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arXiv 2023年

作者： Wang, Zilong Shultz, Thomas R. Nobandegani, Ardavan S. Integrated Program in Neuroscience McGill University Canada Department of Psychology School of Computer Science McGill University Canada Department of Psychology Department of Electrical & Computer Engineering McGill University Canada

Recent empirical work has shown that human children are adept at learning and reasoning with probabilities. Here, we model a recent experiment investigating the development of school-age children's non-symbolic probability reasoning ability using the Neural Probability Learner and Sampler (NPLS) system. We demonstrate that NPLS can accurately simulate children's probability judgments at different ages, tasks and difficulty levels to discriminate two probabilistic choices through accurate probability learning and sampling. An extension of NPLS using a skewed heuristic distribution can also model children's tendency to wrongly select the outcome with more favorable items but less likely to draw the favorable ones when the probabilistic choices are similar. We discuss the roles of two model parameters that can be adjusted to simulate the probability matching versus probability maximization phenomena in children, and why frequency biases children's probabilistic judgments. Copyright © 2023, The Authors. All rights reserved.

关键词： Probability distributions

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Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse

arXiv

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arXiv 2025年

作者： Liu, Guangyuan Du, Hongyang Wang, Jiacheng Niyato, Dusit Kim, Dong In College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user experience. However, generating these images, especially through Generative Diffusion Models (GDMs), in mobile edge computing environments presents significant challenges due to the limited computing resources of edge devices and the dynamic nature of wireless networks. This paper proposes a novel framework that integrates contract-inspired contest theory, Deep Reinforcement Learning (DRL), and GDMs to optimize image generation in these resource-constrained environments. The framework addresses the critical challenges of resource allocation and semantic data transmission quality by incentivizing edge devices to efficiently transmit high-quality semantic data, which is essential for creating realistic and immersive images. The use of contest and contract theory ensures that edge devices are motivated to allocate resources effectively, while DRL dynamically adjusts to network conditions, optimizing the overall image generation process. Experimental results demonstrate that the proposed approach not only improves the quality of generated images but also achieves superior convergence speed and stability compared to traditional methods. This makes the framework particularly effective for optimizing complex resource allocation tasks in mobile edge Metaverse applications, offering enhanced performance and efficiency in creating immersive virtual environments. © 2025, CC BY.

关键词： Mobile edge computing

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Dynamic Mapping of Temperature Using Phase-Change materials

Dynamic Mapping of Temperature Using Phase-Change Materials

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CLEO: science and Innovations, S and I 2022

作者： Nobile, Nicholas Erickson, John Ríos, Carlos Zhang, Yifei Hu, Juejun Xiong, Feng Youngblood, Nathan Univ. of Pittsburgh Dept. of Electrical and Computer Engineering Benedum Hall 3700 O'Hara St. PittsburghPA15261 United States Department of Materials Science & Engineering University of Maryland College ParkMD United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD United States Department of Materials Science & Engineering MIT CambridgeMA United States

GST pixels are fabricated on metallic heaters where the optical reflection is observed and used to extract dynamic temperature changes. Our results provide a new way to measure the thermal response of microsystems in ... 详细信息

ISBN: (纸本)9781557528209

关键词： Phase change materials

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Surasachai Doungtap Jirayu Petchhan Varinya Phanichraksaphong Jenq-Haur Wang International Graduate Program of Electrical Engineering and Computer Science Dept. of Electrical Engineering National Taiwan University of Science & Technology Taiwan R. O. C. Department of Computer Science and Information Engineering National Taipei University of Technology Taiwan R. O. C.

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle.

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Atomic-scale investigation of γ-Ga2O3 deposited on MgAl2O4 and its relationship with β-Ga2O3

arXiv

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arXiv 2023年

作者： Tang, Jingyu Jiang, Kunyao Xu, Chengchao Cabral, Matthew J. Xiao, Kelly Porter, Lisa M. Davis, Robert F. Department of Materials Science and Engineering Carnegie Mellon University PittsburghPA15213 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States

Nominally phase-pure γ-Ga2O3 was deposited on (100) MgAl2O4 within a narrow temperature window centered at ~470 ℃ using metal-organic chemical vapor deposition (MOCVD). The film deposited at 440 ℃ exhibited either poor crystallization or an amorphous structure;the film grown at 500 ℃ contained both β-Ga2O3 and γ-Ga2O3. A nominally phase-pure β-Ga2O3 film was obtained at 530 ℃. Atomic-resolution scanning transmission electron microscopy (STEM) investigations of the γ-Ga2O3 film grown at 470 ℃ revealed a high density of antiphase boundaries. A planar defect model developed for γ-Al2O3 was extended to explain the stacking sequences of the Ga sublattice observed in the STEM images of γ-Ga2O3. The presence of the 180° rotational domains and 90° rotational domains of β-Ga2O3 inclusions within the γ-Ga2O3 matrix is discussed within the context of a comprehensive investigation of the epitaxial relationship between those two phases in the as-grown film at 470 ℃ and the same film annealed at 600 ℃. The results led to the hypotheses that (i) incorporation of certain dopants including Si, Ge, Sn, Mg, Al, and Sc, into β-Ga2O3, locally stabilizes the "γ-phase" and (ii) the site preference(s) for these dopants promotes the formation of the "γ-phase" and/or γ-Ga2O3 solid solutions. However, in the absence of such dopants, pure γ-Ga2O3 remains the least stable Ga2O3 polymorph, as indicated by its very narrow growth window, lower growth temperatures relative to other Ga2O3 polymorphs, and the largest calculated difference in Helmholtz free energy per formula unit between γ-Ga2O3 and β-Ga2O3 than all other polymorphs. Copyright © 2023, The Authors. All rights reserved.

