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The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
doctoralThesis -
84
Current trends and future orientation in diagnosing lung pathologies: A systematic survey
Published 2025“…These VOCs can aid in the diagnosis of lung pathologies such as pneumonia. The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…The results revealed that the RFBXSQLQC technique outperforms the existing algorithms by 19% with pattern detection accuracy, 34% minimized time complexity, 64% false-positive rate, and 31% in terms of computational overhead.…”
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Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications
Published 2023“…This review introduces set of related works of GBO where distributed into; GBO variants, GBO applications, and evaluate the efficiency of GBO compared with other metaheuristic algorithms. Finally, the conclusions concentrate on the existing work on GBO, showing its disadvantages, and propose future works. …”
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Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection
Published 2024“…Although Evolutionary Algorithms (EAs) have shown promise in the literature for feature selection, creating EAs for high dimensions is still challenging. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Sentiment analysis for Arabizi in social media. (c2015)
Published 2015“…Yalla 7abibi, it is very useful to have a data mining tool that can analyze the sentiment of Twitter users in the Arab world. …”
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masterThesis -
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An Adapted Load-Balancing implementation for Sharded Blockchains
Published 2024Get full text
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masterThesis -
93
An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network
Published 2021“…In this work, an efficient medical decision system for diabetes prediction based on Deep Neural Network (DNN) is presented. Such algorithms are state‐of‐the‐art in computer vision, language processing, and image analysis, and when applied in healthcare for prediction and diagnosis purposes, these algorithms can produce highly accurate results. …”
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Simultaneous identification of robust synergistic subnetwork markers for effective cancer prognosis
Published 2014“…<p>Accurate prediction of cancer prognosis based on gene expression data is generally difficult, and identifying robust prognostic markers for cancer remains a challenging problem. …”
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Assessment of four dose calculation algorithms using IAEA-TECDOC-1583 with medium dependency correction factor (K<sub>med</sub>) application
Published 2024“…K<sub>med</sub> is calculated for D<sub>m.m</sub> and D<sub>w.w </sub>algorithm types in bone and lung media for both photon beams. …”
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A multi-pretraining U-Net architecture for semantic segmentation
Published 2025“…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …”
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From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …”
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Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. Moving forward, a set of recommendations is derived to improve datasets collection, such as the adoption of multi-modal data collection, smart Internet of things data collection, low-cost hardware platforms and privacy and security mechanisms. …”