9 resultados para High level architecture

em Aston University Research Archive


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We address the question of how to obtain effective fusion of identification information such that it is robust to the quality of this information. As well as technical issues data fusion is encumbered with a collection of (potentially confusing) practical considerations. These considerations are described during the early chapters in which a framework for data fusion is developed. Following this process of diversification it becomes clear that the original question is not well posed and requires more precise specification. We use the framework to focus on some of the technical issues relevant to the question being addressed. We show that fusion of hard decisions through use of an adaptive version of the maximum a posteriori decision rule yields acceptable performance. Better performance is possible using probability level fusion as long as the probabilities are accurate. Of particular interest is the prevalence of overconfidence and the effect it has on fused performance. The production of accurate probabilities from poor quality data forms the latter part of the thesis. Two approaches are taken. Firstly the probabilities may be moderated at source (either analytically or numerically). Secondly, the probabilities may be transformed at the fusion centre. In each case an improvement in fused performance is demonstrated. We therefore conclude that in order to obtain robust fusion care should be taken to model the probabilities accurately; either at the source or centrally.

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THE PURPOSE OF THIS ARTICLE is two-fold, first to provide a general overview of two of the main cognitive neuroscientific techniques available, specifically functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS); and secondly to apply these techniques to elaborate a discussion of an aspect of higher level vision, namely implied motion, that is the perception of movement from a static image.

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Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.

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Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

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Software architecture plays an essential role in the high level description of a system design, where the structure and communication are emphasized. Despite its importance in the software engineering process, the lack of formal description and automated verification hinders the development of good software architecture models. In this paper, we present an approach to support the rigorous design and verification of software architecture models using the semantic web technology. We view software architecture models as ontology representations, where their structures and communication constraints are captured by the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). Specific configurations on the design are represented as concrete instances of the ontology, to which their structures and dynamic behaviors must conform. Furthermore, ontology reasoning tools can be applied to perform various automated verification on the design to ensure correctness, such as consistency checking, style recognition, and behavioral inference.

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This thesis explores translating well-written sequential programs in a subset of the Eiffel programming language - without syntactic or semantic extensions - into parallelised programs for execution on a distributed architecture. The main focus is on constructing two object-oriented models: a theoretical self-contained model of concurrency which enables a simplified second model for implementing the compiling process. There is a further presentation of principles that, if followed, maximise the potential levels of parallelism. Model of Concurrency. The concurrency model is designed to be a straightforward target for mapping sequential programs onto, thus making them parallel. It aids the compilation process by providing a high level of abstraction, including a useful model of parallel behaviour which enables easy incorporation of message interchange, locking, and synchronization of objects. Further, the model is sufficient such that a compiler can and has been practically built. Model of Compilation. The compilation-model's structure is based upon an object-oriented view of grammar descriptions and capitalises on both a recursive-descent style of processing and abstract syntax trees to perform the parsing. A composite-object view with an attribute grammar style of processing is used to extract sufficient semantic information for the parallelisation (i.e. code-generation) phase. Programming Principles. The set of principles presented are based upon information hiding, sharing and containment of objects and the dividing up of methods on the basis of a command/query division. When followed, the level of potential parallelism within the presented concurrency model is maximised. Further, these principles naturally arise from good programming practice. Summary. In summary this thesis shows that it is possible to compile well-written programs, written in a subset of Eiffel, into parallel programs without any syntactic additions or semantic alterations to Eiffel: i.e. no parallel primitives are added, and the parallel program is modelled to execute with equivalent semantics to the sequential version. If the programming principles are followed, a parallelised program achieves the maximum level of potential parallelisation within the concurrency model.

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There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture.The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability.

