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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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Distributed Task-Oriented Communication Networks with Multimodal Semantic Relay and Edge Intelligence

arXiv

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arXiv 2024年

作者： Guo, Jie Chen, Hao Song, Bin Chi, Yuhao Yuen, Chau Yu, Fei Richard Li, Geoffrey Ye Niyato, Dusit The State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China The Hangzhou Institute of Technology Xidian University Hangzhou311231 China The School of Electrical and Electronics Engineering The School of Computer Science and Engineering Respectively Nanyang Technological University 639798 Singapore The Department of Systems and Computer Engineering Carleton University OttawaK1S 5B6 Canada The Faculty of Engineering Imperial College London LondonSW7 2AZ United Kingdom

In this article, we present a novel framework, named distributed task-oriented communication networks (DTCN), based on recent advances in multimodal semantic transmission and edge intelligence. In DTCN, the multimodal knowledge of semantic relays and the adaptive adjustment capability of edge intelligence can be integrated to improve task performance. Specifically, we propose the key techniques in the framework, such as semantic alignment and complement, a semantic relay scheme for deep joint source-channel relay coding, and collaborative device-server optimization and inference. Furthermore, a multimodal classification task is used as an example to demonstrate the benefits of the proposed DTCN over existing methods. Numerical results validate that DTCN can significantly improve the accuracy of classification tasks, even in harsh communication scenarios (e.g., low signal-to-noise regime), thanks to multimodal semantic relay and edge intelligence. © 2024, CC BY-NC-SA.

关键词： Signal to noise ratio

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

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Optik 2023年 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

引用

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

引用

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

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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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Wireless-Friendly Window Position Optimization for RIS-Aided Outdoor-to-Indoor Networks based on Multi-Modal Large Language Model

arXiv

引用

arXiv 2024年

作者： Hou, Jinbo Qiu, Kehai Zhang, Zitian Yu, Yong Wang, Kezhi Capolongo, Stefano Zhang, Jiliang Li, Zeyang Zhang, Jie The Department of Electronic and Electrical Engineering the University of Sheffield Sheffield United Kingdom The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom Brunel University London United Kingdom The School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China The Design & Health Lab Department of Architecture Built Environment and Construction Engineering Politecnico di Milano Italy The Department of Computer Science Brunel University London Middlesex UxbridgeUB8 3PH United Kingdom The State Key Laboratory of Synthetical Automation for Process Industries The College of Information Science and Engineering Northeastern University Shenyang China The Centre for Wireless Innovation Queen’s University of Belfast BelfastBT3 9DT United Kingdom

This paper aims to simultaneously optimize indoor wireless and daylight performance by adjusting the positions of windows and the beam directions of window-deployed reconfigurable intelligent surfaces (RISs) for RIS-aided outdoor-to-indoor (O2I) networks utilizing large language models (LLM) as optimizers. Firstly, we illustrate the wireless and daylight system models of RIS-aided O2I networks and formulate a joint optimization problem to enhance both wireless traffic sum rate and daylight illumination performance. Then, we present a multi-modal LLM-based window optimization (LMWO) framework, accompanied by a prompt construction template to optimize the overall performance in a zero-shot fashion, functioning as both an architect and a wireless network planner. Finally, we analyze the optimization performance of the LMWO framework and the impact of the number of windows, room size, number of RIS units, and daylight factor. Numerical results demonstrate that our proposed LMWO framework can achieve outstanding optimization performance in terms of initial performance, convergence speed, final outcomes, and time complexity, compared with classic optimization methods. The building’s wireless performance can be significantly enhanced while ensuring indoor daylight performance. Copyright © 2024, The Authors. All rights reserved.

关键词： Daylighting

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Cooperative Jamming and Relay Selection for Covert Communications

arXiv

引用

arXiv 2023年

作者： Gao, Chan Yang, Bin Zheng, Dong Jiang, Xiaohong Taleb, Tarik National Engineering Laboratory for Wireless Security School of Cybersecurity Xi’an University of Posts and Telecommunications Xi’an710121 China School of Computer and Information Engineering Chuzhou University China School of Systems Information Science Future University Hakodate Japan Information Technology and Electrical Engineering University of Oulu Oulu90570 Finland Department of Computer and Information Security Sejong University Seoul05006 Korea Republic of

This paper investigates the covert communications via cooperative jamming and relay selection in a wireless relay system, where a source intends to transmit a message to its destination with the help of a selected relay, and a warden attempts to detect the existence of wireless transmissions from both the source and relay, while friendly jammers send jamming signals to prevent warden from detecting the transmission process. To this end, we first propose two relay selection schemes, namely random relay selection (RRS) and max-min relay selection (MMRS), as well as their corresponding cooperative jamming (CJ) schemes for ensuring covertness in the system. We then provide theoretical modeling for the covert rate performance under each relay selection scheme and its CJ scheme and further explore the optimal transmit power controls of both the source and relay for covert rate maximization. Finally, extensive simulation/numerical results are presented to validate our theoretical models and also to illustrate the covert rate performance of the relay system under cooperative jamming and relay selection. Copyright © 2023, The Authors. All rights reserved.

关键词： Jamming

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Optical Integrated Sensing and Communication: architectures, Potentials and Challenges

arXiv

引用

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

引用

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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