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    Hohai University Reports Findings in Machine Learning (Bionic study of distance-azimuth discrimination of multi-scattered point objects in bat bio-sonar)

    57-57页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Jiangsu, People’s Republic of China, by NewsRx correspondents, research stated, “This paper presents a novel approach to enhance the discrimination capacity of multi-scattered point objects in bat bio-sonar. A broadband interferometer mathematical model is developed, incorporating both distance and azimuth information, to simulate the transmitted and received signals of bats.” Our news editors obtained a quote from the research from Hohai University, “The Fourier transform is employed to simulate the preprocessing step of bat information for feature extraction. Furthermore, the bat bio-sonar model based on convolutional neural network (BS-CNN) is constructed to compensate for the limitations of conventional machine learning and CNN networks, including three strategies: Mix-up data enhancement, joint feature and hybrid atrous convolution module. The proposed BS-CNN model emulates the perceptual nerves of the bat brain for distance-azimuth discrimination and compares with four conventional classifiers to assess its discrimination efficacy. Experimental results demonstrate that the overall discrimination accuracy of the BS-CNN model is 93.4%, surpassing conventional CNN networks and machine learning methods by at least 5.9%.”
      原文链接:
    • NETL
    • NSTL

    Data on Artificial Intelligence Described by Researchers at Swansea University [Responsible Artificial Intelligence (Ai) for Value Formation and Market Performance In Healthcare: the Mediating Role of Patient’s Cognitive Engagement]

    58-58页
    查看更多>>摘要：A new study on Artificial Intelligence is now available. According to news reporting originating in Swansea, United Kingdom, by NewsRx journalists, research stated, “The Healthcare sector has been at the forefront of the adoption of artificial intelligence (AI) technologies. Owing to the nature of the services and the vulnerability of a large section of end-users, the topic of responsible AI has become the subject of widespread study and discussion.” The news reporters obtained a quote from the research from Swansea University, “We conduct a mixedmethod study to identify the constituents of responsible AI in the healthcare sector and investigate its role in value formation and market performance. The study context is India, where AI technologies are in the developing phase. The results from 12 in-depth interviews enrich the more nuanced understanding of how different facets of responsible AI guide healthcare firms in evidence-based medicine and improved patient centered care. PLS-SEM analysis of 290 survey responses validates the theoretical framework and establishes responsible AI as a third-order factor.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Study Results from Sun Yat-sen University Update Understanding of Machine Learning (Lds-fl: Loss Differential Strategy Based Federated Learning for Privacy Preserving)

    59-59页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news originating from Shenzhen, People’s Republic of China, by NewsRx correspondents, research stated, “Federated Learning (FL) has attracted extraordinary attention from the industry and academia due to its advantages in privacy protection and collaboratively training on isolated datasets. Since machine learning algorithms usually try to find an optimal hypothesis to fit the training data, attackers also can exploit the shared models and reversely analyze users’ private information.” Financial support for this research came from National Natural Science Foundation of China (NSFC). Our news journalists obtained a quote from the research from Sun Yat-sen University, “However, there is still no good solution to solve the privacy-accuracy trade-off, by making information leakage more difficult and meanwhile can guarantee the convergence of learning. In this work, we propose a Loss Differential Strategy (LDS) for parameter replacement in FL. The key idea of our strategy is to maintain the performance of the Private Model to be preserved through parameter replacement with multi-user participation, while the efficiency of privacy attacks on the model can be significantly reduced. To evaluate the proposed method, we have conducted comprehensive experiments on four typical machine learning datasets to defend against membership inference attack. For example, the accuracy on MNIST is near 99%, while it can reduce the accuracy of attack by 10.1% compared with FedAvg.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    New Robotics Findings Reported from Commonwealth Scientific and Industrial Research Organisation (CSIRO) (Diversity-based Topology Optimization of Soft Robotic Grippers)

