838 resultados para Object Oriented


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Six subject areas prompted the broad field of inquiry of this mission-oriented dust control and surface improvement project for unpaved roads: • DUST--Hundreds of thousands of tons of dust are created annually by vehicles on Iowa's 70,000 miles of unpaved roads and streets. Such dust is often regarded as a nuisance by Iowa's highway engineers. • REGULATIONS--Establishment of "fugitive dust" regulations by the Iowa DEQ in 1971 has created debates, conferences, legal opinions, financial responsibilities, and limited compromises regarding "reasonable precaution" and "ordinary travel," both terms being undefined judgment factors. • THE PUBLIC--Increased awareness by the public that regulations regarding dust do in fact exist creates a discord of telephone calls, petitions, and increasing numbers of legal citations. Both engineers and politicians are frustrated into allowing either the courts or regulatory agencies to resolve what is basically a professional engineering responsibility. • COST--Economics seldom appear as a tenet of regulatory strategies, and in the case of "fugitive dust," four-way struggles often occur between the highway professions, political bodies, regulatory agencies, and the general public as to who is responsible, what can be done, how much it will cost, or why it wasn't done yesterday. • CONFUSION--The engineer lacks authority, and guidelines and specifications to design and construct a low-cost surf acing system are nebulous, i.e., construct something between the present crushed stone/gravel surface and a high-type pavement. • SOLUTION--The engineer must demonstrate that dust control and surface improvement may be engineered at a reasonable cost to the public, so that a higher degree of regulatory responsibility can be vested in engineering solutions.

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Memoria de TFC en el que se analiza el estándar SQL:1999 y se compara con PostgreeSQL y Oracle.

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The
 aim
 of
 this
 paper
 is
 to
 bring
 into
 consideration
 a
 way
 of
 studying
 culture
 in
 infancy.
 An
 emphasis 
is 
put 
on
 the
 role 
that 
the 
material 
object 
plays 
in 
early 
interactive
 processes. 
Accounted
 as
 a
 cultural
 artefact,
 the
 object
 is
 seen
 as
 a
 fundamental
 element
 within
 triadic
 mother‐object‐ infant
 interactions
 and
 is
 believed
 to
 be
 a
 driving
 force
 both
 for
 communicative
 and
 cognitive
 development.
 In
 order
 to
 reconsider
 the
 importance
 of
 the
 object
 in
 child
 development
 and
 to
 present
 an 
approach
 of 
studying
object
 construction,
accounts 
in 
literature 
on 
early 
communication
 development
 and
 the
 importance
 of
 the
 object
 are
 reviewed
 and
 discussed
 under
 the
 light
 of
 the
 cultural 
specificity 
of 
the 
material 
object.


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The information presented in this summary document has been based on the comprehensive,"Task Force Report on Water-Oriented Outdoor Recreation, Fish and Wildlife." The overriding principle the main task force report conveyed is that Iowa should not forsake the remaining water-oriented fish and wildlife resource base in the name of economic development.The reader should refer to the task force document for more detailed information.

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The institutional regimes framework has previously been applied to the institutional conditions that support or hinder the sustainability of housing stocks. This resource-based approach identifies the actors across different sectors that have an interest in housing, how they use housing, the mechanisms affecting their use (public policy, use rights, contracts, etc.) and the effects of their uses on the sustainability of housing within the context of the built environment. The potential of the institutional regimes framework is explored for its suitability to the many considerations of housing resilience. By identifying all the goods and services offered by the resource 'housing stock', researchers and decision-makers could improve the resilience of housing by better accounting for the ecosystem services used by housing, decreasing the vulnerability of housing to disturbances, and maximizing recovery and reorganization following a disturbance. The institutional regimes framework is found to be a promising tool for addressing housing resilience. Further questions are raised for translating this conceptual framework into a practical application underpinned with empirical data.

