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    Studies Conducted at Jiangsu Open University on Artificial Intelligence Recently Published (Modernization of Intellectual Property Discipline Governance Based on Multivariate Statistical Analysis Towards the Construction of a Powerful ...)

    40-40页
    查看更多>>摘要：Research findings on artificial intelligence are discussed in a new report. According to news reporting out of Jiangsu, People’s Republic of China, by NewsRx editors, research stated, “In this paper, after using the TF-IDF algorithm to calculate the weights of intellectual property keywords of digital content, the weights of fused word multi-features are improved to obtain the proportion of intellectual property keywords.” Our news editors obtained a quote from the research from Jiangsu Open University: “Based on intellectual property keywords, combining adversarial fingerprint generation and intellectual property authentication, an intellectual property protection model based on RCNN is constructed. From the perspective of strong nation-building, the research on intellectual property affecting the artificial intelligence industry is designed, and multivariate statistical analysis of scientific governance of intellectual property in the context of strong nation-building is carried out. The results show that the SSIM values obtained by the method of this paper are much better than those obtained by the comparison method in terms of model analysis. Except for the anti-quantization attack, the rest of the indicators are all greater than 0.9. It confirms that the method presented in this paper has excellent robustness in protecting intellectual property. In the empirical analysis of the impact of intellectual property rights on the artificial intelligence industry, except for RDF, which is significant at the 5% level, the regression coefficients of the other explanatory variables are all significant at the 1% level, 2 R amounting to 0.860771 and with a DW value of 1.667387 in the range of 1.5-2.5, that is, it indicates that the level of China’s intellectual property rights protection and the competitiveness of the AI industry are positively correlated.”
      原文链接:
    • NETL
    • NSTL

    Studies from Malaviya National Institute of Technology Jaipur Provide New Data on Machine Learning (Thermal Runaway Fault Prediction In Air-cooled Lithium-ion Battery Modules Using Machine Learning Through Temperature Sensors Placement ...)

    41-42页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating in Rajasthan, India, by NewsRx journalists, research stated, “The rise of severe accidents caused due to thermal runaway (TR) and its propagation in lithium-ion battery (LiB) modules is one of the most challenging factors that decelerate the rapid expansion of the electric vehicle (EV) industry. Timely detection of the TR undergoing cells in the module is crucial as the heat generated during TR is adequate to trigger the TR of the surrounding cells.” Funders for this research include Science and Engineering Research Board, Department of Science and Technology, Government of India, Ministry of Education, Government of India. The news reporters obtained a quote from the research from the Malaviya National Institute of Technology Jaipur, “In this study, an accurate machine learning (ML) based faulty cell position prediction model is developed for the air-cooled cylindrical LiB modules with the cells in aligned, staggered, and cross arrangements. The CFD model used for data generation is validated with the in-house experiments on an aligned surrogate 32-cell module for multiple failure positions. Further, to predict the TR cell position in the battery module, the random forest classification (RFC) model is developed based on the temperature distribution data obtained from the optimized temperature sensors derived for the two types of initial temperature sensor distributions (single and multiple-planes) using a heat map approach. The model developed is tested for varying design and operating conditions, and the prediction results, along with the error metrics and the prediction timings, are compared. It is revealed that except for the cross-cell arrangement in the single-plane temperature sensors distribution scenario, the RFC model produces higher accuracy when tested on the optimized temperature sensor layouts for the multiple-plane sensor distribution.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Study Findings on Robotics Published by Researchers at Shanghai University (A magnetic multi-layer soft robot for on-demand targeted adhesion)

