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2nd IEEE International Conference on Data Science and computer Application, ICDSCA 2022

作者： Guo, Yifan Mao, Helen X. Yin, Jijun Mao, Zhi-Hong Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA United States North Allegheny Senior High School WexfordPA United States Department of Electrical and Computer Engineering Department of Bioengineering University of Pittsburgh PittsburghPA United States

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

Data deficiency has long been a major obstacle for many areas of machine learning. Manually labeling data could be utterly time-consuming and expensive, especially in medical fields including the sleep research. To address this challenge, we propose a cluster-then-label strategy, which inserts clustering algorithms into traditional supervised learning pipelines. In this paper, we demonstrate the cluster-then-label strategy for sleep detection using electroencephalogram (EEG) data and show that our proposed strategy can boost the classifier's performance on previously unseen subjects. We also developed a method based on nonlinear transformations that can reshape the feature distributions to resemble normal distributions with which the cluster-then-label algorithm becomes more efficient and robust. © 2022 IEEE.

关键词： Electroencephalography

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Tactile Displays Driven by Projected Light

arXiv

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arXiv 2024年

作者： Linnander, Max Goetz, Dustin Reardon, Gregory Kumar, Vijay Hawkes, Elliot Visell, Yon Department of Mechanical Engineering United States Department of Bioengineering United States Media Arts & Technology Program United States Department of Electrical and Computer Engineering University of California Santa Barbara United States

Tactile displays that lend tangible form to digital content could transform computing interactions. However, achieving the resolution, speed, and dynamic range needed for perceptual fidelity remains challenging. We present a tactile display that directly converts projected light into visible tactile patterns via a photomechanical surface populated with millimeter-scale optotactile pixels. The pixels transduce incident light into mechanical displacements through photostimulated thermal gas expansion, yielding millimeter scale displacements with response times of 2 to 100 milliseconds. Employing projected light for power transmission and addressing renders these displays highly scalable. We demonstrate optically driven displays with up to 1,511 addressable pixels – several times more pixels than any prior tactile display attaining comparable performance. Perceptual studies confirm that these displays can reproduce diverse spatiotemporal tactile patterns with high fidelity. This research establishes a foundation for practical, versatile high-resolution tactile displays driven by light. Copyright © 2024, The Authors. All rights reserved.

关键词： Light transmission

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Automatic LPI Radar Waveform Recognition Using Vision Transformer

Automatic LPI Radar Waveform Recognition Using Vision Transf...

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2023 IEEE International Radar Conference, RADAR 2023

作者： Kim, Junseob Cho, Sunghwan Hwang, Sunil Choi, Yeongyoon Korea Military Academy Department of Electrical Engineering 01805 Korea Republic of Defense Acquisition Program Administration Maneuver System Coordination and Contract Team 13809 Korea Republic of Gist Department of Electrical Engineering and Computer Science 61005 Korea Republic of

ISBN: (纸本)9781665482783

This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at -10dB SNR. © 2023 IEEE.

关键词： Convolutional neural networks

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Filament-free Bulk RRAM with High Endurance and Long Retention for Neuromorphic Few-Shot Learning On-Chip

Filament-free Bulk RRAM with High Endurance and Long Retenti...

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2024 IEEE International Electron Devices Meeting, IEDM 2024

作者： Kumar, Ashwani Zhou, Yucheng Potladurthy, Sai Praneeth Kim, Jeong-Hoon Xu, Weihong Ponzina, Flavio Kim, Seonghyun Cubukcu, Ertugrul Rosing, Tajana Cauwenberghs, Gert Kuzum, Duygu Department of Electrical and Computer Engineering University of California San DiegoCA United States Department of Bioengineering University of California San DiegoCA United States Department of Computer Science University of California San DiegoCA United States Department of NanoEngineering University of California San DiegoCA United States SK Hynix Korea Republic of

ISBN: (纸本)9798350365429

Bulk switching RRAM devices have emerged to address nonidealities of filamentary RRAM for AI at the edge. However, long retention and high endurance needed for continual on-chip learning have yet to be demonstrated. Here, we report a filament-free and multi-level bulk RRAM (b-RRAM) technology with long retention and high endurance. The oxygen vacancy gradient across the TiOx switching layer and Al2O3 tunnel barrier are designed to suppress filament formation and achieve multi-level switching through modulation of oxygen vacancy distribution. Al-Ti-O oxygen barrier enables reliable switching with high uniformity, retention and endurance. We develop a compact model that captures both DC and pulse switching. MΩ-level resistance and switching current nonlinearity allow highly accurate read/write operations and matrix vector multiplications (MVM) in selectorless b-RRAM crossbars. A neuro-inspired few-shot learning (FSL) algorithm based on dendritic computation and behavioral time plasticity (BTSP) is mapped onto b-RRAM crossbar arrays. Weights are continuously updated on-chip to learn shortest navigation to reward within a few trials in a 2D maze. We also present FSL of large-size images with hyperdimensional (HD) computing using our b-RRAM model. System-level simulations with 64-level b-RRAM arrays show an increase in accuracy by 5.9 % and 5.4 % for a 5-way 10-shot learning of CIFAR-100 and CUB-200 datasets as compared to the state-of-the-art FSL-HD. © 2024 IEEE.

