Experimenting through the web a linear variable differential transformer

Aiming for teaching/learning support in sciences and engineering areas, the Remote Experimentation concept (an E-learning subset) has grown in last years with the development of several infrastructures that enable doing practical experiments from anywhere and anytime, using a simple PC connected to the Internet. Nevertheless, given its valuable contribution to the teaching/learning process, the development of more infrastructures should continue, in order to make available more solutions able to improve courseware contents and motivate students for learning. The work presented in this paper contributes for that purpose, in the specific area of industrial automation. After a brief introduction to the Remote Experimentation concept, we describe a remote accessible lab infrastructure that enables users to conduct real experiments with an important and widely used transducer in industrial automation, named Linear Variable Differential Transformer.

Linear algebra: selected problems

Linear Algebra���Selected Problems is a unique book for senior undergraduate and graduate students to fast review basic materials in Linear Algebra. Vector spaces are presented first, and linear transformations are reviewed secondly. Matrices and Linear systems are presented. Determinants and Basic geometry are presented in the last two chapters. The solutions for proposed excises are listed for readers to references.

Numerical solution of a PDE system with non-linear steady state conditions that translates the air stripping pollutants removal

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Conditional probability applied to the definition of limestone geochemical facies: A new Methodological Approach

A new method, based on linear correlation and phase diagrams was successfully developed for processes like the sedimentary process, where the deposition phase can have different time duration - represented by repeated values in a series - and where the erosion can play an important rule deleting values of a series. The sampling process itself can be the cause of repeated values - large strata twice sampled - or deleted values: tiny strata fitted between two consecutive samples. What we developed was a mathematical procedure which, based upon the depth chemical composition evolution, allows the establishment of frontiers as well as the periodicity of different sedimentary environments. The basic tool isn't more than a linear correlation analysis which allow us to detect the existence of eventual evolution rules, connected with cyclical phenomena within time series (considering the space assimilated to time), with the final objective of prevision. A very interesting discovery was the phenomenon of repeated sliding windows that represent quasi-cycles of a series of quasi-periods. An accurate forecast can be obtained if we are inside a quasi-cycle (it is possible to predict the other elements of the cycle with the probability related with the number of repeated and deleted points). We deal with an innovator methodology, reason why it's efficiency is being tested in some case studies, with remarkable results that shows it's efficacy. Keywords: sedimentary environments, sequence stratigraphy, data analysis, time-series, conditional probability.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Le��a river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Le��a River.

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.

A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions

The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.

An integer programming model for the minimum interval graph completion problem

The minimum interval graph completion problem consists of, given a graph G = ( V, E ), ���nding a supergraph H = ( V, E ��� F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.

Aplica����o de um modelo de programa����o linear inteira mista (PLIM) na expans��o da rede de distribui����o de energia el��trica em Angola

Em Angola, apenas cerca de 30% da popula����o tem acesso �� energia el��trica, n��vel que decresce para valores inferiores a 10% em zonas rurais mais remotas. Este problema �� agravado pelo facto de, na maioria dos casos, as infraestruturas existentes se encontrarem danificadas ou n��o acompanharem o desenvolvimento da regi��o. Em particular na capital angolana, Luanda que, sendo a menor prov��ncia de Angola, �� a que regista atualmente a maior densidade populacional. Com uma popula����o de cerca de 5 milh��es de habitantes, n��o s�� h�� frequentemente problemas relacionados com a falha do fornecimento de energia el��trica como h�� ainda uma percentagem consider��vel de munic��pios onde a rede el��trica ainda nem sequer chegou. O governo de Angola, no seu esfor��o de crescimento e aproveitamento das suas enormes potencialidades, definiu o setor energ��tico como um dos fatores cr��ticos para o desenvolvimento sustent��vel do pa��s, tendo assumido que este �� um dos eixos priorit��rios at�� 2016. Existem objetivos claros quanto �� reabilita����o e expans��o das infraestruturas do setor el��trico, aumentando a capacidade instalada do pa��s e criando uma rede nacional adequada, com o intuito n��o s�� de melhorar a qualidade e fiabilidade da rede j�� existente como de a aumentar. Este trabalho de disserta����o consistiu no levantamento de dados reais relativamente �� rede de distribui����o de energia el��trica de Luanda, na an��lise e planeamento do que �� mais premente fazer relativamente �� sua expans��o, na escolha dos locais onde �� vi��vel localizar novas subesta����es, na modela����o adequada do problema real e na proposta de uma solu����o ��tima para a expans��o da rede existente. Depois de analisados diferentes modelos matem��ticos aplicados ao problema de expans��o de redes de distribui����o de energia el��trica encontrados na literatura, optou-se por um modelo de programa����o linear inteira mista (PLIM) que se mostrou adequado. Desenvolvido o modelo do problema, o mesmo foi resolvido por recurso a software de otimiza����o Analytic Solver e CPLEX. Como forma de valida����o dos resultados obtidos, foi implementada a solu����o de rede no simulador PowerWorld 8.0 OPF, software este que permite a simula����o da opera����o do sistema de tr��nsito de pot��ncias.

