935 resultados para accessibility analysis tools


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The Internet has become an integral part of our nation’s critical socio-economic infrastructure. With its heightened use and growing complexity however, organizations are at greater risk of cyber crimes. To aid in the investigation of crimes committed on or via the Internet, a network forensics analysis tool pulls together needed digital evidence. It provides a platform for performing deep network analysis by capturing, recording and analyzing network events to find out the source of a security attack or other information security incidents. Existing network forensics work has been mostly focused on the Internet and fixed networks. But the exponential growth and use of wireless technologies, coupled with their unprecedented characteristics, necessitates the development of new network forensic analysis tools. This dissertation fostered the emergence of a new research field in cellular and ad-hoc network forensics. It was one of the first works to identify this problem and offer fundamental techniques and tools that laid the groundwork for future research. In particular, it introduced novel methods to record network incidents and report logged incidents. For recording incidents, location is considered essential to documenting network incidents. However, in network topology spaces, location cannot be measured due to absence of a ‘distance metric’. Therefore, a novel solution was proposed to label locations of nodes within network topology spaces, and then to authenticate the identity of nodes in ad hoc environments. For reporting logged incidents, a novel technique based on Distributed Hash Tables (DHT) was adopted. Although the direct use of DHTs for reporting logged incidents would result in an uncontrollably recursive traffic, a new mechanism was introduced that overcome this recursive process. These logging and reporting techniques aided forensics over cellular and ad-hoc networks, which in turn increased their ability to track and trace attacks to their source. These techniques were a starting point for further research and development that would result in equipping future ad hoc networks with forensic components to complement existing security mechanisms.

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The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

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The Internet has become an integral part of our nation's critical socio-economic infrastructure. With its heightened use and growing complexity however, organizations are at greater risk of cyber crimes. To aid in the investigation of crimes committed on or via the Internet, a network forensics analysis tool pulls together needed digital evidence. It provides a platform for performing deep network analysis by capturing, recording and analyzing network events to find out the source of a security attack or other information security incidents. Existing network forensics work has been mostly focused on the Internet and fixed networks. But the exponential growth and use of wireless technologies, coupled with their unprecedented characteristics, necessitates the development of new network forensic analysis tools. This dissertation fostered the emergence of a new research field in cellular and ad-hoc network forensics. It was one of the first works to identify this problem and offer fundamental techniques and tools that laid the groundwork for future research. In particular, it introduced novel methods to record network incidents and report logged incidents. For recording incidents, location is considered essential to documenting network incidents. However, in network topology spaces, location cannot be measured due to absence of a 'distance metric'. Therefore, a novel solution was proposed to label locations of nodes within network topology spaces, and then to authenticate the identity of nodes in ad hoc environments. For reporting logged incidents, a novel technique based on Distributed Hash Tables (DHT) was adopted. Although the direct use of DHTs for reporting logged incidents would result in an uncontrollably recursive traffic, a new mechanism was introduced that overcome this recursive process. These logging and reporting techniques aided forensics over cellular and ad-hoc networks, which in turn increased their ability to track and trace attacks to their source. These techniques were a starting point for further research and development that would result in equipping future ad hoc networks with forensic components to complement existing security mechanisms.

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The need of the oil industry to ensure the safety of the facilities, employees and the environment, not to mention the search for maximum efficiency of its facilities, makes it seeks to achieve a high level of excellence in all stages of its production processes in order to obtain the required quality of the final product. Know the reliability of equipment and what it stands for a system is of fundamental importance for ensuring the operational safety. The reliability analysis technique has been increasingly applied in the oil industry as fault prediction tool and undesirable events that can affect business continuity. It is an applied scientific methodology that involves knowledge in engineering and statistics to meet and or analyze the performance of components, equipment and systems in order to ensure that they perform their function without fail, for a period of time and under a specific condition. The results of reliability analyzes help in making decisions about the best maintenance strategy of petrochemical plants. Reliability analysis was applied on equipment (bike-centrifugal fan) between the period 2010-2014 at the Polo Petrobras Guamaré Industrial, situated in rural Guamaré municipality in the state of Rio Grande do Norte, where he collected data field, analyzed historical equipment and observing the behavior of faults and their impacts. The data were processed in commercial software reliability ReliaSoft BlockSim 9. The results were compared with a study conducted by the experts in the field in order to get the best maintenance strategy for the studied system. With the results obtained from the reliability analysis tools was possible to determine the availability of the centrifugal motor-fan and what will be its impact on the security of process units if it will fail. A new maintenance strategy was established to improve the reliability, availability, maintainability and decreased likelihood of Moto-Centrifugal Fan failures, it is a series of actions to promote the increased system reliability and consequent increase in cycle life of the asset. Thus, this strategy sets out preventive measures to reduce the probability of failure and mitigating aimed at minimizing the consequences.

