., 'a beach contains sand'), which provide additional supervisory signals at training time t hus reducing the need for labelled data, providing better predictions, and even allowing predicting concepts unseen at training time."
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    Investigators at University of Udine Detail Findings in Robotics (How the Social Robot Sophia Is Mediated By a Youtube Video)

    36-36页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Robotics. According to news reporting from Udine, Italy, by NewsRx journalists, research stated, "In robotics, a field of research still populated by prototypes , much of the research is made through videos and pictures of robots. We study h ow the highly human-like robot Sophia is perceived through a YouTube video." The news correspondents obtained a quote from the research from the University o f Udine, "Often researchers take for granted in their experiments that people pe rceive humanoids as such. With this study we wanted to understand to what extent a convenience sample of university students perceive Sophia's human-likeness; s econd, we investigated which mental capabilities and emotions they attribute to her; and third, we explored the possible uses of Sophia they imagine. Our findin gs suggest that the morphological human-likeness of Sophia, through the video, i s not salient in the Sophia's representations of these participants. Only some m ental functions are attributed to Sophia and no emotions."
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    Universitat Jaume I Researcher Describes Research in Robotics (Towards Fish Welf are in the Presence of Robots: Zebrafish Case)

    37-38页
    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 ro botics. According to news reporting out of the Universitat Jaume I by NewsRx edi tors, research stated, "Zebrafish (Danio rerio) have emerged as a valuable anima l model for neurobehavioral research, particularly in the study of anxiety-relat ed states." Funders for this research include Generalitat Valenciana; Universitat Jaume I; M inisterio De Ciencia, Innovacion Y Universidades. The news journalists obtained a quote from the research from Universitat Jaume I : "This article explores the use of conceptual models to investigate stress, fea r, and anxiety in zebrafish induced by bio-inspired mini-robotic fish with diffe rent components and designs. The objective is to optimize robotic biomimicry and its impact on fish welfare."
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    New Machine Learning Findings from Guangdong University of Technology Described (Machine Learning and Dft Coupling: a Powerful Approach To Explore Organic Amine Catalysts for Ringopening Polymerization Reaction)

    38-39页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting from Guangdong, People's Republic of Chi na, by NewsRx journalists, research stated, "Recently, using well-known data to drive the chemical feature of catalysts for the specified reaction has emerged a s a prevalent approach in catalysis science. Amines as essential compounds play crucial roles in living organisms, pharmaceutical, agricultural applications, an d various chemical reactions." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Open Project of State Key Labo- ratory of Inorganic Synthesi s and Preparation of Jilin University, Guangdong Basic and Applied Basic Researc h Foundation.
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    Semmelweis University Reports Findings in Artificial Intelligence (Validation of Artificial Intelligence Application for Dental Caries Diagnosis on Intraoral Bi tewing and Periapical Radiographs)

    39-40页
    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 originating from Budapest, Hunga ry, by NewsRx correspondents, research stated, "This study aimed to assess the r eliability of AI-based Diagnocat system that assists the healthcare processes in the diagnosis of caries on intraoral radiographs. The proximal surfaces of the 323 selected teeth on the intraoral radiographs were evaluated by two independen t observers using the AI-based Diagnocat system." Our news journalists obtained a quote from the research from Semmelweis Universi ty, "The presence or absence of carious lesions was recorded during Phase 1. Aft er 4 months, the AI-aided human observers evaluated the same radiographs (Phase 2), and the advanced convolutional neural network (CNN) reassessed the radiograp hic data (Phase 3). Subsequently, data reflecting human disagreements were exclu ded (Phase 4). For each phase, the Cohen and Fleiss kappa values, as well as the sensitivity, specificity, positive and negative predictive values, and diagnost ic accuracy of Diagnocat, were calculated. During the four phases, the range of Cohen kappa values between the human observers and Diagnocat were k=0.66-1, k=0. 58-0.7, and k=0.49-0.7. The Fleiss kappa values were k=0.57-0.8. The sensitivity , specificity and diagnostic accuracy values ranged between 0.51-0.76, 0.88-0.97 and 0.76-0.86, respectively. The Diagnocat CNN supports the evaluation of intra oral radiographs for caries diagnosis, as determined by consensus between human and AI system observers."
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    Studies from Anhui University of Technology Provide New Data on Intelligent Syst ems (Adaptive Local Neighborhood Information Based Efficient Fuzzy Clustering Ap proach)

