951 resultados para Self-organizing networks
Defining the role of floating periphyton mats in shaping food-web dynamics in the Florida Everglades
Resumo:
Expansive periphyton mats are a striking characteristic of the Florida Everglades. Floating periphyton mats are home to a diverse macroinvertebrate community dominated by chironomid and ceratopogonid larvae and amphipods that use the mat as both a food resource and refuge from predation. While this periphyton complex functions as a self-organizing system, it also serves as a base for trophic interactions with larger organisms. The purpose of my research was to quantify variation in the macroinvertebrate community inhabiting floating periphyton mats, describe the role of mats in shaping food-web dynamics, and describe how these trophic interactions change with eutrophication. ^ I characterized the macroinvertebrate community inhabiting periphyton through a wet-season by describing spatial variation on scales from 0.2 m to 3 km. Floating periphyton mats contained a diverse macroinvertebrate community, with greater taxonomic richness and higher densities of many taxa than adjacent microhabitats. Macroinvertebrate density increased through the wet season as periphyton mats developed. While some variation was noted among sites, spatial patterns were not observed on smaller scales. I also sampled ten sites representing gradients of hydroperiod and nutrient (P) levels. The density of macroinvertebrates inhabiting periphyton mats increased with increasing P availability; however, short-hydroperiod P-enriched sites had the highest macroinvertebrate density. This pattern suggests a synergistic interaction of top-down and bottom-up effects. In contrast, macroinvertebrate density was lower in benthic floc, where it was negatively correlated with hydroperiod. ^ I used two types of mesocosms (field cages and tanks) to manipulate large consumers (fish and grass shrimp) with inclusion/exclusion cages over an experimental P gradient. In most cases, periphyton mats served as an effective predation refuge. Macroinvertebrates were consumed more frequently in P-enriched treatments, where mats were also heavily grazed. Macroinvertebrate densities decreased with increasing P in benthic floc, but increased with enrichment in periphyton mats until levels were reached that caused disassociation of the mat. ^ This research documents several indirect trophic interactions that can occur in complex habitats, and emphasizes the need to characterize dynamics of all microhabitats to fully describe the dynamics of an ecosystem. ^
Resumo:
In the primary visual cortex, neurons with similar physiological features are clustered together in columns extending through all six cortical layers. These columns form modular orientation preference maps. Long-range lateral fibers are associated to the structure of orientation maps since they do not connect columns randomly; they rather cluster in regular intervals and interconnect predominantly columns of neurons responding to similar stimulus features. Single orientation preference maps – the joint activation of domains preferring the same orientation - were observed to emerge spontaneously and it was speculated whether this structured ongoing activation could be caused by the underlying patchy lateral connectivity. Since long-range lateral connections share many features, i.e. clustering, orientation selectivity, with visual inter-hemispheric connections (VIC) through the corpus callosum we used the latter as a model for long-range lateral connectivity. In order to address the question of how the lateral connectivity contributes to spontaneously generated maps of one hemisphere we investigated how these maps react to the deactivation of VICs originating from the contralateral hemisphere. To this end, we performed experiments in eight adult cats. We recorded voltage-sensitive dye (VSD) imaging and electrophysiological spiking activity in one brain hemisphere while reversible deactivating the other hemisphere with a cooling technique. In order to compare ongoing activity with evoked activity patterns we first presented oriented gratings as visual stimuli. Gratings had 8 different orientations distributed equally between 0º and 180º. VSD imaged frames obtained during ongoing activity conditions were then compared to the averaged evoked single orientation maps in three different states: baseline, cooling and recovery. Kohonen self-organizing maps were also used as a means of analysis without prior assumption (like the averaged single condition maps) on ongoing activity. We also evaluated if cooling had a differential effect on evoked and ongoing spiking activity of single units. We found that deactivating VICs caused no spatial disruption on the structure of either evoked or ongoing activity maps. The frequency with which a cardinally preferring (0º or 90º) map would emerge, however, decreased significantly for ongoing but not for evoked activity. The same result was found by training self-organizing maps with recorded data as input. Spiking activity of cardinally preferring units also decreased significantly for ongoing when compared to evoked activity. Based on our results we came to the following conclusions: 1) VICs are not a determinant factor of ongoing map structure. Maps continued to be spontaneously generated with the same quality, probably by a combination of ongoing activity from local recurrent connections, thalamocortical loop and feedback connections. 2) VICs account for a cardinal bias in the temporal sequence of ongoing activity patterns, i.e. deactivating VIC decreases the probability of cardinal maps to emerge spontaneously. 3) Inter- and intrahemispheric long-range connections might serve as a grid preparing primary visual cortex for likely junctions in a larger visual environment encompassing the two hemifields.
