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2024 International Conference on Smart Systems for Applications in electrical Sciences, ICSSES 2024

作者： Shoba, L.K. Maruthukannan, B. Venkataraman, N.L. Chandrakala, D. Mohankumar, N. Malathi, N. Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chenagalpattu Tamil Nadu Chennai India NPR College of Engineering & Technology Department of Computer Science and Engineering Tamil Nadu Dindigul India J.J.College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Tiruchirappalli India Easwari Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Maharashtra Nagpur India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364040

Cardiovascular rehabilitation is essential for illness prevention and management. A unique method for cardiovascular rehabilitation uses cloud computing and recurrent neural networks (RNNs) to dynamically create personalized workout regimens. Traditional rehabilitation plans lack flexibility and are less successful. The suggested system analyses real-time physiological data and adapts workout regimens in the cloud using RNNs. Heart rate, blood pressure, and physical activity are monitored using wearable sensors. These gadgets smoothly send data to the cloud, where a powerful RNN model processes it. The RNN adapts workout suggestions to the user's physiological reactions, historical data, and health objectives. The cloud-based system, which effectively processes sizable datasets and accommodates expanding user bases, ensures scalability. Remote access to rehabilitation services allows healthcare practitioners to monitor patients and alter workout routines remotely. The personalized approach tailors therapies to each person's health profile to promote adherence and rehabilitation results. The suggested dynamic cardiovascular rehabilitation system uses cloud computing and powerful machine learning to build adaptive, personalized workout regimens, revolutionizing rehabilitation. This technique may improve cardiovascular rehabilitation plans, improving long-term health outcomes for at-risk or recovering cardiovascular disease patients. © 2024 IEEE.

关键词： Recurrent neural networks

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A Comparative Analysis of Wavelet and Fourier Transform for Image Fusion 15

A Comparative Analysis of Wavelet and Fourier Transform for ...

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Kuppuraj, T. Saini, Ramesh Jayadurga, R. Aggarwal, Diksha Eti, Muktha Birare, Komal M. Karpagam Academy of Higher Education Department of Computer Applications Coimbatore India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Business Administration Chennai India Quantum University Research Center Quantum University India School of Engineering and Technology Electrical and Electronics Engineering Karnataka Bangalore India Vishwakarma Institute of Technology Department of Information Technology Pune India

ISBN: (纸本)9798350370249

The purposes of image fusion are to acquire a comprehensive picture which can show extra unique visual facts while compared to its original person supply pix. On this regard, a comparative evaluation of Fourier remodel (feet) and Wavelet transform (WT) for photo fusion is proposed. Firstly, a wavelet-based totally fusion method is advanced using Discrete Wavelet transform (DWT) followed by singular fee decomposition (SVD). The proposed approach uses a pair of images which includes low-pass and high-skip images, with which the fusion method is completed. Then again, a feet-primarily based fusion technique is advanced through making use of the 2d-ft at the pair of snap shots after which performing SVD on them. Secondly, each fusion algorithms are applied on a set of pictures which will compare the overall performance. In the end, several metrics together with PSNR (peak signal-to-Noise Ratio), SSIM (Structural Similarity Index) and EN (Entropy) are used to assess the fusion performance in terms of each objective and subjective criteria. The received effects virtually display that the wavelet-based totally fusion method is greater green for photograph fusion in comparison to that primarily based at the toes. The better overall performance is attributed to the better © 2024 IEEE.

关键词： Comparison Fusion Greater Performance Photograph Similarity

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Heterogeneous Integration of Lithium Niobate and Silicon Photonics for Nonlinear Optics

Heterogeneous Integration of Lithium Niobate and Silicon Pho...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Palici, Alexandra Maria Lu, Xiyuan Srinivasan, Kartik Lu, Xinda Labbe, Fabien Ding, Yunhong Laroque, Hugo Hamerly, Ryan Errando-Herranz, Carlos Pu, Minhao Englund, Dirk Heuck, Mikkel Department of Electrical and Photonics Engineering Technical University of Denmark Lyngby2800 Denmark Microsystems and Nanotechnology Division Physical Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Joint Quantum Institute NIST University of Maryland College ParkMD20742 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands

We demonstrate a hybrid device consisting of a thin film lithium niobate membrane transfer-printed onto a silicon nitride ring resonator. We measure quality factors in the 105 range at telecom wavelengths. CLEO 2024 &... 详细信息

