566 resultados para Modeling Geomorphological Processes


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Over recent years, many scholars have studied the conceptual modeling of information systems based on a theory of ontological expressiveness. This theory offers four constructs that inform properties of modeling grammars in the form of ontological deficiencies, and their implications for development and use of conceptual modeling in IS practice. In this paper we report on the development of a valid and reliable instrument for measuring the perceptions that individuals have of the ontological deficiencies of conceptual modeling grammars. We describe a multi-stage approach for instrument development that incorporates feedback from expert and user panels. We also report on a field test of the instrument with 590 modeling practitioners. We further study how different levels of modeling experience influence user perceptions of ontological deficiencies of modeling grammars. We provide implications for practice and future research.

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Purpose: To ascertain the effectiveness of object-centered three-dimensional representations for the modeling of corneal surfaces. Methods: Three-dimensional (3D) surface decomposition into series of basis functions including: (i) spherical harmonics, (ii) hemispherical harmonics, and (iii) 3D Zernike polynomials were considered and compared to the traditional viewer-centered representation of two-dimensional (2D) Zernike polynomial expansion for a range of retrospective videokeratoscopic height data from three clinical groups. The data were collected using the Medmont E300 videokeratoscope. The groups included 10 normal corneas with corneal astigmatism less than −0.75 D, 10 astigmatic corneas with corneal astigmatism between −1.07 D and 3.34 D (Mean = −1.83 D, SD = ±0.75 D), and 10 keratoconic corneas. Only data from the right eyes of the subjects were considered. Results: All object-centered decompositions led to significantly better fits to corneal surfaces (in terms of the RMS error values) than the corresponding 2D Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters (2, 4, 6, and 8 mm), and model orders (4th to 10th radial orders) The best results (smallest RMS fit error) were obtained with spherical harmonics decomposition which lead to about 22% reduction in the RMS fit error, as compared to the traditional 2D Zernike polynomials. Hemispherical harmonics and the 3D Zernike polynomials reduced the RMS fit error by about 15% and 12%, respectively. Larger reduction in RMS fit error was achieved for smaller corneral diameters and lower order fits. Conclusions: Object-centered 3D decompositions provide viable alternatives to traditional viewer-centered 2D Zernike polynomial expansion of a corneal surface. They achieve better fits to videokeratoscopic height data and could be particularly suited to the analysis of multiple corneal measurements, where there can be slight variations in the position of the cornea from one map acquisition to the next.

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Adiabatic compression testing of components in gaseous oxygen is a test method that is utilized worldwide and is commonly required to qualify a component for ignition tolerance under its intended service. This testing is required by many industry standards organizations and government agencies. This paper traces the background of adiabatic compression testing in the oxygen community and discusses the thermodynamic and fluid dynamic processes that occur during rapid pressure surges. This paper is the first of several papers by the authors on the subject of adiabatic compression testing and is presented as a non-comprehensive background and introduction.

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Road and highway infrastructure provides the backbone for a nation’s economic growth. The versatile dispersion of population in Australia and its resource boom, coupled with improved living standards and growing societal expectations, calls for continuing development and improvement of road infrastructure under the current local, state and federal governments’ policies and strategic plans. As road infrastructure projects involve huge resources and mechanisms, achieving sustainability not only on economic scales but also through environmental and social responsibility becomes a crucial issue. While sustainability is a logical link to infrastructure development, literature study and consultation with the industry found that there is a lack of common understanding on what constitutes sustainability in the infrastructure context. Its priorities are often interpreted differently among multiple stakeholders. For road infrastructure projects which typically span over long periods of time, achieving tangible sustainability outcomes during the lifecycle of development remains a formidable task. Sustainable development initiatives often remain ideological as in macro-level policies and broad-based concepts. There were little elaboration and exemplar cases on how these policies and concepts can be translated into practical decision-making during project implementation. In contrast, there seemed to be over commitment on research and development of sustainability assessment methods and tools. Between the two positions, there is a perception-reality gap and mismatch, specifically on how to enhance sustainability deliverables during infrastructure project delivery. Review on past research in this industry sector also found that little has been done to promote sustainable road infrastructure development; this has wide and varied potential impacts. This research identified the common perceptions and expectations by different stakeholders towards achieving sustainability in road and highway infrastructure projects. Face to face interviews on selected representatives of these stakeholders were carried out in order to select and categorize, confirm and prioritize a list of sustainability performance targets identified through literature and past research. A Delphi study was conducted with the assistance of a panel of senior industry professionals and academic experts, which further considered the interrelationship and influence of the sustainability indicators, and identified critical sustainability indicators under ten critical sustainability criteria (e.g. Environmental, Health & Safety, Resource Utilization & Management, Social & Cultural, Economic, Public Governance & Community Engagement, Relations Management, Engineering, Institutional and Project Management). This presented critical sustainability issues that needed to be addressed at the project level. Accordingly, exemplar highway development projects were used as case studies to elicit solutions for the critical issues. Through the identification and integration of different perceptions and priority needs of the stakeholders, as well as key sustainability indicators and solutions for critical issues, a set of decision-making guidelines was developed to promote and drive consistent sustainability deliverables in road infrastructure projects.

