Publications associées à Offre et demande

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

David Atienza Alonso, Marina Zapater Sancho, Ali Pahlevan, Xiaoyu Qu

Modern cloud data centers (DCs) need to tackle efficiently the increasing demand for computing resources and address the energy efficiency challenge. Therefore, it is essential to develop resource provisioning policies that are aware of virtual machine (VM ...

2018

Dispatch and Primary Frequency Control with Electrochemical Storage: a System-wise Verification

Mario Paolone, Fabrizio Sossan, Mokhtar Bozorg, Yihui Zuo

Uncertainty levels in forecasting of renewable generation and demand are known to affect the amount of reserve required to operate the power grid with a given level of reliability. In this paper, we quantify the effects on the system reserve and reliabilit ...

IEEE2018

A Lagrangian relaxation technique for the demand-based benefit maximization problem

Michel Bierlaire, Shadi Sharif Azadeh, Virginie Janine Camille Lurkin, Meritxell Pacheco Paneque, Bernard Gendron

Discrete choice models are the state-of-the-art of demand modeling at the disaggregate level. Their integration with Mixed Integer Linear Programming (MILP) models provides a better understanding of customers' preferences to operators while planning for t ...

2018

Ultrafast optical ranging using microresonator soliton frequency combs

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts

Light detection and ranging is widely used in science and industry. Over the past decade, optical frequency combs were shown to offer advantages in optical ranging, enabling fast distance acquisition with high accuracy. Driven by emerging high-volume appli ...

2018

Evaluating the Critical Roles of Precursor Nature and Water Content When Tailoring Magnetic Nanoparticles for Specific Applications

Assil Bouzid, Carlo Massobrio

Because of the broad range of application of iron oxide nanoparticles (NPs), the control of their size and shape on demand remains a great challenge, as these parameters are of upmost importance to provide NPs with magnetic properties tailored to the targe ...

AMER CHEMICAL SOC2018

Introduction to disaggregate demand models

Michel Bierlaire, Virginie Janine Camille Lurkin

Demand information is an input for a great deal of operations research models. Assumed as given in many problem instances addressed in the literature, demand data are difficult to generate. In this tutorial, we provide an introduction to disaggregate deman ...

2017

Recent advances in nanoplasmonic biosensors: applications and lab-on-a-chip integration

Maria Soler Aznar

Motivated by the recent progress in the nanofabrication field and the increasing demand for cost--effective, portable, and easy-to-use point-of-care platforms, localized surface plasmon resonance (LSPR) biosensors have been subjected to a great scientific ...

Walter De Gruyter Gmbh2017

Data-driven Demand Response Modeling and Control of Buildings with Gaussian Processes

Colin Neil Jones, Xuan Truong Nghiem

This paper presents an approach to provide demand response services with buildings. Each building receives a normalized signal that tells it to increase or decrease its power demand, and the building is free to implement any suitable strategy to follow the ...

2017

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Offre et demande

Adding flexibility to multi-tenant networks

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

Improved stability of optimal traffic paths

Dispatch and Primary Frequency Control with Electrochemical Storage: a System-wise Verification

A Lagrangian relaxation technique for the demand-based benefit maximization problem

Ultrafast optical ranging using microresonator soliton frequency combs

Evaluating the Critical Roles of Precursor Nature and Water Content When Tailoring Magnetic Nanoparticles for Specific Applications

Introduction to disaggregate demand models

Recent advances in nanoplasmonic biosensors: applications and lab-on-a-chip integration

Data-driven Demand Response Modeling and Control of Buildings with Gaussian Processes

Graph Chatbot

Chattez avec Graph Search

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

Data-driven Demand Response Modeling and Control of Buildings with Gaussian Processes

Adding flexibility to multi-tenant networks

A Lagrangian relaxation technique for the demand-based benefit maximization problem

Evaluating the Critical Roles of Precursor Nature and Water Content When Tailoring Magnetic Nanoparticles for Specific Applications

Introduction to disaggregate demand models

Dispatch and Primary Frequency Control with Electrochemical Storage: a System-wise Verification

Recent advances in nanoplasmonic biosensors: applications and lab-on-a-chip integration

Improved stability of optimal traffic paths

Ultrafast optical ranging using microresonator soliton frequency combs