896 resultados para dynamic and static collection


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The book represents a very interesting example of the possibility to combine in a single publication basic theory of structures and quite advanced topics on the same subject. The author fulfills this objective in a reasonable size book, less than 400 pages divided into 15 chapters averaging 20 pages each plus 9 short appendices. A diskette is also included in the book. This diskette contains training as well practical executable programs on different aspects of structural analysis, such as cross-sections properties,general-purpose computer programs for the static, dynamic and stability analysis of simple bar structures, etc. The book figures are didactic and have been carefully drawn.

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Mode of access: Internet.

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Issued in 3 parts. The second (p. [81]-158) has special t.p.: A catalogue of the remaining part of this collection of prints ... which will be sold by Mr. Greenwood ... on Tuesday the 21st day of February, 1786, and seventeen following days. The third (p. 159-169) has special t.p.: A continuation, of a most curious, scarce, valuable, and fine collection of all those persons who ... are entitled to a place in the English school ... [sold March 14-15, 1786].

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Thesis (Ph.D.)--University of Washington, 2016-06

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The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approach to overcome degradation in performance with respect to increasing dimensions is to reduce the dimensionality of the original dataset before constructing the index. However, identifying the correlation among the dimensions and effectively reducing them are challenging tasks. In this paper, we present an adaptive Multi-level Mahalanobis-based Dimensionality Reduction (MMDR) technique for high-dimensional indexing. Our MMDR technique has four notable features compared to existing methods. First, it discovers elliptical clusters for more effective dimensionality reduction by using only the low-dimensional subspaces. Second, data points in the different axis systems are indexed using a single B+-tree. Third, our technique is highly scalable in terms of data size and dimension. Finally, it is also dynamic and adaptive to insertions. An extensive performance study was conducted using both real and synthetic datasets, and the results show that our technique not only achieves higher precision, but also enables queries to be processed efficiently. Copyright Springer-Verlag 2005

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Business environments have become exceedingly dynamic and competitive in recent times. This dynamism is manifested in the form of changing process requirements and time constraints. Workflow technology is currently one of the most promising fields of research in business process automation. However, workflow systems to date do not provide the flexibility necessary to support the dynamic nature of business processes. In this paper we primarily discuss the issues and challenges related to managing change and time in workflows representing dynamic business processes. We also present an analysis of workflow modifications and provide feasibility considerations for the automation of this process.

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This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup)

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This paper builds on Granovetter's distinction between strong and weak ties [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol. 78(6) 1360–1380] in order to respond to recent calls for a more dynamic and processual understanding of networks. The concepts of potential and latent tie are deductively identified, and their implications for understanding how and why networks emerge, evolve, and change are explored. A longitudinal empirical study conducted with companies operating in the European motorsport industry reveals that firms take strategic actions to search for potential ties and reactivate latent ties in order to solve problems of network redundancy and overload. Examples are given, and their characteristics are examined to provide theoretical elaboration of the relationship between the types of tie and network evolution. These conceptual and empirical insights move understanding of the managerial challenge of building effective networks beyond static structural contingency models of optimal network forms to highlight the processes and capabilities of dynamic relationship building and network development. In so doing, this paper highlights the interrelationship between search and redundancy and the scope for strategic action alongside path dependence and structural influences on network processes.

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The research presented in this thesis was developed as part of DIBANET, an EC funded project aiming to develop an energetically self-sustainable process for the production of diesel miscible biofuels (i.e. ethyl levulinate) via acid hydrolysis of selected biomass feedstocks. Three thermal conversion technologies, pyrolysis, gasification and combustion, were evaluated in the present work with the aim of recovering the energy stored in the acid hydrolysis solid residue (AHR). Mainly consisting of lignin and humins, the AHR can contain up to 80% of the energy in the original feedstock. Pyrolysis of AHR proved unsatisfactory, so attention focussed on gasification and combustion with the aim of producing heat and/or power to supply the energy demanded by the ethyl levulinate production process. A thermal processing rig consisting on a Laminar Entrained Flow Reactor (LEFR) equipped with solid and liquid collection and online gas analysis systems was designed and built to explore pyrolysis, gasification and air-blown combustion of AHR. Maximum liquid yield for pyrolysis of AHR was 30wt% with volatile conversion of 80%. Gas yield for AHR gasification was 78wt%, with 8wt% tar yields and conversion of volatiles close to 100%. 90wt% of the AHR was transformed into gas by combustion, with volatile conversions above 90%. 5volO2%-95vol%N2 gasification resulted in a nitrogen diluted, low heating value gas (2MJ/m3). Steam and oxygen-blown gasification of AHR were additionally investigated in a batch gasifier at KTH in Sweden. Steam promoted the formation of hydrogen (25vol%) and methane (14vol%) improving the gas heating value to 10MJ/m3, below the typical for steam gasification due to equipment limitations. Arrhenius kinetic parameters were calculated using data collected with the LEFR to provide reaction rate information for process design and optimisation. Activation energy (EA) and pre-exponential factor (ko in s-1) for pyrolysis (EA=80kJ/mol, lnko=14), gasification (EA=69kJ/mol, lnko=13) and combustion (EA=42kJ/mol, lnko=8) were calculated after linearly fitting the data using the random pore model. Kinetic parameters for pyrolysis and combustion were also determined by dynamic thermogravimetric analysis (TGA), including studies of the original biomass feedstocks for comparison. Results obtained by differential and integral isoconversional methods for activation energy determination were compared. Activation energy calculated by the Vyazovkin method was 103-204kJ/mol for pyrolysis of untreated feedstocks and 185-387kJ/mol for AHRs. Combustion activation energy was 138-163kJ/mol for biomass and 119-158 for AHRs. The non-linear least squares method was used to determine reaction model and pre-exponential factor. Pyrolysis and combustion of biomass were best modelled by a combination of third order reaction and 3 dimensional diffusion models, while AHR decomposed following the third order reaction for pyrolysis and the 3 dimensional diffusion for combustion.

