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2024 Laser Science, LS 2024

作者： Bartos, Jan Ba Tis, Taleb Park, Wounjhang Huang, Shu-Wei Department of Electrical Computer and Energy Engineering University of Colorado Boulder80309 United States Material Science and Engineering Program University of Colorado Boulder80309 United States

We present progress towards an imaging magnetometer using a magneto-optical polymer nanocomposite thin film, experimentally demonstrating 29nT/√Hz sensitivity with © 2024 The Author(s). © Optica Publishing ... 详细信息

关键词： Heterodyne detection

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Wigner non-negative states that verify the Wigner entropy conjecture

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Physical Review A 2024年第1期110卷 012228-012228页

作者： Qipeng Qian Christos N. Gagatsos Program in Applied Mathematics The Department of Electrical and Computer Engineering The Wyant College of Optical Sciences The

We present further progress, in the form of analytical results, on the Wigner entropy conjecture set forth by Van Herstraeten and Cerf [Phys. Rev. A 104, 042211 (2021)] and Hertz et al. [J. Phys. A: Math. Theor. 50, 385301 (2017)]. Said conjecture asserts that the differential entropy defined for non-negative, yet physical, Wigner functions is minimized by pure Gaussian states while the minimum entropy is equal to 1+lnπ. We prove this conjecture for the qubits formed by Fock states |0〉 and |1〉 that correspond to non-negative Wigner functions. In particular, we derive an explicit form of the Wigner entropy for those states lying on the boundary of the set of Wigner non-negative qubits. We then consider general mixed states and derive a sufficient condition for the conjecture's validity. Lastly, we elaborate on the states which are in accordance with our condition.

关键词： Quantum foundations Quantum information theory

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Learning cortico-muscular dependence through orthonormal decomposition of density ratios 24

Learning cortico-muscular dependence through orthonormal dec...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Shihan Ma Bo Hu Tianyu Jia Alexander Kenneth Clarke Blanka Zicher Arnault H. Caillet Dario Farina José C. Principe Department of Bioengineering Imperial College London Department of Electrical and Computer Engineering University of Florida

ISBN: (纸本)9798331314385

The cortico-spinal neural pathway is fundamental for motor control and movement execution, and in humans it is typically studied using concurrent electroencephalography (EEG) and electromyography (EMG) recordings. However, current approaches for capturing high-level and contextual connectivity between these recordings have important limitations. Here, we present a novel application of statistical dependence estimators based on orthonormal decomposition of density ratios to model the relationship between cortical and muscle oscillations. Our method extends from traditional scalar-valued measures by learning eigenvalues, eigenfunctions, and projection spaces of density ratios from realizations of the signal, addressing the interpretability, scalability, and local temporal dependence of cortico-muscular connectivity. We experimentally demonstrate that eigenfunctions learned from cortico-muscular connectivity can accurately classify movements and subjects. Moreover, they reveal channel and temporal dependencies that confirm the activation of specific EEG channels during movement. Our code is available at https://***/bohu615/corticomuscular-eigen-encoder.

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Optimum classical beam-position sensing

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Physical Review Applied 2024年第4期22卷 L041004页

作者： Wenhua He Christos N. Gagatsos Dalziel J. Wilson Saikat Guha Wyant College of Optical Sciences Department of Electrical and Computer Engineering Program in Applied Mathematics

Beam-displacement measurements are widely used in optical sensing and communications; however, their performance is affected by numerous intrinsic and extrinsic factors, including beam profile, propagation loss, and receiver architecture. Here we present a framework for designing a classically optimal beam-displacement transceiver, using quantum estimation theory. We consider the canonical task of estimating the position of a diffraction-limited laser beam after passing through an apertured volume characterized by Fresnel-number product DF. As a rule of thumb, higher-order Gaussian modes provide more information about beam displacement, but are more sensitive to loss. Applying quantum Fisher information, we design mode combinations that optimally leverage this trade-off, and show that a greater than tenfold improvement in precision is possible, relative to the fundamental mode, for a practically relevant DF=100. We also show that this improvement is realizable with a variety of practical receiver architectures. Our findings extend previous works on lossless transceivers, may have immediate impact on applications, such as atomic force microscopy and near-field optical communication, and pave the way towards globally optimal transceivers using nonclassical laser fields.