Resumo:
In the primary visual cortex, neurons with similar physiological features are clustered together in columns extending through all six cortical layers. These columns form modular orientation preference maps. Long-range lateral fibers are associated to the structure of orientation maps since they do not connect columns randomly; they rather cluster in regular intervals and interconnect predominantly columns of neurons responding to similar stimulus features. Single orientation preference maps – the joint activation of domains preferring the same orientation - were observed to emerge spontaneously and it was speculated whether this structured ongoing activation could be caused by the underlying patchy lateral connectivity. Since long-range lateral connections share many features, i.e. clustering, orientation selectivity, with visual inter-hemispheric connections (VIC) through the corpus callosum we used the latter as a model for long-range lateral connectivity. In order to address the question of how the lateral connectivity contributes to spontaneously generated maps of one hemisphere we investigated how these maps react to the deactivation of VICs originating from the contralateral hemisphere. To this end, we performed experiments in eight adult cats. We recorded voltage-sensitive dye (VSD) imaging and electrophysiological spiking activity in one brain hemisphere while reversible deactivating the other hemisphere with a cooling technique. In order to compare ongoing activity with evoked activity patterns we first presented oriented gratings as visual stimuli. Gratings had 8 different orientations distributed equally between 0º and 180º. VSD imaged frames obtained during ongoing activity conditions were then compared to the averaged evoked single orientation maps in three different states: baseline, cooling and recovery. Kohonen self-organizing maps were also used as a means of analysis without prior assumption (like the averaged single condition maps) on ongoing activity. We also evaluated if cooling had a differential effect on evoked and ongoing spiking activity of single units. We found that deactivating VICs caused no spatial disruption on the structure of either evoked or ongoing activity maps. The frequency with which a cardinally preferring (0º or 90º) map would emerge, however, decreased significantly for ongoing but not for evoked activity. The same result was found by training self-organizing maps with recorded data as input. Spiking activity of cardinally preferring units also decreased significantly for ongoing when compared to evoked activity. Based on our results we came to the following conclusions: 1) VICs are not a determinant factor of ongoing map structure. Maps continued to be spontaneously generated with the same quality, probably by a combination of ongoing activity from local recurrent connections, thalamocortical loop and feedback connections. 2) VICs account for a cardinal bias in the temporal sequence of ongoing activity patterns, i.e. deactivating VIC decreases the probability of cardinal maps to emerge spontaneously. 3) Inter- and intrahemispheric long-range connections might serve as a grid preparing primary visual cortex for likely junctions in a larger visual environment encompassing the two hemifields.
Resumo:
This thesis, part of the research line "Work, Society and Education" analyzes, in a dialectical perspective, in the light of Tragtenberg´s studies, the conception of subject of schoolwork, considering the organization and the complexity of this context and inviting the investigative gaze. Our hypothesis is that the workers of education have, in the schoolwork, a fragile politicization field and overcoming the installed model, accepting themselves as executers with self-organizing difficulties, distanced from the effective participation, autonomy and self-management. We consider studies on the logic of the work, believing that the understanding of schoolwork is constitute into the current societal model, in whom its bureaucratic and hierarchical matrix, linked to articulated / articulators of the dominant socio-economic class interests. Scholars such as Braverman, Frigotto and Tragtenberg, among others, are important contributions to this reflection. We have analyzed the logic of the work also in dialogue with pedagogies differentiated, among them, the Libertarian defended by Tragtenberg, aiming to understand the conceptions and practices of the subjects involved. We accomplished a bibliographical critical analysis, in a dialectical character, focusing on the categories: work, schoolwork, control, autonomy and self-management, in order to understand the complexity of the praxis in study, dialoguing with the pillars categories historicity, contradiction and totality, which transversalize the developed analysis. The consideration of these concepts allows us to uncover the dominant bureaucratic structure and its possible overcoming fields. We believe contribute to problematizing and proposers studies, reflections and discussions, strengthening debates, deconstructing naturalizations and contributing to the political process of the subjects.
Resumo:
This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction.
Resumo:
We employed a multitechnique approach using piezo-force response microscopy and photoemission microscopy to investigate a self-organizing polarization domain pattern in PbTiO3/La0.7Sr0.3MnO3 (PTO/LSMO) nanostructures. The polarization is correlated with the nanostructure morphology as well as with the thickness and Mn valence of the LSMO template layer. On the LSMO dots, the PTO is upwards polarized, whereas outside the nanodots, the polarization appears both strain and interface roughness dependent. The results suggest that the electronic structure and strain of the PTO/LSMO interface contribute to determining the internal bias of the ferroelectric layer.