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Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

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In this paper we describe a proposal for defining the relationships between resources, users and services in a digital repository. Nowadays, virtual learning environments are widely used but digital repositories are not fully integrated yet into the learning process. Our final goal is to provide final users with recommendation systems and reputation schemes that help them to build a true learning community around the institutional repository, taking into account their educational context (i.e. the courses they are enrolled into) and their activity (i.e. system usage by their classmates and teachers). In order to do so, we extend the basic resource concept in a traditional digital repository by adding all the educational context and other elements from end-users' profiles, thus bridging users, resources and services, and shifting from a library-centered paradigm to a learning-centered one.

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The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

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In robotics, having a 3D representation of the environment where a robot is working can be very useful. In real-life scenarios, this environment is constantly changing for example by human interaction, external agents or by the robot itself. Thus, the representation needs to be constantly updated and extended to account for these dynamic scene changes. In this work we face the problem of representing the scene where a robot is acting. Moreover, we ought to improve this representation by reusing the information obtained in previous scenes. Our goal is to build a method to represent a scene and to update it while changes are produced. In order to achieve that, different aspects of computer vision such as space representation or feature tracking are discussed

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Multisensory processes facilitate perception of currently-presented stimuli and can likewise enhance later object recognition. Memories for objects originally encountered in a multisensory context can be more robust than those for objects encountered in an exclusively visual or auditory context [1], upturning the assumption that memory performance is best when encoding and recognition contexts remain constant [2]. Here, we used event-related potentials (ERPs) to provide the first evidence for direct links between multisensory brain activity at one point in time and subsequent object discrimination abilities. Across two experiments we found that individuals showing a benefit and those impaired during later object discrimination could be predicted by their brain responses to multisensory stimuli upon their initial encounter. These effects were observed despite the multisensory information being meaningless, task-irrelevant, and presented only once. We provide critical insights into the advantages associated with multisensory interactions; they are not limited to the processing of current stimuli, but likewise encompass the ability to determine the benefit of one's memories for object recognition in later, unisensory contexts.

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Single-trial encounters with multisensory stimuli affect both memory performance and early-latency brain responses to visual stimuli. Whether and how auditory cortices support memory processes based on single-trial multisensory learning is unknown and may differ qualitatively and quantitatively from comparable processes within visual cortices due to purported differences in memory capacities across the senses. We recorded event-related potentials (ERPs) as healthy adults (n = 18) performed a continuous recognition task in the auditory modality, discriminating initial (new) from repeated (old) sounds of environmental objects. Initial presentations were either unisensory or multisensory; the latter entailed synchronous presentation of a semantically congruent or a meaningless image. Repeated presentations were exclusively auditory, thus differing only according to the context in which the sound was initially encountered. Discrimination abilities (indexed by d') were increased for repeated sounds that were initially encountered with a semantically congruent image versus sounds initially encountered with either a meaningless or no image. Analyses of ERPs within an electrical neuroimaging framework revealed that early stages of auditory processing of repeated sounds were affected by prior single-trial multisensory contexts. These effects followed from significantly reduced activity within a distributed network, including the right superior temporal cortex, suggesting an inverse relationship between brain activity and behavioural outcome on this task. The present findings demonstrate how auditory cortices contribute to long-term effects of multisensory experiences on auditory object discrimination. We propose a new framework for the efficacy of multisensory processes to impact both current multisensory stimulus processing and unisensory discrimination abilities later in time.

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ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.

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Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

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Semantic Web technology is able to provide the required computational semantics for interoperability of learning resources across different Learning Management Systems (LMS) and Learning Object Repositories (LOR). The EU research project LUISA (Learning Content Management System Using Innovative Semantic Web Services Architecture) addresses the development of a reference semantic architecture for the major challenges in the search, interchange and delivery of learning objects in a service-oriented context. One of the key issues, highlighted in this paper, is Digital Rights Management (DRM) interoperability. A Semantic Web approach to copyright management has been followed, which places a Copyright Ontology as the key component for interoperability among existing DRM systems and other licensing schemes like Creative Commons. Moreover, Semantic Web tools like reasoners, rule engines and semantic queries facilitate the implementation of an interoperable copyright management component in the LUISA architecture.