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Phong shading approximation of computer-generated holography based on fully analytical triangle meshes

Chinese Optics Letters 2025年第4期 6-13页

作者：邹茜符庆杨刘燕杨敏王品张亚萍潘定中 School of Physics and Electronic Information Yunnan Normal University Smart Computational Imaging Laboratory SCILab School of Electronic and Optical Engineering Nanjing University of Science and Technology Yunnan Provincial Key Laboratory of Modern Information Optics LMIO Kunming University of Science and Technology Bradley Department of Electrical and Computer Engineering Virginia Tech

We propose a Phong shading approximation,which gives the amplitude of each point inside the triangle through linear interpolation within the framework of self-similarity segmentation and affine transformation in polygon-based computer-generated *** is important as it reflects the geometric properties of the *** accurately represent the geometric properties of objects in three-dimensional space,the method involves calculating the amplitude distribution on each triangle and maintaining a complete analytical framework,with the edges of the reconstructed polygons nearly *** simulations and optical reconstructions demonstrate that the proposed method successfully addresses the issue of edge discontinuity on polygonal surfaces.

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Explainable AI Framework for Alzheimer’s Diagnosis Using Convolutional Neural Networks

Explainable AI Framework for Alzheimer’s Diagnosis Using Co...

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International Conference on advanced Technologies for Signal and Image Processing (ATSIP)

作者： Dhekra Mansouri Amira Echtioui Rafik Khemakhem Ahmed Ben Hamida Advanced Technologies for Medicine and Signals Laboratory ‘ATMS’ National Engineering School of Sfax (ENIS) Sfax University Sfax Tunisia Higher Institute of Management of Gabès Gabès University Gabès Tunisia Department IS College of Computer Science King Khaled University ‘KKU’ Abha Kingdom of Saudi Arabia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Alzheimer’s disease (AD) stands as a form of dementia characterized by the gradual degeneration of brain cells, resulting in compromised memory, cognitive functions, and the loss of fundamental skills, ultimately leading to fatality. While a definitive cure for AD remains elusive, early detection plays a pivotal role in managing its progression and enhancing the quality of life for patients. This study delves into the realm of Alzheimer’s disease identification through the application of various Neural Network models employing classification techniques. Leveraging a contemporary hybrid dataset, the investigation yielded four distinct classifications. Moreover, the study delved into elucidating the specific brain regions contributing to each classification using the Grad-CAM (Gradient-weighted Class Activation Mappings) based XAI (eXplainable Artificial Intelligence) framework applied to patients’ MRI images. A comprehensive assessment was conducted on pre-trained deep neural networks, particularly focusing on Convolutional Neural Network (CNN) models trained exclusively on authentic MRIs and a combination of authentic and synthetic MRIs. The efficacy of deep learning in disease detection was exemplified, with the CNN model trained on both real and synthetic MRIs outperforming its counterpart trained solely on real MRIs. The former achieved an impressive accuracy of 97.50%, a Balanced Accuracy Score (BA) of $98.58 \%$, and a Matthew’s Correlation Coefficient (MCC) of 95.95%. In contrast, the model trained exclusively on real MRIs exhibited an accuracy of $88.98 \%$, a BA of 94.01%, and an MCC of $83.67 \%$.

关键词： Correlation coefficient Accuracy Explainable AI Magnetic resonance imaging Brain modeling Data models Convolutional neural networks

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Detection of biofuel adulterants using an optical fiber-based refractive index sensor

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Optik 2023年第1期291卷

作者： Prasanth, A. Harini, V.K. Manivannan, P. Velumani, M. Narasimman, S. Meher, S.R. Alex, Z.C. Department of Sensor and Biomedical Technology School of Electronics Engineering Vellore Institute of Technology Vellore India Department of Physics School of Advanced sciences Vellore Institute of Technology Vellore India Department of CSE – Cyber Security & IoT Sri Ramachandra Faculty of Engineering and Technology Sri Ramachandra Institute of Higher Education and Research Chennai600116 India Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

