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    Reports from University of Science and Technology Beijing Add New Data to Findin gs in Machine Learning (Synchronously Enhancing the Strength, Toughness, and Str ess Corrosion Resistance of Highend Aluminum Alloys Via Interpretable Machine . ..)

    1-2页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating in Beijing, People’s Re public of China, by NewsRx journalists, research stated, “Strength, toughness, a nd stress corrosion resistance are critical properties of aluminum alloys for hi gh-end equipment manufacturing. Unfortunately, the situation of complex alloy co mposition, diverse aging systems, and conflicting property relationships hinder the synchronous enhancement of three properties.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from the University of Sci ence and Technology Beijing, “Here, we proposed an interpretable machine learnin g design strategy for high-end aluminum alloy. The critical intrinsic factors an d explicit laws of elements affecting the ultimate tensile strength (UTS), fract ure toughness (KIC), and stress corrosion sensitivity factor (ISSRT) of alloys w ere excavated: The elements with large number of electrons in d-valence electron orbitals, high boiling point, and low nuclear electron distance help enhance th e UTS; The elements with low density and minimized difference in first ionizatio n energy with aluminum help improve the KIC; The elements with high diffusion ac tivation energy in aluminum and high corrosion potential in seawater help reduce the ISSRT. Based on the above findings, three microalloying elements of Ti, Cr, and Zr, which have the remarkable combined effect of enhancing synchronously th e three properties, were selected, and a new advanced aluminum alloy Al-10.50Zn- 2.31Mg-1.56Cu-0.09Ti-0.15Cr-0.10Zr was designed. The UTS, KIC, and ISSRT were 76 0 +/- 4 MPa, 34.9 +/- 0.3 MPa & sdot;m1/2, and 13.3 % +/- 1.7 %, respectively, after RRA treatment. Microstructure analys is revealed that the new alloy had almost no micron secondary phase after RRA tr eatment, reducing the sites for pitting and cavity formation. The addition of Ti , Cr, and Zr formed dispersoids Al18(Cr, Ti)2Mg3 and Al3Zr, which contributed to the synchronous improvement of strength, toughness, and stress corrosion resist ance.”
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    New Findings in Machine Learning Described from Murdoch University (Lora Localis ation Using Single Mobile Gateway)

    2-3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 Machine Learning. According to news reporting originating in Murdoch, Australia, by NewsRx journalists, research stated, “Effective use of GPS and mobile networ ks for localisation in rangeland areas is constrained by their high power consum ption and high deployment costs. Long-range (LoRa), a low -power wide area netwo rk (LPWAN) technology, can be employed to mitigate these challenges.” The news reporters obtained a quote from the research from Murdoch University, “ In contrast to prior research where the prevalent approaches entail multiple gat eways. This work proposes a valuable methodology focused on a single mobile LoRa gateway for localisation. A particle filtering and machine learning -based pipe line is employed to map the distance between a target node and the gateway from the received signal strength indicator (RSSI). Particle filtering is used to red uce the impact of noise on the RSSI values. Then, several machine learning techn iques, such as support vector machines, random forest, and k -nearest neighbour, are used on the RSSI values to estimate the distance. The estimated distance is then used for tracking using a centroid pseudotrilateration method. The propose d method was tested in a real -world semi -line -of -sight setting, using three datasets generated by LoRaWAN-specified hardware components and a server. Two fo rms of experiments were performed: active searching and passive monitoring. We p ropose an iterative estimation process to address the dilution of precision caus ed by the initial positions of the gateway required for active searching applica tions. The results show that active searching typically requires 2 to 3 hops to reach a target node.”
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    Study Results from National University of Lesotho Update Understanding of Artifi cial Intelligence (Do in-service teachers accept artificial intelligence-driven technology? The mediating role of school support and resources)

    3-3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 artificial intelligence is now available. According to news reporting out of National University of Les otho by NewsRx editors, research stated, “This study investigates the acceptance and utilization of artificial intelligence (AI) among in-service teachers in Le sotho, focusing on the mediating role of school support and resources (SSR). In Lesotho’s educational landscape, which is characterized by a growing interest in technology integration, this study fills an essential gap in the existing liter ature by exploring in-service teachers’ perspectives on AI adoption and the medi ating influence of SSR.” Our news reporters obtained a quote from the research from National University o f Lesotho: “Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, the study adopts a cross-sectional design, collec ting data from a sample of 315 in-service teachers through online surveys. The d ata was analyzed using maximum likelihood estimation. The results reveal a subst antial positive relationship between perceived usefulness, perceived ease of use , and a positive attitude towards AI, with SSR playing a pivotal role as a compl ementary mediator in these connections. However, the study identifies a non-sign ificant relationship between technical proficiency and behavioral intention, sug gesting a need for further investigation into the technical skills essential for effective AI integration. The results highlight the critical role of SSR in sha ping in-service teachers’ intentions to use AI in their teaching practices. As a result, the study recommends tailored continuous professional development progr ams and collaborative learning communities to enhance teachers’ skills.”
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    Recent Findings in Machine Learning Described by a Researcher from Arab American University (An Adaptive Security Framework for Internet of Things Networks Leve raging SDN and Machine Learning)