    41-41页
    查看更多>>摘要：Current study results on robotics have been published. According to news reporting out of Shanghai University by NewsRx editors, research stated, “Magnetic soft robots have shown great potential for biomedical applications due to their high shape reconfigurability, motion agility, and multifunctionality in physiological environments.” Financial supporters for this research include National Natural Science Foundation of China. Our news editors obtained a quote from the research from Shanghai University: “Magnetic soft robots with multi-layer structures can enhance the loading capacity and function complexity for targeted delivery. However, the interactions between soft entities have yet to be fully investigated, and thus the assembly of magnetic soft robots with on-demand motion modes from multiple film-like layers is still challenging. Herein, we model and tailor the magnetic interaction between soft film-like layers with distinct in-plane structures, and then realize multi-layer soft robots that are capable of performing agile motions and targeted adhesion. Each layer of the robot consists of a soft magnetic substrate and an adhesive film. The mechanical properties and adhesion performance of the adhesive films are systematically characterized. The robot is capable of performing two locomotion modes, i.e., translational motion and tumbling motion, and also the on-demand separation with one side layer adhered to tissues.”
      原文链接:
    • NETL
    • NSTL

    Reports Summarize Machine Learning Findings from Xi’an Jiaotong University (Assessment of Machine Learning Models and Conventional Correlations for Predicting Heat Transfer Coefficient of Liquid Hydrogen During Flow Boiling)

    42-43页
    查看更多>>摘要：Researchers detail new data in Machine Learning. According to news originating from Shaanxi, People’s Republic of China, by NewsRx correspondents, research stated, “Liquid hydrogen has attracted widespread attention due to industrial decarbonization as an excellent carrier of renewable energy accommodation. Accurate prediction of the heat transfer coefficient during flow boiling has become a fundamental prerequisite for enhancing the design rationality and safety of hydrogen devices since a slight heat leak will trigger flow boiling.” Our news journalists obtained a quote from the research from Xi’an Jiaotong University, “A novel selection standard of the dataset for liquid hydrogen flow boiling is proposed, and an experimental database of liquid hydrogen is compiled, including 923 data points from 5 sources. The prediction performance of eight conventional empirical correlations and six machine learning models for liquid hydrogen flow boiling is compared and evaluated. Results show that the prediction ability of machine learning models for the heat transfer coefficient of liquid hydrogen flow boiling is much higher than that of traditional correlations. Fang correlation is recommended to use as the calculation benchmark due to simplicity and reliability if the inlet condition is obscure. The Extra tree model shows the most excellent evaluating performance among the six machine learning models with a mean absolute deviation of 11.44% and a fairly superior R2 of 0.9543. The Froude number Fr exhibits an essential impact according to the feature importance analysis, which may need to be taken into account when developing new empirical cor-relations. An improved correlation for the flow boiling of liquid hydrogen is provided based on the Fang correlation, achieving a mean absolute deviation of 18.61% and a mean relative deviation of 16.49%.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    University of Cyprus Reports Findings in Artificial Intelligence [Gynaecological Artificial Intelligence Diagnostics (GAID) GAID and Its Performance as a Tool for the Specialist Doctor]