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Human Resource (HR) systems and practices generally referred to as High Performance Work Practices (HPWPs), (Huselid, 1995) (sometimes termed High Commitment Work Practices or High Involvement Work Practices) have attracted much research attention in past decades. Although many conceptualizations of the construct have been proposed, there is general agreement that HPWPs encompass a bundle or set of HR practices including sophisticated staffing, intensive training and development, incentive-based compensation, performance management, initiatives aimed at increasing employee participation and involvement, job safety and security, and work design (e.g. Pfeffer, 1998). It is argued that these practices either directly and indirectly influence the extent to which employees’ knowledge, skills, abilities, and other characteristics are utilized in the organization. Research spanning nearly 20 years has provided considerable empirical evidence for relationships between HPWPs and various measures of performance including increased productivity, improved customer service, and reduced turnover (e.g. Guthrie, 2001; Belt & Giles, 2009). With the exception of a few papers (e.g., Laursen &Foss, 2003), this literature appears to lack focus on how HPWPs influence or foster more innovative-related attitudes and behaviours, extra role behaviors, and performance. This situation exists despite the vast evidence demonstrating the importance of innovation, proactivity, and creativity in its various forms to individual, group, and organizational performance outcomes. Several pertinent issues arise when considering HPWPs and their relationship to innovation and performance outcomes. At a broad level is the issue of which HPWPs are related to which innovation-related variables. Another issue not well identified in research relates to employees’ perceptions of HPWPs: does an employee actually perceive the HPWP –outcomes relationship? No matter how well HPWPs are designed, if they are not perceived and experienced by employees to be effective or worthwhile then their likely success in achieving positive outcomes is limited. At another level, research needs to consider the mechanisms through which HPWPs influence –innovation and performance. The research question here relates to what possible mediating variables are important to the success or failure of HPWPs in impacting innovative behaviours and attitudes and what are the potential process considerations? These questions call for theory refinement and the development of more comprehensive models of the HPWP-innovation/performance relationship that include intermediate linkages and boundary conditions (Ferris, Hochwarter, Buckley, Harrell-Cook, & Frink, 1999). While there are many calls for this type of research to be made a high priority, to date, researchers have made few inroads into answering these questions. This symposium brings together researchers from Australia, Europe, Asia and Africa to examine these various questions relating to the HPWP-innovation-performance relationship. Each paper discusses a HPWP and potential variables that can facilitate or hinder the effects of these practices on innovation- and performance- related outcomes. The first paper by Johnston and Becker explores the HPWPs in relation to work design in a disaster response organization that shifts quickly from business as usual to rapid response. The researchers examine how the enactment of the organizational response is devolved to groups and individuals. Moreover, they assess motivational characteristics that exist in dual work designs (normal operations and periods of disaster activation) and the implications for innovation. The second paper by Jørgensen reports the results of an investigation into training and development practices and innovative work behaviors (IWBs) in Danish organizations. Research on how to design and implement training and development initiatives to support IWBs and innovation in general is surprisingly scant and often vague. This research investigates the mechanisms by which training and development initiatives influence employee behaviors associated with innovation, and provides insights into how training and development can be used effectively by firms to attract and retain valuable human capital in knowledge-intensive firms. The next two papers in this symposium consider the role of employee perceptions of HPWPs and their relationships to innovation-related variables and performance. First, Bish and Newton examine perceptions of the characteristics and awareness of occupational health and safety (OHS) practices and their relationship to individual level adaptability and proactivity in an Australian public service organization. The authors explore the role of perceived supportive and visionary leadership and its impact on the OHS policy-adaptability/proactivity relationship. The study highlights the positive main effects of awareness and characteristics of OHS polices, and supportive and visionary leadership on individual adaptability and proactivity. It also highlights the important moderating effects of leadership in the OHS policy-adaptability/proactivity relationship. Okhawere and Davis present a conceptual model developed for a Nigerian study in the safety-critical oil and gas industry that takes a multi-level approach to the HPWP-safety relationship. Adopting a social exchange perspective, they propose that at the organizational level, organizational climate for safety mediates the relationship between enacted HPWS’s and organizational safety performance (prescribed and extra role performance). At the individual level, the experience of HPWP impacts on individual behaviors and attitudes in organizations, here operationalized as safety knowledge, skills and motivation, and these influence individual safety performance. However these latter relationships are moderated by organizational climate for safety. A positive organizational climate for safety strengthens the relationship between individual safety behaviors and attitudes and individual-level safety performance, therefore suggesting a cross-level boundary condition. The model includes both safety performance (behaviors) and organizational level safety outcomes, operationalized as accidents, injuries, and fatalities. The final paper of this symposium by Zhang and Liu explores leader development and relationship between transformational leadership and employee creativity and innovation in China. The authors further develop a model that incorporates the effects of extrinsic motivation (pay for performance: PFP) and employee collectivism in the leader-employee creativity relationship. The papers’ contributions include the incorporation of a PFP effect on creativity as moderator, rather than predictor in most studies; the exploration of the PFP effect from both fairness and strength perspectives; the advancement of knowledge on the impact of collectivism on the leader- employee creativity link. Last, this is the first study to examine three-way interactional effects among leader-member exchange (LMX), PFP and collectivism, thus, enriches our understanding of promoting employee creativity. In conclusion, this symposium draws upon the findings of four empirical studies and one conceptual study to provide an insight into understanding how different variables facilitate or potentially hinder the influence various HPWPs on innovation and performance. We will propose a number of questions for further consideration and discussion. The symposium will address the Conference Theme of ‘Capitalism in Question' by highlighting how HPWPs can promote financial health and performance of organizations while maintaining a high level of regard and respect for employees and organizational stakeholders. Furthermore, the focus on different countries and cultures explores the overall research question in relation to different modes or stages of development of capitalism.

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Some organizations end up reimplementing the same class of business process over and over: an "administrative process", which consists of managing a form through several states and involving various roles in the organization. This results in wasted time that could be dedicated to better understanding the process or dealing with the fine details that are specific to the process. Existing virtual office solutions require specific training and infrastructure andmay result in vendor lock-in. In this paper, we propose using a high-level domain-specific language (AdminDSL) to describe the administrative process and a separate code generator targeting a standard web framework. We have implemented the approach using Xtext, EGL and the Django web framework, and we illustrate it through two case studies: a synthetic examination process which illustrates the architecture of the generated code, and a real-world workplace survey process that identified several future avenues for improvement.