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On the System Performance of Mobile Edge Computing in an Uplink NOMA WSN With a Multiantenna Access Point Over Nakagami-m Fading

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 668-685页

作者： Van-Truong Truong Van Nhan Vo Dac-Binh Ha Chakchai So-In the Faculty of Electrical-Electronic Engineering Duy Tan University the Institute of Research and Development Duy Tan University the Faculty of Information Technology Duy Tan University IEEE the Applied Network Technology(ANT)Laboratory Department of Computer ScienceCollege of ComputingKhon Kaen University

In this paper,we study the system performance of mobile edge computing(MEC)wireless sensor networks(WSNs)using a multiantenna access point(AP)and two sensor clusters based on uplink nonorthogonal multiple access(NOMA).Due to limited computation and energy resources,the cluster heads(CHs)offload their tasks to a multiantenna AP over Nakagami-m *** proposed a combination protocol for NOMA-MEC-WSNs in which the AP selects either selection combining(SC)or maximal ratio combining(MRC)and each cluster selects a CH to participate in the communication process by employing the sensor node(SN)*** derive the closed-form exact expressions of the successful computation probability(SCP)to evaluate the system performance with the latency and energy consumption constraints of the considered *** results are provided to gain insight into the system performance in terms of the SCP based on system parameters such as the number of AP antennas,number of SNs in each cluster,task length,working frequency,offloading ratio,and transmit power ***,to determine the optimal resource parameters,i.e.,the offloading ratio,power allocation of the two CHs,and MEC AP resources,we proposed two algorithms to achieve the best system *** approach reveals that the optimal parameters with different schemes significantly improve SCP compared to other similar *** use Monte Carlo simulations to confirm the validity of our analysis.

关键词： Mobile edge computing(MEC) Nakagami-m fading offloading selection combining(SC)/maximal ratio combining(MRC) successful computation probability(SCP) uplink nonortho-gonal multiple access(NOMA) wireless sensor networks(WSNs)

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Generative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles 59

Generative AI-Enhanced Cooperative MEC of UAVs and Ground St...

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

作者： You, Jiahao Jia, Ziye Dong, Chao Wu, Qihui Han, Zhu Nanjing University of Aeronautics and Astronautics The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

ISBN: (纸本)9798331513269

The increasing deployment of unmanned surface vehicles (USVs) require computational support and coverage in applications such as maritime search and rescue. Unmanned aerial vehicles (UAVs) can offer low-cost, flexible aerial services, and ground stations (GSs) can provide powerful supports, which can cooperate to help the USVs in complex scenarios. However, the collaboration between UAVs and GSs for USVs faces challenges of task uncertainties, USVs trajectory uncertainties, heterogeneities, and limited computational resources. To address these issues, we propose a cooperative UAV and GS based robust multi-access edge computing framework to assist USVs in completing computational tasks. Specifically, we formulate the optimization problem of joint task offloading and UAV trajectory to minimize the total execution time, which is in the form of mixed integer nonlinear programming and NP-hard to tackle. Therefore, we propose the algorithm of generative artificial intelligence-enhanced heterogeneous agent proximal policy optimization (GAI-HAPPO). The proposed algorithm integrates GAI models to enhance the actor network ability to model complex environments and extract high-level features, thereby allowing the algorithm to predict uncertainties and adapt to dynamic conditions. Additionally, GAI stabilizes the critic network, addressing the instability of multi-agent reinforcement learning approaches. Finally, extensive simulations demonstrate that the proposed algorithm outperforms the existing benchmark methods, thus highlighting the potentials in tackling intricate, cross-domain issues in the considered scenarios. © 2025 IEEE.

关键词： Unmanned surface vehicles

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Soccer Player Recognition using Artificial Intelligence and computer Vision

Soccer Player Recognition using Artificial Intelligence and ...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Diop, Charles-Alexandre Pelloux, Baptiste Yu, Xinrui Yi, Won-Jae 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)9781665480093

Groundbreaking features and functionalities are available in sports broadcasting programs, specifically in soccer games, such as post-game analysis, tracking of players, tracking of the ball, and associated teams' and players' statistical information. However, viewers don't have control to choose which features to view on-demand and aren't able to interact with any of these functionalities. Our system aims for the fundamental system of an on-demand viewer-driven application that would be able to track players on the field, identify formation changes, follow team strategy changes, and gather all statistical information of the player and the team on a single screen. In order to realize such an application, we focus on developing a method to track players on the field using multiple Artificial Intelligence (AI) and computer vision techniques where our application employs facial recognition and jersey number recognition algorithms. As a live soccer game broadcast would have various camera views of the players, our custom-made database contains captured images from different scenarios of camera views such as different angles and zooms of the player and is used to train the model using Convolutional Neural Network (CNN). Our system is scalable to different types of sports, such as basketball, baseball, volleyball, and more where players have their numbers on their jerseys and would be feasible to apply our system since soccer involves more players on the field than other sports games. © 2022 IEEE.

