Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

A scalable expressive ensemble learning using Random Prism: a MapReduce approach

The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the influence of noise in the data, ensemble learners are often applied. However, most ensemble learners are based on decision tree classifiers which are affected by noise. The Random Prism classifier has recently been proposed as an alternative to the popular Random Forests classifier, which is based on decision trees. Random Prism is based on the Prism family of algorithms, which is more robust to noise. However, like most ensemble classification approaches, Random Prism also does not scale well on large training data. This paper presents a thorough discussion of Random Prism and a recently proposed parallel version of it called Parallel Random Prism. Parallel Random Prism is based on the MapReduce programming paradigm. The paper provides, for the first time, novel theoretical analysis of the proposed technique and in-depth experimental study that show that Parallel Random Prism scales well on a large number of training examples, a large number of data features and a large number of processors. Expressiveness of decision rules that our technique produces makes it a natural choice for Big Data applications where informed decision making increases the user’s trust in the system.

Decimal growth stages for precision wheat production in changing environments?

The utility of the decimal growth stage (DGS) scoring system for cereals is reviewed. The DGS is the most widely used scale in academic and commercial applications because of its comprehensive coverage of cereal developmental stages, the ease of use and definition provided and adoption by official agencies. The DGS has demonstrable and established value in helping to optimise the timing of agronomic inputs, particularly with regard to plant growth regulators, herbicides, fungicides and soluble nitrogen fertilisers. In addition, the DGS is used to help parameterise crop models, and also in understanding the response and adaptation of crops to the environment. The value of the DGS for increasing precision relies on it indicating, to some degree, the various stages in the development of the stem apex and spike. Coincidence of specific growth stage scores with the transition of the apical meristem from a vegetative to a reproductive state, and also with the period of meiosis, is unreliable. Nonetheless, in pot experiments it is shown that the broad period of booting (DGS 41–49) appears adequate for covering the duration when the vulnerability of meiosis to drought and heat stress is exposed. Similarly, the duration of anthesis (61–69) is particularly susceptible to abiotic stresses: initially from a fertility perspective, but increasingly from a mean grain weight perspective as flowering progresses to DGS 69 and then milk development. These associations with DGS can have value at the crop level of organisation: for interpreting environmental effects, and in crop modelling. However, genetic, biochemical and physiological analysis to develop greater understanding of stress acclimation during the vegetative state, and tolerance at meiosis, does require more precision than DGS can provide. Similarly, individual floret analysis is needed to further understand the genetic basis of stress tolerance during anthesis.

Análise e projeto de superfícies seletivas de frequência com elementos pré-fractais para aplicações em comunicações indoor

In this thesis, a frequency selective surface (FSS) consists of a two-dimensional periodic structure mounted on a dielectric substrate, which is capable of selecting signals in one or more frequency bands of interest. In search of better performance, more compact dimensions, low cost manufacturing, among other characteristics, these periodic structures have been continually optimized over time. Due to its spectral characteristics, which are similar to band-stop or band-pass filters, the FSSs have been studied and used in several applications for more than four decades. The design of an FSS with a periodic structure composed by pre-fractal elements facilitates the tuning of these spatial filters and the adjustment of its electromagnetic parameters, enabling a compact design which generally has a stable frequency response and superior performance relative to its euclidean counterpart. The unique properties of geometric fractals have shown to be useful, mainly in the production of antennas and frequency selective surfaces, enabling innovative solutions and commercial applications in microwave range. In recent applications, the FSSs modify the indoor propagation environments (emerging concept called wireless building ). In this context, the use of pre-fractal elements has also shown promising results, allowing a more effective filtering of more than one frequency band with a single-layer structure. This thesis approaches the design of FSSs using pre-fractal elements based on Vicsek, Peano and teragons geometries, which act as band-stop spatial filters. The transmission properties of the periodic surfaces are analyzed to design compact and efficient devices with stable frequency responses, applicable to microwave frequency range and suitable for use in indoor communications. The results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as: fractal iteration number (or fractal level), scale factor, fractal dimension and periodicity of FSS, according the pre-fractal element applied on the surface. The analysis of the fractal dimension s influence on the resonant properties of a FSS is a new contribution in relation to researches about microwave devices that use fractal geometry. Due to its own characteristics and the geometric shape of the Peano pre-fractal elements, the reconfiguration possibility of these structures is also investigated and discussed. This thesis also approaches, the construction of efficient selective filters with new configurations of teragons pre-fractal patches, proposed to control the WLAN coverage in indoor environments by rejecting the signals in the bands of 2.4~2.5 GHz (IEEE 802.11 b) and 5.0~6.0 GHz (IEEE 802.11a). The FSSs are initially analyzed through simulations performed by commercial software s: Ansoft DesignerTM and HFSSTM. The fractal design methodology is validated by experimental characterization of the built prototypes, using alternatively, different measurement setups, with commercial horn antennas and microstrip monopoles fabricated for low cost measurements

