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arXiv 2023年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In Shen, Xuemin The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada

Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potential, especially when integrating with semantic communication (SemCom). In this paper, a novel comprehensive conceptual model for the integration of AIGC and SemCom is developed. Particularly, a content generation level is introduced on top of the semantic level that provides a clear outline of how AIGC and SemCom interact with each other to produce meaningful and effective content. Moreover, a novel framework that employs AIGC technology is proposed as an encoder and decoder for semantic information, considering the joint optimization of semantic extraction and evaluation metrics tailored to AIGC services. The framework can adapt to different types of content generated, the required quality and the semantic information utilized. By employing a Deep Q Network (DQN), a case study is presented that provides useful insights into the feasibility of the optimization problem and its convergence characteristics. © 2023, CC BY.

关键词： Wireless networks

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Norepinephrine changes behavioral state through astroglial purinergic signaling

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science (New York, N.Y.) 2025年第6748期388卷 769-775页

作者： Chen, Alex B. Duque, Marc Rymbek, Altyn Dhanasekar, Mahalakshmi Wang, Vickie M. Mi, Xuelong Tocquer, Loeva Narayan, Sujatha Legorreta, Emmanuel Marquez Eddison, Mark Yu, Guoqiang Wyart, Claire Prober, David A. Engert, Florian Ahrens, Misha B. Howard Hughes Medical Institute Janelia Research Campus Ashburn VA United States Department of Molecular and Cellular Biology Harvard University Cambridge MA United States Graduate Program in Neuroscience Harvard Medical School Boston MA United States Tianqiao and Chrissy Chen Institute for Neuroscience Division of Biology and Biological Engineering California Institute of Technology Pasadena CA United States Sorbonne Université Paris Brain Institute (Institut du Cerveau Institut National de la Santé et de la Recherche Médicale U1127 Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225 Assistance Publique-Hôpitaux de Paris Campus Hospitalier Pitié-Salpêtrière Paris France Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington VA United States Present address: Allen Institute for Brain Science Seattle WA United States Department of Automation Tsinghua University Beijing China

Both neurons and glia communicate through diffusible neuromodulators;however, how neuron-glial interactions in such neuromodulatory networks influence circuit computation and behavior is unclear. During futility-induced behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine (NE) drives fast excitation and delayed inhibition of behavior and circuit activity. We found that astroglial purinergic signaling implements the inhibitory arm of this motif. In larval zebrafish, NE triggers astroglial release of adenosine triphosphate (ATP), extracellular conversion of ATP into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. Our results suggest a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in NE-mediated behavioral and brain state transitions and position astroglia as important effectors in neuromodulatory signaling.

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The Michigan Robotics Undergraduate Curriculum: Defining the Discipline of Robotics for Equity and Excellence

arXiv

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arXiv 2023年

作者： Jenkins, Odest Chadwicke Grizzle, Jessy Atkins, Ella Stirling, Leia Rouse, Elliott Guzdial, Mark Provost, Damen Mann, Kimberly Millunchick, Joanna Robotics and Electrical Engineering & Computer Science United States Undergraduate Education Robotics Institute United States Robotics Institute United States Graduate Programs Robotics Institute United States Robotics and Industrial Engineering United States Robotics and Mechanical Engineering United States Electrical Engineering & Computer Science United States Engineering Education Research Program United States Undergraduate Education College of Engineering United States University of Michigan United States

The Robotics Major at the University of Michigan was successfully launched inthe 2022-23 academic year as an innovative step forward to better servestudents, our communities, and our society. Building on our guiding principleof "Robotics with Respect" and our larger Robotics Pathways model, the MichiganRobotics Major was designed to define robotics as a true academic disciplinewith both equity and excellence as our highest priorities. Understanding thattalent is equally distributed but opportunity is not, the Michigan RoboticsMajor has embraced an adaptable curriculum that is accessible through adiversity of student pathways and enables successful and sustained career-longparticipation in robotics, AI, and automation professions. The results afterour planning efforts (2019-22) and first academic year (2022-23) have beenhighly encouraging: more than 100 students declared Robotics as their major,completion of the Robotics major by our first two graduates, soaringenrollments in our Robotics classes, thriving partnerships with HistoricallyBlack Colleges and Universities. This document provides our original curricularproposal for the Robotics Undergraduate program at the University of Michigan,submitted to the Michigan Association of State Universities in April 2022 andapproved in June 2022. The dissemination of our program design is in the spiritof continued growth for higher education towards realizing equity andexcellence. The most recent version of this document is also available on Google Docsthrough this link: https://***/robotics_majorMSC Codes 97 © 2023, CC BY.