关键词： RRAM

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The Effect of Vehicles Speed on the Performance of VANET Protocol 1

The Effect of Vehicles Speed on the Performance of VANET Pro...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Qasim, Osama A. Mahdi, Dania Mohammed Noori, Mohammed S. Ali, Rabei Raad Sari, Christy Atika Rachmawanto, Eko Hari Northern Technical University Department of Computer Engineering Technology Mosul Iraq Uniersiti Tenaga Nasional Department of Electrical and Electronics Engineering Selangor Malaysia University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

At present, ad hoc networks are getting a lot of attention, because they have many features that differ from the rest of the networks and because they are technically advanced. In routing protocols, the Vehicular Ad-hoc network (VANET) differ in performance because each protocol has different variables, such as variable density, speed, and traffic scenarios. In this work, we proposed topology-based routing namely Ad hoc On Demand Distance Vector (AODV) protocol. The AODV protocol has been simulated in case of the movement of vehicles at a fixed velocity at 60km/h, and in case of randomly changing the vehicle's locations in the network. There are three parameters used to investigate the performance of the proposed AODV protocol which are packet delivery ratio, and overheads. The Simulation results show a significant decrease from 0.55 to 0.82 in the packet delivery ratio. On the other hand, the performance of the AODV protocol demonstrates effective communication for the VANETs. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Concealment of secret messages into ordinary images using diffractive processors

Concealment of secret messages into ordinary images using di...

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2024 Frontiers in Optics, FiO 2024

作者： Li, Yuhang Bai, Bijie Lee, Ryan Gan, Tianyi Wang, Yuntian Jarrahi, Mona Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States Computer Science Department University of California Los Angeles90095 United States University of California Los AngelesCA90095 United States

We present an information-hiding camera that conceals secret messages and information into ordinary images, deceiving human perception. These images are securely decoded by a jointly optimized neural network to retrie...

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On the Non-Existence of Immersions for Systems with Multiple Omega-Limit Sets

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IFAC-PapersOnLine 2023年第2期56卷 60-64页

作者： Zexiang Liu Necmiye Ozay Eduardo D. Sontag Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109 USA Department of Electrical and Computer Engineering and Department of Bioengineering Northeastern University Boston MA 02115 USA

Linear immersions (or Koopman eigenmappings) of a nonlinear system have wide applications in prediction and control. In this work, we study the existence of one-to-one linear immersions for nonlinear systems with multiple omega-limit sets. For this class of systems, existing work shows that a discontinuous one-to-one linear immersion may exist, but it is unclear if a continuous one-to-one linear immersion exists. Under mild conditions, we prove that systems with multiple omega-limit sets cannot admit a continuous one-to-one immersion to a class of systems including linear systems. Multiple examples are studied to verify our results.

关键词： Nonlinear Systems Immersion Koopman Operator Equivalent Systems

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Wavelength-multiplexed Multiplane Quantitative Phase Imaging Using Diffractive Visual Processing

Wavelength-multiplexed Multiplane Quantitative Phase Imaging...

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2024 Frontiers in Optics, FiO 2024

作者： Shen, Che-Yung Li, Jingxi Gan, Tianyi Li, Yuhang Bai, Langxing Jarrahi, Mona Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Department of Computer Science University of California Los AngelesCA90095 United States

We present a wavelength-multiplexed diffractive optical processor that can transform the phase profiles of input objects at multiple axial depths into intensity variations at different wavelengths, enabling rapid mult... 详细信息

关键词： Diffractive optics

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Prediction of Internet Broadband Connectivity Classification in West Java Indonesia using Machine Learning

Prediction of Internet Broadband Connectivity Classification...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Kusuma Atmaja, Wahyu Haris Heryadi, Yaya Sonata, Ilvico Lukas Suparta, Wayan Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department West Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Engineering Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

A location's Take-up Rate was significantly influenced by its Internet connectivity and availability. The purpose of this research is to answer concerns about internal Internet Service Provider issues that affect Internet connectivity in clusters of West Java, Indonesia. It also aims to evaluate the results of models that forecast how these internal factors will affect internet connectivity. According to the research findings, the FTTH Cluster has eight significant Internet predictor connectivity out of 18 elements. Activation delay and Administration Documentation of Activation with Connectivity were the two major parameters modeled out of the 18 components. Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree (DT) models were used to predict Internet Broadband Connectivity Classification based on the two most important variables. According to the study, ANN is the best model, with 99% accuracy and 99.6% precision when compared to SVM and DT. Furthermore, it exceeds previous studies that used the ANN model and achieved 97.92% accuracy. © 2023 IEEE.

关键词： Prediction models

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Analyzing Voltage Transients Under Different Stimulation Configurations and Rates in Rat Cortex 46

Analyzing Voltage Transients Under Different Stimulation Con...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Nguyen, Christopher K. Sturgill, Brandon S. Negi, Sandeep Cogan, Stuart F. University of Texas at Dallas Department of Bioengineering RichardsonTX75080 United States Blackrock Neurotech Salt Lake CityUT84108 United States University of Utah Department Electrical and Computer Engineering Salt Lake CityUT84112 United States

ISBN: (纸本)9798350371499

This study introduces a method for measuring the voltage transients (VTs) in different stimulation configurations as a function of stimulation rate. Utilizing a stimulator with two-electrode setup and an isolated input oscilloscope, VTs across monopolar (MP), bipolar (BP), tripolar (TP), and partial tripolar (PTP) stimulation configurations could be measured with a proper reference electrode (Ag|AgCl) without a potentiostat or custom-built stimulator. We tested this methodology with Utah electrode arrays (UEAs) with sputtered iridium oxide film (SIROF) electrodes and amorphous silicon carbide (a-SiC) encapsulation in rat cortex at 24 weeks. Our investigation revealed the impact of quasi-reference electrode (QRE) polarization, which leads to underestimating the chargeinjection capacity - max(Qinj) - for electrode *** Relevance - This research offers advancement in understanding electrode behavior during neural stimulation, emphasizing the importance of protocol optimization for enhanced clinical outcomes in neural stimulation. © 2024 IEEE.

关键词： Silver halides

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