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Integrated preparation and manipulation of high‑dimensional flying structured photons

eLight 2024年第1期4卷 185-192页

作者： Haoqi Zhao Yichi Zhang Zihe Gao Jieun Yim Shuang Wu Natalia MLitchinitser Li Ge Liang Feng Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA 19104USA Department of Materials Science and Engineering University of PennsylvaniaPhiladelphiaPA 19104USA Department of Electrical and Computer Engineering and Department of Physics Duke UniversityDurhamNC 27708USA Department of Engineering Science and Physics College of Staten IslandCUNYStaten IslandNY 10314USA The Graduate Center CUNYNew YorkNY 10016USA

The hope for a futuristic global quantum internet that provides robust and high-capacity quantum information transfer lies largely on qudits,the fundamental quantum information carriers prepared in high-dimensional superposition ***,preparing and manipulating N-dimensional flying qudits as well as subsequently establishing their entanglement are still challenging tasks,which require precise and simultaneous maneuver of 2(N-1)parameters across multiple degrees of ***,using an integrated approach,we explore the synergy from two degrees of freedom of light,spatial mode and polarization,to generate,encode,and manipulate flying structured photons and their formed qudits in a four-dimensional Hilbert space with high quantum fidelity,intrinsically enabling enhanced noise resilience and higher quantum data *** four eigen spin–orbit modes of our qudits possess identical spatial–temporal characteristics in terms of intensity distribution and group velocity,thereby preserving long-haul coherence within the entirety of the quantum data transmission *** leveraging the bi-photon entanglement,which is well preserved in the integrated manipulation process,we present versatile spin–orbit cluster states in an extensive dimensional Hilbert *** cluster states hold the promise for quantum error correction which can further bolster the channel robustness in long-range quantum communication.

关键词： cluster thereby preparing

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Deep RL-based Volt-VAR Control and Attack Resiliency for DER-integrated Distribution Grids

Deep RL-based Volt-VAR Control and Attack Resiliency for DER...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Kumar, Kundan Ravikumar, Gelli Iowa State University Department of Computer Science and Electrical and Computer Engineering IA50010 United States

ISBN: (纸本)9798350313604

Integrating distributed energy resources (DERs) into a power system requires more advanced control mechanisms. One of the control strategies used for Volt-VAR control (VVC) is to manage voltage and reactive power. With the increase in the complexity of the power system, there is a need to develop an autonomous and robust control mechanism using deep reinforcement learning (DRL) to enhance grid performance and adjust voltage and reactive power settings. These adjustments minimize losses and enhance voltage stability in the grid. In this paper, we proposed a novel approach to develop a DRL-based VVC framework and mitigation techniques to protect against stealthy white-box attacks targeting the trained control policies of the DRL model. The mitigation technique on the trained DRL is proposed to control the voltage violations on the smart grid to enhance the stability of the grid and minimize voltage irregularities. Our proposed mitigation technique provided better control policies for DRL-based VVC, successfully mitigating 100 percent of voltage violations in the smart grid environment. The results show that the mitigation technique enhances the security and robustness of trained DRL VVC agents. © 2024 IEEE.

关键词： Reinforcement learning

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Direct Edge-To-Edge Local-Learning-Assisted Model-Based Transfer Learning

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IEEE Internet of Things Journal 2024年第11期11卷 20223-20235页

作者： Huang, Zih-Syuan Lu, Ching-Hu Hwang, I-Shyan Hsinchu308 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Yuan-Ze University Department of Computer Science and Engineering Taoyuan320 Taiwan

With the gradual advancement of technology in the production of consumer goods, the Internet of Things (IoT) systems have experienced rapid development, resulting in a massive amount of data that can be processed using deep neural networks. However, annotating the data and training the models require significant manpower, time, and computational resources. Transfer learning can address this problem. Traditional systems rely on centralized servers for transfer learning. Although several studies have proposed distributed systems for direct edge-To-edge (e2e) instance-based and feature-based transfer learning, they neglect model-based transfer learning (MTL) within the same domain. This leads to lower learning efficiency, lower privacy protection, and higher transmission costs. Therefore, our study proposes direct e2e local-learning-Assisted MTL for a direct e2e many-To-many MTL scenario. The method can transfer model structures and weights between distributed devices without relying on powerful centralized servers. The effectiveness of the proposed approach is demonstrated by applying it to various scenarios. © 2014 IEEE.

