Search results for "Data type"
showing 10 items of 1183 documents
ChemInform Abstract: Selecting Speed-Dependent Pathways for a Programmable Nanoscale Texture by Wet Interfaces
2013
The realization of well-defined and ordered structures on the nanoscale is a main issue in nanoscience and nanotechnology, biotechnology and other related fields like plastic or organic electronics. Among the bottom-up approaches, to date, self-assembly (equilibrium aggregates) received a major attention. In spite of this, far from equilibrium conditions allow for the generation of a wider landscape of organized systems depending on the set of control parameters employed. Under an adaptation vision of the structures, here we report some case studies showing how it is possible to programme and control the nanoscale features of ordered super- or supra-aggregates at wet interfaces by modulatin…
Selecting speed-dependent pathways for a programmable nanoscale texture by wet interfaces
2012
The realization of well-defined and ordered structures on the nanoscale is a main issue in nanoscience and nanotechnology, biotechnology and other related fields like plastic or organic electronics. Among the bottom-up approaches, to date, self-assembly (equilibrium aggregates) received a major attention. In spite of this, far from equilibrium conditions allow for the generation of a wider landscape of organized systems depending on the set of control parameters employed. Under an adaptation vision of the structures, here we report some case studies showing how it is possible to programme and control the nanoscale features of ordered super- or supra-aggregates at wet interfaces by modulatin…
Using Cellular Automata for feature construction - preliminary study
2007
When first faced with a learning task, it is often not clear what a good representation of the training data should look like. We are often forced to create some set of features that appear plausible, without any strong confidence that they will yield superior learning. Beside, we often do not have any prior knowledge of what learning method is the best to apply, and thus often try multiple methods in an attempt to find the one that performs best. This paper describes a new method and its preliminary study for constructing features based on cellular automata (CA). Our approach uses self-organisation ability of cellular automata by constructing features being most efficient for making predic…
DiDuSoNet: A P2P architecture for Ditributed Dunbar-based Social Networks,
2015
Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. One of the most important challenges is the data availability problem when a user is offline. In this paper we propose DiDuSoNet, a novel P2P Distributed Online Social Network where users can exercise full access control on their data. Our system exploits trust relationships for providing a set of important social services, such as trustness, informati…
Trusted dynamic storage for dunbar-based P2P online social networks
2014
Online Social Networks (OSNs) are becoming more and more popular in today's Internet. Distributed Online Social Networks (DOSNs), are OSNs which do not exploit a central server for storing users' data and enable users to have more control on their profile content, ensuring a higher level of privacy. The main challenge of DOSNs comes from guaranteeing availability of the data when the data owner is offline. In this paper we propose a new P2P dynamic approach to the problem of data persistence in DOSNs. By following Dunbar's approach, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Users in this set are chosen by considerin…
Epidemic diffusion of social updates in Dunbar-based DOSN
2014
Distributed Online Social Networks (DOSNs) do not rely on a central repository for storing social data so that the users can keep control of their private data and do not depend on the social network provider. The ego network, i.e. the network made up of an individual, the ego, along with all the social ties she has with other people, the alters, may be exploited to define distributed social overlays and dissemination protocols. In this paper we propose a new epidemic protocol able to spread social updates in Dunbar-based DOSN overlays where the links between nodes are defined by considering the social interactions between users. Our approach is based on the notion of Weighted Ego Betweenne…
NAUTILUS framework : towards trade-off-free interaction in multiobjective optimization
2016
In this paper, we present a framework of different interactive NAUTILUS methods for multiobjective optimization. In interactive methods, the decision maker iteratively sees solution alternatives and provides one’s preferences in order to find the most preferred solution. We question the widely used setting that the solutions shown to the decision maker should all be Pareto optimal which implies that improvement in any objective function necessitates allowing impairment in some others. Instead, in NAUTILUS we enable the decision maker to make a free search without having to trade-off by starting from an inferior solution and iteratively approaching the Pareto optimal set by allowing all obje…
A solution process for simulation-based multiobjective design optimization with an application in the paper industry
2014
In this paper, we address some computational challenges arising in complex simulation-based design optimization problems. High computational cost, black-box formulation and stochasticity are some of the challenges related to optimization of design problems involving the simulation of complex mathematical models. Solving becomes even more challenging in case of multiple conflicting objectives that must be optimized simultaneously. In such cases, application of multiobjective optimization methods is necessary in order to gain an understanding of which design offers the best possible trade-off. We apply a three-stage solution process to meet the challenges mentioned above. As our case study, w…
Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies
2018
We consider multiobjective optimization problems where objective functions have different (or heterogeneous) evaluation times or latencies. This is of great relevance for (computationally) expensive multiobjective optimization as there is no reason to assume that all objective functions should take an equal amount of time to be evaluated (particularly when objectives are evaluated separately). To cope with such problems, we propose a variation of the Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) called heterogeneous K-RVEA (short HK-RVEA). This algorithm is a merger of two main concepts designed to account for different latencies: A single-objective evolutionary a…
PAINT : Pareto front interpolation for nonlinear multiobjective optimization
2011
A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem. When the scalarizations of the interactive method used do not introduce nonlinearity to the problem (which is true e.g., for the synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed integer linear solvers. Thus, the use of the interactive meth…