关键词： Classical optics Metrology Quantum Fisher information Quantum optics Quantum parameter estimation Devices Wireless communication networks Atomic force microscopy

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Microdevice for directional axodendritic connectivity between micro 3D neuronal cultures

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Microsystems & Nanoengineering 2021年第5期7卷 227-239页

作者： Yixuan Ming Md Joynal Abedin Svetlana Tatic-Lucic Yevgeny Berdichevsky Department of Electrical&Computer Engineering Lehigh UniversityBethlehemPAUSA Department of Bioengineering Lehigh UniversityBethlehemPAUSA

Neuronal cultures are widely used in neuroscience ***,the randomness of circuits in conventional cultures prevents accurate in vitro modeling of cortical development and of the pathogenesis of neurological and psychiatric disorders.A basic feature of cortical circuits that is not captured in standard cultures of dissociated cortical cells is directional *** this work,a polydimethylsiloxane(PDMS)-based device that achieves directional connectivity between micro 3D cultures is *** device consists of through-holes for micro three-dimensional(n3D)clusters of cortical cells connected by microtrenches for axon and dendrite *** design of the trenches relies in part on the concept of axonal edge guidance,as well as on the novel concept of specific dendrite *** replicates dominant excitatory connectivity in the cortex,enables the guidance of the axon after it forms a synapse in passing(an"en passant"synapse),and ensures that directional selectivity is preserved over the lifetime of the *** directionality of connections was verified morphologically and *** were dependent on glutamatergic *** design of this device has the potential to serve as a building block for the reconstruction of more complex cortical circuits in vitro.

关键词： connectivity directional lifetime

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Using Random Forest and Linear SVM for Dyslexia Classification on Hebb-Williams Mazes 59

Using Random Forest and Linear SVM for Dyslexia Classificati...

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59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Kaushik, Padmanabh Yu, Yih-Choung Gabel, Lisa Lafayette College Department of Electrical and Computer Engineering EastonPA18042 United States Lafayette College Department of Psychology and Neuroscience Program EastonPA18042 United States

ISBN: (纸本)9798331513269

Dyslexia is a learning disability that negatively impacts an individual's ability to read, write, spell, and sometimes speak. It results in difficulties in recognizing and decoding words and patterns, despite normal level of education and intelligence. Studies have shown that early detection of dyslexia is vital for improving learning abilities in young children. Many virtual platforms exist for diagnosing and rehabilitating dyslexia;however, most require tests that measure reading skills. Since developing reading capabilities can delay the detection of dyslexia, a gaming platform based on Hebb-Williams mazes has been developed. This platform does not rely on reading skills and can diagnose dyslexia in young children. This paper presents a machine learning driven approach using two algorithms - Random Forest and Linear SVM - to classify reading abilities based on data from participants performing virtual maze tasks, which are indicative of symptoms of dyslexia. Results from this study indicate that it is possible to predict dyslexia with up to 95% accuracy based on a participant's performance in virtual gaming environments. © 2025 IEEE.

关键词： Adversarial machine learning

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Optimal control of electric automated buses in intercity lines: scenario-based analysis of the Pareto-optimal solutions

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IFAC-PapersOnLine 2024年第10期58卷 37-42页

作者： C. Pasquale S. Sacone S. Siri A. Ferrara Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Italy Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

This paper deals with the optimal control of electric and automated buses that have to follow an intercity line, where some stops are equipped with a flash-charging infrastructure to charge the batteries, while others are not. In order to control these buses, it is necessary to account for the traffic conditions along the roads of the bus line, and to minimize two objectives related to the deviations from the bus timetable and the lack of energy, at the end of the bus trip, with respect to a desired final energy level. The resulting optimal control problem is a multi-objective linear quadratic problem with both continuous and integer variables. In this paper, we propose and apply two methods based on lexicographic ordering aimed at determining the Pareto-optimal solutions of the control problem in twelve scenarios inspired by a real case.

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OCT-Trans: A Novel Transformer Backbone with Multimodal Feature Extraction in OCT-Based Retinal Disease Classification 22

OCT-Trans: A Novel Transformer Backbone with Multimodal Feat...

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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Elsharkawy, Mohamed Abdelhalim, Ibrahim Ghazal, Mohammed Mahmoud, Ali Sandhu, Harpal S. Thanos, Aristomenis El-Baz, Ayman University of Louisville Department of Bioengineering LouisvilleKY United States Abu Dhabi University Electrical and Computer Engineering Department Abu Dhabi United Arab Emirates Legacy Devers Eye Institute PortlandOR United States

ISBN: (纸本)9798331520526

Early detection of retinal diseases is vital for preventing irreversible vision loss. Unlike traditional machine learning (ML) approaches, this study introduces OCT-Trans, an innovative transformer-based backbone that significantly enhances the performance of ML classifiers in analyzing Optical Coherence Tomography (OCT) images. OCT-Trans demonstrates superior capability in distinguishing between normal retinas, Diabetic Retinopathy (DR), and Age-related Macular Degeneration (AMD). Our approach integrates multimodal features from OCT images acquired using two distinct imaging devices, thereby enhancing both generalizability and reproducibility. First, using an atlas-based method, we automatically segment OCT images into eleven retinal layers, extracting clinically relevant features that mimic ophthalmologists' diagnostics to get a final diagnosis. By examining each layer, our approach identifies critical indicators of DR and AMD such as the percentage of subretinal and sub-RPE fluid accumulation, abnormal tissue presence, and missing OCT layers. Additionally, we enrich our feature set by analyzing morphological and texture characteristics like estimating layer curvature, thickness, and reflectivity. All extracted features are integrated and fed into OCT-Trans, which utilizes a transformer architecture tailored for complex multimodal data. This innovative framework generates contextual embeddings that are subsequently classified using a multilayer perceptron. In a comprehensive evaluation involving 541 patients, OCT-Trans achieved remarkable results, with an accuracy of 96.68%, a Cohen's Kappa of 94.07%, and an F1 Score of 96.12%, significantly outperforming current state-of-the-art methods. Statistical analysis using Wilcoxon signed-rank tests confirmed significant enhancements (p © 2025 IEEE.

关键词： Image enhancement

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ConvNeXt Model for Breast Cancer Image Classification 6

ConvNeXt Model for Breast Cancer Image Classification

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Setiawan, Devin Karnyoto, Andrea Stevens Intan, Indo Pardamean, Bens Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifies the process of analyzing, providing objective and accurate results. By leveraging machine learning algorithms and computer vision techniques, we developed breast cancer detection. The dataset is histopathology dataset from BreakHis and UNHAS Hospital. We chose the ConvNeXt-Tiny model then modified the classifier head as the proposed method. Before the dataset is processed by the model, we augment the images by applying random horizontal and vertical flips, adjustments to brightness, contrast, saturation, and hue using color jitter. The augmentation process simulates real-world variance and enhances the model's ability to generalize to unseen data. Our proposed model gained better performance (accuracy, F1-Score) results compared two other techniques to VGG16 and SVM. According to our experiments, the F1-Score for the ConvNeXt-Tiny model with classifier head modification is higher at 0.9516, than the gain for VGG16 at 0.9292, and the gain for the SVM at 0.83. © 2024 IEEE.

关键词： Lung cancer

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Mini Prototype of the Futuristic Bin with an Automatic Waste Sortation System for Managing the Garbage Problems in Society 10

Mini Prototype of the Futuristic Bin with an Automatic Waste...

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10th International Conference on Wireless and Telematics, ICWT 2024

作者： Putra, Muhammad Taufik Dwi Adiwilaga, Anugrah Munggaran, Jezzy Putra Adhitama, Muhammad Azka As'ad, Raihan Anwar Alhafidz, Ahmad Ali Nurmalasari, Rin Rin Juhana, Agus Universitas Pendidikan Indonesia Computer Engineering Study Program Bandung Indonesia UIN Sunan Gunung Djati Department of Electrical Engineering Bandung Indonesia Universitas Pendidikan Indonesia Multimedia Education Study Program Bandung Indonesia

ISBN: (纸本)9798350377057

This article explores the development and implementation of futuristic bins with automated waste sortation systems to address improper and mixed waste disposal challenges. Despite the existence of categorized waste bins, individuals often dispose of waste improperly, hindering the sorting and decomposition processes. Integrating advanced technologies, such as Artificial Intelligence (AI), futuristic bins offer innovative solutions. Futuristic bins with automated sorting systems facilitate accurate waste sorting, reduce mixing, and optimize waste disposal. These bins increase efficiency, reduce costs, and optimize collection routes while promoting environmental cleanliness and awareness of waste management. The article describes the research methodology, including preliminary study, specification requirements analysis, prototype development, and testing. The results demonstrate the implemented system's accuracy and real-time object detection capabilities. The study also acknowledges limitations and suggests future research directions, including improving communication between object detection algorithms and microcontrollers. Overall, the development of futuristic bins with automated waste sortation systems represents a significant advancement in waste management, with the potential to revolutionize waste management systems and create sustainable cities and communities. © 2024 IEEE.

关键词： Waste disposal

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