This study presents a Lossy Mode Resonance (LMR) based on fiber optic sensor for detecting biofuel adulteration. Tin Oxide (SnO2), coated over the clad removed portion of the optical fiber using the Radio Frequency Magnetron sputtering technique, was utilized as the sensing layer. The fabricated sensor probe was analyzed with various concentrations of the analytes that include methanol in ethanol, ethanol in methanol, methanol in water, ethanol in water, water in methanol, and water in ethanol. The absorption spectra of the fabricated sensor probe revealed two LMR peaks namely, LMR1 and LMR2 that exhibited wavelength shift under varying concentration of the analytes. The maximum sensor responses for the above combinations of the analytes were 4.95%, 3.30%, 3.00%, 3.56%, 2.91% and 3.57%, respectively. The sensitivities of the sensor probe towards these analytes were 0.46 nm/vol%, 0.17 nm/vol%, 0.49 nm/vol%, 0.58 nm/vol%, 0.08 nm/vol%, and 0.4 nm/vol%, respectively. The real time sample were examined using metal oxides coated sensors. The result exhibits SnO2 coated probe is sensitive than other probes. © 2023 Elsevier GmbH

关键词： Biofuels

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Epitaxial Growth Mechanism and Structural Characterization of Spinel-Type LixMn2O4 Electrodes Realized via Pulsed Laser Deposition

SSRN

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SSRN 2025年

作者： Sanna, Simone Orgiani, Pasquale Krymskaya, Olga Di Castro, Daniele Galdi, Alice Tkalčević, Marija Aruta, Carmela Tebano, Antonello Department of Civil Engineering and Computer Science University of Rome "Tor Vergata" CNR-SPIN RomeI-00133 Italy TASC Laboratory in Area Science Park Trieste34139 Italy Department of Astronautical Electrical and Energetic Engineering University of Rome "La Sapienza" CNR-SPIN RomeI-00184 Italy I-84084 Italy CNR-SPIN Via Del Fosso del Cavaliere 100 RomeI-00133 Italy

Spinel-type lithium manganese oxide (LiMn2O4) is considered one of the most promising cathode materials for rechargeable batteries due to its high operating voltage, reduced toxicity, and lower cost compared to cobalt-based cathodes. However, the stability of LiMn2O4 is a significant challenge, as it tends to degrade over time, with manganese ion segregation leading to a reduction in battery capacity. The crystal structure of LixMn2O4 is highly dependent on the lithium content (x), and it can exist either in a single-phase or a two-phase form. These structural variations significantly affect the material’s electrochemical performance. In this work, we present the growth and structural characterization of LixMn2O4 thin films, with (x) values of 1 and 0.7, aimed at improving chemical stability and overall performance. The epitaxial LixMn2O4 films were deposited using Pulsed Laser Deposition on different single-crystal substrates, including water-soluble Sr3Al2O6-buffered SrTiO3(100). Films grown on MgO(001) for both x=1 and x=0.7 exhibited excellent crystallographic quality, while films deposited on SrTiO3(001) showed good quality for x=1, albeit with a slightly higher mosaic spread compared to those on MgO. Notably, for x=0.7, a two-phase region was observed on the SrTiO3 and MgO substrates, where both phases shared the same structure but differed slightly in lattice parameters. © 2025, The Authors. All rights reserved.

关键词： Single crystals

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Optical Integrated Sensing and Communication: architectures, Potentials and Challenges

arXiv

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arXiv 2023年

作者： Wen, Yunfeng Yang, Fang Song, Jian Han, Zhu The Department of Electronic Engineering Tsinghua University Beijing100084 China The Key Laboratory of Digital TV System of Shenzhen City Research Institute of Tsinghua University in Shenzhen Shenzhen518057 China The Shenzhen International Graduate School Tsinghua University Shenzhen518055 China The Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

Integrated sensing and communication (ISAC) is viewed as a crucial component of future mobile networks and has gained much interest in both academia and industry. Similar to the emergence of radio-frequency (RF) ISAC, the integration of free space optical communication and optical sensing yields optical ISAC (O-ISAC), which is regarded as a powerful complement to its RF counterpart. In this article, we first introduce the generalized system structure of O-ISAC, and then elaborate on three advantages of O-ISAC, i.e., increasing communication rate, enhancing sensing precision, and reducing interference. Next, waveform design and resource allocation of O-ISAC are discussed based on pulsed waveform, constant-modulus waveform, and multi-carrier waveform. Furthermore, we put forward future trends and challenges of O-ISAC, which are expected to provide some valuable directions for future research. Copyright © 2023, The Authors. All rights reserved.

