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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Innem V.A.K Reddy Andrea Bertoncini Carlo Liberale Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Electrical Engineering University at Buffalo NY USA Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia

ISBN: (纸本)9798350345995

Diffraction-free propagation and self-healing characteristics [1] of Bessel beams have generated significant interest in the scientific community. Zeroth-order Bessel beams (ZOBBs) have maximum intensity at the center and found many applications, including bio-imaging material processing, optical trapping, bio-imaging, and quantum communication. On the other hand, higher-order (vortex) Bessel beams (HOBBs) present a helical wavefront, so they have a node due to a phase singularity and carry orbital angular momentum (OAM). Over the past years, Bessel beams have been generated by using different approaches - which could be different for ZOBBs and HOBBs - namely by Fourier transforming a narrow circular beam with a lens, by using axicons or with holographic beam shaping techniques.

关键词： Beam shaping Fourier transforms Materials processing Optical trapping Optical vortices Single mode fibers

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Statistical Spectral and Coherence Analysis of Electroencephalography (EEG) Data: Neural Biomarkers of Attention Deficit Hyperactivity Disorder (ADHD)

Statistical Spectral and Coherence Analysis of Electroenceph...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Fai Alismail Hernando Ombao Biostatistics/Biological Environmental Sciences and Engineering King Abdullah University of Science and Technology (KAUST) Saudi Arabia Biostatistics/Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology (KAUST) Saudi Arabia

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Electroencephalography (EEG) is a non-invasive tool widely used for studying brain activity, offering high temporal resolution for real-time analysis of neural dynamics. This study investigates the neurophysiological underpinnings of Attention Deficit Hyperactivity Disorder (ADHD) through statistical spectral and coherence analysis of EEG data. By focusing on frequency bands, we identified distinct patterns in ADHD subjects, including increased beta and alpha power, reduced gamma activity, and altered connectivity in key brain regions. These findings underscore the potential of EEG-based biomarkers for improving ADHD diagnosis and treatment strategies.

关键词： Visualization Protocols Neural activity Focusing Coherence Biomarkers Electroencephalography Real-time systems Reliability Object recognition

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TransNet: Transparent Object Manipulation Through Category-Level Pose Estimation

arXiv

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arXiv 2023年

作者： Zhang, Huijie Opipari, Anthony Chen, Xiaotong Zhu, Jiyue Yu, Zeren Jenkins, Odest Chadwicke Electrical Engineering and Computer Science Mechanical Engineering and Robotics departments University of Michigan Ann ArborMI United States Department of Computer Science University of Southern California Los AngelesCA United States

Transparent objects present multiple distinct challenges to visual perception systems. First, their lack of distinguishing visual features makes transparent objects harder to detect and localize than opaque objects. Even humans find certain transparent surfaces with little specular reflection or refraction, like glass doors, difficult to perceive. A second challenge is that depth sensors typically used for opaque object perception cannot obtain accurate depth measurements on transparent surfaces due to their unique reflective properties. Stemming from these challenges, we observe that transparent object instances within the same category, such as cups, look more similar to each other than to ordinary opaque objects of that same category. Given this observation, the present paper explores the possibility of category-level transparent object pose estimation rather than instance-level pose estimation. We propose TransNet, a two-stage pipeline that estimates category-level transparent object pose using localized depth completion and surface normal estimation. TransNet is evaluated in terms of pose estimation accuracy on a large-scale transparent object dataset and compared to a state-of-the-art category-level pose estimation approach. Results from this comparison demonstrate that TransNet achieves improved pose estimation accuracy on transparent objects. Moreover, we use TransNet to build an autonomous transparent object manipulation system for robotic pick-and-place and pouring tasks. The project webpage is available at https://***/projects/transnet/. © 2023, CC BY.

关键词： Object detection

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Advancing Volumetric Medical Image Segmentation via Global-Local Masked Autoencoders

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IEEE Transactions on Medical Imaging 2025年

作者： Zhuang, Jiaxin Luo, Luyang Wang, Qiong Wu, Mingxiang Luo, Lin Chen, Hao Hong Kong University of Science and Technology Departments of Computer Science and Engineering Hong Kong Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen China Peking University College of Engineering Beijing China Hong Kong University of Science and Technology Department of Computer Science and Engineering Department of Chemical and Biological Engineering Hong Kong HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China

Masked Autoencoder (MAE) is a self-supervised pre-training technique that holds promise in improving the representation learning of neural networks. However, the current application of MAE directly to volumetric medical images poses two challenges: (i) insufficient global information for clinical context understanding of the holistic data, and (ii) the absence of any assurance of stabilizing the representations learned from randomly masked inputs. To conquer these limitations, we propose the Global-Local Masked AutoEncoders (GL-MAE), a simple yet effective selfsupervised pre-training strategy. GL-MAE acquires robust anatomical structure features by incorporating multilevel reconstruction from fine-grained local details to high-level global semantics. Furthermore, a complete global view serves as an anchor to direct anatomical semantic alignment and stabilize the learning process through global-to-global consistency learning and global-to-local consistency learning. Our fine-tuning results on eight mainstream public datasets demonstrate the superiority of our method over other state-of-the-art self-supervised algorithms, highlighting its effectiveness on versatile volumetric medical image segmentation and classification tasks. © 1982-2012 IEEE.