关键词： Curricula

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Glaucoma identification with retinal fundus images using deep learning: Systematic review

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Informatics in Medicine Unlocked 2025年 56卷

作者： Meedeniya, Dulani Shyamalee, Thisara Lim, Gilbert Yogarajah, Pratheepan Department of Computer Science and Engineering University of Moratuwa Moratuwa 10400 Sri Lanka First-Year Division Faculty of Computing Sri Lanka Institute of Information Technology Malabe 10115 Sri Lanka SingHealth AI Health Program SingHealth Group Singapore 168582 Singapore School of Computing Engineering and Intelligent System Ulster University Londonderry BT48 7JL United Kingdom

Glaucoma is a leading cause of blindness, affecting millions of people worldwide. It is a chronic eye condition that damages the optic nerve and, if left untreated, can lead to vision loss and a decreased quality of life. Therefore, there is a need to explore practical and reliable mechanisms for glaucoma identification. This study systematically reviews deep-learning approaches for glaucoma identification using retinal fundus images from 2018 to 2024. Compared to existing survey studies, we cover the latest research, including several public retinal fundus image datasets, and focus on segmentation, classification based on convolutional neural networks and vision transformers, and explainability. The findings of this study, including comparisons of existing methods and key insights, will assist researchers and developers in identifying the most suitable techniques for glaucoma detection. © 2025 The Authors

关键词： Artificial intelligence Classification Deep learning Explainability Glaucoma Segmentation Trustworthiness

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Evaluation of multiple SAR speckling filter techniques performance in irrigated rice areas

Evaluation of multiple SAR speckling filter techniques perfo...

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2024 Symposium on Beyond the Canopy: Technologies and Applications of Remote Sensing

作者： Garcia, Andre Dalla Bernardina Celeste, Jimuel Cheng, Irene Prudente, Victor Hugo Rohden Del’Arco Sanches, Ieda INPE National Institute for Space Research PGSER Remote Sensing Graduate Program Coordination of Teaching COEPE São José dos Campos São Paulo12227-010 Brazil UoA University of Alberta Dept. Of Computing Science EdmontonABT6G 2S4 Canada UofM University of Michigan School for Environment and Sustainability Ann ArborMI48109 United States Multimedia Research Centre University of Alberta EdmontonABT6G 2E8 Canada DIOTG Earth Observation and Geoinformatics Division CG-TG General Coodination of Earth Science INPE National Institute for Space Research Teaching COEPE São Paulo São José dos Campos12227-010 Brazil

Monitoring irrigated rice crops is essential for efficient agricultural management, and Synthetic Aperture Radar (SAR) images are beneficial due to their capability to function in all weather conditions. However, speckle noise in SAR images complicates the classification of land cover. This study evaluates speckle filtering techniques to enhance the image quality of SAR for rice field monitoring. We extend previous work by comparing Bayesian filters in the spatial domain with advanced transform domain methods, including block matching 3D (BM3D) and Discrete Fourier Transform-extracted Edge (DFT Edge) techniques, across different rice growth stages. Twenty-two Sentinel-1B SAR images from the municipality of Turvo, Santa Catarina, Brazil were analyzed. Filters were assessed using metrics for speckle suppression and edge preservation. Our experiments reveal that BM3D with a sigma parameter of 10 (BM3Dsigma10) provided superior results, balancing effective speckle suppression and edge preservation. Specifically, BM3Dsigma10 was superior in preserving edge details compared to other techniques. However, as the σ value increased, a loss in resolution was observed, even for the DFT Edge method, which, while efficient in edge preservation, often resulted in reduced detail resolution. These findings highlight the importance of selecting appropriate filtering techniques for accurate agricultural monitoring using SAR data. © Author(s) 2024.

