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Mineração multi-relacional: o algoritmo GFP-growth
(Universidade Federal de São Carlos, 2006-05-25) Pizzi, Luciene Cristina; Vieira, Marina Teresa Pires; https://lattes.cnpq.br/5446518523049572
Data mining is the phase of the knowledge discovery in database process where an algorithm is applied to the available data, in order to prove a hypothesis or discover a still unknown pattern. The traditional data mining techniques can deal only with single tables; however it is interesting to look for patterns involving several related tables, aiming to analyze the existing relation between the entities present in one table and the data of the same entities present in another table. Depending on the relationship existing between these tables, applying a traditional algorithm to the joint table is not sufficient, as the joint table may contain duplicated attribute values which interfere in the analysis process of the generated rules. In order to solve this problem, this project adopts an approach which consists on looking for association rules mining the joint table. The adopted process considers the groups of tuples, where each group is formed by tuples of the same entity. Following this approach the GFP-Growth algorithm was developed, which is presented in this monograph along with its results and comparisons with other multi-relational algorithms.
Respostas ao estresse osmótico e hipóxico em traíra, Hoplias malabaricus (Teleostei, Erythrinedae) aspectos fisiológicos e adaptativos
(Universidade Federal de São Carlos, 2006-05-25) Sakuragui, Marise Margareth; Fernandes, Marisa Narciso; https://lattes.cnpq.br/3021357484136942; https://lattes.cnpq.br/9839007287526459
The stress level, via change in the plasma concentration of cortisol and the physiological and metabolic responses caused by osmotic shock and hypoxia and the effect of cortisol injection on theses responses, were studied in traíra, Hoplias malabaricus, injected and non-injected with cortisol exogenous (IC) and maintained in water similar to it natural environment (C- control) and in deionized water (AD) in normoxia (PO2 = 140 mmHg) and severe hypoxia (H, PO2 = 25-30 mmHg) during 48h. Animals injected with soy oil consisted the sham-operated group (TEST). Blood variables, pH, hematocrit (Hct) and hemoglobin concentration (Hb), osmolality, Na+, K+, and Cl- ion concentration, cortisol, glucose, lactate, ammonium and protein concentration were determined following 6, 12, 24, 36 and 48h in each experimental condition, after blood sample obtained via implanted catheter in the ventral vein. Twenty four and forty eight hours after the beginning of experiments, the gills of 5 animals from each group were removed for determination of Na+/K+-ATPase activity and chloride cell (CC) density using immunohistochemistry against Na+/K+-ATPase enzyme. Osmotic shock resulted in slow increasing of cortisol level in normoxia until 24h in group AD and fast increasing (6h) in fish exposed to hypoxia evidencing that the activation of hypothalamus hypophysis -interrenal axis depends on stressor agent. Cortisol injection (IC) in normoxia induced plasma glucose increasing in all experimental groups, with exception of AD group compared with controls that showed a tendency to increase only after 36-48h. During hypoxia, glucose increased in the DH+IC group only on the first 24h. Hydromineral unbalance, in normoxia, was observed with the increase of [Na+] and [K+] in all experimental groups and a decreasing of plasma [Cl-] only in the AD group in 6 and 24h, returning to values of control group after 36h, meanwhile, in hypoxia, the osmolality, [Cl-] and [Na+] decreased on the first 12, 6 and 12h, respectively, in non-injected groups. Transitory [K+] disturbance was observed in ADH (6h) and CH+IC (24 and 48h) groups. Changes in plasma glucose and lactate were observed in all injected groups in normoxia and hypoxia (with exception lactate concentration in CH+IC group), which evidences a possible effect of cortisol on these responses. In normoxia, the increasing of lactate, glucose and Na+ concentration in the injected groups may be related to exogenous cortisol and/or cholinergic activation instead of HHI activation axis. The changes of plasma glucose, lactate, pyruvate, ammonium and proteins suggested an increase of energy demand to homeostasis maintenance as a consequence of changes in cortisol. The significant increasing of pH may be due to metabolic alkalosis caused by a decreasing in plasma K+ and Cl- ions, which may stimulate the secretion of H+ ions to renal tubules in AD group in normoxia, while the increasing of pH in hypoxia may be explained by carbonic anhydrase activity in the erythrocytes with H+ production that combined with Hb+ or was changed with bicarbonate (HCO3 -/Cl-) in ADH. The reduction of pH, in hypoxia, in the ADH+IC group may be due to increase of lactate produced by cellular metabolism (acid metabolic). Hct showed a tendency to decrease, in normoxia, on the first 6h in C, TEST and AD groups and 12h in C+IC group, and to increase in the AD+IC group in 6 and 24h. In hypoxia, the Hct decreased on the first 6h in ADH+IC group and 12h in the CH, ADH e CH+ IC groups. Hb concentration did not change either in normoxia or hypoxia. Two chloride cell populations were identified in the gill filaments and lamellae of H. malabaricus; light-CC and dark-CC are restricted in the filaments an rarely in the lamellae. After osmotic and hypoxic stresses there were a density increase of CC of both types in the filament and lamella. Dark-CC density (mature and/or active) increased with the increase of cortisol levels and, consequently, the Na+/K+-ATPase activity followed these increasing in CC. The results of present study evidenced that the cortisol increasing above it basal level in H. malabaricus affect in the ionic equilibrium and energetic metabolism in fish kept in environment similar to it natural habitat. However, the effects of stress on the ionic equilibrium and metabolism may be reduced if cortisol level is above of the basal level of this species.