ISBN: (纸本)9781957171395

关键词： Silicon nitride

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Successive Cancellation Sampling Decoder: An Attempt to Analyze List Decoding Theoretically

arXiv

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arXiv 2024年

作者： Wang, Hsin-Po Guruswami, Venkatesan Department of Electrical Engineering and Computer Science Simons Institute The Theory of Computing University of California Berkeley BerkeleyCA United States

Successive cancellation list (SCL) decoders of polar codes excel in practical performance but pose challenges for theoretical analysis. Existing works either limit their scope to erasure channels or address general channels without taking advantage of soft information. In this paper, we propose the successive cancellation sampling (SCS) decoder. SCS hires iid "agents" to sample codewords using posterior probabilities. This makes it fully parallel and amenable for some theoretical analysis. As an example, when comparing SCS with a agents to any list decoder with list size , we can prove that the error probability of the former is at most /ae more than that of the latter. In this paper, we also describe how to adjust the "temperature" of agents. Warmer agents are less likely to sample the same codewords and hence can further reduce error probability. Copyright © 2024, The Authors. All rights reserved.

关键词： Decoding

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Carrying Out CNN Channel Pruning in a White Box

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IEEE Transactions on Neural Networks and Learning Systems 2023年第10期34卷 7946-7955页

作者： Zhang, Yuxin Lin, Mingbao Lin, Chia-Wen Chen, Jie Wu, Yongjian Tian, Yonghong Ji, Rongrong Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen361005 China Youtu Laboratory Tencent Shanghai200233 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu30013 Taiwan Peng Cheng Laboratory Shenzhen518000 China Peking University Department of Computer Science and Technology Beijing100871 China School of Informatics and the Institute of Artificial Intelligence Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence Xiamen361005 China

Channel pruning has been long studied to compress convolutional neural networks (CNNs), which significantly reduces the overall computation. Prior works implement channel pruning in an unexplainable manner, which tends to reduce the final classification errors while failing to consider the internal influence of each channel. In this article, we conduct channel pruning in a white box. Through deep visualization of feature maps activated by different channels, we observe that different channels have a varying contribution to different categories in image classification. Inspired by this, we choose to preserve channels contributing to most categories. Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner with respect to the input image's category. On the basis of the learned class-wise mask, we perform a global voting mechanism to remove channels with less category discrimination. Lastly, a fine-tuning process is conducted to recover the performance of the pruned model. To our best knowledge, it is the first time that CNN interpretability theory is considered to guide channel pruning. Extensive experiments on representative image classification tasks demonstrate the superiority of our White-Box over many state-of-the-arts (SOTAs). For instance, on CIFAR-10, it reduces 65.23% floating point operations per seconds (FLOPs) with even 0.62% accuracy improvement for ResNet-110. On ILSVRC-2012, White-Box achieves a 45.6% FLOP reduction with only a small loss of 0.83% in the top-1 accuracy for ResNet-50. Code is available at https://***/zyxxμWhite-Box. © 2012 IEEE.

关键词： Visualization

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Calibrating Practical Privacy Risks for Differentially Private Machine Learning

Calibrating Practical Privacy Risks for Differentially Priva...

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IEEE International Conference on Big Data

作者： Yuechun Gu Keke Chen Trustworthy and Intelligent Computing Lab Computer Science and Electrical Engineering Cybersecurity Institute University of Maryland Baltimore County Baltimore USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Differential privacy quantifies privacy through the privacy budget , yet its practical interpretation is complicated by variations across models and datasets. Recent research on differentially private machine learning and membership inference has highlighted that with the same theoretical setting, the likelihood-ratio-based membership inference (LiRA) attack success rate (ASR) may vary according to specific datasets and models, which might be a better indicator for evaluating real-world privacy risks. Inspired by this practical privacy measure, we study the positive correlation between the setting and ASR. We also find that for a specific dataset and a specific task we can lower the attack success rate by modifying the dataset. As a result, we may enable flexible privacy budget settings in model training. One dataset modification strategy is selectively suppressing privacy-sensitive features without significantly damaging application-specific data utility. We use the SHAP (or LIME) model explainer to evaluate features’ privacy sensitivity and utility importance and develop an optimized feature-masking algorithm. We have conducted extensive experiments to show (1) the inherent link between ASR and the dataset’s privacy risk in terms of a specific modeling task; (2) By carefully selecting features to mask, we can preserve more data utility with equivalent practical privacy protection and relaxed settings. The implementation details are shared online at https://***/RhincodonE/On-sensitive-features-and-empirical-epsilon-lower-bounds.

