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Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Enhanced Heart Rate Prediction Model Using Damped Least-Squares Algorithm, Angela An, Mohammad Al-Fawa’Reh, James Jin Kang
Enhanced Heart Rate Prediction Model Using Damped Least-Squares Algorithm, Angela An, Mohammad Al-Fawa’Reh, James Jin Kang
Research outputs 2022 to 2026
Monitoring a patient’s vital signs is considered one of the most challenging problems in telehealth systems, especially when patients reside in remote locations. Companies now use IoT devices such as wearable devices to participate in telehealth systems. However, the steady adoption of wearables can result in a significant increase in the volume of data being collected and transmitted. As these devices run on limited battery power, they can run out of power quickly due to the high processing requirements of the device for data collection and transmission. Given the importance of medical data, it is imperative that all transmitted data …
Expressiveness Of Real-Time Motion Captured Avatars Influences Perceived Animation Realism And Perceived Quality Of Social Interaction In Virtual Reality, Alan D. Fraser, Isabella Branson, Ross C. Hollett, Craig P. Speelman, Shane L. Rogers
Expressiveness Of Real-Time Motion Captured Avatars Influences Perceived Animation Realism And Perceived Quality Of Social Interaction In Virtual Reality, Alan D. Fraser, Isabella Branson, Ross C. Hollett, Craig P. Speelman, Shane L. Rogers
Research outputs 2022 to 2026
Using motion capture to enhance the realism of social interaction in virtual reality (VR) is growing in popularity. However, the impact of different levels of avatar expressiveness on the user experience is not well understood. In the present study we manipulated levels of face and body expressiveness of avatars while investigating participant perceptions of animation realism and interaction quality when disclosing positive and negative experiences in VR. Moderate positive associations were observed between perceptions of animation realism and interaction quality. Post-experiment questions revealed that many of our participants (approximately 40 %) indicated the avatar with the highest face and body …
Anomaly Detection In Cybersecurity Datasets Via Cooperative Co-Evolution-Based Feature Selection, Bazlur A. N. M. Rashid, Mohiuddin Ahmed, Leslie F. Sikos, Paul Haskell-Dowland
Anomaly Detection In Cybersecurity Datasets Via Cooperative Co-Evolution-Based Feature Selection, Bazlur A. N. M. Rashid, Mohiuddin Ahmed, Leslie F. Sikos, Paul Haskell-Dowland
Research outputs 2022 to 2026
Anomaly detection from Big Cybersecurity Datasets is very important; however, this is a very challenging and computationally expensive task. Feature selection (FS) is an approach to remove irrelevant and redundant features and select a subset of features, which can improve the machine learning algorithms’ performance. In fact, FS is an effective preprocessing step of anomaly detection techniques. This article’s main objective is to improve and quantify the accuracy and scalability of both supervised and unsupervised anomaly detection techniques. In this effort, a novel anomaly detection approach using FS, called Anomaly Detection Using Feature Selection (ADUFS), has been introduced. Experimental analysis …
Ransomware 2.0: An Emerging Threat To National Security, Mohiuddin Ahmed, Sascha Dominik Dov Bachmann, Abu Barkat Ullah, Shaun Barnett
Ransomware 2.0: An Emerging Threat To National Security, Mohiuddin Ahmed, Sascha Dominik Dov Bachmann, Abu Barkat Ullah, Shaun Barnett
Research outputs 2022 to 2026
The global Covid-19 pandemic has seen the rapid evolution of our traditional working environment; more people are working from home and the number of online meetings has increased. This trend has also affected the security sector. Consequently, the evolution of ransomware to what is now being described as ‘Ransomware 2.0’ has governments, businesses and individuals alike rushing to secure their data.
