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201
An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition
Published 2025Get full text
doctoralThesis -
202
Ensemble Deep Random Vector Functional Link Neural Network for Regression
Published 2022“…Subsequently, we propose a novel regularization method [boosted factor (BF)], two dRVFLs variants [edRVFL with skip connection (edRVFL-SC) and edRVFL with random skip connections (edRVFL-RSC)] and one strategy [ensemble skip connection edRVFL (esc-edRVFL)] which show significant improvement over the original dRVFL. The BF is a newly introduced hyperparameter to scale the values of the activated hidden neurons to accommodate the diversity of the data, and it is also able to filter the neurons. edRVFL-SC and edRVFL-RSC are the edRVFL variants with skip connections. …”
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203
A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities
Published 2021“…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …”
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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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207
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…The most prominent topic, observed in over half of the analyzed studies, was “the impact of COVID-19.”…”
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”
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210
Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…This work investigates occupancy detection methods to develop an efficient system for processing sensor data while providing accurate occupancy information. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …”
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212
An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication
Published 2019“…Of late, within the ambit of control of systems over networks, event-triggered control has proved to be instrumental in ensuring acceptable closed-loop performance while respecting bandwidth constraints of the underlying network. …”
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213
Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
Published 2024“…<p dir="ltr">Over the past decade, Unmanned Aerial Vehicles (UAVs) have attracted significant attention due to their potential applications in emergency-response applications, including wireless power transfer (WPT) and data collection from Internet of Things (IoT) devices in disaster-affected areas. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”
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215
Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter
Published 2023“…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”
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PERF solutions for distributed query optimization. (c1999)
Published 1999Get full text
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masterThesis -
218
Design and analysis of entropy-constrained reflected residual vector quantization
Published 2002“…Jointly optimized RVQ (JORVQ) is an effective design algorithm for minimizing the overall quantization error. …”
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article -
219
A survey and comparison of wormhole routing techniques in a meshnetworks
Published 1997“…They consist of many processing nodes that interact by sending messages (containing both data and synchronization information) over a communication link, between nodes. …”
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220
Optimizing ADWIN for Steady Streams
Published 2022“…However, online machine learning comes with many challenges for the different aspects of the learning process, starting from the algorithm design to the evaluation method. …”
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