关键词： Self-supervised learning

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TOWARDS GENERAL FUNCTION APPROXIMATION IN ZERO-SUM MARKOV GAMES 10

TOWARDS GENERAL FUNCTION APPROXIMATION IN ZERO-SUM MARKOV GA...

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10th International Conference on Learning Representations, ICLR 2022

作者： Huang, Baihe Lee, Jason D. Wang, Zhaoran Yang, Zhuoran School of Mathematical Sciences Peking University China Department of Electrical and Computer Engineering Princeton University United States Departments of Industrial Engineering & Management Sciences Northwestern University United States Department of Statistics and Data Science Yale University United States

This paper considers two-player zero-sum finite-horizon Markov games with simultaneous moves. The study focuses on the challenging settings where the value function or the model is parameterized by general function classes. Provably efficient algorithms for both decoupled and coordinated settings are developed. In the decoupled setting where the agent controls a single player and plays against an arbitrary opponent, we propose a new model-free algorithm. The sample complexity is governed by the Minimax Eluder dimension-a new dimension of the function class in Markov games. As a special case, this method improves the state-of-the-art algorithm by a √d factor in the regret when the reward function and transition kernel are parameterized with d-dimensional linear features. In the coordinated setting where both players are controlled by the agent, we propose a model-based algorithm and a model-free algorithm. In the model-based algorithm, we prove that sample complexity can be bounded by a generalization of Witness rank to Markov games. The model-free algorithm enjoys a √K-regret upper bound where K is the number of episodes. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

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Road Surface Detection for Autonomous Smart Wheelchair 5

Road Surface Detection for Autonomous Smart Wheelchair

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5th World Symposium on Communication engineering, WSCE 2022

作者： Utaminingrum, Fitri Mayena, Sri Karim, Corina Wahyudi, Slamet Huda, Fais Al Lin, Chih-Yang Shih, Timothy K. Thaipisutikul, Tipajin Computer Vision Research Groups Brawijaya University Faculty of Computer Science Malang Indonesia Brawijaya University Mathematics Departments Malang Indonesia Brawijaya University Faculty of Computer Science Malang Indonesia Yuan-Ze University Department of Electrical Engineering Taoyuan32003 Taiwan National Central University Department of Computer Science and Information Engineering Taoyuan32001 Taiwan Mohidol University Faculty of Information and Communication Technology Thailand

ISBN: (数字)9781665450577

ISBN: (纸本)9781665450577

Today's wheelchair technology is evolving, with options ranging from manual wheelchairs, electric wheelchairs to the latest smart wheelchairs. However, wheelchairs on the market today still lack of the resources to facilitate advanced security for their users, particularly from the risk of injury or death caused by user neglect to differences in the rough and uneven texture surface structure and distinctions in road height levels when crossed by wheelchairs. Which would be at risk of accidents such as the existence of descending stairs. The victim may sustain physically visible physiological effects because of the accident, such as abrasions, bruises, tears, fractures, head injuries, and even death in fatal cases. The goal of this research is to enhance the security and safety of smart wheelchairs by developing autonomous controls with the extraction of gray level cooccurrence matrix (GLCM) texture features and the Naive Bayes Classification in anticipation of irregular road conditions and the existence of levels that are at risk of endangering wheelchair users based on camera input. According to the results of 100 experiments using 2-dimensional imagery data tested at d = 1, 2, 3, 4 and θ = 0°, 45°, 90°, 135° values, the resulting d = 1 and θ = 0° levels have the highest accuracy of 87% when classifying images of descending stairs and floors. © 2022 IEEE.

关键词： Wheelchairs

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Controlling gene-expression variability via sequestration-based feedbacks

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IFAC-PapersOnLine 2024年第23期58卷 13-18页

作者： Supravat Dey Cesar A. Vargas-Garcia Abhyudai Singh Department of Physics and Department of Computer Science and Engineering SRM University-AP Amaravati Andhra Pradesh Department of Physics SRM University - AP Amaravati Andhra Pradesh 522240 India Corporación Colombiana de Investigación Agropecuaria - AGROSAVIA Mosquera Colombia Departments of Electrical and Computer Engineering Biomedical Engineering at the University of Delaware Newark DE 19716 USA

Expressed Transcription Factors (TFs) not only bind to sites at target promoters but also to decoy sites scattered across the genome. Binding to such “decoys” sequesters TFs critically impacting the response time and stochasticity (noise) in TF and target gene expression level. When the TF is a stable molecule, whose concentration is diluted by cellular growth, our results show that for fixed mean concentration levels, such decoy bindings can both enhance or suppress random fluctuations in TF levels depending on the source of noise (i.e., intrinsic vs. extrinsic noise) and the strength of binding (i.e., weak vs. strong decoys). We implement negative autoregulation where free (unbound) TF molecules inhibit their synthesis. Our analytical results corroborated by numerical simulations reveal that sequestration accentuates the effects of feedback in the sense that noise attenuation by negative feedback is higher with sequestration than in the absence of feedback. We next consider an alternative form of feedback where the TF increases the production of its decoys, and such feedback architectures are frequently seen in endogenous gene regulation involving microRNA-TF circuits and in controlling cellular stress responses. For these circuits where decoy numbers are TF-regulated, we identify limits of noise suppression, and in many cases, these limits occur at intermediate TF-decoy binding affinities.