Predicao de campo em comunicacao sem fio

Even living in the XXI century are still some difficulties in access to broadband Internet in several Brazilian cities, due to the purchasing power of people and lack of government investment. But even with these difficulties, we seek to encourage the use of wireless technology, which is based on the IEEE 802.11b protocol - also known as Wi-Fi (Wireless Fidelity) Wireless Fidelity Communications, having wide range of commercial applications in the world market, nationally and internationally. In Brazil, this technology is in full operation in major cities and has proved attractive in relation to the access point to multipoint and point-to-point. This paper is a comparative analysis of prediction field, using models based on the prediction of propagation loss. To validate the techniques used here, the Okumura-Hata models, modified Okumura-Hata, Walfisch-Ikegami model, were applied to a wireless computer network, located in the neighborhood of Cajupiranga in the city of Melbourn, in Rio Grande do Norte . They are used for networking wireless 802.11b, using the Mobile Radio to measure signal levels, beyond the heights of the antennas and distances from the transmitter. The performance data versus distance are added to the graphs generated and compared with results obtained through calculations of propagation models

Desenvolvimento de misturas instantâneas de mandioca e caseína: efeito do teor de proteína e parâmetros de extrusão sobre a viscosidade

O interesse da indústria de alimentos por produtos desenvolvidos a partir de farinhas acrescidas de proteína não se deve somente às suas características nutricionais, senão também às suas propriedades funcionais e reológicas, as quais definem as suas aplicações comerciais. Este trabalho teve por objetivo avaliar o efeito de parâmetros operacionais do processo de extrusão sobre as propriedades de pasta de misturas de farinha de mandioca e caseína. O processo de extrusão seguiu o delineamento 'central composto rotacional' para três fatores: teor de proteína (2,5 a 9,5%), umidade (14,5 a 19,5%) e temperatura de extrusão (65 a 135 ºC). As misturas antes e após a extrusão foram analisadas no Rapid Visco Analyser (RVA) quanto a: viscosidade inicial, pico de viscosidade, quebra de viscosidade, viscosidade final e tendência à retrogradação. Os resultados obtidos nas misturas antes da extrusão mostraram aumento dos valores de viscosidade com o aumento da concentração de proteína até o ponto central (6%) e, nos teores mais elevados de proteína, ocorreu redução destes. Após a extrusão, observou-se que o teor de proteína foi a variável de maior efeito sobre as propriedades de pasta, seguida pela umidade das misturas.

Effect of oxidizing and reducing atmospheres on the electrical properties of dense SnO2-based varistors

The SnO2 based varistor systems recently presented in the literature appear to have a promising potential in commercial applications. Experimental evidence shows that there is a dependence of nonlinear constant values with thermal treatment under different atmospheres. Thermal treatments in oxygen and nitrogen rich atmospheres at 900 degreesC prove this dependence, indicating that the nonlinear constant values are significantly lower when the material is submitted to a nitrogen atmosphere. Moreover, electrical properties can be restored when the varistor is subjected to thermal treatment at the same temperature in an oxygen atmosphere, indicating that the mechanism seems to be reversible. This paper discusses this behavior focusing in the grain boundary region. Ta2O5 mol% concentrations are also analyzed and the results indicate an optimum Ta2O5 concentration of 0.05 mol% for the electrical properties (alpha = 44 and E-B = 6150 V cm(-1)). (C) 2001 Elsevier B.V. Ltd. All rights reserved.

