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Articles 1 - 12 of 12
Full-Text Articles in Engineering
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Research outputs 2014 to 2021
Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …
Effective Plant Discrimination Based On The Combination Of Local Binary Pattern Operators And Multiclass Support Vector Machine Methods, Vi N T Le, Beniamin Apopei, Kamal Alameh
Effective Plant Discrimination Based On The Combination Of Local Binary Pattern Operators And Multiclass Support Vector Machine Methods, Vi N T Le, Beniamin Apopei, Kamal Alameh
Research outputs 2014 to 2021
Accurate crop and weed discrimination plays a critical role in addressing the challenges of weed management in agriculture. The use of herbicides is currently the most common approach to weed control. However, herbicide resistant plants have long been recognised as a major concern due to the excessive use of herbicides. Effective weed detection techniques can reduce the cost of weed management and improve crop quality and yield. A computationally efficient and robust plant classification algorithm is developed and applied to the classification of three crops: Brassica napus (canola), Zea mays (maize/corn), and radish. The developed algorithm is based on the …
Application Of 3d Delaunay Triangulation In Fingerprint Authentication System, Wencheng Yang, Ahmed Ibrahim, Junaid Chaudhry, Song Wang, Jiankun Hu, Craig Valli
Application Of 3d Delaunay Triangulation In Fingerprint Authentication System, Wencheng Yang, Ahmed Ibrahim, Junaid Chaudhry, Song Wang, Jiankun Hu, Craig Valli
Research outputs 2014 to 2021
Biometric security has found many applications in Internet of Things (IoT) security. Many mobile devices including smart phones have supplied fingerprint authentication function. However, the authentication performance in such restricted environment has been downgraded significantly. A number of methods based on Delaunay triangulation have been proposed for minutiae-based fingerprint matching, due to some favorable properties of the Delaunay triangulation under image distortion. However, all existing methods are based on 2D pattern, of which each unit, a Delaunay triangle, can only provide limited discrimination ability and could cause low matching performance. In this paper, we propose a 3D Delaunay triangulation based …
Review Of Deep Learning Methods In Robotic Grasp Detection, Shehan Caldera, Alexander Rassau, Douglas Chai
Review Of Deep Learning Methods In Robotic Grasp Detection, Shehan Caldera, Alexander Rassau, Douglas Chai
Research outputs 2014 to 2021
For robots to attain more general-purpose utility, grasping is a necessary skill to master. Such general-purpose robots may use their perception abilities to visually identify grasps for a given object. A grasp describes how a robotic end-effector can be arranged to securely grab an object and successfully lift it without slippage. Traditionally, grasp detection requires expert human knowledge to analytically form the task-specific algorithm, but this is an arduous and time-consuming approach. During the last five years, deep learning methods have enabled significant advancements in robotic vision, natural language processing, and automated driving applications. The successful results of these methods …
Influence Of Substrate Stage Temperature And Rotation Rate On The Magneto-Optical Quality Of Rf-Sputtered Bi2.1dy0.9fe3.9ga1.1o12 Garnet Thin Films, Mohammad E. Alam, Mikhail Vasiliev, Kamal Alameh
Influence Of Substrate Stage Temperature And Rotation Rate On The Magneto-Optical Quality Of Rf-Sputtered Bi2.1dy0.9fe3.9ga1.1o12 Garnet Thin Films, Mohammad E. Alam, Mikhail Vasiliev, Kamal Alameh
Research outputs 2014 to 2021
Highly bismuth-substituted iron garnet thin films are prepared on quartz substrates by using a radio frequency (RF) magnetron sputtering technique. We study the factors (process parameters associated with the RF magnetron sputter deposition technique) affecting the magneto-optical (MO) properties of ferrite garnet films of composition Bi2.1Dy0.9Fe3.9Ga1.1O12. All films show high MO response across the visible range of wavelengths after being annealed. In particular, the effects of substrate stage temperature and rotation rate on the various properties of films are studied. Experimental results reveal that the characteristics of garnet films of this type can be tuned and optimized for use in …
A Security Review Of Local Government Using Nist Csf: A Case Study, Ahmed Ibrahim, Craig Valli, Ian Mcateer, Junaid Chaudhry
A Security Review Of Local Government Using Nist Csf: A Case Study, Ahmed Ibrahim, Craig Valli, Ian Mcateer, Junaid Chaudhry
Research outputs 2014 to 2021
Evaluating cyber security risk is a challenging task regardless of an organisation’s nature of business or size, however, an essential activity. This paper uses the National Institute of Standards and Technology (NIST) cyber security framework (CSF) to assess the cyber security posture of a local government organisation in Western Australia. Our approach enabled the quantification of risks for specific NIST CSF core functions and respective categories and allowed making recommendations to address the gaps discovered to attain the desired level of compliance. This has led the organisation to strategically target areas related to their people, processes, and technologies, thus mitigating …
