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201
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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202
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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203
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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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 2024“…The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …”
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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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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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207
Competitive learning/reflected residual vector quantization for coding angiogram images
Published 2003“…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
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208
Design and analysis of entropy-constrained reflected residual vector quantization
Published 2002“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …”
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209
PERF solutions for distributed query optimization. (c1999)
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masterThesis -
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Communications in electronic textile systems
Published 2017“…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …”
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conferenceObject -
214
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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215
Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves
Published 2018“…The TOA data of the wave reflected from the damage is used in the two arrival time difference and astroid algorithms to locate the damage in an enclosed area. …”
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216
Bridge Structural Health Monitoring Using Mobile Sensor Networks
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doctoralThesis -
217
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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A novel hybrid methodology for fault diagnosis of wind energy conversion systems
Published 2023“…Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …”
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Vehicular-OBUs-As-On-Demand-Fogs
Published 2020“…For instance, real-time vehicular applications require fast processing of the vast amount of generated data by vehicles in order to maintain service availability and reachability while driving. …”
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