查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in Robotics. According to news originating from Shaanxi, People's Republic of China, by NewsRx correspondents, research stated, "Flying cable-driven parallel robots (CDPRs) are a special subclass of cable-driven robots that offer mobility in air compared with the traditional CDPRs. These flying CDPRs possess weaker stiffness due to their high maneuverability and cable's unilaterality, which may result in fluctuations around a desired nominal moving platform pose." Financial support for this research came from Shaanxi Provincial Science and Technology Department. Our news journalists obtained a quote from the research from Xi'an Technological University, "The focus of this study is on the derivation of the overall stiffness and enhancement method of stiffness with regard to the weakest degree of freedom. The overall stiffness is divided into two parts, namely, active and passive stiffnesses. The line geometry theory is introduced to derive the explicit expression of the active stiffness, which is a 3D Hessian matrix. Results showed that the rotational stiffness around the z-axis kzz is the weakest stiffness based on the overall stiffness matrix expression. Furthermore, we summarize the stiffness distribution of the flying CDPR in the entire workspace. Specifically, we present a stiffness-oriented cable tension distribution algorithm to achieve the best feasible stiffness considering the enhancement of kzz and tensions' limit, which is only applicable for the flying CDPR with redundant actuation."
查看更多>>摘要：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 originating from Sakarya University of Applied Sciences by NewsRx correspondents, research stated, "In this study, an interface design was carried out in order to provide convenience to the user in the control and monitoring of the Robot Operating System (ROS) based autonomous mobile robot (AMR). Qt Designer and Python were used in the interface design." Funders for this research include Sakarya Uygulamali Bilimler Universitesi, Bilimsel Arastirma Projeleri Koordinatorlugu, Tubi tak. Our news editors obtained a quote from the research from Sakarya University of Applied Sciences: "Thanks to the designed interface, autonomous and manual control of AMR was provided. Using the gmapping algorithm, the environment in the virtual world was mapped and transformed into a picture in .png format and visualized in the interface. The location information from the ROS was transferred to the said picture and the instant tracking of the AMR was done via the interface. It was shown which algorithm is used locally and globally at that moment. While in autonomous mode, the vehicle was provided to move to the previously recorded point. The total distance and time spent by the AMR while moving between two points were also calculated by the interface. The location (x, y, z) and orientations (x, y, z, w) of the previously recorded station were monitored from the stop list."
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 Robotics have been published. According to news report- ing originating in Cambridge, Massachusetts, by NewsRx journalists, research stated, "Human-machine interfaces for capturing, conveying, and sharing tactile information across time and space hold immense potential for healthcare, augmented and virtual reality, human-robot collaboration, and skill development. To realize this potential, such interfaces should be wearable, unobtrusive, and scalable regarding both resolution and body coverage." Financial supporters for this research include Wistron, Toyota Research Institute, Ericsson.
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 Artificial Intelligence. According to news reporting originating from Iasi, Romania, by NewsRx correspondents, research stated, "This paper tackles the influence of the functionalization of polystyrene and graphene oxide (GO) composites on the flammability characteristics. A microscale combustion calorimeter (MCC) was used to experimentally determine the heat release capacity (HRC), the specific heat release rate (HRR) and the total heat released (THR)." Financial supporters for this research include Ministerul Cercetabreve;rii, Inovabreve;rii scedil;i Digitalizabreve; rii, Ministry of Research, Innovation and Digitization, CNCS/CCCDI-UEFISCDI.
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 out of Punjab, India, by NewsRx editors, research stated, "Deep generative models, especially Generative Adversarial Networks (GANs), have recently demonstrated outstanding performance in realworld applications such as image generation and content production for large-scale public datasets and social media platforms, enabling high-resolution compelling fake content generation. Deepfakes have raised global concerns and disbelief due to the potential implications of misleading multimedia." Our news journalists obtained a quote from the research from the Dr B.R. Ambedkar National Institute of Technology, "Several algorithms to detect deepfakes have emerged; however, most rely on deep learning and video datasets. So, an automated approach is needed to detect the generated deepfakes. This paper presents a deepfake detection technique employing simple machine learning to identify low-resolution deepfakes and introduces a dataset that contains high-resolution, low-resolution, and mixed images. The method utilizes classification algorithms and an ensemble model in the frequency domain."
查看更多>>摘要：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 originating from Vicksburg, Mississippi, by NewsRx correspondents, research stated, "Connecting the Mississippi River and the Gulf of Mexico, the Southwest Pass (SWP) is one of the most highly utilized commercial waterways in the United States. Hard-to-predict accumulation of sediments in the SWP affects the access of deep-draft vessels to four of the nation's top 15 ports measured by tonnage. The U.S." Funders for this research include USACE Mississippi Valley Division, Dredging Innovations Group (DIG), USACE New Orleans District, USGS National Water Information System.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intelligence are discussed in a new report. According to news reporting from Shanghai, People's Republic of China, by NewsRx journalists, research stated, "The evaluation of thermoelectric materials relies significantly on the thermoelectric figure of merit, ZT, which serves as a crucial parameter in assessing their properties." Funders for this research include National Natural Science Foundation of China; Science And Technology Innovation Plan of Shanghai Science And Technology Commission. Our news editors obtained a quote from the research from Shanghai Polytechnic University: "The accurate prediction of ZT values can be accomplished by utilizing machine learning models to learn material characteristics. However, factors such as the size of the dataset, model hyperparameters, and data quality can all impact the accuracy of machine learning. In contrast to previous research where high-dimensional features were simply discarded to transform them into low-dimensional ones, deep learning models such as autoencoder can extract more effective information. Therefore, in this article, the combination of autoencoders and the Light Gradient Boosting Machine (LightGBM) is employed to learn the chemical characteristics and ZT values of various materials. The reliability of the model was confirmed by achieving an R2 score of 0.94 during tenfold cross-validation. 130 000 materials were predicted and screened, the temperature dependence of the screened materials was studied in depth, and 13 materials with high ZT values were identified."
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 Machine Learning. According to news reporting originating from Prayagraj, India, by NewsRx correspondents, research stated, "In today's revolution of artificial intelligence, machine learning (ML) has come up with providing most rapid, accurate solution towards many complicated design problems. In this paper, a regression-based machine learning model has been developed, trained, and tested to forecast the performance of the Terahertz absorber." Our news editors obtained a quote from the research from the Motilal Nehru National Institute of Technology Allahabad, "Different parameter variations of the dual circular ring Graphene FSS absorber viz., periodicity, thicknesses and radius of circular rings have been performed to attain maximum absorption of 99.9 % at center frequency 10.5 THz and bandwidth 1 THz (10.0 THz-11.0 THz). The efficiency of nine different regression models (Keras regressor, Histogram gradient regressor, adaboost regressor, gradient boosting regressor, random forest regressor, decision tree regressor, k neighbours regressor, ridge regression, and linear regression) were tested against accurately predicting the absorption values and their performances were compared using R2 score and RSME. The study yielded very good R2 scores (near to 1.0) in case of random forest regression, thereby, demonstrating its effectiveness for future absorptivity prediction."
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 Intelligence is the subject of a report. According to news reporting out of Istanbul, Turkey, by NewsRx editors, research stated, "To determine how radiology, nuclear medicine, and medical imaging journals encourage and mandate the use of reporting guidelines for artificial intelligence (AI) in their author and reviewer instructions. The primary source of journal information and associated citation data used was the Journal Citation Reports (June 2023 release for 2022 citation data; Clarivate Analytics, UK)." Our news journalists obtained a quote from the research from the University of Health Sciences, "The first- and second-quartile journals indexed in the Science Citation Index Expanded and the Emerging Sources Citation Index were included. The author and reviewer instructions were evaluated by two independent readers, followed by an additional reader for consensus, with the assistance of automatic annotation. Encouragement and submission requirements were systematically analyzed. The reporting guidelines were grouped as AI-specific, related to modeling, and unrelated to modeling. Out of 102 journals, 98 were included in this study, and all of them had author instructions. Only five journals (5%) encouraged the authors to follow AI-specific reporting guidelines. Among these, three required a filled-out checklist. Reviewer instructions were found in 16 journals (16%), among which one journal (6%) encouraged the reviewers to follow AI-specific reporting guidelines without submission requirements. The proportions of author and reviewer encouragement for AI-specific reporting guidelines were statistically significantly lower compared with those for other types of guidelines (<0.05 for all). The findings indicate that AI-specific guidelines are not commonly encouraged and mandated (i.e., requiring a filled-out checklist) by these journals, compared with guidelines related to modeling and unrelated to modeling, leaving vast space for improvement. This meta-research study hopes to contribute to the awareness of the imaging community for AI reporting guidelines and ignite large-scale group efforts by all stakeholders, making AI research less wasteful. This meta-research highlights the need for improved encouragement of AI-specific guidelines in radiology, nuclear medicine, and medical imaging journals."
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 out of Punjab, India, by NewsRx editors, research stated, "This study proposes an ensemble approach to develop a tomato ripeness and shelf life prediction system based on defects and color intensity. The dataset has been created by designing an image acquisition system to capture 3450 images." Financial support for this research came from Thapar-TAU Centre for Excellence in Food Security (T2CEFS) under the research project "A Data-Driven Approach to Precision Agriculture in Small Farms Project.
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