关键词： Stochastic gene expression decoys feedback regulation transcription factors

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Learned, Uncertainty-driven Adaptive Acquisition for Photon-Efficient Multiphoton Microscopy

arXiv

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arXiv 2023年

作者： Cassandra Tong, Y.E. Han, Jiashu Liu, Kunzan Angelopoulos, Anastasios Griffith, Linda Monakhova, Kristina You, Sixian the Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States Fu Foundation School of Engineering and Applied Science Columbia University in the City of New York United States Department of Electrical Engineering and Computer Science University of California Berkeley United States Department of Biological Engineering Massachusetts Institute of Technology United States

Multiphoton microscopy (MPM) is a powerful imaging tool that has been a critical enabler for live tissue imaging. However, since most multiphoton microscopy platforms rely on point scanning, there is an inherent trade-off between acquisition time, field of view (FOV), phototoxicity, and image quality, often resulting in noisy measurements when fast, large FOV, and/or gentle imaging is needed. Deep learning could be used to denoise multiphoton microscopy measurements, but these algorithms can be prone to hallucination, which can be disastrous for medical and scientific applications. We propose a method to simultaneously denoise and predict pixel-wise uncertainty for multiphoton imaging measurements, improving algorithm trustworthiness and providing statistical guarantees for the deep learning predictions. Furthermore, we propose to leverage this learned, pixel-wise uncertainty to drive an adaptive acquisition technique that rescans only the most uncertain regions of a sample. We demonstrate our method on experimental noisy MPM measurements of human endometrium tissues, showing that we can maintain fine features and outperform other denoising methods while predicting uncertainty at each pixel. Finally, with our adaptive acquisition technique, we demonstrate a 120× reduction in acquisition time and total light dose while successfully recovering fine features in the sample. We are the first to demonstrate distribution-free uncertainty quantification for a denoising task with real experimental data and the first to propose adaptive acquisition based on reconstruction uncertainty. © 2023, CC BY.

关键词： Pixels

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TWIGMA: a dataset of ai-generated images with metadata from twitter 23

TWIGMA: a dataset of ai-generated images with metadata from ...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Yiqun T. Chen James Zou Department of Biomedical Data Science Stanford University Stanford CA Departments of Biomedical Data Science Electrical Engineering and Computer Science Stanford University Stanford CA

Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos. In this work, we introduce TWIGMA (TWItter Generative-ai images with MetadatA), a comprehensive dataset encompassing over 800,000 gen-AI images collected from Jan 2021 to March 2023 on Twitter, with associated metadata (e.g., tweet text, creation date, number of likes), available at https://***/records/8031785. Through a comparative analysis of TWIGMA with natural images and human artwork, we find that gen-AI images possess distinctive characteristics and exhibit, on average, lower variability when compared to their non-gen-AI counterparts. Additionally, we find that the similarity between a gen-AI image and natural images is inversely correlated with the number of likes. Finally, we observe a longitudinal shift in the themes of AI-generated images on Twitter, with users increasingly sharing artistically sophisticated content such as intricate human portraits, whereas their interest in simple subjects such as natural scenes and animals has decreased. Our findings underscore the significance of TWIGMA as a unique data resource for studying AI-generated images.

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Adapting Software-defined Information Centric Networks for IEC 61850-based Substations

Adapting Software-defined Information Centric Networks for I...

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IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

作者： Kuldeep Singh Shivran Sharad Shrestha George Torres Sarasij Das Satyajayant Misra Department of Electrical Engineering Indian Institute of Science Bengaluru India Computer Science Department New Mexico State University Las Cruces USA Computer Science and ECE Departments New Mexico State University Las Cruces USA

ISBN: (数字)9798350373929

ISBN: (纸本)9798350373936

A robust communication infrastructure is the backbone of power system efficiency and reliability advancements, enabling real-time data exchange and control. The smart grid, a complex network of digital devices, relies on their seamless communication to share information for monitoring, control, and protection. As the number of these devices and their communication needs increase, the role of software-defined and information-centric networking frameworks will become more pronounced for offering reliable and secure operation solutions. Given the time-sensitive nature and specific architecture of smart grid protocols, software-defined information centric networks (SD-ICN) can be appropriately designed to meet these requirements. SD-ICN can improve security by controlling access and authentication and efficient distribution of contents in the network. This paper explores recent SD-ICN structures and strategies to improve the reliability and security of communication in power systems substations. An IEC 61850-based substation networking architecture is presented to demonstrate the application of SD-ICN. Additionally, a mechanism to map the substation devices using Substation Configuration Language (SCL) to a routable Named Data Networking (NDN) name to route in the SD-ICN network is proposed.

关键词： Substations Scalability Information-centric networking Asia Smart grids Power system reliability Reliability Security IEC Standards Standards

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