Ransomware Behavioural Analysis On Windows Platforms, Nikolai Hampton, Zubair A. Baig, Sherali Zeadally
Ransomware Behavioural Analysis On Windows Platforms, Nikolai Hampton, Zubair A. Baig, Sherali Zeadally
Research outputs 2014 to 2021
Ransomware infections have grown exponentially during the recent past to cause major disruption in operations across a range of industries including the government. Through this research, we present an analysis of 14 strains of ransomware that infect Windows platforms, and we do a comparison of Windows Application Programming Interface (API) calls made through ransomware processes with baselines of normal operating system behaviour. The study identifies and reports salient features of ransomware as referred through the frequencies of API calls
A Novel Privacy Preserving User Identification Approach For Network Traffic, Nathan Clarke, Fudong Li, Steven Furnell
A Novel Privacy Preserving User Identification Approach For Network Traffic, Nathan Clarke, Fudong Li, Steven Furnell
Research outputs 2014 to 2021
The prevalence of the Internet and cloud-based applications, alongside the technological evolution of smartphones, tablets and smartwatches, has resulted in users relying upon network connectivity more than ever before. This results in an increasingly voluminous footprint with respect to the network traffic that is created as a consequence. For network forensic examiners, this traffic represents a vital source of independent evidence in an environment where anti-forensics is increasingly challenging the validity of computer-based forensics. Performing network forensics today largely focuses upon an analysis based upon the Internet Protocol (IP) address – as this is the only characteristic available. More typically, …
A Feature-Based Structural Measure: An Image Similarity Measure For Face Recognition, Noor A. Shnain, Zahir Hussain, Song F. Lu
A Feature-Based Structural Measure: An Image Similarity Measure For Face Recognition, Noor A. Shnain, Zahir Hussain, Song F. Lu
Research outputs 2014 to 2021
Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues such as security, surveillance systems and forensics analysis. Despite this high level of attention to facial recognition, the success is still limited by certain conditions; there is no method which gives reliable results in all situations. In this paper, we propose an efficient similarity index that resolves the shortcomings of the existing measures of feature and structural similarity. This measure, called …
Optical Fiber Sensors In Physical Intrusion Detection Systems: A Review, Gary Andrew Allwood, Graham Wild, Steven Hinkley
Optical Fiber Sensors In Physical Intrusion Detection Systems: A Review, Gary Andrew Allwood, Graham Wild, Steven Hinkley
Research outputs 2014 to 2021
Fiber optic sensors have become a mainstream sensing technology within a large array of applications due to their inherent benefits. They are now used significantly in structural health monitoring, and are an essential solution for monitoring harsh environments. Since their first development over 30 years ago, they have also found promise in security applications. This paper reviews all of the optical fiber-based techniques used in physical intrusion detection systems. It details the different approaches used for sensing, interrogation, and networking, by research groups, attempting to secure both commercial and residential premises from physical security breaches. The advantages and the disadvantages …
A Forecasting Tool For Predicting Australia's Domestic Airline Passenger Demand Using A Genetic Algorithm, Panarat Srisaeng, Glenn Baxter, Steven Richardson, Graham Wild
A Forecasting Tool For Predicting Australia's Domestic Airline Passenger Demand Using A Genetic Algorithm, Panarat Srisaeng, Glenn Baxter, Steven Richardson, Graham Wild
Research outputs 2014 to 2021
This study has proposed and empirically tested for the first time genetic algorithm optimization models for modelling Australia’s domestic airline passenger demand, as measured by enplaned passengers (GAPAXDE model) and revenue passenger kilometres performed (GARPKSDE model). Data was divided into training and testing datasets; 74 training datasets were used to estimate the weighting factors of the genetic algorithm models and 13 out-of-sample datasets were used for testing the robustness of the genetic algorithm models. The genetic algorithm parameters used in this study comprised population size (n): 200; the generation number: 1,000; and mutation rate: 0.01. The modelling results have shown …
Forensic Analysis Of A Sony Playstation 4: A First Look, Matthew Davies, Huw Read, Konstantinos Xynos, Iain Sutherland
Forensic Analysis Of A Sony Playstation 4: A First Look, Matthew Davies, Huw Read, Konstantinos Xynos, Iain Sutherland
Research outputs 2014 to 2021
The primary function of a games console is that of an entertainment system. However the latest iteration of these consoles has added a number of new interactive features that may prove of value to the digital investigator. This paper highlights the value of these consoles, in particular Sony's latest version of their PlayStation. This console provides a number of features including web browsing, downloading of material and chat functionality; all communication features that will be of interest to forensic investigators. In this paper we undertake an initial investigation of the PlayStation 4 games console. This paper identifies potential information sources …