查看更多>>摘要：Researchers detail new data in Artificial Intelligence. According to news originating from Cambridge, Massachusetts, by NewsRx correspondents, research stated, “The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge is systematically translated to engineering solutions. To accelerate discovery and guide insights, an opensource autoregressive transformer large language model (LLM), BioinspiredLLM, is reported.” Funders for this research include Army Research Office, Office of Naval Research, U.S. Department of Agriculture.
查看更多>>摘要：A new study on Robotics is now available. According to news originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “To address the problem of multirobot collaborative task scheduling considering the degradation of industrial robot performance and the recovery of robot performance through intervention of compensation measures, a robot collaborative task scheduling method based on multiagent reinforcement learning with heuristic graph convolution is proposed in this paper. Five types of constraints between tasks and robots from the temporal and spatial dimensions are designed, and a graph structure with different connection forms is utilized to represent the tasks, robots, and their mutual constraints.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), Defense Industrial Technology Development Program of China.
查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting out of Chengalpattu, India, by NewsRx editors, research stated, “Tilted Fiber Bragg Grating (TFBG) coated with humidity and temperature responsive material is proposed for simultaneous measurement of environmental parameters. Different types of materials are analyzed to optimize the coating material on the grating structure for the measurement of humidity and temperature simultaneously.” Financial supporters for this research include SRM Institute of Science and Technology, Kattankulathur, India, Institution of Engineers (India). Our news journalists obtained a quote from the research from the College of Engineering and Technology, “The optimized coating material is used to fabricate the sensor and experimentally investigated under different humidity and temperature conditions. To further enhance the performance, machine learning algorithms such as Gaussian Progress Regression, Random Forest, K-Nearest Neighbor, AdaBoost, Gradient Boosting algorithm were trained with the spectrum data to estimate the environmental parameters simultaneously.”
查看更多>>摘要：Fresh data on robotics are presented in a new report. According to news reporting originating from the School of Engineering and Sciences by NewsRx correspondents, research stated, “Human-robot collaboration has gained attention in the field of manufacturing and assembly tasks, necessitating the development of adaptable and user-friendly forms of interaction.” Financial supporters for this research include Tecnologico De Monterrey, Vicerrectory of Research And Technology Transfer. Our news journalists obtained a quote from the research from School of Engineering and Sciences: “To address this demand, collaborative robots (cobots) have emerged as a viable solution. Deep Learning has played a pivotal role in enhancing robot capabilities and facilitating their perception and understanding of the environment. This study proposes the integration of cobots and Deep Learning to assist users in assembly tasks such as part handover and storage. The proposed system includes an object classification system to categorize and store assembly elements, a voice recognition system to classify user commands, and a hand-tracking system for close interaction. Tests were conducted for each isolated system and for the complete application as used by different individuals, yielding an average accuracy of 91.25%.”
查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting out of Trento, Italy, by NewsRx editors, research stated, “Default prediction is the primary goal of credit risk management. This problem has long been tackled using well-established statistical classification models.” Financial support for this research came from We would like to thank the associate editor and an anonymous reviewer for valuable comments that have considerably improved a preliminary version of the paper.. Our news journalists obtained a quote from the research from the University of Trento, “Still, nowadays, the availability of large datasets and cheap software implementations makes it possible to employ machine learning techniques. This paper uses a large sample of small Italian companies to compare the performance of various machine learning classifiers and a more traditional logistic regression approach. In particular, we perform feature selection, use the algorithms for default prediction, evaluate their accuracy, and find a more suitable threshold as a function of sensitivity and specificity. Our outcomes suggest that machine learning is slightly better than logistic regression.”
查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news originating from Changsha, People’s Republic of China, by NewsRx correspondents, research stated, “Machine learning(ML) assisted high-entropy alloys(HEA) design is dedicated to solving the problem of long period and high cost of designing by traditional trial and error experimental methods.” Our news reporters obtained a quote from the research from National University of Defense Technology: “The classic AlCoCrCuFeNi HEA was taken as the research object. The phase structure prediction model and hardness prediction model were established respectively. The support vector machine(SVM) models have the best training performance in both tasks. The best phase classification accuracy is 0.944, and the root mean square error(RMSE) of the hardness regression model is 56.065HV. The two ML models are further connected in series. Based on the upper and lower limits of the data set, the high-throughput prediction and selection of phases and hardness of AlCoCrCuFeNi HEA are carried out simultaneously, thus realizing the efficient composition design of the new alloy.”
查看更多>>摘要：Data detailed on robotics have been presented. According to news reporting originating from Ho Chi Minh City, Vietnam, by NewsRx correspondents, research stated, “Accurate and robust pedestrian detection is fundamental for indoor robotic systems to navigate safely and seamlessly alongside humans in spatially constrained, unpredictable indoor environments. This paper presents a novel method, IRBGHR-PIXOR, a detection framework specifically engineered for pedestrian perception in indoor mobile robots.” Our news journalists obtained a quote from the research from Ho Chi Minh City University of Technology: “This novel approach employs an enhanced adaptation of the cutting-edge PIXOR model, integrating two pivotal augmentations: a remodeled convolutional backbone leveraging Inverted Residual Blocks (IRB) in unison with Gaussian Heatmap Regression (GHR), as well as a Modified Focal Loss (MFL) function to tackle data imbalance issues. The IRB component notably bolsters the network’s aptitude for processing intricate spatial representations generated from sparse 3D LiDAR scans. Meanwhile, integrating GHR further elevates accuracy by enabling precise localization of pedestrian subjects. This is achieved by modeling the probability distribution and predicting the central location of individuals in the point cloud data. Extensively evaluated on the large-scale JRDB dataset comprising intense scans from 16-beam Velodyne LiDAR sensors, IRBGHR-PIXOR accomplishes exceptional results, attaining 97.17% Average Precision (AP) at the 0.5 IOU threshold. Notably, this level of accuracy is achieved without significantly increasing model complexity. By enhancing algorithms to overcome challenges in confined indoor environments, this research paves the way for safe and effective deployment of autonomous technologies once encumbered by perceptual limitations in human-centered spaces.”
查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating in Teresina, Brazil, by NewsRx journalists, research stated, “The aging process affects mechanisms for maintaining physical integrity. The assessment of the risk of falls is routine in the services of assistance to the elderly, but subjective and time-consuming, so that the automation of the process is desirable as a supporting tool.” Funders for this research include Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES), Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ). The news reporters obtained a quote from the research from Federal University Piaui, “In this regard, the aim of this study is to carry out a comprehensive evaluation study on the use of machine learning techniques as an instrument to predict the Berg Balance Scale (BBS) score, using different sets of electromyographic and dynamometric data collected during a voluntary isometric contraction. Thirty participants were evaluated with the BBS and with electromyography and dynamometry of the vastus lateralis, biceps femoris, lateral gastrocnemius and tibialis anterior muscles during maximal isometric voluntary contractions. After pre-processing the dataset, the features were selected through principal components analysis (PCA), correlation-based function select (CFS) and relief-F to then be applied to the multilayer perceptron (MLP), random forest (RF), random tree (RT), k-nearest neighbors (KNN), Multiple Linear Regression (MLR), and least-squares support vector regression (LS-SVR). From the fitted regression models, our ultimate goal is to infer which selected features correlate most with the risk of falling for elderly people and how those features connect themselves to certain groups of muscles. In this regard, the features extracted from myoelectric signals proved to be more effective for use in predicting the risk of falls in the elderly in relation to the force-related signal.”
查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting from Atlanta, Georgia, by NewsRx journalists, research stated, “We present a Delta-machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine-learned force field (MLFF) scheme based on the kernel method to capture the difference between Kohn-Sham and orbital-free DFT energies/forces.” Funders for this research include United States Department of Energy (DOE), United States Department of Energy (DOE), United States Department of Energy (DOE), Advanced Computing Environment (PACE) through its Hive (U.S. National Science Foundation), Phoenix clusters at Georgia Institute of Technology, Atlanta, Georgia.
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Guangdong, People’s Republic of China, by NewsRx correspondents, research stated, “With the rapid development of medical imaging technology and computer technology, the medical imaging artificial intelligence of computer-aided diagnosis based on machine learning has become an important part of modern medical diagnosis. With the application of medical image security technology, people realize that the difficulty of its development is the inherent defect of advanced image processing technology.” Our news journalists obtained a quote from the research from the Southern University of Science and Technology Hospital, “This paper introduces the background of colorectal cancer diagnosis and monitoring, and then carries out academic research on the medical imaging artificial intelligence of colorectal cancer diagnosis and monitoring and machine learning, and finally summarizes it with the advanced computational intelligence system for the application of safe medical imaging.In the experimental part, this paper wants to carry out the staging preparation stage. It was concluded that the staging preparation stage of group Y was higher than that of group X and the difference was statistically significant. Then the overall accuracy rate of multimodal medical image fusion was 69.5% through pathological staging comparison. Finally, the diagnostic rate, the number of patients with effective treatment and satisfaction were analyzed. Finally, the average diagnostic rate of the new diagnosis method was 8.75% higher than that of the traditional diagnosis method. With the development of computer science and technology, the application field was expanding constantly.”
NETL
NSTL
Wiley
Elsevier
Mdpi
Springer Nature
IEEE