3 resultados para Spatial Database Systems
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
In this work the landscape morphodynamics was used to check the strength and importance of the changes carried out by man on the environment over time, in Natal-RN municipality. The occupation of partially preserved natural areas was analyzed, but environmentally fragile, such as riparian forests, vegetation on the banks of waterways, which play regulatory role of the water flow, and the dunes, which guarantee the rapid recharge of aquifers. The impacts of urban sprawl in Natal Southern and West zones Were identified and characterized, through a detailed mapping in the period between 1969 and 2013 the main Permanent Preservation Areas - PPA (banks of rivers and lagoons, and dunes remaining) and their temporal changes. For this were used aerial photographs and satellite imagery, altimetry data, and pre-existing information, which allowed the creation of a spatial database, and evolution of maps of impervious areas, evolution of the use and occupation and Digital Terrain Model (DTM) from contour lines with contour interval of 1 meter. Based on this study presents a diagnosis of the environmental situation and the state of conservation of natural areas, over the last 44 years, compared to human pressures. In general, it was found that the urban settlement has advanced about 60% of studied natural areas. This advance was growing by the year 2006, when there was a slowdown in the process, except for the Environmental Protection Zone (EPZ) 03, where the river Pitimbú and your PPA, which experienced a more significant loss area. The urban occupation affected the natural drainage and contributed to the contamination of groundwater Natal, due to increased sealed area, the release of liquid and solid waste, as well as the removal of riparian vegetation. Changed irreversibly the natural landscape, and reduced the quality and quantity of water resources necessary for the population. Thus, it is necessary to stimulate the adoption of use and protection of PPA planning measures, to the preservation of the San Valley Region inserted into the EPZ 01, and integrate more remaining dunes, in good condition, this EPZ, due to the importance of those remaining on the environment and the maintenance of quality of life. It is suggested, also, protection of catchment areas, such as PPA ponds and Pitimbú River. Finally, it is expected that this study can assist the managers in making decisions in urban and environmental planning of the municipality
Resumo:
Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
Resumo:
This study aimed to evaluate the influence of the main meteorological mechanisms trainers and inhibitors of precipitation, and the interactions between different scales of operation, the spatial and temporal variability of the annual cycle of precipitation in the Rio Grande do Norte. Além disso, considerando as circunstâncias locais e regionais, criando assim uma base científica para apoiar ações futuras na gestão da demanda de água no Estado. Database from monthly precipitation of 45 years, ranging between 1963 and 2007, data provided by EMPARN. The methodology used to achieve the results was initially composed of descriptive statistical analysis of historical data to prove the stability of the series, were applied after, geostatistics tool for plotting maps of the variables, within the geostatistical we opted for by Kriging interpolation method because it was the method that showed the best results and minor errors. Among the results, we highlight the annual cycle of rainfall the State which is influenced by meteorological mechanisms of different spatial and temporal scales, where the main mechanisms cycle modulators are the Conference Intertropical Zone (ITCZ) acting since midFebruary to mid May throughout the state, waves Leste (OL), Lines of instability (LI), breeze systems and orographic rainfall acting mainly in the Coastal strip between February and July. Along with vortice of high levels (VCANs), Complex Mesoscale Convective (CCMs) and orographic rain in any region of the state mainly in spring and summer. In terms of larger scale phenomena stood out El Niño and La Niña, ENSO in the tropical Pacific basin. In La Niña episodes usually occur normal or rainy years, as upon the occurrence of prolonged periods of drought are influenced by EL NIÑO. In the Atlantic Ocean the standard Dipole also affects the intensity of the rainfall cycle in State. The cycle of rains in Rio Grande do Norte is divided into two periods, one comprising the regions West, Central and the Western Portion of the Wasteland Potiguar mesoregions of west Chapada Borborema, causing rains from midFebruary to mid-May and a second period of cycle, between February-July, where rains occur in mesoregions East and of the Wasteland, located upwind of the Chapada Borborema, both interspersed with dry periods without occurrence of significant rainfall and transition periods of rainy - dry and dry-rainy where isolated rainfall occur. Approximately 82% of the rainfall stations of the state which corresponds to 83.4% of the total area of Rio Grande do Norte, do not record annual volumes above 900 mm. Because the water supply of the State be maintained by small reservoirs already are in an advanced state of eutrophication, when the rains occur, act to wash and replace the water in the reservoirs, improving the quality of these, reducing the eutrophication process. When rain they do not significantly occur or after long periods of shortages, the process of eutrophication and deterioration of water in dams increased significantly. Through knowledge of the behavior of the annual cycle of rainfall can have an intimate knowledge of how it may be the tendency of rainy or prone to shortages following period, mainly observing the trends of larger scale phenomena