Resumo:
Elasticity is one of the most known capabilities related to cloud computing, being largely deployed reactively using thresholds. In this way, maximum and minimum limits are used to drive resource allocation and deallocation actions, leading to the following problem statements: How can cloud users set the threshold values to enable elasticity in their cloud applications? And what is the impact of the applications load pattern in the elasticity? This article tries to answer these questions for iterative high performance computing applications, showing the impact of both thresholds and load patterns on application performance and resource consumption. To accomplish this, we developed a reactive and PaaS-based elasticity model called AutoElastic and employed it over a private cloud to execute a numerical integration application. Here, we are presenting an analysis of best practices and possible optimizations regarding the elasticity and HPC pair. Considering the results, we observed that the maximum threshold influences the application time more than the minimum one. We concluded that threshold values close to 100% of CPU load are directly related to a weaker reactivity, postponing resource reconfiguration when its activation in advance could be pertinent for reducing the application runtime.
Resumo:
En este documento se expondrá una implementación del problema del viajante de comercio usando una implementación personalizada de un mapa auto-organizado basándose en soluciones anteriores y adaptándolas a la arquitectura CUDA, haciendo a la vez una comparativa de la implementación eficiente en CUDA C/C++ con la implementación de las funciones de GPU incluidas en el Parallel Computing Toolbox de Matlab. La solución que se da reduce en casi un cuarto las iteraciones necesarias para llegar a una solución buena del problema mencionado, además de la mejora inminente del uso de las arquitecturas paralelas. En esta solución se estudia la mejora en tiempo que se consigue con el uso específico de la memoria compartida, siendo esta una de las herramientas más potentes para mejorar el rendimiento. En lo referente a los tiempos de ejecución, se llega a concluir que la mejor solución es el lanzamiento de un kernel de CUDA desde Matlab a través de la funcionalidad incluida en el Parallel Computing Toolbox.
Resumo:
The dendritic cell algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a ‘context aware’ detection system. Previous applications of the DCA have included the detection of potentially malicious port scanning activity, where it has produced high rates of true positives and low rates of false positives. In this work we aim to compare the performance of the DCA and of a self-organizing map (SOM) when applied to the detection of SYN port scans, through experimental analysis. A SOM is an ideal candidate for comparison as it shares similarities with the DCA in terms of the data fusion method employed. It is shown that the results of the two systems are comparable, and both produce false positives for the same processes. This shows that the DCA can produce anomaly detection results to the same standard as an established technique.
Resumo:
Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.
Resumo:
We present and evaluate a novel supervised recurrent neural network architecture, the SARASOM, based on the associative self-organizing map. The performance of the SARASOM is evaluated and compared with the Elman network as well as with a hidden Markov model (HMM) in a number of prediction tasks using sequences of letters, including some experiments with a reduced lexicon of 15 words. The results were very encouraging with the SARASOM learning better and performing with better accuracy than both the Elman network and the HMM.
Resumo:
La autoorganización es un proceso de aprendizaje no supervisado mediante el cual se descubren características, relaciones, patrones significativos o prototipos en los datos. Entre los sistemas neuronales autoorganizados más usados destaca el el mapa autoorganizado o SOM (Self-Organizing Map), el cual ha sido aplicado en multitud de campos distintos. Sin embargo, este modelo autoorganizado tiene varias limitaciones relacionadas con su tamaño, topología, falta de representación de relaciones jerárquicas, etc. La red neuronal llamada gas neuronal creciente o GNG (Growing Neural Gas), es un ejemplo de modelo neuronal autoorganizado con mayor flexibilidad que el SOM ya que está basado en un grafo de unidades de proceso en vez de en una topología fija. A pesar de su éxito, se ha prestado poca atención a su extensión jerárquica, a diferencia de muchos otros modelos que tienen varias versiones jerárquicas. El gas neuronal jerárquico creciente o GHNG (Growing Hierarchical Neural Gas) es una extensión jerárquica del GNG en el que se aprende un árbol de grafos, donde el algoritmo original del GNG se ha mejorado distinguiendo entre una fase de crecimiento y una fase de convergencia. Los resultados experimentales demuestran las capacidades de autoorganización y aprendizaje jerárquico de esta red.
