The current urban intelligent transportation is in a rapid development stage, and coherence control of vehicle formations has important implications in urban intelligent transportation research. This article focuses o...
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Multiple patterning lithography (MPL) has been introduced in the integrated circuits manufacturing industry to enhance feature density as the technology node advances. A crucial step of MPL is assigning layout feature...
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The innovative city network integrates numerous computational and physical components to develop real-time systems. These systems can capture sensor data and distribute it to end stations. Most solutions have been pre...
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The recent transport measurements of La_(3)Ni_(2)O_(7)uncovered a“right-triangle”shape of the superconducting dome in the pressure-temperature(P-T)phase *** by this,we perform theoretical first-principles studies of...
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The recent transport measurements of La_(3)Ni_(2)O_(7)uncovered a“right-triangle”shape of the superconducting dome in the pressure-temperature(P-T)phase *** by this,we perform theoretical first-principles studies of La_(3)Ni_(2)O_(7)with the pressure ranging from 0 to 100 ***,we reveal a pressure dependence of the Ni-d_(z^(2))electron density at the Fermi energy(n_(z)^(E_(F)))that highly coincides with such *** this basis,we further explore the electronic structure under uniaxial *** tracking the stress response of n_(z)^(E_(F)),we propose that superconductivity can be achieved by applying only ~2GPa of compression along the c *** idea is further exemplified from the perspectives of lattice distortion,band structure,Fermi surface and superconducting phase *** also discuss the possible charge modulation under the stress and provide an insight into the relation between nz E Fand the superconducting T_(c)in La_(3)Ni_(2)O_(7)*** study provides new routes to the search of high-T_(c)superconductors in future experiments.
Enhanced regular expressions (EREs), which extend standard regular expressions with shuffle and counting operators, provide exponentially more succinct descriptions of regular languages. The membership problem, determ...
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In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance po...
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There is a growing interest in sustainable ecosystem development, which includes methods such as scientific modeling, environmental assessment, and development forecasting and planning. However, due to insufficient su...
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Named Entity Recognition is the task to locate and classify the entities in the text. However, Unlabeled Entity Problem in NER datasets seriously hinders the improvement of NER performance. This paper proposes SCL-RAI...
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Reliable effort estimation is of paramount importance to software planning and management, especially in industry that requires effective and on-time delivery. Although various estimation approaches have been proposed...
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ISBN:
(纸本)9798400702174
Reliable effort estimation is of paramount importance to software planning and management, especially in industry that requires effective and on-time delivery. Although various estimation approaches have been proposed (e.g., planning poker and analogy), they may be manual and/or subjective, which are difficult to apply to other projects. In recent years, deep learning approaches for effort estimation that rely on learning expert features or semantic features respectively have been extensively studied and have been found to be promising. Semantic features and expert features describe software tasks from different perspectives, however, in the literature, the best combination of these two features has not been explored to enhance effort estimation. Additionally, there are a few studies that discuss which expert features are useful for estimating effort in the industry. To this end, we investigate the potential 13 expert features that can be used to estimate effort by interviewing 26 enterprise employees. Based on that, we propose a novel model, called Fine-SE, that leverages semantic features and expert features for effort estimation. To validate our model, a series of evaluations are conducted on more than 30,000 software tasks from 17 industrial projects of a global ICT enterprise and four open-source software (OSS) projects. The evaluation results indicate that Fine-SE provides higher performance than the baselines on evaluation measures (i.e., mean absolute error, mean magnitude of relative error, and performance indicator), particularly in industrial projects with large amounts of software tasks, which implies a significant improvement in effort estimation. In comparison with expert estimation, Fine-SE improves the performance of evaluation measures by 32.0%-45.2% in within-project estimation. In comparison with the state-of-the-art models, Deep-SE and GPT2SP, it also achieves an improvement of 8.9%-91.4% in industrial projects. The experimental results reveal th
Concerns over climate change and sustainable agriculture have made nation-wide high resolution environment monitoring and modelling desirable. Recent developments in technology have made it affordable. An environment ...
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ISBN:
(纸本)9783031521850;9783031521867
Concerns over climate change and sustainable agriculture have made nation-wide high resolution environment monitoring and modelling desirable. Recent developments in technology have made it affordable. An environment modelling network is a supercomputer, but not of a familiar kind. Conventional supercomputing approaches are appropriate for the modelling aspect, but not the monitoring aspect. While sensor networks are familiar in the Internet of Things (IoT), geographically remote sensors without access to mains power have harsher resource constraints than, say, internet-ready light bulbs. A "two-realm" approach to system software is needed.
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