944 resultados para Extração semi-automática


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Given the exponential growth in the spread of the virus world wide web (Internet) and its increasing complexity, it is necessary to adopt more complex systems for the extraction of malware finger-prints (malware fingerprints - malicious software; is the name given to extracting unique information leading to identification of the virus, equivalent to humans, the fingerprint). The architecture and protocol proposed here aim to achieve more efficient fingerprints, using techniques that make a single fingerprint enough to compromise an entire group of viruses. This efficiency is given by the use of a hybrid approach of extracting fingerprints, taking into account the analysis of the code and the behavior of the sample, so called viruses. The main targets of this proposed system are Polymorphics and Metamorphics Malwares, given the difficulty in creating fingerprints that identify an entire family from these viruses. This difficulty is created by the use of techniques that have as their main objective compromise analysis by experts. The parameters chosen for the behavioral analysis are: File System; Records Windows; RAM Dump and API calls. As for the analysis of the code, the objective is to create, in binary virus, divisions in blocks, where it is possible to extract hashes. This technique considers the instruction there and its neighborhood, characterized as being accurate. In short, with this information is intended to predict and draw a profile of action of the virus and then create a fingerprint based on the degree of kinship between them (threshold), whose goal is to increase the ability to detect viruses that do not make part of the same family

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Boron is a semi-metal present in certain types of soils and natural waters. It is essential to the healthy development of plants and non-toxic to humans, depending on its concentration. It is used in various industries and it s present in water production coming from oil production. More specifically in Rio Grande do Norte, one of the largest oil producers on shore of Brazil, the relationship water/oil in some fields becomes more than 90%. The most common destination of this produced water is disposal in open sea after processing to meet the legal specification. In this context, this research proposes to study the extraction of boron in water produced by microemulsion systems for industrial utilization. It was taken into account the efficiency of extraction of boron related to surfactant (DDA and OCS, both characterized by FT-IR), cosurfactant (butanol and isoamyl alcohol), organic phase (kerosene and heptanes) and aqueous phase (solution of boron 3.6 ppm in alkaline pH). The ratio cosurfactant/ surfactant used was four and the percentage of organic phases for all points of study was set at 5%. It was chosen points with the highest percentage of aqueous phase. Each system was designed for three points of different compositions in relation to the constituents of a pseudoternary diagram. These points were chosen according to studies of phase behavior in pseudoternary diagrams made in previous studies. For this research, points were chosen in the Winsor II region. The excess aqueous solution obtained in these systems was separated and analyzed by ICP OES. For the data set obtained, the better efficiency in the extraction of boron was obtained using the system with DAC, isoamyl alcohol and heptanes, which extracted 49% in a single step. OCS was not viable to the extraction of boron by microemulsion system in the conditions defined in this study

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Caatinga is an important laboratory for studies about arthropods adaptations and aclimatations because its precipitation is highly variable in time. We studied the effects of time variability over the composition of Arthropods in a caatinga area. The study was carried out at a preservation area on Almas Farm, São José dos Cordeiros, Paraíba. Samples were collected in two 100 m long parallel transects, separated for a 30 m distance, in a dense tree dominated caatinga area, between August 2007 and July 2008. Samples were collected in each transect every 10 m. Ten soil samples were taken from each transect, both at 0-5 cm (A) and 5-10 cm (B) depth, resulting in 40 samples each month. The Berlese funnel method was used for fauna extraction. We registered 26 orders and the arthropods density in the soil ranged from 3237 to 22774 individuals.m-2 from January 2007 to March 2008, respectively. There was no difference between layers A and B regarding orders abundance and richness. The groups recorded include groups with few records or that had no records in the Caatinga region yet as Pauropoda, Psocoptera, Thysanoptera, Protura and Araneae. Acari was the most abundant group, with 66,7% of the total number of individuals. Soil Arthropods presented a positive correlation with soil moisture, vegetal cover, precipitation and real evapotranspiration. Increases in fauna richness and abundance were registered in February, a month after the beginning of the rainy season. A periodic rain events in arid and semiarid ecosystems triggers physiological responses in edafic organisms, like arthropods. Edafic arthropods respond to time variability in the Caatinga biome. This fauna variation has to be considered in studies of this ecosystem, because the variation of Arthropods composition in soil can affect the dynamics of the food web through time

