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4th International Conference on Digital Futures and Transformative Technologies, ICoDT2 2024

作者： Sikander, Saad Rehman, Hamood Ur Naqvi, Syed Fakhr Abbas Aslam, Waqar Perwaiz, Nazia Sir Syed CASE Institute of Technology Department of Electrical Engineering Islamabad Pakistan Sir Syed CASE Institute of Technology Department of Electrical Engineering and Computer Science Islamabad Pakistan National University of Sciences and Technology NUST School of Electrical Engineering and Computer Science Islamabad Pakistan

ISBN: (纸本)9798350391862

Monitoring the environment and managing water bodies are crucial for preserving ecosystems and ensuring sustainable resource utilization. This study aims to propose a robust approach for segmenting water bodies by combining various complementary attributes extracted from deep learning techniques. By leveraging deep contextual features learned from attention regions and enhanced edge detection, our method significantly improves the accuracy of detecting water bodies in low-resolution satellite imagery. Utilizing S1 and S2 Sentinel imagery data and exploring multi-band features, we enhance key attributes through advanced UNet architectures - specifically, Ki-UNet and Attention UNet - and integrate complementary features for downstream tasks. Additionally, we assembled a local dataset from the Khyber Pakhtunkhwa (KPK) region of Pakistan, facilitating precise water body segmentation from satellite or aerial views. Our ensemble model achieved remarkable accuracy and Intersection over Union (IoU) scores, reaching up to 99.01% and 96.2%, respectively, surpassing state-of-the-art models. This research provides automated, accurate segmentation techniques essential for environmental management and resource assessment, offering a promising solution for delineating water bodies. github link : (https://***/SaadBaloch96/Dataset/blob/main/***) © 2024 IEEE.

关键词： Environmental monitoring

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Young's double slit interference with vortex source

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Chinese Physics B 2024年第1期33卷 395-399页

作者：段琦琳赵鹏飞殷玉杭陈焕阳 Institute of Electromagnetics and Acoustics and Department of Physics College of Physical Science and TechnologyXiamen UniversityXiamen 361005China Jiujiang Research Institute of Xiamen University Jiujiang 332000China Department of Electrical and Computer Engineering National University of Singapore117583Singapore

The fast and convenient demultiplex of optical vortex(OV) mode is crucial for its further application. We propose a novel approach that combines classic Young's doublet with an OV source to effectively identify the OV mode through the analysis of interference patterns. The interference patterns of the OV source incident on the double slits can be perfectly illustrated by using both the classical double-slit interference method and the Huygens–Fresnel principle. The interference fringes will twist along the negative or positive direction of x axis when topological charge(TC)l>0 or l<0, and the degree of the movement varies with the TC, allowing for a quantitative display of the OV characteristics through the interference patterns. Additionally, we deduce analytically that the zeroth-order interference fringe has a linear relationship with the TC and the vertical position. These findings highlight the ability to identify the OV mode by analyzing the interference patterns produced by Young's doublet.

关键词： Young's double slit vortex source inteference patterns

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In-band full-duplex MIMO PLC systems for relaying networks

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Digital Communications and Networks 2025年第1期11卷 145-159页

作者： Francisco J.Canete Gautham Prasad Lutz Lampe Communications and Signal Processing Lab Telecommunication Research Institute(TELMA)ETS Ingenieria TelecomunicacionUniversidad de MalagaSpain Ofinno RestonVAUSA Department of Electrical and Computer Engineering The University of British ColumbiaCanada

In Power Line Communications(PLC),there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons,which creates coverage issues despite the not too long ***,PLC networks often employ repeaters/relays,especially in smart grid neighborhood area *** in broadband indoor PLC systems that offer a notable data rate,relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things *** this paper,we study Multiple-Input Multiple-Output(MIMO)PLC systems that incorporate inband full-duplex functionality in relaying *** present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC *** reach this analysis,we get channel realizations from random network layouts for indoor and outdoor *** adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC *** concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput:smart grids with enhanced communications in outdoor scenarios,and“last meter”systems for high-speed connections everywhere in indoor ones.

关键词： PLC MIMO Relaying networks OFDM Spatial correlation Performance analysis

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computer Vision-Based Hydroponic Lettuce Contour and Area Recognition System

Computer Vision-Based Hydroponic Lettuce Contour and Area Re...

