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lower optimization » motor optimization (Expand Search), global optimization (Expand Search), spider optimization (Expand Search)
level optimization » global optimization (Expand Search), based optimization (Expand Search)
lower optimization » motor optimization (Expand Search), global optimization (Expand Search), spider optimization (Expand Search)
level optimization » global optimization (Expand Search), based optimization (Expand Search)
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1
Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021Get full text
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2
Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
doctoralThesis -
3
Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery
Published 2018Get full text
doctoralThesis -
4
Optimizing clopidogrel dose response
Published 2016“…A reduced function of the gene variant of the CYP2C19 has been associated with lower drug metabolite levels, and hence diminished platelet inhibition. …”
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5
Exploiting Sparsity in Amplify-and-Forward Broadband Multiple Relay Selection
Published 2019“…Therefore, to solve this problem and enhance the spatial and frequency diversity orders of large amplify and forward cooperative communication networks, in this paper, we develop three multiple relay selection and distributed beamforming techniques that exploit sparse signal recovery theory to process the subcarriers using the low complexity orthogonal matching pursuit algorithm (OMP). In particular, by separating all the subcarriers or some subcarrier groups from each other and by optimizing the selection and beamforming vector(s) using OMP algorithm, a higher level of frequency diversity can be achieved. …”
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6
A multi-objective planning approach for optimal DG allocation for droop based microgrids
Published 2021“…The proposed formulation is compared to existing planning algorithms for droop-based microgrids. The re-sults show that including the secondary control region in the optimization problem achieves lower volt-age deviations and no frequency deviations at all demand levels. …”
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7
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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8
Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations
Published 2021Get full text
doctoralThesis -
9
Blood Glucose Regulation Modelling and Intelligent Control
Published 2024Get full text
doctoralThesis -
10
Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP
Published 2021Get full text
doctoralThesis -
11
Energy-Aware Physical Synthesis of Deep Neural Networks for Edge-AI Applications in Robotics and VLSI Systems
Published 2025“…Energy-aware physical synthesis is essential for deploying deep neural networks (DNNs) in edge-AI applications for robotics and VLSI systems, where stringent power, area, and latency constraints prevail. Beyond algorithm-and software-level optimizations such as network compression and compiler techniques, the physical effects during VLSI imple-mentation including clock tree synthesis (CTS), routing congestion, IR-drop, cell sizing, and placement significantly influence energy consumption and timing closure. …”
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12
State-of-Charge Estimation Using Triple Forgetting Factor Adaptive Extended Kalman Filter for Battery Energy Storage Systems in Electric Bus Applications
Published 2025“…Nevertheless, considering system complexity and computational efforts, the suggested SoC estimate techniques fall short of providing optimal filtering performance with high noise levels. …”
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13
Reinforcement Learning-Based School Energy Management System
Published 2020“…In this work, a Deep Reinforcement Learning agent is proposed for controlling and optimizing a school building’s energy consumption. It is designed to search for optimal policies to minimize energy consumption, maintain thermal comfort, and reduce indoor contaminant levels in a challenging 21-zone environment. …”
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Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d...
Published 2020“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”
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15
MoveSchedule
Published 1995“…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …”
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masterThesis -
16
A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications
Published 2011“…The proposed scheme monitors the signal strength level during the file transfer process and compresses data blocks on-the-fly only whenever energy reduction gain is expected. …”
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