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Your search keyword '"Yu, Jiaqi"' showing total 621 results
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621 results on '"Yu, Jiaqi"'

1. Pixel-scale NIR-VIS Spectral Routers Based on 2D Mie-type Metagratings

Author

Shao, Yifan, Guo, Shuhan, Chen, Rui, Dang, Yongdi, Zhou, Yi, Wang, Yubo, Zhan, Junjie, Yu, Jiaqi, Ju, Bing-Feng, and Ma, Yungui

Subjects
Physics - Optics
Abstract

The out-of-band energy loss caused by in-built color filters significantly degrades the signal-to-noise ratio and the dynamic range of conventional image sensors, which has restricted the attempt to develop ultrahigh-density imaging devices by merely shrinking the pixel size. This issue will be more serious for security cameras which need to collect visible (VIS) light and near-infrared (NIR) photons as well. The existing solutions mostly explore complex photonic nanostructures, which are often too complicated for production. In this work, we demonstrate a pixel-scale spectral router utilizing two-dimensional (2D) Si3N4 Mie scattering metagratings that can spatially divide NIR (850 nm) and VIS (400-700 nm) light to different pixels at high efficiencies. It has a minimum feature size larger than 360 nm, highly promising for massive production. Compared with the traditional filter design, our router can gain about 42% and 30% signal enhancement for NIR and VIS band, respectively. We show that it also has good polarization insensitivity and incident angle tolerance. The NIR-VIS simultaneous imaging is inspected without any complex reconstruction algorithm. Mode analysis indicates that the multipolar scattering of our Mie-type metagratings provides the necessary degrees of freedom to spatially optimize the routing functions for broadband photons.

Published
2024
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2. A refined saturation theorem for polynomials and applications

Author

Ye, Xiangdong and Yu, Jiaqi

Subjects
Mathematics - Dynamical Systems
Abstract

For a dynamical system $(X,T)$, $d\in\mathbb{N}$ and distinct non-constant integral polynomials $p_1,\ldots, p_d$ vanishing at $0$, the notion of regionally proximal relation along $C=\{p_1,\ldots,p_d\}$ (denoted by $RP_C^{[d]}(X,T)$) is introduced. It turns out that for a minimal system, $RP_C^{[d]}(X,T)=\Delta$ implies that $X$ is an almost one-to-one extension of $X_k$ for some $k\in\mathbb{N}$ only depending on a set of finite polynomials associated with $C$ and has zero entropy, where $X_k$ is the maximal $k$-step pro-nilfactor of $X$. Particularly, when $C$ is a collection of linear polynomials, it is proved that $RP_C^{[d]}(X,T)=\Delta$ implies $(X,T)$ is a $d$-step pro-nilsystem, which answers negatively a conjecture in \cite{5p}. The results are obtained by proving a refined saturation theorem for polynomials.

Published
2024

5. Saturated theorem along cubes for a measure and applications

Author

Qiu, Jiahao and Yu, Jiaqi

Subjects
Mathematics - Dynamical Systems
Abstract

We show that for a minimal system $(X,T)$, the set of saturated points along cubes with respect to its maximal $\infty$-step pro-nilfactor $X_\infty$ has a full measure. As an application, it is shown that if a minimal system $(X,T)$ has no non-trivial $(k+1)$-tuples with arbitrarily long finite IP-independence sets, then it has only at most $k$ ergodic measures and is an almost $k'$ to one extension of $X_\infty$ for some $k'\leqslant k$. Particularly, for $k=1$ we prove that $(X,T)$ is uniquely ergodic (even regular with respect to $X_\infty$), which answers a conjecture stated in [3]., Comment: arXiv admin note: text overlap with arXiv:2202.08782; text overlap with arXiv:1105.3584, arXiv:1007.0189 by other authors

Published
2023

8. DREAM: Domain-free Reverse Engineering Attributes of Black-box Model

Author

Li, Rongqing, Yu, Jiaqi, Li, Changsheng, Luo, Wenhan, Yuan, Ye, and Wang, Guoren

Subjects
Computer Science - Machine Learning, Computer Science - Cryptography and Security
Abstract

