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789 results on '"Zhou, Ting"'

1. Bridging Design and Development with Automated Declarative UI Code Generation

Author

Zhou, Ting, Zhao, Yanjie, Hou, Xinyi, Sun, Xiaoyu, Chen, Kai, and Wang, Haoyu

Subjects
Computer Science - Software Engineering
Abstract

Declarative UI frameworks have gained widespread adoption in mobile app development, offering benefits such as improved code readability and easier maintenance. Despite these advantages, the process of translating UI designs into functional code remains challenging and time-consuming. Recent advancements in multimodal large language models (MLLMs) have shown promise in directly generating mobile app code from user interface (UI) designs. However, the direct application of MLLMs to this task is limited by challenges in accurately recognizing UI components and comprehensively capturing interaction logic. To address these challenges, we propose DeclarUI, an automated approach that synergizes computer vision (CV), MLLMs, and iterative compiler-driven optimization to generate and refine declarative UI code from designs. DeclarUI enhances visual fidelity, functional completeness, and code quality through precise component segmentation, Page Transition Graphs (PTGs) for modeling complex inter-page relationships, and iterative optimization. In our evaluation, DeclarUI outperforms baselines on React Native, a widely adopted declarative UI framework, achieving a 96.8% PTG coverage rate and a 98% compilation success rate. Notably, DeclarUI demonstrates significant improvements over state-of-the-art MLLMs, with a 123% increase in PTG coverage rate, up to 55% enhancement in visual similarity scores, and a 29% boost in compilation success rate. We further demonstrate DeclarUI's generalizability through successful applications to Flutter and ArkUI frameworks.

Published
2024

2. DTR: A Unified Deep Tensor Representation Framework for Multimedia Data Recovery

Author

Zhou, Ting-Wei, Zhao, Xi-Le, Wang, Jian-Li, Luo, Yi-Si, Wang, Min, Bai, Xiao-Xuan, and Yan, Hong

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recently, the transform-based tensor representation has attracted increasing attention in multimedia data (e.g., images and videos) recovery problems, which consists of two indispensable components, i.e., transform and characterization. Previously, the development of transform-based tensor representation mainly focuses on the transform aspect. Although several attempts consider using shallow matrix factorization (e.g., singular value decomposition and negative matrix factorization) to characterize the frontal slices of transformed tensor (termed as latent tensor), the faithful characterization aspect is underexplored. To address this issue, we propose a unified Deep Tensor Representation (termed as DTR) framework by synergistically combining the deep latent generative module and the deep transform module. Especially, the deep latent generative module can faithfully generate the latent tensor as compared with shallow matrix factorization. The new DTR framework not only allows us to better understand the classic shallow representations, but also leads us to explore new representation. To examine the representation ability of the proposed DTR, we consider the representative multi-dimensional data recovery task and suggest an unsupervised DTR-based multi-dimensional data recovery model. Extensive experiments demonstrate that DTR achieves superior performance compared to state-of-the-art methods in both quantitative and qualitative aspects, especially for fine details recovery.

Published
2024

3. Plasma membrane abundance dictates phagocytic capacity and functional cross-talk in myeloid cells

Author

Winer, Benjamin Y, Settle, Alexander H, Yakimov, Alexandrina M, Jeronimo, Carlos, Lazarov, Tomi, Tipping, Murray, Saoi, Michelle, Sawh, Anjelique, Sepp, Anna-Liisa L, Galiano, Michael, Perry, Justin SA, Wong, Yung Yu, Geissmann, Frederic, Cross, Justin, Zhou, Ting, Kam, Lance C, Pasolli, H Amalia, Hohl, Tobias, Cyster, Jason G, Weiner, Orion D, and Huse, Morgan

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Immunology, Cancer, 2.1 Biological and endogenous factors, Animals, Phagocytosis, Cell Membrane, Mice, Mice, Knockout, Myeloid Cells, Mice, Inbred C57BL, Neutrophils, Macrophages, Clinical sciences
Abstract

Professional phagocytes like neutrophils and macrophages tightly control what they consume, how much they consume, and when they move after cargo uptake. We show that plasma membrane abundance is a key arbiter of these cellular behaviors. Neutrophils and macrophages lacking the G protein subunit Gβ4 exhibited profound plasma membrane expansion, accompanied by marked reduction in plasma membrane tension. These biophysical changes promoted the phagocytosis of bacteria, fungus, apoptotic corpses, and cancer cells. We also found that Gβ4-deficient neutrophils are defective in the normal inhibition of migration following cargo uptake. Sphingolipid synthesis played a central role in these phenotypes by driving plasma membrane accumulation in cells lacking Gβ4. In Gβ4 knockout mice, neutrophils not only exhibited enhanced phagocytosis of inhaled fungal conidia in the lung but also increased trafficking of engulfed pathogens to other organs. Together, these results reveal an unexpected, biophysical control mechanism central to myeloid functional decision-making.

