63 resultados para Dynamic systems theory
em Deakin Research Online - Australia
Resumo:
Two of the most commonly used classifications in IS research are the factor approach and the process approach. While many studies of IS implementation are undertaken using a factor approach, little research so far examines the process of e-commerce implementation, especially in relation to the implementation of e-commerce in business-to-business (B2B) relationships. A holistic understanding of implementation which combines both the factor and process approaches using a case study method, is suggested as particularly suitable because of its ability to capture the reality of e-commerce implementation in an organisation's natural environment and in much greater detail than is possible using one of these approaches alone. In this paper, therefore, we endeavour to contribute to what we perceive as a gap in the body of theory surrounding the implementation process in the business-to-business e-commerce literature. We describe the findings of multiple case studies involving ten major Australian e-commerce initiators. In addition to confirming our earlier finding of the importance of non-technical factors for the success of the implementation process we also present, through our case studies, the various management and business issues associated with the success or failure of B2B e-commerce implementation.
Resumo:
This thesis provides a unified and comprehensive treatment of the fuzzy neural networks as the intelligent controllers. This work has been motivated by a need to develop the solid control methodologies capable of coping with the complexity, the nonlinearity, the interactions, and the time variance of the processes under control. In addition, the dynamic behavior of such processes is strongly influenced by the disturbances and the noise, and such processes are characterized by a large degree of uncertainty. Therefore, it is important to integrate an intelligent component to increase the control system ability to extract the functional relationships from the process and to change such relationships to improve the control precision, that is, to display the learning and the reasoning abilities. The objective of this thesis was to develop a self-organizing learning controller for above processes by using a combination of the fuzzy logic and the neural networks. An on-line, direct fuzzy neural controller using the process input-output measurement data and the reference model with both structural and parameter tuning has been developed to fulfill the above objective. A number of practical issues were considered. This includes the dynamic construction of the controller in order to alleviate the bias/variance dilemma, the universal approximation property, and the requirements of the locality and the linearity in the parameters. Several important issues in the intelligent control were also considered such as the overall control scheme, the requirement of the persistency of excitation and the bounded learning rates of the controller for the overall closed loop stability. Other important issues considered in this thesis include the dependence of the generalization ability and the optimization methods on the data distribution, and the requirements for the on-line learning and the feedback structure of the controller. Fuzzy inference specific issues such as the influence of the choice of the defuzzification method, T-norm operator and the membership function on the overall performance of the controller were also discussed. In addition, the e-completeness requirement and the use of the fuzzy similarity measure were also investigated. Main emphasis of the thesis has been on the applications to the real-world problems such as the industrial process control. The applicability of the proposed method has been demonstrated through the empirical studies on several real-world control problems of industrial complexity. This includes the temperature and the number-average molecular weight control in the continuous stirred tank polymerization reactor, and the torsional vibration, the eccentricity, the hardness and the thickness control in the cold rolling mills. Compared to the traditional linear controllers and the dynamically constructed neural network, the proposed fuzzy neural controller shows the highest promise as an effective approach to such nonlinear multi-variable control problems with the strong influence of the disturbances and the noise on the dynamic process behavior. In addition, the applicability of the proposed method beyond the strictly control area has also been investigated, in particular to the data mining and the knowledge elicitation. When compared to the decision tree method and the pruned neural network method for the data mining, the proposed fuzzy neural network is able to achieve a comparable accuracy with a more compact set of rules. In addition, the performance of the proposed fuzzy neural network is much better for the classes with the low occurrences in the data set compared to the decision tree method. Thus, the proposed fuzzy neural network may be very useful in situations where the important information is contained in a small fraction of the available data.
Resumo:
This paper focuses on the problem of tracking people through occlusions by scene objects. Rather than relying on models of the scene to predict when occlusions will occur as other researchers have done, this paper proposes a linear dynamic system that switches between two alternatives of the position measurement in order to handle occlusions as they occur. The filter automatically switches between a foot-based measure of position (assuming z = Q) to a head-based position measure (given the person's height) when an occlusion of the person's lower body occurs. No knowledge of the scene or its occluding objects is used. Unlike similar research [2, 14], the approach does not assume a fixed height for people and so is able to track humans through occlusions even when they change height during the occlusion. The approach is evaluated on three furnished scenes containing tables, chairs, desks and partitions. Occlusions range from occlusions of legs, occlusions whilst being seated and near-total occlusions where only the person's head is visible. Results show that the approach provides a significant reduction in false-positive tracks in a multi-camera environment, and more than halves the number of lost tracks in single monocular camera views.
Resumo:
Social networking has recently flourished in popularity through the use of social websites. Pervasive computing resources have allowed people stay well-connected to each other through access to social networking resources. We take the position that utilizing information produced by relationships within social networks can assist in the establishment of trust for other pervasive computing applications. Furthermore, we describe how such a system can augment a sensor infrastructure used for event observation with information from mobile sensors (ie, mobile phones with cameras) controlled by potentially untrusted third parties.
