925 resultados para Artificial Intelligence and Robotics
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This paper presents the overall methodology that has been used to encode both the Brazilian Portuguese WordNet (WordNet.Br) standard language-independent conceptual-semantic relations (hyponymy, co-hyponymy, meronymy, cause, and entailment) and the so-called cross-lingual conceptual-semantic relations between different wordnets. Accordingly, after contextualizing the project and outlining the current lexical database structure and statistics, it describes the WordNet.Br editing GUI that was designed to aid the linguist in carrying out the tasks of building synsets, selecting sample sentences from corpora, writing synset concept glosses, and encoding both language-independent conceptual-semantic relations and cross-lingual conceptual-semantic relations between WordNet.Br and Princeton WordNet © Springer-Verlag Berlin Heidelberg 2006.
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One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.
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Purpose: This study aimed to evaluate the effect of different storage periods in artificial saliva and thermal cycling on Knoop hardness of 8 commercial brands of resin denture teeth. Methods: Eigth different brands of resin denture teeth were evaluated (Artplus group, Biolux group, Biotone IPN group, Myerson group, SR Orthosit group, Trilux group, Trubyte Biotone group, and Vipi Dent Plus group). Twenty-four teeth of each brand had their occlusal surfaces ground flat and were embedded in autopolymerized acrylic resin. After polishing, the teeth were submitted to different conditions: (1) immersion in distilled water at 37 ± 2 °C for 48 ± 2. h (control); (2) storage in artificial saliva at 37 ± 2 °C for 15, 30 and 60 days, and (3) thermal cycling between 5 and 55 °C with 30-s dwell times for 5000 cycles. Knoop hardness test was performed after each condition. Data were analyzed with two-way ANOVA and Tukey's test (α= .05). Results: In general, SR Orthosit group presented the highest statistically significant Knoop hardness value while Myerson group exhibited the smallest statistically significant mean (P< .05) in the control period, after thermal cycling, and after all storage periods. The Knoop hardness means obtained before thermal cycling procedure (20.34 ± 4.45 KHN) were statistically higher than those reached after thermal cycling (19.77 ± 4.13 KHN). All brands of resin denture teeth were significantly softened after storage period in artificial saliva. Conclusion: Storage in saliva and thermal cycling significantly reduced the Knoop hardness of the resin denture teeth. SR Orthosit denture teeth showed the highest Knoop hardness values regardless the condition tested. © 2010 Japan Prosthodontic Society.
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The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind of classifier can be important for many applications. In this paper we report a fast method to combine OPF-based classifiers trained with disjoint training subsets. Given a fixed number of subsets, the algorithm chooses random samples, without replacement, from the original training set. Each subset accuracy is improved by a learning procedure. The final decision is given by majority vote. Experiments with simulated and real data sets showed that the proposed combining method is more efficient and effective than naive approach provided some conditions. It was also showed that OPF training step runs faster for a series of small subsets than for the whole training set. The combining scheme was also designed to support parallel or distributed processing, speeding up the procedure even more. © 2011 Springer-Verlag.
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We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.
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This paper presents a domain ontology, the FeelingTheMusic Ontology - FTMOntology. FTMOntology is designed to represent the complex domain of music and how it relates to other domains like mood, personality and physiology. This includes representing the main concepts and relations of music domain with each of the above-mentioned domains. The concepts and relations between music, mood, personality and physiology. The main contribution of this work is to model and relate these different domains in a consistent ontology. © 2011 Springer-Verlag.
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The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.
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Bos indicus cattle, the preferred genetic group in tropical climates, are characterized by having a lower reproductive efficiency than Bos taurus. The reasons for the poorer reproductive efficiency of the Bos indicus cows include longer lengths of gestation and postpartum anestrus, a short length of estrous behavior with a high incidence of estrus occurring during the dark hours, and puberty at older age and at a higher percentage of body weight relative to mature body weight. Moreover, geography, environment, economics, and social traditions are factors contributing for a lower use of reproductive biotechnologies in tropical environments. Hormonal protocols have been developed to resolve some of the reproductive challenges of the Bos indicus cattle and allow artificial insemination, which is the main strategy to hasten genetic improvement in commercial beef ranches. Most of these treatments use exogenous sources of progesterone associated with strategies to improve the final maturation of the dominant follicle, such as temporary weaning and exogenous gonadotropins. These treatments have caused large impacts on reproductive performance of beef cattle reared under tropical areas. Copyright © 2011 O. G. Sá Filho and J. L. M. Vasconcelos.
