982 resultados para Engineering structures
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The overarching goal of the proposed research was to evaluate the hydraulic performance of twenty two (22) fish-passage structures located in close proximity to bridges in western Iowa and within the HCA (Hungry Canyon Alliance) territory. Such structures include riprap weirs, fish ladders and grouted ripraps. The hydraulic performance of the aforementioned structures was evaluated via detailed field tests for a range of flow conditions relevant to fish migration through bridge waterways in different streams in western Iowa.
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Of the approximately 25,000 bridges in Iowa, 28% are classified as structurally deficient, functionally obsolete, or both. Because many Iowa bridges require repair or replacement with a relatively limited funding base, there is a need to develop new bridge materials that may lead to longer life spans and reduced life-cycle costs. In addition, new and effective methods for determining the condition of structures are needed to identify when the useful life has expired or other maintenance is needed. Due to its unique alloy blend, high-performance steel (HPS) has been shown to have improved weldability, weathering capabilities, and fracture toughness than conventional structural steels. Since the development of HPS in the mid-1990s, numerous bridges using HPS girders have been constructed, and many have been economically built. The East 12th Street Bridge, which replaced a deteriorated box girder bridge, is Iowa’s first bridge constructed using HPS girders. The new structure is a two-span bridge that crosses I-235 in Des Moines, Iowa, providing one lane of traffic in each direction. A remote, continuous, fiber-optic based structural health monitoring (SHM) system for the bridge was developed using off-the-shelf technologies. In the system, sensors strategically located on the bridge collect raw strain data and then transfer the data via wireless communication to a gateway system at a nearby secure facility. The data are integrated and converted to text files before being uploaded automatically to a website that provides live strain data and a live video stream. A data storage/processing system at the Bridge Engineering Center in Ames, Iowa, permanently stores and processes the data files. Several processes are performed to check the overall system’s operation, eliminate temperature effects from the complete strain record, compute the global behavior of the bridge, and count strain cycles at the various sensor locations.
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College of Engineering at Iowa State University produced a strategic plan for the years 2005-2010.
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The shrews of the Sorex araneus group, characterized by the sexual chromosome complex XY1, Y2 have been intensively studied by morphological, karyotypical, and biochemical analyses. Nevertheless, the phylogenetic relationships among the species belonging to the araneus complex are still under debate, as different approaches gave often contradictory results. In this paper, partial nucleotide sequences of the mitochondrial DNA cytochrome b gene (1011 bp) were determined for 6 species of the araneus group from Eurasia and North America. We also included in the data set the sequences of Sorex samniticus, whose relationships with the araneus group remain controversial. Three other species representing two major karyological groups were also examined. Both parsimony and distance trees strongly support the monophyly of the araneus group. Sorex sumniticus is significantly more closely related to the araneus complex than to the other species included in the analysis. Based on the branching pattern within the araneus group, an attempt has been made to reconstruct the colonization history of the Holarctic region.
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Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.
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One of the key emphases of these three essays is to provide practical managerial insight. However, good practical insight, can only be created by grounding it firmly on theoretical and empirical research. Practical experience-based understanding without theoretical grounding remains tacit and cannot be easily disseminated. Theoretical understanding without links to real life remains sterile. My studies aim to increase the understanding of how radical innovation could be generated at large established firms and how it can have an impact on business performance as most businesses pursue innovation with one prime objective: value creation. My studies focus on large established firms with sales revenue exceeding USD $ 1 billion. Usually large established firms cannot rely on informal ways of management, as these firms tend to be multinational businesses operating with subsidiaries, offices, or production facilities in more than one country. I. Internal and External Determinants of Corporate Venture Capital Investment The goal of this chapter is to focus on CVC as one of the mechanisms available for established firms to source new ideas that can be exploited. We explore the internal and external determinants under which established firms engage in CVC to source new knowledge through investment in startups. We attempt to make scholars and managers aware of the forces that influence CVC activity by providing findings and insights to facilitate the strategic management of CVC. There are research opportunities to further understand the CVC phenomenon. Why do companies engage in CVC? What motivates them to continue "playing the game" and keep their active CVC investment status. The study examines CVC investment activity, and the importance of understanding the influential factors that make a firm decide to engage in CVC. The main question is: How do established firms' CVC programs adapt to changing internal conditions and external environments. Adaptation typically involves learning from exploratory endeavors, which enable companies to transform the ways they compete (Guth & Ginsberg, 1990). Our study extends the current stream of research on CVC. It aims to contribute to the literature by providing an extensive comparison of internal and external determinants leading to CVC investment activity. To our knowledge, this is the first study to examine the influence of internal and external determinants