ORCID Profile
0000-0002-0253-938X
Current Organisation
University of South Australia
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Publisher: Springer Science and Business Media LLC
Date: 21-05-2019
Publisher: Wiley
Date: 08-01-2016
DOI: 10.1002/CPLX.21646
Publisher: Wiley
Date: 30-03-2016
DOI: 10.1002/CPLX.21767
Publisher: Informa UK Limited
Date: 30-11-2010
Publisher: Informa UK Limited
Date: 31-10-2007
Publisher: IEEE
Date: 17-04-2023
Publisher: Springer International Publishing
Date: 17-11-2018
Publisher: Springer International Publishing
Date: 17-11-2019
Publisher: Elsevier BV
Date: 2018
Publisher: IEEE
Date: 04-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
Publisher: IEEE
Date: 05-2015
Publisher: IEEE
Date: 04-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Cambridge University Press (CUP)
Date: 07-06-2011
DOI: 10.1017/S0373463311000075
Abstract: Cooperative positioning (CP) is a localization technique originally developed for use across wireless sensor networks. With the emergence of Dedicated Short Range Communications (DSRC) infrastructure for use in Intelligent Transportation Systems (ITS), CP techniques can now be adapted for use in location determination across vehicular networks. In vehicular networks, the technique of CP fuses GPS positions with additional sensed information such as inter-vehicle distances between the moving vehicles to determine their location within a neighbourhood. This paper presents the results obtained from a research study undertaken to demonstrate the capabilities of DSRC for meeting the positioning accuracies of road safety applications. The results show that a CP algorithm that fully integrates both measured/sensed data as well as navigation information such as map data can meet the positioning requirements of safety related applications of DSRC ( ·5 m). This paper presents the results of a Cramer Rao Lower Bound analysis which is used to benchmark the performance of the CP algorithm developed. The Kalman Filter (KF) models used in the CP algorithm are detailed and results obtained from integrating GPS positions, inter-vehicular ranges and information derived from in-vehicle maps are then discussed along with typical results as determined through a variety of network simulation studies.
Publisher: Wiley
Date: 12-05-2023
DOI: 10.1002/SYS.21690
Abstract: When dealing with problems with more than two objectives, sophisticated multi‐objective optimization algorithms might be needed. Pareto optimization, which is based on the concept of dominated and non‐dominated solutions, is the most widely utilized method when comparing solutions within a multi‐objective setting. However, in the context of optimization, where three or more objectives are involved, the effectiveness of Pareto dominance approaches to drive the solutions to convergence is significantly compromised as more and more solutions tend to be non‐dominated by each other. This in turn reduces the selection pressure, especially for algorithms that rely on evolving a population of solutions such as evolutionary algorithms, particle swarm optimization, differential evolution, etc. The size of the non‐dominated set of trade‐off solutions can be quite large, rendering the decision‐making process difficult if not impossible. The size of the non‐dominated solution set increases exponentially with an increase in the number of objectives. This paper aims to expand a framework for coping with many/multi‐objective and multidisciplinary optimization problems through the introduction of a min‐max metric that behaves like a median measure that can locate the center of a data set. We compare this metric to the Chebyshev norm L_∞ metric that behaves like a mean measure in locating the center of a data set. The median metric is introduced in this paper for the first time, and unlike the mean metric is independent of the data normalization method. These metrics advocate balanced, natural, and minimum compromise solutions about all objectives. We also demonstrate and compare the behavior of the two metrics for a Tradespace case study involving more than 1200 CubeSat design alternatives identifying a manageable set of potential solutions for decision‐makers.
Publisher: SAGE Publications
Date: 2021
DOI: 10.1177/18479790211004010
Abstract: Large organisations use both internal and external methods to educate their workforce. Workforce approaches in Defence were usually of a closed nature, characterised by entry at recruitment and sequential and hierarchical rank progression. More recently, emerging technology and the associated pace of societal change has required Defence to recruit more laterally and to outsource more education, both ab initio and development. The growing complexity of workforce problems, therefore, challenges military educational decision making to increase its focus on organisational resilience. Modelling and Simulation (M& S) can take messy, ill-defined problems and build models for decision support and problem-solving. M& S is being explored in Defence workforce employability planning to deliver education that is more resilient to perturbations and can more confidently predict graduate demand for educational support partnering. However, the effective use of M& S can be compromised if it is not cognitively useful for the problem owner. A new transformational approach between the modeller and the managers of Defence educational workforce is proposed and illustrated by two conceptual case studies. The method uses the module-based translation between Business Process Model Notation (BPMN) design patterns and systems dynamics building blocks to reduce the problem owner’s reliance on specialist modellers. This approach increases the cognitive effectiveness of proposed workforce education solutions and the sharing and reuse of workforce M& S applications. Any large organisation with sufficient human resource and systems engineering support could adopt this new approach to model and simulate their workforce education and examine their resilience to fluctuations.
