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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 …
Real-Time Classification Of Multivariate Olfaction Data Using Spiking Neural Networks, Arnup Vanarse, Adam Osseiran, Alexander Rassau, Therese O'Sullivan, Jonny Lo, Amanda Devine
Real-Time Classification Of Multivariate Olfaction Data Using Spiking Neural Networks, Arnup Vanarse, Adam Osseiran, Alexander Rassau, Therese O'Sullivan, Jonny Lo, Amanda Devine
Research outputs 2014 to 2021
Recent studies in bioinspired artificial olfaction, especially those detailing the application of spike-based neuromorphic methods, have led to promising developments towards overcoming the limitations of traditional approaches, such as complexity in handling multivariate data, computational and power requirements, poor accuracy, and substantial delay for processing and classification of odors. Rank-order-based olfactory systems provide an interesting approach for detection of target gases by encoding multi-variate data generated by artificial olfactory systems into temporal signatures. However, the utilization of traditional pattern-matching methods and unpredictable shuffling of spikes in the rank-order impedes the performance of the system. In this paper, we present an …
A Hardware-Deployable Neuromorphic Solution For Encoding And Classification Of Electronic Nose Data, Anup Vanarse, Alexander Rassau, Peter Van Der Made
A Hardware-Deployable Neuromorphic Solution For Encoding And Classification Of Electronic Nose Data, Anup Vanarse, Alexander Rassau, Peter Van Der Made
Research outputs 2014 to 2021
In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments in spike-based bio-inspired approaches have delivered solutions for the highly accurate classification of multivariate sensor data with minimized computational and power requirements. Although these methods have addressed issues related to efficient data processing and classification accuracy, other areas, such as reducing the processing latency to support real-time application and deploying spike-based solutions on supported hardware, have yet to be studied in detail. Through this investigation, we proposed a spiking …
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 …
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 …
Finding Evidence Of Wordlists Being Deployed Against Ssh Honeypots – Implications And Impacts, Priya Rabadia, Craig Valli
Finding Evidence Of Wordlists Being Deployed Against Ssh Honeypots – Implications And Impacts, Priya Rabadia, Craig Valli
Australian Digital Forensics Conference
This paper is an investigation focusing on activities detected by three SSH honeypots that utilise Kippo honeypot software. The honeypots were located on the same /24 IPv4 network and configured as identically as possible. The honeypots used the same base software and hardware configurations. The data from the honeypots were collected during the period 17th July 2012 and 26th November 2013, a total of 497 active day periods. The analysis in this paper focuses on the techniques used to attempt to gain access to these systems by attacking entities. Although all three honeypots are have the same configuration settings and …
Performance Evaluation Of Ieee 802.15.4 For Mobile Sensor Network, Kartinah Zen, Daryoush Habibi, Alexander Rassau, Iftekhar Ahmad
Performance Evaluation Of Ieee 802.15.4 For Mobile Sensor Network, Kartinah Zen, Daryoush Habibi, Alexander Rassau, Iftekhar Ahmad
Research outputs pre 2011
The IEEE 802.15.4 standard medium access control (MAC) protocol for low rate wireless personal area networks (LRWPAN) is design mainly for static sensor networks and its capability to support mobile sensor networks has not yet been established. To the best knowledge of authors, this is the first paper that evaluates the suitability of IEEE 802.15.4 MAC in mobile sensor networks environment. We evaluate the performance based on node's speed and beacon order, and observe the effect on energy usage, packet delivery ratio and time required to associate with its coordinator. From the experiment we observe that the moving nodes experienced …
Improving Mobile Sensor Connectivity Time In The Ieee 802.15.4 Networks, Kartinah Zen, Daryoush Habibi, Iftekhar Ahmad
Improving Mobile Sensor Connectivity Time In The Ieee 802.15.4 Networks, Kartinah Zen, Daryoush Habibi, Iftekhar Ahmad
Research outputs pre 2011
In the IEEE 802.15.4 medium access control (MAC) protocol for wireless sensor networks, a sensor node needs to associate with a coordinator before it starts sending or receiving data. The sensor node will mostly choose the nearest coordinator to associate with. However, this method is not suitable for a constantly moving sensor node because it will end up switching coordinators too often due to short connectivity time. The IEEE 802.15.4 has a simplistic and inadequate method of choosing a coordinator in this context. In this paper, we introduce a method to increase the mobile sensor node connectivity time with its …