on CVC activity throughout specific expansion and contraction periods determined by structural breaks occurring between 1985 to 2008. Our econometric analysis indicates a strong and significant positive association between CVC activity and R&D, cash flow availability and environmental financial market conditions, as well as a significant negative association between sales growth and the decision to engage into CVC. The analysis of this study reveals that CVC investment is highly volatile, as demonstrated by dramatic fluctuations in CVC investment activity over the past decades. When analyzing the overall cyclical CVC period from 1985 to 2008 the results of our study suggest that CVC activity has a pattern influenced by financial factors such as the level of R&D, free cash flow, lack of sales growth, and external conditions of the economy, with the NASDAQ price index as the most significant variable influencing CVC during this period. II. Contribution of CVC and its Interaction with R&D to Value Creation The second essay takes into account the demands of corporate executives and shareholders regarding business performance and value creation justifications for investments in innovation. Billions of dollars are invested in CVC and R&D. However there is little evidence that CVC and its interaction with R&D create value. Firms operating in dynamic business sectors seek to innovate to create the value demanded by changing market conditions, consumer preferences, and competitive offerings. Consequently, firms operating in such business sectors put a premium on finding new, sustainable and competitive value propositions. CVC and R&D can help them in this challenge. Dushnitsky and Lenox (2006) presented evidence that CVC investment is associated with value creation. However, studies have shown that the most innovative firms do not necessarily benefit from innovation. For instance Oyon (2007) indicated that between 1995 and 2005 the most innovative automotive companies did not obtain adequate rewards for shareholders. The interaction between CVC and R&D has generated much debate in the CVC literature. Some researchers see them as substitutes suggesting that firms have to choose between CVC and R&D (Hellmann, 2002), while others expect them to be complementary (Chesbrough & Tucci, 2004). This study explores the interaction that CVC and R&D have on value creation. This essay examines the impact of CVC and R&D on value creation over sixteen years across six business sectors and different geographical regions. Our findings suggest that the effect of CVC and its interaction with R&D on value creation is positive and significant. In dynamic business sectors technologies rapidly relinquish obsolete, consequently firms operating in such business sectors need to continuously develop new sources of value creation (Eisenhardt & Martin, 2000; Qualls, Olshavsky, & Michaels, 1981). We conclude that in order to impact value creation, firms operating in business sectors such as Engineering & Business Services, and Information Communication & Technology ought to consider CVC as a vital element of their innovation strategy. Moreover, regarding the CVC and R&D interaction effect, our findings suggest that R&D and CVC are complementary to value creation hence firms in certain business sectors can be better off supporting both R&D and CVC simultaneously to increase the probability of generating value creation. III. MCS and Organizational Structures for Radical Innovation Incremental innovation is necessary for continuous improvement but it does not provide a sustainable permanent source of competitiveness (Cooper, 2003). On the other hand, radical innovation pursuing new technologies and new market frontiers can generate new platforms for growth providing firms with competitive advantages and high economic margin rents (Duchesneau et al., 1979; Markides & Geroski, 2005; O'Connor & DeMartino, 2006; Utterback, 1994). Interestingly, not all companies distinguish between incremental and radical innovation, and more importantly firms that manage innovation through a one-sizefits- all process can almost guarantee a sub-optimization of certain systems and resources (Davila et al., 2006). Moreover, we conducted research on the utilization of MCS along with radical innovation and flexible organizational structures as these have been associated with firm growth (Cooper, 2003; Davila & Foster, 2005, 2007; Markides & Geroski, 2005; O'Connor & DeMartino, 2006). Davila et al. (2009) identified research opportunities for innovation management and provided a list of pending issues: How do companies manage the process of radical and incremental innovation? What are the performance measures companies use to manage radical ideas and how do they select them? The fundamental objective of this paper is to address the following research question: What are the processes, MCS, and organizational structures for generating radical innovation? Moreover, in recent years, research on innovation management has been conducted mainly at either the firm level (Birkinshaw, Hamel, & Mol, 2008a) or at the project level examining appropriate management techniques associated with high levels of uncertainty (Burgelman & Sayles, 1988; Dougherty & Heller, 1994; Jelinek & Schoonhoven, 1993; Kanter, North, Bernstein, & Williamson, 1990; Leifer et al., 2000). Therefore, we embarked on a novel process-related research framework to observe the process stages, MCS, and organizational structures that can generate radical innovation. This article is based on a case study at Alcan Engineered Products, a division of a multinational company provider of lightweight material solutions. Our observations suggest that incremental and radical innovation should be managed through different processes, MCS and organizational structures that ought to be activated and adapted contingent to the type of innovation that is being pursued (i.e. incremental or radical innovation). More importantly, we conclude that radical can be generated in a systematic way through enablers such as processes, MCS, and organizational structures. This is in line with the findings of Jelinek and Schoonhoven (1993) and Davila et al. (2006; 2007) who show that innovative firms have institutionalized mechanisms, arguing that radical innovation cannot occur in an organic environment where flexibility and consensus are the main managerial mechanisms. They rather argue that radical innovation requires a clear organizational structure and formal MCS.