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Cambridge University Press (CUP)
Date: 12-03-2012
DOI: 10.1017/S0373463311000610
Abstract: Vehicular communication technologies are becoming staples of modern societies. This paper proposes a new positioning algorithm for vehicular networks. The algorithm is a non-classic Multi-Dimensional Scaling Filter (MDSF) that builds on a novel and computationally effective Multi-Dimensional Scaling (MDS) solution covariance estimation technique and also a Maximum Likelihood (ML) filter. In general a major drawback of the non-classic MDS is the high computational cost because of its iterative nature. It is shown that a special blend between vehicular Map-Matching (MM) and MDSF considerably reduces the number of iterations and the convergence time, making the MDSF a suitable algorithm for vehicular network positioning. The performance of MDSF is compared with that of an Extended Kalman Filter (EKF) together with the Cramar Rao Lower Bound (CRLB). It is shown through simulation that for all types of traffic conditions MDSF performs better than EKF and closer to CRLB than EKF. It is also shown that both MDSF and EKF algorithms are robust to typical Global Positioning System (GPS) outages in deep urban canyons. CRLB also proves that Cooperative Positioning (CP) in general has the ability to bridge short GPS outages.
Publisher: IEEE
Date: 03-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: IEEE
Date: 03-2012
Publisher: Informa UK Limited
Date: 2020
Publisher: Elsevier BV
Date: 07-2017
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IEEE
Date: 03-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2017
Publisher: Elsevier BV
Date: 2016
Publisher: Inderscience Publishers
Date: 2016
Publisher: IEEE
Date: 06-2014
Publisher: IEEE
Date: 04-2016
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Informa UK Limited
Date: 16-05-2017
Publisher: Informa UK Limited
Date: 26-11-2023
Publisher: IGI Global
Date: 2012
DOI: 10.4018/978-1-4666-0209-0.CH012
Abstract: This chapter introduces the concept of Cooperative Positioning (CP) for vehicular networks, or more precisely, VANETs (Vehicular Adhoc NETworks), as an application of DSRC (Dedicated Short Range Communication). It includes a comprehensive review of available and hypothetical vehicular positioning technologies. Amongst these, the importance of CP for Location Based Services using DSRC is emphasized, and some important issues are addressed that need to be resolved in order to implement CP successfully with standard DSRC infrastructure. The performance bounds of CP are derived. Ranging between vehicles is identified as the main hurdle to be overcome. Time-based techniques of ranging are introduced, and the bandwidth requirements are investigated. The robustness of CP to inter-node connection failure as well as GPS (Global Positioning System) dropout is demonstrated via simulation. Kalman Filter performance for CP is evaluated, and proven to be efficient under conditions such as the consistency of GPS signal availability ranging between vehicles. CP has, however, shown to increase the positioning accuracy to 1-meter level, even in the deep urban valleys where vehicles frequently become invisible to navigation. Overall, CP is proven to be a viable concept and worthy of development as a DSRC application.
Publisher: IEEE
Date: 2009
Publisher: Inderscience Publishers
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: MDPI AG
Date: 02-04-2023
Abstract: Changeability analysis methods primarily assist with formulating a response to uncertain and new requirements from various system stakeholders and include asset management issues such as modelling lifecycle path dependency. Epoch-era networks proved to be an effective tool for managing the evolving requirements of a capability system, ensuring sustained value through life. Over the life of a system, stakeholders are faced with countless options to change their capability systems to sustain value, which is path dependent and can greatly impact the scope of decisions available later in life. This paper introduces and demonstrates the application of a revised epoch-era network approach to explore many potential lifecycle paths, along with utility vs. expense strategies, demonstrated through an ex le of a military frigate subject to evolving requirements. Results indicated the future limitations to sustaining value if the largest and most capable technology upgrades are selected too early in life. The two best lifecycle paths from different strategies were compared to understand the utility/expense trade-offs for the most optimal frigate upgrade trajectory.
Publisher: Informa UK Limited
Date: 02-08-2017
Publisher: IEEE
Date: 04-2018
Publisher: Springer Science and Business Media LLC
Date: 04-02-2012
No related grants have been discovered for Mahmoud Efatmaneshnik.