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.

Multi-strand narrative structures: a filmic game of multiple players

Session 7: Playing with Roles, images and improvising New States of Awareness, 3rd Global Conference, 1st November – 3rd November, 2014, Prague, Czech Republic.

Multiple Roots of Systems of Equations by Repulsion Merit Functions

In this paper we address the problem of computing multiple roots of a system of nonlinear equations through the global optimization of an appropriate merit function. The search procedure for a global minimizer of the merit function is carried out by a metaheuristic, known as harmony search, which does not require any derivative information. The multiple roots of the system are sequentially determined along several iterations of a single run, where the merit function is accordingly modified by penalty terms that aim to create repulsion areas around previously computed minimizers. A repulsion algorithm based on a multiplicative kind penalty function is proposed. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Multiple sequence alignment correction using constraints

Trabalho apresentado no âmbito do European Master in Computational Logics, como requisito parcial para obtenção do grau de Mestre em Computational Logics

Possibilidade e rentabilidade da utilização do gás de xisto em Portugal

Mestrado em Engenharia Mecânica- Energia

Decay of antibody isotypes against early developmental stages of Schistosoma mansoni after treatment of schistosomiasis patients

Antibodies to a number of parasite antigens are found in schistosomiasis patients, and antibodies to early developmental stages were demonstrated to be efficient immunologic markers for the diagnosis of schistosomiasis. In the present study, decay patterns of IgM and IgG antibodies against cercariae and schistosomula were investigated, in comparison to antibodies against worms and eggs in schistosomiasis patients after chemotherapy, for an investigation of seroepidemiologic aspects. Data obtained in the study of 359 serum samples from patients with Schistosoma mansoni infection, noninfected individuals, and patients followed-up for a period of 12 to 15 months after treatment provided the basis to postulate a general pattern for the kinetics of antibody decay. Before treatment, the antibody pattern was represented by a unimodal curve, which shifted to a bimodal curve after treatment, and ended with a unimodal curve similar to that for the noninfected group. Different types of antibodies were classified into four categories according to their decay features, and anti-schistosomulum IgM was classified into the moderate-decay caterogy, whereas other antibodies to early parasite stages were classified into the slow-decay category. The present methodology permits the identification of the most suitable antibodies to be detected in field control programs for schistosomiasis or other parasitoses

Estimation of infection rate in epidemic models with multiple populations

Dissertação para obtenção do Grau de Mestre em Matemática e Aplicações Especialização em Actuariado, Estatística e Investigação Operacional

Confluent peripheral multiple mononeuropathy associated to acute hepatitis B: a case report

A thirty three year-old, male patient was admitted at the Hospital of the São Paulo University School of Medicine, at the city of São Paulo, Brazil, with complaint of pains, tingling and decreased sensibility in the right hand for the last four months. This had progressed to the left hand, left foot and right foot, in addition to a difficulty of flexing and stretching in the left foot. Tests were positive for HBeAg, IgM anti-HBc and HBsAg, thus characterizing the condition of acute hepatitis B. The ALT serum level was 15 times above the upper normal limit. Blood glucose, cerebral spinal fluid, antinuclear antibodies (ANA) and anti-HIV and anti-HCV serum tests were either normal or negative. Electroneuromyography disclosed severe peripheral neuropathy with an axon prevalence and signs of denervation; nerve biopsy disclosed intense vasculitis. The diagnosis of multiple confluent mononeuropathy associated to acute hepatitis B was done. This association is not often reported in international literature and its probable cause is the direct action of the hepatitis B virus on the nerves or a vasculitis of the vasa nervorum brought about by deposits of immune complexes.

Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

Coordinated Maneuver for Gradient Search Using Multiple AUV's

OCEANS 2003. Proceedings (Volume:1 )

Hybrid Maneuver for Gradient Search with Multiple Coordinated AUVs

This work presents a hybrid maneuver for gradient search with multiple AUV's. The mission consists in following a gradient field in order to locate the source of a hydrothermal vent or underwater freshwater source. The formation gradient search exploits the environment structuring by the phenomena to be studied. The ingredients for coordination are the payload data collected by each vehicle and their knowledge of the behaviour of other vehicles and detected formation distortions.

Response Time Analysis for Fixed-Priority Tasks with Multiple Probabilistic Parameters

Demo presented in 12th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015). 8 to 12, Jun, 2015. La Roche-en-Ardenne, Belgium. Extended abstract.

E-assessment in mathematics courses with multiple-choice questions tests

With the implementation of the Bologna Process several challenges have been posed to higher education institution, particularly in Portugal. One of the main implications is related to the change of the paradigm of a teacher centered education, to a paradigm that is student centered. This change implies the change of the way to assess courses in higher education institutions. Continuous and formative assessments emerged as the focus, catalyzed by electronic assessment, or e-assessment. This paper presents a case of the implementation of an e-assessment strategy, implemented in order to allow continuous, formative assessment in numerous mathematics classes using multiple-choice questions tests implement in Moodle open-source learning management system. The implementation can be considered a success.

E-assessment in mathematics courses with multiple-choice questions tests

With the implementation of the Bologna Process several challenges have been posed to higher education institution, particularly in Portugal. One of the main implications is related to the change of the paradigm of a teacher centered education, to a paradigm that is student centered. This change implies the change of the way to assess courses in higher education institutions. Continuous and formative assessments emerged as the focus, catalyzed by electronic assessment, or e-assessment. This paper presents a case of the implementation of an e-assessment strategy, implemented in order to allow continuous, formative assessment in numerous mathematics classes using multiple-choice questions tests implement in Moodle open-source learning management system. The implementation can be considered a success.