Search results for "DEC"

Interrogating witnesses for geometric constraint solving

2012

International audience; Classically, geometric constraint solvers use graph-based methods to decompose systems of geometric constraints. These methods have intrinsic limitations, which the witness method overcomes; a witness is a solution of a variant of the system. This paper details the computation of a basis of the vector space of free infinitesimal motions of a typical witness, and explains how to use this basis to interrogate the witness for dependence detection. The paper shows that the witness method detects all kinds of dependences: structural dependences already detectable by graph-based methods, but also non-structural dependences, due to known or unknown geometric theorems, which…

Decomposition and Mean-Field Approach to Mixed Integer Optimal Compensation Problems

2016

Mixed integer optimal compensation deals with optimization problems with integer- and real-valued control variables to compensate disturbances in dynamic systems. The mixed integer nature of controls could lead to intractability in problems of large dimensions. To address this challenge, we introduce a decomposition method which turns the original n-dimensional optimization problem into n independent scalar problems of lot sizing form. Each of these problems can be viewed as a two-player zero-sum game, which introduces some element of conservatism. Each scalar problem is then reformulated as a shortest path one and solved through linear programming over a receding horizon, a step that mirro…

2021

Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an important part in systems that aim to ensure correct operation of a given model. However, for high-dimensional input data such as images, the individual symbols, i.e. pixels, are not easily interpretable. Therefore, rule-based approaches are not typically used for this kind of high-dimensional data. We introduce the concept of first-order convolutional rules, which are logical rules that can be extracted using a convolutional neural network (CNN), and w…

Networked Bio-Inspired Evolutionary Dynamics on a Multi-Population

2019

We consider a multi-population, represented by a network of groups of individuals. Every player of each group can choose between two options, and we study the problem of reaching consensus. The dynamics not only depend on the dynamics within the group, but they also depend on the topology of the network, so neighboring groups influence individuals as well. First, we develop a mathematical model of this networked bio-inspired evolutionary behavior and we study its steady-state. We look at the special case where the underlying network topology is a regular and unweighted graph and show that the steady-state is a consensus equilibrium. A sufficient condition for exponential stability is given.…

Design of a telescopic tower for wind energy production with reduced environmental impact

2019

A prototype of a telescopic pole for wind energy production with low environmental impact and its lifting system for a 60 to 250 kW turbine and a height of 30 m have been designed and manufactured. A telescopic tower, which is raised and lowered by automation or by remote control, allows to differentiate the presence of the generator within the landscape over time. The technology currently available for lifting and lowering wind turbines is made up of telescopic poles of heights of less than 10 meters and with tilting posts of height below 30 m. Without a state of the art to refer to, the telescopic pole and its lifting system have been designed starting from scratch and solving with innova…

DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

2021

Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …

Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

2020

Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…

Il barocco nel diritto. Le "Decisiones" dei supremi tribunali del "Regnum Siciliae"

2017

Exploring the application of blockchain to humanitarian supply chains: insights from Humanitarian Supply Blockchain pilot project

2021

PurposeSome studies and reports have recently suggested using blockchain technology to improve transparency and trust in humanitarian supply chains (HSCs). However, evidence-based studies to display the utility and applicability of blockchains in HSCs are missing in the literature. This paper aims to investigate the key drivers and barriers of blockchain application to HSCs and explore whether evidence could support that the application of blockchain improves transparency and trust in HSCs.Design/methodology/approachThis paper puts forward a two-stage approach to explore the blockchain application in HSCs: an initial exploration of humanitarian practitioners and academicians interested in b…

Ranking corporate sustainability: a flexible multidimensional approach based on linguistic variables

2017

Corporate sustainability implies a compromise between the present environmental, social, and economic needs of a firm's stakeholders and their future needs. Corporate sustainability is therefore a multidimensional concept. Nowadays, several independent rating agencies rate firms in terms of environmental, social, and governance (ESG) criteria. These ratings are usually used by main sustainability indices such as the Dow Jones Sustainability Index, FTSE4 Good, Stoxx Sustainability Index, or Euronext Vigeo Family to select companies to invest in. Only those firms performing better than the average of their sector are selected. However, although providing linguistic ratings about the performan…