Search results for " Image processing"
showing 10 items of 2323 documents
Spatialization of the Semantic Web
2012
syntax for Horn-like rules. The SWRL as the form, antecedentconsequent, where both antecedent and consequent are conjunctions of atoms written a1^ ... ^ an. Atoms in rules can be of the form C(x), P(x,y), Q(x,z), sameAs(x,y), differentFrom(x,y), or builtIn(pred, z1, ..., zn), where C is an OWL description, P is an OWL individual-valued property, Q is an OWL data-valued property, pred is a datatype predicate URIref, x and y are either individual-valued variables or OWL individuals, and z, z1, ... zn are either data-valued variables or OWL data literals. An OWL data literal is either a typed literal or a plain literal. Variables are indicated by using the standard convention of prefixing the…
Cyberbullying in schools : mobile phone and internet effect in adolescents
2017
El objetivo del estudio está enfocado a conocer la prevalencia de las formas de cyberbullying (teléfono móvil e internet) y cómo estas se ven influenciadas por las variables personales y escolares. La muestra final estuvo formada por un total de 749 alumnos de Educación Secundaria Obligatoria, con edades comprendidas entre los 12 y los 15 años (M = 13.77 años; DT = 1.12). Para la recogida de información se utiliza un cuestionario “ad hoc” (datos socioescolares) y la escala de Victimización entre Adolescentes a través del Teléfono Móvil y de Internet (CYBVIC) (Buelga, Cava & Musitu, 2012). De un primer análisis descriptivo, se obtienen porcentajes similares pero con ligera prevalencia en…
One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals
2021
Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…
A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities
2020
The concept of Smart City has spread as a solution to ensure better access to information and services to citizens, but also as a means to reduce the environmental footprint of cities. To this end, a continuous and wide observation of the environment is necessary to analyze information that enables government bodies to act on the environment appropriately. Moreover, a diffused acquisition of information requires adequate infrastructure and proper devices, which results in relevant installation and maintenance costs. Our proposal enables reducing the number of necessary sensors to be deployed while ensuring that information is available at any time and anywhere. We present the HybridIoT syst…
Urban Growth and Real Estate Income. A Comparison of Analytical Models
2016
I processi di crescita urbana sono notoriamente complessi dipendendo da un’ampia varietà di fattori demografici, socio-culturali ed economici. L’analisi è ancora più complessa nelle aree metropolitane che sono il risultato di antichi processi di agglomerazione in una fase d’intenso accrescimento dell’insediamento e, più recentemente, della formazione di policentrismo urbano. L’investigazione richiede l’acquisizione, l’analisi e l’elaborazione d’idonee informazioni a livello delle unità territoriali omogenee, basandosi su modelli consolidati o su nuovi protocolli da verificare. Il presente contributo analizza la crescita urbana secondo un approccio di piccola scala, individuando i distretti …
Towards digital cognitive clones for the decision-makers: adversarial training experiments
2021
Abstract There can be many reasons for anyone to make a digital copy (clone) of own decision-making behavior. This enables virtual presence of a professional decision-maker simultaneously in many places and processes of Industry 4.0. Such clone can be used as one’s responsible representative when the human is not available. Pi-Mind (“Patented Intelligence”) is a technology, which enables “cloning” cognitive skills of humans using adversarial machine learning. In this paper, we present a cyber-physical environment as an adversarial learning ecosystem for cloning image classification skills. The physical component of the environment is provided by the logistic laboratory with camera-surveilla…
Taxonomy of generative adversarial networks for digital immunity of Industry 4.0 systems
2021
Abstract Industry 4.0 systems are extensively using artificial intelligence (AI) to enable smartness, automation and flexibility within variety of processes. Due to the importance of the systems, they are potential targets for attackers trying to take control over the critical processes. Attackers use various vulnerabilities of such systems including specific vulnerabilities of AI components. It is important to make sure that inappropriate adversarial content will not break the security walls and will not harm the decision logic of critical systems. We believe that the corresponding security toolset must be organized as a trainable self-protection mechanism similar to immunity. We found cer…
Integration of high resolution spatial and spectral data acquisition systems to provide complementary datasets for cultural heritage applications
2010
International audience; Modern optical measuring systems are able to record objects with high spatial and spectral precision. The acquisition of spatial data is possible with resolutions of a few hundredths of a millimeter using active projection-based camera systems, while spectral data can be obtained using filter-based multispectral camera systems that can capture surface spectral reflectance with high spatial resolution. We present a methodology for combining data from these two discrete optical measuring systems by registering their individual measurements into a common geometrical frame. Furthermore, the potential for its application as a tool for the non-invasive monitoring of painti…
Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
2019
In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed
Data-Driven Evolutionary Optimization: An Overview and Case Studies
2019
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist, instead computationally expensive numerical simulations or costly physical experiments must be performed for fitness evaluations. In more extreme cases, only historical data are available for performing optimization and no new data can be generated during optimization. Solving evolutionary optimization problems driven by data collected in simulations, physical experiments, production processes, or daily life are termed data-driven evolutionary optimization. In this…