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This paper presents vectorized methods of construction and descent of quadtrees that can be easily adapted to message passing parallel computing. A time complexity analysis for the present approach is also discussed. The proposed method of tree construction requires a hash table to index nodes of a linear quadtree in the breadth-first order. The hash is performed in two steps: an internal hash to index child nodes and an external hash to index nodes in the same level (depth). The quadtree descent is performed by considering each level as a vector segment of a linear quadtree, so that nodes of the same level can be processed concurrently. © 2012 Springer-Verlag.
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Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.
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The effects of artificial substrate and night-time aeration on the culture of Macrobrachium amazonicum were evaluated in 12 ponds stocked with 45 prawns m-2. A completely randomized design in 2 × 2 factorial scheme with three replicates was used. The combination of factors resulted in four treatments: with substrate and aeration (SA), with substrate and without aeration (SWA), without substrate and with aeration (WSA) and without substrate and aeration (WSWA). The presence of substrate in SA and SWA treatments reduced suspended particles (seston) by ~17.3% and P-orthophosphate by ~50%. The use of aerator (WSA and SA treatments) significantly (P < 0.05) increased the concentration of dissolved oxygen, suspended particles and nutrients in the pond water. These results indicate that the effect of substrate on turbidity and total suspended solids (TSS) values is opposite to the effect of the aerator. The aerators in semi-intensive grow-out M. amazonicum farming lower water quality because they increased the amount of detritus and nutrients in the pond water. On the other hand, the use of artificial substrate reduces turbidity values, chlorophyll a, TSS and P-orthophosphate concentrations. Therefore, the combination of substrate addition and night-time aeration is not interesting because they have opposite effects. © 2013 John Wiley & Sons Ltd.
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This paper presents a usability evaluation of the MTE (Ministry of Labor e Employment) website in order to measure the effectiveness, efficiency and user satisfaction regarding the website. The participants were 12 users (07 users were female and 05 male). The results indicate that although the education level of all participants and computing experience, many of them have had difficulty in finding information and do not recommend the site. © 2013 Springer-Verlag Berlin Heidelberg.
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Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Obtaining ecotoxicological data on pesticides in tropical regions is imperative for performing more realistic risk analysis, and avoidance tests have been proposed as a useful, fast and cost-effective tool. Therefore, the present study aimed to evaluate the avoidance behavior of Eisenia andrei to a formulated product, Vertimec(A (R)) 18 EC (a.i abamectin), in tests performed on a reference tropical artificial soil (TAS), to derive ecotoxicological data on tropical conditions, and a natural soil (NS), simulating crop field conditions. In TAS tests an adaptation of the substrate recommended by OECD and ISO protocols was used, with residues of coconut fiber as a source of organic matter. Concentrations of the pesticide on TAS test ranged from 0 to 7 mg abamectin/kg (dry weight-d.w.). In NS tests, earthworms were exposed to samples of soils sprayed in situ with: 0.9 L of Vertimec(A (R)) 18 EC/ha (RD); twice as much this dosage (2RD); and distilled water (Control), respectively, and to 2RD: control dilutions (12.5, 25, 50, 75%). All tests were performed under 25 +/- A 2A degrees C, to simulate tropical conditions, and a 12hL:12hD photoperiod. The organisms avoided contaminated TAS for an EC50,48h = 3.918 mg/kg soil d.w., LOEC = 1.75 mg/kg soil d.w. and NOEC = 0.85 mg/kg soil d.w. No significant avoidance response occurred for any NS test. Abamectin concentrations in NS were rather lower than EC50, 48h and LOEC determined in TAS tests. The results obtained contribute to overcome a lack of ecotoxicological data on pesticides under tropical conditions, but more tests with different soil invertebrates are needed to improve pesticides risk analysis.