Deep learning models are usually black boxes when deployed on machine learning platforms. Prior works have shown that the attributes ($e.g.$, the number of convolutional layers) of a target black-box neural network can be exposed through a sequence of queries. There is a crucial limitation: these works assume the dataset used for training the target model to be known beforehand and leverage this dataset for model attribute attack. However, it is difficult to access the training dataset of the target black-box model in reality. Therefore, whether the attributes of a target black-box model could be still revealed in this case is doubtful. In this paper, we investigate a new problem of Domain-agnostic Reverse Engineering the Attributes of a black-box target Model, called DREAM, without requiring the availability of the target model's training dataset, and put forward a general and principled framework by casting this problem as an out of distribution (OOD) generalization problem. In this way, we can learn a domain-agnostic model to inversely infer the attributes of a target black-box model with unknown training data. This makes our method one of the kinds that can gracefully apply to an arbitrary domain for model attribute reverse engineering with strong generalization ability. Extensive experimental studies are conducted and the results validate the superiority of our proposed method over the baselines.

Published
2023

11. Developing a Stealth Assessment System Using a Continuous Conjunctive Model

Author

Yu, Jiaqi, Ma, Wenchao, Moon, Jewoong, and Denham, Andre R.

Abstract

Integrating learning analytics in digital game-based learning has gained popularity in recent decades. The interactive nature of educational games creates an ideal environment for learning analytics data collection. However, past research has limited success in producing accessible and effective assessments using game learning analytics. In this study, a mathematics educational game called The Nomads was designed and developed to train learners' adaptive expertise in rational number arithmetic. Players' game log data were captured and fitted to a cognitive diagnostic model (CDM)--CCM (continuous conjunctive model). CCM lends itself well to the complex and dynamic nature of game learning analytics. Unlike traditional CDMs, CCM generates parameters at an attribute level and offers more parsimonious diagnoses using continuous variables. The findings suggest that learners' attribute mastery improved during the gameplay and that learners benefit from using the scaffolds for three of the attributes instructed by the game. This study presents the application of a powerful new tool for game learning analytics. Future studies can benefit from more generalized analytics models and more specified learning attributes and game tasks.

Published
2022

13. We Do What We Are: Representation of the Self-Concept and Identity-Based Choice.

Author

Chen, Stephanie Y, Urminsky, Oleg, and Yu, Jiaqi

Subjects
REASONING, IDENTITY (Psychology), SELF-perception, GROUP identity, CONSUMER preferences, CONSUMER behavior, CONSUMER behavior research, CAUSATION (Philosophy)
Abstract

The current research proposes a novel approach to identity-based choice that focuses on consumers' representations of the self-concept, as captured by the perceived cause–effect relationships among features of an individual consumer's self-concept. More specifically, the studies reported here test the proposal that the causal centrality of an identity—the number of other features of a consumer's self-concept that the consumer believes influenced or were influenced by the identity—underlies identity importance and is a determinant of identity-based consumer behaviors. Across seven studies, using both measured and manipulated causal centrality, the current research provides evidence for the role of causal centrality in identity-based choice. Among consumers who share an identity (belong to the same social category), those who believe that the identity is more causally central perceive the identity as more important and are more likely to engage in behaviors consistent with the norms of the social category. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Preparation and Crosslinking Capacity of Dialdoxylose

Author

JING Shutong, LI Zhengsheng’ao, LI Han, CAO Honghua, LI Xuecong, LIU Yonghao, YU Jiaqi, WEN Jingru, SUN Xun

Subjects
crosslinking, chitosan, gel, dialdoxylose, Food processing and manufacture, TP368-456
Abstract

Objective: To design and synthesize dialdoxylose, a glutaraldehyde analogue which is expected to have a low toxicity, and to characterize its performance in crosslinking chitosan in 1% acetic acid solution. Methods: Dialdoxylose was obtained by sodium periodate oxidation and deprotection of monoacetone glucose and used to form crosslinked chitosan gels. The gel strength, fluid properties, water activity and thermal stability of chitosan gels were analyzed by texture profile analysis (TPA), low field-nuclear magnetic resonance (NMR) spectroscopy and differential scanning calorimetry (DSC). Results: It was found that dialdoxylose exhibited two structures in water, (α,β) and (β,β), with a ratio of 44.4:65.6. The hardness, viscosity and water-holding capacity of the chitosan gel crosslinked with 0.002 g/mL dialdoxylose were highest. Conclusion: Dialdoxylose has an obvious crosslinking effect on chitosan, which is greatly affected by its concentration. The results of this study are of theoretical guiding significance for the development of new low-toxicity small-molecule crosslinking agents.

Published
2023
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