Verification and FPGA circuits of a block-2 fast path-based predictor

This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

Emergence of a small-world functional network in cultured neurons

The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.

Study of the relationship between roads, relief, land use, and natural vegetation in the Ibiuna Plateau - SP, focusing on landscape ecology

Roads facilitate access by deforestation agents, being relevant in studies approaching conservationist matters in rainforests. It is important to understand the relationship between road distribution, relief, land use, and forest coverage in order to evaluate where forests are more vulnerable. This study aimed at: 1) understanding the relationship between relief and density and road connectivity in three moments in time; and 2) evaluating the relationship between distance from roads and forest coverage, farmlands and rural and urban facilities in a fragmented Atlantic Forest landscape in three moments in time. Maps of roads, altitude, and land use and coverage were used. Chi-square tests showed that: 1) density and road connectivity did not present significant relationship with the relief; and 2) forest areas occupy areas distant from the roads, while farmlands and rural and urban facilities occupy areas nearer the roads. Roads and land use, regardless of relief, influence forest coverage distribution. Thus, we suggest that roads are taken into account in conservationist strategies and environmental planning.

Using gap-crossing capacity to evaluate functional connectivity of two Atlantic rainforest birds and their response to fragmentation

One of the main consequences of habitat loss and fragmentation is the increase in patch isolation and the consequent decrease in landscape connectivity. In this context, species persistence depends on their responses to this new landscape configuration, particularly on their capacity to move through the interhabitat matrix. Here, we aimed first to determine gap-crossing probabilities related to different gap widths for two forest birds (Thamnophilus caerulescens, Thamnophilidae, and Basileuterus culicivorus, Parulidae) from the Brazilian Atlantic rainforest. These values were defined with a playback technique and then used in analyses based on graph theory to determine functional connections among forest patches. Both species were capable of crossing forest gaps between patches, and these movements were related to gap width. The probability of crossing 40 m gaps was 50% for both species. This probability falls to 10% when the gaps are 60 m (for B. culicivorus) or 80 m (for T caerulescens). Actually, birds responded to stimulation about two times more distant inside forest trials (control) than in gap-crossing trials. Models that included gap-crossing capacity improved the explanatory power of species abundance variation in comparison to strictly structural models based merely on patch area and distance measurements. These results highlighted that even very simple functional connectivity measurements related to gap-crossing capacity can improve the understanding of the effect of habitat fragmentation on bird occurrence and abundance.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

Estimating complex cortical networks via surface recordings-A critical note

We discuss potential caveats when estimating topologies of 3D brain networks from surface recordings. It is virtually impossible to record activity from all single neurons in the brain and one has to rely on techniques that measure average activity at sparsely located (non-invasive) recording sites Effects of this spatial sampling in relation to structural network measures like centrality and assortativity were analyzed using multivariate classifiers A simplified model of 3D brain connectivity incorporating both short- and long-range connections served for testing. To mimic M/EEG recordings we sampled this model via non-overlapping regions and weighted nodes and connections according to their proximity to the recording sites We used various complex network models for reference and tried to classify sampled versions of the ""brain-like"" network as one of these archetypes It was found that sampled networks may substantially deviate in topology from the respective original networks for small sample sizes For experimental studies this may imply that surface recordings can yield network structures that might not agree with its generating 3D network. (C) 2010 Elsevier Inc All rights reserved

Performance evaluation of routing protocols for MANETs with known connectivity patterns using evolving graphs

The assessment of routing protocols for mobile wireless networks is a difficult task, because of the networks` dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and some delay tolerant networks (DTNs), have more predictable dynamics, as the temporal variations in the network topology can be considered as deterministic, which may make them easier to study. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of such networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study about the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we use the NS2 network simulator to first implement an evolving graph based routing protocol, and then to use it as a benchmark when comparing the four major ad hoc routing protocols (AODV, DSR, OLSR and DSDV). Interestingly, our experiments show that evolving graphs have the potential to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like adaptive algorithms. We also discuss such issues in this paper, as a result of our experience.

Geodesics and Almost Geodesic Cycles in Random Regular Graphs

A geodesic in a graph G is a shortest path between two vertices of G. For a specific function e(n) of n, we define an almost geodesic cycle C in G to be a cycle in which for every two vertices u and v in C, the distance d(G)(u, v) is at least d(C)(u, v) - e(n). Let omega(n) be any function tending to infinity with n. We consider a random d-regular graph on n vertices. We show that almost all pairs of vertices belong to an almost geodesic cycle C with e(n)= log(d-1)log(d-1) n+omega(n) and vertical bar C vertical bar =2 log(d-1) n+O(omega(n)). Along the way, we obtain results on near-geodesic paths. We also give the limiting distribution of the number of geodesics between two random vertices in this random graph. (C) 2010 Wiley Periodicals, Inc. J Graph Theory 66: 115-136, 2011

Mapas cognitivos SODA ampliados: prescrição de um método para articular atitudes, comportamentos e seqüências cognitivas a mapas SODA