关键词： Feature extraction

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Effectiveness of Almost Sub Frame Approach as Inter Cell Interference Management in LTE-A Macro - Pico Scenario 9

Effectiveness of Almost Sub Frame Approach as Inter Cell Int...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Jember, Kehali A. Abose, Tadele A. Kassahun, Ermias Madhav, T. Venu Adama Science And Technology University Department Electronics And Communication Engineering Adama Ethiopia Mettu University Department Electrical And Computer Engineering Ethiopia Gondar University Department Electrical And Computer Engineering Gondar Ethiopia

ISBN: (纸本)9798350394474

Heterogeneous networks are promising solutions for enhancing network performance of LTE-A mobile networks by deploying small cells within the area of the serving macro cells. The goal of deploying such networks is to offload data from the congested macro cells towards the small cells. However, cross tier interference is a serious issue, which is introduced due to the transmitted power difference between Macro cell node and small cell node. Hence, cell age users are mainly affected by high power interference originated from Macro node. The paper develops enhanced inter-cell interference coordination using Almost Blank Sub-Frame (ABS) to improve user throughput. This can be achieved by stopping data transmission on in certain sub frame of macro cell while Pico users are scheduled at the same frame. computer simulation results depict that the performance of Pico cell users is highly degraded, especially for cell edge users. The ABS technique improves cell edge user throughput of Pico cell by 95% and center cell user throughput by 75.25%. © 2024 IEEE.

关键词： Heterogeneous networks

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SHPIA 2.0: An Easily Scalable, Low-Cost, Multi-purpose Smart Home Platform for Intelligent Applications

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SN computer science 2024年第1期5卷 42页

作者： Demrozi, Florenc Turetta, Cristian Pravadelli, Graziano Department of Electrical Engineering and Computer Science University of Stavanger Stavanger Norway Department of Engineering for Innovation Medicine University of Verona Verona Italy

Sensors, electronic devices, and smart systems have invaded the market and our daily lives. As a result, their utility in smart home contexts to improve the quality of life, especially for the elderly and people with special needs, is getting stronger and stronger. Therefore, many systems based on smart applications and intelligent devices have been developed, for example, to monitor people’s environmental contexts, help in daily-life activities, and analyze their health status. However, most existing solutions have drawbacks related to accessibility and usability. They tend to be expensive and lack generality and interoperability. These solutions are not easily scalable and are typically designed for specific constrained scenarios. This paper tackles such drawbacks by presenting SHPIA 2.0, an easily scalable, low-cost, multi-purpose smart home platform for intelligent applications. It leverages low-cost Bluetooth Low Energy (BLE) devices featuring both BLE connected and BLE broadcast modes, to transform common objects of daily life into smart objects. Moreover, SHPIA 2.0 allows the collection and automatic labeling of different data types to provide indoor monitoring and assistance. Specifically, SHPIA 2.0 is designed to be adaptable to different home-based application scenarios, including human activity recognition, coaching systems, and occupancy detection and counting. The SHPIA platform is open source and freely available to the scientific community, fostering collaboration and innovation. © 2023, The Author(s).

关键词： Automatic data annotation Automatic data collection BLE broadcast mode BLE connected mode Human activity recognition Smart home platform

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Analysis of Signal Propagations Between an Access Point and IoT Devices in a Complex Indoor Environment Using Ray Tracing

Analysis of Signal Propagations Between an Access Point and ...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Kaur, Kanwalinderjit Zavala, Priscilla California State University Department of Computer & Electrical Engineering & Computer Science BakersfieldCA United States