Resumo:
Issue addressed: Our Watch led a complex 12-month evaluation of a whole school approach to Respectful Relationships Education (RRE) implemented in 19 schools. RRE is an emerging field aimed at preventing gender-based violence. This paper will illustrate how from an implementation science perspective, the evaluation was a critical element in the change process at both a school and policy level. Methods: Using several conceptual approaches from systems science, the evaluation sought to examine how the multiple systems layers – student, teacher, school, community and government – interacted and influenced each other. A distinguishing feature of the evaluation included ‘feedback loops’; that is, evaluation data was provided to participants as it became available. Evaluation tools included a combination of standardised surveys (with pre- and post-intervention data provided to schools via individualised reports), reflection tools, regular reflection interviews and summative focus groups. Results: Data was shared during implementation with project staff, department staff and schools to support continuous improvement at these multiple systems levels. In complex settings, implementation can vary according to context; and the impact of evaluation processes, tools and findings differed across the schools. Interviews and focus groups conducted at the end of the project illustrated which of these methods were instrumental in motivating change and engaging stakeholders at both a school and departmental level and why. Conclusion: The evaluation methods were a critical component of the pilot’s approach, helping to shape implementation through data feedback loops and reflective practice for ongoing, responsive and continuous improvement. Future health promotion research on complex interventions needs to examine how the evaluation itself is influencing implementation. So what? The pilot has demonstrated that the evaluation, including feedback loops to inform project activity, were an asset to implementation. This has implications for other health promotion activities, where evaluation tools could be utilised to enhance, rather than simply measure, an intervention. The findings are relevant to a range of health promotion research activities because they demonstrate the importance of meta-evaluation techniques that seek to understand how the evaluation itself was influencing implementation and outcomes.
Resumo:
Introduction: A nonlinear dynamic systems model has previously been proposed to explain pacing strategies employed during exercise.
Purpose: This study was conducted to examine the pacing strategies used under varying conditions during the cycle phase of an Ironman triathlon.
Methods: The bicycles of six well-trained male triathletes were equipped with SRM power meters set to record power output, cadence, speed, and heart rate. The flat, three-lap, out-and-back cycle course, coupled with relatively consistent wind conditions (17-30 km·h-1), enabled comparisons to be made between three consecutive 60-km laps and relative wind direction (headwind vs tailwind).
Results: Participants finished the cycle phase (180 km) with consistently fast performance times (5 h, 11 ± 2 min; top 10% of all finishers). Average power output (239 ± 25 to 203 ± 20 W), cadence (89 ± 6 to 82 ± 8 rpm), and speed (36.5 ± 0.8 to 33.1 ± 0.8 km·h-1) all significantly decreased with increasing number of laps (P < 0.05). These variables, however, were not significantly different between headwind and tailwind sections. The deviation (SD) in power output and cadence did not change with increasing number of laps; however, the deviations in torque (6.8 ± 1.6 and 5.8 ± 1.3 N·m) and speed (2.1 ± 0.5 and 1.6 ± 0.3 km·h-1) were significantly greater under headwind compared with tailwind conditions, respectively. The median power frequency tended to be lower in headwind (0.0480 ± 0.0083) compared with tailwind (0.0531 ± 0.0101) sections.
Conclusion: These data show evidence that a nonlinear dynamic pacing strategy is used by well-trained triathletes throughout various segments and conditions of the Ironman cycle phase. Moreover, an increased variation in torque and speed was found in the headwind versus the tailwind condition.
Resumo:
Previous research that addressed determents of employer satisfaction with employees with a disability (EWDs) mainly targeted employers’ perceptions of workplace performance. This thesis used quantitative and qualitative approaches to examine perspectives of employers and disability employment service providers (DESPs) on the complex nature of employer satisfaction with EWDs within an ecological paradigm. Three studies were undertaken. The first analysed questionnaire ratings for 656 employers of workplace performance of EWDs. Analyses found: (1) employers rated EWDs lower than non-disabled employees (NDEs) on employer satisfaction and work performance; (2) determinants of employer satisfaction differed between EWDs and NDEs; (3) employers were more satisfied with EWDs than NDEs in relation to work performance; (4) lower comparative ratings on employer satisfaction for EWDs influenced future employment intentions toward people with a disability; (5) employers’ perceptions of job-match affected ratings on employer satisfaction and performance; (6) effects of job-match on employer satisfaction were direct and indirect, through work performance; and (7) variables representing job-match were relatively more important to employers’ decisions to hire and retain a person with a disability than variables representing Social Concerns and employer/management items. A theoretical model that depicted the influence of processes (job-match) and outcomes (work performance) on employer satisfaction with EWDs was supported. The second study analysed questionnaire ratings from 36 non-employers of EWDs. Findings indicated very similar responses between employers and non-employers of EWDs on experiences related to employer satisfaction with NDEs. Views about the relative importance of variable related to hiring and retaining a person with a disability suggested that generalising findings from the first study to all employers was reasonable. The third study analysed data from interviews with 50 employers and 40 DESPs; and questionnaire responses for 56 DESPs and 36 non-employers of EWDs. This study validated the importance of job-match to successful employment outcomes; suggesting DESPs were undervaluing their services to the employers. The study also showed that Bronfenbrenner’s Ecological Systems Theory provided a relevant framework with which to interpret complex information from different stakeholders, important to understanding employer satisfaction. In summary, employer satisfaction was shown to be a relative concept that varied with referent, and a developmental phenomenon that was influences by many factors operating and interacting at a number of ecological levels. Policies and practices to promote employer satisfaction with EWDs need co-ordinated approaches that recognise the influence of contexts internal and external to the workplace and the dynamic nature and interrelationships of characteristics within these contexts.