A NEW CU-BASED SMA WITH EXTREMELY HIGH MARTENSITIC-TRANSFORMATION TEMPERATURES

A new series of high temperature copper based shape memory alloys has recently been patented. These alloys contain 8-20 wt% Al, 1-20 wt% Ag, 0-2 wt% of a minor element (preferably Co), balance copper. The martensitic start transformation temperatures of these alloys are above 200 degrees C and, in some cases, they have good high temperature stability and may be useful in commercial applications where higher operating temperatures than those obtained from Cu-Zn-Al and Cu-Al-Ni shape memory alloys are required.

Photoelectrocatalytic production of active chlorine on nanocrystalline titanium dioxide thin-film electrodes

The production of chlorine and hypochlorite is of great economical and technological interest due to their large-scale use in many kinds of commercial applications. Yet, the current processes are not without problems such as inevitable side reactions and the high cost of production. This work reports the photoelectrocatalytic oxidation of chloride ions to free chlorine as it has been investigated by using titanium dioxide (TiO2) and several metal-doped titanium dioxide (M-TiO2) material electrodes. An average concentration of 800 mg L-1 of free chlorine was obtained in an open-air reactor using a TiO2 thin-film electrode biased at +1.0 V (SCE) and illuminated by UV light. The M-doped electrodes have performed poorly compared with the pure TiO2 counterpart. Test solutions containing 0.05 mol L-1 NaCl pH 2.0-4.0 were found to be the best conditions for fast production of free chlorine. A complete investigation of all parameters that influence the global process of chlorine production by the photoelectrocatalytic method such as applied potential, concentration of NaCl, pH solution, and time is presented in detail. In addition, photocurrent vs potential curves and the reaction order are also discussed.

Biomass-to-bio-products application of feruloyl esterase from Aspergillus clavatus

The structural polysaccharides contained in plant cell walls have been pointed to as a promising renewable alternative to petroleum and natural gas. Ferulic acid is a ubiquitous component of plant polysaccharides, which is found in either monomeric or dimeric forms and is covalently linked to arabinosyl residues. Ferulic acid has several commercial applications in food and pharmaceutical industries. The study herein introduces a novel feruloyl esterase from Aspergillus clavatus (AcFAE). Along with a comprehensive functional and biophysical characterization, the low-resolution structure of this enzyme was also determined by small-angle X-ray scattering. In addition, we described the production of phenolic compounds with antioxidant capacity from wheat arabinoxylan and sugarcane bagasse using AcFAE. The ability to specifically cleave ester linkages in hemicellulose is useful in several biotechnological applications, including improved accessibility to lignocellulosic enzymes for biofuel production. © 2012 Springer-Verlag Berlin Heidelberg.

Características reológicas do exopolissacarídeo botiosferana produzido pelo Botryosphaeria rhodina MAMB-05 em três fontes de carbono: glucose, frutose e sacarose

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Propriedades reológicas de exopolissacarídeos produzidos por bactérias dos gêneros

Pós-graduação em Engenharia e Ciência de Alimentos - IBILCE

Estudo da produção de dextranasacarase por Leuconostoc mesenteroides FT 045 B

Pós-graduação em Ciências Biológicas (Microbiologia Aplicada) - IBRC

Desenvolvimento de cerâmicas de mulita a partir de alumina, ácido silícico e aerosil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Complexo xilanolítico de Penicillium sclerotiorum: produção, purificação e caracterização de xilanases e de ß-xilosidases

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