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201
A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …”
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202
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203
Lung nodule classification utilizing support vector machines
Published 2002“…The SVM classifier is trained with features extracted from 30 nodule images and 20 non-nodule images, and is tested with features out of 16 nodule/non-nodule images. …”
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204
Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles
Published 2000“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
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205
A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study
Published 2022“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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206
Exploring new horizons in neuroscience disease detection through innovative visual signal analysis
Published 2024“…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …”
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207
Vibration suppression in a cantilever beam using a string-type vibration absorber
Published 2017“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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208
Supervised term-category feature weighting for improved text classification
Published 2022“…Training the ANN using the gradient descent algorithm allows updating the term-category matrix until reaching convergence. …”
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209
An effective design system for dynamically reconfigurable architectures
Published 2017“…In this paper, we use the Joint Photographic Experts Group (JPEG) image compression algorithm as a design example to demonstrate the effectiveness of dynamic reconfiguration achieved using SPARCS. …”
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210
Single-channel speech denoising by masking the colored spectrograms
Published 2025“…In this paper, a novel SD technique is proposed that masks the colored spectrogram. U-Net (a deep neural network fundamentally developed for image segmentation) is trained on the noisy log-powered colored spectrograms (LPcS), using the binarized Mel spectrograms as ground truth (GT). …”
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211
The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review
Published 2022“…The most common signal normalization and feature extractions in the included studies were the bandpass filter and wavelet-based feature extraction. We categorized the studies based on AI techniques, such as machine learning and deep learning. …”
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212
A Terrain classification system for coseismic landslide hazard analysis: Lebanon, a case study
Published 2014“…Terrain susceptible to rock failures, shallow and deep soil failures, and lateral spreading were identified and assessed. …”
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213
STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization
Published 2025“…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …”
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214
Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
Published 2024“…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …”
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215
Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates
Published 2022“…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. …”
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216
Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation
Published 2024“…The latter is trained using the gradient descent algorithm allowing to iteratively update the term-category matrix until reaching convergence. …”
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217
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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218
Automated skills assessment in open surgery: A scoping review
Published 2025“…In this scoping review, we present the open surgeries and clinical settings where AI-based skill assessment has been applied, the kind of surgical data acquired for the AI-based algorithms, and the types of AI-based models used for automated skills assessment. …”
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219
A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem
Published 2008“…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
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220
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. …”