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In the global Internet economy, e-business as a driving force to redefine business models and operational processes is posing new challenges for traditional organizational structures and information system (IS) architectures. These are showing promises of a renewed period of innovative thinking in e-business strategies with new enterprise paradigms and different Enterprise Resource Planning (ERP) systems. In this chapter, the authors consider and investigate how dynamic e-business strategies, as the next evolutionary generation of e-business, can be realized through newly diverse enterprise structures supported by ERP, ERPII and so-called "ERPIII" solutions relying on the virtual value chain concept. Exploratory inductive multi-case studies in manufacturing and printing industries have been conducted. Additionally, it proposes a conceptual framework to discuss the adoption and governance of ERP systems within the context of three enterprise forms for enabling dynamic and collaborative e-business strategies, and particularly demonstrate how an enterprise can dynamically migrate from its current position to the patterns it desires to occupy in the future - a migration that must and will include dynamic e-business as a core competency, but that also relies heavily on ERP-based backbone and other robust technological platform and applications.

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Strategy is highly important for organisational success and the achievement of competitive advantage. Strategy is dynamic and it depends on accurate individual decision-making from medium and high-level managers and executives. Since managers always formulate strategy, its formulation depends mostly on their assertive decisions. Making good decisions is a complex task, even more in today’s business world where a large quantity of information and a dynamic environment forces people to decide without having complete information. As Shafir, Simonson, & Tversky (1993) point out, "the making of decisions, both big and small, is often difficult because of uncertainty and conflict". In this paper the author will explain a basic theoretical framework about top manager's individual decision-making, showing how complex the process of making high-impact decisions is; then, he will compare this theory with one of the most important streams in strategic management, the Resource-Based View (RBV) of the firm. Finally, within the context of individual decision-making and the RBV stream, the author will show how individual decision makers in top management positions constitute a valuable, rare, non-imitable and non-substitutable resource that provides sustained competitive advantage.

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Current reform initiatives recommend that geometry instruction include the study of three-dimensional geometric objects and provide students with opportunities to use spatial skills in problem-solving tasks. Geometer's Sketchpad (GSP) is a dynamic and interactive computer program that enables the user to investigate and explore geometric concepts and manipulate geometric structures. Research using GSP as an instructional tool has focused primarily on teaching and learning two-dimensional geometry. This study explored the effect of a GSP based instructional environment on students' geometric thinking and three-dimensional spatial ability as they used GSP to learn three-dimensional geometry. For 10 weeks, 18 tenth-grade students from an urban school district used GSP to construct and analyze dynamic, two-dimensional representations of three-dimensional objects in a classroom environment that encouraged exploration, discussion, conjecture, and verification. The data were collected primarily from participant observations and clinical interviews and analyzed using qualitative methods of analysis. In addition, pretest and posttest measures of three-dimensional spatial ability and van Hiele level of geometric thinking were obtained. Spatial ability measures were analyzed using standard t-test analysis. ^ The data from this study indicate that GSP is a viable tool to teach students about three-dimensional geometric objects. A comparison of students' pretest and posttest van Hiele levels showed an improvement in geometric thinking, especially for students on lower levels of the van Hiele theory. Evidence at the p < .05 level indicated that students' spatial ability improved significantly. Specifically, the GSP dynamic, visual environment supported students' visualization and reasoning processes as students attempted to solve challenging tasks about three-dimensional geometric objects. The GSP instructional activities also provided students with an experiential base and an intuitive understanding about three-dimensional objects from which more formal work in geometry could be pursued. This study demonstrates that by designing appropriate GSP based instructional environments, it is possible to help students improve their spatial skills, develop more coherent and accurate intuitions about three-dimensional geometric objects, and progress through the levels of geometric thinking proposed by van Hiele. ^

