期刊,Robotics & Machine Learning Daily News 2024年卷Mar.5期_国家学术搜索

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Robotics & Machine Learning Daily News

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Robotics & Machine Learning Daily News/Journal Robotics & Machine Learning Daily News

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Imageomics poised to enable new understanding of life

1-2页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Embargoed until 1:30 p.m. ET, DENVER-Imageomics, a new field of science, has made stunning progress in the past year and is on the verge of major discoveries about life on Earth, according to one of the founders of the discipline. Tanya Berger-Wolf, faculty director of the Translational Data Analytics Institute at The Ohio State University, outlined the state of imageomics in a presentation on Feb. 17, 2024, at the annual meeting of the American Association for the Advancement of Science. "Imageomics is coming of age and is ready for its first major discoveries," Berger-Wolf said in an interview before the meeting. Imageomics is a new interdisciplinary scientific field focused on using machine learning tools to understand the biology of organisms, particularly biological traits, from images. Those images can come from camera traps, satellites, drones-even the vacation photos that tourists take of animals like zebras and whales, said Berger-Wolf, who is director of the Imageomics Institute at Ohio State, funded by the National Science Foundation.

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Study Results from Rush University Medical Center in the Area of Robotics Reported (Single Port Robot-assisted Pyeloplasty: an Early Comparative Outcomes Analysis)

2-3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 Robotics is the subject of a report. According to news originating from Chicago, Illinois, by NewsRx correspondents, research stated, "The treatment paradigm for ureteropelvic junction obstruction (UPJO) has shifted towards minimally invasive pyeloplasty. A comparison Single Port (SP) and Multi Port (MP) robot-assisted pyeloplasty (RAP) was performed." Our news journalists obtained a quote from the research from Rush University Medical Center, "Data from consecutive patients undergoing SP RAP or MP RAP between January 2021 and September 2023 were collected and analysed. Co-primary outcomes were length of stay (LOS), Defense and Veterans Pain Rating Scale (DVPRS), and narcotic dose. The choice of the robotic system depended on the surgeon's preference and availability of a specific robotic platform. A total of 10 SP RAPs and 12 MP RAPs were identified. SP RAP patients were significantly younger [23 years (20-34)] than MP RAP [42 years (35.5- 47.5), p<0.01]. No difference in terms of OT (p = 0.6), LOS (p = 0.1), DVPRS (p = 0.2) and narcotic dose (p = 0.1) between the two groups was observed."

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Researcher at Basque Center on Cognition Discusses Research in Machine Learning (Early language dissociation in bilingual minds: magnetoencephalography evidence through a machine learning approach)

3-4页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on artificial intelligence. According to news reporting originating from Donostia San Sebastian, Spain, by NewsRx correspondents, research stated, "Does neural activity reveal how balanced bilinguals choose languages? Despite using diverse neuroimaging techniques, prior studies haven't provided a definitive solution to this problem." Funders for this research include Basque Government; Berc; Spanish State Research Agency; Bcbl's Severo; Spanish Ministry of Economy And Competitiveness; "la Caixa" Foundation; Agencia Estatal De Investigacion; Spanish Ministry of Science, Innovation And University; Fondo Europeo De Desarrollo Regional. The news editors obtained a quote from the research from Basque Center on Cognition: "Nonetheless, studies involving direct brain stimulation in bilinguals have identified distinct brain regions associated with language production in different languages. In this magnetoencephalography study with 45 proficient Spanish-Basque bilinguals, we investigated language selection during covert picture naming and word reading tasks. Participants were prompted to name line drawings or read words if the color of the stimulus changed to green, in 10% of trials. The task was performed either in Spanish or Basque. Despite similar sensor-level evoked activity for both languages in both tasks, decoding analyses revealed language-specific classification 100 ms post-stimulus onset. During picture naming, right occipital-temporal sensors predominantly contributed to language decoding, while left occipital-temporal sensors were crucial for decoding during word reading."