关键词： Optical communication

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Large-scale and high-quality III-nitride membranes through microcavity-assisted crack propagation by engineering tensile-stressed Ni layers

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Opto-Electronic science 2022年第10期1卷 51-61,42-50页

作者： Jung-Hong Min Kwangjae Lee Tae-Hoon Chung Jung-Wook Min Kuang-Hui Li Chun Hong Kang Hoe-Min Kwak Tae-Hyeon Kim Youyou Yuan Kyoung-Kook Kim Dong-Seon Lee Tien Khee Ng Boon S.Ooi Photonics Laboratory ComputerElectrical and Mathematical Sciences and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Department of Electrical Engineering Stanford UniversityStanfordCA 94305USA Light Source Research Division Korea Photonics Technology Institute(KOPTI)Gwangju 61007Republic of Korea School of Electrical Engineering and Computer Science Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea Department of Advanced Convergence Technology Research Institute of Advanced Convergence TechnologyKorea Polytechnic University237 Sangidaehak-roSiheung-si 15073Republic of Korea King Abdullah University of Science and Technology(KAUST) Thuwal 23955-6900Saudi Arabia

Epitaxially grown III-nitride alloys are tightly bonded materials with mixed covalent-ionic *** tight bonding presents tremendous challenges in developing III-nitride membranes,even though semiconductor membranes can provide numerous advantages by removing thick,inflexible,and costly ***,cavities with various sizes were introduced by overgrowing target layers,such as undoped GaN and green LEDs,on nanoporous templates prepared by electrochemical etching of n-type *** large primary interfacial toughness was effectively reduced according to the design of the cavity density,and the overgrown target layers were then conveniently exfoliated by engineering tensile-stressed Ni *** resulting III-nitride membranes maintained high crystal quality even after exfoliation due to the use of GaN-based nanoporous templates with the same lattice *** microcavity-assisted crack propagation process developed for the current III-nitride membranes forms a universal process for developing various kinds of large-scale and high-quality semiconductor membranes.

关键词： III-nitride alloys membranes nanoporous Ni stressor light-emitting diodes ultraviolet photodetectors

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Atmosphere-Dependent Pyrolytic Transformability of Glass Fiber/Epoxy Resin Composites in Waste Wind Turbine Blades

SSRN

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SSRN 2024年

作者： Chen, Siqi Liu, Jingyong Lin, Ziting Lin, Sen Li, Liangzhong Chen, Yan Evrendilek, Fatih Yang, Chenyu Yuan, Haoran He, Yao Xie, Wuming School of Environmental Science and Engineering Guangdong University of Technology Guangzhou510006 China Guangdong Provincial Key Laboratory of High-Quality Recycling of End-of-Life New Energy Devices Guangzhou Institute of Energy Research Chinese Academy of Sciences Guangzhou510630 China Department of Electrical and Computer Engineering College of Engineering Boston University BostonMA02215 United States

The wind power industry is grappling with the sustainable disposal of a growing volume of retired wind turbine blades. While these blades contain recyclable composite materials (e.g., glass fiber/epoxy resin), effective recycling methods remain limited. This study characterized the influence of the N2 and CO2 atmospheres on the thermal decomposition of glass fiber/epoxy resin composite through thermogravimetry (TG), TG-Fourier transform infrared spectroscopy (TG-FTIR), and pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS). Both atmospheres exhibited similar mass loss profiles, with devolatilization occurring between 237.80−578.30 °C (N2) and 236.62−553.32 °C (CO2). CO2 inhibited pyrolytic gas formation compared with N2. Pyrolytic oils identified primarily consisted of phenols, alcohols/ethers, and aliphatics, with compositional changes with 400 °C, 500 °C, and 600 °C. At the elevated temperatures, phenolic compounds underwent deoxidation to form aromatic structures, while pyrolytic carbon surface fragments contracted and melted. Not only were residual mass, decomposition rate, and five volatile products jointly optimized, but also their sensitivities to the temperature and atmosphere were quantified using artificial neural networks. This study provides a theoretical and scalable basis for developing sustainable strategies of thermal circularity for waste wind turbine blades. © 2024, The Authors. All rights reserved.

关键词： Fourier transform infrared spectroscopy

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Hardware-Aware In Situ Learning Based on Stochastic Magnetic Tunnel Junctions

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Physical Review Applied 2022年第1期17卷 014016-014016页

作者： Jan Kaiser William A. Borders Kerem Y. Camsari Shunsuke Fukami Hideo Ohno Supriyo Datta Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette Indiana 47906 USA Laboratory for Nanoelectronics and Spintronics Research Institute of Electrical Communication Tohoku University Sendai Japan Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara California 93106 USA Center for Innovative Integrated Electronic Systems Tohoku University Sendai Japan Center for Spintronics Research Network Tohoku University Sendai Japan Center for Science and Innovation in Spintronics Tohoku University Sendai Japan WPI-Advanced Institute for Materials Research Tohoku University Sendai Japan

