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Robotics & Machine Learning Daily News

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    New Findings from City University of London in the Area of Machine Learning Described (Fesad Ransomware Detection Framework With Machine Learning Using Adaption To Concept Drift)

    29-30页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting from London, United Kingdom, by NewsRx journalists, research stated, “This paper proposes FeSAD, a framework that will allow a machine learning classifier to detect evolutionary ransomware. Ransomware is a critical player in the malware space that causes hundreds of millions of dollars of damage globally and evolves quickly.” The news correspondents obtained a quote from the research from the City University of London, “The evolution of ransomware in machine learning classifiers is often calculated as concept drift. Concept drift is dangerous as changes in the behavior of ransomware can easily lead to misclassifications, and misclassification can harm individuals and businesses. Our proposed framework consists of a feature selection layer, drift calibration layer and drift decision layer that allows a machine learning classifier to detect and classify concept drift samples reliably. We evaluate the FeSAD framework in various concept drift scenarios and observe its ability to detect drifting samples effectively. The FeSAD framework also evaluated on its ability to extend the lifespan of a classifier.”
      原文链接:
    • NETL
    • NSTL

    Georgia Institute of Technology Reports Findings in Robotics (Realtime Pose Tracking for a Continuum Guidewire Robot under Fluoroscopic Imaging)

    30-31页
    查看更多>>摘要：New research on Robotics is the subject of a report. According to news reporting out of Atlanta, Georgia, by NewsRx editors, research stated, “Atherosclerosis is a medical condition that causes buildup of plaque in the blood vessels and narrowing of the arteries. Surgeons often treat this condition through angioplasty with catheter placements.” Our news journalists obtained a quote from the research from the Georgia Institute of Technology, “Continuum guidewire robots offer significant advantages for catheter placements due to their dexterity. Tracking these guidewire robots and their surrounding workspace under fluoroscopy in real-time can be useful for visualization and accurate control. This paper discusses algorithms and methods to track the shape and orientation of the guidewire and the surrounding workspaces of phantom vasculatures in real-time under C-arm fluoroscopy. The shape of continuum guidewires is found through a semantic segmentation architecture based on MobileNetv2 with a Tversky loss function to deal with class imbalances. This shape is refined through medial axis filtering and parametric curve fitting to quantitatively describe the guidewire’s pose. Using a constant curvature assumption for the guidewire’s bending segments, the parameters that describe the joint variables are estimated in real-time for a tendon-actuated COaxially Aligned STeerable (COAST) guidewire robot and tracked through its traversal of an aortic bifurcation phantom.”
      原文链接:
    • NETL
    • NSTL

    Study Results from Mechanical Engineering Faculty Update Understanding of Robotics (Development and Optimisation of a Robot Arm System for Additive Manufacturing Applications)

    31-31页
    查看更多>>摘要：New research on robotics is the subject of a new report. According to news originating from Timisoara, Romania, by NewsRx correspondents, research stated, “The paper presents the development of a new platform that represents a robotic arm system, useful and appropriate for the Additive Manufacturing applications.” Our news reporters obtained a quote from the research from Mechanical Engineering Faculty: “The main objective of this work was to explore the feasibility of integrating the off-the-shelf (COTS) Additive Manufacturing technologies and the six-degree-of-freedom industrial robotic arm, achieving a 3D Additive Manufacturing system which is able to perform six-degree fused deposition printing. The authors investigated the materials suitable to be used and performed more experiments with the aim to find the right configuration of the printing system.”
      原文链接:
    • NETL
    • NSTL

    Fudan University Reports Findings in Artificial Intelligence (Detection of circulating plasma cells in peripheral blood using deep learning-based morphological analysis)

