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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bea, Khean-Thye Wei-Hsuan Lin, Shih-Shin Hu Lin, Da-Zheng Hu, Hsin-Hui Chen, Xiu-Zhi Lin, Ting-Ru Chen, Yen-Lin Chen, Kun-Ming Cheng, Wai Khuen National Taipei University of Technology Dep. of Electronic Engineering Taipei106 Taiwan National Taipei University of Technology Dep. of Computer Science and Information Engineering Taipei106 Taiwan Taiwan Semiconductor Research Institute Hsinchu30078 Taiwan Universiti Tunku Abdul Rahman Faculty of Information and Communication Technology Kampar31900 Malaysia

ISBN: (纸本)9798350337020

In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a high R2 score of 0.9704 with a low-computing-power hardware-friendly method that reduced time consumption significantly compared to prior approaches. The findings have practical implications for mitigating the time-consuming nature of TCAD simulations, and the method can expand to various types of input data while ensuring high performance and generalization. We demonstrated significant improvement in generalization and accuracy through a k-fold validation. © 2023 IEEE.

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A Review of Grid-Connected Inverters and Control Methods Under Unbalanced Grid Conditions

A Review of Grid-Connected Inverters and Control Methods Und...

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Power Electronic and Drive Systems and Technologies Conference (PEDSTC)

作者： Milad Ghavipanjeh Marangalu Fazal Ur Rehman Naser Vosoughi Kurkdjian Dep. Of Electrical and Computer Engineering Computer Queen’s University Kingston Ontario Canada Dep. Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Faculty of Electrical and Computer Engineering San Diego State University San Diego CA USA

ISBN: (数字)9798331533946

ISBN: (纸本)9798331533953

Grid-connected inverters play a pivotal role in integrating renewable energy sources into modern power systems. However, the presence of unbalanced grid conditions poses significant challenges to the stable operation of these inverters. This review paper provides a comprehensive overview of grid-connected inverters and control methods tailored to address unbalanced grid conditions. Beginning with an introduction to the fundamentals of grid-connected inverters, the paper elucidates the impact of unbalanced grid voltages on their performance. Various control strategies, including voltage and current control methods, are examined in detail, highlighting their strengths and limitations in mitigating the effects of grid imbalance. Lastly, the review identifies emerging trends and future research directions in the field, emphasizing the need for innovative solutions to address the evolving challenges posed by unbalanced grid conditions in the context of renewable energy integration.

关键词： Current control Photovoltaic systems Renewable energy sources Technological innovation Reviews Pressing Market research Inverters Power systems Voltage control

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Detecting 5G Signal Jammers with Autoencoders Based on Loose Observations

Detecting 5G Signal Jammers with Autoencoders Based on Loose...

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IEEE Globecom Workshops

作者： Matteo Varotto Stefan Valentin Stefano Tomasin Dep. of Information Engineering University of Padova Padova Italy Dep. of Computer Science Darmstadt University of Applied Sciences Darmstadt Germany Dep. of Information Engineering Dep. of Mathematics University of Padova Padova Italy

Fifth-generation (5G) networks are prone to jamming attacks, which are particularly dangerous in mission-critical applications such as factory automation. In this paper, we present a simple method to detect jamming attacks with machine learning techniques operating on in-phase and quadrature (IQ) modulated signals. In particular, a convolutional autoencoder (CAE) learns the structure of the clean signal to distinguish it from jammed signals in real time. This approach requires only a loose synchronization to the OFDM symbol, while equalization and decoding are not necessary. Despite its simplicity, our technique has shown high detection rates in experiments on a 5G testbed.

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COVID-19 detection from Xray and CT scans using transfer learning

COVID-19 detection from Xray and CT scans using transfer lea...

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2021 International Conference of Women in Data science at Taif University, WiDSTaif 2021

作者： Berrimi, Mohamed Hamdi, Skander Yahia Cherif, Raoudha Moussaoui, Abdelouahab Oussalah, Mourad Chabane, Mafaza Dep. of Computer Science University of Ferhat Abbes Setif I Setif Algeria Dep. of Computer Science and Engineering University of Oulu Oulu Finland

ISBN: (纸本)9781665449489

Since the novel coronavirus SARS-CoV-2 outbreak, intensive research has been conducted to find suitable tools for diagnosis and identifying infected people in order to take appropriate action. Chest imaging plays a significant role in this phase where CT and Xrays scans have proven to be effective in detecting COVID-19 within the lungs. In this research, we propose deep learning models using Transfer learning to detect COVID-19. Both X-ray and CT scans were considered to evaluate the proposed methods. © 2021 IEEE.

