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28 results on '"Rong Zhang"'

1. Exploring Reader-Text Transactions between Wordless Picture Books and Young Children

Author

Rong Zhang

Abstract

Wordless picture book reading is one of the common literacy practices for young children that happen at schools and homes. This dissertation of three studies explores the reader-text transactions between young children and wordless picture books in three ways: a content analysis of wordless books potentially featuring characters of color, a multimodal analysis exploring children's multimodal meaning making, and a mixed-method content analysis analyzing children's performing social imagination and narrative imagination and change over time. Through analyzing a set of 39 wordless picturebooks with protagonists that can be potentially identified as people of color, the first article analyzed the books' book themes, story events, and illustrations to explore how such books can function what Bishop suggested as windows, mirrors, and sliding glass doors and support young children to learn about themselves and others. The second article explores the potential of preschoolers' multimodal meaning making during reading wordless picturebooks. Multimodal meaning making can be valued as literacy practices that are closely related to reading comprehension, teaching instructions, and assessments. The third article focuses on kindergarteners' use of social imagination and narrative imagination during reading wordless picturebooks that reveal young children's active engagement and meaning making in reading. This series of articles hold implication for teachers and researchers to understand the potential of using wordless picture books for young children's access to diverse topics of readings, literacy practices, and assessment, specifically children's imaginative and multimodal ways of responding to reading of wordless picture books. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2023

2. Feedforward Neural Network for Time Series Anomaly Detection

Author

Rong, Zhang, Shandong, Dong, Xin, Nie, and Shiguang, Xiao

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

Time series anomaly detection is usually formulated as finding outlier data points relative to some usual data, which is also an important problem in industry and academia. To ensure systems working stably, internet companies, banks and other companies need to monitor time series, which is called KPI (Key Performance Indicators), such as CPU used, number of orders, number of online users and so on. However, millions of time series have several shapes (e.g. seasonal KPIs, KPIs of timed tasks and KPIs of CPU used), so that it is very difficult to use a simple statistical model to detect anomaly for all kinds of time series. Although some anomaly detectors have developed many years and some supervised models are also available in this field, we find many methods have their own disadvantages. In this paper, we present our system, which is based on deep feedforward neural network and detect anomaly points of time series. The main difference between our system and other systems based on supervised models is that we do not need feature engineering of time series to train deep feedforward neural network in our system, which is essentially an end-to-end system.

Published
2018

6. Long-Term Geospace Climate Monitoring

Author

Shun-Rong Zhang, Ingrid Cnossen, Jan Laštovička, Ana G. Elias, Xinan Yue, Christoph Jacobi, Jia Yue, Wenbin Wang, Liying Qian, and Larisa Goncharenko

Subjects
Geophysics
Abstract

Climate change is characterized by global surface warming associated with the increase of greenhouse gas population since the start of the industrial era. Growing evidence shows that the upper atmosphere is experiencing appreciable cooling over the last several decades. The seminal modeling study by Roble and Dickinson (1989) suggested potential effects of increased greenhouse gases on the ionosphere and thermosphere cooling which appear consistent with some observations. However, several outstanding issues remain regarding the role of CO2, other important contributors, and impacts of the cooling trend in the ionosphere and thermosphere: for example, (1) what is the regional variability of the trends? (2) the very strong ionospheric cooling observed by multiple incoherent scatter radars that does not fit with the prevailing theory based on the argument of anthropogenic greenhouse gas increases, why? (3) what is the effect of secular changes in Earth’s main magnetic field? Is it visible now in the ionospheric data and can it explain some of the regional variability in the observed ionospheric trends? (4) what is the impact of long-term cooling in the thermosphere on operational systems? (5) what are the appropriate strategic plans to ensure the long-term monitoring of the critical space climate?

Published
2023
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23. Reaction dynamics of H + O2 at 1.6 eV collision energy

Author

Bronikowski, Michael J, Rong, Zhang, Rakestraw, David J, and Zare, Richard N

Subjects
Atomic And Molecular Physics
Abstract

The hot hydrogen atom reaction, H + O2 yields OH + O, has been studied at a center of mass collision energy of 1.6 eV. H atoms were generated by 266 nm photolysis of HI in a mixture of HI and O2 at 293 K. The OH product was probed by laser induced fluorescence and the nascent OH vibrational, rotational, and fine structure distributions were determined. The OH(v=0/OH(v=1) vibrational branching ratio was measured to be 1.72 + or - 0.09. The data suggest that the H + O2 reaction at this collision energy proceeds via two competing mechanisms: reaction involving a long-lived complex and direct reaction.

Published
1989

28. Risk Reduction for Alzheimer's Disease (rrAD)

Author

Texas Health Resources, University of Kansas Medical Center, Washington University School of Medicine, Pennington Biomedical Research Center, Michigan State University, and Rong Zhang, Professor of Neurology

Published
2022

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