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2023 International Conference on electrical engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

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Integrated encoder-decoder-based wide and deep convolution neural networks strategy for electricity theft arbitration

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Journal of engineering and Applied Science 2024年第1期71卷 94页

作者： Kumawat, Manoj Onaolapo, Adeniyi Sharma, Gulshan Barutcu, Ibrahim Cagri Adefarati, Temitope Bansal, Ramesh Department of Electrical Engineering National Institute of Technology Delhi Delhi India Department of Electrical Engineering Technology University of Johannesburg Johannesburg2006 South Africa Department of Electricity and Energy Çölemerik V.H.S. Hakkari University Hakkari30000 Turkey Department of Electrical and Electronics Engineering Federal University Oye Ekiti Oye Ekiti Nigeria Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electric Electronic and Computer Engineering University of Pretoria Pretoria South Africa

Integrating energy systems with information systems in smart grids offers a promising avenue for combating electricity theft by leveraging real-time data insights. Suspicious activity indicative of theft can be identified through anomalous consumption patterns observed in smart networks. However, a smart model is required for capturing and analysing the data intelligently to accurately detect electricity theft. In the paper, electricity theft has been detected using an encoder-decoder-based classifier that integrates two models of convolutional neural networks (CNN). The aim is to scan the strength of the data and built a smart model that analysed the connections in complex data and determine the pattern of theft. The model comprises three compartments: the auto-encoder, the wide convolutional neural network (1-D CNN model), and the deep convolutional neural network (2-D CNN model). The auto-encoder has been trained on the complex and in-depth linkage between the theft data and the normal data as it removes noise and unnecessary information. The 1-D CNN model gathers relevant connections and general features, while the 2-D CNN model determines the rate at which energy theft occurs and differentiates between the energy-stealing consumers and normal consumers. The efficacy of the approach is underscored by its superiority over traditional deep learning and machine learning techniques. This paper elucidates the distinct advantages and applications of the proposed model in combating electricity theft within smart grid environments. © The Author(s) 2024.

关键词： Smart power grids

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A 103 fJ/b/dB, 10-26 Gb/s Receiver With a Dual Feedback Nested Loop CDR for Wide Bandwidth Jitter Tolerance Enhancement

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IEEE Journal of Solid-State Circuits 2023年第10期58卷 2801-2811页

作者： Liu, Yao-Chia Chen, Wei-Zen Lee, Yuan-Sheng Chen, Yu-Hsiang Ming, Shawn Lin, Ying-Hsi National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Department of Electronics and Electrical Engineering The Institute of Electronics Hsinchu30010 Taiwan Realtek Hsinchu30076 Taiwan

A 10-26 Gb/s energy-efficient receiver incorporating a dual-feedback nested loop clock and data recovery circuit (DF-CDR) is proposed. Combining a direct modulation path on voltage-controlled oscillator (VCO) and phase interpolator (PI)-based phase rotator inside a phase locked loop (PLL), it improves high-frequency jitter tolerance by 0.15 UI. An edge-first equalization scheme is proposed to reduce power and hardware overhead of decision feedback equalizers. Meanwhile, it facilitates adaptive equalization of continuous time linear equalizer, and background offset calibration of the receiver frontend. A three-stage latch comparator is adopted to enable high-speed direct feedback equalizer. By applying PRBS-31 test pattern through a 32 dB loss channel, the receiver is error-free and features the best energy efficiency of 103 fJ/b/dB at 26 Gb/s. © 1966-2012 IEEE.

关键词： Bandwidth

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On-Demand Coordinated Spectrum and Resource Provisioning under an Open C-RAN Architecture for Dense Small Cell Networks

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IEEE Transactions on Mobile Computing 2024年第1期23卷 673-688页

作者： Wu, Sau-Hsuan Ko, Chun-Hsien Chao, Hsi-Lu National Yang Ming Chiao Tung University Institute of Communications Engineering College of Electrical and Computer Engineering Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Institute of Information Engineering Department of Computer Science Hsinchu30010 Taiwan

Mobile networks have seen more than a thousand times traffic increases in the past decade. Network operators face an ever increasing demand and cost to deploy denser networks in order to maintain the quality of services. In view of this paradigm shift, an open cloud radio access network (C-RAN) service model is studied in this work. Integrating the cross-layer functions of spectrum resource sharing, channel and power allocation, and interference management in a C-RAN architecture, we explore the feasibility of providing a scalable yet efficient broadband wireless service with dense small cell networks (DSN). The proposed methods and architecture can be applied to DSN that support the functions of (further enhanced) inter-cell interference cancelation (feICIC/ICIC) techniques of 3GPP standard, and have the potential to provide a cost-effective solution for high-quality DSN. Simulation results across an area of 100 km2 show that the proposed scheme can offer an aggregate downlink throughput of 21 Gbps over a maximum channel bandwidth of 20 MHz, which is 5 times the throughput with a typical ICIC method. Moreover, the service satisfaction degree can reach 85% under the proposed C-RAN architecture, making it a promising and cost-effective solution for future broadband wireless services. © 2002-2012 IEEE.

