This research employed feature engineering techniques to preprocess an original stock dataset, followed by the introduction of a decision tree prediction model for forecasting the dataset. Experimental results demonst...
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AUTOSAR enhances the management of complex automotive electrical and electronic architectures by improving the reusability and interchangeability of software modules between OEMs and suppliers. However, existing AUTOS...
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Large sky Area Multi-Object fiber Spectroscopic Telescope(LAMOST) has completed the observation of nearly 20 million celestial objects,including a class of spectra labeled “Unknown.” Besides low signal-to-noise rati...
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Large sky Area Multi-Object fiber Spectroscopic Telescope(LAMOST) has completed the observation of nearly 20 million celestial objects,including a class of spectra labeled “Unknown.” Besides low signal-to-noise ratio,these spectra often show some anomalous features that do not work well with current *** this paper,a total of 637,889 “Unknown” spectra from LAMOST DR5 are selected,and an unsupervised-based analytical framework of “Unknown” spectra named SA-Frame(Spectra Analysis-Frame) is provided to explore their origins from different *** SA-Frame is composed of three parts:NAPC-Spec clustering,characterization and origin ***,NAPC-Spec(Nonparametric density clustering algorithm for spectra) characterizes different features in the “unknown” spectrum by adjusting the influence space and divergence distance to minimize the effects of noise and high dimensionality,resulting in 13 ***,characteristic extraction and representation of clustering results are carried out based on spectral lines and continuum,where these 13 types are characterized as regular spectra with low S/Ns,splicing problems,suspected galactic emission signals,contamination from city light and un-gregarious type ***,a preliminary analysis of their origins is made from the characteristics of the observational targets,contamination from the sky,and the working status of the *** results would be valuable for improving the overall data quality of large-scale spectral surveys.
With the trend of intelligence, automobile architecture has become more complex. It is necessary to predict and discover reliability-related issues to reduce the cost of correction in the later period. In AUTOSAR-base...
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Prior foveated rendering methods often suffer from a limitation where the shading load escalates with increasing display resolution, leading to decreased efficiency, particularly when dealing with retinal-level resolu...
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As the application of smart contracts in blockchain technology becomes increasingly widespread, their security issues have emerged as a focal point of both research and practice. Although symbolic execution technology...
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Building an effective sequential recommendation system is still a challenging task due to limited interactions among users and *** work has shown the effectiveness of incorporating textual or visual information into s...
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Building an effective sequential recommendation system is still a challenging task due to limited interactions among users and *** work has shown the effectiveness of incorporating textual or visual information into sequential recommendation to alleviate the data sparse *** data sparse problem now is attracting a lot of attention in both industry and academic ***,considering interactions among modalities on a sequential scenario is an interesting yet challenging task because of multimodal *** this paper,we introduce a novel recommendation approach of considering both textual and visual information,namely Multimodal Interactive Network(MIN).The advantage of MIN lies in designing a learning framework to leverage the interactions among modalities from both the item level and the sequence level for building an efficient ***,an item-wise interactive layer based on the encoder-decoder mechanism is utilized to model the item-level interactions among modalities to select the informative ***,a sequence interactive layer based on the attention strategy is designed to capture the sequence-level preference of each *** seamlessly incorporates interactions among modalities from both the item level and the sequence level for sequential *** is the first time that interactions in each modality have been explicitly discussed and utilized in sequential *** results on four real-world datasets show that our approach can significantly outperform all the baselines in sequential recommendation task.
Concrete is a vital component in modern construction, prized for its strength, durability, and versatility. Accurately determining the quantities of concrete components is crucial in civil engineering applications to ...
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Cylindrical Algebraic Decomposition (CAD) is one of the pillar algorithms of symbolic computation, and its worst-case complexity is double exponential to the number of variables. Researchers found that variable order ...
Cylindrical Algebraic Decomposition (CAD) is one of the pillar algorithms of symbolic computation, and its worst-case complexity is double exponential to the number of variables. Researchers found that variable order dramatically affects efficiency and proposed various heuristics. The existing learning-based methods are all supervised learning methods that cannot cope with diverse polynomial sets. This paper proposes two Reinforcement Learning (RL) approaches combined with Graph Neural Networks (GNN) for Suggesting Variable Order (SVO). One is GRL-SVO(UP), a branching heuristic integrated with CAD. The other is GRL-SVO(NUP), a fast heuristic providing a total order directly. We generate a random dataset and collect a real-world dataset from SMT-LIB. The experiments show that our approaches outperform state-of-the-art learning-based heuristics and are competitive with the best expert-based heuristics. Interestingly, our models show a strong generalization ability, working well on various datasets even if they are only trained on a 3-var random dataset. The source code and data are available at https://***/dongyuhang22/GRL-SVO.
Cyber-Physical Systems (CPS) are complex systems that integrate information control devices with physical resources, which can be automatically and formalized verified by model checking according to the expected requi...
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