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Marinho L.B.,Instituto Federal do Ceara | de Souza Junior A.H.,Instituto Federal do Ceara | Filho P.P.R.,Instituto Federal do Ceara
Advances in Intelligent Systems and Computing | Year: 2017

Recognition of human activities aims a wide diversity of applications. However, identifying complicated activities continues a challenging and active research area. In this work, we assess a new approach of feature selection for human activity recognition. For the task, we also compare state-of-the-art classifiers, e.g., Bayes classifier, kNN, MLP, SVM, MLM and MLM-NN. Based on the experiments, the MLM-NN is able to speed up the original MLM while holding equivalent accuracy. MLM and SVM achieved accuracy of more than 99.2% in the original data set and 98.1% using new feature selection method. Results show that the proposed feature selection approach is a promising alternative to activity recognition on smartphones. © Springer International Publishing AG 2017.

Coelho M.E.H.,Instituto Federal do Ceara | Freitas F.C.L.,Federal Rural University of the Semiarid Region | Cunha J.L.X.L.,Federal University of Alagoas | Silva K.S.,Doutoranda em Fitotecnia | And 2 more authors.
Planta Daninha | Year: 2013

To evaluate the effect of the no-tillage and conventional systems, weed management strategies on soil temperature variation, and yield of sweet pepper, a field experiment was arranged in a randomized block split-plot design with four replications. Tillage systems (no-tillage and conventional) were evaluated in the plots, and three weed management strategies in the split-plots (soil cover with black polyethylene film, with weeding, and without weeding). At 60 and 147 days after transplanting (DAT), density and dry mass of the weeds were assessed in the treatments without weeding. In each split-plot, thermocouple type sensors were installed at 5 cm depth to measure soil temperature. Based on the data obtained, temperature variation along the day was determined from 20 to 30 days after planting the sweet pepper seedlings, while the mean maximum and minimum temperatures and temperature range were evaluated every five days. The treatments with polyethylene film and clean weeding under the conventional tillage system showed an increase in maximum daily soil temperature at 6.7 and 5.0 oC, respectively, compared to no-tillage and weeding. The temperature range was 11 oC in the treatments using polyethylene film and clean weeding under the conventional system, 6.3 oC under no-tillage with weeding, 4.5 oC in the treatments without weeding, and 4.0 oC under no-tillage with polyethylene film. The no-tillage system proved to be a good technique for the cultivation of sweet peppers under high temperature conditions. Weed interference in the treatments without weeding resulted in a reduction of 94.95% and 92.10% of marketable yield under no-tillage and conventional systems, respectively.

Couprie M.,University Paris Est Creteil | Bezerra N.,Instituto Federal Do Ceara | Bertrand G.,University Paris Est Creteil
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Grayscale skeletonization offers an interesting alternative to traditional skeletonization following a binarization. It is well known that parallel algorithms for skeletonization outperform sequential ones in terms of quality of results, yet no general and well defined framework has been proposed until now for parallel grayscale thinning. We introduce in this paper a parallel thinning algorithm for grayscale images, and prove its topological soundness based on properties of the critical kernels framework. The algorithm and its proof, given here in the 2D case, are also valid in 3D. Some applications are sketched in conclusion. © 2013 Springer-Verlag Berlin Heidelberg.

Valente I.R.S.,Instituto Federal do Ceara | Valente I.R.S.,Federal University of Ceará | Cortez P.C.,Federal University of Ceará | Neto E.C.,Federal University of Ceará | And 3 more authors.
Computer Methods and Programs in Biomedicine | Year: 2016

This work presents a systematic review of techniques for the 3D automatic detection of pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze the latest technology being used for the development of computational diagnostic tools to assist in the acquisition, storage and, mainly, processing and analysis of the biomedical data. Also, this work identifies the progress made, so far, evaluates the challenges to be overcome and provides an analysis of future prospects. As far as the authors know, this is the first time that a review is devoted exclusively to automated 3D techniques for the detection of pulmonary nodules from lung CT images, which makes this work of noteworthy value. The research covered the published works in the Web of Science, PubMed, Science Direct and IEEEXplore up to December 2014. Each work found that referred to automated 3D segmentation of the lungs was individually analyzed to identify its objective, methodology and results. Based on the analysis of the selected works, several studies were seen to be useful for the construction of medical diagnostic aid tools. However, there are certain aspects that still require attention such as increasing algorithm sensitivity, reducing the number of false positives, improving and optimizing the algorithm detection of different kinds of nodules with different sizes and shapes and, finally, the ability to integrate with the Electronic Medical Record Systems and Picture Archiving and Communication Systems. Based on this analysis, we can say that further research is needed to develop current techniques and that new algorithms are needed to overcome the identified drawbacks. © 2015 Elsevier Ireland Ltd.