    40-41页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in Machine Lea rning - Intelligent Systems. According to news reporting originating in Ma'ansha n, People's Republic of China, by NewsRx journalists, research stated, "The purp ose of clustering is to partition data similar with each other into a same group and partition data dissimilar with each other into different groups." Financial supporters for this research include Educational Commission of Anhui P rovince, Anhui Province Collaborative Innovation Project, National Natural Scien ce Foundation of China (NSFC).
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    Studies from Henan University Further Understanding of Intelligent Systems (A Su rvey On Social Network's Anomalous Behavior Detection)

    41-42页
    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 Ma chine Learning - Intelligent Systems. According to news reporting originating in Luoyang, People's Republic of China, by NewsRx journalists, research stated, "T he onset of Web 3.0 has catalyzed the rapid advancement of social networking, tr ansforming platforms into essential elements deeply embedded within the fabric o f daily life. Researchers have proposed several methods for detecting anomalous behaviors in various scenarios." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of China (NSFC), Henan P rovince Science Fund for Distinguished Young Scholars.
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    Researchers from Xidian University Detail New Studies and Findings in the Area o f Computational Intelligence (Apr-net Tracker: Attention Pyramidal Residual Netw ork for Visual Object Tracking)

    42-43页
    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 Machine Learn ing - Computational Intelligence have been published. According to news reportin g out of Guangzhou, People's Republic of China, by NewsRx editors, research stat ed, "Visual object tracking has attracted much attention thanks to its remarkabl e capability to identify a moving target accurately in real-world video scenario s. Recently, tracking performance has improved significantly." Financial support for this research came from State Scholarship Fund.
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    New Computational Intelligence Findings from Hebei Agricultural University Discu ssed (A Generative Adversarial Networks Model Based Evolutionary Algorithm for M ultimodal Multi-objective Optimization)

    43-44页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Machine Learning - Compu tational Intelligence have been published. According to news reporting from Baod ing, People's Republic of China, by NewsRx journalists, research stated, "The ke y to solving multimodal multi-objective optimization problems is to achieve good diversity in the decision space. However, the existing algorithms usually adopt the reproduction operation based on random mechanism, which do not make full us e of the distribution features of promising solutions in the population, resulti ng in the defects of the diversity of the obtained Parteo optimal solution sets. " Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from Hebei Agricultur al University, "In order to solve the above problem, this paper proposes a multi modal multi-objective optimization evolutionary algorithm (MMOEA) based on gener ative adversarial networks (GANs). Specifically, we firstly design a classificat ion strategy to distinguish good solutions from poor solutions. The solutions in the population are classified as real samples and fake samples by non-dominated selection sorting based on special crowding distance, and the training data of GANs are obtained. Secondly, a GANs-based offspring generation method is propose d. Through the adversarial training of GANs, the generator can simulate the dist ribution of promising solutions in the population and generate offspring with go od diversity. Thirdly, an environment selection strategy based on GANs is constr ucted. By sorting the classification probability of the solutions output by the discriminator, the population are selected and updated."
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    Researcher from China University of Geosciences Publishes Findings in Machine Le arning (A machine learning approach to discrimination of igneous rocks and ore d eposits by zircon trace elements)

    45-45页
    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 new report. According to news reporting out of Beijing, Pe ople's Republic of China, by NewsRx editors, research stated, "The mineral zirco n has a robust crystal structure, preserving a wealth of geological information through deep time. Traditionally, trace elements in magmatic and hydrothermal zi rcon have been employed to distinguish between different primary igneous or meta llogenic growth fluids." The news reporters obtained a quote from the research from China University of G eosciences: "However, classical approaches based on mineral geochemistry are not only time consuming but often ambiguous due to apparent compositional overlap f or different growth environments. Here, we report a compilation of 11 004 zircon trace element measurements from 280 published articles, 7173 from crystals in i gneous rocks, and 3831 from ore deposits. Geochemical variables include Hf, Th, U, Y, Ti, Nb, Ta, and the REEs. Igneous rock types include kimberlite, carbonati te, gabbro, basalt, andesite, diorite, granodiorite, dacite, granite, rhyolite, and pegmatite. Ore types include porphyry Cu-Au-Mo, skarn-type polymetallic, int rusion-related Au, skarn-type Fe-Cu, and Nb-Ta deposits. We develop Decision Tre e, XGBoost, and Random Forest algorithms with this zircon geochemical informatio n to predict lithology or deposit type. The F1-score indicates that the Random F orest algorithm has the best predictive performance for the classification of bo th lithology and deposit type."
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