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The current study builds upon a previous study, which examined the degree to which the lexical properties of students’ essays could predict their vocabulary scores. We expand on this previous research by incorporating new natural language processing indices related to both the surface- and discourse-levels of students’ essays. Additionally, we investigate the degree to which these NLP indices can be used to account for variance in students’ reading comprehension skills. We calculated linguistic essay features using our framework, ReaderBench, which is an automated text analysis tools that calculates indices related to linguistic and rhetorical features of text. University students (n = 108) produced timed (25 minutes), argumentative essays, which were then analyzed by ReaderBench. Additionally, they completed the Gates-MacGinitie Vocabulary and Reading comprehension tests. The results of this study indicated that two indices were able to account for 32.4% of the variance in vocabulary scores and 31.6% of the variance in reading comprehension scores. Follow-up analyses revealed that these models further improved when only considering essays that contained multiple paragraph (R2 values = .61 and .49, respectively). Overall, the results of the current study suggest that natural language processing techniques can help to inform models of individual differences among student writers.

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Finance is one of the fastest growing areas in modern applied mathematics with real world applications. The interest of this branch of applied mathematics is best described by an example involving shares. Shareholders of a company receive dividends which come from the profit made by the company. The proceeds of the company, once it is taken over or wound up, will also be distributed to shareholders. Therefore shares have a value that reflects the views of investors about the likely dividend payments and capital growth of the company. Obviously such value will be quantified by the share price on stock exchanges. Therefore financial modelling serves to understand the correlations between asset and movements of buy/sell in order to reduce risk. Such activities depend on financial analysis tools being available to the trader with which he can make rapid and systematic evaluation of buy/sell contracts. There are other financial activities and it is not an intention of this paper to discuss all of these activities. The main concern of this paper is to propose a parallel algorithm for the numerical solution of an European option. This paper is organised as follows. First, a brief introduction is given of a simple mathematical model for European options and possible numerical schemes of solving such mathematical model. Second, Laplace transform is applied to the mathematical model which leads to a set of parametric equations where solutions of different parametric equations may be found concurrently. Numerical inverse Laplace transform is done by means of an inversion algorithm developed by Stehfast. The scalability of the algorithm in a distributed environment is demonstrated. Third, a performance analysis of the present algorithm is compared with a spatial domain decomposition developed particularly for time-dependent heat equation. Finally, a number of issues are discussed and future work suggested.

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Hyperspectral sensors are being developed for remote sensing applications. These sensors produce huge data volumes which require faster processing and analysis tools. Vertex component analysis (VCA) has become a very useful tool to unmix hyperspectral data. It has been successfully used to determine endmembers and unmix large hyperspectral data sets without the use of any a priori knowledge of the constituent spectra. Compared with other geometric-based approaches VCA is an efficient method from the computational point of view. In this paper we introduce new developments for VCA: 1) a new signal subspace identification method (HySime) is applied to infer the signal subspace where the data set live. This step also infers the number of endmembers present in the data set; 2) after the projection of the data set onto the signal subspace, the algorithm iteratively projects the data set onto several directions orthogonal to the subspace spanned by the endmembers already determined. The new endmember signature corresponds to these extreme of the projections. The capability of VCA to unmix large hyperspectral scenes (real or simulated), with low computational complexity, is also illustrated.

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O presente trabalho é o resultado de um projecto experimental que teve como principal objetivo a redução dos tempos de setup, através da implementação da metodologia Single Minute Exchange of Die (SMED) em equipamentos de eletroerosão (EDM) por fio e penetração. Para garantir o sucesso da implementação, após uma revisão bibliográfica centrada no tema SMED, estabelece-se uma metodologia, numa lógica de melhoria contínua análoga a um ciclo PDCA. A metodologia estabelecida envolve as seguintes fases: caracterização da situação inicial, observação, recolha de dados, análise dos dados e implementação SMED. A caracterização da situação inicial visa qualificar a situação encontrada e identificar a zona de atuação - equipamentos em estudo. A observação do processo produtivo é suportada pela ferramenta fluxograma do processo, por sua vez, a recolha de dados visa a avaliação inicial e nessa perspectiva recorre-se à abordagem OEE. Na fase de análise dos dados são introduzidas as ferramentas de análise VSM e diagrama de causa e efeito que auxiliam a identificação de um conjunto de acções de melhoria, a realizar previamente à fase de implementação SMED, culminando assim uma fase PRÉ-SMED. Reunidas as condições ideais iniciou-se a implementação efectiva da metodologia SMED obtendo-se reduções do tempo total de setup superiores a 60%. O presente estudo permite concluir que podem surgir diferenças significativas em diversas aplicações SMED, enfatizando a importância de uma fase PRÉ-SMED de modo a potenciar os resultados alcançados com uma implementação SMED.

