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    New Machine Learning Research from Uppsala University Discussed (Sentiment analysis of reviews on cappadocia: The land of beautiful horses in the eyes of tourists)

    29-30页
    查看更多>>摘要：Fresh data on artificial intelligence are presented in a new report. According to news originating from Uppsala, Sweden, by NewsRx correspondents, research stated, “The Cappadocia region is one of the most popular tourist destinations in Turkey, and its tourism sector has a significant share in the Turkish economy.” The news journalists obtained a quote from the research from Uppsala University: “In this study, we scraped TripAdvisor reviews of visitors of the Cappadocia region with the Python programming language and used them to analyse public sentiment using various supervised machine learning algorithms. The main purpose of the study is to help create competitive intelligence on both regional and global scales using social media data. For this, we applied Random Forest, Naive Bayes, and Support Vector Machine methods to classify 4,770 reviews and get insights about the visitors’ perspectives. Results show that the majority of the tourists (90%) had a positive experience during their visit. Most of the complaints focused on the attitudes of staff members.”
      原文链接:
    • NETL
    • NSTL
    • Sciendo

    Instituto Gulbenkian de Ciencia Reports Findings in Artificial Intelligence (Harnessing artificial intelligence to reduce phototoxicity in live imaging)

    30-31页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Oeiras, Portugal, by NewsRx correspondents, research stated, “Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination.” Funders for this research include Fundacao Calouste Gulbenkian, European Research Council, Horizon 2020, Horizon Europe, European Molecular Biology Organization, Chan Zuckerberg Initiative, LS4FUTURE Associated Laboratory, Academy of Finland, Sigrid Juselius Foundation, Syopajarjestot, Abo Akademi University, University College London.
      原文链接:
    • NETL
    • NSTL
    • Company Biologists Ltd

    New Research on Machine Learning from Zhengzhou Tobacco Research Institute Summarized (Quantitative analysis of pyrolysis characteristics and chemical components of tobacco materials based on machine learning)

    31-31页
    查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news originating from Zhengzhou, People’s Republic of China, by NewsRx correspondents, research stated, “To investigate the quantitative relationship between the pyrolysis characteristics and chemical components of tobacco materials, various machine learning methods were used to establish a quantitative analysis model of tobacco.” Our news reporters obtained a quote from the research from Zhengzhou Tobacco Research Institute: “The model relates the thermal weight loss rate to 19 chemical components, and identifies the characteristic temperature intervals of the pyrolysis process that significantly relate to the chemical components. The results showed that: 1) Among various machine learning methods, partial least squares (PLS), support vector regression (SVR) and Gaussian process regression (GPR) demonstrated superior regression performance on thermogravimetric data and chemical components. 2) The PLS model showed the best performance on fitting and prediction effects, and has good generalization ability to predict the 19 chemical components. For most components, the determination coefficients R2 are above 0.85. While the performance of SVR and GPR models was comparable, the R2 for most chemical components were below 0.75. 3) The significant temperature intervals for various chemical components were different, and most of the affected temperature intervals were within 130℃-400℃.”
      原文链接:
    • NETL
    • NSTL
    • Frontiers Media Sa

    China Medical University Reports Findings in Artificial Intelligence (Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review)

    32-33页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation.” Our news editors obtained a quote from the research from China Medical University, “PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789). In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as ‘recommended’; however, 281 and 187 were ‘not recommended’ and ‘warning,’ respectively. AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Data on Robotics Discussed by Researchers at Beijing Institute of Petrochemical Technology (Combining closed-form and numerical solutions for the inverse kinematics of six-degrees-of-freedom collaborative handling robot)

    33-33页
    查看更多>>摘要：New study results on robotics have been published. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “In the process of solving the inverse kinematics of six-degrees-of-freedom collaborative robots, the numerical solution has problems such as low accuracy and singular configurations.” The news correspondents obtained a quote from the research from Beijing Institute of Petrochemical Technology: “Moreover, due to the high coupling of its position and attitude, the direct closed-form solution fails. To address these problems, an inverse kinematics algorithm that combines closed-form and numerical solutions was proposed. The Jacobian matrix was established based on the forward kinematics equation of the six-degrees-of-freedom collaborative robot. Its inverse matrix was obtained by a singular value decomposition of the matrix using the Manocha elimination method to avoid the singularities of the Jacobian matrix. The optimal inverse kinematics solution was obtained using the Newton-Raphson iterative method. A computer simulation implemented in MATLAB and Visual C++ was used to evaluate the accuracy and speed of the proposed algorithm.”
      原文链接:
    • NETL
    • NSTL
    • Sage

    NASA Langley Research Center Researcher Provides New Insights into Machine Learning (Spectral Fingerprinting of Methane from Hyper-Spectral Sounder Measurements Using Machine Learning and Radiative Kernel-Based Inversion)

    34-35页
    查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news reporting originating from Hampton, Virginia, by NewsRx correspondents, research stated, “Satellite-based hyper-spectral infrared (IR) sensors such as the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI) cover many methane (CH4) spectral features, including the n1 vibrational band near 1300 cm-1 (7.7 mm); therefore, they can be used to monitor CH4 concentrations in the atmosphere.” Financial supporters for this research include Nasa 2017 Research Opportunities in Space And Earth Sciences; Nasa 2020 Roses Solicitation. Our news reporters obtained a quote from the research from NASA Langley Research Center: “However, retrieving CH4 remains a challenge due to the limited spectral information provided by IR sounder measurements. The information required to resolve the weak absorption lines of CH4 is often obscured by interferences from signals originating from other trace gases, clouds, and surface emissions within the overlapping spectral region. Consequently, currently available CH4 data product derived from IR sounder measurements still have large errors and uncertainties that limit their application scope for high-accuracy climate and environment monitoring applications. In this paper, we describe the retrieval of atmospheric CH4 profiles using a novel spectral fingerprinting methodology and our evaluation of performance using measurements from the CrIS sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The spectral fingerprinting methodology uses optimized CrIS radiances to enhance the CH4 signal and a machine learning classifier to constrain the physical inversion scheme. We validated our results using the atmospheric composition reanalysis results and data from airborne in situ measurements.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    New Machine Learning Study Results Reported from Dar Al-Hekma University (A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats)

