917 resultados para Identification systems


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This paper investigates the impact of carrier frequency offset (CFO) on Single Carrier wireless communication systems with Frequency Domain Equalization (SC-FDE). We show that CFO in SC-FDE systems causes irrecoverable channel estimation error, which leads to inter-symbol-interference (ISI). The impact of CFO on SC-FDE and OFDM is compared in the presence of CFO and channel estimation errors. Closed form expressions of signal to interference and noise ratio (SINR) are derived for both systems, and verified by simulation results. We find that when channel estimation errors are considered, SC-FDE is similarly or even more sensitive to CFO, compared to OFDM. In particular, in SC-FDE systems, CFO mainly deteriorates the system performance via degrading the channel estimation. Both analytical and simulation results highlight the importance of accurate CFO estimation in SC-FDE systems.

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Jordan is adopting Enterprise Resource Planning (ERP) systems in both its public and private sectors. Jordan's emerging private sector has historically close ties to the public sector; though a global market orientation requires a shift in its organizational culture. ERPs however embed business processes which do not necessarily fit with traditional cultural practices, and implementation success is not assured. This study looks at the perceptions of both public and private sector ERP implementations in Jordan and assesses these on various measures of success. There were few differences between public and private sectors, but the benefits actually realized in Jordanian ERPs fell short of claims made for the technology in other cultures.

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Transport Certification Australia Limited, jointly with the National Transport Commission, has undertaken a project to investigate the feasibility of on-board mass monitoring (OBM) devices for regulatory purposes. OBM increases jurisdictional confidence in operational heavy vehicle compliance. This paper covers technical issues regarding potential use of dynamic data from OBM systems to indicate that tampering has occurred. Tamper-evidence and accuracy of current OBM systems needed to be determined before any regulatory schemes were put in place for its use. Tests performed to determine potential for, and ease of, tampering. An algorithm was developed to detect tamper events. Its results are detailed.

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Objective • Feasibility programme for on-board mass (OBM) monitoring of heavy vehicles (HVs) • Australian road authorities through Transport Certification Australia (TCA) • Accuracy of contemporary, commercially-available OBM units in Australia • Results need to be addressed/incorporated into specifications for Stage 2 of Intelligent Access Program (IAP) by Transport Certification Australia

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The phenomenon of organizations offering service bundles can typically be observed in dynamic markets with heterogeneous customer demand. Available literature broaching the issue of service bundling covers strategic considerations for organizations related to their respective market position as well as their pricing options for different bundle configurations. However, little guidance can be found regarding the identification of potential bundle candidates and the actual process of bundling. In this paper, we present an approach to service bundling that can be utilized by organizations to identify services that are suitable for bundling. The contribution of the paper is twofold. Firstly, the proposed method represents a structured conceptualization approach for organizations to facilitate the creation of bundles in practice based on empirical findings. Secondly, from a Design Science research perspective, the proposed method represents an innovative artifact that extends the academic knowledge base related to service management.

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The Dynamic Data eXchange (DDX) is our third generation platform for building distributed robot controllers. DDX allows a coalition of programs to share data at run-time through an efficient shared memory mechanism managed by a store. Further, stores on multiple machines can be linked by means of a global catalog and data is moved between the stores on an as needed basis by multi-casting. Heterogeneous computer systems are handled. We describe the architecture of DDX and the standard clients we have developed that let us rapidly build complex control systems with minimal coding.

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Visual servoing has been a viable method of robot manipulator control for more than a decade. Initial developments involved positionbased visual servoing (PBVS), in which the control signal exists in Cartesian space. The younger method, image-based visual servoing (IBVS), has seen considerable development in recent years. PBVS and IBVS offer tradeoffs in performance, and neither can solve all tasks that may confront a robot. In response to these issues, several methods have been devised that partition the control scheme, allowing some motions to be performed in the manner of a PBVS system, while the remaining motions are performed using an IBVS approach. To date, there has been little research that explores the relative strengths and weaknesses of these methods. In this paper we present such an evaluation. We have chosen three recent visual servo approaches for evaluation in addition to the traditional PBVS and IBVS approaches. We posit a set of performance metrics that measure quantitatively the performance of a visual servo controller for a specific task. We then evaluate each of the candidate visual servo methods for four canonical tasks with simulations and with experiments in a robotic work cell.