关键词： Discrete Fourier transforms

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Intrinsic Parameter Fluctuation and Process Variation Effect of Vertically Stacked Silicon Nanosheet Complementary Field-Effect Transistors

Intrinsic Parameter Fluctuation and Process Variation Effect...

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IEEE International Symposium on Quality Electronic Design

作者： Sekhar Reddy Kola Yiming Li Min-Hui Chuang Parallel and Scientific Computing Laboratory Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program Hsinchu Taiwan Institute of Communications Engineering Hsinchu Taiwan Institute of Biomedical Engineering Hsinchu Taiwan Institute of Pioneer Semiconductor Innovation Hsinchu Taiwan Institute of Artificial Intelligence Innovation Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Center for mmWave Smart Radar System and Technologies National Yang Ming Chiao Tung University Hsinchu Taiwan

We study the variability of vertically stacked gate-all-around silicon nanosheet (GAA Si NS) complementary field-effect transistors (CFETs). The process variation effect (PVE), the work function fluctuation (WKF), and the random dopant fluctuation (RDF) of CFETs are statistically estimated using an experimentally validated device simulation technique. Among five factors of PVE, the channel thickness (T Nch /T Pch ), the channel width (W ch ), and the gate length (L G ) are significant. Owing to superior GAA channel control and increased effective gate area, both WKF and RDF are suppressed. Notably, the PVE on both N-/P-FETs of GAA Si CFET induce the largest off-state current fluctuations of 80% and 278%, respectively, because the device characteristic is very sensitive to the layer thickness and width of channel.

关键词： Fluctuations Gallium arsenide Logic gates Electric variables Silicon Resource description framework Semiconductor process modeling

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High-Resolution Hydrogen Molecule Detection Utilizing a Nanocandle-Based Optical Sensor

High-Resolution Hydrogen Molecule Detection Utilizing a Nano...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Nu-Ri Park Min-Joong Kim Jongsu Lee Minah Seo Yong-Sang Ryu Myung-Ki Kim KU-KIST Graduate School of Converging Science and Technology Korea University Seoul Republic of Korea Sensor System Research Center Korea Institute of Science and Technology Seoul Republic of Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA School of Biomedical Engineering Korea University Seoul Republic of Korea Interdisciplinary Program in Precision Public Health Korea University Seoul Republic of Korea

Our research introduces a novel method for safe hydrogen detection. We've developed an advanced nano-candle sensor, combining Pd with nano-candles, enabling accurate detection of low-concentration hydrogen (<3%... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Electric potential Accuracy Hydrogen Lasers and electrooptics Optical sensors Electro-optical waveguides

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COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

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computers, Materials & Continua 2021年第7期68卷 391-407页

作者： Aqib Ali Wali Khan Mashwani Samreen Naeem Muhammad Irfan Uddin Wiyada Kumam Poom Kumam Hussam Alrabaiah Farrukh Jamal Christophe Chesneau Department of Computer Science Concordia College BahawalpurBahawalpur63100Pakistan Department of Computer Science&IT Glim Institute of Modern StudiesBahawalpur63100Pakistan Institute of Numerical Sciences Kohat University of Science&TechnologyKohat26000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Program in Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiThanyaburi12110Thailand Departments of Mathematics Faculty of ScienceCenter of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research LaboratoryRoom SCL 802 Fixed Point LaboratoryScience Laboratory BuildingKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand Department of Medical Research China Medical University HospitalTaichung40402Taiwan College of Engineering Al Ain UniversityAl Ain64141United Arab Emirates Department of Mathematics Tafila Technical UniversityTafila66110Jordan Department of Statistics The Islamia University of BahawalpurBahawalpur63100Pakistan 11Department of MathematicsUniversitéde CaenLMNOCaen14032France

The purpose of this research is the segmentation of lungs computed tomography(CT)scan for the diagnosis of COVID-19 by using machine learning *** dataset contains data from patients who are prone to the *** contains three types of lungs CT images(Normal,Pneumonia,and COVID-19)collected from two different sources;the first one is the Radiology Department of Nishtar Hospital Multan and Civil Hospital Bahawalpur,Pakistan,and the second one is a publicly free available medical imaging database known as *** the preprocessing,a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest(ROIs)and acquire 52 hybrid statistical features for each ***,12 optimized statistical features are selected via the chi-square feature reduction *** the classification,five machine learning classifiers named as deep learning J4,multilayer perceptron,support vector machine,random forest,and naive Bayes are deployed to optimize the hybrid statistical features *** is observed that the deep learning J4 has promising results(sensitivity and specificity:0.987;accuracy:98.67%)among all the deployed *** a complementary study,a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.