Dimens��o do sector p��blico e crescimento econ��mico: uma rela����o n��o linear na Uni��o Europeia dos 15?

Os Estados-Membros da Uni��o Europeia t��m tido a preocupa����o de reduzirem a dimens��o da Administra����o P��blica na economia, a par de a tornar muito mais eficiente de forma a promover o crescimento econ��mico. Neste artigo analisam-se as rela����es entre a despesa p��blica e o crescimento econ��mico em 14 Estados-Membros da Uni��o Europeia dos 15, com o objectivo de determinar a dimens��o ��ptima das Administra����es P��blicas, tendo por base te��rica a Curva de Armey. Os resultados, para o per��odo 1965-2007, sugerem uma dimens��o do sector p��blico maximizadora do crescimento econ��mico de 47,37% e 22,17% do PIB, quando avaliada pelas despesas p��blicas totais e o consumo p��blico, respectivamente.

Distributed Linear Precoding and User Selection in Coordinated Multicell Systems

In this manuscript we tackle the problem of semidistributed user selection with distributed linear precoding for sum rate maximization in multiuser multicell systems. A set of adjacent base stations (BS) form a cluster in order to perform coordinated transmission to cell-edge users, and coordination is carried out through a central processing unit (CU). However, the message exchange between BSs and the CU is limited to scheduling control signaling and no user data or channel state information (CSI) exchange is allowed. In the considered multicell coordinated approach, each BS has its own set of cell-edge users and transmits only to one intended user while interference to non-intended users at other BSs is suppressed by signal steering (precoding). We use two distributed linear precoding schemes, Distributed Zero Forcing (DZF) and Distributed Virtual Signalto-Interference-plus-Noise Ratio (DVSINR). Considering multiple users per cell and the backhaul limitations, the BSs rely on local CSI to solve the user selection problem. First we investigate how the signal-to-noise-ratio (SNR) regime and the number of antennas at the BSs impact the effective channel gain (the magnitude of the channels after precoding) and its relationship with multiuser diversity. Considering that user selection must be based on the type of implemented precoding, we develop metrics of compatibility (estimations of the effective channel gains) that can be computed from local CSI at each BS and reported to the CU for scheduling decisions. Based on such metrics, we design user selection algorithms that can find a set of users that potentially maximizes the sum rate. Numerical results show the effectiveness of the proposed metrics and algorithms for different configurations of users and antennas at the base stations.

Integer/fractional decomposition of the impulse response of fractional linear systems

The decomposition of a fractional linear system is discussed in this paper. It is shown that it can be decomposed into an integer order part, corresponding to possible existing poles, and a fractional part. The first and second parts are responsible for the short and long memory behaviors of the system, respectively, known as characteristic of fractional systems.

An Extension of Estimation of Domain of Attraction for Fractional Order Linear System Subject to Saturation Control

This paper employs the Lyapunov direct method for the stability analysis of fractional order linear systems subject to input saturation. A new stability condition based on saturation function is adopted for estimating the domain of attraction via ellipsoid approach. To further improve this estimation, the auxiliary feedback is also supported by the concept of stability region. The advantages of the proposed method are twofold: (1) it is straightforward to handle the problem both in analysis and design because of using Lyapunov method, (2) the estimation leads to less conservative results. A numerical example illustrates the feasibility of the proposed method.

On the analysis of data emerging in non-linear and complex systemscomparison of two X-Ray prony spectra

New arguments proving that successive (repeated) measurements have a memory and actually remember each other are presented. The recognition of this peculiarity can change essentially the existing paradigm associated with conventional observation in behavior of different complex systems and lead towards the application of an intermediate model (IM). This IM can provide a very accurate fit of the measured data in terms of the Prony's decomposition. This decomposition, in turn, contains a small set of the fitting parameters relatively to the number of initial data points and allows comparing the measured data in cases where the ���best fit��� model based on some specific physical principles is absent. As an example, we consider two X-ray diffractometers (defined in paper as A- (���cheap���) and B- (���expensive���) that are used after their proper calibration for the measuring of the same substance (corundum a-Al2O3). The amplitude-frequency response (AFR) obtained in the frame of the Prony's decomposition can be used for comparison of the spectra recorded from (A) and (B) - X-ray diffractometers (XRDs) for calibration and other practical purposes. We prove also that the Fourier decomposition can be adapted to ���ideal��� experiment without memory while the Prony's decomposition corresponds to real measurement and can be fitted in the frame of the IM in this case. New statistical parameters describing the properties of experimental equipment (irrespective to their internal ���filling���) are found. The suggested approach is rather general and can be used for calibration and comparison of different complex dynamical systems in practical purposes.