    43-44页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Nicosia, Cyprus, by NewsRx correspondents, research stated, “Human-centric artificial intelligence (HCAI) aims to provide support systems that can act as peer companions to an expert in a specific domain, by simulating their way of thinking and decision-making in solving real-life problems. The gynaecological artificial intelligence diagnostics (GAID) assistant is such a system.” Our news journalists obtained a quote from the research from the University of Cyprus, “Based on artificial intelligence (AI) argumentation technology, it was developed to incorporate, as much as possible, a complete representation of the medical knowledge in gynaecology and to become a real-life tool that will practically enhance the quality of healthcare services and reduce stress for the clinician. Our study aimed to evaluate GAIDS’ efficacy and accuracy in assisting the working expert gynaecologist during day-to-day clinical practice. Knowledge-based systems utilize a knowledge base (theory) which holds evidence-based rules (‘IF-THEN’ statements) that are used to prove whether a conclusion (such as a disease, medication or treatment) is possible or not, given a set of input data. This approach uses argumentation frameworks, where rules act as claims that support a specific decision (arguments) and argue for its dominance over others. The result is a set of admissible arguments which support the final decision and explain its cause. Based on seven different subcategories of gynaecological presentations-bleeding, endocrinology, cancer, pelvic pain, urogynaecology, sexually transmitted infections and vulva pathology in fifty patients-GAID demonstrates an average overall closeness accuracy of zero point eighty-seven. Since the system provides explanations for supporting a diagnosis against other possible diseases, this evaluation process further allowed for a learning process of modular improvement in the system of the diagnostic discrepancies between the system and the specialist. GAID successfully demonstrates an average accuracy of zero point eighty-seven when measuring the closeness of the system’s diagnosis to that of the senior consultant. The system further provides meaningful and helpful explanations for its diagnoses that can help clinicians to develop an increasing level of trust towards the system. It also provides a practical database, which can be used as a structured history-taking assistant and a friendly, patient record-keeper, while improving precision by providing a full list of differential diagnoses. Importantly, the design and implementation of the system facilitates its continuous development with a set methodology that allows minimal revision of the system in the face of new information.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Findings from International Business School in the Area of Robotics Described (Constructing the Intelligent Expressway Traffic Monitoring System Using the Internet of Things and Inspection Robot)

    45-46页
    查看更多>>摘要：Current study results on Robotics have been published. According to news reporting out of Fuzhou, People’s Republic of China, by NewsRx editors, the research stated, “With the continuous acceleration of urbanization, traffic congestion, traffic accidents, and urban environmental problems are becoming increasingly serious, which negatively impacts the lives of city residents. With today’s urbanization trend, traffic management is a pressing issue, and the safety and smoothness of highways profoundly affect a city’s economy and quality of life.” Financial support for this research came from Major Project of Fujian Social Science Fund Base. Our news journalists obtained a quote from the research from International Business School, “As a result, the intelligent inspection robot has entered the public view. It has the advantages of stability and efficiency, can continue to work in a high-intensity state, and helps reduce a lot of human workloads. Firstly, an intelligent transport monitoring system based on the Internet of Things (IoT) is proposed. This system integrates deep learning and artificial intelligence technology, which can quickly query traffic parameters, environmental parameters, and violations that may cause traffic accidents. Secondly, an intelligent inspection robot is introduced to monitor road traffic flow and violation records in real-time, which provides technical support for further scientific management of road traffic. Finally, the intelligent monitoring system’s sensitivity and improvement measures are analyzed using the Simultaneous Localization and Mapping (SLAM) algorithm results, making intelligent traffic monitoring more popular. A section of closed safety road is selected for the inspection robot test. The results reveal that (1) the urban transportation model based on the IoT can meet the architecture of intelligent urban transportation. (2) Considering the performance of the inspection robot, the SLAM algorithm is more suitable for road intelligent traffic monitoring. (3) When the number of particles in the improved SLAM algorithm is small, the accuracy and real-time performance of the algorithm can also be guaranteed. The calculation efficiency is improved to 80%, and the modeling accuracy is improved by 23.3%. Traditional traffic monitoring methods typically rely on static sensors and limited data sources. However, the proposed system leverages IoT technology’s and inspection robots’ real-time data collection capabilities, achieving a more comprehensive, accurate, and flexible acquisition of traffic data. Through this exploration, the overall ideas and objectives of the construction of intelligent highways are clarified, which will lay a solid foundation for the follow-up construction of intelligent highways and provide comprehensive design and practical ideas. The improved SLAM algorithm can more stably complete the positioning and mapping of the tunnel inspection robot in the road environment. In the SLAM algorithm, an Extended Kalman Filter is introduced to ensure the accuracy and real-time of the improved algorithm, which can be applied to the modeling and positioning of unknown environments.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Research from University of Louisiana Has Provided New Data on Robotics (Investigating Suitable Combinations of Dynamic Models And Control Techniques For Offline Reinforcement Learning Based Navigation: Application Universal Omni-wheeled Robots)

