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    Reports Outline Machine Learning Study Results from Kutateladze Institute of Thermophysics (The application of machine learning techniques to detect combustion modes in a pulverised coal boiler)

    67-67页
    查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news reporting from the Kutateladze Institute of Thermophysics by NewsRx journalists, research stated, “The development of machine learning algorithms based on semi-industrial thermal benches will approach the development of an automated system capable of detecting and tweaking energy-efficient and environmentally friendly combustion modes in large power plants and increasing their efficiency without significant changes in the design of boiler equipment.” Our news journalists obtained a quote from the research from Kutateladze Institute of Thermophysics: “Determination of combustion modes and optimisation of the combustion process based on neural network analysis of visualisation patterns of the coal flame in the boiler. Determining the combustion mode in the furnace space and superimposing (automatically adjusting) the parameters based on sensor readings to bring it to the optimum mode and maintain stable combustion is a complex task. Currently, the selection of necessary parameters is done by operator-assisted automatic process control systems, but this process is based on known design parameters and is not always efficient or environmentally friendly in practice.”
      原文链接:
    • NETL
    • NSTL

    Researchers from Italian National Agency for New Technologies Discuss Research in Robotics (Considerations on the Dynamics of Biofidelic Sensors in the Assessment of Human-Robot Impacts)

    68-69页
    查看更多>>摘要：Investigators publish new report on robotics. According to news reporting originating from Bologna, Italy, by NewsRx correspondents, research stated, “Ensuring the safety of physical humanrobot interaction (pHRI) is of utmost importance for industries and organisations seeking to incorporate robots into their workspaces.” The news correspondents obtained a quote from the research from Italian National Agency for New Technologies: “To address this concern, the ISO/TS 15066:2016 outlines hazard analysis and preventive measures for ensuring safety in Human-Robot Collaboration (HRC). To analyse human-robot contact, it is common practice to separately evaluate the ‘transient’ and ‘quasi-static’ contact phases. Accurately measuring transient forces during close human-robot collaboration requires so-called ‘biofidelic’ sensors that closely mimic human tissue properties, featuring adequate bandwidth and balanced damping. The dynamics of physical human-robot interactions using biofidelic measuring devices are being explored in this research. In this paper, one biofidelic sensor is tested to analyse its dynamic characteristics and identify the main factors influencing its performance and its practical applications for testing. To this aim, sensor parameters, such as natural frequency and damping coefficient, are estimated by utilising a custom physical pendulum setup to impact the sensor.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Lanzhou University Reports Findings in Machine Learning (Risk predictions of surgical wound complications based on a machine learning algorithm: A systematic review)

    69-70页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Lanzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Surgical wounds may arise due to harm inflicted upon soft tissue during surgical intervention, and many complications and injuries may accompany them. These complications can lead to prolonged hospitalization and poorer clinical outcomes.” Our news editors obtained a quote from the research from Lanzhou University, “Also, Machine learning (ML) is a Section of artificial intelligence (AI) that has emerged in medical care and is increasingly used for diagnosis, complications, prognosis and recurrence prediction. This study aims to investigate surgical wound risk predictions and management using a ML algorithm by R programming language analysis. The systematic review, following PRISMA guidelines, spanned electronic databases using search terms like ‘machine learning’, ‘surgical’ and ‘wound’. Inclusion criteria covered experimental studies from 1990 to the present on ML’s application in surgical wound evaluation. Exclusion criteria included studies lacking full text, focusing on ML in all surgeries, neglecting wound assessment and duplications. Two authors rigorously assessed titles, abstracts and full texts, excluding reviews and guidelines. Ultimately, relevant articles were then analysed. The present study identified nine articles employing ML for surgical wound management. The analysis encompassed various surgical procedures, including Cardiothoracic, Caesarean total abdominal colectomy, Burn plastic surgery, facial plastic surgery, laparotomy, minimal invasive surgery, hernia repair and unspecified surgeries. ML was skillful in evaluating surgical site infections (SSI) in seven studies, while two extended its use to burn-grade diagnosis and wound classification. Support Vector Machine (SVM) and Convolutional Neural Network (CNN) were the most utilized algorithms. ANN achieved a 96% accuracy in facial plastic surgery wound management. CNN demonstrated commendable accuracies in various surgeries, and SVM exhibited high accuracy in multiple surgeries and burn plastic surgery.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Beijing University of Chemical Technology Reports Findings in Nipah Virus [Immunoinformatics-driven In silico vaccine design for Nipah virus (NPV): Integrating machine learning and computational epitope prediction]