关键词： Gallium compounds

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Uncovering In-Plane Domain Structures in Two-Dimensional Ferroelectric SnSe Using Machine-Learning Assisted 4D-STEM

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Microscopy and Microanalysis 2022年第S1期28卷 374-375页

作者： Shi, Chuqiao Mao, Nannan Kong, Jing Han, Yimo Department of Materials Science and NanoEngineering Rice University Houston TX Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA

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Experimental Entanglement-Enhanced Covert Sensing

Experimental Entanglement-Enhanced Covert Sensing

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CLEO: QELS_Fundamental science, QELS 2022

作者： Hao, Shuhong Shi, Haowei Gagatsos, Christos N. Mishra, Mayank Bash, Boulat Djordjevic, Ivan Guha, Saikat Zhuang, Quntao Zhang, Zheshen Department of Materials Science and Engineering University of Arizona TucsonAZ85721 United States James C. Wyant College of Optical Sciences University of Arizona TucsonAZ85721 United States Department of Electrical and Computer Engineering University of Arizona TucsonAZ85721 United States

We report the theory and experiment for entanglement-enhanced covert sensing, a paradigm that simultaneously offers high measurement precision and data integrity by concealing the execution of the protocol. © Opt...

ISBN: (纸本)9781557528209

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Recent Advancements in Nanophotonics for Optofluidics

arXiv

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arXiv 2024年

作者： Yang, Sen Hong, Chuchuan Zhu, Guodong Anyika, Theodore Hong, Ikjun Ndukaife, Justus C. Institute of Physics Chinese Academy of Sciences Beijing National Laboratory for Condensed Matter Physics Beijing100190 China Department of Chemistry Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37240 United States

Optofluidics is dedicated to achieving integrated control of particle and fluid motion, particularly on the micrometer scale, by utilizing light to direct fluid flow and particle motion. The field has seen significant growth recently, driven by the concerted efforts of researchers across various scientific disciplines, notably for its successful applications in biomedical science. In this review, we explore a range of optofluidic architectures developed over the past decade, with a primary focus on mechanisms for precise control of micro and nanoscale biological objects and their applications in sensing. Regarding nanoparticle manipulation, we delve into mechanisms based on optical nanotweezers using nanolocalized light fields and light-based hybrid effects with dramatically improved performance and capabilities. In the context of sensing, we emphasize those works that used optofluidics to aggregate molecules or particles to promote sensing and detection. Additionally, we highlight emerging research directions, encompassing both fundamental principles and practical applications in the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Flow of fluids

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CPS, Sustainability and Efficiency in an Aquaponic Greenhouse

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2022年 20卷 210-215页

作者： Galvão, J. Santos, P. Aires, L. Neves, F. Department of Electrical Engineering/ESTG Polytechnic of Leiria Leiria2411-901 Portugal LSRE-LCM-Laboratory of Separation and Reaction Engineering Laboratory of Catalysis and Materials Escola Superior de Tecnologia e Gestão Instituto Politécnico de Leiria Leiria2411-901 Portugal ALiCE-Associate Laboratory in Chemical Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal R&D Unit Institute for Systems Engineering and Computers/INESC Coimbra Portugal Department of Computer Science Polytechnic of Leiria Leiria2411-901 Portugal

Nowadays the humanity needs to produce food in greater quantity and quality, in order to satisfy citizens and markets, supported by advanced technologies such as cyber-physical system (CPS) or intelligent systems where software and electronic devices and receivers of physical variables are mechanisms that control the management of multiple actions inherent to plant growth. Electronic devices and receivers of physical variables are mechanisms that involve a network of IoT components and control multiple actions inherent to plant growth in agricultural greenhouses, which in short, are intensive food production systems. In this context, this paper presents a case study that uses a monitoring and management system that considers environmental parameters measured inside a greenhouse, allowing the manager to assess the working status of an aquaponic systems, and detect critical conditions that require quick decisions in real time. It is intended to develop technology that can be used in greenhouses, close to consumer centres or cities, to mitigate the impact of transport, lowering CO2 emissions resulting from the distribution channels between the producers and consumers. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Energy efficiency

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Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Deep Learning Technologies

Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Dee...

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Telecommunications Conference (ITC-Egypt), International

作者： Mohamed M. El-Sheikh Aya Bayoumy Nada M. Ahmed Amany Mohamed Eldeeb Fatma I. Rabea Amira A. Nawar Mohamed G. Khattap Hend Galal Eldeen Mohamed Ali Hassan Mariam Mostafa Nayra Ibrahim Reem Ramadan Yomna Refaat Mennatallah Khaled Ali Maher Mohamed Abd Elaziz Ahmed Gamal Abdellatif Ibrahim Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez Egypt Biomedical Informatics Faculty of Computer Science and Engineering Galala University Suez Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez Egypt Department of Electronics and Electrical Communications Engineering Air Defense College Alexandria Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique utilizes EfficientNet, a deep learning model, designed to extract features from MRI images thereby enhancing the detection of acute ischemic infarctions. The performance of EfficientNet is compared against two other models, CNN and MobileNet, demonstrating its superior efficacy through metrics such as accuracy, precision, recall, and F1-score, which stand at 92.31%, 92.28%, 92.33%, and 92.30%, respectively.

关键词： Deep learning Accuracy Magnetic resonance imaging Soft sensors Medical services Feature extraction Regulation

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