523 resultados para due process


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A configurable process model describes a family of similar process models in a given domain. Such a model can be configured to obtain a specific process model that is subsequently used to handle individual cases, for instance, to process customer orders. Process configuration is notoriously difficult as there may be all kinds of interdependencies between configuration decisions.} In fact, an incorrect configuration may lead to behavioral issues such as deadlocks and livelocks. To address this problem, we present a novel verification approach inspired by the ``operating guidelines'' used for partner synthesis. We view the configuration process as an external service, and compute a characterization of all such services which meet particular requirements using the notion of configuration guideline. As a result, we can characterize all feasible configurations (i.\,e., configurations without behavioral problems) at design time, instead of repeatedly checking each individual configuration while configuring a process model.

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Windscape is a graphic work produced from information gathered in the field by the author. A number of measurement methods were employed including: Real Tine Kinematic Global Positioning System survey (RTKGPS), still photography, plant distribution studies and handheld GPS survey. This creative work is one outcome of the author’s research into a design methodology wherein the designer conducts their own measurements and then produces their own maps of sites. Windscape is a test of the hypothesis that such maps have greater relevance to the design process due to the manner in which they are created (site based research) and the information they depict, namely the relationships between landscape processes and structures.

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Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time.

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Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

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Principal Topic : Nascent entrepreneurship has drawn the attention of scholars in the last few years (Davidsson, 2006, Wagner, 2004). However, most studies have asked why firms are created focussing on questions such as what are the characteristics (Delmar and Davidsson, 2000) and motivations (Carter, Gartner, Shaver & Reynolds, 2004) of nascent entrepreneurs, or what are the success factors in venture creation (Davidsson & Honig; 2003; Delmar and Shane, 2004). In contrast, the question of how companies emerge is still in its infancy. On a theoretical side, effectuation, developed by Sarasvathy (2001) offers one view of the strategies that may be at work during the venture creation process. Causation, the theorized inverse to effectuation, may be described as a rational reasoning method to create a company. After a comprehensive market analysis to discover opportunities, the entrepreneur will select the alternative with the higher expected return and implement it through the use of a business plan. In contrast, effectuation suggests that the future entrepreneur will develop her new venture in a more iterative way by selecting possibilities through flexibility and interaction with the market, affordability of loss of resources and time invested, development of pre-commitments and alliances from stakeholders. Another contrasting point is that causation is ''goal driven'' while an effectual approach is ''mean driven'' (Sarasvathy, 2001) One of the predictions of effectuation theory is effectuation is more likely to be used by entrepreneurs early in the venture creation process (Sarasvathy, 2001). However, this temporal aspect and the impact of the effectuation strategy on the venture outcomes has so far not been systematically and empirically tested on large samples. The reason behind this research gap is twofold. Firstly, few studies collect longitudinal data on emerging ventures at an early enough stage of development to avoid severe survivor bias. Second, the studies that collect such data have not included validated measures of effectuation. The research we are conducting attempts to partially fill this gap by combining an empirical investigation on a large sample of nascent and young firms with the effectuation/causation continuum as a basis (Sarasvathy, 2001). The objectives are to understand the strategies used by the firms during the creation process and measure their impacts on the firm outcomes. Methodology/Key Propositions : This study draws its data from the first wave of the CAUSEE project where 28,383 Australian households were randomly contacted by phone using a specific methodology to capture emerging firms (Davidsson, Steffens, Gordon, Reynolds, 2008). This screening led to the identification of 594 nascent ventures (i.e., firms that are not operating yet) and 514 young firms (i.e., firms that have started operating from 2004) that were willing to participate in the study. Comprehensive phone interviews were conducted with these 1108 ventures. In a likewise comprehensive follow-up 12 months later, 80% of the eligible cases completed the interview. The questionnaire contains specific sections designed to distinguish effectual and causal processes, innovation, gestation activities, business idea changes and ventures outcomes. The effectuation questions are based on the components of effectuation strategy as described by Sarasvathy (2001) namely: flexibility, affordable loss and pre-commitment from stakeholders. Results from two rounds of pre-testing informed the design of the instrument included in the main survey. The first two waves of data have will be used to test and compare the use of effectuation in the venture creation process. To increase the robustness of the results, temporal use of effectuation will be tested both directly and indirectly. 1. By comparing the use of effectuation in nascent and young firms from wave 1 to 2, we will be able to find out how effectuation is affected by time over a 12-month duration and if the stage of venture development has an impact on its use. 2. By comparing nascent ventures early in the creation process versus nascent ventures late in the creation process. Early versus late can be determined with the help of time-stamped gestation activity questions included in the survey. This will help us to determine the change on a small time scale during the creation phase of the venture. 3. By comparing nascent firms to young (already operational) firms. 4. By comparing young firms becoming operational in 2006 with those first becoming operational in 2004. Results and Implications : Wave 1 and 2 data have been completed and wave 2 is currently being checked and 'cleaned'. Analysis work will commence in September, 2009. This paper is expected to contribute to the body of knowledge on effectuation by measuring quantitatively its use and impact on nascent and young firms activities at different stages of their development. In addition, this study will also increase the understanding of the venture creation process by comparing over time nascent and young firms from a large sample of randomly selected ventures. We acknowledge the results from this study will be preliminary and will have to be interpreted with caution as the changes identified may be due to several factors and may not only be attributed to the use/not use of effectuation. Meanwhile, we believe that this study is important to the field of entrepreneurship as it provides some much needed insights on the processes used by nascent and young firms during their creation and early operating stages.

