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A Simplified Technique Of Design For Double Density Wavelets With Enhanced Denoising APPLICATIONS 40

A Simplified Technique Of Design For Double Density Wavelets...

引用

40th National Radio science Conference, NRSC 2023

作者： Fahmy, Gamal Fahmy, Mamdouh F. Fahmy, Omar Galala University Faculty of Computer Science and Engineering Egypt Assiut University Electrical Engineering Dept. Assiut Egypt Badr University in Cairo Electrical Engineering Dept. Egypt

ISBN: (纸本)9798350311440

Denoising Images is a crucial step in noise removal in any data or image communication problem. Recently two image denoising techniques were presented that depends on bivariate analysis. These two techniques were called Double Density Discrete Wavelet Transform (DD DWT) and Double Density Dual Tree Complex Wavelet Transform (DD CWT). They relayed on the decomposition of noisy images with either DD CWT or DD DWT decompositions. This decomposition was after the bivariate based shrinkage technique was applied to exploit the wavelet parent and children correlation for better denoising performance. In this paper we present a novel filter design technique for a DD DWT structure for denoising applications. It composed of 3 dimensional cascaded orthogonal sections. This proposed 3-channel Double Density Wavelet decomposition structure is simple and is fast in terms of convergence. It overcomes most problems for other filter design techniques of being slowly iterative and relays on randomness in parameter optimization. The proposed filter design DD-DWT structure guarantees the Perfect Reconstruction PR and the Alias Cancellation AC conditions and is suitable for VLSI iterative designs. Illustrative examples for the usage of the proposed DD-DWT based design in different image denoising applications are shown in comparison with other denoising structures from recent literature. © 2023 IEEE.

关键词： Image denoising

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Teaching Practice Using ChatGPT in Higher Education 26

Teaching Practice Using ChatGPT in Higher Education

引用

26th International Conference on Enterprise Information Systems, ICEIS 2024

作者： Canedo, Edna Dias Calazans, Angelica Toffano Seidel Silva, Geovana Ramos Sousa Masson, Eloisa Toffano Seidel Mendonça, Fábio Lúcio Lopes Department of Computer Science Brasília Brazil DF Brasília70910-900 Brazil Electrical Engineering Department DF Brasília Brazil

ISBN: (纸本)9789897586927

ChatGPT is an Artificial Intelligence (AI) chatbot platform developed by OpenAI. Several studies have highlighted the advantages and disadvantages of integrating ChatGPT into teaching methodologies and knowledge generation within higher education. We conducted a survey involving 86 professors within the computer science field in Brazil. Our findings indicate that professors are utilizing ChatGPT for content generation and the creation of teaching materials, including practical exercises, slides, assignments, and tests. Moreover, they view ChatGPT as a potential facilitator of learning by fostering interaction between students and professors. In the realm of knowledge production, professors are leveraging ChatGPT for tasks such as aiding in the composition of research papers or articles and generating automatic summaries. However, as per the professors’ perceptions, a notable limitation of ChatGPT is its inability to provide bibliographic references for the content it delivers. Most professors believe that ChatGPT can be used as a support tool in higher education to generate knowledge. However, it is essential to address the challenges associated with the lack of bibliographic references in the content provided by ChatGPT. Copyright © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Knowledge management

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A Multi-agent Reinforcement Learning based Offloading and Resource Allocation for Vehicle Edge Computing 16

A Multi-agent Reinforcement Learning based Offloading and Re...

引用

16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Yang, Jiazhi Yang, Xinjie Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Ningbo Arrowdeep Internet Technology Co. Ltd. Ningbo China

ISBN: (纸本)9798331506322

This paper investigates the the challenges of resource allocation optimization for computation offloading in vehicular edge networks. It is assumed that multiple moving vehicles select Mobile Edge Computing (MEC) servers on Road Side Units (RSUs) to offload their computation tasks, for which, MEC servers allocate appropriate resources. To achieve the best balance between minimizing latency and resource consumption to ensure system performance, this study utilizes a Multi-Agent Reinforcement Learning (MARL) framework, where each vehicle and MEC server acts as an agent and learns optimal strategies through interactions with the environment. To improve performance, a new Global Heterogeneous MARL (GHMARL) framework is purposely designed based on existing MARL approaches. The proposed framework trains two Critic networks, namely, a global Critic network to ensure service quality and a local Critic network to ensure resource utilization efficiency. Extensive simulation results demonstrate the performance superiority of this approach over benchmark algorithms. © 2024 IEEE.

关键词： Mobile Edge Computing Multi-Agent Reinforcement Learning Resource allocation Vehicular edge networks

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Communicate or Sense? AP Mode Selection in mmWave Cell-Free Massive MIMO-ISAC 58

Communicate or Sense? AP Mode Selection in mmWave Cell-Free ...

