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Autor:
Nadia Khan, Muhammad Nauman, Ahmad S. Almadhor, Nadeem Akhtar, Abdullah Alghuried, Adi Alhudhaif
Publikováno v:
IEEE Access, Vol 12, Pp 90299-90316 (2024)
In recent years, Explainable Artificial Intelligence (XAI) has attracted considerable attention from the research community, primarily focusing on elucidating the opaque decision-making processes inherent in complex black-box machine learning systems
Externí odkaz:
https://doaj.org/article/728dfda10c2648d5854b80515fa2c9df
Publikováno v:
IEEE Access, Vol 12, Pp 86043-86066 (2024)
This study explores the contemporary landscape of integrating numerical algorithms, artificial intelligence (AI), and expert methodologies within the domain of nephrology. Focusing on automation and decision support, we scrutinize the impact of numer
Externí odkaz:
https://doaj.org/article/ec0d1b5c69ed44c182abfc41b431cea4
Publikováno v:
IEEE Access, Vol 12, Pp 86728-86738 (2024)
Fence intrusion detection system (FIDS) must ideally detect all malicious intrusions without producing false alarms arising from environmental sources. Classification of intrusions can provide security personnel with additional information regarding
Externí odkaz:
https://doaj.org/article/10a69ea43c9b46d3b57204fd800bcfe4
Publikováno v:
IEEE Access, Vol 12, Pp 83154-83168 (2024)
In deep learning, various optimizers use a starting value for the learning rate. In general, this value is the one defined by default in the optimizer or chosen by the user after searching for a value giving the best performances of the studied neura
Externí odkaz:
https://doaj.org/article/68cebb31e6fc4c119bf55ccd752d715d
Publikováno v:
IEEE Access, Vol 12, Pp 82880-82896 (2024)
This paper proposes a fault location and protection method for power distribution system with Distributed generation (DG) resources, considering fault impedance. A multi-layer perceptron (MLP) Artificial Neural Network (ANN)-based approach using the
Externí odkaz:
https://doaj.org/article/3b6c63e7e64a4af6820922848694a111
Autor:
Syamsul Rizal, Yuniarti Ana Rahma
Publikováno v:
IEEE Access, Vol 12, Pp 80317-80326 (2024)
The current study presents a novel, non-invasive method for estimating both systolic and diastolic blood pressure by combining photoplethysmogram (PPG) signals with physiological data, such as sex, age, weight, height, heart rate, and BMI, using two
Externí odkaz:
https://doaj.org/article/03537603aa224308a3ea23a79bb4a50d
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 404-420 (2024)
Goal: Augment a small, imbalanced, wound dataset by using semi-supervised learning with a secondary dataset. Then utilize the augmented wound dataset for deep learning-based wound assessment. Methods: The clinically-validated Photographic Wound Asses
Externí odkaz:
https://doaj.org/article/0dd534e396e0400a8669feb4673feb1a
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 2134-2142 (2024)
The global trend of population aging presents an urgent challenge in ensuring the safety and well-being of elderly individuals, especially those living alone due to various circumstances. A promising approach to this challenge involves leveraging Hum
Externí odkaz:
https://doaj.org/article/6dd6e0a9dca44b178cd5099b6b666f11
Publikováno v:
IEEE Access, Vol 12, Pp 78773-78786 (2024)
Accurate estimation of the state of charge (SoC) is crucial for optimizing battery performance, battery health estimation, and ensuring reliable operation. In recent years, deep learning techniques have shown promising results in capturing complex no
Externí odkaz:
https://doaj.org/article/0bc356c633d3484fa5ace6dee38295ad
Autor:
Seul Ki Hong, Yongkeun Lee
Publikováno v:
IEEE Access, Vol 12, Pp 77475-77485 (2024)
This paper presents a comprehensive study on fault identification in Hall sensors within Brushless Direct Current (BLDC) motor drives using neural networks. Detecting these faults is critical for optimizing motor performance, enhancing energy efficie
Externí odkaz:
https://doaj.org/article/34f1e27b6e394d32bde7f63b6e8d0f7d