Published
2024

4. Oxygen vacancies modulated VO2 for neurons and Spiking Neural Network construction

Author

Li, Liang, Zhou, Ting, Liu, Tong, Liu, Zhiwei, Li, Yaping, Wu, Shuo, Zhao, Shanguang, Zhu, Jinglin, Liu, Meiling, Lin, Zhihan, Sun, Bowen, Li, Jianjun, Sun, Fangwen, and Zou, Chongwen

Subjects
Computer Science - Neural and Evolutionary Computing, Condensed Matter - Strongly Correlated Electrons
Abstract

Artificial neuronal devices are the basic building blocks for neuromorphic computing systems, which have been motivated by realistic brain emulation. Aiming for these applications, various device concepts have been proposed to mimic the neuronal dynamics and functions. While till now, the artificial neuron devices with high efficiency, high stability and low power consumption are still far from practical application. Due to the special insulator-metal phase transition, Vanadium Dioxide (VO2) has been considered as an idea candidate for neuronal device fabrication. However, its intrinsic insulating state requires the VO2 neuronal device to be driven under large bias voltage, resulting in high power consumption and low frequency. Thus in the current study, we have addressed this challenge by preparing oxygen vacancies modulated VO2 film(VO2-x) and fabricating the VO2-x neuronal devices for Spiking Neural Networks (SNNs) construction. Results indicate the neuron devices can be operated under lower voltage with improved processing speed. The proposed VO2-x based back-propagation SNNs (BP-SNNs) system, trained with the MNIST dataset, demonstrates excellent accuracy in image recognition. Our study not only demonstrates the VO2-x based neurons and SNN system for practical application, but also offers an effective way to optimize the future neuromorphic computing systems by defect engineering strategy., Comment: 18 pages,4 figures

Published
2024

21. Compartmentalized ocular lymphatic system mediates eye–brain immunity

Author

Yin, Xiangyun, Zhang, Sophia, Lee, Ju Hyun, Dong, Huiping, Mourgkos, George, Terwilliger, Gordon, Kraus, Aurora, Geraldo, Luiz Henrique, Poulet, Mathilde, Fischer, Suzanne, Zhou, Ting, Mohammed, Farrah Shalima, Zhou, Jiangbing, Wang, Yongfu, Malloy, Seth, Rohner, Nicolas, Sharma, Lokesh, Salinas, Irene, Eichmann, Anne, Thomas, Jean-Leon, Saltzman, W. Mark, Huttner, Anita, Zeiss, Caroline, Ring, Aaron, Iwasaki, Akiko, and Song, Eric

Published
2024
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24. 'Research progress in flame retardancy and smoke suppression of silicone rubber foam'

Author

KANG Fu-ru, TU Jia-yao, ZHAO Heng, ZHOU Ting-bin

Subjects
silicone rubber foam， metal hydro-xide flame retardant，phosphorus-based flame retardant， microcapsule， ceramicization， review，, Organic chemistry, QD241-441, Chemical engineering, TP155-156, Chemicals: Manufacture, use, etc., TP200-248
Abstract

The flame retardancy and smoke suppression performance of silicone rubber foam (SiFs) greatly affected its promotion and application in the field of high performance materials. Improving the flame retardancy and smoke suppression performance of SiFs had became a hot and difficult topic in recent years. The current research status of flame retardancy and smoke suppression of SiFs in flame retardant systems such as metal hydroxide flame retardants, boron- based flame retardants, phosphorus-and nitrogen-based flame retardants, platinum catalysts, microcapsule flame retardants, and ceramic-based flame retardants had been summarized with 67 references. Besides, the corresponding flame retardancy mechanisms had been expounded. Finally, the future research direction of flame retardancy and smoke suppression of SiFs was presented.

Published
2024
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28. Preconditioned USSOR Iterative Method for H-matrix Linear Systems

Author

Zhou, Ting, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Zhang, Yonghong, editor, Qi, Lianyong, editor, Liu, Qi, editor, Yin, Guangqiang, editor, and Liu, Xiaodong, editor

Published
2024
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