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2041
A Computable Phenotype Algorithm for Postvaccination Myocarditis/Pericarditis Detection Using Real-World Data: Validation Study
Published 2024-11-01“…ResultsThe algorithm required 200-250 hours to implement and optimize. …”
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2042
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2043
BESO Topology Optimization Driven by an ABAQUS-MATLAB Cooperative Framework with Engineering Applications
Published 2025-04-01“…The Bi-directional Evolutionary Structural Optimization (BESO) method, owing to its algorithmic simplicity and strong scalability, has emerged as one of the most prevalent topology optimization methodologies in current research and industrial applications. …”
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2044
Post-Anesthesia Care Unit (PACU) readiness predictions using machine learning: a comparative study of algorithms
Published 2025-03-01“…Machine learning algorithms offer a promising solution by leveraging large amounts of patient data to predict optimal discharge times. …”
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2045
Enhancing Coverage and Efficiency in Wireless Sensor Networks: A Review of Optimization Techniques
Published 2024-09-01“…To address these issues, coverage optimization techniques are employed to maximize spatial coverage while minimizing energy consumption and deployment costs. …”
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2046
Optimal Zero-Defect Solution for Multiple Inspection Items in Incoming Quality Control
Published 2025-04-01Get full text
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2047
AI-Driven Optimization of Breakwater Design: Predicting Wave Reflection and Structural Dimensions
Published 2025-01-01“…Further, the objective is to achieve controlled wave reflection allowing a specific wave run-up and optimized energy dissipation, while ensuring maritime stability. …”
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2048
OPTIMIZATION-BASED APPROACH TO TILING OF FINITE AREAS WITH ARBITRARY SETS OF WANG TILES
Published 2017-11-01Get full text
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2049
A Computational Sketch-Based Approach Towards Optimal Product Design Solutions
Published 2025-02-01“…The proposed approach enables the transformation of simple hand-drawn sketches into digital models suitable for complex computational simulations and design optimization. Using computer vision algorithms, sketches are processed to generate digital design components that serve as inputs for Finite Element Analysis (FEA). …”
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2050
Thermal-Aware Test Schedule and TAM Co-Optimization for Three-Dimensional IC
Published 2012-01-01“…We used both greedy and simulated annealing algorithms to solve this optimization problem. We compare the results of two assumptions: soft-die mode and hard-die mode. …”
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2051
Optimization of High-Performance Computing Job Scheduling Based on Offline Reinforcement Learning
Published 2024-12-01“…Experimental results demonstrate that, compared to heuristic and online DRL algorithms, the proposed approach achieves more efficient scheduling performance across various workloads and optimization goals, showcasing its practicality and broad applicability.…”
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2052
Research on coal mine robot positioning algorithm based on integration of ORB-SLAM3 vision and inertial navigation
Published 2025-06-01“…According to the principle of tight coupling of visual inertial navigation, the residual function of the whole positioning system is constructed by fusing visual residual error and IMU residual error, and the sliding window BA algorithm based on nonlinear optimization is used to iteratively optimize the residual function to obtain accurate pose estimation of the mobile robot. …”
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2053
Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising
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2054
ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space
Published 2025-05-01“…This paper proposes a novel improved crisscross optimization (ICSO) algorithm, a hybrid evolutionary approach that integrates crisscross optimization and perturbation mechanisms to find the suitable latent vector. …”
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2055
Optimal Low-Carbon Scheduling for Smart Microgrids With Dynamic Thermal Capacity Constraints
Published 2025-01-01“…This study aims to integrate electric vehicles, photovoltaic and battery energy storage systems, and distribution network information in a microgrid to achieve decarbonized optimal operation. Under the different operating states of distribution networks, the paper proposes a decarbonized two-stage deeply integrated operational mode for a photovoltaic, battery energy storage system, and electric vehicles integrated microgrid, incorporating the electricity market to optimize overall revenue. …”
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2056
Optimizing Inotropic Infusion With Cluster Specific AI Decision Models and Digital Twins
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2057
Machine Learning‐Enhanced Optimization for High‐Throughput Precision in Cellular Droplet Bioprinting
Published 2025-05-01“…To address these obstacles, machine learning is employed to optimize five critical printing parameters (i.e., bioink viscosity, nozzle size, printing time, printing pressure, and cell concentration), and develop algorithms capable of immediate cellular droplet size prediction. …”
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2058
Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment
Published 2025-04-01“…This study reviews the potential of artificial intelligence (AI) to optimize ICI therapy in melanoma by integrating various diagnostic tools. …”
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2059
Integrating IT and OT for Cybersecurity: A Stochastic Optimization Approach via Attack Graphs
Published 2025-01-01“…The defense strategies identified by our approach demonstrate that robust security protection can be achieved with optimal resource allocation, providing robust protection while minimizing implementation costs across the most critical vulnerabilities in the manufacturing network.…”
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2060
Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility
Published 2025-02-01“…This approach has resulted in models that are able of approximating complex simulations with high accuracy (less than 17% percentage error for the worst case) and significantly reduced inference time (ranging from 2 to 6 orders of magnitude) while being differentiable. The substantial speed-up factors enable the application of online reinforcement learning algorithms, and the differentiable nature of the models allows for seamless integration with differentiable programming techniques, facilitating the solving of inverse problems to find the optimal parameters for a given objective. …”
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