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Principal Topic: Resource decisions are critical to the venture creation process, which has important subsequent impacts on venture creation and performance (Boeker, 1989). Most entrepreneurs however, suffer substantial resource constraints in venture creation and during venture growth (Shepherd et al., 2000). Little is known about how high potential, sustainability ventures (the ventures of interest in this research), despite resource constraints, achieve continued venture persistence and venture success. One promising theory that explicitly links to resource constraints is a concept developed by Levi Strauss (1967) termed bricolage. Bricolage aligns with notions of resourcefulness: using what's on hand, through making do, and recombining resources for new or novel purposes (Baker & Nelson 2005). To the best of our knowledge, previous studies have not systematically investigated internal and external constraints, their combinations, and subsequent bricolage patterns. The majority of bricolage literature focuses on external environmental constraints (e.g. Wieck 1989; Baker & Nelson 2005), thereby paying less attention to in evaluating internal constraints (e.g. skills and capabilities) or constraint combinations. In this paper we focus on ventures that typically face resource-poor environments. High potential, nascent and young sustainability ventures are often created and developed with resource constraints and in some cases, have greater resource requirements owing to higher levels of technical sophistication of their products (Rothaermel & Deeds 2006). These ventures usually have high aspirations and potential for growth who ''seeks to meet the needs and aspirations without compromising the ability to meet those of the future'' (Brundtland Commission 1983). High potential ventures are increasingly attributed with a central role in the development of innovation, and employment in developed economies (Acs 2008). Further, increasing awareness of environmental and sustainability issues has fostered demand for business processes that reduce detrimental environmental impacts of global development (Dean & McMullen 2007) and more environmentally sensitive products and services: representing an opportunity for the development of ventures that seek to satisfy this demand through entrepreneurial action. These ventures may choose to ''make do'' with existing resources in developing resource combinations that produce the least impact on the environment. The continuous conflict between the greater requirements for resources and limited resource availability in high potential sustainable ventures, with the added complexity of balancing this with an uncompromising focus on using ''what's on hand'' to lessen environment impacts may make bricolage behaviours critical for these ventures. Research into bricolage behaviour is however, the exception rather than the rule (Cunha 2005). More research is therefore needed to further develop and extend this emerging concept, especially in the context of sustainability ventures who are committed to personal and social goals of resourcefulness. To date, however, bricolage has not been studied specifically among high potential sustainable ventures. This research seeks to develop an in depth understanding of the impact of internal and external constraints and their combinations on the mechanisms employed in bricolage behaviours in differing dynamic environments. The following research question was developed to investigate this: How do internal, external resource constraints (or their combinations) impact bricolage resource decisions in high potential sustainability ventures? ---------- Methodology/Key Propositions: 6 case studies will be developed utilizing survey data from the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) large-scale longitudinal study of new venture start-ups in Australia. Prior to commencing case studies, 6 scoping interviews were conducted with key stakeholders including industry members, established businesses and government to ensure practical relevance in case development. The venture is considered the unit of analysis with the key informant being the entrepreneur and other management team members where appropriate. Triangulation techniques are used in this research including semi-structured interviews, survey data, onsite visits and secondary documentation website analysis, resumes, and business plans. These 6 sustainability ventures have been selected based on different environmental dynamism conditions including a traditionally mature market (building industry) and a more dynamic, evolving industry (renewable energy/solar ventures). In evaluating multidisciplinary literature, we expect the following external constraints are critical including: technology constraints (seen through lock-in of incumbents existing technology), institutional regulation and standards, access to markets, knowledge and training to nascent and young venture bricolage processes. The case studies will investigate internal constraints including resource fungability, resource combination capabilities, translating complex science/engineering knowledge into salient, valuable market propositions, i.e. appropriate market outcomes, and leveraging relationships may further influence bricolage decisions. ---------- Results and Implications: Intended ventures have been identified within the CAUSEE sample and have agreed to participate and secondary data collection for triangulation purposes has already commenced. Data collection of the case studies commenced 27th of May 2009. Analysis is expected to be completed finalised by 25th September 2009. This paper will report on the pattern of resource constraints and its impact on bricolage behaviours: its subsequent impact on resource deployment within venture creation and venture growth. As such, this research extends the theory of bricolage through the systematic analysis of constraints on resource management processes in sustainability ventures. For practice, this research may assist in providing a better understanding of the resource requirements and processes needed for continued venture persistence and growth in sustainability ventures. In these times of economic uncertainty, a better understanding of the influence on constraints and bricolage: the interplay of behaviours, processes and outcomes may enable greater venture continuance and success.