引用

58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Yan, Weixian Topal, Ozan Alp Behdad, Zinat Demir, Özlem Tuǧfe Cavdar, Cicek Kth Royal Institute of Technology Department of Computer Science Kista Sweden Tobb University of Economics and Technology Department of Electrical-Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350354058

Integrated sensing and communication (ISAC) is a promising technology for future mobile networks, enabling sensing applications to be performed by existing communication networks, consequently improving the system efficiency. Millimeter wave (mmWave) signals provide high sensing resolution and high data rate but suffer from sensitivity to blockage. Cell-free massive multiple-input multiple-output (MIMO), with a large number of distributed access points (APs), can overcome this challenge by providing macro diversity against changing blockages and can save energy consumption by deactivating unfavorable APs. Thus, in this work, we propose a joint dynamic AP mode selection and power allocation scheme for mmWave cell-free massive MIMO-ISAC, where APs are assigned either as ISAC transmitters, sensing receivers, or shut down. Due to the large size of the original problem, we propose three different sub-optimal algorithms that minimize the number of active APs while guaranteeing the sensing and communication constraints. Numerical results demonstrate that assigning ISAC transmitters only satisfying communication constraints, followed up by sensing receiver assignment only for sensing constraint achieves the best performance-complexity balance. © 2024 IEEE.

关键词： Transmitters

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Identification and Classification of Electronic Devices Using Harmonic Radar 19

Identification and Classification of Electronic Devices Usin...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Perez, Beatrice Pierson, Timothy J. Mazzaro, Gregory Kotz, David Dartmouth College Department of Computer Science HanoverNH United States The Citadel the Military College of South Carolina Department of Electrical and Computer Engineering CharlestonSC United States

ISBN: (纸本)9798350346497

Smart home electronic devices invisibly collect, process, and exchange information with each other and with remote services, often without a home occupants' knowledge or consent. These devices may be mobile or fixed and may have wireless or wired network connections. Detecting and identifying all devices present in a home is a necessary first step to control the flow of data, but there exists no universal mechanism to detect and identify all electronic devices in a space. In this paper we present ICED (Identification and Classification of Electronic Devices), a system that can (i) identify devices from a known set of devices, and (ii) detect the presence of previously unseen devices. ICED, based on harmonic radar technology, collects measurements at the first harmonic of the radar's transmit frequency. We find that the harmonic response contains enough information to infer the type of device. It works when the device has no wireless network interface, is powered off, or attempts to evade detection. We evaluate performance on a collection of 17 devices and find that by transmitting a range of frequencies we correctly identify known devices with 97.6% accuracy and identify previously unseen devices as 'unknown' with 69.0% balanced accuracy. © 2023 IEEE.

关键词： Classification (of information)

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Hybrid distributed acoustic sensing and Kramers-Kronig communication system over a two-mode fiber

Hybrid distributed acoustic sensing and Kramers-Kronig commu...

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Marin, Juan M. Briantcev, Dmitrii Kang, Chun Hong Alkhazragi, Omar Ng, Tien Khee Ashry, Islam Trichili, Abderrahmen Ooi, Boon S. King Abdullah University of Science and Technology Computer Electrical and Mathematical Sciences & Engineering Thuwal23955-6900 Saudi Arabia

We report on the co-propagation of distributed acoustic sensing (DAS) and Kramers-Kronig communication scheme over a two-mode fiber, achieving DAS with a signal-to-noise ratio larger than 2 dB and gross data rate of 2... 详细信息

ISBN: (纸本)9781957171180

关键词： Signal to noise ratio

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Shared Cross-Prediction Neural Network for Efficient Key Generation in IoT Networks 14

Shared Cross-Prediction Neural Network for Efficient Key Gen...

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14th International ITG Conference on Systems, Communications and Coding, SCC 2025

作者： Alashqar, Anas Torshizi, Ehsan Olyaei Mesleh, Raed Henkel, Werner School of Computer Science and Engineering Constructor University Bremen28759 Germany School of Electrical Engineering and Information Technology German Jordanian University Amman11180 Jordan

ISBN: (纸本)9798331522896

Physical layer secret key generation (PSKG) leverages the reciprocal properties of wireless channels to establish cryptographic keys between legitimate users. However, in time-division duplex (TDD) systems, this reciprocity can be compromised by hardware imperfections and channel noise, complicating the key generation process. To address these challenges, we propose a shared cross-prediction neural network (SCP-NN) model that operates in an unsupervised manner, eliminating the need for perfect channel state information (CSI). Specifically, the proposed SCP-NN model employs a cross-prediction strategy that minimizes the difference between the predicted channels of legitimate users, ensuring that the outputs converge toward each other. Furthermore, we present a comprehensive PSKG procedure that leverages the SCP-NN architecture to extract key information from the phase characteristics of the channel frequency responses. Experimental results demonstrate that the proposed SCP-NN significantly reduces the key disagreement ratio (KDR), providing a robust and effective solution for secure key generation in dynamic IoT environments. © 2025 IEEE.

