查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial intelligence have been published. According to news reporting from the University Institute of Technology by NewsRx journalists, research stated, “The purpose of this work is to classify pepper seeds using color filter array (CFA) images.” The news reporters obtained a quote from the research from University Institute of Technology: “This study focused specifically on Penja pepper, which is found in the Litoral region of Cameroon and is a type of Piper nigrum. India and Brazil are the largest producers of this variety of pepper, although the production of Penja pepper is not as significant in terms of quantity compared to other major producers. However, it is still highly sought after and one of the most expensive types of pepper on the market. It can be difficult for humans to distinguish between different types of peppers based solely on the appearance of their seeds. To address this challenge, we collected 5618 samples of white and black Penja pepper and other varieties for classification using image processing and a supervised machine learning method.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – 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 Tallinn, Estonia, by NewsRx editors, research stated, “The Forming Limit Curve (FLC), which describes the maximum applicable strain before localization, depends the particular material, but also on the applied load and history of the load. Recent investigations have shown that the non-proportional loading effect on the FLC can be predicted with data-driven or machine-learning based methods.” Financial support for this research came from Estonian Research Council.
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Neurodegenerative Diseases and Conditions - Huntington Disease is the subject of a report. According to news reporting originating in Rochester, New York, by NewsRx journalists, research stated, “Speech changes are an early symptom of Huntington disease (HD) and may occur prior to other motor and cognitive symptoms. Assessment of HD commonly uses clinician-rated outcome measures, which can be limited by observer variability and episodic administration.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting out of Winnipeg, Canada, by NewsRx editors, research stated, “Links between human milk (HM) and infant development are poorly understood and often focus on individual HM components. Here we apply multi-modal predictive machine learning to study HM and head circumference (a proxy for brain development) among 1022 mother-infant dyads of the CHILD Cohort.” Funders for this research include Bundesministerium fur Bildung und Forschung, National Institutes of Health, Alfred E. Mann Foundation, Canadian Institutes of Health Research, AllerGen Network of Centers of Excellence, Research Manitoba, Children’s Hospital Research Institute of Manitoba, Canadian Respiratory Research Network, Manitoba Medical Services Foundation, Canada Research Chairs Program, Don and Debbie Morrison, SickKids Foundation.
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics are discussed in a new report. According to news reporting out of Punjab, India, by NewsRx editors, research stated, “Enormous assistance is required during rehabilitation activities, which might result in a variety of complications if performed manually. To solve this issue, several solutions in the form of assistive devices have been presented recently.” Financial supporters for this research include Department of Science & Technology (India), Global Innovation and Technology Alliance (GITA).
查看更多>>摘要：2024 FEB 20 (NewsRx) – 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 originating from Samsun, Turkey, by NewsRx correspondents, research stated, “Having the advantages of speed, suitability and high accuracy, computer vision has been effectively utilized as a non-destructive approach to automatically recognize and classify fruits and vegetables, to meet the increased demand for food quality-sensing devices.” Funders for this research include National University of Science And Technology Politehnica Bucharest.
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics are discussed in a new report. According to news reporting out of Qinhuangdao, People’s Republic of China, by NewsRx editors, research stated, “In tasks that require improved mechanical strength and load-bearing capacity, such as the handling of heavy or large-volume objects, multi-robot collaborative control is of utmost importance. In this paper, a novel control framework is introduced for multi-robot cooperation, aiming to address the challenges presented by dynamic coupling, anisotropy, the lack of velocity information, and the significant network transmission load within large-scale robot cooperation systems.” Financial support for this research came from National Natural Science Foundation of China (NSFC).
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on artificial intelligence have been presented. According to news reporting originating from Rasht, Iran, by NewsRx correspondents, research stated, “Applying efficient feature extraction and selection methods is essential in improving the performance of machine learning algorithms employed in brain-computer interface (BCI) systems.” The news correspondents obtained a quote from the research from University of Guilan: “The current study aims to enhance the performance of a motor imagery-based BCI by improving the feature extraction and selection stages of the machine-learning algorithm applied to classify the different imagined movements. In this study, a multi-rate system for spectral decomposition of the signal is designed, and then the spatial and temporal features are extracted from each sub-band. To maximize the classification accuracy while simplifying the model and using the smallest set of features, the feature selection stage is treated as a multiobjective optimization problem, and the Pareto optimal solutions of these two conflicting objectives are obtained. For the feature selection stage, non-dominated sorting genetic algorithm Ⅱ (NSGA-II), an evolutionary-based algorithm, is used wrapper-based, and its effect on the BCI performance is explored. The proposed method is implemented on a public dataset known as BCI competition Ⅲ dataset IVa. Extracting the spatial and temporal features from different sub-bands and selecting the features with an evolutionary optimization approach in this study led to an improved classification accuracy of 92.19% which has a higher value compared to the state of the art.”
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Robotics have been presented. According to news reporting originating from Cambridge, Massachusetts, by NewsRx correspondents, research stated, “In this article, we develop an algorithm for resilient path planning, where a team of robots must navigate in a resilient formation such that they achieve $F$-resilience, meaning they can coordinate in the presence of up to $F$ adversaries. Resilient formations are those having high connectivity often achieved by driving robots close together.” Financial support for this research came from Office of Naval Research.
查看更多>>摘要：2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Coronavirus - COVID-19 is the subject of a report. According to news reporting originating in Valencia, Spain, by NewsRx journalists, research stated, “Vaccination against SARS-CoV-2 in immunocompromised patients with hematologic malignancies (HM) is crucial to reduce the severity of COVID-19. Despite vaccination efforts, over a third of HM patients remain unresponsive, increasing their risk of severe breakthrough infections.” The news reporters obtained a quote from the research from University Hospital Clinic Valencia, “This study aims to leverage machine learning’s adaptability to COVID-19 dynamics, efficiently select- ing patient-specific features to enhance predictions and improve healthcare strategies. Highlighting the complex COVID-hematology connection, the focus is on interpretable machine learning to provide valuable insights to clinicians and biologists. The study evaluated a dataset with 1166 patients with hematological diseases. The output was the achievement or non-achievement of a serological response after full COVID- 19 vaccination. Various machine learning methods were applied, with the best model selected based on metrics such as the Area Under the Curve (AUC), Sensitivity, Specificity, and Matthew Correlation Coeffi- cient (MCC). Individual SHAP values were obtained for the best model, and Principal Component Analysis (PCA) was applied to these values. The patient profiles were then analyzed within identified clusters. Sup- port vector machine (SVM) emerged as the best-performing model. PCA applied to SVM-derived SHAP values resulted in four perfectly separated clusters. These clusters are characterized by the proportion of patients that generate antibodies (PPGA). Cluster 1, with the second-highest PPGA (69.91%), included patients with aggressive diseases and factors contributing to increased immunodeficiency. Cluster 2 had the lowest PPGA (33.3%), but the small sample size limited conclusive findings. Cluster 3, representing the majority of the population, exhibited a high rate of antibody generation (84.39%) and a better prognosis compared to cluster 1. Cluster 4, with a PPGA of 66.33%, included patients with B-cell non-Hodgkin’s lymphoma on corticosteroid therapy. The methodology successfully identified four separate patient clusters using Machine Learning and Explainable AI (XAI). We then analyzed each cluster based on the percentage of HM patients who generated antibodies after COVID-19 vaccination.”
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