dos Santos J.C.N.,Engineering Agricola CCA UFC | de Andrade E.M.,Federal University of Ceará | de Araujo Neto J.R.,Instituto Federal do Ceara | Meireles A.C.M.,Federal University of Ceará | de Queiroz Palacio H.A.,Instituto Federal do Ceara
Revista Ciencia Agronomica | Year: 2014

Water body eutrophication process has been a serious problem around the world, especially in semiarid and arid region where main approach to storage water is reservoir. The aim of this work was to investigate the spatial and seasonal variability in water quality of a reservoir in a semi-arid tropical region with regards to its trophic state, and to identify the sources of nutrient input to the reservoir. Essa pesquisa foi realizada no reservatório Orós, segundo maior do estado do Ceará-Brasil. This research was developed in the Orós reservoir, the second one most important reservoir in Ceará State, Brazil. Samples were collected bimonthly during the period April 2008 to April 2010, from sex sampling points representing the outlet of tributaries, and one point down of the dam. The study included the following variables: total phosphorus, transparency and chlorophyll-a. Trophic state was evaluated by application of the Carlson modified Trophic State Index (TSI). Maps of the spatial and seasonal dynamics of the water quality in the reservoir were constructed using GIS soft. According to the average values of total phosphorus (> 0.050 mg L-1), the waters can be classified as eutrophic. The highest concentrations of chlorophyll-a were found during the dry season, with values ranging from 3.8 to 26.5 μg L-1, showing high temporal and spatial variations. The waters presented as eutrophic regarding average TSI, at all points sampled. The results indicate a deterioration in water quality and the need for intervention to reduce the release of waste, and thus improve the trophic state of the waters of the Orós reservoir.

Rodrigues J.O.,Federal University of Ceará | De Andrade E.M.,Federal University of Ceará | Palacio H.A.Q.,Instituto Federal do Ceara | Mendonca L.A.R.,Federal University of Ceará | Dos Santos J.C.N.,Federal University of Ceará
Revista Ciencia Agronomica | Year: 2013

The aim of this study was to evaluate and compare the sedimentological behavior in two small rural watersheds in the semiarid Northeast of Brazil, examining the influence of human activity on the sediment yields. The studied area is sited in the Alto Jaguaribe basin, more precisely in the Iguatu County, Ceará State. The experimental area was composed of two small watersheds denominated B1 and B2. In watershed B1 a treatment (thinning) was applied, eliminating the plant species with diameters lower than 10 cm. The results showed that the Caatinga clearing practice did have an influence in changing the sediment yield during the first events. It was also found that the magnitude of previous events contributed to an increase in the sediment yields by the subsequent events as a consequence of the sediment deposit in the drainage network. The accumulated sediment yields reached at the end of the 2009 rainfall season values of 1.45 and 1.39 tons ha-1 year-1 for B1 and B2, respectively, with no significant difference at 5%. It was concluded that, even when the effect of treatment on the sediment yields at the beginning of the rainy season is measured, the total sediment yields was not changed by the adoption of clearing. Therefore, it is a management system that can be employed in the land use at semiarid regions.

dos Santos J.C.N.,Federal University of Ceará | Palacio H.A.D.Q.,Instituto Federal do Ceara | de Andrade E.M.,Federal University of Ceará | Meireles A.C.M.,Federal University of Ceará | Neto J.R.D.A.,Federal University of Ceará
Revista Ciencia Agronomica | Year: 2011

