Soft topographic map for clustering and classification of bacteria

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification or erroneous annotations in the database.

Efficient tree construction for the multicast problem

A new heuristic for the Steiner Minimal Tree problem is presented here. The method described is based on the detection of particular sets of nodes in networks, the “Hot Spot” sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used CIS comparison terms in the experimental analysis which demonstrates the goodness of the heuristic discussed in this paper.

Efficient tree construction for the multicast problem

A new heuristic for the Steiner minimal tree problem is presented. The method described is based on the detection of particular sets of nodes in networks, the “hot spot” sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used as comparison terms in the experimental analysis which demonstrates the capability of the heuristic discussed

Space partitioning for scalable K-means

K-Means is a popular clustering algorithm which adopts an iterative refinement procedure to determine data partitions and to compute their associated centres of mass, called centroids. The straightforward implementation of the algorithm is often referred to as `brute force' since it computes a proximity measure from each data point to each centroid at every iteration of the K-Means process. Efficient implementations of the K-Means algorithm have been predominantly based on multi-dimensional binary search trees (KD-Trees). A combination of an efficient data structure and geometrical constraints allow to reduce the number of distance computations required at each iteration. In this work we present a general space partitioning approach for improving the efficiency and the scalability of the K-Means algorithm. We propose to adopt approximate hierarchical clustering methods to generate binary space partitioning trees in contrast to KD-Trees. In the experimental analysis, we have tested the performance of the proposed Binary Space Partitioning K-Means (BSP-KM) when a divisive clustering algorithm is used. We have carried out extensive experimental tests to compare the proposed approach to the one based on KD-Trees (KD-KM) in a wide range of the parameters space. BSP-KM is more scalable than KDKM, while keeping the deterministic nature of the `brute force' algorithm. In particular, the proposed space partitioning approach has shown to overcome the well-known limitation of KD-Trees in high-dimensional spaces and can also be adopted to improve the efficiency of other algorithms in which KD-Trees have been used.

Epidemic K-Means clustering

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. This work proposes a fully decentralised algorithm (Epidemic K-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art distributed K-Means algorithms based on sampling methods. The experimental analysis confirms that the proposed algorithm is a practical and accurate distributed K-Means implementation for networked systems of very large and extreme scale.

Symmetric Push-Sum Protocol for decentralised aggregation

Gossip (or Epidemic) protocols have emerged as a communication and computation paradigm for large-scale networked systems. These protocols are based on randomised communication, which provides probabilistic guarantees on convergence speed and accuracy. They also provide robustness, scalability, computational and communication efficiency and high stability under disruption. This work presents a novel Gossip protocol named Symmetric Push-Sum Protocol for the computation of global aggregates (e.g., average) in decentralised and asynchronous systems. The proposed approach combines the simplicity of the push-based approach and the efficiency of the push-pull schemes. The push-pull schemes cannot be directly employed in asynchronous systems as they require synchronous paired communication operations to guarantee their accuracy. Although push schemes guarantee accuracy even with asynchronous communication, they suffer from a slower and unstable convergence. Symmetric Push- Sum Protocol does not require synchronous communication and achieves a convergence speed similar to the push-pull schemes, while keeping the accuracy stability of the push scheme. In the experimental analysis, we focus on computing the global average as an important class of node aggregation problems. The results have confirmed that the proposed method inherits the advantages of both other schemes and outperforms well-known state of the art protocols for decentralized Gossip-based aggregation.

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

Efficient wireless power delivery for biomedical implants

Power delivery for biomedical implants is a major consideration in their design for both measurement and stimulation. When performed by a wireless technique, transmission efficiency is critically important not only because of the costs associated with any losses but also because of the nature of those losses, for example, excessive heat can be uncomfortable for the individual involved. In this study, a method and means of wireless power transmission suitable for biomedical implants are both discussed and experimentally evaluated. The procedure initiated is comparable in size and simplicity to those methods already employed; however, some of Tesla’s fundamental ideas have been incorporated in order to obtain a significant improvement in efficiency. This study contains a theoretical basis for the approach taken; however, the emphasis here is on practical experimental analysis

Efficient wireless power delivery for biomedical implants

Power delivery for biomedical implants is a major consideration in their design for both measurement and stimulation. When performed by a wireless technique, transmission efficiency is critically important not only because of the costs associated with any losses but also because of the nature of those losses, for example, excessive heat can be uncomfortable for the individual involved. In this study, a method and means of wireless power transmission suitable for biomedical implants are both discussed and experimentally evaluated. The procedure initiated is comparable in size and simplicity to those methods already employed; however, some of Tesla’s fundamental ideas have been incorporated in order to obtain a significant improvement in efficiency. This study contains a theoretical basis for the approach taken; however, the emphasis here is on practical experimental analysis.

