Results 51 to 60 of about 10,517,802 (309)

Evaluation of Whale, Fruit Fly and Cuckoo Search Algorithms in Optimizing Multi-Objective Operation of Golestan Dam Reservoir Based on Multi-Criteria Decision-Making Method [PDF]

مهندسی منابع آب, 2020
In this research, after introducing the Whale, Cuckoo search and fruit fly Multi-Objective Optimization Algorithms, their performance individually and compared to each other was evaluated to optimize the Golestan Dam reservoir operation policies with an ...
Alireza Donyaii, Amirpouya Sarraf, hassan ahmadi   +2 more
doaj  

Optimizing Daylight and Energy Consumption for Climate Change Adaptation: Integrating an Artificial Neural Network Model with a Multi-Objective Optimization Approach

Engineering Proceedings, 2023
Machine learning models have been proven for their capability to improve the computational efficiency of building performance simulations. However, studies on their reliability to produce Pareto front solutions for multi-objective optimization are ...
Nur Nasuha Abd Salam, Simon Lannon
doaj   +1 more source

Multi-objective reliability based design optimization of coupled acoustic-structural system

Engineering structures, 2019
Vibro-acoustic optimization for coupled acoustic-structural system signifies one of the key topics of research to improve its performances. However, majority of the studies have not considered the presence of uncertainties while it has been shown that a ...
K. Dammak, A. El Hami
semanticscholar   +1 more source

Blood RNA Biomarker Signatures for Early Diagnosis and Prognosis in Ischemic and Hemorrhagic Stroke: The IBIS‐CT1 Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau, Marie Bruguet, Irina Viakhireva‐Dovganyuk, François‐Mathias Merrien, Denis Marechal, Aurore Jourdain, Philippe Goas, Jordan Coris, Julien Asselineau, Maëlys Consigny, Gérald Le Gac, Serge Timsit   +11 more
wiley   +1 more source

New simulation-based frameworks for multi-objective reliability-based design optimization of structures

Applied Mathematical Modelling, 2018
In the present study, two new simulation-based frameworks are proposed for multi-objective reliability-based design optimization (MORBDO). The first is based on hybrid non-dominated sorting weighted simulation method (NSWSM) in conjunction with iterative
N. S. Hamzehkolaei, M. Miri, M. Rashki
semanticscholar   +1 more source

Baseline Neuroinflammation Stratifies TSPO‐PET Response to Disease‐Modifying Therapy in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate which baseline clinical and imaging characteristics best predict TSPO‐PET‐measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker‐based clinical trials targeting glial activation.
Marlene T. Morch, Markus Matilainen, Giulia N. Baldrighi, Marjo Nylund, Maija Saraste, Laura Airas   +5 more
wiley   +1 more source

Deep reinforcement learning-driven multi-objective optimization and its applications on lighting infrastructure operation and maintenance strategy

Scientific Reports
This study addresses the challenges facing tunnel lighting system maintenance, where conventional single-objective optimization strategies and traditional maintenance approaches struggle to balance multidimensional requirements.
Zhiliu Wang, Jiabao Tang, Pengda Wei, Wenhao Lun, Yulong Wang, Weihong Yang, Hui Xiao   +6 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Multi-Objective Metrics to Evaluate Deduplication Approaches

IEEE Access, 2017
Data deduplication is a lossless compression technology that has been widely used in storage systems for space optimization. However, due to the removal of redundant data, the data deduplication has negative influences on data writing, data reading, and ...
Yujuan Tan, Zhichao Yan
doaj   +1 more source

Integrating Patient‐Reported Quality Measures in Systemic Lupus Erythematosus: Development of the American College of Rheumatology Implementation Guide

Arthritis Care &Research, EarlyView.
Objective To support high‐quality, patient‐centered care for systemic lupus erythematosus (SLE), the American College of Rheumatology (ACR) developed evidence‐based measures incorporating clinical and patient‐reported outcome measures (PROMs). Using the Consolidated Framework for Implementation Research (CFIR), we conducted semistructured interviews ...
Catherine Nasrallah, Cherish Wilson, Christine Hariz, Christie M. Bartels, Shanthini Kasturi, Wambui Machua, Amy Bennett, Kate Chiseri, Allison Plitman, Starla Hairston Blanks, April Jorge, Patti Katz, Jinoos Yazdany, Shivani Garg   +13 more
wiley   +1 more source