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Data on Machine Learning Reported by Researchers at Southern University of Science and Technology (SUSTech) (Application of Machine Learning Models In Groundwater Quality Assessment and Prediction: Progress and Challenges)

4-5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 Learning have been published. According to news reporting originating from Shenzhen, People's Republic of China, by NewsRx correspondents, research stated, "Groundwater quality assessment and prediction (GQAP) is vital for protecting groundwater resources. Traditional GQAP methods can not adequately capture the complex relationships among attributes and have the disadvantage of being computationally demanding." Financial support for this research came from Ministry of Science and Technology, China. Our news editors obtained a quote from the research from the Southern University of Science and Technology (SUSTech), "Recently, the application of machine learning (ML) in GAQP (GQAPxML) has been widely studied due to ML's reliability and efficiency. While many GQAPxML publications exist, a thorough review is missing. This review provides a comprehensive summary of the development of ML applications in the field of GQAP. First, the workflow of ML modeling is briefly introduced, as are data preparation, model development, model evaluation, and model application. Second, 299 publications related to the topic are filtered, mainly through ML modeling. Subsequently, many aspects of GQAPxML, such as publication trends, the spatial distribution of study areas, the size of data sets, and ML algorithms, are discussed from a bibliometric perspective. In addition, we review in detail the well-established applications and recent findings for several subtopics, including groundwater quality assessment, groundwater quality modeling using groundwater quality parameters, groundwater quality spatial mapping, probability estimation of exceeding the groundwater quality threshold, groundwater quality temporal prediction, and the hybrid use of ML and physics-based models. Finally, the development of GQAPxML is explored from three perspectives: data collection and preprocessing, model building and evaluation, and the broadening of model applications."

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Findings from Miguel Hernandez University of Elche Broaden Understanding of Machine Learning (Evaluating Different Methods for Ranking Inputs In the Context of the Performance Assessment of Decision Making Units: a Machine Learning Approach)

5-6页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Machine Learning. According to news reporting originating from Alicante, Spain, by NewsRx correspondents, research stated, "In the context of assessing the performance of decision-making units (companies, institutions, etc.), it is important to know the contribution or importance of each input to the generation of products and services in the production process. Identifying the degree of relevance of each input is a challenge from both an applied and a methodological point of view, especially within the field of non-parametric techniques, such as Data Envelopment Analysis (DEA), where the mathematical expression of the production function associated with the data generating process is not specified." Financial supporters for this research include Ministerio de Ciencia e Innovacion/Agencia Estatal de Investigacion, Center for Forestry Research & Experimentation (CIEF), Catedra Santander en Eficiencia y Productividad, Miguel Hernandez University (UMH), Valencian Community (Spain).

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New Robotics Study Findings Reported from Royal Melbourne Institute of Technology-RMIT University (Robust trajectory tracking of a 3-DOF robotic arm using a Super-Twisting Fast finite time Non-singular Terminal Sliding Mode Control in the ...)

6-7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 robotics. According to news reporting from Melbourne, Australia, by NewsRx journalists, research stated, "Extensive research has focused on enhancing the efficiency and stability of robotic arms. Sliding mode control (SMC) is commonly used in industrial robots due to its robustness and simplicity." The news journalists obtained a quote from the research from Royal Melbourne Institute of Technology-RMIT University: "However, SMC approaches have challenges such as chattering and slow convergence rates which can compromise tracking accuracy. To address these issues, this paper proposes a novel Super-Twisting Fast Non-singular Terminal Sliding Mode Control (ST-FNTSMC) strategy for a 3-DOF arm robot. The proposed approach significantly improves trajectory tracking accuracy, robustness, and convergence time and eliminates chattering. The proposed controller was tested in the presence of model mismatches and external disturbances. The super-twisting methodology avoided chattering effects and increased robustness against perturbations. Two Lyapunov functions ensure closed system stability and finite-time convergence."

