Search results for " optimization."
showing 10 items of 2333 documents
PINCoC: a Co-Clustering based Method to Analyze Protein-Protein Interaction Networks
2007
Anovel technique to search for functionalmodules in a protein-protein interaction network is presented. The network is represented by the adjacency matrix associated with the undirected graph modelling it. The algorithm introduces the concept of quality of a sub-matrix of the adjacency matrix, and applies a greedy search technique for finding local optimal solutions made of dense submatrices containing the maximum number of ones. An initial random solution, constituted by a single protein, is evolved to search for a locally optimal solution by adding/removing connected proteins that best contribute to improve the quality function. Experimental evaluations carried out on Saccaromyces Cerevis…
Modeling and Performance Assessment of the Split-Pi Used as a Storage Converter in All the Possible DC Microgrid Scenarios. Part II: Simulation and E…
2021
Bidirectional DC/DC converters such as the Split-pi can be used to integrate an energy storage system (ESS) into a DC microgrid providing manifold benefits. However, this integration deserves careful design because the ESS converter must behave like a stiff voltage generator, a non-stiff voltage generator, or a current generator depending on the microgrid configuration. Part I of this work presented a comprehensive theoretical analysis of the Split-pi used as an ESS converter in all the possible DC microgrid scenarios. Five typical microgrid scenarios were identified. Each of them required a specific state-space model of the Split-pi and a suitable control scheme. The present paper complete…
A new compact formulation for the discrete p-dispersion problem
2017
Abstract This paper addresses the discrete p -dispersion problem (PDP) which is about selecting p facilities from a given set of candidates in such a way that the minimum distance between selected facilities is maximized. We propose a new compact formulation for this problem. In addition, we discuss two simple enhancements of the new formulation: Simple bounds on the optimal distance can be exploited to reduce the size and to increase the tightness of the model at a relatively low cost of additional computation time. Moreover, the new formulation can be further strengthened by adding valid inequalities. We present a computational study carried out over a set of large-scale test instances i…
Optimal standalone data center renewable power supply using an offline optimization approach
2022
Abstract Because of the increasing energy consumption of data centers and their C O 2 emissions, the ANR DATAZERO2 project aims to design autonomous data centers running solely on local renewable energy coupled with storage devices to overcome the intermittency issue. In order to optimize the use of renewable energy and storage devices, a MILP solver is usually in charge of assigning the power to be supplied to the data center. However, in order to reduce the computation time and make the approach scalable, it would be more appropriate to use a polynomial time algorithm. This paper aims at showing and proving that it is possible to provide an optimal power profile via a deterministic algori…
Following ionic activity by electrochemistry during the polymerase chain reaction
2009
The most commonly used technique for gene detection is the polymerase chain reaction (PCR). PCR is associated with alterations in ionic activity because inorganic pyrophosphate (PPi) and inorganic phosphate (Pi) ions are produced during nucleotide polymerization. To maintain electro-neutrality, magnesium, potassium, and ammonium ions are bound to DNA. Deoxynucleotides are also bound to DNA during PCR. Some authors have described DNA itself as an electrically conducting polymer formed by base stapling with the formation of extensive Pi systems. In the current study, alterations in electrical conductivity determined experimentally during PCR are reported, and a model explaining the observed c…
Blind deconvolution using TV regularization and Bregman iteration
2005
In this paper we formulate a new time dependent model for blind deconvolution based on a constrained variational model that uses the sum of the total variation norms of the signal and the kernel as a regularizing functional. We incorporate mass conservation and the nonnegativity of the kernel and the signal as additional constraints. We apply the idea of Bregman iterative regularization, first used for image restoration by Osher and colleagues [S.J. Osher, M. Burger, D. Goldfarb, J.J. Xu, and W. Yin, An iterated regularization method for total variation based on image restoration, UCLA CAM Report, 04-13, (2004)]. to recover finer scales. We also present an analytical study of the model disc…
A time evolution model for total-variation based blind deconvolution
2007
Departamento Matematica Aplicada, Universidad de Valencia, Burjassot 46100, Spain.We propose a time evolution model for total-variation based blind deconvolution consisting of two evolution equations evolv-ing the signal by means of a nonlinear scale space method and the kernel by using a diffusion equation starting from the zerosignal and a delta function respectively. A preliminary numerical test consisting of blind deconvolution of a noiseless blurredimage is presented.
Ancillary Services in the Energy Blockchain for Microgrids
2019
The energy blockchain is a distributed Internet protocol for energy transactions between nodes of a power system. Recent applications of the energy blockchain in microgrids only consider the energy transactions between peers without considering the technical issues that can arise, especially when the system is islanded. One contribution of the paper is, thus, to depict a comprehensive framework of the technical and economic management of microgrids in the blockchain era, considering, for the first time, the provision of ancillary services and, in particular, of the voltage regulation service. When more PV nodes are operating in the grid, large reactive power flows may appear in the branches…
Robust Allocation Rules in Dynamical Cooperative TU Games
2011
Robust dynamic coalitional TU games are repeated TU games where the values of the coalitions are unknown but bounded variables. We set up the game supposing that the Game Designer uses a vague measure of the extra reward that each coalition has received up to the current time to re-adjust the allocations among the players. As main result, we provide a constructive method for designing allocation rules that converge to the core of the average game. Both the set up and the solution approach also provide an insight on commonalities between coalitional games and stability theory.
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
2012
During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuz…