998 resultados para K-arc


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The Texas Transportation Commission (“the Commission”) is responsible for planning and making policies for the location, construction, and maintenance of a comprehensive system of highways and public roads in Texas. In order for the Commission to carry out its legislative mandate, the Texas Constitution requires that most revenue generated by motor vehicle registration fees and motor fuel taxes be used for constructing and maintaining public roadways and other designated purposes. The Texas Department of Transportation (TxDOT) assists the Commission in executing state transportation policy. It is the responsibility of the legislature to appropriate money for TxDOT’s operation and maintenance expenses. All money authorized to be appropriated for TxDOT’s operations must come from the State Highway Fund (also known as Fund 6, Fund 006, or Fund 0006). The Commission can then use the balance in the fund to fulfill its responsibilities. However, the value of the revenue received in Fund 6 is not keeping pace with growing demand for transportation infrastructure in Texas. Additionally, diversion of revenue to nontransportation uses now exceeds $600 million per year. As shown in Figure 1.1, revenues and expenditures of the State Highway Fund per vehicle mile traveled (VMT) in Texas have remained almost flat since 1993. In the meantime, construction cost inflation has gone up more than 100%, effectively halving the value of expenditure.

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This research report documents work conducted by the Center for Transportation (CTR) at The University of Texas at Austin in analyzing the Joint Analysis using the Combined Knowledge (J.A.C.K.) program. This program was developed by the Texas Department of Transportation (TxDOT) to make projections of revenues and expenditures. This research effort was to span from September 2008 to August 2009, but the bulk of the work was completed and presented by December 2008. J.A.C.K. was subsequently renamed TRENDS, but for consistency with the scope of work, the original name is used throughout this report.

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The proliferation of media services enabled by digital technologies poses a serious challenge to public service broadcasting rationales based on media scarcity. Looking to the past and future, we articulate an important role that the Australian Broadcasting Corporation (ABC) might play in the digital age. We argue that historically the ABC has acted beyond its institutional broadcasting remit to facilitate cultural development and, drawing on the example of Pool (an online community of creative practitioners established and maintained by the ABC), point to a key role it might play in fostering network innovation in what are now conceptualised as the creative industries.

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Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

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In this paper we present pyktree, an implementation of the K-tree algorithm in the Python programming language. The K-tree algorithm provides highly balanced search trees for vector quantization that scales up to very large data sets. Pyktree is highly modular and well suited for rapid-prototyping of novel distance measures and centroid representations. It is easy to install and provides a python package for library use as well as command line tools.

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In order to tackle the growth of air travelers in airports worldwide, it is important to simulate and understand passenger flows to predict future capacity constraints and levels of service. We discuss the ability of agent-based models to understand complicated pedestrian movement in built environments. In this paper we propose advanced passenger traits to enable more detailed modelling of behaviors in terminal buildings, particularly in the departure hall around the check-in facilities. To demonstrate the concepts, we perform a series of passenger agent simulations in a virtual airport terminal. In doing so, we generate a spatial distribution of passengers within the departure hall to ancillary facilities such as cafes, information kiosks and phone booths as well as common check-in facilities, and observe the effects this has on passenger check-in and departure hall dwell times, and facility utilization.

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Simulating passenger flows within airports is very important as it can provide an indication of queue lengths, bottlenecks, system capacity and overall level of service. To date, visual simulation tools such as agent based models have focused on processing formalities such as check-in, and not incorporate discretionary activities such as duty-free shopping. As airport retail contributes greatly to airport revenue generation, but also has potentially detrimental effects on facilitation efficiency benchmarks, this study developed a simplistic simulation model which captures common duty-free purchasing opportunities, as well as high-level behaviours of passengers. It is argued that such a model enables more realistic simulation of passenger facilitation, and provides a platform for simulating real-time revenue generation as well as more complex passenger behaviours within the airport. Simulations are conducted to verify the suitability of the model for inclusion in the international arrivals process for assessing passenger flow and infrastructure utilization.

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Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.

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PCR-based cancer diagnosis requires detection of rare mutations in k- ras, p53 or other genes. The assumption has been that mutant and wild-type sequences amplify with near equal efficiency, so that they are eventually present in proportions representative of the starting material. Work on factor IX suggests that this assumption is invalid for one case of near- sequence identity. To test the generality of this phenomenon and its relevance to cancer diagnosis, primers distant from point mutations in p53 and k-ras were used to amplify wild-type and mutant sequences from these genes. A substantial bias against PCR amplification of mutants was observed for two regions of the p53 gene and one region of k-ras. For k-ras and p53, bias was observed when the wild-type and mutant sequences were amplified separately or when mixed in equal proportions before PCR. Bias was present with proofreading and non-proofreading polymerase. Mutant and wild-type segments of the factor V, cystic fibrosis transmembrane conductance regulator and prothrombin genes were amplified and did not exhibit PCR bias. Therefore, the assumption of equal PCR efficiency for point mutant and wild-type sequences is invalid in several systems. Quantitative or diagnostic PCR will require validation for each locus, and enrichment strategies may be needed to optimize detection of mutants.

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The molecular structure of the mineral archerite ((K,NH4)H2PO4) has been determined and compared with that of biphosphammite ((NH4,K)H2PO4). Raman spectroscopy and infrared spectroscopy has been used to characterise these ‘cave’ minerals. Both minerals originated from the Murra-el-elevyn Cave, Eucla, Western Australia. The mineral is formed by the reaction of the chemicals in bat guano with calcite substrates. Raman and infrared bands are assigned to H2PO4-, OH and NH stretching vibrations. The Raman band at 981 cm-1 is assigned to the HOP stretching vibration. Bands in the 1200 to 1800 cm-1 region are associated with NH4+ bending modes. The molecular structure of the two minerals appear to be very similar, and it is therefore concluded that the two minerals are identical.

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It has been argued that the origins of modern creative industries policies can be found in Australia. The Creative Nation national cultural policy statement released by the Labor government headed by the Prime Minister Paul Keating in 1994 sought an original synthesis of arts and media policies that was outwardly looking, identifying the opportunities presented by what were then new digital media technologies, and clearly stated the economic opportunities presented by promotion of what were referred to at the time as the cultural industries. Several commentators have identified the influence that Creative Nation had on the Blair Labour government when it came to power in the United Kingdom in 1997. Faced with the question of how to revitalise the once-mighty industrial cities of the U.K. after the Conservative government, the Department of Culture, Media and Sport drew upon policy documents such as Australia’s Creative Nation, as well as the experience of local governments in these cities, in looking to the cultural sectors to spearhead new jobs growth, as well as re-branding the cities as cultural or creative cities in a post-industrial economic landscape. This growing alignment of culture and economics, that has been a characteristic of creative industries policies as they have developed in Australia, Britain, East Asia and Europe, marks an interesting shift in the traditional focus of arts and cultural policy as compensatory to the economic domain. The first Chair of what would become the Arts Council of Great Britain (now the Arts Council of England) was the famous economist John Maynard Keynes. In the First Annual Report of the Arts Council for 1945-1946, prepared in the latter stages of the Second World War, Keynes proposed that “the day is not far off when the economic problem will take the back seat where it belongs, and the arena of the heart and the head will be occupied or reoccupied, by our real problems — the problems of life and of human relations, of creation and behaviour and religion”. 中文摘要 1994年工黨執政時期澳洲總理基挺(Paul Keating)發表創意的國家(The Creative Nation)的文化政策聲明堪稱是澳洲現代創意產業的起源,該聲明試圖將藝術與媒體政策結合在一起,其目的在面向海外,為新數位媒體技術尋找機會。聲明中明確指出要推動文化產業為經濟帶來機會。「文化政策也是經濟政策。文化創造財富與附加價值,對創新、行銷與設計有重要貢獻,是我們工業的標誌(badge)。我們創意的層次實際上決定了我們適應新經濟imperatives的能力。文化本身就是項重要出口,是其他產品出口的主要附件(essential accompaniment)。文化吸引觀光與學生,也是我們經濟成功之關鍵。」 創意產業的策略是構建藝術、媒體與資訊電信科技的網絡以利文化產業在國家創新政策策略中擁有一席之地。此一策略最早是由1990年代末英國布萊爾(Tony Blair)的新工黨政府所採行,其後歐洲聯盟、澳洲、紐西蘭、新加坡、台灣、南韓與中國。

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Resolving a noted open problem, we show that the Undirected Feedback Vertex Set problem, parameterized by the size of the solution set of vertices, is in the parameterized complexity class Poly(k), that is, polynomial-time pre-processing is sufficient to reduce an initial problem instance (G, k) to a decision-equivalent simplified instance (G', k') where k' � k, and the number of vertices of G' is bounded by a polynomial function of k. Our main result shows an O(k11) kernelization bound.

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Compressive Sensing (CS) is a popular signal processing technique, that can exactly reconstruct a signal given a small number of random projections of the original signal, provided that the signal is sufficiently sparse. We demonstrate the applicability of CS in the field of gait recognition as a very effective dimensionality reduction technique, using the gait energy image (GEI) as the feature extraction process. We compare the CS based approach to the principal component analysis (PCA) and show that the proposed method outperforms this baseline, particularly under situations where there are appearance changes in the subject. Applying CS to the gait features also avoids the need to train the models, by using a generalised random projection.

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Many phosphate containing minerals are found in the Jenolan Caves. Such minerals are formed by the reaction of bat guano and clays from the caves. Among these cave minerals is the mineral taranakite (K,NH4)Al3(PO4)3(OH)•9(H2O) which has been identified by X-ray diffraction. Jenolan Caves taranakite has been characterised by Raman spectroscopy. Raman and infrared bands are assigned to H2PO4-, OH and NH stretching vibrations. By using a combination of XRD and Raman spectroscopy, the existence of taranakite in the caves has been proven.