关键词： Cameras

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High Precision Analog Gauge Reader Using Optical Flow and computer Vision

High Precision Analog Gauge Reader Using Optical Flow and Co...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Chavan, Shruti Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

This paper aims at developing algorithms to automate the process of reading analog gauges at different operational industries, healthcare sector and automobiles using Artificial Intelligence (AI) techniques. Proposed algorithms start with video stabilization using optical flow followed by image processing which performs segmentation using HSV color space and morphological operations. Next, Hough transform is applied to determine the dial region and pointer. Using the coordinates locating the pointer in the frame, angle made with minimum valued scale mark is calculated using trigonometry and evaluated reading is displayed in the form of text and a progress bar. The proposed algorithms for Analog Gauge Reader (AGR) is executed using open-source libraries such as OpenCV, NumPy, PIL with Python programming and it is developed in the PyCharm environment. The experimental results show significant decrease in the error with the introduction of image preprocessing and the generalizability of the algorithm to different types of analog gauges captured in different conditions of illuminance. The accuracy and precision of the algorithms is 99% to 100% in the experimental studies. © 2022 IEEE.

关键词： Hough transforms

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Discharge image reconstruction and frequency domain analysis based on event data

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High Voltage 2024年第6期9卷 1195-1201页

作者： Quan Yuan Lei Deng Hao Guo Qishen Lyu Xin Zhang Jibin Wu Yu Deng Hongyang Zhou Xilin Wang Zhidong Jia Engineering Laboratory of Power Equipment Reliability in Complicated Coastal Environments Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenGuangdongChina Department of Precision Instrument Center for Brain Inspired Computing ResearchTsinghua UniversityBeijingChina College of Information and Computer Taiyuan University of TechnologyTaiyuanChina Shenzhen Power Supply Corporation China Southern Power Grid CorporationShenzhenChina Department of Computing The Hong Kong Polytechnic UniversityHong KongChina China Electric Power Research Institute BeijingChina School of Electrical Engineering and Automation Xiamen University of TechnologyXiamenChina

Optical image method has been the earliest and most used direct method for observing gas ***,research on gas discharge monitoring based on visible light mainly relies on high-speed cameras,but the large size,significant data storage requirements,and susceptibility to interference from complex backgrounds and lighting conditions limit their further *** vision sensing(DVS)technology is a neuromorphic sensing technology that asynchronously measures the luminance changes at each *** offers advantages such as a large dynamic range(>120 dB),high temporal resolution(up to 1µs),and small data volume(MB level).In this study,dynamic vision sensing technology was employed to monitor both 30 mm short-gaps and 1080 mm long-gaps discharge processes *** study developed the CountImage encoding method for event data and conducted image reconstruction,time-domain analysis,and frequency-domain charac-teristic analysis based on the event *** results show that the event-reconstructed images are highly consistent with the high-speed camera images,and the arc develop-ment process and its path can also be clearly ***,this study discovered a correlation between the electrical characteristics and event information during the discharge *** the time domain,the duration of the maximum DVS event count closely matches the duration during which the voltage drops to zero during *** the frequency domain,the Pearson correlation coefficient between the event stream spectrum and the voltage signal spectrum is greater than *** the maximum number of brightening events(ONmax)and the maximum number of darkening events(OFFmax)are positively correlated with the voltage applied between the *** study demonstrates that,compared to the GB/s data rate of high-speed cameras,this approach can record the discharge process and accurately reconstruct the discharge process,arc morphology,and discharge path at M

关键词： image analysis holds

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Impact of Daily Irradiance Profiles on Intra-Day Solar Forecasting 49

Impact of Daily Irradiance Profiles on Intra-Day Solar Forec...

