School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau

Permanent link for this collection

https://hdl.handle.net/10292/553
AUT is home to a number of renowned research institutes in engineering, and computer and mathematical sciences. The School of Engineering, Computer and Mathematical Sciences strong industry partnerships and the unique combination of engineering, computer and mathematical sciences within one school stimulates interdisciplinary research beyond traditional boundaries. Current research interests include:
  • Artificial Intelligence; Astronomy and Space Research;
  • Biomedical Technologies;
  • Computer Engineering; Computer Vision; Construction Management;
  • Data Science;
  • Health Informatics and eHealth;
  • Industrial Optimisation, Modelling & Control;
  • Information Security;
  • Mathematical Sciences Research; Materials & Manufacturing Technologies;
  • Networking, Instrumentation and Telecommunications;
  • Parallel and Distributed Systems; Power and Energy Engineering;
  • Software Engineering; Signal Processing; STEM Education;
  • Wireless Engineering;

Browse

Recent Submissions

Now showing 1 - 5 of 1448
  • Item
    Analytical and Computational Sliding Wear Prediction of Ultrahigh Molecular Weight Polyethylene (UHMWPE) in Block-on-Ring (BOR) Tribometer
    (Malaysian Tribology Society, 2024-06) Hussin, MS; Hamat, S; Kelly, PA; Fernandez, JW; Ramezani, M; Pranesh, K
    In knee joint replacement, wear of Ultrahigh Molecular Weight Polyethylene (UHMWPE) can be a significant factor in shortening the implant life span. With advancements in computational technology, virtual testing has become more reliable at a lower cost compared to physical testing. This paper evaluates the wear coefficient, kD, from physical tests as a reliable predictor of wear volume in the computational method. The physical test run with a block-on-ring (BOR) configuration of UHMWPE on a steel counterface with 225N load for wear coefficient, kD acquisition and 130N load for computational prediction validation using the same wear coefficient, kD. The computational methodology involved the use of an Abaqus solver incorporating the UMESHMOTION subroutine to implement Archard's law. The maximum FEA result error was 14% in the 225N load test, and FEA prediction for the 130N load test was 17%. The results show that the wear coefficient,kD produced by coupling UMESHMOTION in the computational method, is reliable for predicting wear volume in BOR physical test.
  • Item
    Machine Learning-Based Resource Allocation Algorithm to Mitigate Interference in D2D-Enabled Cellular Networks
    (MDPI AG, 2024-11-06) Kamruzzaman, Md; Sarkar, Nurul I; Gutierrez, Jairo
    Mobile communications have experienced exponential growth both in connectivity and multimedia traffic in recent years. To support this tremendous growth, device-to-device (D2D) communications play a significant role in 5G and beyond 5G networks. However, enabling D2D communications in an underlay, heterogeneous cellular network poses two major challenges. First, interference management between D2D and cellular users directly affects a system’s performance. Second, achieving an acceptable level of link quality for both D2D and cellular networks is necessary. An optimum resource allocation is required to mitigate the interference and improve a system’s performance. In this paper, we provide a solution to interference management with an acceptable quality of services (QoS). To this end, we propose a machine learning-based resource allocation method to maximize throughput and achieve minimum QoS requirements for all active D2D pairs and cellular users. We first solve a resource optimization problem by allocating spectrum resources and controlling power transmission on demand. As resource optimization is an integer nonlinear programming problem, we address this problem by proposing a deep Q-network-based reinforcement learning algorithm (DRL) to optimize the resource allocation issue. The proposed DRL algorithm is trained with a decision-making policy to obtain the best solution in terms of spectrum efficiency, computational time, and throughput. The system performance is validated by simulation. The results show that the proposed method outperforms the existing ones.
  • Item
    Design and Equivalent Circuit Model Extraction of a Fractal Slot-Loaded 3–40 GHz Super Wideband Antenna
    (MDPI, 2024-11-08) Alamro, Wasan; Seet, Boon-Chong; Wang, Lulu; Parthiban, Prabakar