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Security Onion is a Network Security Manager (NSM) platform that provides multiple Intrusion Detection Systems (IDS) including Host IDS (HIDS) and Network IDS (NIDS). Many types of data can be acquired using Security Onion for analysis. This includes data related to: Host, Network, Session, Asset, Alert and Protocols. Security Onion can be implemented as a standalone deployment with server and sensor included or with a master server and multiple sensors allowing for the system to be scaled as required. Many interfaces and tools are available for management of the system and analysis of data such as Sguil, Snorby, Squert and Enterprise Log Search and Archive (ELSA). These interfaces can be used for analysis of alerts and captured events and then can be further exported for analysis in Network Forensic Analysis Tools (NFAT) such as NetworkMiner, CapME or Xplico. The Security Onion platform also provides various methods of management such as Secure SHell (SSH) for management of server and sensors and Web client remote access. All of this with the ability to replay and analyse example malicious traffic makes the Security Onion a suitable low cost alternative for Network Security Management. In this paper, we have a feature and functionality review for the Security Onion in terms of: types of data, configuration, interface, tools and system management.

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The building envelope is the principal mean of interaction between indoors and environment, with direct influence on thermal and energy performance of the building. By intervening in the envelope, with the proposal of specific architectural elements, it is possible to promote the use of passive strategies of conditioning, such as natural ventilation. The cross ventilation is recommended by the NBR 15220-3 as the bioclimatic main strategy for the hot and humid climate of Natal/RN, offering among other benefits, the thermal comfort of occupants. The analysis tools of natural ventilation, on the other hand, cover a variety of techniques, from the simplified calculation methods to computer fluid dynamics, whose limitations are discussed in several papers, but without detailing the problems encountered. In this sense, the present study aims to evaluate the potential of wind catchers, envelope elements used to increase natural ventilation in the building, through CFD simplified simulation. Moreover, it seeks to quantify the limitations encountered during the analysis. For this, the procedure adopted to evaluate the elements implementation and efficiency was the CFD simulation, abbreviation for Computer Fluid Dynamics, with the software DesignBuilder CFD. It was defined a base case, where wind catchers were added with various settings, to compare them with each other and appreciate the differences in flows and air speeds encountered. Initially there has been done sensitivity tests for familiarization with the software and observe simulation patterns, mapping the settings used and simulation time for each case simulated. The results show the limitations encountered during the simulation process, as well as an overview of the efficiency and potential of wind catchers, with the increase of ventilation with the use of catchers, differences in air flow patterns and significant increase in air speeds indoors, besides changes found due to different element geometries. It is considered that the software used can help designers during preliminary analysis in the early stages of design

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Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

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O presente estudo refere-se a uma Dissertação de Mestrado em Educação Ambiental (EA) a qual teve como objetivo estabelecer um diálogo em torno do conceito de nature-za a partir da análise das formas desse discurso veiculadas nas histórias em quadrinhos (HQs) do personagem Chico Bento e suas relações com as concepções presentes no campo de saber da EA. Com a intenção de problematizar a forma como as HQs, através do discurso de natureza, vêm contribuindo para pensarmos sobre EA, selecionaram-se HQs do Chico Bento publicadas entre os anos de 2009 e 2013 e que fazem referência à natureza. Apoiado em autores como Michel Foucault, Isabel Carvalho, Leandro Belina-so Guimarães, Maria Lúcia Castagna Wortmann, Mônica Meyer, Keith Thomas, Ray-mond Williams, entre outros, a pesquisa analisou as enunciações de natureza que com-puseram o corpus de análise desta investigação. O caminho metodológico selecionado para operar com o material empírico trata especificamente de algumas ferramentas da Análise do Discurso, a partir de Michel Foucault. Na análise do material posto em sus-penso, a pesquisa apontou para dois enunciados potentes, os quais vêm auxiliando na constituição do discurso de natureza por meio das HQs: a natureza constituída nos des-locamentos operados pelas diferenças culturais entre as realidades rural e urbana e um ideal romântico de natureza produzido pela visibilidade e enunciabilidade das HQs do Chico Bento. Com isso, evidenciou-se que as HQs analisadas entram na ordem do dis-curso verdadeiro no campo da EA. Sendo assim, ressalta-se a importância de atentarmos para os gibis e suas histórias, como um artefato cultural potente que vem nos auxiliando a olhar para o dispositivo da EA. Tal dispositivo interpelando-nos a constituir modos de ser e de viver, diante de saberes e verdades produzidas na e pela cultura, pois, diante dos significados travados por meio da cultura, vamos engendrando nossos modos de vida, bem como estabelecendo relações com o mundo em que vivemos.