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Current reform initiatives recommend that school geometry teaching and learning include the study of three-dimensional geometric objects and provide students with opportunities to use spatial abilities in mathematical tasks. Two ways of using Geometer's Sketchpad (GSP), a dynamic and interactive computer program, in conjunction with manipulatives enable students to investigate and explore geometric concepts, especially when used in a constructivist setting. Research on spatial abilities has focused on visual reasoning to improve visualization skills. This dissertation investigated the hypothesis that connecting visual and analytic reasoning may better improve students' spatial visualization abilities as compared to instruction that makes little or no use of the connection of the two. Data were collected using the Purdue Spatial Visualization Tests (PSVT) administered as a pretest and posttest to a control and two experimental groups. Sixty-four 10th grade students in three geometry classrooms participated in the study during 6 weeks. Research questions were answered using statistical procedures. An analysis of covariance was used for a quantitative analysis, whereas a description of students' visual-analytic processing strategies was presented using qualitative methods. The quantitative results indicated that there were significant differences in gender, but not in the group factor. However, when analyzing a sub sample of 33 participants with pretest scores below the 50th percentile, males in one of the experimental groups significantly benefited from the treatment. A review of previous research also indicated that students with low visualization skills benefited more than those with higher visualization skills. The qualitative results showed that girls were more sophisticated in their visual-analytic processing strategies to solve three-dimensional tasks. It is recommended that the teaching and learning of spatial visualization start in the middle school, prior to students' more rigorous mathematics exposure in high school. A duration longer than 6 weeks for treatments in similar future research studies is also recommended.

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Over the past five years, XML has been embraced by both the research and industrial community due to its promising prospects as a new data representation and exchange format on the Internet. The widespread popularity of XML creates an increasing need to store XML data in persistent storage systems and to enable sophisticated XML queries over the data. The currently available approaches to addressing the XML storage and retrieval issue have the limitations of either being not mature enough (e.g. native approaches) or causing inflexibility, a lot of fragmentation and excessive join operations (e.g. non-native approaches such as the relational database approach). ^ In this dissertation, I studied the issue of storing and retrieving XML data using the Semantic Binary Object-Oriented Database System (Sem-ODB) to leverage the advanced Sem-ODB technology with the emerging XML data model. First, a meta-schema based approach was implemented to address the data model mismatch issue that is inherent in the non-native approaches. The meta-schema based approach captures the meta-data of both Document Type Definitions (DTDs) and Sem-ODB Semantic Schemas, thus enables a dynamic and flexible mapping scheme. Second, a formal framework was presented to ensure precise and concise mappings. In this framework, both schemas and the conversions between them are formally defined and described. Third, after major features of an XML query language, XQuery, were analyzed, a high-level XQuery to Semantic SQL (Sem-SQL) query translation scheme was described. This translation scheme takes advantage of the navigation-oriented query paradigm of the Sem-SQL, thus avoids the excessive join problem of relational approaches. Finally, the modeling capability of the Semantic Binary Object-Oriented Data Model (Sem-ODM) was explored from the perspective of conceptually modeling an XML Schema using a Semantic Schema. ^ It was revealed that the advanced features of the Sem-ODB, such as multi-valued attributes, surrogates, the navigation-oriented query paradigm, among others, are indeed beneficial in coping with the XML storage and retrieval issue using a non-XML approach. Furthermore, extensions to the Sem-ODB to make it work more effectively with XML data were also proposed. ^

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An increase in the demand for the freight shipping in the United States has been predicted for the near future and Longer Combination Vehicles (LCVs), which can carry more loads in each trip, seem like a good solution for the problem. Currently, utilizing LCVs is not permitted in most states of the US and little research has been conducted on the effects of these heavy vehicles on the roads and bridges. In this research, efforts are made to study these effects by comparing the dynamic and fatigue effects of LCVs with more common trucks. Ten Steel and prestressed concrete bridges with span lengths ranging from 30’ to 140’ are designed and modeled using the grid system in MATLAB. Additionally, three more real bridges including two single span simply supported steel bridges and a three span continuous steel bridge are modeled using the same MATLAB code. The equations of motion of three LCVs as well as eight other trucks are derived and these vehicles are subjected to different road surface conditions and bumps on the roads and the designed and real bridges. By forming the bridge equations of motion using the mass, stiffness and damping matrices and considering the interaction between the truck and the bridge, the differential equations are solved using the ODE solver in MATLAB and the results of the forces in tires as well as the deflections and moments in the bridge members are obtained. The results of this study show that for most of the bridges, LCVs result in the smallest values of Dynamic Amplification Factor (DAF) whereas the Single Unit Trucks cause the highest values of DAF when traveling on the bridges. Also in most cases, the values of DAF are observed to be smaller than the 33% threshold suggested by the design code. Additionally, fatigue analysis of the bridges in this study confirms that by replacing the current truck traffic with higher capacity LCVs, in most cases, the remaining fatigue life of the bridge is only slightly decreased which means that taking advantage of these larger vehicles can be a viable option for decision makers.