386 resultados para Convergence conditionnelle
Resumo:
Convergence of pervasive technologies, techno-centric customers and the emergence of digitized channels, overabundance of user friendly retail applications are having a profound impact on retail experience, leading to the advent of ‘everywhere retailing’. With the rapid uptake of digital complimentary assets and smart mobile applications are revolutionizing the relationship of retailers with their customers and suppliers. Retail firms are increasingly investing substantial resources on dynamic Customer Relationship Management systems (D-CRM / U-CRM) to better engage with customers to sense and respond quickly (Agility of the firm) to their demands. However, unlike traditional CRM systems, engagement with U-CRM systems requires that firms be hyper sensitive to volatile customer needs and wants. Following the notions of firm agility, this study attempts to develop a framework to understand such unforeseen benefits and issues of U-CRM. This research-in-progress paper reports an a-priory framework including 62 U-CRM benefits derived through an archival analysis of literature.
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Cenozoic extension in western Mexico has been divided into two episodes separated by the change from convergence to oblique divergence at the plate boundary. The Gulf Extensional Province is thought to have started once subduction ended at ~12.5 Ma whereas early extension is classified as Basin and Range. Mid-Miocene volcanism of the Comondú group has been considered as a subduction-related arc, whereas post ~12.5 Ma volcanism would be extension-related. Our new integration of the continental onshore and offshore geology of the south-east Gulf region, backed by tens of Ar-Ar and U-Pb ages and geochemical studies, document an early-mid Miocene rifting and extension-related bimodal to andesitic magmatism prior to subduction termination. Between ~21 and 11 Ma a system of NNW-SSE high-angle extensional faults rifted the western side of the Sierra Madre Occidental (SMO) ignimbrite plateau. In Nayarit, rhyolitic domes and some basalts were emplaced along this extensional belt at 18-17 Ma. These rocks show strong antecrystic inheritance but an absence of Mesozoic and older xenocrysts, suggesting a genesis in the mid-upper crust triggered by extension-induced basaltic influx. In Sinaloa, large grabens were floored by huge dome complexes at ~21-17 Ma and filled by continental sediments with interlayered basalts dated at 15 Ma. Mid-Miocene volcanism, including the largely volcaniclastic Comondú strata in Baja California, was thus emplaced in rift basins and appears associated to decompression melting rather than subduction. Along the coast, flat-lying basaltic lava flows dated at 11-10 Ma are exposed just above the present sea level. Here crustal thickness is 25-20 Km, almost half that in the core of the SMO, implying significant lithosphere stretching before ~11 Ma. This mafic pulse, with relatively high Ti but still clear Nb-Ta negative spikes, may be related to the detachment of the lower part of the subducted slab, allowing asthenosphere to flow into parts of the mantle previously fluxed by subduction fluids. Very uniform OIB-like lavas appear in late Pliocene and Pleistocene, only 18 m.y. after the onset of rifting and ~9 m.y. after the end of subduction. Our study shows that rifting began much earlier than Late Miocene and progressively overwhelmed subduction in generating magmatism.
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Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.
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This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.
Resumo:
In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.
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This paper deals with the transformations that have occurred in news journalism worldwide in the early 21st century. I argue that they havebeen the most significant changes to the profession for 100 years, and the challenges facing the news media industry in responding to them are substantial, as are those facing journalism education. This argument is developed in relation to the crisis of the newspaper business model, and why social media, blogging and citizen journalism have not filled the gap left by the withdrawal of resources from traditional journalism. It also draws upon Wikileaks as a case study in debates about computational and data-driven journalism, and whether large-scale "leaks" of electronic documents may be the future of investigative journalism.
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This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.
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This report looks at opportunities in relation to what is either already available or starting to take off in Information and Communication Technology (ICT). ICT focuses on the entire system of information, communication, processes and knowledge within an organisation. It focuses on how technology can be implemented to serve the information and communication needs of people and organisations. An ICT system involves a combination of work practices, information, people and a range of technologies and applications organised to make the business or organisation fully functional and efficient, and to accomplish goals in an organisation. Our focus is on vocational, workbased education in New Zealand. It is not about eLearning, although we briefly touch on the topic. We provide a background on vocational education in New Zealand, cover what we consider to be key trends impacting workbased, vocational education and training (VET), and offer practical suggestions for leveraging better value from ICT initiatives across the main activities of an Industry Training Organisation (ITO). We use a learning value chain approach to demonstrate the main functions ITOs engage in and also use this approach as the basis for developing and prioritising an ICT strategy. Much of what we consider in this report is applicable to the wider tertiary education sector as it relates to life-long learning. We consider ICT as an enabler that: a) connects education businesses (all types including tertiary education institutions) to learners, their career decisions and their learning, and as well, b) enables those same businesses to run more efficiently. We suggest that these two sets of activities are considered as interconnected parts of the same education or training business ICT strategy.
Resumo:
Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.
Resumo:
An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.
Resumo:
Process modeling grammars are used to create scripts of a business domain that a process-aware information system is intended to support. A key grammatical construct of such grammars is known as a Gateway. A Gateway construct is used to describe scenarios in which the workflow of a process diverges or converges according to relevant conditions. Gateway constructs have been subjected to much academic discussion about their meaning, role and usefulness, and have been linked to both process-modeling errors and process-model understandability. This paper examines perceptual discriminability effects of Gateway constructs on an individual's abilities to interpret process models. We compare two ways of expressing two convergence and divergence patterns – Parallel Split and Simple Merge – implemented in a process modeling grammar. On the basis of an experiment with 98 students, we provide empirical evidence that Gateway constructs aid the interpretation of process models due to a perceptual discriminability effect, especially when models are complex. We discuss the emerging implications for research and practice, in terms of revisions to grammar specifications, guideline development and design choices in process modeling.
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In light of the high stakes of the deepwater horizon civil trial and the important precedent-setting role that the case will have on the assessment of future marine disasters, the methodologies underpinning the calculations of damage on both sides will be subjected to considerable scrutiny. Despite the importance of the case, however, there seems to be a pronounced lack of convergence about it in the academic literature. Contributions from scientific journals frequently make comparisons to the Ixtoc I oil spill off the coast of Mexico in 1979; the legal literature, by stark contrast, seems to be much more focused on the Exxon Valdez spill that occurred off the shores of Alaska in 1989. This paper accordingly calls for a more thorough consideration of other analogs beyond the Exxon Valdez spill—most notably, the Ixtoc I incident—in arriving at an assessment of the damage caused by the Deepwater Horizon disaster.
Resumo:
This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.
Resumo:
In many applications of active noise control (ANC), an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Comparative simulation results shown in this paper indicate effectiveness of the proposed method.
Resumo:
We propose a new active noise control (ANC) technique. The technique has a feedback structure to have a simple configuration in practical implementation. In this approach, the secondary path is modelled online to ensure convergence of the system as the secondary paths are practically time varying or non-linear. The proposed method consists of two steps: a noise controller which is based on a modified FxLMS algorithm, and a new variable step size (VSS) LMS algorithm which is used to adapt the modelling filter with the secondary path. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Eliminating continuous injection of the white noise increases the performance of the proposed method significantly and makes it more desirable for practical ANC systems. The computer simulations are presented to show the effectiveness of the proposed method.