查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting out of Atlanta, Georgia, by NewsRx edito rs, research stated, “Shape transformations of active composites (ACs) depend on the spatial distribution and active response of constituent materials. Voxel-le vel complex material distributions offer a vast possibility for attainable shape changes of 4D-printed ACs, while also posing a significant challenge in efficie ntly designing material distributions to achieve target shape changes.” Financial supporters for this research include Air Force Office of Scientific Re search (AFOSR), HP, Inc.
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 originating from the State Key Laboratory by NewsRx correspondents, research stated, “In order to eliminate the limitations of traditional winter wheat yield prediction methods, the prediction models base d on machine learning are used to improve the accuracy of winter wheat yield pre diction.” Funders for this research include Development Mode And Intelligent Control Techn ology of Ecological Agriculture in Modern Irrigation Area.
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 th e subject of a report. According to news originating from Urbana, Illinois, by N ewsRx correspondents, research stated, “Adversarial examples have recently drawn considerable attention in the field of machine learning due to the fact that sm all perturbations in the data can result in major performance degradation. This phenomenon is usually modeled by a malicious adversary that can apply perturbati ons to the data in a constrained fashion, such as being bounded in a certain nor m.” Financial support for this research came from National Science Foundation (NSF).
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 Intell igence are discussed in a new report. According to news reporting out of Santa B arbara, California, by NewsRx editors, research stated, “The discovery of new cr ystalline inorganic compounds- novel compositions of matter within known structu re types, or even compounds with completely new crystal structures-constitutes a n important goal of solid-state and materials chemistry. Some fractions of new c ompounds can eventually lead to new structural and functional materials that enh ance the efficiency of existing technologies or even enable completely new techn ologies.” Financial supporters for this research include United States Department of Energ y (DOE), United States Department of Energy (DOE).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning - Compu tational Intelligence are presented in a new report. According to news originati ng from Tulsa, Oklahoma, by NewsRx correspondents, research stated, “Due to the increasing demand for electricity and the inherent uncertainty in power generati on, finding efficient solutions to the stochastic alternating current optimal po wer flow (AC-OPF) problem has become crucial. However, the nonlinear and non-con vex nature of AC-OPF, coupled with the growing stochasticity resulting from the integration of renewable energy sources, presents significant challenges in achi eving fast and reliable solutions.” Our news journalists obtained a quote from the research from the University of T ulsa, “To address these challenges, this study proposes a novel graph-based gene rative methodology that effectively captures the uncertainties in power system m easurements, enabling the learning of probability distribution functions for gen eration dispatch and voltage setpoints. Our approach involves modeling the power system as a weighted graph and utilizing a deep spectral graph convolution netw ork to extract powerful spatial patterns from the input graph measurements. A un ique variational approach is introduced to identify the most relevant latent fea tures that accurately describe the setpoints of the AC-OPF problem. Additionally , a capsule network with a new greedy dynamic routing algorithm is proposed to p recisely decode the latent features and estimate the probabilistic AC-OPF proble m. Further, a set of carefully designed physics-informed loss functions is incor porated in the training procedure of the model to ensure adherence to the fundam ental physics rules governing power systems. Notably, the proposed physics-infor med loss functions not only enhance the accuracy of AC-OPF estimation by effecti vely regularizing the deep learning model but also significantly reduce the time complexity.”
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 th e subject of a report. According to news originating from London, Canada, by New sRx correspondents, research stated, “It remains difficult to predict longitudin al outcomes in long-COVID, even with chest CT and functional MRI. Xe MRI reflect s airway dysfunction, measured using ventilation defect percent (VDP) and in lon g-COVID patients, MRI VDP was abnormal, suggestive of airways disease.”
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 subjec t of a report. According to news reporting out of Quebec, Canada, by NewsRx edit ors, research stated, “This review article examines the extant literature on ani mism and anthropomorphism in infants and young children. A substantial body of w ork indicates that both infants and young children have a broad concept of what constitutes a sentient agent and react to inanimate objects as they do to people in the same context.” Our news journalists obtained a quote from the research from Concordia Universit y, “The literature has also revealed a developmental pattern in which anthropomo rphism decreases with age, but social robots appear to be an exception to this p attern. Additionally, the review shows that children attribute psychological pro perties to social robots less so than people but still anthropomorphize them. Im portantly, some research suggests that anthropomorphism of social robots is depe ndent upon their morphology and human-like behaviors. The extent to which childr en anthropomorphize robots is dependent on their exposure to them and the presen ce of human-like features. Based on the existing literature, we conclude that in infancy, a large range of inanimate objects (e.g., boxes, geometric figures) th at display animate motion patterns trigger the same behaviors observed in child- adult interactions, suggesting some implicit form of anthropomorphism. The revie w concludes that additional research is needed to understand what infants and ch ildren judge as social agents and how the perception of inanimate agents changes over the lifespan. As exposure to robots and virtual assistants increases, futu re research must focus on better understanding the full impact that regular inte ractions with such partners will have on children’s anthropomorphizing.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics - Robotics and Automation are presented in a new report. According to news originating from Sha nghai, People’s Republic of China, by NewsRx correspondents, research stated, “T actile perception stands as a critical sensory modality for human interaction wi th the environment. Among various tactile sensor techniques, optical sensor-base d approaches have gained traction, notably for producing high-resolution tactile images.” Financial support for this research came from National Key Ramp;D Program of Chi na.
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 Beijing, People’s Re public of China, by NewsRx editors, research stated, “In this study, a novel met hod integrating machine learning with damage mechanics is proposed for predictin g the high cycle fatigue life of ZM6 with internal defects. First, the character ization model of the effects of internal defects is presented, and the relations hip between the stress concentration factor and the parameters of the ellipsoida l void is established.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Immune System Diseases and Conditions - HIV/AIDS is the subject of a report. According to news origina ting from Guangxi, People’s Republic of China, by NewsRx correspondents, researc h stated, “This study aimed to construct a coronary heart disease (CHD) risk-pre diction model in people living with human immunodeficiency virus (PLHIV) with th e help of machine learning (ML) per electronic medical records (EMRs). Sixty-one medical characteristics (including demography information, laboratory measureme nts, and complicating disease) readily available from EMRs were retained for cli nical analysis.” Our news journalists obtained a quote from the research, “These characteristics further aided the development of prediction models by using seven ML algorithms [light gradient-boosting machine (LightGBM), support vector m achine (SVM), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), decision tree, multilayer perceptron (MLP), and logistic regression] . The performance of this model was assessed using the area under the receiver o perating characteristic curve (AUC). Shapley additive explanation (SHAP) was fur ther applied to interpret the findings of the best-performing model. The LightGB M model exhibited the highest AUC (0.849; 95% CI, 0.814-0.883). Ad ditionally, the SHAP plot per the LightGBM depicted that age, heart failure, hyp ertension, glucose, serum creatinine, indirect bilirubin, serum uric acid, and a mylase can help identify PLHIV who were at a high or low risk of developing CHD. This study developed a CHD risk prediction model for PLHIV utilizing ML techniq ues and EMR data. The LightGBM model exhibited improved comprehensive performanc e and thus had higher reliability in assessing the risk predictors of CHD.”
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