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802 results on '"Zhu, Yimin"'

5. Chapter Investigating the Ability of Immersive Virtual Environments to Facilitate Occupant Thermal State Data Collection Involving Face Masks

Author

Rentala, Girish Srivatsa and Zhu, Yimin

Subjects
Immersive virtual environment, thermal sensation, thermal comfort, thermal acceptability, face masks., thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTV Virtualization
Abstract

This study examines the capability of an immersive virtual environment (IVE–based) experimental protocol to support occupant thermal state (sensation, acceptability, and comfort) data collection when participants wear face masks. Specifically, the goal is to see if there is a change in local thermal states due to face covering and would such a change affect overall thermal states. A between-subject experiment was conducted with fifty-four participants (27 masked; 27 unmasked) who were exposed to three-step temperatures (18.3ºC, 23.8ºC, and 29.4ºC) in a climate chamber under both cooling and heating sequences. In masked IVE experiments, participants donned a face mask and viewed the chamber's virtual model on a head-mounted display. In contrast, in unmasked IVE experiments, participants didn't use a face mask. Skin temperatures and overall/local thermal state responses were collected during the experiments. They were then statistically compared between masked IVE and unmasked IVE experiments. The results suggest that forehead temperature was significantly different under all step temperatures in the cooling sequence, with mean forehead temperature being larger in masked IVE than in unmasked IVE experiments. Furthermore, in masked IVE experiments, thermal sensation in the forehead, neck, and upper-back increased while the thermal acceptability in those same skin sites decreased, but this difference was not statistically significant. Also, in masked IVE experiments, the overall thermal sensation increased, whereas both the overall thermal acceptability and comfort decreased when compared with unmasked IVE experiments. Nonetheless, this difference was not statistically significant. To summarize, wearing a face mask didn't affect the participant's overall and local thermal states in IVEs, although few statistical differences were observed in skin temperatures

Published
2023
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6. Chapter Virtual Human-Building Interaction Experimentation Ontology (VHBIEO): A VHBIEO-Based Metadata-Driven Exploration

Author

Chokwitthaya, Chanachok, Zhu, Yimin, and Lu, Weizhuo

Subjects
Ontology, Metadata, Human-building interaction, Occupant behavior, Virtual reality, Building, thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTV Virtualization
Abstract

Virtual reality (VR) offers promise as a tool for building performance simulations, especially when considering human-building interactions in buildings or spaces still under design. However, the absence of standardized data protocols impedes the consistent sharing of VR-related experiments and findings. This makes advancing VR experimentation as a reliable method for studying human-building dynamics challenging. The authors introduced the Virtual Human-Building Interaction Experimentation Ontology (VHBIEO) to address the challenge. VHBIEO seeks to standardize experimentation details as a domain-specific ontology, enhancing their interoperability. It includes essential experimentation concepts and employs semantic web technologies to ensure machine readability. Moreover, it integrates an application view (APV) to tailor details to specific experiments. Using VHBIEO-based metadata, this paper presents a case study aiming to standardize experiments that validate thermal sensations in immersive virtual environments (IVE), encompassing experimental protocol, variables, design, and data gathering. By exploring the main characteristics of VHBIEO-based metadata, the authors discuss its potential to improve the reliability of human-building interaction research

Published
2023
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13. Cache-Oblivious Parallel Convex Hull in the Binary Forking Model

Author

Browne, Reilly, Chowdhury, Rezaul, Tsai, Shih-Yu, and Zhu, Yimin

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Computational Geometry
Abstract

We present two cache-oblivious sorting-based convex hull algorithms in the Binary Forking Model. The first is an algorithm for a presorted set of points which achieves $O(n)$ work, $O(\log n)$ span, and $O(n/B)$ serial cache complexity, where $B$ is the cache line size. These are all optimal worst-case bounds for cache-oblivious algorithms in the Binary Forking Model. The second adapts Cole and Ramachandran's cache-oblivious sorting algorithm, matching its properties including achieving $O(n \log n)$ work, $O(\log n \log \log n)$ span, and $O(n/B \log_M n)$ serial cache complexity. Here $M$ is the size of the private cache., Comment: 15 pages 3 figures

Published
2023

14. Fast American Option Pricing using Nonlinear Stencils

Author

Ahmad, Zafar, Browne, Reilly, Chowdhury, Rezaul, Das, Rathish, Huang, Yushen, and Zhu, Yimin

Subjects
Computer Science - Computational Engineering, Finance, and Science, Computer Science - Data Structures and Algorithms, Quantitative Finance - Computational Finance
Abstract

We study the binomial, trinomial, and Black-Scholes-Merton models of option pricing. We present fast parallel discrete-time finite-difference algorithms for American call option pricing under the binomial and trinomial models and American put option pricing under the Black-Scholes-Merton model. For $T$-step finite differences, each algorithm runs in $O(\left(T\log^2{T}\right)/p + T)$ time under a greedy scheduler on $p$ processing cores, which is a significant improvement over the $\Theta({T^2}/{p}) + \Omega(T\log{T})$ time taken by the corresponding state-of-the-art parallel algorithm. Even when run on a single core, the $O(T\log^2{T})$ time taken by our algorithms is asymptotically much smaller than the $\Theta(T^2)$ running time of the fastest known serial algorithms. Implementations of our algorithms significantly outperform the fastest implementations of existing algorithms in practice, e.g., when run for $T \approx 1000$ steps on a 48-core machine, our algorithm for the binomial model runs at least $15\times$ faster than the fastest existing parallel program for the same model with the speed-up factor gradually reaching beyond $500\times$ for $T \approx 0.5 \times 10^6$. It saves more than 80\% energy when $T \approx 4000$, and more than 99\% energy for $T > 60,000$. Our option pricing algorithms can be viewed as solving a class of nonlinear 1D stencil (i.e., finite-difference) computation problems efficiently using the Fast Fourier Transform (FFT). To our knowledge, ours are the first algorithms to handle such stencils in $o(T^2)$ time. These contributions are of independent interest as stencil computations have a wide range of applications beyond quantitative finance.

