Publications related to Optimal Design of Magnetorheological Valve Integrated in an Intelligent Footwear for Diabetic Patients with Foot Insensitivity

Related publications (19)

A shortcut model for batch distillation columns using pertinent effective factors

A shortcut model is a low-order model that provides a simplified representation of a complex process, thereby enabling faster and more efficient analysis, design and optimization without the computational intensity of a full-scale model. For continuous dis ...

Elsevier2025

Convex Computation of Value-at-risk Bounds for Stochastic Processes

Matteo Raphael Tacchi

This article formulates algorithms to upper-bound the maximum value-at-risk (VaR) of a state function along trajectories of stochastic processes. The VaR is upper bounded by two methods: minimax tail-bounds (Cantelli/Vysochanskij-Petunin) and Expected Shor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

Philippe Schwaller, Jeff Guo

Synthesizability in generative molecular design remains a pressing challenge. Existing methods to assess synthesizability include heuristics-based metrics or retrosynthesis models which predict a synthetic pathway. By contrast, an explicit approach anchors ...

ROYAL SOC CHEMISTRY2025

SOStab: A Matlab toolbox for transient stability analysis

Colin Neil Jones

This paper presents a new Matlab toolbox, aimed at facilitating the use of polynomial optimization for stability analysis of nonlinear systems. In the past decade several decisive contributions made it possible to recast this type of problems as convex opt ...

Elsevier2024

Computational models of episodic-like memory in food-caching birds

Wulfram Gerstner, Johanni Michael Brea

How the 'what', 'where', and 'when' of past experiences are stored in episodic memories and retrieved for suitable decisions remains unclear. In an effort to address these questions, the authors present computational models of neural networks that behave l ...

Nature Portfolio2023

Experimental data-driven model predictive control of a hospital HVAC system during regular use

Colin Neil Jones, Christophe Salzmann, Emilio Maddalena

Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case study of an industrial plant responsible for cooling a hospital surgery center. The adopted approach to guaranteeing thermal comfort and reducing electrical energy ...

2022

Real-Time Optimization of Wastewater Treatment Plants via Constraint Adaptation

Dominique Bonvin

An important requirement of wastewater treatment plants (WWTPs) is compliance with the local regulations on effluent discharge, which are going to become more stringent in the future. The operation of WWTPs exhibits a trade-off between operational cost and ...

MDPI2022

Differentially Private Stochastic Coordinate Descent

Rachid Guerraoui, Georgios Damaskinos

In this paper we tackle the challenge of making the stochastic coordinate descent algorithm differentially private. Compared to the classical gradient descent algorithm where updates operate on a single model vector and controlled noise addition to this ve ...

AIAA2021

Manufacturing, installation, commissioning, and first results with the 3D low-temperature co-fired ceramic high-frequency magnetic sensors on the Tokamak a Configuration Variable

Duccio Testa

Innovative high-frequency magnetic sensors have been designed and manufactured in-house for installation on the Tokamak a Configuration Variable (TCV), which are now routinely operational during the TCV experimental campaigns. These sensors combine the Low ...

2020

Sparsified SGD with Memory

Martin Jaggi, Sebastian Urban Stich, Jean-Baptiste Francis Marie Juliette Cordonnier

Huge scale machine learning problems are nowadays tackled by distributed optimization algorithms, i.e. algorithms that leverage the compute power of many devices for training. The communication overhead is a key bottleneck that hinders perfect scalability. ...

2018

Optimal Lagrange Multipliers for Dependent Rate Allocation in Video Coding

Pascal Frossard, Fernando Joaquim Leite Pereira, Ana Karina De Abreu Goes

In a typical video rate allocation problem, the objective is to optimally distribute a source rate budget among a set of (in)dependently coded data units to minimize the total distortion. Conventional Lagrangian approaches convert the lone rate constraint ...

Elsevier2018

Robust multi-objective optimization of gasifier and solid oxide fuel cell plant for electricity production using wood

François Maréchal, Shivom Sharma, Ayse Dilan Celebi

Biomass is an attractive renewable and stored energy that can be converted to transportation fuels, chemicals and electricity using bio-chemical and thermo-chemical conversion routes. Notably, biofuels have relatively lower greenhouse gas emissions compare ...

2017

Preserving Perceptual Contrast in Decolorization with Optimized Color Orders

Sabine Süsstrunk, Bin Jin

Converting a color image to a grayscale image, namely decolorization, is an important process for many real-world applications. Previous methods build contrast loss functions to minimize the contrast differences between the color images and the resultant g ...

2017

Automating Ad hoc Data Representation Transformations

Martin Odersky, Vlad Ureche

To maximize run-time performance, programmers often specialize their code by hand, replacing library collections and containers by custom objects in which data is restructured for efficient access. However, changing the data representation is a tedious and ...

Assoc Computing Machinery2015

Assembling Self-Supporting Structures

Mark Pauly, Mario Moacir Deuss

Self-supporting structures are prominent in historical and contemporary architecture due to advantageous structural properties and efficient use of material. Computer graphics research has recently contributed new design tools that allow creating and inter ...

2014

Hessian Schatten-Norm Regularization for Linear Inverse Problems

Michaël Unser, John Paul Ward, Stamatios Lefkimmiatis

We introduce a novel family of invariant, convex, and non-quadratic functionals that we employ to derive regularized solutions of ill-posed linear inverse imaging problems. The proposed regularizers involve the Schatten norms of the Hessian matrix, which a ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Thermo-Economic Optimization of Integrated First and Second Generation Sugarcane Ethanol Plant

François Maréchal, Adriano Viana Ensinas, Victor Codina Gironès, Juliana Queiroz Albarelli

The sugarcane industry has been responsible in some countries for the production of most of the sugar and ethanol available in the world for internal and external markets. In this sector, ethanol can be produced by fermentation of sugars obtained directly ...

2013

On the distribution of urban road space for multimodal congested networks

Nikolaos Geroliminis, Nan Zheng

Transport systems in real cities are complex with many modes of transport sharing and competing for limited road space. This work intends to understand how space distributions for modes and interactions among modes affect network traffic performance. While ...

Elsevier2013

Coordination and Sampling in Distributed Constraint Optimization

Brammert Ottens

The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...

EPFL2012