关键词： Training Data privacy Privacy Differential privacy Sensitivity Correlation Machine learning Big Data Data models Protection

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Development of an Analytical quantum Full-Wave Solution for a Transmon Qubit in a 3D Cavity

Development of an Analytical Quantum Full-Wave Solution for ...

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European Conference on Antennas and Propagation, EuCAP

作者： Soomin Moon Thomas E. Roth Elmore Family School of Electrical and Computer Engineering West Lafayette Indiana USA Purdue Quantum Science and Engineering Institute West Lafayette Indiana USA

Circuit quantum electrodynamics is one of the most promising platforms for building quantum information processors. To meet the stringent performance requirements, high-fidelity general-purpose numerical methods are increasingly needed to improve designs. Currently, there exist a limited number of methods for analyzing these systems and they suffer from problematic efficiency limitations. One challenge in developing more efficient methods is the lack of available reference data that can be generated to validate them. Here, we develop an analytical quantum full-wave solution for a transmon qubit in a 3D cavity that can validate numerical methods in the future. We start by reviewing the basics of the field-based quantization method used before showing how classical electromagnetic theories can be used to analytically evaluate all field-based parameters in our formulation. We validate our analytical solution by calculating experimentally-relevant system parameters and comparing against approaches that use numerical EM eigenmodes in their solution.

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Integrating Cloud computing and Naive Bayes for Precision Detection and Classification of Sheet and Rill Erosion in Agriculture 2

Integrating Cloud Computing and Naive Bayes for Precision De...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Deshpande, Ashish Govindrao Raman, Ramakrishnan Vekariya, Vipul Mishra, Nilamadhab Arumugam, Sundaram Srinivasan, C. Pune Maharashtra Pune India Symbiosis Institute of Business Management Pune Maharashtra Pune India Parul Institute of Engineering and Technology Parul University Faculty of Engineering and Technology Gujarat Vadodara India Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh India Navajo Technical University Department of Electrical Engineering Crown pointNM United States Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350368413

Sustainable agriculture has significant challenges from sheet and rill erosion for effective techniques. A new way to accurately identify and classifier sheet and rill erosion in agricultural landscapes with the combination of cloud computing and Naïve Bayes. To differentiate between these erosion patterns work proposes a technique that uses ground truth data and high-resolution satellite images. The technique gets results by using the Naïve Bayes algorithm, which is famous for being simple and successful in classification problems. More efficient and accurate and advanced methods by conducting comprehensive experiments and validations. This technology takes use of the scalability and accessibility of cloud computing to conduct erosion risk assessments in real-time, providing agricultural stakeholders with valuable information to enhance soil conservation initiatives. It highlights the revolutionary power of new technology to improve agricultural land management methods and address environmental issues. Sustainable agricultural practices mitigate the adverse implications of soil erosion by offering exact detection and classification of erosion events, which lead to better informed decision-making. © 2024 IEEE.

关键词： Environmental Monitoring Erosion Risk Assessment Ground Truth Data Land Management Satellite Imagery Soil Conservation Sustainable Agriculture

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Exact quantum Sensing Limits for Bosonic Dephasing Channels

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PRX quantum 2024年第2期5卷 020354-020354页

作者： Zixin Huang Ludovico Lami Mark M. Wilde School of Mathematical and Physical Sciences Centre for Quantum Software and Information Faculty of Engineering and Information Technology Science Park 123 Amsterdam 1098 XG the Netherlands Korteweg–de Vries Institute for Mathematics Institute for Theoretical Physics School of Electrical and Computer Engineering

Dephasing is a prominent noise mechanism that afflicts quantum information carriers, and it is one of the main challenges toward realizing useful quantum computation, communication, and sensing. Here, we consider discrimination and estimation of bosonic dephasing channels, when using the most general adaptive strategies allowed by quantum mechanics. We reduce these difficult quantum problems to simple classical ones based on the probability densities defining the bosonic dephasing channels. By doing so, we rigorously establish the optimal performance of various distinguishability and estimation tasks and construct explicit strategies to achieve this performance. To the best of our knowledge, this is the first example of a non-Gaussian bosonic channel for which there are exact solutions for these tasks.

关键词： Non-gaussian quantum states quantum channels quantum fluctuations & noise quantum information theory quantum parameter estimation quantum sensing

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Heterogeneous Integration of Lithium Niobate and Silicon Photonics for Nonlinear Optics

Heterogeneous Integration of Lithium Niobate and Silicon Pho...

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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Silicon photonics

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