    32-33页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “The presence of circulating plasma cells (CPCs) is an important laboratory indicator for the diagnosis, staging, risk stratification, and progression monitoring of multiple myeloma (MM). Early detection of CPCs in the peripheral blood (PB) followed by timely interventions can significantly improve MM prognosis and delay its progression.” Financial support for this research came from National Natural Science Foundation of China. Our news journalists obtained a quote from the research from Fudan University, “Although the conventional cell morphology examination remains the predominant method for CPC detection because of accessibility, its sensitivity and reproducibility are limited by technician expertise and cell quantity constraints. This study aims to develop an artificial intelligence (AI)-based automated system for a more sensitive and efficient CPC morphology detection. A total of 137 bone marrow smears and 72 PB smears from patients with at Zhongshan Hospital, Fudan University, were retrospectively reviewed. Using an AI-powered digital pathology platform, Morphogo, 305,019 cell images were collected for training. Morphogo’s efficacy in CPC detection was evaluated with additional 184 PB smears (94 from patients with MM and 90 from those with other hematological malignancies) and compared with manual microscopy. Morphogo achieved 99.64% accuracy, 89.03% sensitivity, and 99.68% specificity in classifying CPCs. At a 0.60 threshold, Morphogo achieved a sensitivity of 96.15%, which was approximately twice that of manual microscopy, with a specificity of 78.03%. Patients with CPCs detected by AI scanning had a significantly shorter median progression-free survival compared with those without CPC detection (18 months vs. 34 months, p<.01). Morphogo is a highly sensitive system for the automated detection of CPCs, with potential applications in initial screening, prognosis prediction, and posttreatment monitoring for MM patients. Diagnosing and monitoring multiple myeloma (MM), a type of blood cancer, requires identifying and quantifying specific cells called circulating plasma cells (CPCs) in the blood. The conventional method for detecting CPCs is manual microscopic examination, which is time-consuming and lacks sensitivity. This study introduces a highly sensitive CPC detection method using an artificial intelligence-based system, Morphogo. It demonstrated remarkable sensitivity and accuracy, surpassing conventional microscopy. This advanced approach suggests that early and accurate CPC detection is achievable by morphology examination, making efficient CPC screening more accessible for patients with MM.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Findings in the Area of Robotics Reported from School of Mechatronical Engineering (Lwosnet: a Lightweight One-shot Network Framework for Object Pose Estimation)

    33-34页
    查看更多>>摘要：Data detailed on Robotics have been presented. According to news reporting from Harbin, People’s Republic of China, by NewsRx journalists, research stated, “The 6-D pose estimation of objects is a crucial task for robotic manipulation. The currently popular methods, that is, deep learningbased methods, usually have high requirements on the training dataset and the network architecture, which is likely to increase the cost of data annotation and training time.” Financial supporters for this research include National Natural Science Foundation of China Integration Project, China Scholarship Council. The news correspondents obtained a quote from the research from the School of Mechatronical Engineering, “In this article, we propose a lightweight one-shot network (LWOSNet) to estimate the 6-D poses of multiple objects in real time and provide two feasible routes to generate synthetic training data with the objects at hand. The input of LWOSNet is a red-green-blue (RGB) image, and the output is the objects’ semantic labels and 6-D poses. The whole process is divided into three stages: the image pre-processing stage, the keypoints extraction stage, and the 6-D pose inference stage. Firstly, we leverage the first eight layers of visual geometry group 19 (VGG-19) and two convolutional layers to downscale the dimensionality of the image feature, which effectively reduces the parameters of the network. Then, the processed features are input into two different network branches to identify the categories of the objects and generate the 3-D bounding boxes. Finally, the LWOSNet outputs the semantic labels and the 6-D poses calculated by the perspective-n-point (PnP) algorithm. Additionally, we conducted a series of detection experiments and robot grasping experiments.”
      原文链接:
    • NETL
    • NSTL

    Investigators from Shanghai University Report New Data on Robotics (The Fmea Model Based On Lopcow-aras Methods With Interval-valued Fermatean Fuzzy Information for Risk Assessment of R&d Projects In Industrial Robot Offline Programming Systems)

    34-35页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Failure mode and effect analysis (FMEA) is a reliability analysis and risk management technique used to analyze the potential causes of system failure modes and their impact on system performance and has been used in many fields. However, the traditional FMEA model often ignores the weight of risk factors and their internal relationship in an uncertain setting.” Funders for this research include National Natural Science Foundation of China (NSFC), Ministry of Education Humanities and Social Sciences Research Planning Fund Project.
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Findings on Robotics Detailed by Investigators at University of Balear Island (Coordination of Marine Multi Robot Systems With Communication Constraints)

    35-36页
    查看更多>>摘要：Fresh data on Robotics are presented in a new report. According to news originating from Palma de Mallorca, Spain, by NewsRx correspondents, research stated, “This article focuses on the coordination and communication aspects of multi-robot systems (MRS) and explores what, how and when robots should coordinate and communicate in marine environment. It includes a comparative analysis of MRS coordination under communication constraints in aerial, terrestrial, and marine environments.” Funders for this research include MCIN/AEI, ERDF A way of making Europe. Our news journalists obtained a quote from the research from the University of Balear Island, “In the light of the gaps identified in the current MRS literature, we focus on how to tackle the inherent communication constraints presents in marine environments. Thus, a review of Marine Multi-Robot systems (MMRS) is presented, proposing a taxonomy that classifies them according to how they communicate and coordinate. In this line, the classification of different communication strategies found in the literature has received significant attention. Additionally, a MMRS coordination approach is proposed where a heterogeneous group of marine vehicles must explore an unknown area maximizing communication. The proposed approach uses a real characterization of the acoustic communication signal quality as input to the decision making process.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Findings from Polytechnic University of Catalonia Advance Knowledge in Robotics (Driving Strategies for Omnidirectional Mobile Robots with Offset Differential Wheels)

    36-36页
    查看更多>>摘要：Researchers detail new data in robotics. According to news originating from Barcelona, Spain, by NewsRx correspondents, research stated, “In this work, we present an analysis of, as well as driving strategies and design considerations for, a type of omnidirectional mobile robot: the offset-differential robot.” The news reporters obtained a quote from the research from Polytechnic University of Catalonia: “This system presents omnidirectionality while using any type of standard wheel, allowing for applications in uneven and rough terrains, as well as cluttered environments. The known fact that these robots, as well as simple differential robots, have an unstable driving zone, has mostly been dealt with by designing driving strategies in the stable zone of internal dynamics. However, driving in the unstable zone may be advantageous when dealing with rough and uneven terrains. This work is based on the full kinematic and dynamic analysis of a robot, including its passive elements, to explain the unexpected behaviors that appear during its motion due to instability. Precise torque calculations taking into account the configuration of the passive elements were performed for better torque control, and design recommendations are included. The stable and unstable behaviors were characterized, and driving strategies were described in order to achieve the desired performance regarding precise positioning and speed.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    University of Adelaide Reports Findings in Epilepsy (Identifying epilepsy surgery referral candidates with natural language processing in an Australian context)

    37-38页
    查看更多>>摘要：New research on Central Nervous System Diseases and Conditions - Epilepsy is the subject of a report. According to news reporting originating in Adelaide, Australia, by NewsRx journalists, research stated, “Epilepsy surgery is known to be underutilized. Machine learning-natural language processing (ML-NLP) may be able to assist with identifying patients suitable for referral for epilepsy surgery evaluation.” The news reporters obtained a quote from the research from the University of Adelaide, “Data were collected from two tertiary hospitals for patients seen in neurology outpatients for whom the diagnosis of ‘epilepsy’ was mentioned. Individual case note review was undertaken to characterize the nature of the diagnoses discussed in these notes, and whether those with epilepsy fulfilled prespecified criteria for epilepsy surgery workup (namely focal drug refractory epilepsy without contraindications). ML-NLP algorithms were then developed using fivefold cross-validation on the first free-text clinic note for each patient to identify these criteria. There were 457 notes included in the study, of which 250 patients had epilepsy. There were 37 (14.8%) individuals who fulfilled the prespecified criteria for epilepsy surgery referral without described contraindications, 32 (12.8%) of whom were not referred for epilepsy surgical evaluation in the given clinic visit. In the prediction of suitability for epilepsy surgery workup using the prespecified criteria, the tested models performed similarly. For example, the random forest model returned an area under the receiver operator characteristic curve of 0.97 (95% confidence interval 0.93-1.0) for this task, sensitivity of 1.0, and specificity of 0.93. This study has shown that there are patients in tertiary hospitals in South Australia who fulfill prespecified criteria for epilepsy surgery evaluation who may not have been referred for such evaluation. ML-NLP may assist with the identification of patients suitable for such referral. Epilepsy surgery is a beneficial treatment for selected individuals with drug-resistant epilepsy. However, it is vastly underutilized. One reason for this underutilization is a lack of prompt referral of possible epilepsy surgery candidates to comprehensive epilepsy centers. Natural language processing, coupled with machine learning, may be able to identify possible epilepsy surgery candidates through the analysis of unstructured clinic notes. This study, conducted in two tertiary hospitals in South Australia, demonstrated that there are individuals who fulfill criteria for epilepsy surgery evaluation referral but have not yet been referred.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    New Machine Learning Study Results from Florida International University Described (A Review of On-device Machine Learning for Iot: an Energy Perspective)

    38-39页
    查看更多>>摘要：Research findings on Machine Learning are discussed in a new report. According to news reporting out of Miami, Florida, by NewsRx editors, research stated, “Recently, there has been a substantial interest in on-device Machine Learning (ML) models to provide intelligence for the Internet of Things (IoT) applications such as image classification, human activity recognition, and anomaly detection. Traditionally, ML models are deployed in the cloud or centralized servers to take advantage of their abundant computational resources.” Financial supporters for this research include Cyber Florida, and Microsoft, Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK).
      原文链接:
    • NETL
    • NSTL
    • Elsevier