Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Methodological and Technological Support for the Coordination of Smart Networks of SMEs

Part 2: Behaviour and Coordination

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

Left-handed metamaterial coatings for subwavelength-resolution imaging

We report on a procedure to improve the resolution of far-field imaging by using a neighboring high-index medium that is coated with a left-handed metamaterial. The resulting plot can also exhibit an enhanced transmission by considering proper conditions to retract backscattering. Based on negative refraction, geometrical aberrations are considered in detail since they may cause a great impact in this sort of diffraction-unlimited imaging by reducing its resolution power. We employ a standard aberration analysis to refine the asymmetric configuration of metamaterial superlenses. We demonstrate that low-order centrosymmetric aberrations can be fully corrected for a given object plane. For subwavelength-resolution imaging, however, high-order aberrations become of relevance, which may be balanced with defocus. Not only the point spread function but also numerical simulations based on the finite-element method support our theoretical analysis, and subwavelength resolution is verified in the image plane.

Subwavelength Bessel beams in wire media

Recent progress is emerging on nondiffracting subwavelength fields propagating in complex plasmonic nanostructures. In this paper, we present a thorough discussion on diffraction-free localized solutions of Maxwell’s equations in a periodic structure composed of nanowires. This self-focusing mechanism differs from others previously reported, which lie on regimes with ultraflat spatial dispersion. By means of the Maxwell–Garnett model, we provide a general analytical expression of the electromagnetic fields that can propagate along the direction of the cylinder’s axis, keeping its transverse waveform unaltered. Numerical simulations based on the finite element method support our analytical approach. In particular, moderate filling fractions of the metallic composite lead to nonresonant-plasmonic spots of light propagating with a size that remains far below the limit of diffraction.

A INFLUÊNCIA DA COMPATIBILIDADE PESSOA-TRABALHO SOBRE O ENGAJAMENTO NO TRABALHO SÃO BERNARDO DO CAMPO 2015

O engajamento no trabalho é um dos objetivos dos gestores de pessoas. Este trabalho se propõe a analisar se a compatibilidade da pessoa com o ambiente de trabalho tem relação com o seu engajamento. Há três fatores na compatibilidade com o ambiente de trabalho (person-environment fit): person-job fit, que aborda a compatibilidade entre as habilidades da pessoa e o trabalho que ela realiza; person-organization fit, que está relacionado com os valores da pessoa frente os valores organizacionais; e needs-supply, que aborda a percepção do indivíduo quanto a ter suas necessidades atendidas pelo seu trabalho e pela organização em que trabalha. Construtos do comportamento organizacional, tais como satisfação no trabalho, comprometimento organizacional e intenções de rotatividade são comumente utilizados como variáveis sucessoras nos estudos de compatibilidade (fit), porém não foram encontrados estudos da relação entre a compatibilidade com o ambiente de trabalho (person-environment fit) e o engajamento no trabalho. Esta pesquisa de abordagem quantitativa baseou-se no instrumento Perceptions Fit, proposto por Cable e DeRue, em 2002; e no instrumento UWES Ultrech Work Engagement Scale, de Schaufelli e colaboradores, de 2006. Participaram da pesquisa 114 respondentes com no mínimo seis meses na atividade atual e pelo menos há cinco anos no mercado de trabalho. As análises por Modelagem de Equações Estruturais pelo método PLS (Partial Least Squares) comprovaram a hipótese de que quanto maior a compatibilidade entre a pessoa e seu trabalho, maior é seu engajamento. Além da hipótese central do trabalho de que a compatibilidade pessoa-trabalho influencia o engajamento no trabalho, a influência das dimensões de fit sobre o engajamento foi testada e os resultados mostraram que a dimensão necessidades atendidas (needs-supply) é a que mais influência tem sobre o engajamento. Este estudo inicia a discussão sobre a relação entre a compatibilidade da pessoa com o ambiente de trabalho e o seu engajamento, sugerindo reaplicação do método em públicos diferenciados, a fim de que os resultados possam ser utilizados para uma melhor eficácia da gestão de pessoas.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Methodology for real-time adaptation of tunnels support using the observational method

The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

A Method and Tool to Support the Analysis and Enhance the Understanding of Peer-to-Peer Learning Experiences

In this paper we look at how a web-based social software can be used to make qualitative data analysis of online peer-to-peer learning experiences. Specifically, we propose to use Cohere, a web-based social sense-making tool, to observe, track, annotate and visualize discussion group activities in online courses. We define a specific methodology for data observation and structuring, and present results of the analysis of peer interactions conducted in discussion forum in a real case study of a P2PU course. Finally we discuss how network visualization and analysis can be used to gather a better understanding of the peer-to-peer learning experience. To do so, we provide preliminary insights on the social, dialogical and conceptual connections that have been generated within one online discussion group.