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Este trabalho sugere uma proposta de desenvolvimento regional sustentável no semiárido nordestino brasileiro promovido por termelétricas convencionais já instaladas e operando atualmente com combustíveis não-renováveis (diesel ou óleo mineral pesada). A proposta está formatada num modelo de cadeia produtiva de oleaginosa composta por processo seqüencial de produção agrícola caracterizada com agricultura familiar, extração de óleo vegetal in natura das sementes de mamona e conversão em biodiesel e, finalmente, aplicação de misturas de óleos de origem vegetal adlcloaados aos atuais combustíveis de termelétricas para geração de eletricidade. Os resultados dessa aplicação são geradores tornando-se agentes de desenvolvimento sustentável sobre os aspectos econômicos, sociais e ambientais, como: estímulo da economia local; a promoção de geração de emprego e renda para a comunidade local; fixação do homem no campo; minimização de emissão de gás de efeito estufa, geração de energia limpa e renovável e etc.

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Based on Newmark-β method, a structural vibration response is predicted. Through finding the appropriate control force parameters within certain ranges to optimize the objective function, the predictive control of the structural vibration is achieved. At the same time, the numerical simulation analysis of a two-storey frame structure with magneto-rheological (MR) dampers under earthquake records is carried out, and the parameter influence on structural vibration reduction is discussed. The results demonstrate that the semi-active control based on Newmark-β predictive algorithm is better than the classical control strategy based on full-state feedback control and has remarkable advantages of structural vibration reduction and control robustness.

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An algorithm to improve the accuracy and stability of rigid-body contact force calculation is presented. The algorithm uses a combination of analytic solutions and numerical methods to solve a spring-damper differential equation typical of a contact model. The solution method employs the recently proposed patch method, which especially suits the spring-damper differential equations. The resulting semi-analytic solution reduces the stiffness of the differential equations, while performing faster than conventional alternatives.

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This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

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Vehicular traffic in urban areas may adversely affect urban water quality through the build-up of traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) on road surfaces. The characterisation of the build-up processes is the key to developing mitigation measures for the removal of such pollutants from urban stormwater. An in-depth analysis of the build-up of SVOCs and NVOCs was undertaken in the Gold Coast region in Australia. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the SVOC and NVOC build-up under combined traffic scenarios of low, moderate, and high traffic in different land uses. It was found that congestion in the commercial areas and use of lubricants and motor oils in the industrial areas were the main sources of SVOCs and NVOCs on urban roads, respectively. The contribution from residential areas to the build-up of such pollutants was hardly noticeable. It was also revealed through this investigation that the target SVOCs and NVOCs were mainly attached to particulate fractions of 75 to 300 µm whilst the redistribution of coarse fractions due to vehicle activity mainly occurred in the >300 µm size range. Lastly, under combined traffic scenario, moderate traffic with average daily traffic ranging from 2300 to 5900 and average congestion of 0.47 was found to dominate SVOC and NVOC build-up on roads.

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The functional properties of cartilaginous tissues are determined predominantly by the content, distribution, and organization of proteoglycan and collagen in the extracellular matrix. Extracellular matrix accumulates in tissue-engineered cartilage constructs by metabolism and transport of matrix molecules, processes that are modulated by physical and chemical factors. Constructs incubated under free-swelling conditions with freely permeable or highly permeable membranes exhibit symmetric surface regions of soft tissue. The variation in tissue properties with depth from the surfaces suggests the hypothesis that the transport processes mediated by the boundary conditions govern the distribution of proteoglycan in such constructs. A continuum model (DiMicco and Sah in Transport Porus Med 50:57-73, 2003) was extended to test the effects of membrane permeability and perfusion on proteoglycan accumulation in tissue-engineered cartilage. The concentrations of soluble, bound, and degraded proteoglycan were analyzed as functions of time, space, and non-dimensional parameters for several experimental configurations. The results of the model suggest that the boundary condition at the membrane surface and the rate of perfusion, described by non-dimensional parameters, are important determinants of the pattern of proteoglycan accumulation. With perfusion, the proteoglycan profile is skewed, and decreases or increases in magnitude depending on the level of flow-based stimulation. Utilization of a semi-permeable membrane with or without unidirectional flow may lead to tissues with depth-increasing proteoglycan content, resembling native articular cartilage.

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Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.