    In this paper, we present the design and equivalent circuit model (ECM) of a fractal slot-loaded super wideband (SWB) antenna for compact and high-performance applications operating in the 3–40 GHz range. The proposed antenna features a compact dimension of 40 × 35 × 1.57 mm³, a measured bandwidth ratio of 13:1, a peak gain of 9.7 dBi, an average radiation efficiency of 94%, and a low cross-polarization level across the entire bandwidth. The presented ECM is derived using transmission line theory and incorporates the individual behavior of each constituting element of the antenna. A dual sequential optimization approach is employed to determine the optimal element values. The ECM results show good agreement with both simulated and measured results in terms of the magnitude of reflection coefficient |𝑆11| and both real and imaginary impedances with low mean absolute percentage errors of 4.9%, 7.5%, and 7.7%, respectively, demonstrating the model’s ability to accurately predict the antenna’s performance.
  • Item
    Comparison of Laminar and Turbulent K–Omega Shear Stress Transport Models Under Realistic Boundary Conditions Using Clinical Data for Arterial Stenosis
    (ASME International, 2024-09-30) Al-Rawi, Mohammad; Belkacemi, Djelloul; Al-Jumaily, Ahmed M
    Abstract Early diagnosis of cardiovascular diseases (CVDs), including arterial stenosis, enables targeted treatments that reduce CVD mortality. It is vital to improve the accuracy of early diagnostic tools. Current computational studies of stenosis use mathematical models, such as laminar and k–omega shear stress transport (SST) models, available in ansys (Fluent and CFX), openfoam, and comsol software packages. Users can adjust boundary conditions, such as inlet velocity and outlet pressure using user-defined functions (UDFs) with different expressions and constant values. However, currently there is no rule over what to impose at these boundaries, and previous studies have used various assumptions, such as rigid artery wall, one-way fluid–structure interaction (FSI) or two-way FSI, and the blood's Newtonian or non-Newtonian material properties. This variety in construction has associated deviations of the models from the clinical data and lessens the value of the models as potential diagnostic or predictive tools for medical practitioners. In this study, we examine arterial stenosis models, with severities of 20%, 40%, and 50%, compared with the healthy artery analyzed in terms of strain energy to the artery wall. Additionally, we investigate elastic walls using one-way FSI, comparing with laminar and k–omega SST. These boundary conditions are based on clinical data. The results regarding the strain energy (mJ) behavior along the artery wall show that the k–omega SST model outperforms the laminar model for short arterial segments and under the Newtonian assumption with a no-slip boundary wall and turbulent flow.
  • Item
    Cointegration Analysis of Crop Yields and Extreme Weather Factors Using Actuaries Climate Index with Application of Bonus–Malus System
    (Taylor and Francis Group, 2024-10-29) Cheung, Eric CK; Ip, Ryan HL; Tam, Ho On; Woo, Jae-Kyung
    This article analyzes the long-term temporal co-movement of the extreme weather variables in the Actuaries Climate Index (ACI) and crop yields, modeling their relationship using an error correction model (ECM). The analysis suggests that significant weather variables can serve as trigger parameters in the pricing framework of weather index crop insurance. To address the challenge of weather index crop insurance while preserving the advantages of a bonus–malus system (BMS), we propose a transition rule that distinguishes between damages caused by severe weather and those resulting from the policyholder’s decisions. Subsequently, we also explore the challenges of implementing such a new hybrid BMS for crop insurance where extreme weather outcomes are integrated into the classical BMS.
Items in these collections are protected by the Copyright Act 1994 (New Zealand). These works may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use:
  • Any use you make of these works must be for research or private study purposes only, and you may not make them available to any other person.
  • Authors control the copyright of their works. You will recognise the author’s right to be identified as the author of the work, and due acknowledgement will be made to the author where appropriate.
  • You will obtain the author’s permission before publishing any material from the work.