Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy

A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Social network analysis applied to knowledge creation and transfer in the portuguese agricultural R&D field: an exploratory study

Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

Railcarrier in Intermodal Freight Transportation Network

The major objective of this thesis is to describe and analyse how a railcarrier is engaged in an intermodal freight transportation network through its role and position. Because of the fact that the role as a conceptualisation has a lot of parallels with the position, both these phenomena are evaluated theoretically and empirically. VR Cargo (a strategical business unitof the Finnish railway company VR Ltd.) was chosen to be the focal firm surrounded by the actors of the focal net. Because of the fact that networks are sets of relationships rather than sets of actors, it is essential to describe the dimensions of the relationships created through the time thus having a past, presentand future. The roles are created during long common history shared by the actors especially when IM networks are considered. The presence of roles is embeddedin the tasks, and the future is anchored to the expectations. Furthermore, in this study role refers to network dynamics, and to incremental and radical changes in the network, in a similar way as position refers to stability and to the influences of bonded structures. The main purpose of the first part of the study was to examine how the two distinctive views that have a dominant position in modern logistics ¿ the network view (particularly IMP-based network approach) and the managerial view (represented by Supply Chain Management) differ, especially when intermodalism is under consideration. In this study intermodalism was defined as a form of interorganisational behaviour characterized by the physical movement of unitized goods with Intermodal Transport Units, using more than one mode as performed by the net of operators. In this particular stage the study relies mainly on theoretical evaluation broadened by some discussions with the practitioners. This is essential, because the continuous dialogue between theory and practice is highly emphasized. Some managerial implications are discussed on the basis of the theoretical examination. A tentative model for empirical analysis in subsequent research is suggested. The empirical investigation, which relies on the interviews among the members in the focal net, shows that the major role of the focal company in the network is the common carrier. This role has some behavioural and functional characteristics, such as an executive's disclosure expressing strategic will attached with stable and predictable managerial and organisational behaviour. Most important is the notion that the focal company is neutral for all the other operators, and willing to enhance and strengthen the collaboration with all the members in the IM network. This also means that all the accounts are aimed at being equal in terms of customer satisfaction. Besides, the adjustments intensify the adopted role. However, the focal company is also obliged tosustain its role as it still has a government-erected right to maintain solely the railway operations on domestic tracks. In addition, the roles of a dominator, principal, partner, subcontractor, and integrator were present appearing either in a dyadic relationship or in net(work) context. In order to reveal differentroles, a dualistic interpretation of the concept of role/position was employed.

Investigations On The Development Of An Ann Model & Visual Manipulation Approach For 2-D Dft Computation In Image Processing

This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

Arctic network builders : the Arctic Coal Company's operations on Spitsbergen and its relationship with the environment

In 1906, two American industrialists, John Munroe Longyear and Frederick Ayer, formed the Arctic Coal Company to make the first large scale attempt at mining in the high-Arctic location of Spitsbergen, north of the Norwegian mainland. In doing so, they encountered numerous obstacles and built an organization that attempted to overcome them. The Americans sold out in 1916 but others followed, eventually culminating in the transformation of a largely underdeveloped landscape into a mining region. This work uses John Law’s network approach of the Actor Network Theory (ANT) framework to explain how the Arctic Coal Company built a mining network in this environmentally difficult region and why they made the choices they did. It does so by identifying and analyzing the problems the company encountered and the strategies they used to overcome them by focusing on three major components of the operations; the company’s four land claims, its technical system and its main settlement, Longyear City. Extensive comparison between aspects of Longyear City and the company’s choices of technology with other American examples place analysis of the company in a wider context and helps isolate unique aspects of mining in the high-Arctic. American examples dominate comparative sections because Americans dominated the ownership and upper management of the company.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

An interaction and network perspective of horizontal relationships in the portuguese pharmaceutical industry

Doutoramento em Gestão

Characterization of DNA sequence properties through network and statistical approaches

In this thesis we will see that the DNA sequence is constantly shaped by the interactions with its environment at multiple levels, showing footprints of DNA methylation, of its 3D organization and, in the case of bacteria, of the interaction with the host organisms. In the first chapter, we will see that analyzing the distribution of distances between consecutive dinucleotides of the same type along the sequence, we can detect epigenetic and structural footprints. In particular, we will see that CG distance distribution allows to distinguish among organisms of different biological complexity, depending on how much CG sites are involved in DNA methylation. Moreover, we will see that CG and TA can be described by the same fitting function, suggesting a relationship between the two. We will also provide an interpretation of the observed trend, simulating a positioning process guided by the presence and absence of memory. In the end, we will focus on TA distance distribution, characterizing deviations from the trend predicted by the best fitting function, and identifying specific patterns that might be related to peculiar mechanical properties of the DNA and also to epigenetic and structural processes. In the second chapter, we will see how we can map the 3D structure of the DNA onto its sequence. In particular, we devised a network-based algorithm that produces a genome assembly starting from its 3D configuration, using as inputs Hi-C contact maps. Specifically, we will see how we can identify the different chromosomes and reconstruct their sequences by exploiting the spectral properties of the Laplacian operator of a network. In the third chapter, we will see a novel method for source clustering and source attribution, based on a network approach, that allows to identify host-bacteria interaction starting from the detection of Single-Nucleotide Polymorphisms along the sequence of bacterial genomes.

Multidisciplinary optimization of a catamaran's hydrofoil design with dynamic response surface and distributive processing

This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.

Occasion setting in Pavlovian ambiguous target discriminations

Rats were trained in a Pavlovian serial ambiguous target discrimination, in which a target cue was reinforced if it was preceded by one stimulus (P -> T+) but was not reinforced if it was preceded by another stimulus (N -> T-). Test performance indicated that stimulus control by these features was weaker than that acquired by features trained within separate serial feature positive (P -> T+, T-) and serial feature negative (N -> W-, W+) discriminations. The form of conditioned responding and the patterns of transfer observed suggested that the serial ambiguous target discrimination was solved by occasion setting. The data are discussed in terms of the use of retrospective coding strategies when solving Pavlovian serial conditional discriminations, and the acquisition of special properties by both feature and target stimuli. (C) 2008 Published by Elsevier B.V.

Bridge architecture to interconnect hybrid wired/wireless PROFIBUS networks

The integration of wired and wireless technologies in modern manufacturing plants is now of paramount importance for the competitiveness of any industry. Being PROFIBUS the most widely used technology in use for industrial communications, several solutions have been proposed to provide PROFIBUS networks with wireless communications. One of them, the bridge-based hybrid wired/wireless PROFIBUS network approach, proposes an architecture in which the Intermediate Systems operate at Data Link Layer level, as bridges. In this paper, we propose an architecture for the implementation of such a bridge and the required protocols to handle communication between stations in different domains and the mobility of wireless stations.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

The adolescent with a chronic condition. Part II: healthcare provision.

The treatment and management of chronic conditions during adolescence pose specific issues that need to be appropriately handled by health professionals. In this paper, questions related to disclosure of the diagnosis, the management of adherence to therapy, the need for an interdisciplinary network approach, lifestyles' anticipatory guidance and prevention, and the transition into an adult healthcare setting are reviewed. Special areas such as the issue of life threatening diseases and the ethical aspects of the treatment of chronic conditions are also discussed.