关键词： Medical imaging

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FOCUSED ACTIVE LEARNING FOR HISTOPATHOLOGICAL IMAGE CLASSIFICATION

arXiv

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arXiv 2024年

作者： Schmidt, Arne Morales-Álvarez, Pablo Cooper, Lee A.D. Newberg, Lee A. Enquobahrie, Andinet Katsaggelos, Aggelos K. Molina, Rafael Dep. of Computer Science and AI University of Granada Granada Spain Dep. of Statistics and Operations Research University of Granada Granada Spain Dep. of Pathology Northwestern University Chicago United States Kitware Inc Carrboro United States Dep. of Electrical Computer Engineering Northwestern University Evanston United States

Active Learning (AL) has the potential to solve a major problem of digital pathology: the efficient acquisition of labeled data for machine learning algorithms. However, existing AL methods often struggle in realistic settings with artifacts, ambiguities, and class imbalances, as commonly seen in the medical field. The lack of precise uncertainty estimations leads to the acquisition of images with a low informative value. To address these challenges, we propose Focused Active Learning (FocAL), which combines a Bayesian Neural Network with Out-of-Distribution detection to estimate different uncertainties for the acquisition function. Specifically, the weighted epistemic uncertainty accounts for the class imbalance, aleatoric uncertainty for ambiguous images, and an OoD score for artifacts. We perform extensive experiments to validate our method on MNIST and the real-world Panda dataset for the classification of prostate cancer. The results confirm that other AL methods are’distracted’ by ambiguities and artifacts which harm the performance. FocAL effectively focuses on the most informative images, avoiding ambiguities and artifacts during acquisition. For both experiments, FocAL outperforms existing AL approaches, reaching a Cohen’s kappa of 0.764 with only 0.69% of the labeled Panda data. © 2024, CC BY.

关键词： Image classification

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model 3

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Elshabrawy, Mahmoud Eid, Marwa M. Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed Delta Higher Institute of Engineering and Technology Dept. of Communications & Electronics Mansoura Egypt Delta University for Science and Technology Faculty of Artificial Intelligence Mansoura35111 Egypt Ain Shams University Faculty of Computer and Information Sciences Dep. of Computer Science Cairo Egypt University Mansoura Faculty of Engineering Computer Engineering and Control Systems Dept. Egypt

ISBN: (纸本)9798350323511

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models. © 2023 IEEE.

关键词： Ant colony optimization

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AbotalebNet: A Novel Deep Learning Architecture for Time Series Forecasting with Convolutional and LSTM Layers Enhanced by Multi-Head Attention

AbotalebNet: A Novel Deep Learning Architecture for Time Ser...

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Trends in Quantum Computing and Emerging Business Technologies (TQCEBT), International Conference on

作者： Mostafa Abotaleb Tatiana Makarovskikh Maad M. Mijwil Indu Bala Kamal Kant Hiran Ruchi Doshi Dep. of System Programming South Ural State University Chelyabinsk Russia Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Electrical and Electronics Engineering Lovely Professional University Punjab India Dep. of Computer Science Sir Padampat Singhania University Udaipur India Dep. of Computer Science and Engineering Universidad Azteca Chalco Mexico

ISBN: (数字)9798350384277

ISBN: (纸本)9798350384284

This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet’s architecture is mathematically represented as:\begin{equation*}\hat Y = {\text{Attention}}(\operatorname{LSTM} ({\text{CNN}}(X)))\tag{1}\end{equation*}Here, X represents the input time series data, and Ŷ is the forecasted output. AbotalebNet integrates the feature extraction capabilities of Convolutional Neural Networks (CNNs) with the sequential data processing power of Long Short-Term Memory (LSTM) networks, further enhanced by a Multi-Head Attention *** address overfitting, a key challenge in deep learning, the model incorporates regularization strategies, dropout mechanisms, and batch normalization:\begin{equation*}\mathop {\min }\limits_\Theta ( Loss (X,\hat Y;\Theta ) + \lambda R(\Theta ))\tag{2}\end{equation*}In this equation, Θ denotes the model parameters, R(Θ) represents regularization terms, and λ is the regularization coefficient. These additions aid in preventing the model from overfitting to the training data, ensuring robust performance on unseen *** evaluation on COVID-19 time series data demonstrates AbotalebNet’s enhanced predictive accuracy over traditional models, solidifying its potential for advanced non-linear time series analysis.