    70-71页
    查看更多>>摘要：New research on RNA Viruses - Nipah Virus is the subject of a report. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India.” Our news journalists obtained a quote from the research from the Beijing University of Chemical Technology, “Currently, there are no specific vaccines available for this virus. The current work employed the reverse vaccinology method to conduct a comprehensive analysis of the entire proteome of the NPV virus. The aim was to identify and choose the most promising antigenic proteins that could serve as potential candidates for vaccine development. We have also designed B and T cell epitopes-based vaccine candidate using immunoinformatics approach. We have identified a total of 5 novel Cytotoxic T Lymphocytes (CTL), 5 Helper T Lymphocytes (HTL), and 6 linear B-cell potential antigenic epitopes which are novel and can be used for further vaccine development against Nipah virus. Then we performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidate against NPV. Further, Computational analysis indicated that these epitopes possessed highly antigenic properties and were capable of interacting with immune receptors. The designed vaccine were then docked with the human immune receptors, namely TLR-2 and TLR-4 showed robust interaction with the immune receptor. Molecular dynamics simulations demonstrated robust binding and good dynamics. After numerous dosages at varied intervals, computational immune response modeling showed that the immunogenic construct might elicit a significant immune response.”
      原文链接:
    • NETL
    • NSTL

    Research Data from National Institute of Standards and Technology Update Understanding of Robotics (Filtering Organized 3D Point Clouds for Bin Picking Applications)

    71-72页
    查看更多>>摘要：New study results on robotics have been published. According to news originating from Gaithersburg, Maryland, by NewsRx correspondents, research stated, “In robotic bin-picking applications, autonomous robot action is guided by a perception system integrated with the robot.” The news editors obtained a quote from the research from National Institute of Standards and Technology: “Unfortunately, many perception systems output data contaminated by spurious points that have no correspondence to the real physical objects. Such spurious points in 3D data are the outliers that may spoil obstacle avoidance planning executed by the robot controller and impede the segmentation of individual parts in the bin. Thus, they need to be removed. Many outlier removal procedures have been proposed that work very well on unorganized 3D point clouds acquired for different, mostly outdoor, scenarios, but these usually do not transfer well to the manufacturing domain. This paper presents a new filtering technique specifically designed to deal with the organized 3D point cloud acquired from a cluttered scene, which is typical for a bin-picking task.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Researcher at Seowon University Publishes Research in Machine Learning (Design of Efficient Phishing Detection Model using Machine Learning)

    72-72页
    查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news reporting originating from Seowon University by NewsRx correspondents, research stated, “Recently, there have been cases of phishing attempts to steal personal information through fake sites disguised as major sites.” The news journalists obtained a quote from the research from Seowon University: “Although phishing attacks continue and increase, countermeasures remain in the form of defense after identifying the attack. Therefore, in this paper, we designed a phishing detection model using machine learning that provides knowledge and prediction by learning patterns from data input to a computer. For this, an analysis model was built using sklearn logistic regression, and the phishing probability was visualized using a heatmap.” According to the news reporters, the research concluded: “In addition, a graph was used to visually indicate the result, and a function for attribute information of a phishing website was provided.”
      原文链接:
    • NETL
    • NSTL

    Data from University of Michigan Provide New Insights into Machine Learning (PM2.5 forecasting under distribution shift: A graph learning approach)

