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    Sumy State University Researchers Update Understanding of Artificial Intelligenc e (Smart technologies in banking)

    20-21页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting from Sumy State Universi ty by NewsRx journalists, research stated, “The article is aimed at the current issues of using smart technologies and innovative approach during evolution and transformation processes in banking. The study identifies the special place of t his topic for achieving a high level of efficiency and competitiveness of banks and characterizes the impact of the introduction of technological approaches on the customer base and its perception of banking products.” Our news correspondents obtained a quote from the research from Sumy State Unive rsity: “The main functions of banking innovations in this area are analyzed and the justification of their feasibility at the present stage of economic developm ent is provided. A number of the most promising technologies and approaches to b anking activities are allocated, namely: contactless payment, digital wallets, b iometric identification, person-to-person payments, collective financing, omnich annel banking, interaction with FinTech companies, blockchain, big data, artific ial intelligence, smart machines, Internet of Things, behavioral banking, retail bank, application programming interfaces, multi-component bank, open banking, a ugmented reality, robotic automation, hybrid clouds. The relevance of the identi fied areas is proved based on their perception by analyzing the popularity of th e identified topics in Google search queries using the Google Trends tool. The p erception of smart technologies in banking by Internet users in the world and sp ecifically in Ukraine is investigated, which gave grounds to conclude that there is a significant interest in them, and therefore the expediency of further stud y and implementation in the activities of banks. It is identified that the most perspective technologies are biometric identification, blockchain, Internet of T hings, big data analysis, artificial intelligence, etc. Several technologies hav e been identified, namely, collective financing (crowdfunding), application prog ramming interfaces (APIs) and digital wallets, which are less popular in Ukraine than in the world in general, and therefore require detailed research and study of the relevance of their application in the domestic banking market. Possible directions for further innovative development of banking institutions based on t he use of smart technologies are proposed. Based on panel data for 60 banks of U kraine for the period 2014-2022, the author analyzes the correlations between th e indicators of the use of digital technologies and the financial performance of banks and builds regression dependencies of financial indicators of banks on th e indicator of the number of electronic means of payment in active circulation. The theoretical value of the study is to identify the most promising smart techn ologies and innovative approaches to banking business in modern conditions.”
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    University of Technology Researcher Provides New Insights into Robotics (Shadow Detection and Elimination for Robot and Machine Vision Applications)

    21-22页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in robotic s. According to news reporting originating from Baghdad, Iraq, by NewsRx corresp ondents, research stated, “Shadow removal is crucial for robot and machine visio n as the accuracy of object detection is greatly influenced by the uncertainty a nd ambiguity of the visual scene.”The news journalists obtained a quote from the research from University of Techn ology: “In this paper, we introduce a new algorithm for shadow detection and rem oval based on different shapes, orientations, and spatial extents of Gaussian eq uations. Here, the contrast information of the visual scene is utilized for shad ow detection and removal through five consecutive processing stages. In the firs t stage, contrast filtering is performed to obtain the contrast information of t he image. The second stage involves a normalization process that suppresses nois e and generates a balanced intensity at a specific position compared to the neig hboring intensities. In the third stage, the boundary of the target object is ex tracted, and in the fourth and fifth stages, respectively, the region of interes t (ROI) is highlighted and reconstructed.”
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    Study Data from Shandong University Update Knowledge of Machine Learning (A mult i-purpose reconstruction method based on machine learning for atmospheric neutri nos at JUNO)

    21-21页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in artificial intelli gence. According to news originating from Shandong University by NewsRx editors, the research stated, “The Jiangmen Underground Neutrino Observatory (JUNO) expe riment is designed to measure the neutrino mass ordering (NMO) using a 20-kton l iquid scintillator (LS) detector.” Our news reporters obtained a quote from the research from Shandong University: “Besides the precise measurement of the reactor neutrino’s oscillation spectrum, an atmospheric neutrino oscillation measurement in JUNO offers independent sens itivity for NMO, which can potentially increase JUNO’s total sensitivity in a jo int analysis. In this contribution, we present a novel multi-purpose reconstruct ion method for atmospheric neutrinos in JUNO at few-GeV based on a machine learn ing technique. This method extracts features related to event topology from PMT waveforms and uses them as inputs to machine learning models. A preliminary stud y based on the JUNO simulation shows good performances for event directionality reconstruction and neutrino flavor identification.”
      原文链接:
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    Study Data from University Pablo de Olavide Update Understanding of Artificial I ntelligence (A New Approach Based On Association Rules To Add Explainability To Time Series Forecasting Models)

    22-23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 Artificial Intelligence. According to news reporting from Seville, Spain, by New sRx journalists, research stated, “Machine learning and deep learning have becom e the most useful and powerful tools in the last years to mine information from large datasets. Despite the successful application to many research fields, it i s widely known that some of these solutions based on artificial intelligence are considered black -box models, meaning that most experts find difficult to expla in and interpret the models and why they generate such outputs.” Funders for this research include Spanish Government, Junta de Andalucia, Univer sidad Pablo de Olavide/CBUA. The news correspondents obtained a quote from the research from University Pablo de Olavide, “In this context, explainable artificial intelligence is emerging w ith the aim of providing black -box models with sufficient interpretability. Thu s, models could be easily understood and further applied. This work proposes a n ovel method to explain black -box models, by using numeric association rules to explain and interpret multi -step time series forecasting models. Thus, a multi -objective algorithm is used to discover quantitative association rules from the target model. Then, visual explanation techniques are applied to make the rules more interpretable.”
      原文链接:
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    New Findings Reported from Menlo College Describe Advances in Artificial Intelli gence (Convergence of artificial intelligence with social media: A bibliometric & qualitative analysis)

    23-24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 originating from Menl o College by NewsRx correspondents, research stated, “The integration of artific ial intelligence (AI) and social media has provided numerous benefits to busines ses, including improved audience analysis and content optimization. However, AI has facilitated the spread of misinformation, emphasizing the importance of taki ng a balanced approach that considers both the technology’s positive application s and its ethical risks.” The news journalists obtained a quote from the research from Menlo College: “Thi s paper looks at the intersection of AI and social media. The researchers use a mixed-method approach to analyze 1540 scholarly documents, combining bibliometri c and systematic literature review techniques. The goal of this research is to i dentify the most important topics and trends, as well as potential business valu es and implications, in the AI Social Media domain. The first stage of the resea rch involved a quantitative keyword co-occurrence analysis, which resulted in th e identification of ten dominant themes. These include Conversational Agents & User Experience, Human Emotion and Content Recommendation & Modera tion, Collective Intelligence in Emergency Management, Algorithmic Activism on s ocial media, Deep Fakes and Fake News, Generative Artificial Intelligence, Algor ithmic Bias in Content Moderation Systems, Deep Sentiment Analysis, Metaverse Te chnologies, and NLP & Mental Health Detection. Each identified the me is then subjected to a qualitative thematic literature review, which provides a more in-depth, contextspecific understanding of the associated findings.”
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    Hebei University of Engineering Researcher Highlights Research in Computational Intelligence (Research on Efficient Asymmetric Attention Module for Real-Time Se mantic Segmentation Networks in Urban Scenes)

    24-25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 co mputational intelligence. According to news originating from Hebei, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Currently, numerous high-precision models have been proposed for semantic segmentation, but the mode l parameters are large and the segmentation speed is slow.” Our news reporters obtained a quote from the research from Hebei University of E ngineering: “Realtime semantic segmentation for urban scenes necessitates a bal ance between accuracy, inference speed, and model size. In this paper, we presen t an efficient solution to this challenge, efficient asymmetric attention module net (EAAMNet) for the semantic segmentation of urban scenes, which adopts an as ymmetric encoder-decoder structure. The encoder part of the network utilizes an efficient asymmetric attention module to form the network backbone. In the decod ing part, we propose a lightweight multi-feature fusion decoder that can maintai n good segmentation accuracy with a small number of parameters. Our extensive ev aluations demonstrate that EAAMNet achieves a favorable equilibrium between segm entation efficiency, model parameters, and segmentation accuracy, rendering it h ighly suitable for real-time semantic segmentation in urban scenes.”
      原文链接:
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    Recent Studies from First Affiliated Hospital of Sun Yat-Sen University Add New Data to Machine Learning (A machine learning-based model for 'In-time' predictio n of periprosthetic joint infection)

    25-26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 from Guangzhou, Pe ople’s Republic of China, by NewsRx journalists, research stated, “Previous crit eria had limited value in early diagnosis of periprosthetic joint infection (PJI ). Here, we constructed a novel machine learning (ML)-derived, “in-time” diagnos tic system for PJI and proved its validity.” Financial supporters for this research include Basic And Applied Basic Research Foundation of Guangdong Province; National Natural Science Foundation of China.
      原文链接:
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    Findings from Northeast Forestry University Broaden Understanding of Machine Lea rning [Forest Smoke-Fire Net (FSF Net): A Wildfire Smoke Dete ction Model That Combines MODIS Remote Sensing Images with Regional Dynamic Brig htness Temperature ...]

    26-27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 originating from Harbin, People ’s Republic of China, by NewsRx correspondents, research stated, “Satellite remo te sensing plays a significant role in the detection of smoke from forest fires. However, existing methods for detecting smoke from forest fires based on remote sensing images rely solely on the information provided by the images, overlooki ng the positional information and brightness temperature of the fire spots in fo rest fires.” Our news journalists obtained a quote from the research from Northeast Forestry University: “This oversight significantly increases the probability of misjudgin g smoke plumes. This paper proposes a smoke detection model, Forest Smoke-Fire N et (FSF Net), which integrates wildfire smoke images with the dynamic brightness temperature information of the region. The MODIS_Smoke_ FPT dataset was constructed using a Moderate Resolution Imaging Spectroradiomete r (MODIS), the meteorological information at the site of the fire, and elevation data to determine the location of smoke and the brightness temperature threshol d for wildfires. Deep learning and machine learning models were trained separate ly using the image data and fire spot area data provided by the dataset. The per formance of the deep learning model was evaluated using metric MAP, while the re gression performance of machine learning was assessed with Root Mean Square Erro r (RMSE) and Mean Absolute Error (MAE). The selected machine learning and deep l earning models were organically integrated.”
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    Studies from University of Quebec Have Provided New Data on Machine Learning (Bl ockchain-Empowered Metaverse: Decentralized Crowdsourcing and Marketplace for Tr ading Machine Learning Data and Models)

    27-27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 Montreal, Canada, by Ne wsRx journalists, research stated, “The Metaverse relies on advanced machine lea rning (ML) techniques to facilitate the seamless mapping between the virtual and physical realms.” The news reporters obtained a quote from the research from University of Quebec: “ML-based technologies also enable metaverse service providers (MSPs) to offer a diverse range of intelligent virtual services to metaverse users (MUs). Howeve r, it can be challenging for MSPs to collect sufficient metaverse data to train ML models by themselves. As a result, MSPs can be interested in seeking contribu tions from MUs in both ML data and models. To address these challenges, we propo se MetaAICM, a blockchainbased framework that empowers the metaverse through tw o key components. Firstly, it incorporates a distributed crowdsourcing system th at allows MSPs to gather metaverse data and ML models from MUs. Secondly, it fea tures a decentralized marketplace, enabling MUs to proactively collect data and train ML models for sale using their metaverse devices and computing resources.”
      原文链接:
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    New Robotics and Automation Findings from Chinese Academy of Sciences Described (Rss: Robust Stereo Slam With Novel Extraction and Full Exploitation of Plane Fe atures)

    28-28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 originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Planar structures, prevalent in man-made environments, can be observed by a ca mera for significant periods of time due to their large spatial presence. These structures provide strong planar regularities for Simultaneous Localization and Mapping (SLAM) systems, facilitating long-term navigation.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
      原文链接:
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