关键词： COVID-19 Analytical models Solid modeling Time series analysis Training data Predictive models Data models

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Impact of PTB Message Usage on Path MTU Discovery for QUIC

Impact of PTB Message Usage on Path MTU Discovery for QUIC

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Conference on Local computer Networks (LCN)

作者： Timo Völker Michael Tüxen Dep. of Electrical Engineering and Computer Science FH Münster University of Applied Sciences Steinfurt Germany

ISBN: (数字)9798350388008

ISBN: (纸本)9798350388015

A data sender in an IP-based network is only capable of efficiently using a network path if it knows the packet size limit of the path, i.e., the Path Maximum Transmission Unit (PMTU). An IP router that cannot forward and must drop an oversized packet should notify the sender with a Packet Too Big (PTB) message, which contains the maximum packet size it can forward. A transport protocol supporting a discovery to determine the PMTU may use PTB messages. However, for the transport protocol QUIC (e.g., used by HTTP/3), we identified only a few implementations that determine the PMTU and none of them process PTB messages. In this paper, we present results from simulations that show how much a QUIC sender using PMTU discovery benefits from processing PTB messages, which includes a result that outlines the benefit of determining the PMTU in general. Further, we analyze the risk of using PTB messages and describe a way to protect against potential attacks with forged PTB messages.

关键词： Transport protocols Routing protocols IP networks

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The Correlation Between Architecture Smells, Package Stability and Reusability: A Case Study 4

The Correlation Between Architecture Smells, Package Stabili...

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4th IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2024

作者： Benidris, Mrwan Elfallah, Ehab A. Omar Cheema, Marwa Aslam Alsma, Mohammed Salah Addin Kadiki, Tareq Ziad Elbarsha, Abdelfattah University of Benghazi Faculty of Information Technology Dep. of Computer Science Libya Libyan International Medical University Faculty of Information Technology Dept. of Software Engineering Libya University of Benghazi Faculty of Public Health Health Informatics Department Libya

ISBN: (纸本)9798350372632

the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. Architecture smells (ASs) can be used to identify any quality issues within the system. To further explore the relationships between ASs, stability, and reusability, Spearman correlation coefficients will be calculated. This paper seeks to examine the connection between architecture smells, software stability, and reusability. To do this, we utilized a dataset created by other researchers and conducted an empirical study of the associations between five types of architecture smells and software stability and reusability. This research is necessary as there is a lack of in-dep.h research on architecture smells and their relationship to software stability and reusability. We found a relationship between the presence of Feature Concentration in package and the stability and reusability of the package. Also, package's stability is affected by both Cyclic dep.ndency and Unstable dep.ndency. A slight positive correlation has been found between God Class and stability, as well as a very weak negative correlation between Unstable dep.ndency and reusability. Finally, we found a slight negative correlation between package stability and reusability. © 2024 IEEE.

关键词： Reusability

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The Realization Factors of Taiwan's Low Altitude Airspace Economy and UAM: Analysis and Evaluation 20

The Realization Factors of Taiwan's Low Altitude Airspace Ec...

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20th IEEE International Conference on e-Business engineering, ICEBE 2024

作者： Wu, Tung-Ling Kung, Chih-Ming Lin, Guan-Ting Tsai, Kuen-Yu Meng, Guang-Yun Huang, Yu-Che Cheng, Wan-Shu Institute of Transportation at Ministry of Transportation and Communications Taiwan Shin Chin Univeristy Kaohsiung Campus Dep. of Information Technology&Communication Taiwan Providence University Dep. of Computer Science and Information Management Taichung Taiwan National Taiwan Univeristy Department of Electrical Engineering Taipei Taiwan Executive Officer Center for Research on High-Performance Remote Sensing and Urban Informatics Ntu Taiwan

ISBN: (纸本)9798350365856

Low altitude airspace economy applications will be of highly effective in a wide range of civil activities and will be a critical element in the smart cities of the future. In view of the main features of unmanned aerial vehicle (UAV), such as automatic piloting system, access to uninhabited areas, low cost compared to road and manned aircraft, shorter delivery time, and the ability to carry heavy payloads, it is important to recognize that UAVs can be used for a wide range of civil activities. With the development of these applications in full swing around the world, in addition to advanced communications technology and other related infrastructure, business demand and a favorable investment climate, clarity, definiteness and feasible regulations in the Taiwanese environment are also essential. Based on the premise of local economic strength, the technical level of the telecommunication industry, and commercial demands, Taiwan should establish a rational standard for the UAV regulatory system as soon as possible, so as to facilitate the development of UAM and to ensure the international competitiveness of the related technologies for market development © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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