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Cape Verde, off the coast of Senegal in western Africa, is a volcanic archipelago where soil and water conservation techniques play an important role in the overall subsistence of half a million inhabitants. In fact, the step slopes in the more agricultural islands due to it's volcanic origin, together with semi-arid and arid environments (the country is located in the Sahelian region), characterized by a very irregular wet season, with high intensity rainfall events, make life tough. The hard conditions lead during the first half of the XX century to frequent cycles of drought with severe implications on the local populations, with impressive numbers of deaths by famine, and a decrease of the number of local inhabitants by more than halve in some islands. Maintain the soil in place and the water inside the soil was there after a mater of survival, and the CapeVerdians implemented over the last half century a number of soil and water conservation techniques that cover all the landscape. In this work, we monitored a number of slope soil and water conservation techniques, such as terraces, half moons, live barriers, etc, together with two cultural strategies, used to plant corn and beans on one side and peanuts on the other, with a semi-quantitative methodology, to evaluate their effectiveness. A discussion is given on the costs and effectiveness of the techniques to reduce overland flow production and therefore erosion, and to promote rainfall infiltration.
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Recombinant strains of the oleaginous yeast Yarrowia lipolytica expressing the PHA synthase gene (PhaC) from Pseudomonas aeruginosa in the peroxisome were found able to produce polyhydroxyalkanoates (PHA). PHA production yield, but not the monomer composition, was dependent on POX genotype (POX genes encoding acyl-CoA oxidases) (Haddouche et al. FEMS Yeast Res 10:917-927, 2010). In this study of variants of the Y. lipolytica β-oxidation multifunctional enzyme, with deletions or inactivations of the R-3-hydroxyacyl-CoA dehydrogenase domain, we were able to produce hetero-polymers (functional MFE enzyme) or homo-polymers (with no 3-hydroxyacyl-CoA dehydrogenase activity) of PHA consisting principally of 3-hydroxyacid monomers (>80%) of the same length as the external fatty acid used for growth. The redirection of fatty acid flux towards β-oxidation, by deletion of the neutral lipid synthesis pathway (mutant strain Q4 devoid of the acyltransferases encoded by the LRO1, DGA1, DGA2 and ARE1 genes), in combination with variant expressing only the enoyl-CoA hydratase 2 domain, led to a significant increase in PHA levels, to 7.3% of cell dry weight. Finally, the presence of shorter monomers (up to 20% of the monomers) in a mutant strain lacking the peroxisomal 3-hydroxyacyl-CoA dehydrogenase domain provided evidence for the occurrence of partial mitochondrial β-oxidation in Y. lipolytica.
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Using data for all the fixtures for the seasons from 1972-73 to 2002-03, we estimate a dynamic model of demand for football pools in Spain paying attention to whether their main economic explanatory variable is the effective price of a ticket or the jackpot. Additionally, we evaluate the importance of the composition of the list of games in terms of whether First Division matches are included or not. Results show that the jackpot model is preferred to the effective price model, having important implications in terms of how the structure of the game should be changed in order to increase demand.
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Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.
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In moment structure analysis with nonnormal data, asymptotic valid inferences require the computation of a consistent (under general distributional assumptions) estimate of the matrix $\Gamma$ of asymptotic variances of sample second--order moments. Such a consistent estimate involves the fourth--order sample moments of the data. In practice, the use of fourth--order moments leads to computational burden and lack of robustness against small samples. In this paper we show that, under certain assumptions, correct asymptotic inferences can be attained when $\Gamma$ is replaced by a matrix $\Omega$ that involves only the second--order moments of the data. The present paper extends to the context of multi--sample analysis of second--order moment structures, results derived in the context of (simple--sample) covariance structure analysis (Satorra and Bentler, 1990). The results apply to a variety of estimation methods and general type of statistics. An example involving a test of equality of means under covariance restrictions illustrates theoretical aspects of the paper.
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We extend to score, Wald and difference test statistics the scaled and adjusted corrections to goodness-of-fit test statistics developed in Satorra and Bentler (1988a,b). The theory is framed in the general context of multisample analysis of moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the relation of the scaled and corrected statistics to the asymptotic robust ones, is discussed. A Monte Carlo study illustrates thecomparative performance in finite samples of corrected score test statistics.
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Today, information technology is strategically important to the goals and aspirations of the business enterprises, government and high-level education institutions – university. Universities are facing new challenges with the emerging global economy characterized by the importance of providing faster communication services and improving the productivity and effectiveness of individuals. New challenges such as provides an information network that supports the demands and diversification of university issues. A new network architecture, which is a set of design principles for build a network, is one of the pillar bases. It is the cornerstone that enables the university’s faculty, researchers, students, administrators, and staff to discover, learn, reach out, and serve society. This thesis focuses on the network architecture definitions and fundamental components. Three most important characteristics of high-quality architecture are that: it’s open network architecture; it’s service-oriented characteristics and is an IP network based on packets. There are four important components in the architecture, which are: Services and Network Management, Network Control, Core Switching and Edge Access. The theoretical contribution of this study is a reference model Architecture of University Campus Network that can be followed or adapted to build a robust yet flexible network that respond next generation requirements. The results found are relevant to provide an important complete reference guide to the process of building campus network which nowadays play a very important role. Respectively, the research gives university networks a structured modular model that is reliable, robust and can easily grow.