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检索条件"任意字段=22nd International Conference on Intelligent Data Engineering and Automated Learning"

共 2237 条记录，以下是11-20 订阅

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An Architecture-Based Approach to Mitigate Confidentiality Violations Using Machine learning 22

An Architecture-Based Approach to Mitigate Confidentiality V...

引用

22nd IEEE international conference on Software Architecture, ICSA 2025

作者： Niehues, Nils Hahner, Sebastian Heinrich, Robert Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798331520908

Today's software systems have become increasingly connected and complex, requiring comprehensive analysis to ensure quality properties like confidentiality. Architecture-based confidentiality analysis enables the early identification of confidentiality violations to counter data breaches effectively. However, uncertainty within the software system and its environment hinders the precise and comprehensive analysis of software architectures. Furthermore, the complexity of both architectural models and uncertainties and their outcomes impede automated model repair due to combinatorial explosion. Ultimately, software architects must manually address all confidentiality violations, which is both bothersome and error-prone. Although existing approaches can identify confidentiality violations due to uncertainty, they fall short of mitigating their effects. In this paper, we address this by utilizing machine learning in the confidentiality analysis both to evaluate the criticality of identified violations and to automatically repair them. This bridges the gap between analysis and mitigation, thereby effectively supporting software architects. Evaluation results show that logistic regression provides the best ranking of the importance of uncertainty sources. Combined with incremental testing, our approach outperforms the state of the art and achieves up to a 60-fold reduction in runtime. © 2025 IEEE.

关键词： data flow analysis

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Deep learning for sleep disorder diagnosis: Enhancing EEG Analysis with Machine learning Techniques 22

Deep learning for sleep disorder diagnosis: Enhancing EEG An...

引用

22nd international learning and Technology conference, L and T 2025

作者： Mohamed, Baher Barkat, Enfel Effat University Dept. of Electrical & Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331532215

The rising prevalence of sleep disorders highlights their disastrous effects on health, well-being, cognitive performance, memory, and learning outcomes. Sleep disorders such as insomnia and sleep apnea normally require extensive instrumentation and expertise for diagnosis, which is not always possible or even available in most cases. This work, therefore, proposes a state-of-the-art use of Machine learning (ML) to develop a model for the classification and detection of sleep patterns from electroencephalogram (EEG) signals. The model is trained on a synthetic dataset, developed using mathematical simulations of real-life EEG data. This is a novelty in this area, which allows this model to be precise yet robust without relying too much on real-world *** application bridges advanced AI techniques with real-world applications and smooths out the experience for healthcare professionals and researchers alike. This research highlights how ML might transform sleep medicine through efficient, extended solutions for EEG data analysis and sleep disorder detection. We provide a realistic EEG simulation combined with an intuitive application, a powerful platform that makes advanced sleep diagnostics more accessible and impactful, which supports the development of educational strategies or technologies. © 2025 IEEE.

关键词： Electroencephalography

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Noise Tolerance and Robustness Ranking in Machine learning Models 25th

Noise Tolerance and Robustness Ranking in Machine Learning M...

引用

25th international conference on intelligent data engineering and automated learning

作者： Padro-Ferragut, Cristina Ramirez-Quintana, Maria Jose Martinez-Plumed, Fernando Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9783031777370;9783031777387

Machine learning models often excel in controlled environments but may struggle with noisy, incomplete, or shifted real-world data. Ensuring that these models maintain high performance despite these imperfections is crucial for practical applications, such as medical diagnosis or autonomous driving. This paper introduces a novel framework to systematically analyse the robustness of Machine learning models against noisy data. We propose two empirical methods: (1) Noise Tolerance Estimation, which calculates the noise level a model can withstand without significant degradation in performance, and (2) Robustness Ranking, which ranks Machine learning models by their robustness at specific noise levels. Utilizing Cohen's kappa statistic, we measure the consistency between a model's predictions on original and perturbed datasets. Our methods are demonstrated using various datasets and Machine learning techniques, identifying models that maintain reliability under noisy conditions.

关键词： Model robustness Noise in data Machine learning Cohen's kappa Performanceevaluation

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Cognitive Radio Receiver Design Employing Pipeline Successive Approximation ADC 22

Cognitive Radio Receiver Design Employing Pipeline Successiv...