    60-60页
    查看更多>>摘要：A new study on Robotics is now available. According to news reporting originating from Pullenvale, Australia, by NewsRx correspondents, research stated, “Soft grippers are ideal for grasping delicate, deformable objects with complex geometries. Universal soft grippers have proven effective for grasping common objects, however complex objects or environments require bespoke gripper designs.” Financial support for this research came from Science and Industry Endowment Fund. Our news editors obtained a quote from the research from Commonwealth Scientific and Industrial Research Organisation (CSIRO), “Multi-material printing presents a vast design-space which, when coupled with an expressive computational design algorithm, can produce numerous, novel, high-performance soft grippers. Finding high-performing designs in challenging design spaces requires tools that combine rapid iteration, simulation accuracy, and fine-grained optimization across a range of gripper designs to maximize performance, no current tools meet all these criteria. Herein, a diversity-based soft gripper design framework combining generative design and topology optimization (TO) are presented. Compositional pattern-producing networks (CPPNs) seed a diverse set of initial material distributions for the fine-grained TO. Focusing on vacuum-driven multi-material soft grippers, several grasping modes (e.g. pinching, scooping) emerging without explicit prompting are demonstrated. Extensive automated experimentation with printed multi-material grippers confirms optimized candidates exceed the grasp strength of comparable commercial designs. Grip strength, durability, and robustness is evaluated across 15,170 grasps. The combination of fine-grained generative design, diversity-based design processes, high-fidelity simulation, and automated experimental evaluation represents a new paradigm for bespoke soft gripper design which is generalizable across numerous design domains, tasks, and environments. Soft grippers are ideal for grasping delicate, deformable objects with complex geometries. A diversity-based soft gripper design framework combining generative design and topology optimization (TO) is presented.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    New Robotics Study Findings Have Been Reported by Investigators at University of Ghent (The Perspectives of Older Adults With Mild Cognitive Impairment and Their Caregivers On the Use of Socially Assistive Robots In Healthcare: Exploring ...)

    61-61页
    查看更多>>摘要：Current study results on Robotics have been published. According to news reporting originating from Ghent, Belgium, by NewsRx correspondents, research stated, “Due to increasing age and an increasing prevalence rate of neurocognitive disorders such as Mild Cognitive Impairment (MCI) and dementia, independent living may become challenging. The use of socially assistive robots (SARs) is one solution that can enable older adults with cognitive impairment to remain independent.” Financial support for this research came from AAL-project ReMIND. Our news editors obtained a quote from the research from the University of Ghent, “However, at present, there is a lack of knowledge about the attitudes of older adults with MCI and their caregivers towards SARs. This study relies on a constructivist grounded theory approach. Semi-structured interviews were conducted to gain a deeper insight into attitudes of two different stakeholder groups; older adults with MCI and their (in)formal caregivers. Forty individual semi-structured interviews were conducted with older adults with MCI (N = 30) and (in)formal caregivers (N = 10). Data revealed different perspectives on SARs in healthcare for the involved stakeholders. Two main topics could be derived: (1) perspectives on robot assistance, discussing different viewpoints on the potential value of robots as helpers, and (2) perspectives on implementation, revealing different factors that could affect implementation. Both topics may explain a positive, impartial or negative attitude towards SARs. This study identified different factors that should be taken into account when implementing a SAR in the home environment of older adults.”
      原文链接:
    • NETL
    • NSTL
    • Taylor & Francis

    Researchers from Sao Paulo State University Julio de Mesquita Filho Report Findings in Robotics (Analysis of Distortion, Corrosion and Mechanical Properties of Welded Csn Civil-300 Steel U-type Profiles)

    62-63页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news originating from Bauru, Brazil, by NewsRx correspondents, research stated, “Several factors affect the performance, manufacturing and assembly of metallic profiles: equipment, welding parameters and consumables. CSN Civil-300 steel profiles are widely used to obtain high-quality welded joints.” Financial support for this research came from CadSteel Engenharia. Our news journalists obtained a quote from the research from Sao Paulo State University Julio de Mesquita Filho, “Three factors in the welded joints need to remain nearly invariable and within predictable limits: distortion, corrosion and mechanical properties. However, industries still have problems with welding steel profiles, such as warping misalignment, misfit and poor mechanical properties. As a result, it is necessary to have a calibrated and affordable methodology for welding CSN Civil-300 steel profiles on the factory floor. Therefore, this study aims to analyse the mechanical performance of CSN Civil-300 steel profile-welded joints using a robot welding machine. A GMAW (metal active gas) welding process was applied to a CSN Civil-300 type U 100 x 50 profile, 3.0-mm thick, employing a Motoman UP6 robotic arm in butt joints, with and without dots. Two different rod electrode types were used (AWS ER70S-3 and ER70S-6), with a 75%Ar/25%CO2 shielding gas and current density welding set at 160.6 A and 20.5 V. A three-dimensional scanning methodology was adopted to investigate welded joint distortions. While salt spray accelerated, corrosion test was used to analyse deterioration. The mechanical properties were analysed by macrography, microhardness and chemical analyses in the heat-affected zone (HAZ). It was found a distortion displacement was lower than 450 mu m on the sample’s surface, and a mass loss of 10.1 mu m/year was detected in terms of corrosion resistance. There was also evidence of chemical heterogeneity between the base metal and weld, mainly in the manganese content with an average reduction of 13% in microhardness measurements when AWS ER70S-3 electrode was used. By using calibrated welding parameters and a welding robot, it was possible to obtain mechanically resistant high-quality standardised welds.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    New Machine Learning Findings from Yildiz Technical University Reported (Prediction of Construction Accident Outcomes Based On an Imbalanced Dataset Through Integrated Resampling Techniques and Machine Learning Methods)