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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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Process models provide visual support for analyzing and improving complex organizational processes. In this paper, we discuss differences of process modeling languages using cognitive effectiveness considerations, to make statements about the ease of use and quality of user experience. Aspects of cognitive effectiveness are of importance for learning a modeling language, creating models, and understanding models. We identify the criteria representational clarity, perceptual discriminability, perceptual immediacy, visual expressiveness, and graphic parsimony to compare and assess the cognitive effectiveness of different modeling languages. We apply these criteria in an analysis of the routing elements of UML Activity Diagrams, YAWL, BPMN, and EPCs, to uncover their relative strengths and weaknesses from a quality of user experience perspective. We draw conclusions that are relevant to the usability of these languages in business process modeling projects.

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Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies.

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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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Student learning research literature has shown that students' learning approaches are influenced by the learning context (Evans, Kirby, & Fabrigar, 2003). Of the many contextual factors, assessment has been found to have the most important influence on the way students go about learning. For example, assessment that is perceived to required a low level of cognitive abilities will more likely elicit a learning approach that concentrate on reproductive learning activities. Moreover, assessment demand will also interact with learning approach to determine academic performance. In this paper an assessment specific model of learning comprising presage, process and product variables (Biggs, 2001) was proposed and tested against data obtained from a sample of introductory economics students (n=434). The model developed was used to empirically investigate the influence of learning inputs and learning approaches on academic performances across assessment types (essay assignment, multiple choice question exam and exam essay). By including learning approaches in the learning model, the mechanism through which learning inputs determine academic performance was examined. Methodological limitations of the study will also be discussed.

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Over the past decade privatised capital city airports in Australia have planned developed a range of non aviation commercial and retail land uses on airport land. Many surrounding municipalities consider this development in conflict with existing regional land use planning. Conversely airport operators are alarmed at continued urban consolidation and encroachment of incompatible regional development. Land use planning within and surrounding Australian capital city airports does not support compatible and integrated land use. It is currently a fragmented process due to: 1) current legislative and policy frameworks; 2) competing stakeholder priorities and interests; and 3) inadequate coordination and disjointed decision-making. This paper will examine privatised Australian airport development and consider three case studies to detail the context of airport and regional land use planning. A series of stakeholder workshops have served to inform the procedural dynamics and relationships between airport and regional decision-making. This exploratory research will assist in informing the knowledge gaps between aviation, airport development and broader urban land use policy. This paper will provide recommendations to enhance approaches to land use planning for airports and adjacent metropolitan regions in Australia and overseas.

