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modelling algorithm » scheduling algorithm (Expand Search)
deer algorithm » search algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
elements deer » elementi per (Expand Search)
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Degree-Based Network Anonymization
Published 2020“…In this thesis, we study a new multi- objective parameterized anonymization approach that generalizes the known degree anonymization problem and attempts at improving it as a more realistic model for data security/privacy. Our model suggests a convenient privacy level for each net- work based on the standard deviation of its degrees. …”
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masterThesis -
183
A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
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184
Geographical Area Network—Structural Health Monitoring Utility Computing Model
Published 2019“…Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. …”
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185
A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
Published 2011Get full text
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masterThesis -
186
Modeling and Bias-Robust Estimation of the Acoustic Release of Chemotherapeutics from Liposomes
Published 2019“…The results suggest that the proposed algorithm, the optimal Kalman filter, performs well in modeling acoustically activated drug release from liposomes.…”
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187
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
doctoralThesis -
188
Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
Published 2022“…Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. …”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”
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191
Identification of errors-in-variables model with observation outliers based on Minimum-Covariance-Determinant
Published 2007“…The proposed algorithm has been applied to a heat exchanger data.…”
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Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models
Published 2024“…Additionally, the GRU-CNN hybrid model attained a notable accuracy of 90%. These findings establish the robustness and effectiveness of hybrid architectures in enhancing emotion recognition accuracy in Arabic speech data, presenting a novel approach for Arabic dialect sentiment analysis.…”
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195
Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta
Published 2023“…Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. …”
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196
Developing a UAE-Based Disputes Prediction Model using Machine Learning
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doctoralThesis -
197
A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…Every communication body wants to secure their data while communicating over the Internet. The internet has various benefits but the main demerit is the privacy and security and the transmission of data over insecure network or channel may happen. …”
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The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Cybersecurity has become vital in information technology, with data protection being a major priority. Despite government and corporate efforts, cybersecurity remains a significant concern. …”
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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. …”