Projeto de um ambiente 3D de visualização e reprodução de eventos capturados e interpretados a partir de ambientes físicos cientes de contexto para aplicações de preparação para emergência
(Universidade Federal de São Carlos, 2006-05-25) Lopes, Altieres Ribeiro; Araujo, Regina Borges de; https://lattes.cnpq.br/8964123297688432; https://lattes.cnpq.br/6735711209617838
Systems for emergency preparedness support, especially those for accurate monitoring of physical environments subjected to emergency situations, are valuable resources for companies and civil defense public institutions, since these systems can help avoiding and/or reducing lives and patrimony losses. Most of the existing monitoring systems described in the literature have limitations, such as: no posterior visualization of emergency situations that have occurred; limited to specific types of applications; inaccurate identification of risk situations; etc. In this work, a system was proposed and evaluated that aims to overcome these limitations through the integrated use of wireless actor and sensor networks, context aware computing and virtual reality. The work consisted on the creation, implementation and evaluation of a recording and playing 3D media in which physical environments subjected to emergency situations are deployed sensors with processing and communication resources. These sensors capture and interpret contexts, which are mapped, through a visual language, on a 3D virtual environment that mimics the physical environment. The use of virtual reality for visualization and access in real-time2 or afterwards of situations that are occurring in the physical environment, through a 3D Virtual Environment, can overcome the limitations of hypermedia interfaces or continuous media, like video, when the experiences of the real world are very complex. This work describes the project of a recording and playing system, which allows users to play live experiences gathered from the real world for analysis, evaluation, monitoring and training. The novelty of the system resides in two aspects: it uses an optimized recording technique that saves processing time and storage space; it records scene updating commands independent from 3D Players, allowing the visualization of the collaborative virtual environment (CVE) through any existing 3D web players. In collaboration with the Arts and Communication Department (DAC) of UFSCar, a visual language to prompt identification of emergency situations was created as well as an interface to complex systems. Examples of use include the monitoring of industrial plants, flight rehearsals, petrol exploration platforms, etc. This work is part of a collaborative Project between the Networked Virtual Reality Lab (LRVNet) of the Computer Science Department at UFSCar and PARADISE Lab of SITE at University of Ottawa.
Aprendizado supervisionado usando redes neurais construtivas
(Universidade Federal de São Carlos, 2006-05-25) Bertini Junior, João Roberto; Nicoletti, Maria do Carmo; https://lattes.cnpq.br/6454154048263145
Constructive neural learning is a neural learning model that does not assume a fixed network topology before training begins. The main characteristic of this learning model is the dynamic construction of the network s hidden layers that occurs simultaneously with training. This work investigates three topics related to constructive neural learning namely algorithms for training an individual TLU, constructive neural algorithms for two class problems and constructive neural algorithms for multiclass problems. The first research topic is approached by discussing a few TLU training algorithms, namely Perceptron, Pocket, Thermal, Modified Thermal, MinOver and BCP. This work approaches constructive neural learning for two class classification tasks by initially reviewing Tower, Pyramid, Tiling and Upstart algorithms, aiming at their multiclass versions. Next five constructive neural algorithms namely Shift, Offset, PTI, Perceptron Cascade and Sequential are investigated and two hybrid algorithms are proposed: Hybrid Tiling, that does not restrict the TLU s training to only one algorithm and the OffTiling, a collaborative approach based on Tiling and Offset. Multiclass constructive neural learning was approached by investigating TLUs training algorithms that deal with multiclass as well as by investigating multiclass versions of Tower, Pyramid, Tiling, Upstart and Perceptron Cascade. This research work also describes an empirical evaluation of all the investigated algorithms conducted using several knowledge domains. Results are discussed and analyzed.
Caracterização e germinação de sementes de Aegiphyla sellowiana Cham
(Universidade Federal de São Carlos, 2006-05-25) Biruel, Rosangela Peres; Perez, Sonia Cristina Juliano Gualtieri de Andrade; https://lattes.cnpq.br/9973185407856723; https://lattes.cnpq.br/5566884806328331