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As a result of the growing adoption of Business Process Management (BPM) technology different stakeholders need to understand and agree upon the process models that are used to configure BPM systems. However, BPM users have problems dealing with the complexity of such models. Therefore, the challenge is to improve the comprehension of process models. While a substantial amount of literature is devoted to this topic, there is no overview of the various mechanisms that exist to deal with managing complexity in (large) process models. It is thus hard to obtain comparative insight into the degree of support offered for various complexity reducing mechanisms by state-of-the-art languages and tools. This paper focuses on complexity reduction mechanisms that affect the abstract syntax of a process model, i.e. the structure of a process model. These mechanisms are captured as patterns, so that they can be described in their most general form and in a language- and tool-independent manner. The paper concludes with a comparative overview of the degree of support for these patterns offered by state-of-the-art languages and language implementations.

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Purpose: As part of a comprehensive research study looking at implementing PPPs, interviews with experienced researchers were conducted to realize their views on private sector involvement in public works projects. Design / methodology / approach: Amongst these interviews, five were launched with academics from Hong Kong and Australia, and two were conducted with Legislative Councillors of the Hong Kong Special Administration Region (HKSAR) government. Findings: The interview findings show that both Hong Kong and Australian interviewees had previously conducted some kind of research in the field of PPP. The interviewees highlighted that “Different risk profiles” and “Private sector more innovative / efficient” were the main differences between projects that were procured by PPP and traditionally. Other differences include risk transfer. In a PPP arrangement the public sector passes on a substantial amount of the project risks to the private sector, whereas in a traditional case the public sector would take the largest responsibility in bearing these risks. Another common feature of the private sector is that they tend to be more efficient and innovative when compared to the public sector hence their expertise is often reflected in PPP projects. The interviewees agreed that the key performance indicators for PPP projects were unique depending on the individual project. The critical success factors mentioned by both groups of interviewees included “Transparent process”, “Project dependent” and “Market need”. Due to the fact that PPP projects tend to be large scaled costly projects, adequate transparency in the process is necessary in order to demonstrate that a fair selection and tendering process is conducted. A market need for the project is also important to ensure that the project will be financially secure and that the private sector can make a reasonable profit to cover their project expenditure. Originality / value: The findings from this study have enabled a comparative analysis between the views of researchers in two completely different jurisdictions. With the growing popularity to implement PPP projects, it is believed that the results presented in this paper would be of interest to the industry at large.

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It is now well known that pesticide spraying by farmers has an adverse impact on their health. This is especially so in developing countries where pesticide spraying is undertaken manually. The estimated health costs are large. Studies to date have examined farmers’ exposure to pesticides, the costs of ill-health and their determinants based on information provided by farmers. Hence, some doubt has been cast on the reliability of such studies. In this study, we rectify this situation by conducting surveys among two groups of farmers. Farmers who perceive that their ill-health is due to exposure to pesticides and obtained treatment and farmers whose ill-health have been diagnosed by doctors and who have been treated in hospital for exposure to pesticides. In the paper, cost comparisons between the two groups of farmers are made. Furthermore, regression analysis of the determinants of health costs show that the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day are the most important determinants of medical costs for both samples. The results have important policy implications.

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Increased industrialisation has brought to the forefront the susceptibility of concrete columns in both buildings and bridges to vehicle impacts. Accurate vulnerability assessments are crucial in the design process due to possible catastrophic nature of the failures that can cause. This paper reports on research undertaken to investigate the impact capacity of the columns of low to medium raised building designed according to Australian Standards. Numerical simulation techniques were used in the process and validation was done by using experimental results published in the literature. The investigation thus far has confirmed that vulnerability of typical columns in five story buildings located in urban areas to medium velocity car impacts and hence these columns need to be re-designed (if possible) or retrofitted. In addition, accuracy of the simplified method presented in EN 1991 to quantify the impact damage was scrutinised. A simplified concept to assess the damage due to all collisions modes was introduced. The research information will be extended to generate a common data base to assess the vulnerability of columns in urban areas against new generation of vehicles.