Although water erosion is the principle agent responsible for soil degradation, field data on the impacts of erosion, due to high operational costs and measurement difficulties, are scarce, especially in semiarid regions. In this context, the aim of this study was to evaluate runoff and soil and nutrient losses in uncultivated areas in the semiarid region of the state of Ceará in Brazil. The experiment was conducted in a 20 m2 erosion plot that was uncultivated and populated with herbaceous plants. Data were collected during the rainy season from January to May 2009. Monthly water losses from overland flow ranged from 3.4 to 168.9 mm, representing 1.8 to 42.3% of the total monthly rainfall for January and April, respectively. Soil loss from erosion totaled 2,166.6 kg ha-1. In February, soil losses were 834.3 kg ha-1, corresponding to 38.5% of the total value. The rainfall erosivity index (EI30) was 5,716.4 MJ mm ha-1 h-1. The observed high variability of soil losses in individual events was influenced mainly by the antecedent soil water content. Although this study used only one year of observations, the findings are important for land use planning, especially in the semiarid region of Brazil, where datasets are scarce.

de Medeiros D.C.,UFERSA | de Medeiros J.F.,UFERSA | Pereira F.A.L.,UFERSA | de Souza R.O.,UFERSA | de Souza P.A.,Instituto Federal do Ceara
Revista Caatinga | Year: 2011

In recent years an increase of 15 to 20% occurred in market share melons like Cantaloupes group, which present more attractive organoleptic characteristics and higher commercial value. However it needs more care in production due its higher sensitivity to soil salinity. Effects of soil and water salinity are among the main limiting factors to melon yield and quality at Rio Grande do Norte Sate, Brazil. This work was carried out with the objective of studying the effect of different irrigation water salinity levels on yield and quality of cantaloupe hybrid 'Sedna'. Experimental design was a randomized complete blocks with four replications. Treatments consisted of five salt concentrations in irrigation water (0.54; 1.48; 2.02; 3.03 and 3.9 dS m -1). Yield and quality characteristics evaluated were: number of marketable fruits per plant, yield of marketable fruits, mean weight of fruits, soluble solids content (SS) and pulp firmness. An increase on irrigation water salinity level negatively influenced yield of melon hybrid 'Sedna'. Yield loss in response to salinity was due to decrease in number of fruits per plant. Mean values of soluble solids and pulp firmness were not influenced by irrigation water salinity.

The mangrove ecosystem performs several natural functions of great ecological and economic importance. This study provided procedures for the recovery of mangrove ecosystems through the characterization of vegetation and zonation patterns and evaluation of growth and survival rates of mangrove species in an experimental plantation. The study was performed in the Acaraú River estuary mangrove on the western coast of Ceará State. The characterization of vegetation was conducted with the use of multiple plots and transects replication. Plants were identified at the species level, and their heights and CBH (circumference at breast height) were measured in each plot. Seedlings of the dominant mangrove species were produced using estuarine propagules. Five mangrove species were sampled: Rhizophora mangle, Avicennia germinans, Avicennia schaueriana, Laguncularia racemosa, and Conocarpus erectus. L. racemosa was the most dominant and frequent species, followed by A. germinas. A total of 111 L. racemosa and 102 Avicennia sp seedlings of were produced. Seedlings were viable for replanting within two months. The results of the analysis of vegetation structure and production and growth of seedlings are encouraging and demonstrate that revegetation is not only possible but also successful in this significantly deforested and degraded mangrove. © 2016, Sociedade de Investigacoes Florestais. All rights reserved.

Silva D.A.,Instituto Federal Do Ceara | Rocha Neto A.R.,Instituto Federal Do Ceara
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

This paper introduces a new approach to building sparse least square support vector machines (LSSVM) based on multi-objective genetic algorithms (GAs) for classification tasks. LSSVM classifiers are an alternative to SVM ones due to the training process of LSSVM classifiers only requires to solve a linear equation system instead of a quadratic programming optimization problem. However, the lost of sparseness in the Lagrange multipliers vector (i.e. the solution) is a significant drawback which comes out with theses classifiers. In order to overcome this lack of sparseness, we propose a multi-objective GA approach to leave a few support vectors out of the solution without affecting the classifier's accuracy and even improving it. The main idea is to leave out outliers, non-relevant patterns or those ones which can be corrupted with noise and thus prevent classifiers to achieve higher accuracies along with a reduced set of support vectors. We point out that the resulting sparse LSSVM classifiers achieve equivalent (in some cases, superior) performances than standard full-set LSSVM classifiers over real data sets. Differently from previous works, genetic algorithms are used in this work to obtain sparseness not to find out the optimal values of the LSSVM hyper-parameters. © 2014 Springer International Publishing Switzerland.

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