    73-73页
    查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news originating from the University of Michigan by NewsRx correspondents, research stated, “We present a new benchmark task for graph-based machine learning, aiming to predict future air quality (PM2.5 concentration) observed by a geographically distributed network of environmental sensors.” The news correspondents obtained a quote from the research from University of Michigan: “While prior work has successfully applied Graph Neural Networks (GNNs) on a wide family of spatio-temporal prediction tasks, the new benchmark task introduced here brings a technical challenge that has been less studied in the context of graph-based spatio-temporal learning: distribution shift across a long period of time. An important goal of this paper is to understand the behavior of spatio-temporal GNNs under distribution shift. We conduct a comprehensive comparative study of both graph-based and non-graph-based machine learning models under two data split methods, one results in distribution shift and one does not.”
      原文链接:
    • NETL
    • NSTL

    Lublin University of Technology Reports Findings in Machine Learning (Ultrasound tomography enhancement by signal feature extraction with modular machine learning method)

    73-74页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting out of Lublin, Poland, by NewsRx editors, research stated, “Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography.” Our news journalists obtained a quote from the research from the Lublin University of Technology, “The key idea is to analyze the time-dependent ultrasonic signal recorded by three independent transducers of an experimental system. It focuses on finding common or related characteristics of these signals using customdesigned deep neural network models. In principle, models use convolution layers to extract common features of signals, which are passed to dense layers responsible for predicting the number of objects or their locations and sizes. Predicting the number and properties of objects are characterized by a high value of the coefficient of determination R2 = 99.8% and R2 = 98.4%, respectively.”
      原文链接:
    • NETL
    • NSTL
    • Public Library Science

    University of Health Sciences Turkey Reports Findings in Artificial Intelligence (Measuring the performance of an artificial intelligencebased robot that classifies blood tubes and performs quality control in terms of preanalytical errors: A ...)

    74-75页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating from Izmir, Turkey, by NewsRx correspondents, research stated, “Artificial intelligencebased robotic systems are increasingly used in medical laboratories. This study aimed to test the performance of KANKA (Labenko), a stand-alone, artificial intelligence-based robot that performs sorting and preanalytical quality control of blood tubes.” Our news editors obtained a quote from the research from the University of Health Sciences Turkey, “KANKA is designed to perform preanalytical quality control with respect to error control and preanalytical sorting of blood tubes. To detect sorting errors and preanalytical inappropriateness within the routine work of the laboratory, a total of 1000 blood tubes were presented to the KANKA robot in 7 scenarios. These scenarios encompassed various days and runs, with 5 repetitions each, resulting in a total of 5000 instances of sorting and detection of preanalytical errors. As the gold standard, 2 experts working in the same laboratory identified and recorded the correct sorting and preanalytical errors. The success rate of KANKA was calculated for both the accurate tubes and those tubes with inappropriate identification. KANKA achieved an overall accuracy rate of 99.98% and 100% in detecting tubes with preanalytical errors. It was found that KANKA can perform the control and sorting of 311 blood tubes per hour in terms of preanalytical errors. KANKA categorizes and records problem-free tubes according to laboratory subunits while identifying and classifying tubes with preanalytical inappropriateness into the correct error sections.”
      原文链接:
    • NETL
    • NSTL
    • Oxford Univ Press

    Researchers at Sungkyunkwan University Publish New Data on Robotics (Unloading sequence planning for autonomous robotic container-unloading system using A-star search algorithm)

    75-76页
    查看更多>>摘要：South Korea, by NewsRx correspondents, research stated, “In autonomous unloading systems, one of the major challenges is planning the unloading sequence in cluttered logistics container environments.” Financial supporters for this research include Ministry of Trade, Industry And Energy; Ministry of Science, Ict And Future Planning; Korea Ministry of Science And Ict. Our news correspondents obtained a quote from the research from Sungkyunkwan University: “Proper unloading sequence planning is crucial to avoid damage to the packages caused by collision and collapse. At the same time, the planned sequence has to minimize the effort during the unloading process, such as energy consumption, time taken, and distance moved, to enhance efficiency. This paper presents a sequence planning method based on the A-star search algorithm applied to unloading randomly stacked unidentical boxes from logistics containers. To represent the general overlap relationships of boxes in a cluttered environment, we utilize an adjacency matrix structure and involve it in the state of the unloading sequence planning. Moreover, by adopting the A-star search algorithm, the method can minimize the cost of system movement for an efficient unloading sequence. As a result, our method can determine the unloading sequence while considering the relationships between packages.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier