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    Studies from SRM University Yield New Data on Machine Learning (Machine Learning -based Thermal Performance Study of Microchannel Heat Sink Under Non-uniform Hea t Load Conditions)

    48-48页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting out of Andhra Pradesh, Indi a, by NewsRx editors, research stated, “The parallel microchannel heat sink stan ds as a pivotal solution in managing high heat flux electronics due to its effic ient heat transfer characteristics and ease of manufacturing. While numerous stu dies have explored the thermal performance and flow characteristics of microchan nel heat sinks, most have focused on uniform heat loads or relied heavily on num erical methods.” Financial supporters for this research include Science and Engineering Research Board (SERB) through the Start-up Research Grant (SRG) , India, Science Engineer ing Research Board (SERB), India.
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    Researchers at Durban University of Technology Have Published New Data on Artifi cial Intelligence (The influence of artificial intelligence on the manufacturing industry in South Africa)

    49-49页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting from Durban University of T echnology by NewsRx journalists, research stated, “The adoption of artificial in telligence (AI) in manufacturing has the potential to considerably improve produ ctivity, efficiency and sustainability.” Our news journalists obtained a quote from the research from Durban University o f Technology: “Artificial intelligence aids with tasks such as data processing a nd process monitoring, process modelling and optimisation, live fault detection, and process quality assessment in manufacturing processes. This study sought to obtain a full understanding of the influence of AI on the South African manufac turing industry by exploring how AI technology is impacting productivity, reshap ing the workforce, affecting quality control practices and optimising supply cha in management among other issues. Data in this study were obtained from 23 quali tative research publications that address the influence of AI on the manufacturi ng industry in South Africa published on ScienceDirect, Scopus, Springer, Web of Science and Google Scholar. Multiple correspondence analysis was utilised to an alyse associations among quality, productivity, supply chain and workforce trans formation in the presence of AI in the South African manufacturing industry. The findings demonstrate a substantial association between the usage of AI and a ra nge of performance measures, suggesting that those organisations embracing AI te chnology can benefit from greater productivity, quality control and supply chain management. Additionally, findings emphasised the necessity of workforce transf ormation because of AI adoption.”
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    New Findings from University of West London Describe Advances in Robotics (An Im plementation of Communication, Computing and Control Tasks for Neuromorphic Robo tics on Conventional Low- Power CPU Hardware)

    50-51页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in robotic s. According to news originating from London, United Kingdom, by NewsRx correspo ndents, research stated, “Bioinspired approaches tend to mimic some biological f unctions for the purpose of creating more efficient and robust systems. These ca n be implemented in both software and hardware designs.” Funders for this research include University of West London. Our news journalists obtained a quote from the research from University of West London: “A neuromorphic software part can include, for example, Spiking Neural N etworks (SNNs) or event-based representations. Regarding the hardware part, we c an find different sensory systems, such as Dynamic Vision Sensors, touch sensors , and actuators, which are linked together through specific interface boards. To run real-time SNN models, specialised hardware such as SpiNNaker, Loihi, and Tr ueNorth have been implemented. However, neuromorphic computing is still in devel opment, and neuromorphic platforms are still not easily accessible to researcher s. In addition, for Neuromorphic Robotics, we often need specially designed and fabricated PCBs for communication with peripheral components and sensors. Theref ore, we developed an all-in-one neuromorphic system that emulates neuromorphic c omputing by running a Virtual Machine on a conventional low-power CPU. The Virtu al Machine includes Python and Brian2 simulation packages, which allow the runni ng of SNNs, emulating neuromorphic hardware. An additional, significant advantag e of using conventional hardware such as Raspberry Pi in comparison to purpose-b uilt neuromorphic hardware is that we can utilise the built-in physical input-ou tput (GPIO) and USB ports to directly communicate with sensors. As a proof of co ncept platform, a robotic goalkeeper has been implemented, using a Raspberry Pi 5 board and SNN model in Brian2. All the sensors, namely DVS128, with an infrare d module as the touch sensor and Futaba S9257 as the actuator, were linked to a Raspberry Pi 5 board. We show that it is possible to simulate SNNs on a conventi onal low-power CPU running real-time tasks for low-latency and low-power robotic applications.”
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    New Findings Reported from All India Institute of Medical Sciences (AIIMS) Descr ibe Advances in Artificial Intelligence (Can Researchers Write their Articles by Artificial Intelligence?)

    51-51页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting out of Jharkhand, India, by NewsRx editors, research stated, “The advent of artificial intelligence (AI) has sparked considerable interest in its potential applications across various domains, including scientific research and academic writing.” Our news editors obtained a quote from the research from All India Institute of Medical Sciences (AIIMS): “However, many academicians are apprehensive about it because of ethical issues. This article explores the question of whether researc hers can leverage AI to write their articles. By analyzing an existing model of taking assistance from third-party editing services, it is clear that the usage of AI in writing articles may not be considered unethical.”
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    University of Bristol Researchers Describe New Findings in Artificial Intelligen ce (Governing AI in Southeast Asia: ASEAN’s way forward)

    52-53页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news reporting from Bristol, United Kingdom, by N ewsRx journalists, research stated, “Despite the rapid development of AI, ASEAN has not been able to devise a regional governance framework to address relevant existing and future challenges.” Our news editors obtained a quote from the research from University of Bristol: “This is concerning, considering the potential of AI to accelerate GDP among ASE AN member states in the coming years.This qualitative inquiry discusses AI gove rnance in Southeast Asia in the past 5 years and what regulatory policies ASEAN can explore to better modulate its use among its member states. It considers the unique political landscape of the region, defined by the adoption of unique nor ms such as non-interference and priority over dialog, commonly termed the ASEAN Way.”
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    Huaiyin Institute of Technology Researcher Focuses on Robotics (An Overview of M odel-Free Adaptive Control for the Wheeled Mobile Robot)

    52-52页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in robotic s. According to news reporting from Huai’an, People’s Republic of China, by News Rx journalists, research stated, “Control technology for wheeled mobile robots i s one of the core focuses in the current field of robotics research.” Our news correspondents obtained a quote from the research from Huaiyin Institut e of Technology: “Within this domain, model-free adaptive control (MFAC) methods , with their advanced data-driven strategies, have garnered widespread attention . The unique characteristic of these methods is their ability to operate without relying on prior model information of the control system, which showcases their exceptional capability in ensuring closed-loop system stability. This paper ext ensively details three dynamic linearization techniques of MFAC: compact form dy namic linearization, partial form dynamic linearization and full form dynamic li nearization. These techniques lay a solid theoretical foundation for MFAC. Subse quently, the article delves into some advanced MFAC schemes, such as dynamic eve nt-triggered MFAC and iterative learning MFAC.”
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    First Affiliated Hospital of Dalian Medical University Reports Findings in Artif icial Intelligence (Multicenter investigation of preoperative distinction betwee n primary central nervous system lymphomas and glioblastomas through interpretab le ...)

    53-54页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating in Liaonin g, People’s Republic of China, by NewsRx journalists, research stated, “Research into the effectiveness and applicability of deep learning, radiomics, and their integrated models based on Magnetic Resonance Imaging (MRI) for preoperative di fferentiation between Primary Central Nervous System Lymphoma (PCNSL) and Gliobl astoma (GBM), along with an exploration of the interpretability of these models. A retrospective analysis was performed on MRI images and clinical data from 261 patients across two medical centers.” The news reporters obtained a quote from the research from the First Affiliated Hospital of Dalian Medical University, “The data were split into a training set (n = 153, medical center 1) and an external test set (n = 108, medical center 2) . Radiomic features were extracted using Pyradiomics to build the Radiomics Mode l. Deep learning networks, including the transformer-based MobileVIT Model and C onvolutional Neural Networks (CNN) based ConvNeXt Model, were trained separately . By applying the ‘late fusion’ theory, the radiomics model and deep learning mo del were fused to produce the optimal Max- Fusion Model. Additionally, Shapley Ad ditive exPlanations (SHAP) and Grad-CAM were employed for interpretability analy sis. In the external test set, the Radiomics Model achieved an Area under the re ceiver operating characteristic curve (AUC) of 0.86, the MobileVIT Model had an AUC of 0.91, the ConvNeXt Model demonstrated an AUC of 0.89, and the Max-Fusion Model showed an AUC of 0.92. The Delong test revealed a significant difference i n AUC between the Max-Fusion Model and the Radiomics Model (P = 0.02). The Max-F usion Model, combining different models, presents superior performance in distin guishing PCNSL and GBM, highlighting the effectiveness of model fusion for enhan ced decision-making in medical applications.”
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    Tianjin University Reports Findings in Artificial Intelligence (Diagnostic evalu ation of blunt chest trauma by imaging-based application of artificial intellige nce: A review)

    54-55页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Tianjin, People ’s Republic of China, by NewsRx editors, research stated, “Artificial intelligen ce (AI) is becoming increasingly integral in clinical practice, such as during i maging tasks associated with the diagnosis and evaluation of blunt chest trauma (BCT). Due to significant advances in imaging-based deep learning, recent studie s have demonstrated the efficacy of AI in the diagnosis of BCT, with a focus on rib fractures, pulmonary contusion, hemopneumothorax and others, demonstrating s ignificant clinical progress.” Our news journalists obtained a quote from the research from Tianjin University, “However, the complicated nature of BCT presents challenges in providing a comp rehensive diagnosis and prognostic evaluation, and current deep learning researc h concentrates on specific clinical contexts, limiting its utility in addressing BCT intricacies. Here, we provide a review of the available evidence surroundin g the potential utility of AI in BCT, and additionally identify the challenges i mpeding its development.” According to the news editors, the research concluded: “This review offers insig hts on how to optimize the role of AI in the diagnostic evaluation of BCT, which can ultimately enhance patient care and outcomes in this critical clinical doma in.”
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    University of Munster Reports Findings in Microsurgery (Fully Telemetric Robotic Microsurgery: Clinical Experience With 23 Cases)

    55-56页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Surgery - Microsurgery is the subject of a report. According to news reporting from Munster, Germany, by NewsRx journalists, research stated, “Recently, there is an ongoing trend in plastic surgery with robotic-assisted microsurgery and supermicrosurgery devices being developed. Combining a telemetrically controlled robotic microscope with an also telemetrically controlled microsurgery robot unlocks synergistic effects with complete disconnection of the operating surgeon from the operating field.” The news correspondents obtained a quote from the research from the University o f Munster, “Here, we report the first clinical free flap reconstructions using t his setup. Twenty-three surgeries were performed with the combined remote approa ch using the Symani Surgical System and the RoboticScope in open microsurgery pr ocedures. Anastomosis time and ischemia time were recorded. The surgical perform ance for anastomoses was assessed using the modified Structured Assessment of Mi crosurgical Skills (SAMS) score. Subjective satisfaction was evaluated by the su rgeons in comparison with conventional microsurgery. To evaluate the learning cu rve, the senior authors first four (first group) and last four (last group) proc edures were compared. Overall, flap survival was 95.7%. The average arterial anastomosis time was 36.7 ? 10.9 min. Total time of surgery was 277.7 ? 63.8 min, and ischemia time was 100.6 ? 24.9 min. Most SAMS score parameters w ere significantly higher in the last group of surgical procedures compared with the first operations. Subjective satisfaction was equal or better with the combi ned robotic-assisted approach in most categories. Our data demonstrates safety a nd feasibility of the use of a combined remote approach.”
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    New Support Vector Machines Study Results Reported from Tianjin Agricultural Uni versity (Multi-task Support Vector Machine Classifier With Generalized Huber Los s)

    56-57页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Support Vector Machines. According to news reporting from Tianjin, People’s Repu blic of China, by NewsRx journalists, research stated, “Compared to single-task learning (STL), multi-task learning (MTL) achieves a better generalization by ex ploiting domain-specific information implicit in the training signals of several related tasks. The adaptation of MTL to support vector machines (SVMs) is a rat her successful example.” The news correspondents obtained a quote from the research from Tianjin Agricult ural University, “Inspired by the recently published generalized Huber loss SVM (GHSVM) and regularized multi-task learning (RMTL), we propose a novel generaliz ed Huber loss multi-task support vector machine including linear and non-linear cases for binary classification, named as MTL-GHSVM. The new method extends the GHSVM from single-task to multi-task learning, and the application of Huber loss to MTL-SVM is innovative to the best of our knowledge. The proposed method has two main advantages: on the one hand, compared with SVMs with hinge loss and GHS VM, our MTL-GHSVM using the differentiable generalized Huber loss has better gen eralization performance; on the other hand, it adopts functional iteration to fi nd the optimal solution, and does not need to solve a quadratic programming prob lem (QPP), which can significantly reduce the computational cost.”
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