Design, Development, And Characterization Of Highly Efficient Colored Photovoltaic Module For Sustainable Buildings Applications, Mohammad Khairul Basher, Mohammad Nur-E-Alam, Momtazur Rahman, Steven Hinckley, Kamal Alameh
Design, Development, And Characterization Of Highly Efficient Colored Photovoltaic Module For Sustainable Buildings Applications, Mohammad Khairul Basher, Mohammad Nur-E-Alam, Momtazur Rahman, Steven Hinckley, Kamal Alameh
Research outputs 2022 to 2026
The building integrated photovoltaic (BIPV) system is one of the contributors which has enormous potential to reach the goal of net-zero energy buildings (NZEB) that significantly reduce the use of fossil fuels that contribute to global warming. However, the limitations of the visual and aesthetic appearance of current BIPV systems make this aspiration unlikely. This study investigates the limitations of the single-color-based PV modules that are dull in appearance and have low photo-conversion efficiency (PCE). In order to solve this issue, we designed, developed, and characterized micro-patterned-based multicolored photovoltaic (MPCPV) modules which are applicable to net-zero building and development. Our …
Development And Validation Of An Astronomy Self-Efficacy Instrument For Understanding And Doing, Rachel Freed, David Mckinnon, Michael Fitzgerald, Christina M. Norris
Development And Validation Of An Astronomy Self-Efficacy Instrument For Understanding And Doing, Rachel Freed, David Mckinnon, Michael Fitzgerald, Christina M. Norris
Research outputs 2022 to 2026
This paper presents a new astronomy self-efficacy instrument, composed of two factors; one relating to learning astronomy content, which we call astronomy personal self-efficacy, and the other relating to the use of astronomical instrumentation, specifically the use of remote robotic telescopes for data collection. The latter is referred to as the astronomy instrumental self-efficacy factor. The instrument has been tested for reliability and construct validity. Reliability testing showed that factor 1 had a Cronbach's α of 0.901 and factor 2 had a Cronbach's α of 0.937. Construct validity was established by computing one-way analyses of variances, with the p value …
Ecu-Ioft: A Dataset For Analysing Cyber-Attacks On Internet Of Flying Things, Mohiuddin Ahmed, David Cox, Benjamin Simpson, Aseel Aloufi
Ecu-Ioft: A Dataset For Analysing Cyber-Attacks On Internet Of Flying Things, Mohiuddin Ahmed, David Cox, Benjamin Simpson, Aseel Aloufi
Research outputs 2022 to 2026
There has been a significant increase in the adoption of unmanned aerial vehicles (UAV) within science, technology, engineering, and mathematics project-based learning. However, the risks that education providers place their student and staff under is often unknown or undocumented. Low-end consumer drones used within the education sector are vulnerable to state-of-the-art cyberattacks. Therefore, datasets are required to conduct further research to establish cyber defenses for UAVs used within the education sector. This paper showcases the development of the ECU-IoFT dataset, documenting three known cyber-attacks targeting Wi-Fi communications and the lack of security in an affordable off-the-shelf drone. At present, there …
Geostatistical Tools To Assess Shifts In Recreational Fishing, Shannon J. Burchert, Glenn A. Hyndes, Karina Ryan, Ute Mueller
Geostatistical Tools To Assess Shifts In Recreational Fishing, Shannon J. Burchert, Glenn A. Hyndes, Karina Ryan, Ute Mueller
Research outputs 2022 to 2026
The use of geostatistical indices to examine fishery-dependent data over time is novel. We assess the value of a range of these indices for describing trends in boat-based recreational fishing in Western Australia and areas of high effort and catches for two demersal species with varying biological characteristics, life histories and distributions. The number of blocks (10- × 10-nautical mile (~19- × 19-km) area) visited decreased by 40%, while the number of fishing trips with demersal species catch increased by 15%. Spatial indices showed a south-easterly shift in demersal catch per unit effort (CPUE) across survey years. The southerly shift …
Realistic Motion Avatars Are The Future For Social Interaction In Virtual Reality, Shane L. Rogers, Rebecca Broadbent, Jemma Brown, Allan Fraser, Craig P. Speelman
Realistic Motion Avatars Are The Future For Social Interaction In Virtual Reality, Shane L. Rogers, Rebecca Broadbent, Jemma Brown, Allan Fraser, Craig P. Speelman
Research outputs 2022 to 2026
This study evaluated participant self-reported appraisal of social interactions with another person in virtual reality (VR) where their conversational partner was represented by a realistic motion avatar. We use the term realistic motion avatar because: 1. The avatar was modelled to look like the conversational partner it represented, and 2. Full face and body motion capture was utilised so that the avatar mimicked the facial and body language of the conversational partner in real-time. We compared social interaction in VR with face-to-face interaction across two communicative contexts: 1. Getting acquainted conversation, and 2. A structured interview where the participant engaged …
A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang
A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang
Research outputs 2022 to 2026
Network intrusion is a well-studied area of cyber security. Current machine learning-based network intrusion detection systems (NIDSs) monitor network data and the patterns within those data but at the cost of presenting significant issues in terms of privacy violations which may threaten end-user privacy. Therefore, to mitigate risk and preserve a balance between security and privacy, it is imperative to protect user privacy with respect to intrusion data. Moreover, cost is a driver of a machine learning-based NIDS because such systems are increasingly being deployed on resource-limited edge devices. To solve these issues, in this paper we propose a NIDS …
Biometric Security: A Novel Ear Recognition Approach Using A 3d Morphable Ear Model, Md Mursalin, Mohiuddin Ahmed, Paul Haskell-Dowland
Biometric Security: A Novel Ear Recognition Approach Using A 3d Morphable Ear Model, Md Mursalin, Mohiuddin Ahmed, Paul Haskell-Dowland
Research outputs 2022 to 2026
Biometrics is a critical component of cybersecurity that identifies persons by verifying their behavioral and physical traits. In biometric-based authentication, each individual can be correctly recognized based on their intrinsic behavioral or physical features, such as face, fingerprint, iris, and ears. This work proposes a novel approach for human identification using 3D ear images. Usually, in conventional methods, the probe image is registered with each gallery image using computational heavy registration algorithms, making it practically infeasible due to the time-consuming recognition process. Therefore, this work proposes a recognition pipeline that reduces the one-to-one registration between probe and gallery. First, a …