Buffer Capacity Allocation: A method to QoS support on MPLS networks

This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network

Evaluation of the multicriteria approval method for timber-harvesting group decision support

Abstract

A support system for evaluating a suitable joining method in the production of sheet metal goods

This report illustrates a comparative study of various joining methods involved in sheet metal production. In this report it shows the selection of joining methods, which includes comparing the advantages and disadvantages of a method over the other ones and choosing the best method for joining. On the basis of various joining process from references, a table is generated containing set of criterion that helps in evaluation of various sheet metal joining processes and in selecting the most suitable process for a particular product. Three products are selected and a comprehensive study of the joining methods is analyzed with the help of various parameters. The table thus is the main part of the analysis process of this study and can be advanced with the beneficial results. It helps in a better and easy understanding and comparing the various methods, which provides the foundation of this study and analysis. The suitability of the joining method for various types of cases of different sheet metal products can be tested with the help of this table. The sections of the created table display the requirements of manufacturing. The important factor has been considered and given focus in the table, as how the usage of these parameters is important in percentages according to particular or individual case. The analysis of the methods can be extended or altered by changing the parameters according to the constraint. The use of this table is demonstrated by pertaining the cases from sheet metal production.

Support for a demographically based selection method at University: The role of competition

Building on the instrumental model of group conflict (IMGC), the present experiment investigates the support for discriminatory and meritocratic method of selections at university in a sample of local and immigrant students. Results showed that local students were supporting in a larger proportion selection method that favors them over immigrants in comparison to method that consists in selecting the best applicants without considering his/her origin. Supporting the assumption of the IMGC, this effect was stronger for locals who perceived immigrants as competing for resources. Immigrant students supported more strongly the meritocratic selection method than the one that discriminated them. However, contrasting with the assumption of the IMGC, this effect was only present in students who perceived immigrants as weakly competing for locals' resources. Results demonstrate that selection methods used at university can be perceived differently depending on students' origin. Further, they suggest that the mechanisms underlying the perception of discriminatory and meritocratic selection methods differ between local and immigrant students. Hence, the present experiment makes a theoretical contribution to the IMGC by delimiting its assumptions to the ingroup facing a competitive situation with a relevant outgroup. Practical implication for universities recruitment policies are discussed.

Synthesis of Short Oligonucleotides on a Soluble Support by the Phosphoramidite Method

In the last decades, the chemical synthesis of short oligonucleotides has become an important aspect of study due to the discovery of new functions for nucleic acids such as antisense oligonucleotides (ASOs), aptamers, DNAzymes, microRNA (miRNA) and small interfering RNA (siRNA). The applications in modern therapies and fundamental medicine on the treatment of different cancer diseases, viral infections and genetic disorders has established the necessity to develop scalable methods for their cheaper and easier industrial manufacture. While small scale solid-phase oligonucleotide synthesis is the method of choice in the field, various challenges still remain associated with the production of short DNA and RNA-oligomers in very large quantities. On the other hand, solution phase synthesis of oligonucleotides offers a more predictable scaling-up of the synthesis and is amenable to standard industrial manufacture techniques. In the present thesis, various protocols for the synthesis of short DNA and RNA oligomers have been studied on a peracetylated and methylated β-cyclodextrin, and also on a pentaerythritol-derived support. On using the peracetylated and methylated β-cyclodextrin soluble supports, the coupling cycle was simplified by replacement of the typical 5′-O-(4,4′-dimethoxytrityl) protecting group with an acid-labile acetal-protected 5′-O-(1-methoxy-1-methylethyl) group, which upon acid-catalyzed methanolysis released easily removable volatile products. For this reason monomeric building blocks 5′-O-(1-methoxy-1-methylethyl) 3′-(2-cyano-ethyl-N,N-diisopropylphosphoramidite) were synthesized. Alternatively, on using the precipitative pentaerythritol support, novel 2´-O-(2-cyanoethyl)-5´-O-(1-methoxy-1-methylethyl) protected phosphoramidite building blocks for RNA synthesis have been prepared and their applicability by the synthesis of a pentamer was demonstrated. Similarly, a method for the preparation of short RNAs from commercially available 5´-O-(4,4´-dimethoxytrityl)-2´-O-(tert-butyldimethyl-silyl)ribonucleoside 3´-(2-cyanoethyl-N,N-diisopropylphosphoramidite) building blocks has been developed