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Protein structure prediction with energy minimization and deep learning approaches
In this paper we discuss the advantages and problems of two alternatives for ab initio protein structure prediction. On one hand, recent approaches...
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Minimization of Energy Functionals via FEM: Implementation of hp-FEM
Many problems in science and engineering can be rigorously recast into minimizing a suitable energy functional. We have been develo** efficient and...
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Trajectory Optimization for Propulsion Energy Minimization of UAV Data Collection
As a flexible communication manner, unmanned aerial vehicle (UAV) communication is a promising technology for wireless communication systems....
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Object tracking using local structural information and energy minimization
Object tracking is one of the fundamental processes for many high level applications in the field of machine vision. Many challenges in this field...
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Gift from Nature: Potential Energy Minimization for Explainable Dataset Distillation
Dataset distillation aims to reduce the dataset size by capturing important information from original dataset. It can significantly improve the...
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Energy Minimization vs. Deep Learning Approaches for Protein Structure Prediction
This article discusses the advantages and problems of different approaches to ab initio protein structure prediction. Recent successful approaches...
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The energy minimization algorithm for elastic optical networks
In this paper, a novel energy-aware grooming-based algorithm, named energy minimization algorithm (EMA), is proposed that aims at providing the...
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On Minimization of Nonlinear Energies Using FEM in MATLAB
Two minimization problems are added to the Moskovka and Valdman MATLAB package (2022): a Ginzburg-Landau (scalar) problem and a topology optimization...
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Image smog restoration using oblique gradient profile prior and energy minimization
Removing the smog from digital images is a challenging pre-processing tool in various imaging systems. Therefore, many smog removal (i.e.,...
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Task consolidation based power consumption minimization in cloud computing environment
Cloud Computing is playing a huge role in future technology. Further, with the explosive growth of the Internet and cloud computing, several service...
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Constrained regret minimization for multi-criterion multi-armed bandits
We consider a stochastic multi-armed bandit setting and study the problem of constrained regret minimization over a given time horizon. Each arm is...
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Infrared small target detection based on Bi-Nuclear norm minimization
Infrared small target detection (ISTD) in complex backgrounds poses significant challenges in modern applications. Existing solutions based on...
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Constrained Energy Minimization for Hyperspectral Multi-target Detection Based on Ensemble Learning
The traditional hyperspectral target detection usually recognizes a single type of object at one time. However, there are usually various categories...
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Server Selection and Resource Allocation for Energy Minimization in Satellite Edge Computing
In this paper we construct a double layer satellite network and let MEO satellites carry computing servers to execute computation tasks generated by...
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A two-dimensional OMA-NOMA user-pairing and power-minimization approach for opportunistic B5G-enabled IoT networks
The integration of cognitive radio (CR) into power domain non-orthogonal multiple access (NOMA) wireless systems has been envisioned as a promising...
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Peak Demand Minimization via Sliced Strip Packing
We study the Non-preemptive Peak Demand Minimization (NPDM) problem, where we are given a set of jobs, specified by their processing times and energy...
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An efficient multiscale topology optimization method for frequency response minimization of cellular composites
It is vital to control the vibration of cellular composites under harmonic excitation in engineering. Due to numerous design variables and expensive...
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Task Scheduling Based Optimized Based Algorithm for Minimization of Energy Consumption in Cloud Computing Environment
Allocating virtual machineries in the cloud optimally for workloads is difficult. In the cloud, finding the best way to schedule tasks is an NP-hard...
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Spin Glass Energy Minimization through Learning and Evolution
AbstractThe research considers the minimization of spin glass energy via learning and evolution. The Sherrington-Kirkpatrick spin-glass model is...
