Particle competition for complex network community detection

In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a way that each of them tries to possess as many nodes as possible. Moreover, we introduce a rule to adjust the level of randomness of particle walking in the network, and we have found that a portion of randomness can largely improve the community detection rate. Computer simulations show that the model has good community detection performance and at the same time presents low computational complexity. (C) 2008 American Institute of Physics.

Performance analysis of an optical network employing waveband and traffic grooming

This paper analyses an optical network architecture composed by an arrangement of nodes equipped with multi-granular optical cross-connects (MG-OXCs) in addition to the usual optical cross-connects (OXCs). Then, selected network nodes can perform both waveband as well as traffic grooming operations and our goal is to assess the improvement on network performance brought by these additional capabilities. Specifically, the influence of the MG-OXC multi-granularity on the blocking probability is evaluated for 16 classes of service over a network based on the NSFNet topology. A mechanism of fairness in bandwidth capacity is also added to the connection admission control to manage the blocking probabilities of all kind of bandwidth requirements. Comprehensive computational simulation are carried out to compare eight distinct node architectures, showing that an adequate combination of waveband and single-wavelength ports of the MG-OXCs and OXCs allow a more efficient operation of a WDM optical network carrying multi-rate traffic.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Title Model for Computer Networks Optimization

The TCP/IP architecture was consolidated as a standard to the distributed systems. However, there are several researches and discussions about alternatives to the evolution of this architecture and, in this study area, this work presents the Title Model to contribute with the application needs support by the cross layer ontology use and the horizontal addressing, in a next generation Internet. For a practical viewpoint, is showed the network cost reduction for the distributed programming example, in networks with layer 2 connectivity. To prove the title model enhancement, it is presented the network analysis performed for the message passing interface, sending a vector of integers and returning its sum. By this analysis, it is confirmed that the current proposal allows, in this environment, a reduction of 15,23% over the total network traffic, in bytes.

Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

A modified epidemiological model for computer viruses

Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.

Dynamic models for computer viruses

Computer viruses are an important risk to computational systems endangering either corporations of all sizes or personal computers used for domestic applications. Here, classical epidemiological models for disease propagation are adapted to computer networks and, by using simple systems identification techniques a model called SAIC (Susceptible, Antidotal, Infectious, Contaminated) is developed. Real data about computer viruses are used to validate the model. (c) 2008 Elsevier Ltd. All rights reserved.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Computational binding assays of antigenic peptides

Computer models can be combined with laboratory experiments for the efficient determination of (i) peptides that bind MHC molecules and (ii) T-cell epitopes. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures. This requires the definition of standards and experimental protocols for model application. We describe the requirements for validation and assessment of computer models. The utility of combining accurate predictions with a limited number of laboratory experiments is illustrated by practical examples. These include the identification of T-cell epitopes from IDDM-, melanoma- and malaria-related antigens by combining computational and conventional laboratory assays. The success rate in determining antigenic peptides, each in the context of a specific HLA molecule, ranged from 27 to 71%, while the natural prevalence of MHC-binding peptides is 0.1-5%.

A randomized controlled trial comparing a computer-assisted insulin infusion protocol with a strict and a conventional protocol for glucose control in critically ill patients

Purpose: The objective of this study is to evaluate blood glucose (BG) control efficacy and safety of 3 insulin protocols in medical intensive care unit (MICU) patients. Methods: This was a multicenter randomized controlled trial involving 167 MICU patients with at least one BG measurement +/- 150 mg/dL and one or more of the following: mechanical ventilation, systemic inflammatory response syndrome, trauma, or burns. The interventions were computer-assisted insulin protocol (CAIP), with insulin infusion maintaining BG between 100 and 130 mg/dL; Leuven protocol, with insulin maintaining BG between 80 and 110 mg/dL; or conventional treatment-subcutaneous insulin if glucose > 150 mg/dL. The main efficacy outcome was the mean of patients` median BG, and the safety outcome was the incidence of hypoglycemia (<= 40 mg/dL). Results: The mean of patients` median BG was 125.0, 127.1, and 158.5 mg/dL for CAIP, Leuven, and conventional treatment, respectively (P = .34, CAIP vs Leuven; P < .001, CAIP vs conventional). In CAIP, 12 patients (21.4%) had at least one episode of hypoglycemia vs 24 (41.4%) in Leuven and 2 (3.8%) in conventional treatment (P = .02, CAIP vs Leuven; P = .006, CAIP vs conventional). Conclusions: The CAIP is safer than and as effective as the standard strict protocol for controlling glucose in MICU patients. Hypoglycemia was rare under conventional treatment. However, BG levels were higher than with IV insulin protocols. (C) 2009 Elsevier Inc. All rights reserved.

Network structures of Bis-GMA/TEGDMA resins differ in DC, shrinkage-strain, hardness and optical properties as a function of reducing agent

Objectives. To evaluate the influence of different tertiary amines on degree of conversion (DC), shrinkage-strain, shrinkage-strain rate, Knoop microhardness, and color and transmittance stabilities of experimental resins containing BisGMA/TEGDMA (3: 1 wt), 0.25wt% camphorquinone, 1wt% amine (DMAEMA, CEMA, DMPT, DEPT or DABE). Different light-curing protocols were also evaluated. Methods. DC was evaluated with FTIR-ATR and shrinkage-strain with the bonded-disk method. Shrinkage-strain-rate data were obtained from numerical differentiation of shrinkage-strain data with respect to time. Color stability and transmittance were evaluated after different periods of artificial aging, according to ISO 7491: 2000. Results were evaluated with ANOVA, Tukey, and Dunnett`s T3 tests (alpha = 0.05). Results. Studied properties were influenced by amines. DC and shrinkage-strain were maximum at the sequence: CQ < DEPT < DMPT <= CEMA approximate to DABE < DMAEMA. Both DC and shrinkage were also influenced by the curing protocol, with positive correlations between DC and shrinkage-strain and DC and shrinkage-strain rate. Materials generally decreased in L* and increased in b*. The strong exception was the resin containing DMAEMA that did not show dark and yellow shifts. Color varied in the sequence: DMAEMA < DEPT < DMPT < CEMA < DABE. Transmittance varied in the sequence: DEPT approximate to DABE < DABE approximate to DMPT approximate to CEMA < DMPT approximate to CEMA approximate to DMAEMA, being more evident at the wavelength of 400 nm. No correlations between DC and optical properties were observed. Significance. The resin containing DMAEMA showed higher DC, shrinkage-strain, shrinkage-strain rate, and microhardness, in addition to better optical properties. (C) 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Efficient implementation of a dominance protocol for wireless medium access

Mestrado em Engenharia Electrotécnica e de Computadores

QoS em WIMAX – Análise e avaliação de módulos para simulação com o ns-2

Mestrado em Engenharia Electrotécnica e de Computadores