Aspectos psicológicos do controle social

O presente trabalho constitui uma tentativa de exploração dos aspectos psicológicos inerentes ao processo de controle social, segundo a perspectiva da "análise experimental do comportamento" de B. F. Skinner. Diversas proposições sociológicas correntes sobre algumas dimensões do problema geral são levantadas e criticamente articuladas com a abordagem comportamental skinneriana. No primeiro capítulo - "O Controle Social nas Instituições Totais”, é feita uma introdução conceitual ao condicionamento operante aproveitando-se para isso a descrição sociológica realizada por Goffman da vida naquelas instituições, são também aí discutidas algumas das interpretações erroneas das proposições skinnerianas e seus maus usos nas organizações fechadas. Desenvolve-se, no segundo capítulo, um exame comparativo das ficções literárias de "1984 “ e "Walden II", com o propósito de pela focalização de suas técnicas características de controle social, suscitar já, de modo informal, diversos pontos críticos do problema, que vêm a receber tratamento mais pormenorizado nos três capítulos seguintes. Em "Controle Social na Vida Cotidiana", discute-se a natureza difusa que o controle assume nesse contexto mais amplo, ressaltando-se o emprego que se faz, para esse fim, de artifícios motivacionais e ideológicos. Para a articulação com o pensamento skinneriano, é privilegiada abordagem da Sociologia do Conhecimento proposta por Berger e Luckmann. No quarto capítulo, que trata da "Identificação de Controladores e Controlados", procede-se a uma reinterpretação comportamentista dos constructos cognitivistas de “intenção” e "percepção”, com que comumente se descreve as iniciativas de controle por parte dos atores sociais. A análise de Becker dos mecanismos de criação e imposição de regras é utilizada par a apoiar a estratégia de reinterpretação. O capítulo final explora uma dimensão menos tradicional do problema - "O Controle para a Mudança Social". As proposições específicas de dois autores Popper e Mannheim - são aqui articuladas com as de Skinner. Caracterizado o estado da sociedade contemporânea como de incessante mudança desordenada, discute-se as condições necessárias para uma mudança planejada e suas implicações psicossociais. Na conclusão do trabalho, busca-se ampliar a perspectiva histórica do problema do controle social, por meio de uma análise retrospectiva proporcionada por Schneider e uma especulação prospectiva envolvendo a apreciação sócio- política do controle gradualista e democrático da mudança social. Defende-se, durante essa apreciação, a tese de que a engenharia comportamental de Skinner é gradualista e democrática em seu todo.

Antenas planares integradas com FSSs para aplicações em sistemas de comunicações sem fio

This work presents a theoretical and experimental analysis about the properties of microstrip antennas with integrated frequency selective surfaces (Frequency Selective Surface - FSS). The integration occurs through the insertion of the FSS on ground plane of microstrip patch antenna. This integration aims to improve some characteristics of the antennas. The FSS using patch-type elements in square unit cells. Specifically, the simulated results are obtained using the commercial computer program CST Studio Suite® version 2011. From a standard antenna, designed to operate in wireless communication systems of IEEE 802.11 a / b / g / n the dimensions of the FSS are varied to obtain an optimization of some antenna parameters such as impedance matching and selectivity in the operating bands. After optimization of the investigated parameters are built two prototypes of microstrip patch antennas with and without the FSS ground plane. Comparisons are made of the results with the experimental results by 14 ZVB network analyzer from Rohde & Schwarz ®. The comparison aims to validate the simulations performed and show the improvements obtained with the FSS in integrated ground plane antenna. In the construction of prototypes, we used dielectric substrates of the type of Rogers Corporation RT-3060 with relative permittivity equal to 10.2 and low loss tangent. Suggestions for continued work are presented

Taking Advantage of Electrostatic Interactions To Grow Langmuir-Blodgett Films Containing Multilayers of the Phospholipid Dipalmitoylphosphatidylglycerol

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DCM Boost interleaved converter for operation in AC and DC to trolleybus application

This paper is based on the development and experimental analysis of a DCM Boost interleaved converter suitable for application in traction systems of electrical vehicles pulled by electrical motors (Trolleybus), which are powered by urban DC or AC distribution networks. This front-end structure is capable of providing significant improvements in trolleybuses systems and in the urban distribution network costs, and efficiency. The architecture of proposed converter is composed by five boost power cells in interleaving connection, operating in discontinuous conduction mode. Furthermore, the converter can operate as AC-DC converter, or as DC-DC converter providing the proper DC output voltage range required by DC or AC adjustable speed drivers. Therefore, when supplied by single-phase AC distribution networks, and operating as AC-DC converter, it is capable to provide high power factor, reduced harmonic distortion in the input current, complying with the restrictions imposed by the IEC 61000-3-4 standards. The digital controller has been implemented using a low cost FPGA and developed totally using a hardware description language VHDL and fixed point arithmetic. Thus, two control strategies are evaluated considering the compliance with input current restrictions imposed by IEC 61000-3-4 standards, the regular PWM modulation and a current correction PWM modulation. In order to verify the feasibility and performance of the proposed system, experimental results from a 15 kW low power scale prototype are presented, operating in DC and AC conditions.

Sizing PZT Transducers in Impedance-Based Structural Health Monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritomos transgenéticos aplicados ao problema da árvore geradora biobjetivo

The Multiobjective Spanning Tree is a NP-hard Combinatorial Optimization problem whose application arises in several areas, especially networks design. In this work, we propose a solution to the biobjective version of the problem through a Transgenetic Algorithm named ATIS-NP. The Computational Transgenetic is a metaheuristic technique from Evolutionary Computation whose inspiration relies in the conception of cooperation (and not competition) as the factor of main influence to evolution. The algorithm outlined is the evolution of a work that has already yielded two other transgenetic algorithms. In this sense, the algorithms previously developed are also presented. This research also comprises an experimental analysis with the aim of obtaining information related to the performance of ATIS-NP when compared to other approaches. Thus, ATIS-NP is compared to the algorithms previously implemented and to other transgenetic already presented for the problem under consideration. The computational experiments also address the comparison to two recent approaches from literature that present good results, a GRASP and a genetic algorithms. The efficiency of the method described is evaluated with basis in metrics of solution quality and computational time spent. Considering the problem is within the context of Multiobjective Optimization, quality indicators are adopted to infer the criteria of solution quality. Statistical tests evaluate the significance of results obtained from computational experiments