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Presents a unified and systematic assessment of ten position control strategies for a hydraulic servo system with single-ended cylinder driven by a proportional directional control valve. We aim at identifying those methods that achieve better tracking, have a low sensitivity to system uncertainties, and offer a good balance between development effort and end results. A formal approach for solving this problem relies on several practical metrics, which is introduced herein. Their choice is important, as the comparison results between controllers can vary significantly, depending on the selected criterion. Apart from the quantitative assessment, we also raise aspects which are difficult to quantify, but which must stay in attention when considering the position control problem for this class of hydraulic servo systems.

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Over recent years, Unmanned Air Vehicles or UAVs have become a powerful tool for reconnaissance and surveillance tasks. These vehicles are now available in a broad size and capability range and are intended to fly in regions where the presence of onboard human pilots is either too risky or unnecessary. This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of UAVs systems via evolutionary computation. The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser named HAPEA, several design modules, mesh generators and post-processing capabilities in an integrated platform. These population –based algorithms such as EAs are good for cases problems where the search space can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise, and also problems where we look for multiple solutions via Game Theory, namely a Nash equilibrium point or a Pareto set of non-dominated solutions. The application of the methodology is illustrated on conceptual and detailed multi-criteria and multidisciplinary shape design problems. Results indicate the practicality and robustness of the framework to find optimal shapes and trade—offs between the disciplinary analyses and to produce a set of non dominated solutions of an optimal Pareto front to the designer.

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Classrooms of the 21st century are complex systems. They support diverse learners from varied contexts and function in a “messy” bricolage of policy contexts. This complexity is also evident in the nature of teaching and learning deployed in these classrooms. There is also, in current contexts, a general expectation that teachers will support students to construct, rather than simply receive knowledge. This process of constructing knowledge requires a focus on critical thinking in complex social and real world contexts (see also Elen & Clarebout, 2001; Yang, Chang & Hsu 2008). Critical thinking, which involves the identification and evaluation of multiple perspectives when making decisions, is a process of knowing – a tool of wisdom (Kuhn & Udell, 2001). Schommer-Aikens, Bird and Bakken (2010) refer to classrooms that encourage critical thinking as “epistemologically based” in which “the teacher encourages his/her students to look for connections among concepts within the text, with their prior knowledge, and with concepts found in the world beyond themselves” (p. 48).

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This teaching case aims to contribute to understanding the phenomenon of Enterprise Systems (ES) implementations in universities. Through this case, students will gain understanding of the importance of ‘contextual elements’ for large scale information systems (IS) implementations, in particular ES. This teaching case illustrates how these contextual factors contribute to the success or failure of such implementations, and how they can influence the decisions that dictate the lifecycle of such systems. The case describes ES implementations at a leading Australian university, and presents a rich account of the institutional, national and industry-sector contexts that have influenced the directions and decisions taken. The journey encountered with the main Enterprise Systems that support Financials, Human Resources and Facilities are described suggesting the lifecycle phases, critical success factors and lessons learnt.

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The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

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The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

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Offering service bundles to the market is a promising option for service providers to strengthen their competitive advantages, cope with dynamic market conditions and deal with heterogeneous consumer demand. Although the expected positive effects of bundling strategies and pricing considerations for bundles are covered well by the available literature, limited guidance can be found regarding the identification of potential bundle candidates and the actual process of bundling. The contribution of this paper is the positioning of bundling based on insights from both business and computer science and the proposition of a structured bundling method, which guides organizations with the composition of bundles in practice.

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Offering service bundles to the market is a promising option for service providers to strengthen their competitive advantages, cope with dynamic market conditions and deal with heterogeneous consumer demand. Although the expected positive effects of bundling strategies and pricing considerations for bundles are covered well by the available literature, limited guidance can be found regarding the identification of potential bundle candidates and the actual process of bundling. The proposed research aims at filling this gap by offering a service bundling method complemented by a proof-of-concept prototype, which extends the existing knowledge base in the multidisciplinary research area of Information Systems and Service Science as well as providing an organisation with a structured approach for bundling services.