    34-34页
    查看更多>>摘要：A new study on artificial intelligence is now available. According to news reporting from Jeddah, Saudi Arabia, by NewsRx journalists, research stated, “Anomaly detection is a critical aspect of various applications, including security, healthcare, and network monitoring.” The news correspondents obtained a quote from the research from Dar Al-Hekma University: “In this study, we introduce FusionNet, an innovative ensemble model that combines the strengths of multiple machine learning algorithms, namely Random Forest, K-Nearest Neighbors, Support Vector Machine, and Multi-Layer Perceptron, for enhanced anomaly detection. FusionNet’s architecture leverages the diversity of these algorithms to achieve high accuracy and precision. We evaluate FusionNet’s performance on two distinct datasets, Dataset 1 and Dataset 2, and compare it with traditional machine learning models, including SVM, KNN, and RF. The results demonstrate that FusionNet consistently outperforms these models across both datasets in terms of accuracy, precision, recall, and F1 score. On Dataset 1, FusionNet achieves an accuracy of 98.5% and on Dataset 2, it attains an accuracy of 99.5%. FusionNet’s remarkable ability to detect anomalies with exceptional accuracy underscores its potential for real-world applications.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    University of the West Indies Reports Findings in Colectomy (Colorectal resections for malignancy: A pilot study comparing conventional vs freehand robot-assisted laparoscopic colectomy)

    36-37页
    查看更多>>摘要：New research on Surgery - Colectomy is the subject of a report. According to news reporting out of St. Augustine, Trinidad and Tobago, by NewsRx editors, research stated, “Laparoscopic colectomy is widely accepted as a safe operation for colorectal cancer, but we have experienced resistance to the introduction of the FreeHand robotic camera holder to augment laparoscopic colorectal surgery. To compare the initial results between conventional and FreeHand robot-assisted laparoscopic colectomy in Trinidad and Tobago.” Our news journalists obtained a quote from the research from the University of the West Indies, “This was a prospective study of outcomes from all laparoscopic colectomies performed for colorectal carcinoma from November 29, 2021 to May 30, 2022. The following data were recorded: Operating time, conversions, estimated blood loss, hospitalization, morbidity, surgical resection margins and number of nodes harvested. All data were entered into an excel database and the data were analyzed using SPSS ver 20.0. There were 23 patients undergoing colectomies for malignant disease: 8 (35%) FreeHand-assisted and 15 (65%) conventional laparoscopic colectomies. There were no conversions. Operating time was significantly lower in patients undergoing robot-assisted laparoscopic colectomy (95.13 ± 9.22 105.67 ± 11.48 min; = 0.045). Otherwise, there was no difference in estimated blood loss, nodal harvest, hospitalization, morbidity or mortality.”
      原文链接:
    • NETL
    • NSTL

    Srinivas University Researcher Releases New Study Findings on Androids (Revolutionizing User Engagement: Integrating Chatbot Technology for Real-Time Assistance and Interactive Dialogue in Human-Robot Interaction)

    36-36页
    查看更多>>摘要：Data detailed on androids have been presented. According to news reporting originating from Karnataka, India, by NewsRx correspondents, research stated, “This research paper explores the integration of chatbot technology to revolutionize human-robot interaction, focusing on enhancing user engagement through real-time assistance and interactive dialogue.” Our news reporters obtained a quote from the research from Srinivas University: “The study delves into the architecture, functionalities, and practical applications of chatbot integration in robots, aiming to optimize user experience and interaction dynamics. Advancements in artificial intelligence and robotics have led to the development of innovative applications, one of which is the integration of chatbot programs into robots for guiding and engaging in real-time conversations with users.”
      原文链接:
    • NETL
    • NSTL

    Researcher at University of California San Diego (UCSD) Releases New Data on Machine Learning (Detecting unitary synaptic events with machine learning)

    37-38页
    查看更多>>摘要：New research on artificial intelligence is the subject of a new report. According to news reporting originating from the University of California San Diego (UCSD) by NewsRx correspondents, research stated, “Spontaneously occurring miniature excitatory postsynaptic currents (mEPSCs) are fundamental electrophysiological events produced by quantal vesicular transmitter release at synapses.” The news editors obtained a quote from the research from University of California San Diego (UCSD): “Their analysis can provide important information regarding pre- and postsynaptic function. However, the small signal relative to recording noise requires expertise and considerable time for their identification. Furthermore, many mEPSCs smaller than 8 pA are not well resolved (e.g., those produced at distant synapses or synapses with few receptor channels).” According to the news editors, the research concluded: “Here, we describe an automated approach to detect mEPSCs using a machine learning-based tool. This method, which can be easily generalized to other one-dimensional signals, eliminates inter-observer bias, provides an estimate of its sensitivity and specificity and permits reliable detection of small (e.g., 5 pA) spontaneous unitary synaptic events.”
      原文链接:
    • NETL
    • NSTL
    • Natl Acad Sciences