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22nd international learning and Technology conference, L and T 2025

作者： Baig, Muhammad Samee Hussein, Aziza I. Effat University Electrical and Computer Engineering Department Saudi Arabia Effat University College of Engineering Energy and Technology Research Center Saudi Arabia

ISBN: (纸本)9798331532215

Smart cities require better cellular communication, incorporating a high data rate that satisfies the Internet, cloud computing, and the Internet of Things (IoT) requirements. A high data rate demands higher bandwidth with low latency. However, the already saturated or underutilized frequency spectrum hinders this realization. 5G and cognitive radio technology can enhance spectrum utilization to meet the high data demands of future cellular communication. Cognitive radio uses spectrum sensing to identify underutilized frequencies without interfering with licensed users, addressing the scarcity of the electromagnetic spectrum. In this paper, a cognitive radio receiver design with a SAR analog-to-digital converter, which is recognized for having a modest resolution for high bandwidth signals, is implemented. Moreover, the pipeline technique in the SAR design is proposed to increase the resolution to be suitable for 5G applications. The high-level model of the system is simulated using MATLAB Simulink software. The quantization error observed in the regular SAR ADC design is compared to that in the proposed pipeline SAR ADC, highlighting the enhanced accuracy and efficiency of the pipeline SAR ADC, which makes it suitable for spectrum sensing in next-generation cognitive radio systems. © 2025 IEEE.

关键词： Bandwidth

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Modeling and Simulation of Grid-Connected PV System Faults Using MATLAB/Simulink 22

Modeling and Simulation of Grid-Connected PV System Faults U...

引用

22nd international learning and Technology conference, L and T 2025

作者： Alkhawaja, Mayar Miguel, Sandy Shabab, Moutaz Abu Eddin Za'ter, Muhy Batarseh, Majd Ghazi Princess Sumaya University for Technology Electrical Engineering Department Amman Jordan King Abdullah University of Science and Technology Now With the Electrical and Computer Engineering Saudi Arabia University of Central Florida Now With the College of Engineering and Computer Science Orlando United States University of Colorado Boulder Electrical and Computer Engineering Boulder United States

ISBN: (纸本)9798331532215

Grid-connected photovoltaic (PV) systems are crucial to modern renewable energy strategies, but various types of faults can significantly impact their performance. Understanding the behavior of these faults is essential for improving system reliability and reducing maintenance costs. This paper investigates the impact of common faults, including open-circuit, short-circuit, partial shading, and grid faults, by simulating them using MATLAB/Simulink. The focus is on modeling faults that lead to power output reduction. The simulation results demonstrate how different fault types affect critical system parameters, such as grid voltage and active power output. The study highlights the value of simulation as a flexible approach for exploring fault scenarios, providing insights into fault detection and mitigation strategies that can help optimize PV system performance and support the development of robust fault data collection, detection, and classification techniques. © 2025 IEEE.

关键词： Power distribution faults

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engineering Quantum Dots: Overcoming Challenges in Telecommunications and Human-Machine Interaction 22

Engineering Quantum Dots: Overcoming Challenges in Telecommu...

引用

22nd international learning and Technology conference, L and T 2025

作者： Majid, M.A. Effat University College of Engineering Electrical and Computer Engineering Department Saudi Arabia

ISBN: (纸本)9798331532215

engineering the inhomogeneity, density, composition, and aspect ratio of self-assembled quantum dots (SAQDs) is essential for various applications, from broadband technologies to telecommunications. This paper investigates the optimization of molecular beam epitaxy (MBE) grown quantum dots in the intrinsic region of optoelectronic devices, such as lasers, highlighting the need for tailored approaches based on specific applications. For instance, superluminescent diodes used for imaging require highly inhomogeneous dots, while inhomogeneity can pose challenges for SAQD lasers in telecommunications, as non-homogeneous QDs may become parasitic and hinder lasing efficiency. This study explores quantum dot lasers by adjusting the thickness of the GaAs spacer layers, which are grown at low temperatures and situated between the dot layers. Our findings reveal enhanced performance in SAQD laser structures, achieving "no blue shift"in peak emission wavelengths - critical for human-machine interaction and photonic integrated circuit applications. Maintaining stable emission wavelengths significantly boosts the efficiency of communication systems and quantum computing platforms, facilitating rapid data processing and interaction between machines and users. © 2025 IEEE.

关键词： Quantum dot lasers

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data, Information and Computing Science - Proceedings of the 2nd international conference, CDICS 2024

Data, Information and Computing Science - Proceedings of the...

引用

2nd international conference on data, Information and Computing Science, CDICS 2024

ISBN: (纸本)9781643685762

The proceedings contain 10 papers. The topics discussed include: comparative analysis of deep learning methods for automated diagnosis of pulmonary diseases from chest X-ray images: a study based on ICD-10;deep residual learning for fruits of ceremonial plants recognition;PiVisionSort: integrating image processing and machine learning for material recognition on conveyor belts;intelligent detection of potholes using SSD algorithm and auto-alert notification system for user;the use of motion and gaze features to detect speaking intention in VR-mediated communication environments;optimized retinal vessel segmentation using IS-Net and high-resolution dataset;a framework for adopting machine learning in the clinical domain;and a study on a domain BERT-based named entity recognition method for faulty text.

