Results 101 to 110 of about 6,652,021 (195)
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
A hybrid evolutionary framework for efficient IoT task scheduling in fog computing
Scientific ReportsThis paper proposes an innovative, hybrid approach to task scheduling and virtual machine (VM) placement in fog computing environments that aims to optimize energy efficiency and task completion for Internet of Things (IoT) applications.
Lianhe Cui
doaj +1 more source
Task-Driven Virtual Machine Optimization Placement Model and Algorithm
Future InternetIn cloud data centers, determining how to balance the interests of the user and the cloud service provider is a challenging issue. In this study, a task-loading-oriented virtual machine (VM) optimization placement model and algorithm is proposed ...
Ran Yang +3 more
doaj +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Profile-based ant colony optimization for energy-efficient virtual machine placement for energy-efficient data centers [PDF]
, 2017 Cloud computing data centers contain a large number of physical machines (PMs) and virtual machine (VMs). This number can increase the energy consumption of the data centers especially when the VMs placed inappropriately on the PMs. This paper presents a
Tang, Maolin +3 more
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Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review
Advanced Science, EarlyView.Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh +8 more
wiley +1 more source
Tenant-Based Hierarchical Virtual Machine Placement Policy in Cloud
Dianxin kexue, 2014 In the cloud ecosystem, regulating virtual machine's position can help reduce the communication cost between virtual machines and the waste of physic machine's resource.
Yanxia Zhou +4 more
doaj +2 more sources
Online traffic-aware virtual machine placement in data center networks
, 2013 Data centers rely on virtualization to provide different services over a shared infrastructure. The placement of the different services and tasks in the physical machines is crucial for the performance of the whole system.
Dias, Daniel, Costa, Luís
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Advanced Science, EarlyView.A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
Virtual Machine Placement in Cloud Environments [Elektronisk resurs]
, 2012 With the emergence of cloud computing, computing resources (i.e., networks, servers, storage, applications, and services) are provisioned as metered on-demand services over networks, and can be rapidly allocated and released with minimal management ...
Tordsson, Johan, +3 more
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