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In this work, we investigate an alternative bootstrap approach based on a result of Ramsey [F.L. Ramsey, Characterization of the partial autocorrelation function, Ann. Statist. 2 (1974), pp. 1296-1301] and on the Durbin-Levinson algorithm to obtain a surrogate series from linear Gaussian processes with long range dependence. We compare this bootstrap method with other existing procedures in a wide Monte Carlo experiment by estimating, parametrically and semi-parametrically, the memory parameter d. We consider Gaussian and non-Gaussian processes to prove the robustness of the method to deviations from normality. The approach is also useful to estimate confidence intervals for the memory parameter d by improving the coverage level of the interval.

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Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists involved in the process modeling. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. Some systems have been developed to support collaborative process modeling, all of which use traditional 2D interfaces. We present an environment for collaborative process modeling, using 3D virtual environment technology. We make use of avatar instantiations of user ego centres, to allow for the spatial embodiment of the user with reference to the process model. We describe an innovative prototype collaborative process modeling approach, implemented as a modeling environment in Second Life. This approach leverages the use of virtual environments to provide user context for editing and collaborative exercises. We present a positive preliminary report on a case study, in which a test group modelled a business process using the system in Second Life.

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The value of business process models is dependent not only on the choice of graphical elements in the model, but also on their annotation with additional textual and graphical information. This research discusses the use of text and icons for labeling the graphical constructs in a process model. We use two established verb classification schemes to examine the choice of activity labels in process modeling practice. Based on our findings, we synthesize a set of twenty-five activity label categories. We propose a systematic approach for graphically representing these label categories through the use of graphical icons, such that the resulting process models are easier and more readily understandable by end users. Our findings contribute to an ongoing stream of research investigating the practice of process modeling and thereby contribute to the body of knowledge about conceptual modeling quality overall.

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In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.

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The role of intangible firm capabilities as a source of competitive advantage has come into prominence in marketing strategy literature, due to the Resource Based View. This paper applies the Resource Based View and hypothesizes that strategic flexibility and organisation learning, conceptualised as capabilities, positively effect e-business adoption and competitive advantage. Partial Lease Squares analysis suggest that theoretical constructs function as hypothesised and explain a significant variation on e-business adoption and competitive advantage. Firms adopting e-business should develop capabilities such as strategic flexibility and organisation learning and that vendor firms may segment their potential clients based on these capabilities.

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This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that the action selection mechanism of a member in a robot team can select an effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probabilistic view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried out to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.

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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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A persistent question in the development of models for macroeconomic policy analysis has been the relative role of economic theory and evidence in their construction. This paper looks at some popular strategies that involve setting up a theoretical or conceptual model (CM) which is transformed to match the data and then made operational for policy analysis. A dynamic general equilibrium model is constructed that is similar to standard CMs. After calibration to UK data it is used to examine the utility of formal econometric methods in assessing the match of the CM to the data and also to evaluate some standard model-building strategies. Keywords: Policy oriented economic modeling; Model evaluation; VAR models

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Our objective was to determine the factors that lead users to continue working with process modeling grammars after their initial adoption. We examined the explanatory power of three theoretical models of IT usage by applying them to two popular process modeling grammars. We found that a hybrid model of technology acceptance and expectation-confirmation best explained user intentions to continue using the grammars. We examined differences in the model results, and used them to provide three contributions. First, the study confirmed the applicability of IT usage models to the domain of process modeling. Second, we discovered that differences in continued usage intentions depended on the grammar type instead of the user characteristics. Third, we suggest implications and practice.

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The objective of this study was to investigate the factors that influence midlife women to make positive exercise and dietary changes. In late 2005 questionnaires were mailed to 866 women aged 51–66 years from rural and urban locations in Queensland, Australia and participating in Stage 2 of the Healthy Aging of Women Study. The questionnaires sought data on socio-demographics, body mass index (BMI), chronic health conditions, self-efficacy, exercise and dietary behavior change since age 40, and health-related quality of life. Five hundred and sixty four (69%) were completed and returned by early 2006. Data analysis comprised descriptive and bivariate statistics and structural equation modeling. The results showed that midlife is a significant time for women to make positive health behavior changes. Approximately one-third of the sample (34.6%) indicated that they had increased their exercise and around 60% had made an effort to eat more healthily since age 40. Modeling showed self-efficacy to be important in making both exercise and dietary changes. Although education appeared to influence self-efficacy in relation to exercise change, this was not the case for dietary change. The study has application for programs promoting healthy aging among women, and implies that those with low education, high BMI and poor mental health may need considerable support to improve their lifestyles.