Modeling of Distributed Control Systems in Intelligent Building based on Colored Petri Nets

Distributed control systems consist of sensors, actuators and controllers, interconnected by communication networks and are characterized by a high number of concurrent process. This work presents a proposal for a procedure to model and analyze communication networks for distributed control systems in intelligent building. The approach considered for this purpose is based on the characterization of the control system as a discrete event system and application of coloured Petri net as a formal method for specification, analysis and verification of control solutions. With this approach, we develop the models that compose the communication networks for the control systems of intelligent building, which are considered the relationships between the various buildings systems. This procedure provides a structured development of models, facilitating the process of specifying the control algorithm. An application example is presented in order to illustrate the main features of this approach.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Building binary-tree-based multiclass classifiers using separability measures

Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.

sigma- and pi-defects at graphene nanoribbon edges: Building spin filters

The presence of certain kinds of defects at the edges of monohydrogenated zigzag graphene nanoribbons changes dramatically the charge transport properties inducing a spin-polarized conductance. Using an approach based on density functional theory and nonequilibrium Green`s function formalism to calculate the transmittance, we classify the defects in different classes depending on their distinct transport properties: (i) sigma-defects, which do not affect the transmittance close to the Fermi energy (E(F)); and (ii) pi-defects, which cause a spin polarization of the transmittance and that can be further divided into either electron or hole defects if the spin transport polarization results in larger transmittance for the up or down spin channel, respectively.

Silsesquioxane as a New Building Block Material for Modified Electrodes Fabrication and Application as Neurotransmitters Sensors

Nanostructured films comprising a 3-n-propylpyridiniunn silsesquioxane polymer (designated as SiPy(+)Cl(-)) and copper (II) tetrasulfophthalocyanine (CuTsPc) were produced using the Layer-by-Layer technique (LbL). To our knowledge this is the first report on the use of silsesquioxane derivative polymers as building blocks for nanostructured thin films fabrication. Deposition of the multilayers were monitored by UV-Vis spectroscopy revealing the linear increment in the absorbance of the Q-band from CuTsPc at 617 nm with the number of SiPy(+)Cl(-)/CuTsPc or CuTsPc/SiPy(+)Cl(-) bilayers. FTIR analyses showed that specific interactions between SiPy+Cl- and CuTsPc occurred between SO(3)(-) groups of tetrasulfophthalocyanine and the pyridinium groups of the polycation. Morphological studies were carried out using the AFM technique, which showed that the roughness and thickness of the films increase with the number of bilayers. The films displayed electroactivity and were employed to detection of dopamine (DA) and ascorbic acid (AA) using cyclic voltammetry, at concentrations ranging from 1.96 x 10(-4) to 1.31 x 10(-3) molL(-1). The number and the sequence of bilayers deposition influenced the electrochemical response in presence of DA and AA. Using differential pulse technique, films comprising SiPy(+)/CuTsPc were able to distinguish between DA and ascorbic acid (AA), with a potential difference of approximately with 500 mV, in the concentration range of 9.0 x 10(-5) to 2.0 x 10(-4) molL(-1), in pH 3.0.

The use of colloidal ferrofluid as building blocks for nanostructured layer-by-layer films fabrication

The electrostatic layer-by-layer technique has been exploited as an useful strategy for fabrication of nanostructured thin films, in which specific properties can be controlled at the molecular level. Ferrofluids consist of a colloidal suspension of magnetic grains (with only a few nanometers of diameter) with present interesting physical properties and applications, ranging from telecommunication to drug delivery systems. In this article, we developed a new strategy to manipulate ferrofluids upon their immobilization in nanostructured layered films in conjunction with conventional polyelectrolytes using the layer-by-layer technique. We investigated the morphological, optical, and magnetic properties of the immobilized ferrofluid as a function of number of bilayers presented in the films. Ferrofluid/polyelectrolyte multilayers homogeneously covered the substrates surface, and the magnetic and optical properties of films exhibited a linear dependence on the number of bilayers adsorbed.

Experimental micromorphology in Tierra del Fuego (Argentina): building a reference collection for the study of shell middens in cold climates

Commonly used in archaeological contexts, micromorphology did not see a parallel advance in the field of experimental archaeology. Drawing from early work conducted in the 1990`s on ethnohistoric sites in the Beagle Channel, we analyze a set of 25 thin sections taken from control features and experimental tests. The control features include animal pathways and environmental contexts (beach samples, forest litter, soils from the proximities of archaeological sites), while the experimental samples comprise anthropic structures, such as hearths, and valves of Mytilus edulis (the most important component of shell middens in the region) heated from 200 degrees C to 800 degrees C. Their micromorphological study constitutes a modern analogue to assist archaeologists studying site formation and ethnographical settings in cold climates, with particular emphasis on shell midden contexts. (c) 2010 Elsevier Ltd. All rights reserved.

