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 originating from Hawthorn, Australia, by NewsRx correspondents, research stated, "Machine learning photo-z methods, t rained directly on spectroscopic redshifts, provide a viable alternative to trad itional template-fitting methods but may not generalize well on new data that de viates from that in the training set. In this work, we present a Hybrid Algorith m for WI(Y)de-range photo-z estimation with Artificial neural networks and TEmpl ate fitting (hayate), a novel photo-z method that combines template fitting and data-driven approaches and whose training loss is optimized in terms of both red shift point estimates and probability distributions." Financial supporters for this research include Australian Research Council, Aust ralian Research Council. Our news journalists obtained a quote from the research from the Swinburne Unive rsity of Technology, "We produce artificial training data from low-redshift gala xy spectral energy distributions (SEDs) at z<1.3, artifici ally redshifted up to z = 5. We test the model on data from the ZFOURGE surveys, demonstrating that hayate can function as a reliable emulator of eazy for the b road redshift range beyond the region of sufficient spectroscopic completeness. The network achieves precise photo-z estimations with smaller errors (sigma(NMAD )) than eazy in the initial low-z region (z <1.3), while b eing comparable even in the high-z extrapolated regime (1.3 <z<5). Meanwhile, it provides more robust photo-z estimati ons than eazy with the lower outlier rate (eta(0.2 )less than or similar to 1 pe r cent) but runs similar to 100 times faster than the original template-fitting method. We also demonstrate hayate offers more reliable redshift probability den sity functions, showing a flatter distribution of Probability Integral Transform scores than eazy. The performance is further improved using transfer learning w ith spec-z samples."
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 reporting out of Memphis, Tennessee, by NewsRx editors, research stated, "Machine learning (ML) may be superior to trad itional methods for clinical outcome prediction. We sought to systematically rev iew the literature on ML for clinical outcome prediction in cerebrovascular and endovascular neurosurgery." Our news journalists obtained a quote from the research from Semmes-Murphey Neur ologic and Spine Institute, "A comprehensive literature search was performed, an d original studies of patients undergoing cerebrovascular surgeries or endovascu lar procedures that developed a supervised ML model to predict a postoperative o utcome or complication were included. A total of 60 studies predicting 71 outcom es were included. Most cohorts were derived from single institutions (66.7% ). The studies included stroke (32), subarachnoid hemorrhage ((SAH) 16), unruptu red aneurysm (7), arteriovenous malformation (4), and cavernous malformation (1) . Random forest was the best performing model in 12 studies (20%) f ollowed by XGBoost (13.3%). Among 42 studies in which the ML model was compared with a standard statistical model, ML was superior in 33 (78.6% ). Of 10 studies in which the ML model was compared with a non-ML clinical predi ction model, ML was superior in nine (90%). External validation was performed in 10 studies (16.7%). In studies predicting functional outcome after mechanical thrombectomy the pooled area under the receiver operato r characteristics curve (AUROC) of the test set performances was 0.84 (95% CI 0.79 to 0.88). For studies predicting outcomes after SAH, the pooled AUROCs f or functional outcomes and delayed cerebral ischemia were 0.89 (95% CI 0.76 to 0.95) and 0.90 (95% CI 0.66 to 0.98), respectively. ML performs favorably for clinical outcome prediction in cerebrovascular and endova scular neurosurgery."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting from the University of C incinnati by NewsRx journalists, research stated, "Hadronization is an important part of physics modeling in Monte Carlo event generators, where quarks and gluo ns are bound into physically observable hadrons." Our news journalists obtained a quote from the research from University of Cinci nnati: "Today's generators rely on finely-tuned phenomenological models, such as the Lund string model; while these models have been quite successful overall, t here remain phenomenological areas where they do not match data well. A machine- learning-based alternative called MLhad, intended ultimately to be data-trainabl e, can simulate hadronization by encoding latentspace vectors, trained to be dis tributed according to a user-defined distribution using the sliced-Wasserstein d istance in the loss function, then decoding them. The multiplicities and cumulat ive kinematic distributions of pions generated with MLhad in this way match thos e generated using Pythia 8. While this architecture has been successful, an alte rnative using normalizing flows is convenient for generating non-pion hadrons an d for taking advantage of reweighting techniques to reduce computing time."
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 originating from Dalian, People's Republic o f China, by NewsRx editors, the research stated, "Although the extant literature demonstrates that mobile device icons change consumers' cognition of review hel pfulness, it reports contradictory findings: displaying mobile device icons eith er helps or hurts review helpfulness." Our news journalists obtained a quote from the research from the Dongbei Univers ity of Finance & Economics, "Drawing on the instability of periphe ral routes (ELM) and perceived effort, we found that the impact of mobile device icons on review helpfulness is contingent on review writing effort, represented by review length. Econometric and experimental analyses ensured the external an d internal validity of results, respectively."
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 disc ussed in a new report. According to news reporting from the University of Bristo l by NewsRx journalists, research stated, "Snails can stably slide across a surf ace with only a single high-payload sucker, offering an efficient adhesive locom otion mechanism for next-generation climbing robots." Financial supporters for this research include Rcuk | Engineering And Physical S ciences Research Council; Royal Academy of Engineering. The news reporters obtained a quote from the research from University of Bristol : "The critical factor for snails' sliding suction behaviour is mucus secretion, which reduces friction and enhances suction. Inspired by this, we proposed an a rtificial sliding suction mechanism. The sliding suction utilizes water as an ar tificial mucus, which is widely available and evaporates with no residue. The sl iding suction allows a lightweight robot (96 g) to slide vertically and upside d own, achieving high speeds (rotation of 53°/s and translation of 19 mm/s) and hi gh payload (1 kg as tested and 5.03 kg in theory), and does not require energy d uring adhesion."
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 originating from Xi'an, People's Repu blic of China, by NewsRx correspondents, research stated, "The transverse streng th of unidirectional carbon fiber reinforced polymer (UD-CFRP) composites is a h igh dimensional and nonlinear function of microstructure due to the wide scatter in mechanical properties and complex failure mechanisms, which is a challenging task to develop a general microstructure dependent strength criterion (MDSC) in theory or computation. Volume fraction and distribution of fibers are among the crucial influencing factors." Funders for this research include National Natural Science Foundation of China ( NSFC), China Scholarship Council.
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 Ro botics - Robotics and Automation. According to news reporting out of Tianjin, Pe ople's Republic of China, by NewsRx editors, research stated, "Lower-limb exoske letons can improve human mobility and endurance, especially for people with leg impairments. To minimize metabolic penalty and maximize assistance capacity, the design of the mobile exoskeleton needs to compromise between the system weight and actuation power." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from Nankai University, "In the paper, we developed a lightweight high-torque mobile bilateral ankle exo skeleton with compliant end-effectors and a high-efficiency actuation. The syste m can provide 80 Nm assistive torques for both ankles with 3.4 kg entire exoskel eton weight by actuators' parallel connection and cooperative operation. Develop ed embedded hardware implemented a real-time torque controller comprising the da mping-injected feedback control, model-based feedforward compensation, and itera tive learning, achieving more than 10 Hz gain-limited closed-loop bandwidths and less than 2% torque tracking error. Preliminary physiological exp eriments demonstrated the exoskeleton's ability to reduce soleus muscle activiti es by over 50% at different walking speeds."
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 Ro botics - Androids. According to news reporting from Edinburgh, United Kingdom, b y NewsRx journalists, research stated, "Planning multicontact motions in a reced ing horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large obstacles. Traditional ly, the value function is approximated by computing trajectories in a prediction horizon (never executed) that foresees the future beyond the execution horizon. " Financial support for this research came from EU H2020 project Enhancing Healthc are with Assistive Robotic Mobile Manipulation HARMONY. The news correspondents obtained a quote from the research from the University o f Edinburgh, "However, given the nonconvex dynamics of multicontact motions, thi s approach is computationally expensive. To enable online receding horizon plann ing (RHP) of multicontact motions, we find efficient approximations of the value function. Specifically, we propose a trajectory-based and a learning-based appr oach. In the former, namely RHP with multiple levels of model fidelity, we appro ximate the value function by computing the prediction horizon with a convex rela xed model. In the latter, namely locally guided RHP, we learn an oracle to predi ct local objectives for locomotion tasks, and we use these local objectives to c onstruct local value functions for guiding a short-horizon RHP. We evaluate both approaches in simulation by planning centroidal trajectories of a humanoid robo t walking on moderate slopes, and on large slopes where the robot cannot maintai n static balance. Our results show that locally guided RHP achieves the best com putation efficiency (95%-98.6% cycles converge online )."
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 are pre sented in a new report. According to news reporting originating from Windhoek, N amibia, by NewsRx correspondents, research stated, "The digitization of the wate r sector has led to the emergence of Smart Water Metering Networks (SWMNs), whic h enable automated and continuous water consumption measurement. However, challe nges persist in efficiently managing and transmitting the vast amount of data ge nerated by these networks." Financial supporters for this research include SASSCAL, Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) under the Integrated Water Resource Management (IWRM) program.
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 artificial intelligence is now available. According to news originating from Fu Jen Catholic University by NewsRx correspondents, research stated, "It is the contention of this paper that ethics of work ought to be anthropological, and artificial intelligence (AI ) research and development, which is the focus of work today, should be anthropo logical, that is, human-centered." The news reporters obtained a quote from the research from Fu Jen Catholic Unive rsity: "This paper discusses the philosophical and theological implications of t he development of AI research on the intrinsic nature of work and the nature of the human person. AI research and the implications of its development and advanc ement, being a relatively new phenomenon, have not been comprehensively interrog ated in the social and ethical teachings of the Catholic Church."
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