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processing algorithm » processing algorithms (Expand Search)
method algorithm » mould algorithm (Expand Search)
query processing » text processing (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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121
Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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122
Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility
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Parallel implementation of clique partitioning using artificial neural networks. (c2000)
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masterThesis -
125
Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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126
Scatter search for protein structure prediction. (c2008)
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masterThesis -
127
Privacy-Preserving Framework for Blockchain-Based Stock Exchange Platform
Published 2022“…<p dir="ltr">This paper presents a privacy persevering framework for a decentralized stock exchange platform, ensuring anonymity and unlinkability of the investors’ accounts and their respective trading activities. …”
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128
A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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masterThesis -
129
A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …”
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Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers
Published 2022“…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …”
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132
Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
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133
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“…We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.…”
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134
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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IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture
Published 2025“…The IoMT sector deals with valuable, confidential healthcare-related data and offers convenient, personalized healthcare services. …”
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Information warfare recovery-fighting back through the matrix. (c2012)
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masterThesis -
138
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A synchronous/asynchronous multi-master replication method. (c2007)
Published 2007Get full text
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masterThesis -
140
Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…Accordingly, a novel visualization strategy based on using power consumption micro-moments has been presented along with an example of deploying machine learning algorithms to classify the micro-moment classes and identify anomalous power usage.…”