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2023 International Conference on electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Tufail, Shahid Tariq, Mohd Batool, Shanzeh Sarwat, Arif Florida International University Electrical and Computer Engineering Miami United States Vellore Institute of Technology School of Computing Science Bhopal India

ISBN: (纸本)9798350322972

This paper compares the accuracy of energy prediction using Feedforward Neural Networks (FNN) with a hybrid Convolutional Neural Network- Long Short-Term Memory (CNN-LSTM) approach. The research builds two models, a FNN and a CNN-LSTM, and tests them on a large dataset of energy usage records. To extract local data and preserve long-range temporal relationships, the CNN-LSTM model draws on the best of convolutional and recurrent neural networks. Metrics like mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE) are used to compare the two models' efficacy. The CNN-LSTM model shows superior accuracy and generalization capabilities over the FNN model when predicting energy usage. These results have the potential to improve energy management system accuracy and reliability, which in turn can increase building energy efficiency and sustainability. © 2023 IEEE.

关键词： Energy efficiency

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Single-Photon Source in Silicon Nitride Photonics for quantum Key Distribution

Single-Photon Source in Silicon Nitride Photonics for Quantu...

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2024 Laser Science, LS 2024

作者： Senichev, Alexander Martin, Zachariah O. Peana, Samuel Lagutchev, Alexei S. Boltasseva, Alexandra Shalaev, Vladimir M. School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Oak RidgeTN37931 United States

We present an evaluation of quantum emitters formed at the interface of nitrogen-rich silicon nitride and silicon dioxide, demonstrating their potential as single-photon sources for quantum photonic applications, focu... 详细信息

关键词： Silicon nitride

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Acceptor-Induced Bulk Dielectric Loss in Superconducting Circuits on Silicon

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Physical Review X 2024年第4期14卷 041022页

作者： Zi-Huai Zhang Kadircan Godeneli Justin He Mutasem Odeh Haoxin Zhou Srujan Meesala Alp Sipahigil Department of Electrical Engineering and Computer Sciences Materials Sciences Division Department of Physics Institute for Quantum Information and Matter

The performance of superconducting quantum circuits is primarily limited by dielectric loss due to interactions with two-level systems (TLSs). State-of-the-art circuits with engineered material interfaces are approaching a limit where dielectric loss from bulk substrates plays an important role. However, a microscopic understanding of dielectric loss in crystalline substrates is still lacking. In this work, we show that boron acceptors in silicon constitute a TLS bath that leads to an energy dissipation channel for superconducting circuits. We discuss how the electronic structure of boron acceptors leads to an effective TLS response in silicon. We sweep the boron concentration in silicon and demonstrate the bulk dielectric loss limit from boron acceptors. We show that boron-induced dielectric loss can be reduced in a magnetic field due to the spin-orbit structure of boron. This work provides the first detailed microscopic description of a TLS bath for superconducting circuits and demonstrates the need for ultrahigh-purity substrates for next-generation superconducting quantum processors.

关键词： quantum engineering Superconducting devices

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Characterizing photon emission from a quantum dot excited by long aboveband pulses

Characterizing photon emission from a quantum dot excited by...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Venuturumilli, S.S. Al Maruf, Rubayet Poole, P.J. Dalacu, D. Reimer, Michael Bajcsy, Michal Department of Electrical and Computer Engineering University of Waterloo WaterlooON Canada Department of Physics and Astronomy University of Waterloo WaterlooON Canada Institute of Quantum Computing University of Waterloo WaterlooON Canada National Research Council Canada OttawaON Canada

We experimentally investigate the quality of single photons produced with longpulse aboveband excitation of a quantum dot embedded in a semiconductor nanowire and model the results via rate equations and Markovchains.... 详细信息

ISBN: (纸本)9781957171258

关键词： Semiconductor quantum dots

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Knowledge-Empowered,Collaborative,and Co-Evolving AI Models:The Post-LLM Roadmap

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工程（英文） 2025年第1期44卷 87-100页

作者： Fei Wu Tao Shen Thomas Bäck Jingyuan Chen Gang Huang Yaochu Jin Kun Kuang Mengze Li Cewu Lu Jiaxu Miao Yongwei Wang Ying Wei Fan Wu Junchi Yan Hongxia Yang Yi Yang Shengyu Zhang Zhou Zhao Yueting Zhuang Yunhe Pan College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Leiden Institute of Advanced Computer Science Leiden UniversityLeiden 2333 CCNetherlands College of Electrical Engineering Zhejiang UniversityHangzhou 310027China School of Engineering Westlake UniversityHangzhou 310024China Department of Computer Science and Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Cyber Science and Technology Sun Yat-Sen UniversityShenzhen 518107China Department of Computing The Hong Kong Polytechnic UniversityHong Kong 999077China

Large language models(LLMs)have significantly advanced artificial intelligence(AI)by excelling in tasks such as understanding,generation,and reasoning across multiple *** these achieve-ments,LLMs have inherent limitations including outdated information,hallucinations,inefficiency,lack of interpretability,and challenges in domain-specific *** address these issues,this survey explores three promising directions in the post-LLM era:knowledge empowerment,model collaboration,and model ***,we examine methods of integrating external knowledge into LLMs to enhance factual accuracy,reasoning capabilities,and interpretability,including incorporating knowledge into training objectives,instruction tuning,retrieval-augmented inference,and knowledge ***,we discuss model collaboration strategies that leverage the complementary strengths of LLMs and smaller models to improve efficiency and domain-specific performance through techniques such as model merging,functional model collaboration,and knowledge ***,we delve into model co-evolution,in which multiple models collaboratively evolve by sharing knowledge,parameters,and learning strategies to adapt to dynamic environments and tasks,thereby enhancing their adaptability and continual *** illustrate how the integration of these techniques advances AI capabilities in science,engineering,and society—particularly in hypothesis development,problem formulation,problem-solving,and interpretability across various *** conclude by outlining future pathways for further advancement and applications.