Dinuclear Azide-Bridged Copper(II) Complex as Building Block for the Assembly of a 2D-Supramolecular Array

A novel Schiff base-copper(II) complex [Cu(2)L(2)(N(3))(2)](ClO(4))(2) 1, where L = (4-imidazolyl)ethylene-2-amino-1-ethylpyridine (apyhist), containing azide-bridges between adjacent copper ions in a dinuclear arrangement was isolated and characterized both in the solid state and in solution by X-ray crystallography and different spectroscopic techniques. Azide binding constants were estimated from titrations of the precursor [CuL(H(2)O)(2)](2+) solutions with sodium azide, giving rise to the azido-bridged species, [Cu(2)L(2)(N(3))(2)](2+). Raman spectra showed asymmetric stretching band at 2060 cm(-1), indicating the presence of azido ligands with a symmetric mu(1,) (1) binding geometry. EPA spectra, in frozen methanol/water solutions at 77 K, exhibited characteristic features of copper centers in tetragonal pyramidal coordination geometry, exhibiting magnetic interactions between them. Further, in solid state, two different values for magnetic coupling in this species were obtained, J/k = -(5.14 +/- 0.02) cm(-1) attributed to the mu(1, 1) azide-bridge mode, and J`z`/k = -(2.94 +/- 0.11) cm(-1) for the interaction between dinuclear moieties via water/perchorate bridges. Finally, an attempt was made to correlate structure and magnetic data for this dinuclear asymmetric end-on azido bridged-copper(II) 1 complex with those of another correlated dinuclear system, complex [Cu(2)L(2)Cl(2)](ClO(4))(2) 2, containing the same tridentate diimine ligand, but with chloro-bridged groups between the copper centres.

Validation of an experimental polyurethane model for biomechanical studies on implant supported prosthesis - tension tests

OBJECTIVES: The complexity and heterogeneity of human bone, as well as ethical issues, frequently hinder the development of clinical trials. The purpose of this in vitro study was to determine the modulus of elasticity of a polyurethane isotropic experimental model via tension tests, comparing the results to those reported in the literature for mandibular bone, in order to validate the use of such a model in lieu of mandibular bone in biomechanical studies. MATERIAL AND METHODS: Forty-five polyurethane test specimens were divided into 3 groups of 15 specimens each, according to the ratio (A/B) of polyurethane reagents (PU-1: 1/0.5, PU-2: 1/1, PU-3: 1/1.5). RESULTS: Tension tests were performed in each experimental group and the modulus of elasticity values found were 192.98 MPa (SD=57.20) for PU-1, 347.90 MPa (SD=109.54) for PU-2 and 304.64 MPa (SD=25.48) for PU-3. CONCLUSION: The concentration of choice for building the experimental model was 1/1.

Inteligência artificial aplicada à Zootecnia

Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

Saving our science from ourselves: the plight of biological classification

Saving our science from ourselves: the plight of biological classification. Biological classification ( nomenclature, taxonomy, and systematics) is being sold short. The desire for new technologies, faster and cheaper taxonomic descriptions, identifications, and revisions is symptomatic of a lack of appreciation and understanding of classification. The problem of gadget-driven science, a lack of best practice and the inability to accept classification as a descriptive and empirical science are discussed. The worst cases scenario is a future in which classifications are purely artificial and uninformative.

Functionalized adamantane: Building blocks for nanostructure self-assembly

We report first-principles calculations on the electronic and structural properties of chemically functionalized adamantane molecules, either in isolated or crystalline forms. Boron and nitrogen functionalized molecules, aza-, tetra-aza-, bora-, and tetra-bora-adamantane, were found to be very stable in terms of energetics, consistent with available experimental data. Additionally, a hypothetical molecular crystal in a zincblende structure, involving the pair tetra-bora-adamantane and tetra-aza-adamantane, was investigated. This molecular crystal presented a direct and large electronic band gap and a bulk modulus of 20 GPa. The viability of using those functionalized molecules as fundamental building blocks for nanostructure self-assembly is discussed.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Building a Open Source Framework for Virtual Medical Training

This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.