One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics is a promising catalyst for this field with the capabilities of nanosecond operation and compatibility with existing microelectronics. Considering large-scale, viable neuromorphic systems however, variability of device properties is a serious concern. In this paper, we show an autonomously operating circuit that performs hardware-aware machine learning utilizing probabilistic neurons built with stochastic magnetic tunnel junctions. We show that in situ learning of weights and biases in a Boltzmann machine can counter device-to-device variations and learn the probability distribution of meaningful operations such as a full adder. This scalable autonomously operating learning circuit using spintronics-based neurons could be especially of interest for standalone artificial-intelligence devices capable of fast and efficient learning at the edge.

关键词： Spintronics Stochastic inference Synapses Artificial neural networks Magnetic tunnel junctions Stochastic dynamical systems Machine learning

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A Framework on Fully Distributed State Estimation and Cooperative Stabilization of LTI Plants

arXiv

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arXiv 2023年

作者： Duan, Peihu Lv, Yuezu Wen, Guanghui Ogorzalek, Maciej School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Advanced Research Institute of Multidisciplinary Sciences Beijing Institute of Technology Beijing100081 China The Department of Systems Science School of Mathematics Southeast University Nanjing211189 China The Department of Information Technologies Jagiellonian University Krakow30-348 Poland

How to realize high-level autonomy of individuals is one of key technical issues to promote swarm intelligence of multi-agent (node) systems with collective tasks, while the fully distributed design is a potential way to achieve this goal. This paper works on the fully distributed state estimation and cooperative stabilization problem of linear time-invariant (LTI) plants with multiple nodes communicating over general directed graphs, and is aimed to provide a fully distributed framework for each node to perform cooperative stabilization tasks. First, by incorporating a novel adaptive law, a consensus-based estimator is designed for each node to obtain the plant state based on its local measurement and local interaction with neighbors, without using any global information of the communication topology. Subsequently, a local controller is developed for each node to stabilize the plant collaboratively with performance guaranteed under mild conditions. Specifically, the proposed method only requires that the communication graph be strongly connected, and the plant be collectively controllable and observable. Further, the proposed method can be applied to pure fully distributed state estimation scenarios and modified for noise-bounded LTI plants. Finally, two numerical examples are provided to show the effectiveness of the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi agent systems

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Electrochemical hydrogen charging treatment for hydrogenated 316 L stainless steel induced hydrogen therapy for orthopedic implantation

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Surface and Coatings Technology 2024年 479卷

作者： Lin, Yu-Chien Dhawan, Udesh Liu, Yen-Chen Lee, Yueh-Lien Liu, Xinke Yen, Hung-Wei Hu, Chih-Chien Chung, Ren-Jei Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan School of Materials Science and Engineering Nanyang Technological University Singapore Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow Glasgow United Kingdom Department of Engineering Science and Ocean Engineering National Taiwan University Taipei Taiwan College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhe China Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Materials Science and Engineering National Taiwan University Taipei Taiwan Bone and Joint Research Center Chang Gung Memorial Hospital Linko Taiwan Department of Orthopaedic Surgery Chang Gung Memorial Hospital Linko Taiwan College of Medicine Chang Gung University Taoyuan Taiwan Taipei Taiwan

Post-implant inflammation is a leading factor in the failure of orthopedic implant surgery. Hydrogen therapy is viewed as a medium capable of reducing reactive oxygen species (ROS) to alleviate inflammatory responses. However, existing hydrogen therapy methods have limitations, often involving undesired inhalation, injection, or non-targeted exposure of hydrogen to the body. To address this, the concept of delivering hydrogen precisely using the implant itself has been conducted in this study. Traditional hydrogen treatments for metallic implant materials, such as 316 L stainless steel (316 L SS), can induce hydrogen embrittlement (HE), significantly restricting the potential applications of hydrogenated implants in the biomedical field. Therefore, in this study, the electrochemical cathodic hydrogen charging method was employed to diffuse a hydrogenated layer of approximately 216 ± 31 nm on the surface of 316 L SS. This renders the material minimized by HE and alters its surface properties. Through in vitro and in vivo experiments, an approximately 80 % free radical scavenging rate was achieved. Additionally, significant anti-inflammatory effects were observed in the histological analysis of Femur implantation. This demonstrates that the surface hydrogenation treatment can impart anti-inflammatory properties to metallic implant materials without compromising their inherent material properties, thereby enhancing the success rate of surgical procedures. © 2024

关键词： Hydrogen

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