    46-46页
    查看更多>>摘要：Fresh data on robotics are presented in a new report. According to news reporting from the University of Louisiana by NewsRx journalists, research stated, “Omni-directional locomotion provides Wheeled Mobile Robots (WMR) with better maneuverability, and flexibility, which enhances their energy efficiency and dexterity.” Our news correspondents obtained a quote from the research from University of Louisiana: “Universal Omni-Wheels are one of the best categories of wheels that can be used to develop a WMR Amarasiri et. al., [1]. We study dynamic modeling and controllers for mobile robots to train in a Reinforcement Learning (RL) based navigation algorithm. RL tasks require copious amounts of learning iteration episodes, which makes training very time-consuming. The choice of dynamic model and controller have significant impact on training time. In this paper, we compare a traditional Kane’s equations model to a non-holonomic canonical momenta model [2]. We implemented four controllers: Proportional Integral Derivative (PID), Linear Quadratic Regulator with Integral action (LQI), pole placement, and a full nonlinear Sliding Mode Controller (SMC).”
      原文链接:
    • NETL
    • NSTL

    Reports Outline Machine Learning Study Results from University of Rouen Normandie (Random Forest Kernel for High-dimension Low Sample Size Classification)

    47-47页
    查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting originating in Rouen, France, by NewsRx journalists, research stated, “High dimension, low sample size (HDLSS) problems are numerous among real-world applications of machine learning. From medical images to text processing, traditional machine learning algorithms are usually unsuccessful in learning the best possible concept from such data.” Financial supporters for this research include This work is part of the DAISI project, co-financed by the European Union with the European Regional Development Fund (ERDF) and by the Normandy Region., DAISI project - European Union, European Union (EU), Normandy Region. The news reporters obtained a quote from the research from the University of Rouen Normandie, “In a previous work, we proposed a dissimilarity-based approach for multi-view classification, the random forest dissimilarity, that perfoms state-of-the-art results for such problems. In this work, we transpose the core principle of this approach to solving HDLSS classification problems, by using the RF similarity measure as a learned precomputed SVM kernel (RFSVM). We show that such a learned similarity measure is particularly suited and accurate for this classification context.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Reports Summarize Machine Learning Findings from Shenyang University of Technology (Explainable Molecular Simulation and Machine Learning for Carbon Dioxide Adsorption On Magnesium Oxide)

    48-49页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating from Liaoning, People’s Republic of China, by NewsRx correspondents, research stated, “The effects of the adsorption energy of CO2 within MgO at different temperatures were investigated by molecular dynamics simulations and experimentally verified. The adsorption mechanism of CO2 within MgO was discussed and explained qualitatively.” Funders for this research include National Natural Science Foundation of China Youth Science Foundation, Liaoning Application demonstration of new generation light, Guangdong Basic and Applied Basic Research Fund, Shantou University.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Boston University Researchers Update Understanding of Artificial Intelligence (Looking towards an automated future: U.S. attitudes towards future artificial intelligence instantiations and their effect)

    48-48页
    查看更多>>摘要：Investigators discuss new findings in artificial intelligence. According to news originating from Boston University by NewsRx editors, the research stated, “The present study explores people’s attitudes towards an assortment of occupations on high and low-likelihood of automation probability.” The news correspondents obtained a quote from the research from Boston University: “An omnibus survey (N = 1150) was conducted to measure attitudes about various emerging technologies, as well as demographic and individual traits. The results showed that respondents were not very comfortable with AI’s management across domains. To some degree, levels of comfort corresponded with the likelihood of automation probability, though some domains diverged from this pattern. Demographic traits explained the most variance in comfort with AI revealing that men and those with higher perceived technology competence were more comfortable with AI management in every domain. With the exception of personal assistance, those with lower internal locus of control were more comfortable with AI managing in almost every domain. Age, education, and employment showed little influence on comfort levels.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature