Abstract: Advances in hierarchical modeling have improved estimation of ecological parameters from count data, especially those quantifying population abundance, distribution, and dynamics by explicitly accounting for observation processes, particularly incomplete detection. Even hierarchical models that account for incomplete detection, however, c...
Published in Machine Learning: Science and Technology
The high computational demand of the Density Functional Theory (DFT) based method for screening new materials properties remains a strong limitation to the development of clean and renewable energy technologies essential to transition to a carbon-neutral environment in the coming decades. Machine Learning comes into play with its innate capacity to...
Published in Open Computer Science
Multimedia teaching is a comprehensive teaching platform that integrates text, images, video, sound, animation, hyperlinks and other teaching methods, and plays an important role in teaching. This article mainly discussed the classification of courseware materials on the basis of data analysis and introduced the selection method of multimedia cours...
The progress of precision medicine research hinges on the gathering and analysis of extensive and diverse clinical datasets. With the continued expansion of modalities, scales, and sources of clinical datasets, it becomes imperative to devise methods for aggregating information from these varied sources to achieve a comprehensive understanding of d...
Published in Frontiers in High Performance Computing
Neutron scattering science is leading to significant advances in our understanding of materials and will be key to solving many of the challenges that society is facing today. Improvements in scientific instruments are actually making it more difficult to analyze and interpret the results of experiments due to the vast increases in the volume and c...
Published in Frontiers in Astronomy and Space Sciences
Interplanetary coronal mass ejections (ICMEs) and the driven geomagnetic storms have a profound influence on the ionosphere, potentially leading to a degradation in positioning performance. In this study, we made a comprehensive analysis of the entire process of the impact of a typical ICME and its driven geomagnetic storm on the low-latitude ionos...
Published in Plasma Physics and Controlled Fusion
Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-chec...
Published in Inverse Problems
The growing time-series data make it possible to glimpse the hidden dynamics in various fields. However, developing a computational toolbox with high interpretability to unveil the interaction dynamics from data remains a crucial challenge. Here, we propose a new computational approach called automated dynamical model inference based on expression ...
Published in Physica Scripta
The accelerated progress in quantum computing has enabled a new form of machine intelligence that runs on quantum hardware, which holds great promise for more powerful computational models in various learning tasks. An emergent application of Quantum Machine Intelligence (QMI) is Quantum Natural Language Processing (QNLP). This paper proposes a mul...
Published in Frontiers in Energy Research
With the increasing penetration level of electric vehicles (EVs) in distribution networks, the limited capacity of distribution networks has become a bottleneck for EV integration. Considering the difficulties of capacity expansion in distribution networks, especially in large cities, integrating EVs with photovoltaic (PV) generation systems and ba...