    63-64页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting from Istanbul, Turkey, by NewsRx journalists, research stated, “Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world.” Financial support for this research came from Republic of Turkey, Social Security Institution (SSI). The news correspondents obtained a quote from the research from Yildiz Technical University, “This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies. Design/methodology/approach Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naive Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes. The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker’s age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes. Practical implications The proposed framework can be used in construction sites on a monthlybasis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents. Social implications Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers’ quality of life and well-being. Originality/value The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain.”
      原文链接:
    • NETL
    • NSTL
    • Emerald Group Publishing

    Study Data from Central University of Finance and Economics Update Understanding of Machine Learning (Prediction on traffic accidents severity levels leveraging machine learning-based methods on imbalanced data)

    64-64页
    查看更多>>摘要：A new study on artificial intelligence is now available. According to news originating from Beijing, People’s Republic of China, by NewsRx editors, the research stated, “Traffic accidents are a significant problem in many countries, resulting in thousands of injuries and deaths every year.” The news reporters obtained a quote from the research from Central University of Finance and Economics: “By estimating the severity of traffic accidents, traffic safety together with the crash survival rates could be improved, by taking effective prevention measures at the location where accidents are plentiful and severe. This paper studies the prediction by different classification methods on traffic accident severity levels. The data set used includes 1.6 million traffic accidents recorded in the United Kingdom, ranging from 2000 to 2016. It is a difficult task, since the levels are imbalanced distributed, making it difficult to classify the records accordingly. To tackle this problem, this work compared several classification methods on the task and evaluates their performances from the aspects of time, accuracy, and adaptability on imbalanced data sets.”
      原文链接:
    • NETL
    • NSTL

    University of Sheffield Reports Findings in Artificial Intelligence (Advancements in cardiac structures segmentation: a comprehensive systematic review of deep learning in CT imaging)

    65-66页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating from Sheffield, United Kingdom, by NewsRx correspondents, research stated, “Segmentation of cardiac structures is an important step in evaluation of the heart on imaging. There has been growing interest in how artificial intelligence (AI) methods-particularly deep learning (DL)-can be used to automate this process.” Our news editors obtained a quote from the research from the University of Sheffield, “Existing AI approaches to cardiac segmentation have mostly focused on cardiac MRI. This systematic review aimed to appraise the performance and quality of supervised DL tools for the segmentation of cardiac structures on CT. Embase and Medline databases were searched to identify related studies from January 1, 2013 to December 4, 2023. Original research studies published in peer-reviewed journals after January 1, 2013 were eligible for inclusion if they presented supervised DL-based tools for the segmentation of cardiac structures and non-coronary great vessels on CT. The data extracted from eligible studies included information about cardiac structure(s) being segmented, study location, DL architectures and reported performance metrics such as the Dice similarity coefficient (DSC). The quality of the included studies was assessed using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). 18 studies published after 2020 were included. The DSC scores median achieved for the most commonly segmented structures were left atrium (0.88, IQR 0.83-0.91), left ventricle (0.91, IQR 0.89-0.94), left ventricle myocardium (0.83, IQR 0.82- 0.92), right atrium (0.88, IQR 0.83-0.90), right ventricle (0.91, IQR 0.85-0.92), and pulmonary artery (0.92, IQR 0.87-0.93). Compliance of studies with CLwas variable. In particular, only 58% of studies showed compliance with dataset description criteria and most of the studies did not test or validate their models on external data (81%). Supervised DL has been applied to the segmentation of various cardiac structures on CT. Most showed similar performance as measured by DSC values.”
      原文链接:
    • NETL
    • NSTL
    • Frontiers Media Sa

    Recent Findings from University of Manchester Has Provided New Information about Robotics (A Multiarm Robotic Platform for Scientific Exploration: Its Design, Digital Twins, and Validation)

    65-65页
    查看更多>>摘要：Fresh data on Robotics are presented in a new report. According to news reporting out of Manchester, United Kingdom, by NewsRx editors, research stated, “There is a large number of robotic platforms with two or more arms targeting surgical applications. Despite that, very few groups have employed such platforms for scientific exploration.” Financial support for this research came from Japan Science and Technology Agency Moonshot Research & Development Program. Our news journalists obtained a quote from the research from the University of Manchester, “Possible applications of a multiarm platform in scientific exploration involve the study of the mechanisms of intractable diseases by using organoids, i.e., miniature human organs. The study of organoids requires the preparation of a cranial window, which is done by carefully removing an 8-mm patch of the skull of a mouse. In this article, we present the first prototype of our artificial intelligence (AI) robot science platform for scientific experimentation, its digital twins, and validation experiments under teleoperation.”
      原文链接:
    • NETL
    • NSTL
    • IEEE