Published
2023

25. A Visual Analytics Framework for Distributed Data Analysis Systems

Author

Nayeem, Abdullah-Al-Raihan, Elshambakey, Mohammed, Dobbs, Todd, Lee, Huikyo, Crichton, Daniel, Zhu, Yimin, Chokwitthaya, Chanachok, Tolone, William J., and Cho, Isaac

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Human-Computer Interaction
Abstract

This paper proposes a visual analytics framework that addresses the complex user interactions required through a command-line interface to run analyses in distributed data analysis systems. The visual analytics framework facilitates the user to manage access to the distributed servers, incorporate data from the source, run data-driven analysis, monitor the progress, and explore the result using interactive visualizations. We provide a user interface embedded with generalized functionalities and access protocols and integrate it with a distributed analysis system. To demonstrate our proof of concept, we present two use cases from the earth science and Sustainable Human Building Ecosystem research domain.

Published
2021

44. Extreme events, energy security and equality through micro- and macro-levels: Concepts, challenges and methods

Author

Chen, Chien-fei, Dietz, Thomas, Fefferman, Nina H, Greig, Jamie, Cetin, Kristen, Robinson, Caitlin, Arpan, Laura, Schweiker, Marcel, Dong, Bing, Wu, Wenbo, Li, Yue, Zhou, Hongyu, Wu, Jianzhong, Wen, Jin, Fu, Joshua S, Hong, Tianzhen, Yan, Da, Nelson, Hannah, Zhu, Yimin, Li, Xueping, Xie, Le, and Fu, Rachel

Subjects
Public Health, Health Sciences, Human Society, Reduced Inequalities, Climate Action, Affordable and Clean Energy, Disasters, COVID-19, Energy justice, Energy insecurity, Energy inequality, Resilience, Human Geography, Policy and Administration
Abstract

Low-income households face long-standing challenges of energy insecurity and inequality (EII). During extreme events (e.g., disasters and pandemics) these challenges are especially severe for vulnerable populations reliant on energy for health, education, and well-being. However, many EII studies rarely incorporate the micro- and macro-perspectives of resilience and reliability of energy and internet infrastructure and social-psychological factors. To remedy this gap, we first address the impacts of extreme events on EII among vulnerable populations. Second, we evaluate the driving factors of EII and how they change during disasters. Third, we situate these inequalities within broader energy systems and pinpoint the importance of equitable infrastructure systems by examining infrastructure reliability and resilience and the role of renewable technologies. Then, we consider the factors influencing energy consumption, such as energy practices, socio-psychological factors, and internet access. Finally, we propose interdisciplinary research methods to study these issues during extreme events and provide recommendations.

Published
2022

49. Exploring thermal state in mixed immersive virtual environments

Author

Saeidi, Sanaz, Rentala, Girish, Rizzuto, Tracey, Hong, Tianzhen, Johannsen, Neil, and Zhu, Yimin

Subjects
Civil Engineering, Engineering, Built Environment and Design, Building, Mixed immersive virtual environment, Thermal experience, Thermal state, Physiological responses, Season, Architecture, Civil engineering
Abstract

Combining immersive virtual environment (IVE) with a controlled environment is a potential solution for analyzing human thermal experience during building design. Existing studies in this field have not adequately analyzed scenarios involving stabilized comfortable and uncomfortable temperature conditions using both thermal state votes and physiological responses, or the influence of the seasons. By combining IVE with a climate chamber, called mixed IVE (MIVE) in this study, experiments were conducted to test the hypothesis that participants' virtual experience did not significantly alter their thermal experience compared to their in-situ experience. Response variables were the control temperature distribution, the thermal state vote (at temperature steps 18.3 °C, 23.8 °C, and 29.4 °C), and physiological responses (heart rate and skin temperature). The results show that the first two response variables were not significantly different between the MIVE and in-situ settings (except for one case). Due to the heat development of the head mounted display device, the mean forehead skin temperature in the MIVE experiments was significantly higher than that in the in-situ experiments in most cases. However, such difference in skin temperature did not seem to affect general thermal state votes. In addition, significant skin temperature differences at some locations were also observed between the MIVE and in-situ settings.

Published
2021

50. Trigger Detection for the sPHENIX Experiment via Bipartite Graph Networks with Set Transformer

Author

Xuan, Tingting, Borca-Tasciuc, Giorgian, Zhu, Yimin, Sun, Yu, Dean, Cameron, Shi, Zhaozhong, Yu, Dantong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Amini, Massih-Reza, editor, Canu, Stéphane, editor, Fischer, Asja, editor, Guns, Tias, editor, Kralj Novak, Petra, editor, and Tsoumakas, Grigorios, editor

Published
2023
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