    4-4页
    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 from Arab American Universit y by NewsRx journalists, research stated, “The Internet of Things (IoT) is expan ding rapidly with billions of connected devices worldwide, necessitating robust security solutions to protect these systems.” The news correspondents obtained a quote from the research from Arab American Un iversity: “This paper proposes a comprehensive and adaptive security framework c alled Enhanced Secure Channel Authentication using random forests and software-d efined networking (SCAFFOLD), tailored for IoT environments. The framework estab lishes secure communication channels between IoT nodes using software-defined ne tworking (SDN) and machine learning techniques. The key components include encry pted channels using session keys, continuous traffic monitoring by the SDN contr oller, ensemble machine-learning for attack detection, precision mitigation via SDN reconfiguration, and periodic reauthentication for freshness. A mathematical model formally defines the protocol.”
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    Data from Escuela Politecnica Nacional Provide New Insights into Intelligent Sys tems (CNN-LSTM and post-processing for EMGbased hand gesture recognition)

    5-5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 intelligent s ystems have been published. According to news reporting from Quito, Ecuador, by NewsRx journalists, research stated, “Hand Gesture Recognition (HGR) using elect romyography (EMG) signals is a challenging problem due to the variability and no ise in the signals across individuals.” Financial supporters for this research include Escuela Politecnica Nacional. The news journalists obtained a quote from the research from Escuela Politecnica Nacional: “This study addresses this challenge by examining the effect of incor porating a post-processing algorithm, which filters the sequence of predictions and removes spurious labels, on the performance of a HGR model based on spectrog rams and Convolutional Neural Networks (CNN). The study also compares CNN vs CNN -LSTM to assess the influence of the memory cells on the model. The EMG-EPN-612 dataset, which contains measurements of EMG signals for 5 hand gestures from 612 subjects, was used for training and testing. The results showed that the post-p rocessing algorithm increased the recognition accuracy by 41.86% f or the CNN model and 24.77% for the CNN-LSTM model. The inclusion of the memory cells increased accuracy by 3.29%, but at the cost of 53 times more learnables. The CNN-LSTM model with post-processing achieved a me an recognition accuracy of 90.55% (SD=9.45%).”
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    Reports Outline Machine Learning Study Results from Guizhou Normal University (I dentifying Key Features for Predicting Glassforming Ability of Bulk Metallic Gl asses Via Interpretable Machine Learning)

    6-6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 Machine Learning are discussed in a new report. According to news reporting from Guiyang, People’ s Republic of China, by NewsRx journalists, research stated, “Bulk metallic glas ses (BMGs) have been receiving extensive attention in the community of physics a nd materials science due to their attractive properties. The traditional trial-a nd-error approach is inefficient in designing good BMGs, then it is imperative t o elaborate a prediction scheme to accelerate the development of BGMs.” Financial supporters for this research include National Key R&D Pro gram of China, National Natural Science Foundation of China (NSFC).
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    Investigators at KTH Royal Institute of Technology Describe Findings in Robotics and Automation (Dufomap: Efficient Dynamic Awareness Mapping)

    7-7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 - Robotics and Automation. According to news reporting out of Stockholm , Sweden, by NewsRx editors, research stated, “The dynamic nature of the real wo rld is one of the main challenges in robotics. The first step in dealing with it is to detect which parts of the world are dynamic.” Financial support for this research came from Wallenberg AI, Autonomous Systems and Software Program.
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    National University of Singapore Reports Findings in Depression (MicroRNA classi fication and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach)

    8-9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 Mental Health Diseases and Conditions - Depression is the subject of a report. According to news repor ting out of Singapore, Singapore, by NewsRx editors, research stated, “Major dep ressive disorder (MDD) is notably underdiagnosed and undertreated due to its com plex nature and subjective diagnostic methods. Biomarker identification would he lp provide a clearer understanding of MDD aetiology.”
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    Study Findings from University of Pavia Provide New Insights into Machine Learni ng (GPT classifications, with application to credit lending)

    8-8页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Pavia, Italy, by NewsRx editors, research stated, “Generative Pre-trained Transformers (GPT) a nd Large language models (LLMs) have made significant advancements in natural la nguage processing in recent years.” Funders for this research include European Commission. Our news correspondents obtained a quote from the research from University of Pa via: “The practical applications of LLMs are undeniable, rendering moot any deba te about their impending influence. The power of LLMs has made them similar to m achine learning models for decision-making problems. In this paper, we focus on binary classification which is a common use of ML models, particularly in credit lending applications. We show how a GPT model can perform almost as accurately as a classical logistic machine learning model but with a much lower number of s ample observations.”
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    Studies from Beihang University Describe New Findings in Symbolic Computation (S tability and Chaos of the Duopoly Model of Kopel: a Study Based On Symbolic Comp utations)

    9-10页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Symbolic Computation are presented in a new report. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “Since Kopel’s duopoly m odel was proposed about 3 decades ago, there are almost no analytical results on the equilibria and their stability in the asymmetric case. The first objective of our study is to fill this gap.” Financial support for this research came from Philosophy and Social Science Foun dation of Guangdong. Our news journalists obtained a quote from the research from Beihang University, “This paper analyzes the asymmetric duopoly model of Kopel analytically by usin g several tools based on symbolic computations.We discuss the possibility of th e existence of multiple positive equilibria and establish conditions for a given number of positive equilibria to exist. The possible positions of the equilibri a in Kopel’s model are also explored. Furthermore, in the asymmetric model of Ko pel, if the duopolists adopt the best response reactions or homogeneous adaptive expectations, we establish conditions for the local stability of equilibria for the first time. The occurrence of chaos in Kopel’s model seems to be supported by observations through numerical simulations, which, however, is challenging to prove rigorously.”
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