Resumo:
A new sliding mode control technique for a class of SISO dynamic systems is presented in this chapter. It is seen that the stability status of the closed-loop system is first checked, based on the approximation of the most recent information of the first-order derivative of the Lyapunov function of the closed-loop system, an intelligent sliding mode controller can then be designed with the following intelligent features: (i) If the closed-loop system is stable, the correction term in the controller will continuously adjust control signal to drive the closed-loop trajectory to reach the sliding mode surface in a finite time and the desired closed-loop dynamics with the zero-error convergence can then be achieved on the sliding mode surface. (ii) If, however, the closed-loop system is unstable, the correction term is capable of modifying the control signal to continuously reduce the value of the derivative of the Lyapunov function from the positive to the negative and then drives the closed-loop trajectory to reach the sliding mode surface and ensures that the desired closed-loop dynamics can be obtained on the sliding mode surface. The main advantages of this new sliding mode control technique over the conventional one are that no chattering occurs in the sliding mode control system because of the recursive learning control structure; the system uncertainties are embedded in the Lipschitz-like condition and thus, no priori information on the upper and/or the lower bounds of the unknown system parameters and uncertain system dynamics is required for the controller design; the zero-error convergence can be achieved after the closed-loop dynamics reaches the sliding mode surface and remains on it. The performance for controlling a third-order linear system is evaluated in the simulation section to show the effectiveness and efficiency of the new sliding mode control technique.
Resumo:
In this theoretical paper, we introduce and describe a model, and demonstrate its origins from the disciplines of Enterprise Architecture, cybernetics and systems theory. We use cybernetic thinking to develop a ‘Co-evolution Path Model’ that describes how enterprises as complex systems co-evolve with their complex environments. The model re-interprets Stafford Beer’s Viable System Model, and also uses the theorem of the ‘good regulator’ of Conant and Ashby, exemplifying how various complexity management theories could be synthesised into a cybernetic theory of Enterprise Architecture, using concepts from the generalisation of EA frameworks.
Resumo:
Analysis of airport and air cargo operations is commonly performed in isolation, sharing only simple information such as flight schedules. Systems theory and Systems methodology can enhance such analysis by considering all aspects of air operations. It provides the decision-maker with an improved understanding of the implication of policy decisions, resource allocations and infrastructure investment strategies, through the capture of emergent behaviours and interdependencies. For example, the term airport operations, initially reminds us of the thought of passengers being transported by aircraft. Deeper thinking would identify activities that affect passenger operations, such as baggage handling systems, aircraft maintenance, and passenger security. In reality, airport operations consist of numerous aspects, including; concourses, runways, airlines, fuel depots, cargo terminal operators, retail, parking, cleaning, catering and many interacting people including travellers, service providers and visitors. For the airport to function effectively, these numerous systems must work together. This talk will focus on new tools and methodologies that are required for model development and analysis. It will then focus on modelling, simulation and analysis of the airport operations, providing greater understanding of airport operation with an emphasis towards security.
Resumo:
In this paper, the problem of global finite-time stabilisation by output feedback is considered for a class of stochastic nonlinear systems. First, based on homogeneous systems theory and the adding a power integrator technique, a homogeneous reduced order observer and control law are constructed in a recursive manner for the nominal system. Then, the homogeneous domination approach is used to deal with the nonlinearities in drift and diffusion terms; it is shown that the proposed output-feedback control law can guarantee that the closed-loop system is global finite-time stable in probability. Finally, simulation examples are carried out to demonstrate the effectiveness of the proposed control scheme.
Resumo:
Ordinary differential equations are used for modelling a wide range of dynamic systems. Even though there are many graphical software applications for this purpose, a fully customised solution for all problems is code-level programming of the model and solver. In this project, a free and open source C++ framework is designed to facilitate modelling in native code environment and fulfill the common simulation needs of control and many other engineering and science applications. The solvers of this project are obtained from ODEINT and specialised for Armadillo matrix library to provide an easy syntax and a fast execution. The solver code is minimised and its modification for users have become easier. There are several features added to the solvers such as controlling maximum step size, informing the solver about sudden input change and forcing custom times into the results and calling a custom method at these points. The comfort of the model designer, code readability, extendibility and model isolation have been considered in the structure of this framework. The application manages the output results, exporting and plotting them. Modifying the model has become more practical and a portion of corresponding codes are updated automatically. A set of libraries is provided for generation of output figures, matrix hashing, control system functions, profiling, etc. In this paper, an example of using this framework for a classical washout filter model is explained.