关键词： Time division multiple access

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YOLO Based Automatic Poultry Monitoring System 3

YOLO Based Automatic Poultry Monitoring System

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3rd International Conference for Advancement in Technology, ICONAT 2024

作者： Paramathma, M. Krishna Kumar, Inukurthi Bharath Karuppasamypandiyan, M. Kalasalingam Academy of Research and Education Department of Electrical and Electronics Engineering Tamil Nadu India Kalasalingam Academy of Research and Education Department of Computer Science Engineering Tamil Nadu India

ISBN: (纸本)9798350354171

Efficient poultry management is essential to ensure the continued availability and affordability of poultry products for consumers. Considering the crucial role of poultry farming in the global economy, this paper introduces a novel automated poultry monitoring system using the YOLO v8 model. In this work, a dataset comprising visual images was collected and utilized to predict the pathological characteristics of chickens. A total of 500 augmented images with the annotated labels as scab, swelling, paralysis and healthy chickens are taken into the account. After training, the proposed YOLOv8-based model showcased outstanding performance by achieving the top accuracy in object detection, boasting an F1 score of 0.86. The proposed system transcends passive monitoring by providing real-time data and triggering alerts via mails with triggered data and insightful images. Additionally, this proposed system emphasizes chicken welfare through proper monitoring of climate conditions such as temperature, humidity, and air quality, which significantly influence chicken health and productivity. The parameters obtained from DHT and MQ6 sensors interfaced with ESP8266 provide valuable insights for optimizing poultry farm operations and improving overall chicken health to maintain a stress-free environment, fostering increased egg production and overall flock health. © 2024 IEEE.

关键词： Farm management Object detection Poultry monitoring YOLOv8

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Self-Play Ensemble Q-learning enabled Resource Allocation for Network Slicing

Self-Play Ensemble Q-learning enabled Resource Allocation fo...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Salehi, Shavbo Iturria-Rivera, Pedro Enrique Elsayed, Medhat Bavand, Majid Gaigalas, Raimundas Ozcan, Yigit Erol-Kantarci, Melike University of Ottawa School of Electrical Engineering and Computer Science Ottawa Canada Ericsson Canada Inc. Ottawa Canada Ericsson Ab Stockhom Sweden

ISBN: (纸本)9798350351255

In 5G networks, network slicing has emerged as a pivotal paradigm to address diverse user demands and service requirements. To meet the requirements, reinforcement learning (RL) algorithms have been utilized widely, but this method has the problem of overestimation and exploration-exploitation trade-offs. To tackle these problems, this paper explores the application of self-play ensemble Q-learning, an extended version of the RL-based technique. Self-play ensemble Q-learning utilizes multiple Q-tables with various exploration-exploitation rates leading to different observations for choosing the most suitable action for each state. Moreover, through self-play, each model endeavors to enhance its performance compared to its previous iterations, boosting system efficiency, and decreasing the effect of overestimation. For performance evaluation, we consider three RL-based algorithms;self-play ensemble Q-learning, double Q-learning, and Q-learning, and compare their performance under different network traffic. Through simulations, we demonstrate the effectiveness of self-play ensemble Q-learning in meeting the diverse demands within 21.92% in latency, 24.22% in throughput, and 23.63% in packet drop rate in comparison with the baseline methods. Furthermore, we evaluate the robustness of self-play ensemble Q-learning and double Q-learning in situations where one of the Q-tables is affected by a malicious user. Our results depicted that the self-play ensemble Q-learning method is more robust against adversarial users and prevents a noticeable drop in system performance, mitigating the impact of users manipulating policies. © 2024 IEEE.

关键词： Contrastive Learning

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Optically Transparent 4-Port UWB Antenna for MIMO Applications 2

Optically Transparent 4-Port UWB Antenna for MIMO Applicatio...

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2nd International Microwave and Antenna Symposium, IMAS 2024

作者： Yahya, Rabia Yin, Haosen Bertuch, David El-Ghazaly, Amal Nouakchott University Department of Physics Faculty of Science and Technology Nouakchott Mauritania Cornell University Department of Electrical and Computer Engineering IthacaNY United States

ISBN: (纸本)9798350356359

Herein, we present a novel transparent antenna with ultra-wideband (UWB) performance along with polarization diversity through 4 ports allowing MIMO operation. The antenna design can be of a great interest for a vehicular applications and Internet of Things (IOT) where the dual polarization and multiple ports allows as well as medical glasses and vehicular windows where transparency is needed for visibility. The proposed antenna provides compact size with dimensions of 50 mm×50 mm, through the employment of CPW, dual orthogonal-polarization, isolation level of 20 dB, and envelope correlation coefficient (ECC) of 0.0016 as well as MIMO performance. © 2024 IEEE.

关键词： Ultra-wideband (UWB)

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