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Reports from Guizhou University Add New Data to Research in Robotics (Electromechanical Coupling Model for Ionic Liquid Gel Soft Actuators)

7-8页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on robotics. According to news reporting out of Guizhou, People's Republic of China, by NewsRx editors, research stated, "A soft robot is composed of soft materials, which exhibit continuous deformation and driving structure integration and can arbitrarily change shapes and sizes over wide ranges." Financial supporters for this research include Department of Education of Guizhou Province. The news editors obtained a quote from the research from Guizhou University: "It shows strong adaptability to unstructured environments and has broad application prospects in military reconnaissance, medical rescues, agricultural production, etc. Soft robots based on ionic electroactive polymers (EAPs) have low-driving voltages, large-actuation displacements, fast responses, light weights, and low powers and have become a hot research field of bionic robots. Ionic liquid gels (ILGs) are new ionic EAPs. In this study, a new soft actuator was designed based on an ILG, and the electromechanical coupling model of an ILG soft actuator was studied in detail. Based on the system transfer function method, a mechatronic coupling model for the soft actuator was developed. According to the material characteristics and current response law of the ILG-containing EAP, an equivalent circuit model was used to describe transfer of the output current and input voltage."

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Data on Intelligent Transport Systems Discussed by Researchers at Southwest Jiaotong University (An Energy-efficient Timetable Optimization Method for Express/local Train With On-board Passenger Number Considered)

8-8页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Research findings on Transportation-Intelligent Transport Systems are discussed in a new report. According to news reporting originating in Chengdu, People's Republic of China, by NewsRx journalists, research stated, "With the expansion of the metropolitan area, the application of express/local mode is gradually increasing. In contrast to the normal mode, the express/local mode has advantages in reducing energy consumption and saving total travel time by having express trains skipping some stops." Financial support for this research came from Natural Science Foundation of Sichuan Province. The news reporters obtained a quote from the research from Southwest Jiaotong University, "This paper aims to minimize the total energy consumption of express and local train throughout the day by optimizing the train operation strategy in the same power supply section and increasing the overlap time between train traction acceleration and train regenerative braking to obtain the optimal energy-efficient timetable. As the consumed energy of a train is highly dependent on the rolling stock weight and the onboard passengers ‘ weight. An integer programming model is proposed with on-board passengers considered accurately, in which the dwell times, departure headway, and total turnaround time of express and local trains are determined. An improved grey wolf algorithm is designed by improving convergence factor and incorporating differential evolution to solve the proposed problem. The real data on Guangzhou Metro Line 18 is adopted for numerical studies."

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Report Summarizes Machine Learning Study Findings from University of Southern California (USC) (Machine Learning Enables Nongaussian Investigation of Changes To Peripheral Nerves Related To Electrical Stimulation)

9-9页

查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting out of Los Angeles, California, by NewsRx editors, research stated, "Electrical stimulation of the peripheral nervous system (PNS) is becoming increasingly important for the therapeutic treatment of numerous disorders." Financial supporters for this research include National Institutes of Health (NIH)-USA, NIBIB of the National Institute of Health, Research to Prevent Blindness (RPB). Our news journalists obtained a quote from the research from the University of Southern California (USC), "Thus, as peripheral nerves are increasingly the target of electrical stimulation, it is critical to determine how, and when, electrical stimulation results in anatomical changes in neural tissue. We introduce here a convolutional neural network and support vector machines for cell segmentation and analysis of histological samples of the sciatic nerve of rats stimulated with varying current intensities."

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Gunadarma University Researchers Describe Research in Machine Learning (Design of a traceability system for a coffee supply chain based on blockchain and machine learning)

10-10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 out of Gunadarma University by NewsRx editors, research stated, "This paper aims to develop a coffee supply chain traceability system based on Blockchain (BC) and Machine Learning (ML) with the aim of ensuring the quality of coffee beans production." Our news reporters obtained a quote from the research from Gunadarma University: "BC functions to ensure supply chain performance, while the ML model ensures product quality. Design/ methodology/approach: Smart Contracts will be built on the Ethereum Virtual Machine BC network based on Ethereum. The ML model to identify good and bad green coffee beans will be built using different YOLO algorithms, which will go through training and validation stages, namely using the k-fold cross validation method. The ML model algorithm is based on Convolutional Neural Network (CNN) using YOLOv5m, YOLOv6m and YOLOv7. The best model will be chosen based on the results of cross-validation with test data in the form of coffee image data that the model has never seen (unseen data). The whole process of building the ML model is done on the Google Collab Pro+ Virtual Machine."

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