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41
Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning
Published 2020Get full text
doctoralThesis -
42
Practical Considerations in Frequency Diverse Array Radar Signal Processing
Published 2021Get full text
doctoralThesis -
43
Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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44
Machine Learning Model for a Sustainable Drilling Process
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doctoralThesis -
45
Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials
Published 1997“…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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46
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47
A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs
Published 2024“…Despite this, concerns about the accuracy and function of automated diagnosis remain among patients. …”
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48
Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks
Published 2019“…We formulate the problem as a mixed integer program, and propose an efficient meta-heuristic solution based on the ions motion optimization algorithm. The performance of the meta-heuristic solution is evaluated and compared to the optimal solution as a function of various system parameters and for different application use cases. …”
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49
A simplified sliding‐mode control method for multi‐level transformerless DVR
Published 2022“…Second, an effective method based on charging/discharging conditions of DC capacitors is proposed for balancing capacitor voltages using relevant switching state rather than combining DC voltage error with the inductor current error through a suitable weighting factor in forming the cost function. Therefore, the weighting factor necessity in the control algorithm is eliminated. …”
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50
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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51
Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Published 2021Get full text
doctoralThesis -
52
Reinforcement Learning-Based School Energy Management System
Published 2020“…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”
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53
Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques
Published 2025“…In the first stage, the WPT is used to split the PV voltage and string currents into specific sub-band frequencies, and then EMD is used to decompose the selected frequency bands into a number of intrinsic mode functions (IMFs) and a residual. The generated IMF components are then fed into the Random Forest (RF) algorithm designed for shading detection and classification. …”
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54
Defense against adversarial attacks: robust and efficient compressed optimized neural networks
Published 2024“…A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. …”
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55
Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System
Published 2025“…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”
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56
Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces
Published 2021“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”
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57
A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications
Published 2011“…We evaluate and optimize the performance of the proposed adaptive compression scheme using experimental measurements in different scenarios and as a function of various parameters. Energy consumption results demonstrate that the proposed scheme achieves notable energy reduction gains when compared to other traditional approaches. …”
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58
Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer
Published 2007Get full text
doctoralThesis -
59
Parallel tabu search in a heterogeneous environment
Published 2003“…We discuss a parallel tabu search algorithm with implementation in a heterogeneous environment. …”
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60
DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
Published 2025“…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …”
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