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101
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
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doctoralThesis -
102
Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”
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Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
Published 2024“…Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. This paper proposes an adaptive Multi-layer Neural Network (MLNN) Luenberger observer-based control for altitude and attitude tracking of a quadrotor UAV. …”
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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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Corona power loss computation in bundled bipolar conductors
Published 2000“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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110
Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants
Published 2006“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
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111
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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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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114
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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115
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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conferenceObject -
116
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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conferenceObject -
117
Online Control and Optimization of Directional Drilling
Published 2020“…The objective function considered is to minimize the tracking error and drilling efforts. Detailed mathematical formulation and computer simulation were used for evaluation of the performance of the proposed techniques for both systems, based on real well data.…”
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masterThesis -
118
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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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120
A forward-backward Kalman for the estimation of time-variant channels in OFDM
Published 2005“…In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem-a structure induced by the data and channel constraints. …”
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