关键词： COVID-19 machine learning fuzzy c-mean deep learning J4

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Vision-based Semantic Communications for Metaverse Services: A Contest Theoretic Approach

Vision-based Semantic Communications for Metaverse Services:...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Guangyuan Liu Hongyang Du Dusit Niyato Jiawen Kang Zehui Xiong Boon Hee Soong Energy Research Institute@NTU Interdisciplinary Graduate Program School of Computer Science and Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Electronic Engineering Nanyang Technological University Singapore

The popularity of Metaverse as an entertainment, social, and work platform has led to a great need for seamless avatar integration in the virtual world. In Metaverse, avatars must be updated and rendered to reflect users' behaviour. Achieving real-time synchronization between the virtual bilocation and the user is complex, placing high demands on the Metaverse Service Provider (MSP)'s rendering resource allocation scheme. To tackle this issue, we propose a semantic communication framework that leverages contest theory to model the interactions between users and MSPs and determine optimal resource allocation for each user. To reduce the consumption of network resources in wireless transmission, we use the semantic communication technique to reduce the amount of data to be transmitted. Under our simulation settings, the encoded semantic data only contains 51 bytes of skeleton coordinates instead of the image size of 8.243 megabytes. Moreover, we implement Deep Q-Network to optimize reward settings for maximum performance and efficient resource allocation. With the optimal reward setting, users are incentivized to select their respective suitable uploading frequency, reducing down-sampling loss due to rendering resource constraints by 66.076% compared with the traditional average distribution method. The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.

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Evaluating Conveyor Belt Health With Signal Processing Applied to Inertial Sensing

Evaluating Conveyor Belt Health With Signal Processing Appli...

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International Workshop on Secure Internet of Things (SIoT)

作者： Saulo Neves Matos Otávio Ferracioli Coletti Fernando Ugucioni Filho Ricardo C. C. L. de Carvalho Thomas V. B. Pinto Luiz G. D. de Barros Caetano Mazzoni Ranieri Bruno Eduardo Lopes Jó Ueyama Gustavo Pessin Institute of Mathematics and Computer Science University of sao Paulo Brazil Sao Carlos School of Engineering University of Sao Paulo Brazil Vale Institute of Technology Ouro Preto Brazil Graduate Program in Electrical Engineering Universidade Federal of Minas Gerais Belo Horizonte MG Brazil Vale -SA Vitoria Brazil

Conveyor belts are commonly used in the mining industry for efficient material transport. However, they are prone to failures such as idler anomalies, belt tears, and misalignment. Current monitoring systems only evaluate the conveyor or idle belt's condition at the installation point. This study proposes a method to detect faults in conveyor belts, specifically idler anomalies and belt deviation, using two IMUs installed at the lateral extremities of the belt to evaluate its health along its route. In a reduced-scale conveyor belt, we conducted experiments by collecting gyroscopes and accelerometer data in various scenarios, including normal conditions and anomaly situations. We modified the idlers' physical structure or changed the belt tracks to create these scenarios. We used similarity analysis techniques to compare the data collected and performed statistical hypothesis analysis to observe the influence of the anomaly scenarios on the gyroscope and accelerometer data. We used Dynamic Time Warping (DTW) for gyroscope data to compare ground truth with anomaly scenarios. For the acceleration data, we performed vibration analysis by converting the time domain data to the frequency using Fast Fourier Transform (FFT) and evaluating the difference in spectral density between the reference and anomaly data. Statistical hypothesis analysis revealed that anomaly scenar-ios influenced the gyroscope x-axis and z-axis more. According to the spectral density analysis of the accelerometer, it was revealed that belt misalignment on the y-axis may be detected.

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