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Intelligent agents offer a new and exciting way of understanding the world of work. Agent-Based Simulation (ABS), one way of using intelligent agents, carries great potential for progressing our understanding of management practices and how they link to retail performance. We have developed simulation models based on research by a multi-disciplinary team of economists, work psychologists and computer scientists. We will discuss our experiences of implementing these concepts working with a well-known retail department store. There is no doubt that management practices are linked to the performance of an organisation (Reynolds et al., 2005; Wall & Wood, 2005). Best practices have been developed, but when it comes down to the actual application of these guidelines considerable ambiguity remains regarding their effectiveness within particular contexts (Siebers et al., forthcoming a). Most Operational Research (OR) methods can only be used as analysis tools once management practices have been implemented. Often they are not very useful for giving answers to speculative ‘what-if’ questions, particularly when one is interested in the development of the system over time rather than just the state of the system at a certain point in time. Simulation can be used to analyse the operation of dynamic and stochastic systems. ABS is particularly useful when complex interactions between system entities exist, such as autonomous decision making or negotiation. In an ABS model the researcher explicitly describes the decision process of simulated actors at the micro level. Structures emerge at the macro level as a result of the actions of the agents and their interactions with other agents and the environment. We will show how ABS experiments can deal with testing and optimising management practices such as training, empowerment or teamwork. Hence, questions such as “will staff setting their own break times improve performance?” can be investigated.

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The incredible rapid development to huge volumes of air travel, mainly because of jet airliners that appeared to the sky in the 1950s, created the need for systematic research for aviation safety and collecting data about air traffic. The structured data can be analysed easily using queries from databases and running theseresults through graphic tools. However, in analysing narratives that often give more accurate information about the case, mining tools are needed. The analysis of textual data with computers has not been possible until data mining tools have been developed. Their use, at least among aviation, is still at a moderate level. The research aims at discovering lethal trends in the flight safety reports. The narratives of 1,200 flight safety reports from years 1994 – 1996 in Finnish were processed with three text mining tools. One of them was totally language independent, the other had a specific configuration for Finnish and the third originally created for English, but encouraging results had been achieved with Spanish and that is why a Finnish test was undertaken, too. The global rate of accidents is stabilising and the situation can now be regarded as satisfactory, but because of the growth in air traffic, the absolute number of fatal accidents per year might increase, if the flight safety will not be improved. The collection of data and reporting systems have reached their top level. The focal point in increasing the flight safety is analysis. The air traffic has generally been forecasted to grow 5 – 6 per cent annually over the next two decades. During this period, the global air travel will probably double also with relatively conservative expectations of economic growth. This development makes the airline management confront growing pressure due to increasing competition, signify cant rise in fuel prices and the need to reduce the incident rate due to expected growth in air traffic volumes. All this emphasises the urgent need for new tools and methods. All systems provided encouraging results, as well as proved challenges still to be won. Flight safety can be improved through the development and utilisation of sophisticated analysis tools and methods, like data mining, using its results supporting the decision process of the executives.

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This study presents an application of the geographical information system technology on plant disease involving a multidisciplinary teamwork of geoprocessing and physiopathology specialists. The spatial analysis tools in a GIS were used to evaluate the spatial distribution of two diseases of maize in Brazil: polysora rusl caused by Puccinia polysora and tropical rust caused by Physopella zeae. A database of cIimate variables (mean temperature. relative humidity. and leaf wetness duration) of cIimatological normal from 1961-1990 was obtained and then related it to a mathematical model of disease development (polysora rust) and to the cIimate intervals (tropical rust) in order to obtain the maps. The choice of the model or the favorable climate interval is the important chalIenge of the method because the difficulty of adequacy to the spatial and temporal scales for the specific application. The major incidence of both disease occurred in almost alI the North region from January to June. although this region has traditionalIy a low production of maize. Considering the biggest producers regions. for both the diseases, favorable areas are located in part of Mato Grosso, Tocanlins. Minas Gerais; Mato Grosso do Sul. and coastal areas of São Paulo, Paraná, and Santa Catarina. varying among the dilferent months from January to June. The method allowed making an adequate distinction of the states and the months considered.