Este trabalho de tese tem por objetivo ampliar o alcance e aplicação de mapas SODA, preservando a metodologia originalmente desenvolvida. Inicialmente é realizada uma revisão do método, abordando de forma conjunta os artigos seminais, a teoria psicológica de Kelly e a teoria dos grafos; e ao final propomos uma identidade entre construtos de mapas SODA com os conhecimentos tácitos e explícitos, da gestão do conhecimento (KM). Essa sequencia introdutória é completada com uma visão de como os mapas SODA tem sido aplicado. No estágio seguinte o trabalho passa a analisar de forma crítica alguns pontos do método que dão margens a interpretações equivocadas. Sobre elas passamos a propor a aplicação de teorias, de diversos campos, tais como a teoria de means-end (Marketing), a teoria da atribuição e os conceitos de atitude (Psicologia), permitindo inferências que conduzem à proposição da primeira tese: mapas SODA são descritores de atitudes. O próximo estágio prossegue analisando criticamente o método, e foca no paradigma estabelecido por Eden, que não permite conferir ao método o status de descritor de comportamento. Propomos aqui uma mudança de paradigma, adotando a teoria da ação comunicativa, de Habermas, e sobre ela prescrevemos a teoria da ação e da escada da inferência (Action Science) e uma teoria da emoção (neuro ciência), o que permite novas inferências, que conduzem à proposição da segunda tese: mapas SODA podem descrever comportamentos. Essas teses servem de base para o alargamento de escopos do método SODA. É proposta aqui a utilização da teoria de máquinas de estado finito determinístico, designadas por autômato. Demonstramos um mapeamento entre autômato com mapas SODA, obtendo assim o autômato SODA, e sobre ele realizamos a última contribuição, uma proposta de mapas SODA hierárquicos, o que vem a possibilitar a descrição de sequencias de raciocínio, ordenando de forma determinística atitudes e comportamentos, de forma estruturada. A visão de como ela pode ser aplicada é realizada por meio de estudo de caso.

Mundos pequenos, produção acadêmica e grafos de colaboração: um estudo de caso dos Enanpads

Utilizando a base de dados dos trabalhos publicados nos Enanpads realizados em 2002-04, este artigo focaliza a área de administração da informação para realizar um estudo exploratório sobre a formação de padrões nas estruturas de disseminação do conhecimento acadêmico no Brasil, apoiado nos conceitos oriundos da análise das redes sociais e conjugados com a base proveniente da teoria dos grafos e em recursos computacionais. Procurou-se mapear os fluxos de informações que possibilitam as trocas de conhecimento através das ligações existentes no meio acadêmico. Os resultados indicam a necessidade de ampliar e estreitar os laços entre os autores, notadamente os que possuem algum grau de centralidade local, no intuito de obter o fortalecimento das instituições de ensino, de forma a quebrar as resistências à produção conjunta entre elas, em detrimento do padrão de reprodução endógena detectado.

Uma metodologia para modelagem e avaliação da dependabilidade de redes industriais sem fio

Ensuring the dependability requirements is essential for the industrial applications since faults may cause failures whose consequences result in economic losses, environmental damage or hurting people. Therefore, faced from the relevance of topic, this thesis proposes a methodology for the dependability evaluation of industrial wireless networks (WirelessHART, ISA100.11a, WIA-PA) on early design phase. However, the proposal can be easily adapted to maintenance and expansion stages of network. The proposal uses graph theory and fault tree formalism to create automatically an analytical model from a given wireless industrial network topology, where the dependability can be evaluated. The evaluation metrics supported are the reliability, availability, MTTF (mean time to failure), importance measures of devices, redundancy aspects and common cause failures. It must be emphasized that the proposal is independent of any tool to evaluate quantitatively the target metrics. However, due to validation issues it was used a tool widely accepted on academy for this purpose (SHARPE). In addition, an algorithm to generate the minimal cut sets, originally applied on graph theory, was adapted to fault tree formalism to guarantee the scalability of methodology in wireless industrial network environments (< 100 devices). Finally, the proposed methodology was validate from typical scenarios found in industrial environments, as star, line, cluster and mesh topologies. It was also evaluated scenarios with common cause failures and best practices to guide the design of an industrial wireless network. For guarantee scalability requirements, it was analyzed the performance of methodology in different scenarios where the results shown the applicability of proposal for networks typically found in industrial environments

Física estatística aplicada a sistemas sociais através do estudo de redes complexas

In this work a study of social networks based on analysis of family names is presented. A basic approach to the mathematical formalism of graphs is developed and then main theoretical models for complex networks are presented aiming to support the analysis of surnames networks models. These, in turn, are worked so as to be drawn leading quantities, such as aggregation coefficient, minimum average path length and connectivity distribution. Based on these quantities, it can be stated that surnames networks are an example of complex network, showing important features such as preferential attachment and small-world character

Anchor Areas to Improve Conservation and Increase Connectivity within the Brazilian "Mesopotamia of Biodiversity"

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)