关键词： Artificial intelligence Large language models Knowledge empowerment Model collaboration Model co-evolution

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Smart Infant Monitoring System Using computer Vision and AI

Smart Infant Monitoring System Using Computer Vision and AI

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Singh, Gurpreet Shekhar, Abhishek Raj Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

The new era of technology is being greatly influenced by the field of artificial intelligence. computer vision and deep learning have become increasingly important due to their ability to process vast amounts of data and provide insights and solutions in a variety of fields. computer vision, deep learning and signal analysis have been used in a growing number of applications and services including smart devices, image, and speech recognition, healthcare, etc., one such device is an infant monitoring system. It monitors the daily activities of the infant such as their sleeping patterns, sounds, and movements. In this paper, deep learning and computer vision libraries were used to develop algorithms to detect whether the infant was in any uncomfortable situation such as sleeping on its back, face being covered and whether the infant was awake. The smart infant monitoring system detects the infant's unsafe resting situation in real time and sent immediate alerts to the caretaker's device. This paper presents the design flow of a smart infant monitoring system consisting of a night vision camera, a Jetson Nano, and a Wi-Fi internet connection. The pose estimation and awake detection algorithms were developed and tested successfully for different infant resting/sleeping situations. The smart infant monitoring system provides significant benefits for safety and an improved understanding of infants' sleep patterns and behavior. © 2023 IEEE.

关键词： Face recognition

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Progress Towards quantum-Enhanced Microwave Remote Sensing and Communication Applications

Progress Towards Quantum-Enhanced Microwave Remote Sensing a...

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US National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)

作者： Jérôme Bourassa Christopher M. Wilson Qubic Inc. Sherbrooke QC CANADA Institute for Quantum Computing & Department of Electrical and Computer Engineering University of Waterloo ON CANADA

RADAR and communications are vulnerable as noise and interference contaminate the received signals and produce errors limiting their resolution, their accuracy and speed. To answer the growing needs for more reliable and accurate microwave intelligence in an ever more complex electromagnetic environment, there is a growing need to develop innovative microwave sensors with greater signal sensitivity, selectivity and integrity.

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Reversible Tuning of Nanowire quantum Dot to Cesium D1 line

Reversible Tuning of Nanowire Quantum Dot to Cesium D1 line

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Al Maruf, Rubayet Venuturumilli, Sreesh Bharadwaj, Divya Anderson, Paul Qiu, Jiawei Zeeshan, Mohd Semnani, Behrooz Poole, Philip Dalacu, Dan Reimer, Michael Bajcsy, Michal Institute for Quantum Computing University of Waterloo WaterlooON Canada Electrical and Computer Engineering University of Waterloo WaterlooON Canada Dept. of Physics and Astronomy University of Waterloo WaterlooON Canada National Research Council of Canada OttawaON Canada

We report local reversible tuning of nanowire quantum dot emission to cesium D1 line (~ 894.6 nm) and demonstrate slow light and resonant absorption of single photons in hot cesium vapor. © 2023 The Author(s)

ISBN: (纸本)9781957171258

关键词： Nanowires

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The Mutual Information In The Vicinity of Capacity-Achieving Input Distributions

The Mutual Information In The Vicinity of Capacity-Achieving...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Cheng, Hao-Chung Nakiboglu, Baris National Taiwan University Department of Electrical Engineering Graduate Institute of Communication Engineering Department of Mathematics Taipei10617 Taiwan Quantum Computing Centre Taiwan Middle East Technical University Department of Electrical and Electronics Engineering Ankara06800 Turkey

ISBN: (纸本)9781665475549

The mutual information is analyzed as a function of the input distribution using an identity due to Topsoe for channels with (possibly multiple) linear constraints and finite input and output sets. The mutual information is bounded above by a function decreasing quadratically with the distance to the set of all capacity-achieving input distributions for the case when the distance is less than a certain threshold. Explicit expressions for the threshold and the coefficient of the quadratic decrease are derived. A counter-example is provided demonstrating the non-existence of such a quadratic bound in the case of infinitely many linear cost constraints. Implications of these observations for the channel coding problem and applications of the proof technique to related problems are discussed. © 2023 IEEE.

关键词： Information theory

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A Data-Driven Approach based on Dynamic Mode Decomposition for Efficient Encoding of Dynamic Light Fields

A Data-Driven Approach based on Dynamic Mode Decomposition f...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Ravishankar, Joshitha Khaidem, Sally Sharma, Mansi Indian Institute of Technology Madras Department of Electrical Engineering India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350302493

Dynamic light fields provide a richer, more realistic 3D representation of a moving scene. However, this leads to higher data rates since excess storage and transmission requirements are needed. We propose a novel approach to efficiently represent and encode dynamic light field data for display applications based on dynamic mode decomposition (DMD). Acquired images are firstly obtained through optimized coded aperture patterns for each temporal frame/camera viewpoint of a dynamic light field. The underlying spatial, angular, and temporal correlations are effectively exploited by a data-driven DMD on these acquired images arranged as time snapshots. Next, High Efficiency Video Coding (HEVC) removes redundancies in light field data, including intra-frame and inter-frame redundancies, while maintaining high reconstruction quality. The proposed scheme is the first of its kind to treat light field videos as mathematical dynamical systems, leverage on dynamic modes of acquired images, and gain flexible coding at various bitrates. Experimental results demonstrate our scheme's superior compression efficiency and bitrate savings compared to the direct encoding of acquired images using HEVC codec. © 2023 IEEE.

关键词： Dynamic mode decomposition

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