Search results for " space"
showing 10 items of 4562 documents
Intelligent system for material quality control using impact-echo testing
2008
This paper introduces an intelligent system to discern the quality of materials inspected by the impact-echo technique. The system includes a hardware setup to inspect parallelepiped-shape materials and a procedure to classify the material depending on its quality condition. Four levels of classification with different grades of knowledge about the material defects are approached: material condition, kind of defect, defect orientation, and defect dimension. The number of classes (material qualities) in the lowest classification level is 12. The procedure is applied on signals coming from 3D finite element simulations and lab experiments with aluminium specimens. The classification procedure…
Hidden attractors on one path : Glukhovsky-Dolzhansky, Lorenz, and Rabinovich systems
2017
In this report, by the numerical continuation method we visualize and connect hidden chaotic sets in the Glukhovsky-Dolzhansky, Lorenz and Rabinovich systems using a certain path in the parameter space of a Lorenz-like system.
State Space-Vector Model of Linear Induction Motors Including End-effects and Iron Losses - Part II: Model Identification and Results
2020
This is the second part of an article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the offline identification of its parameters. This second part is devoted to the description of an identification technique that has been suitably developed for the estimation of the electrical parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses. Such an identification technique is strictly related to the state formulation of the proposed model and exploits genetic algorithms for minimizing a suitable cost …
Color illusions also deceive CNNs for low-level vision tasks: Analysis and implications.
2019
The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural images may be deceived by brightness and color illusions, some network illusions can be inconsistent with the perception of humans. Next, we analyze where these similarities and differences may come from. On one hand, the proposed linear eigenanalysis explains the overall similarities: in simple CNNs trained for tasks like denoising or deblurring, the linear version of the network has center-surround receptive fields, and global transfer functions are very similar to the human …
Universal design as resilient urban space plan strategy. New scenarios for environmental resources’ sustainable management
2021
Nowadays, urban framework, stressed by the growing anthropic pressure and its constantly evolving use requests is split by uneven structures, contexts, users and patchy needs, which come out to be inefficient and ineffective in access and management. This fact is directly connected both with morph-functional structure of urban texture and its continuous changing trends. The most important consequences of this situation are some negative effects that produce entropy, mistaken anthropic space uses, ecological networks decrease and most of all a substantial urban life quality reduction connected with mobility problems and non-resilient spaces' use at the different plan scales. These elements m…
State Space-Vector Model of Linear Induction Motors including End-Effects and Iron Losses Part I: Theoretical Analysis
2020
This is the first part of the article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its offline identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel nonlinear control techniques, nonlinear observers as well as electrical losses minimization techniques. Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined effects …
World`s Most Valuable Brand Resonation With Categories of Different Customer Needs
2017
One of the key performance indicators of brand success is its value. Brand value is an outcome of brand`s performance in market, and is largely depended from brand`s ability to satisfy certain customer needs. For the greatest success in the world`s market brand should resonate its ability to satisfy some of customer`s most universal needs. In this paper authors strives to find out which of the needs world`s most successful brands are resonating with. Therefore paper goal is to is to determine what customer needs world`s most valuable brands are primarily satisfying. First part of paper authors briefly evaluate Maslow theory of needs. In second part of paper authors identify main challenges …
Bounded approximation properties via integral and nuclear operators
2010
Published version of an article in the journal:Proceedings of the American Mathematical Society. Also available from the publisher, Open Access
Conceptual representations of actions for autonomous robots
2001
An autonomous robot involved in long and complex missions should be able to generate, update and process its own plans of action. In this perspective, it is not plausible that the meaning of the representations used by the robot is given from outside the system itself. Rather, the meaning of internal symbols must be firmly anchored to the world through the perceptual abilities and the overall activities of the robot. According to these premises, in this paper we present an approach to action representation that is based on a "conceptual" level of representation, acting as an intermediate level between symbols and data coming from sensors. Symbolic representations are interpreted by mapping …
Anchoring symbols to conceptual spaces: the case of dynamic scenarios.
2003
In recent years, there have been several proposals for the realization of models inspired to biological solutions for pattern recognition. In this work we propose a new approach, based on a hierarchical modular structure, to realize a system capable to learn by examples and recognize objects in digital images. The adopted techniques are based on multiresolution image analysis and neural networks. Performance on two different data sets and experimental timings on a single instruction multiple data (SIMD) machine are also reported.