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181
Approximate XML structure validation technical report
Published 2014“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
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182
AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients
Published 2015“…In this paper, we propose and compare three techniques two of which are Artificial Intelligence techniques, namely C4.5 and Case-Based Reasoning, and the third one is a meta-heuristic namely genetic algorithms. The performance of the three algorithms is evaluated on a data set found in the public UCMI repository.…”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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185
The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”
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186
Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
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187
Artificial Intelligence for Skin Cancer Detection: Scoping Review
Published 2021“…Performance scores were affected by factors such as data set size, number of diagnostic classes, and techniques. …”
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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012)
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190
A Machine Learning Approach to Predicting Diabetes Complications
Published 2021Get full text
doctoralThesis -
191
Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters
Published 2025“…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …”
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192
Real-Time Implementation of GPS Aided Low Cost Strapdown Inertial Navigation System
Published 2009Get full text
doctoralThesis -
193
Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes
Published 2023“…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER<sup>+</sup>), HER2<sup>+</sup>, ER<sup>+</sup>HER2<sup>+</sup>, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”
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194
THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar
Published 2020“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”
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Copy number variations in the genome of the Qatari population
Published 2015“…Genotyping intensities and genome sequencing data from 97 Qataris were analyzed with four different algorithms and integrated to discover 16,660 high confidence CNV regions (CNVRs) in the total population, affecting ~28 Mb in the median Qatari genome. …”
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196
SemIndex: Semantic-Aware Inverted Index
Published 2017“…We provide here a new approach, called SemIndex, that extends the standard inverted index by constructing a tight coupling inverted index graph that combines two main resources: a general purpose semantic network, and a standard inverted index on a collection of textual data. We also provide an extended query model and related processing algorithms with the help of SemIndex. …”
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197
Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits
Published 2022“…Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.…”
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199
Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta
Published 2023“…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”
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