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49th IEEE Photovoltaics Specialists Conference, PVSC 2022

作者： Lopez-Lorente, Javier Theocharides, Spyros Makrides, George Georghiou, George E. Foss Research Centre for Sustainable Energy University of Cyprus Pv Technology Laboratory Department of Electrical and Computer Engineering Nicosia1678 Cyprus

ISBN: (数字)9781728161174

ISBN: (纸本)9781728161174

The analysis of solar energy integration requires capturing the temporal variability of solar irradiance, which can highly increase the errors of solar forecasting models. In this paper, a classification of day types for solar energy applications is investigated and the impact on intra-day solar generation forecasting is assessed. The proposed classification approach uses unsupervised learning based on a combination of self-organized maps and mean-shift clustering with six location-independent metrics related to irradiance variability and energy yield. Two types of forecasts (a deterministic forecast and a probabilistic one) are used as a basis to illustrate the impact of the resulting daily irradiance profiles. The forecasts are emulated by adding white noise to historic hourly irradiance observations and their performance is compared to state-of-the-art benchmarking models. The results illustrate the magnitude of dispersion between intra-hour observations and hourly forecasts, where deterministic forecasts observed 16% to 64% of deviation and probabilistic forecasts observed prediction intervals from 11% to 36%, depending on the daily typology. The findings of this study provide useful information on the impact of intra-day irradiance variability on the performance of forecasting models and how these can be adapted based on each day type to support the integration of solar generation in electricity systems. © 2022 IEEE.

关键词： Solar energy

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Artificial Intelligence System for Emotion Recognition and Text Analytics

Artificial Intelligence System for Emotion Recognition and T...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Chaudhari, Namrata Agarwal, Reshu Narwade, Meghna Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

Harnessing the power of emotional intelligence by analyzing a person's behavioral and linguistic skills can help humans improve their approach to social interactions. In this paper, we propose an artificial intelligence-based stand-alone system that will allow us to classify and analyze facial expressions in real-time and perform sentiment analysis by examining the body of the text (extracted from audio) to understand the opinion expressed by it. This helps us provide a deeper understanding of how humans really feel at a given time. The proposed system uses a deep neural network (DNN) for classifying eight basic emotions based on features extracted from facial expressions and uses pretrained sentiment analysis tools to quantify text (extracted from audio) based on polarity. The system is implemented by extracting the audio and visual cues from real-time scenarios and using these extracted cues to perform facial expression recognition and text sentiment analysis. The integrated system extracts video and audio simultaneously with a frame rate of 4-5 fps. The facial emotion detection system successfully detects facial expressions of faces detected in real-time video with an accuracy of about 86.75%. The speech extracted is converted to text, cleaned, and processed to determine if the attitude of the speaker in a given situation is positive, negative, or neutral. © 2022 IEEE.

关键词： Deep neural networks

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Synthetic generation of hourly photovoltaic power forecasts using Bayesian Regularised Neural Networks 2

Synthetic generation of hourly photovoltaic power forecasts ...

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2nd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2022

作者： Theocharides, Spyros Lopez-Lorente, Javier Makrides, George Georghiou, George E. University of Cyprus Pv Technology Laboratory Foss Research Center for Sustainable Energy Department of Electrical and Computer Engineering Nicosia1678 Cyprus

ISBN: (数字)9781665461078

ISBN: (纸本)9781665461078

Accurate day-ahead photovoltaic (PV) power output forecasting techniques are important for grid and plant operators. In this study, a methodology for PV power forecasting is proposed based on a synthetic generation of multiple Bayesian regularised neural network (BRNN) models. Specifically, different BRNN models were developed for every hour of each day within the power production period. The final PV power production forecasting was provided by combining the outputs of all the developed models. The accuracy of the developed model was experimentally validated by deploying it to a test system installed in Cyprus. The day ahead power production forecasting performance accuracy of the proposed methodology in terms of normalised root mean square error and mean absolute percentage error was 5.80% and 4.49%, respectively. © 2022 IEEE.

关键词： Neural network models

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Quantum correlations in multimode nonlinear optics

Quantum correlations in multimode nonlinear optics

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Uddin, Shiekh Zia Sloan, Jamison Rivera, Nicholas Pontula, Sahil Salamin, Yannick Birk, Michael Sidorenko, Pavel Kaminer, Ido Soljačić, Marin Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Electrical and Computer Engineering Solid State Institute Technion Israel Institute of Technology Haifa32000 Israel

We develop a framework describing quantum noise propagation in highly spatially multimode nonlinear optical systems. We predict quantum deviations of the spatial intensity noise distribution from the spatial power dis... 详细信息

关键词： Quantum noise

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Fluctuation and dissipation in quantum nonlinear optics

Fluctuation and dissipation in quantum nonlinear optics

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Uddin, Shiekh Zia Rivera, Nicholas Seyler, Devin Salamin, Yannick Sloan, Jamison Xu, Shutao Sander, Michelle Y. Soljačić, Marin Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States

We present a new fluctuation-dissipation relation that shows how quantum noise transforms under engineered nonlinear dissipation found in many important nonlinear optical devices and validate the theory with experimen... 详细信息

ISBN: (纸本)9781957171395

关键词： Quantum noise

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