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Low-rank matrix recovery via novel double nonconvex nonsmooth rank minimization with ADMM
In recent years, using the low-rank structure of the data to recover the matrix has become one of the hot issues in image processing. However, it...
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Holonic Energy Management Systems: Towards Flexible and Resilient Smart Grids
The increasing global warming and soaring fossil fuel prices have made energy generation minimization a crucial objective. As a result, the relevance...
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Malleable Techniques and Resource Scheduling to Improve Energy Efficiency in Parallel Applications
The high energy consumption of computing platforms has become one of the major problems in high-performance computing (HPC). Computer energy...
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Experimental Study of Algorithms for Minimization of Binary Decision Diagrams Using Algebraic Representations of Cofactors
AbstractBinary decision diagram (BDD) is used for technology-independent optimization, performed as the first stage in the synthesis of logic...
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Classes of linear programs solvable by coordinate-wise minimization
Coordinate-wise minimization is a simple popular method for large-scale optimization. Unfortunately, for general (non-differentiable and/or...
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Deep Reinforcement Learning-based Power Control and Bandwidth Allocation Policy for Weighted Cost Minimization in Wireless Networks
Mobile edge computing (MEC) can dispatch its powerful servers close by to assist with the computation workloads that intelligent wireless terminals...
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Geometric Programming (GP) Based Processor Energy Minimization Model for DVS Enabled Real-Time Task Set System
An analytical processor-level energy model to overcome power walls in communication and computation-intensive mobile applications is proposed. In...
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Kidney segmentation in MR images using active contour model driven by fractional-based energy minimization
In the field of diagnosis and treatment planning of kidney-related diseases, accurate kidney segmentation is challenging due to intensity...
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Constraint Energy Minimizing Generalized Multiscale Finite Element Method for Highly Heterogeneous Compressible Flow
This work presents a Constraint Energy Minimizing Generalized Multiscale Finite Element Method (CEM-GMsFEM) for solving a single-phase compressible...
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Construction of energy minimized WSN using GA-SAMP-MWPSO and K-mean clustering algorithm with LDCF deployment strategy
Energy is the most valuable resource in WSN. As the power storage capability of the tiny WSN is very limited, efficient mechanisms for energy...
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A Hybrid Genetic Algorithm for Optimal Active Power Curtailment Considering Renewable Energy Generation
This paper analyzes the application of a population-based algorithm and its improvement in solving an optimal power flow problem. Simulations were...
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Energy efficient routing and secured data transmission in the IoV: Improved deep learning model for energy prediction
In the Internet of Vehicles (IoV), vehicle data exchange for cooperative assessment can enhance the experience of driving along with service quality....
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Fog Intelligence for Energy Optimized Computation in Industry 4.0
The field of communication and computation is experiencing ongoing expansion with the emergence of Industry 4.0 technology enabling efficient data...
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Exploring Ductal Carcinoma In-Situ to Invasive Ductal Carcinoma Transitions Using Energy Minimization Principles
Ductal carcinoma in-situ (DCIS) presents a risk of transformation to malignant intraductal carcinoma (IDC) of the breast. Three tumor suppressor...
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Constraint programming versus heuristic approach to MapReduce scheduling problem in Hadoop YARN for energy minimization
In this paper, we consider a deadline-constrained MR scheduling problem of minimizing energy consumption in Hadoop’s generic resource manager known...
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Storage System for Energy Communities
Energy communities play a critical role as stakeholders in modern power grids. However, operating such communities can be challenging due to the...
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Medical image fusion algorithm based on L0 gradient minimization for CT and MRI
In this paper, a novel medical image fusion method based on L 0 Gradient Minimization for CT and MRI is proposed. Compared with traditional...
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Allegro-Legato: Scalable, Fast, and Robust Neural-Network Quantum Molecular Dynamics via Sharpness-Aware Minimization
Neural-network quantum molecular dynamics (NNQMD) simulations based on machine learning are revolutionizing atomistic simulations of materials by...
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Energy-Based Policy Constraint for Offline Reinforcement Learning
Offline RL suffers from the distribution shift problem. One way to address this issue is to constrain the divergence between the target policy and...