Resumo:
Este trabajo se inscribe en uno de los grandes campos de los estudios organizacionales: la estrategia. La perspectiva clásica en este campo promovió la idea de que proyectarse hacia el futuro implica diseñar un plan (una serie de acciones deliberadas). Avances posteriores mostraron que la estrategia podía ser comprendida de otras formas. Sin embargo, la evolución del campo privilegió en alguna medida la mirada clásica estableciendo, por ejemplo, múltiples modelos para ‘formular’ una estrategia, pero dejando en segundo lugar la manera en la que esta puede ‘emerger’. El propósito de esta investigación es, entonces, aportar al actual nivel de comprensión respecto a las estrategias emergentes en las organizaciones. Para hacerlo, se consideró un concepto opuesto —aunque complementario— al de ‘planeación’ y, de hecho, muy cercano en su naturaleza a ese tipo de estrategias: la improvisación. Dado que este se ha nutrido de valiosos aportes del mundo de la música, se acudió al saber propio de este dominio, recurriendo al uso de ‘la metáfora’ como recurso teórico para entenderlo y alcanzar el objetivo propuesto. Los resultados muestran que 1) las estrategias deliberadas y las emergentes coexisten y se complementan, 2) la improvisación está siempre presente en el contexto organizacional, 3) existe una mayor intensidad de la improvisación en el ‘como’ de la estrategia que en el ‘qué’ y, en oposición a la idea convencional al respecto, 4) se requiere cierta preparación para poder improvisar de manera adecuada.
Resumo:
This dissertation consists of three papers. The first paper "Managing the Workload: an Experiment on Individual Decision Making and Performance" experimentally investigates how decision-making in workload management affects individual performance. I designed a laboratory experiment in order to exogenously manipulate the schedule of work faced by each subject and to identify its impact on final performance. Through the mouse click-tracking technique, I also collected interesting behavioral measures on organizational skills. I found that a non-negligible share of individuals performs better under externally imposed schedules than in the unconstrained case. However, such constraints are detrimental for those good in self-organizing. The second chapter, "On the allocation of effort with multiple tasks and piecewise monotonic hazard function", tests the optimality of a scheduling model, proposed in a different literature, for the decisional problem faced in the experiment. Under specific assumptions, I find that such model identifies what would be the optimal scheduling of the tasks in the Admission Test. The third paper "The Effects of Scholarships and Tuition Fees Discounts on Students' Performances: Which Monetary Incentives work Better?" explores how different levels of monetary incentives affect the achievement of students in tertiary education. I used a Regression Discontinuity Design to exploit the assignment of different monetary incentives, to study the effects of such liquidity provision on performance outcomes, ceteris paribus. The results show that a monetary increase in the scholarships generates no effect on performance since the achievements of the recipients are all centered near the requirements for non-returning the benefit. Secondly, students, who are actually paying some share of the total cost of college attendance, surprisingly, perform better than those whose cost is completely subsidized. A lower benefit, relatively to a higher aid, it motivates students to finish early and not to suffer the extra cost of a delayed graduation.
Resumo:
The research project is focused on the investigation of the polymorphism of crystalline molecular material for organic semiconductor applications under non-ambient conditions, and the solid-state characterization and crystal structure determination of the different polymorphic forms. In particular, this research project has tackled the investigation and characterization of the polymorphism of perylene diimides (PDIs) derivatives at high temperatures and pressures, in particular N,N’-dialkyl-3,4,9,10-perylendiimide (PDI-Cn, with n = 5, 6, 7, 8). These molecules are characterized by excellent chemical, thermal, and photostability, high electron affinity, strong absorption in the visible region, low LUMO energies, good air stability, and good charge transport properties, which can be tuned via functionalization; these features make them promising n-type organic semiconductor materials for several applications such as OFETs, OPV cells, laser dye, sensors, bioimaging, etc. The thermal characterization of PDI-Cn was carried out by a combination of differential scanning calorimetry, variable temperature X-ray diffraction, hot-stage microscopy, and in the case of PDI-C5 also variable temperature Raman spectroscopy. Whereas crystal structure determination was carried out by both Single Crystal and Powder X-ray diffraction. Moreover, high-pressure polymorphism via pressure-dependent UV-Vis absorption spectroscopy and high-pressure Single Crystal X-ray diffraction was carried out in this project. A data-driven approach based on a combination of self-organizing maps (SOM) and principal component analysis (PCA) is also reported was used to classify different π-stacking arrangements of PDI derivatives into families of similar crystal packing. Besides the main project, in the framework of structure-property analysis under non-ambient conditions, the structural investigation of the water loss in Pt- and Pd- based vapochromic potassium/lithium salts upon temperature, and the investigation of structure-mechanical property relationships in polymorphs of a thienopyrrolyldione endcapped oligothiophene (C4-NT3N) are reported.