关键词： Radio access networks

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Effect of individual atmospheric parameters on beam spreading of higher-order Gaussian beam

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Optical and Quantum Electronics 2024年第12期56卷 1-18页

作者： kumar, Mukesh Khandelwal, Arpit Azeemuddin, Syed Center for VLSI and Embedded System Technologies International Institute of Information Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology Jodhpur India Department of Electrical and Computer Engineering Behrend College Penn State University EriePA United States

The beam spreading is essential for evaluating the higher-order Gaussian beam when it propagates through atmospheric turbulence. In this paper, we investigate the impact of individual atmospheric parameters such as jitter, turbulence, wind speed, and thermal blooming on beam spreading of Hermite Gaussian (HG), and Laguerre Gaussian (LG) beams. We also examine spot size variations due to beam quality on various HG and LG modes. It is seen that the impact of spreading caused by beam quality and turbulence is higher than that of jitter, wind speed, and thermal blooming. As the mode order increases, the effect of turbulence strength increases, leading to more spread for HG and LG beams. Spreading due to diffraction and beam quality on higher mode LG beam is higher than the HG beam in different modes. Beam spreading due to thermal blooming for the lower mode is higher compared to the higher mode for LG and HG beams. The sensitivity of higher mode LG beams to turbulence distortions is greater than HG beams as they experience more significant fractional increases in their spot size due to turbulence. The combined beam spread for the Laguerre Gaussian beam is larger than the Hermite Gaussian beam. This paper aims to understand better individual beam spreading in the atmosphere and its impact on the overall performance of higher-order laser propagation to develop optimized laser systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Gaussian beams

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Hardware and Software Improvements of Spatial Light Modulator (SLM)-Based Optical Wireless Communication Supporting Four Users Using Non-Orthogonal Multiple Access (NOMA)

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Journal of Lightwave Technology 2024年第17期42卷 5839-5845页

作者： Jian, Yin-He Yang, Kai-Jyun Wei, Tzu-Chieh Wang, Chih-Chun Chow, Chi-Wai National Yang Ming Chiao Tung University Department of Photonics Graduate Institute of Electro-Optical Engineering College of Electrical and Computer Engineering Hsinchu30010 Taiwan

We propose and experimentally demonstrate a spatial-light-modulator (SLM) based optical wireless communication (OWC) system using non-orthogonal multiple access realizing four-layer of successive interference cancellation (SIC) iterations for the first time. This can be attributed by our two contributions. First, an iterative phase correction algorithm (PCA) is proposed for addressing the SLM non-ideal effects. Second, low-density parity check is utilized to provide coding gain for the SIC. Experimental results show that 3.5-dB improvement at a steering angle of (5o, 5o) is achieved by the PCA, and >54-Gbps total data rate is achieved in the 4-user OWC system. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Self-Supervised Representation Learning for Knee Injury Diagnosis From Magnetic Resonance Data

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1613-1623页

作者： Manna, Siladittya Bhattacharya, Saumik Pal, Umapada Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata700108 India Indian Institute of Technology Kharagpur Department of Electronics and Electrical Communication Engineering Kharagpur721302 India

In medical image analysis, the cost of acquiring high-quality data and annotation by experts is a barrier in many medical applications. Most of the techniques used are based on a supervised learning framework and require a large amount of annotated data to achieve satisfactory performance. As an alternative, in this article, we propose a self-supervised learning approach for learning the spatial anatomical representations from the frames of magnetic resonance (MR) video clips for the diagnosis of knee medical conditions. The pretext model learns meaningful context-invariant spatial representations. The downstream task in our article is a class-imbalanced multilabel classification. Different experiments show that the features learned by the pretext model provide competitive performance in the downstream task. Moreover, the efficiency and reliability of the proposed pretext model in learning representations of minority classes without applying any strategy toward imbalance in the dataset can be seen from the results. To the best of our knowledge, this work is the first of its kind in showing the effectiveness and reliability of self-supervised learning algorithms in imbalanced multilabel classification tasks on MR scans. © 2020 IEEE.

关键词： Supervised learning

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