Zobrazeno 1 - 10
of 1 217
pro vyhledávání: '"ZHANG Xingyi"'
Publikováno v:
Shuitu Baochi Xuebao, Vol 38, Iss 2, Pp 47-56 (2024)
[Objective] Rainfall is the driving force of hydraulic erosion in black soil sloping farmland. It is of great significance to study soil erosion characteristics under natural rainfall conditions for soil erosion control. [Methods] Based on 43 erosive
Externí odkaz:
https://doaj.org/article/5ff6af75bc7648e290704194001ca74c
Autor:
Zhao Kang, Han Weina, Han Zihao, Zhang Xiaobin, Zhang Xingyi, Duan Xiaofeng, Wang Mengmeng, Yuan Yanping, Zuo Pei
Publikováno v:
Nanophotonics, Vol 11, Iss 13, Pp 3101-3113 (2022)
In this paper, we report an approach for tuning the surface morphology and phase of Ge2Sb2Te5 (GST) by using an ultrafast laser in a one-step process. Four surface micro/nanostructures with specific phase states were sequentially formed by changing t
Externí odkaz:
https://doaj.org/article/68b873d76aaf468484b5238230d6eb8e
Molecular optimization, which aims to discover improved molecules from a vast chemical search space, is a critical step in chemical development. Various artificial intelligence technologies have demonstrated high effectiveness and efficiency on molec
Externí odkaz:
http://arxiv.org/abs/2411.15183
Computerized Adaptive Testing (CAT) aims to select the most appropriate questions based on the examinee's ability and is widely used in online education. However, existing CAT systems often lack initial understanding of the examinee's ability, requir
Externí odkaz:
http://arxiv.org/abs/2411.12182
Autor:
Yang, Shangshang, Chen, Mingyang, Wang, Ziwen, Yu, Xiaoshan, Zhang, Panpan, Ma, Haiping, Zhang, Xingyi
Existing graph learning-based cognitive diagnosis (CD) methods have made relatively good results, but their student, exercise, and concept representations are learned and exchanged in an implicit unified graph, which makes the interaction-agnostic ex
Externí odkaz:
http://arxiv.org/abs/2410.17564
The rapid development of online recruitment platforms has created unprecedented opportunities for job seekers while concurrently posing the significant challenge of quickly and accurately pinpointing positions that align with their skills and prefere
Externí odkaz:
http://arxiv.org/abs/2410.07671
In high-energy particle physics, extracting information from complex detector signals is crucial for energy reconstruction. Recent advancements involve using deep learning to process calorimeter images from various sub-detectors in experiments like t
Externí odkaz:
http://arxiv.org/abs/2410.07250
Domain generalization (DG) task aims to learn a robust model from source domains that could handle the out-of-distribution (OOD) issue. In order to improve the generalization ability of the model in unseen domains, increasing the diversity of trainin
Externí odkaz:
http://arxiv.org/abs/2409.04699
Autor:
Yu, Xiaoshan, Qin, Chuan, Shen, Dazhong, Yang, Shangshang, Ma, Haiping, Zhu, Hengshu, Zhang, Xingyi
In the realm of education, both independent learning and group learning are esteemed as the most classic paradigms. The former allows learners to self-direct their studies, while the latter is typically characterized by teacher-directed scenarios. Re
Externí odkaz:
http://arxiv.org/abs/2406.12465
Node embedding learns low-dimensional vectors for nodes in the graph. Recent state-of-the-art embedding approaches take Personalized PageRank (PPR) as the proximity measure and factorize the PPR matrix or its adaptation to generate embeddings. Howeve
Externí odkaz:
http://arxiv.org/abs/2405.19649