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Strategies for Effective EEG Preprocessing 22

Strategies for Effective EEG Preprocessing

引用

22nd international learning and Technology conference, L and T 2025

作者： Salem, Nema Alamoudi, Nora Mustafa, Lama Bagais, Fatima Effat University Electrical Research Laboratory College of Engineering Jeddah Saudi Arabia Effat University College of Engineering Department of Electrical and Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331532215

The administration of anesthesia is critical for ensuring the safety of surgical procedures, yet it comes with inherent risks associated with medication mistakes. Monitoring EEG signals during anesthesia is crucial for understanding patient physiology;however, the accuracy of this information heavily relies on effectively eliminating noise. Decreasing noise in EEG signals is vital for accurately interpreting data, ultimately enhancing patient safety and refining anesthesia management. This research concentrates on an advanced preprocessing technique for EEG signals, employing segmentation, detrending, variational mode decomposition (VMD), and noise reduction through Gaussian filtering, moving averages, Independent Component Analysis (ICA), and Discrete Wavelet Transform (DWT). The study utilized EEG data collected during surgeries and applied these preprocessing approaches to reduce noise and artifacts. Our results indicate that employing the Discrete Wavelet Transform (DWT) for denoising is robust and produces superior outcomes compared to other techniques investigated, achieving a high Signal-To-Noise Ratio (SNR) of 43.23 dB. © 2025 IEEE.

关键词： Anesthesia Discrete Wavelet Transform EEG preprocessing Gaussian Independent Component Analysis Moving average Noise removal SDG 17

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Glaucoma Diagnosis with Fundus Image Analysis Using Cup-To-Disc Ratios 22

Glaucoma Diagnosis with Fundus Image Analysis Using Cup-To-D...

引用

22nd international learning and Technology conference, L and T 2025

作者： Salem, Nema Mateen, Kulsoom Alharbi, Wafa Sarfaraz, Safiya Effat University Department of Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331532215

Glaucoma, a leading cause of irreversible blindness globally, manifests as a gradual, stealthy progression of ocular structural changes that pose challenges for early detection. Attentive monitoring and proactive measures are essential to mitigate vision loss linked to this condition. The Cup-To-Disc Ratio (CDR) plays a pivotal role in identifying and assessing glaucoma. By comparing the dimensions of the optic cup with those of the optic disc, the CDR provides vital insights into disease progression and severity. Our study employed image processing techniques to calculate the CDR and explored its correlation with glaucomatous and healthy fundus images. Our analysis revealed significant variations in CDR values between images indicating glaucoma and those depicting normal ocular states. Particularly noteworthy is our successful differentiation of these two categories using a threshold value of 0.5. The model achieved an accuracy of 73.33%, with sensitivity and specificity values of 67% and 80%, respectively, highlighting CDR's diagnostic utility in assessing glaucoma. © 2025 IEEE.

关键词： Clock and data recovery circuits (CDR circuits)

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Enhancing 6G-Satellite Network Integration with Artificial Intelligence: A Future Communication Paradigm 22

Enhancing 6G-Satellite Network Integration with Artificial I...

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22nd international learning and Technology conference, L and T 2025

作者： Salah, Ibrahim Hussein, Aziza I. Wageh Lotfy, Mostafa Mabrook, Mohamed Mourad Almaaqal University College of Engineering Control and Computer Department Basrah61001 Iraq Effat University College of Engineering Energy and Technology Research Center Saudi Arabia Faculty of Technology and Education Beni-Suef University Dept. of Process Control Technology Beni-Suef Egypt Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt

ISBN: (纸本)9798331532215

The integration of 6G networks and satellite communications is set to revolutionize global connectivity, offering seamless coverage across terrestrial and non-terrestrial environments. Artificial Intelligence (AI) is essential for improving this integration, addressing challenges such as dynamic resource management, latency reduction, and network optimization. AI techniques like machine learning, deep learning, and reinforcement learning offer innovative solutions to handle the complexities of 6G-satellite networks. These advancements promise to significantly improve network efficiency, enhance data transmission reliability, and ensure seamless connectivity across different areas. Potential use cases include smart cities, autonomous vehicles, and Internet of Things (IoT) applications, where AI-driven 6G-satellite integration will be crucial. The proposed AI-enhanced 6G-satellite framework not only addresses current challenges but also lays the groundwork for a resilient, scalable, and globally interconnected communication infrastructure, offering a promising future. © 2025 IEEE.

关键词： Satellite communication systems

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