ISBN: (纸本)9798350364910

The fifth generation (5G) of wireless communication networks uses the advantages of Massive Multiple-Input Multiple-Output (MIMO) technologies to improve network coverage, increase data speeds, and enhance reliability. One of the challenges that has risen from utilizing massive MIMO as a leading technology in the advancement of 5G is the difficulty to model massive MIMO channels due to the high cost of the hardware and the computational complexity. In this research, ray tracing, which is an effective channel modeling method, is employed using the MIMO- Orthogonal frequency division multiplexing (OFDM) technique to simulate the interactions between various IoT devices and the network's access point. The ray tracing evaluation is performed on a 3D model of a conference room which allows for the evaluation of the network's performance in a complex indoor environment. The experiments are run using different surface materials and channel parameters are measured for each experiment to understand the different factors that affect the performance. The power delay and the path loss for an IoT device in the line of sight (LOS) and an IoT device not in LOS are analyzed. The magnitude of the signals propagated to an IoT device in LOS are higher and the path loss is lower. Furthermore, using metal as the surface material results in the least amount of path loss, and using wood results in the highest amount of path loss. The bit error rates when metal, glass, and wood are used are also measured. The use of metal results in the lowest bit error rates and wood results in the highest bit error rates for the IoT devices. © 2024 IEEE.

关键词： Bit error rate

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Design and Analysis of a UWB Slotted Vivaldi Antenna for Microwave Imaging Applications

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IEIE Transactions on Smart Processing and Computing 2023年第4期12卷 350-357页

作者： Paul, Liton Chandra Majumder, Akash Rani, Tithi Hossain, Md. Najmul Rahim, Md. Abdur Shin, Jungpil Yun, Keun Soo Department of Electrical Electronic and Communication Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh Department of Electronics & Telecommunication Engineering Faculty of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh School of Computer Science and Engineering The University of Aizu / Fukushima Aizuwakamatsu965-8580 Japan School of Computer and Information Technology Ulsan College / Dong-gu Ulsan44610 Korea Republic of

An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3 in size. The proposed compact Vivaldi antenna showed good radiation characteristics and spanned an ultra-wide bandwidth of 10 GHz, ranging from 3.6 to 13.6 GHz, using a microstrip line feed with a radial stub, tapered slots, and resonant cavities. After analyzing the simulation findings, the proposed compact slotted UWB Vivaldi antenna was compared with the basic Vivaldi antenna. The maximum gain and efficiency were 7.35 dB and 82%, respectively. The antenna was simulated in the time domain using the computer simulation technology (CST) microwave studio. The frequency domain solver was also used for cross-validation, and the results were equally good. In conclusion, the proposed compact Vivaldi antenna is a good option for microwave imaging applications. © 2023 The Institute of Electronics and Information Engineers.

关键词： Cavity resonators

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A Self-Labeling Method for Adaptive Machine Learning by Interactive Causality

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2093-2102页

作者： Ren, Yutian Yen, Aaron Haohua Li, Guann-Pyng University of California Irvine Department of Electrical Engineering and Computer Science The California Institute for Telecommunications and Information Technology IrvineCA92697 United States

Learning from unlabeled data or self-learning, can substantially reduce the complexity of machine learning (ML) utilization in real-time deployment. While the development of un/semisupervised algorithms shows promising results in learning with reduced labels, the fundamental assumption of data smoothness restricts its scope of application, especially with nonstationary data distributions in different domains. Leveraging transdomain invariant causal relationships, causality has recently been employed to foster robust ML. In this article, we have developed a generic method for self-labeling data that relies on known causality among interactive objects and learned temporal relations among causal events for identifying and associating labels and input data. The causal time-interval between asynchronous cause and effect events is studied to achieve self-labeling. We utilize dynamical system theory in a 1-d setting to demonstrate that our proposed method outperforms traditional feature similarity-based semisupervised learning. A computer simulation experiment was conducted to generate high-dimensional data, and the comprehensive results reveal the potential of learning adaptation in dynamic environments to improve ML robustness against shifts in data distribution. © 2023 IEEE.

关键词： Timing circuits

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Generalized hybrid LiFi-WiFi UniPHY learning framework towards intelligent UAV-based indoor networks

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International Journal of Intelligent Networks 2024年第1期5卷 255-266页

作者： Ahmad, Rizwana Anwar, Dil Nashin Bany Salameh, Haythem Elgala, Hany Ayyash, Moussa Almajali, Sufyan El-Khazali, Reyad Electronic and Electrical Engineering Department University of Cambridge United Kingdom Electrical and Computer Engineering Department University at Albany-State University of New York United States Artificial Intelligence Research Center Al Ain University Al Ain United Arab Emirates Telecommunications Engineering Department Yarmouk University Irbid Jordan Department of Computing Information and Technology Chicago State University ChicagoIL United States Department of Computer Science Princess Sumaya University for Technology Amman Jordan Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi United Arab Emirates

Advancements in unmanned aerial vehicle (UAV) technology, along with indoor hybrid LiFi-WiFi networks (HLWN), promise the development of cost-effective, energy-efficient, adaptable, reliable, rapid, and on-demand HLWN-capable indoor flying networks (IFNs). To achieve this, a unified physical layer (UniPHY) capable of simultaneous control communication, data transfer, and sensing is crucial. However, traditional block-based decoders, designed independently for LiFi and WiFi, perform poorly in complex and hybrid LiFi-WiFi-enabled UniPHY systems. In this study, we propose an end-to-end learning framework based on convolutional neural networks (CNNs) for UniPHY, which can be trained to serve hybrid LiFi-WiFi transmissions to improve error performance and simplify UAV hardware. In this work, the performance of the proposed framework is assessed and compared with that of the conventional independent block-based communication system. Furthermore, a comprehensive summary of optimal hyper-parameters for efficient training of our learning framework has been provided. It is shown that, with optimal hyper-parameters, the proposed CNN-based framework outperforms the conventional block-based approach by providing a signal-to-noise ratio gain of approximately 7 dB for the LiFi channel and 23 dB for the WiFi channel. In addition, we evaluate the complexity and training convergence for loss and accuracy. © 2024 The Authors

关键词： Data transfer

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Stable, deep blue tandem phosphorescent organic light-emitting diode enabled by the double-sided polariton-enhanced Purcell effect

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Nature Photonics 2025年第6期19卷 607-614页

作者： Zhao, Haonan Arneson, Claire E. Forrest, Stephen R. Department of Physics University of Michigan Ann ArborMI United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States Department of Materials Science and Engineering University of Michigan Ann ArborMI United States

Blue phosphorescent organic light-emitting diodes (PHOLEDs) are highly efficient, although their short operational lifetimes have limited their commercial acceptance in displays and lighting. A high density of energetic triplet excitons accumulates in the emission layer that eventually annihilate, leading to molecular degradation. Here we report long operational lifetime, efficient and deep blue tandem PHOLEDs using the polariton-enhanced Purcell (PEP) effect at both the diode cathode and anode. The Pt- and Ir-complex-based bottom-emitting tandem PEP-PHOLEDs show a tenfold increase in lifetime and colour saturation compared with their analogous single-junction PHOLEDs. Particularly, the Pt-complex-based tandem PEP-PHOLED on flat glass substrates has lifetimes of LT90 = 830 ± 30 h and 1,800 ± 100 h (LT90 = the time to reach 90% of the initial luminance of 500 cd m−2), and forward-viewing external quantum efficiencies of 36.8 ± 0.5% or 56.0 ± 1.0% without or with substrate light extraction, respectively. The lifetime enhancement is equivalent to 250 times that of conventional single-junction Ir-based PHOLED lifetimes with similar blue chromaticity coordinates. The tandem PEP-PHOLED has chromaticity coordinates of CIExy = (0.14, 0.12) and a marginally perceptible colour shift with viewing angle up to ±75°. The double-sided PEP effect is readily integrated with other established lifetime-extending technologies, allowing for a multiplicative increase in lifetime. To our knowledge, this is the first demonstration of a deep blue PHOLED that shows stability comparable to green PHOLEDs, accelerating the use of the deep blue phosphorescent emitters in power-efficient displays and lighting. © The Author(s), under exclusive licence to Springer Nature Limited 2025.

关键词： Organic light emitting diodes (OLED)

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