Computer Sciences Commons^™

A Novel Energy Consumption Model For Autonomous Mobile Robot, Gürkan Gürgöze, İbrahi̇m Türkoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel predictive energy consumption model has been developed to facilitate the development of tasks based on efficient energy consumption strategies in mobile robot systems. For the proposed energy consumption model, an advanced mathematical system model that takes into account all parameters during the motion of the mobile robot is created. The parameters of inclination, load, dynamic friction, wheel slip and speed-torque saturation limit, which are often neglected in existing models, are especially used in our model. Thus, the effects of unexpected disruptors on energy consumption in the real world environment are also taken into account. As …

Automatically Classifying Familiar Web Users From Eye-Tracking Data:A Machine Learning Approach, Meli̇h Öder, Şükrü Eraslan, Yeli̇z Yesi̇lada

Turkish Journal of Electrical Engineering and Computer Sciences

Eye-tracking studies typically collect enormous amount of data encoding rich information about user behaviours and characteristics on the web. Eye-tracking data has been proved to be useful for usability and accessibility testing and for developing adaptive systems. The main objective of our work is to mine eye-tracking data with machine learning algorithms to automatically detect users' characteristics. In this paper, we focus on exploring different machine learning algorithms to automatically classify whether users are familiar or not with a web page. We present our work with an eye-tracking data of 81 participants on six web pages. Our results show that …

An Effective Prediction Method For Network State Information In Sd-Wan, Erdal Akin, Ferdi̇ Saraç, Ömer Aslan

Turkish Journal of Electrical Engineering and Computer Sciences

In a software-defined wide area network (SD-WAN), a logically centralized controller is responsible for computing and installing paths in order to transfer packets among geographically distributed locations and remote users. Accordingly, this would necessitate obtaining the global view and dynamic network state information (NSI) of the network. Therefore, the centralized controller periodically collects link-state information from each port of each switch at fixed time periods. While collecting NSI in short periods causes protocol overhead on the controller, collecting in longer periods leads to obtaining inaccurate NSI. In both cases, packet losses are inevitable, which is not preferred for quality of …

Temporal Bagging: A New Method For Time-Based Ensemble Learning, Göksu Tüysüzoğlu, Derya Bi̇rant, Volkan Kiranoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

One of the main problems associated with the bagging technique in ensemble learning is its random sample selection in which all samples are treated with the same chance of being selected. However, in time-varying dynamic systems, the samples in the training set have not equal importance, where the recent samples contain more useful and accurate information than the former ones. To overcome this problem, this paper proposes a new time-based ensemble learning method, called temporal bagging (T-Bagging). The significant advantage of our method is that it assigns larger weights to more recent samples with respect to older ones, so it …

An Active Contour Model Using Matched Filter And Hessian Matrix For Retinalvessels Segmentation, Mahtab Shabani, Hossein Pourghassem

Turkish Journal of Electrical Engineering and Computer Sciences

Medical image analysis, especially of the retina, plays an important role in diagnostic decision support tools. The properties of retinal blood vessels are used for disease diagnoses such as diabetes, glaucoma, and hypertension. There are some challenges in the utilization of retinal blood vessel patterns such as low contrast and intensity inhomogeneities. Thus, an automatic algorithm for vessel extraction is required. Active contour is a strong method for edge extraction. However, it cannot extract thin vessels and ridges very well. In this research, we propose an improved active contour method that uses discrete wavelet transform for energy minimization to solve …

Stressed Or Just Running? Differentiation Of Mental Stress And Physical Activityby Using Machine Learning, Yekta Sai̇d Can

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, modern people have excessive stress in their daily lives. With the advances in physiological sensors and wearable technology, people?s physiological status can be tracked, and stress levels can be recognized for providing beneficial services. Smartwatches and smartbands constitute the majority of wearable devices. Although they have an excellent potential for physiological stress recognition, some crucial issues need to be addressed, such as the resemblance of physiological reaction to stress and physical activity, artifacts caused by movements and low data quality. This paper focused on examining and differentiating physiological responses to both stressors and physical activity. Physiological data are collected …

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 …

Contexts For Children’S Digital Citizenship In India, Korea And Australia: A Literature Review, Kylie Stevenson, Emma Jayakumar, Viet Tho Le, Yeonghwi Ryu, Harrison See

Research outputs 2022 to 2026

Children’s digital citizenship today: In an increasingly digitised and technically mediated world, an individual’s digital citizenship, or “ability to use digital technology and media in safe, responsible and ethical ways” (DQ Institute, 2019) has never been more relevant, particularly when it concerns our youngest digital citizens. Navigating online spaces safely and confidently are skills fundamental to a modern individual’s social and emotional development, education, work and play. A digital citizen’s abilities, however, are greatly impacted by notions of access; not just physical access, but also access mediated culturally and socio-economically. Less is known about very young children’s experiences of digital …

Cyber Security Curriculum In Western Australian Primary And Secondary Schools: Interim Report: Curriculum Mapping, Nicola Johnson, Ahmed Ibrahim, Leslie Sikos, Cheryl Glowrey

Research outputs 2022 to 2026

Cyber-crime poses a significant threat to Australians—think of, for example, how scams take advantage of vulnerable people and systems. There is a need to educate people from an early age to protect them from cyberthreats.

Consistent with the increasing prevalence of cyberthreats to individuals and organisations in Australia, the national Australian curriculum has been updated (version 9.0) to include specific content for cyber security for primary and secondary students up to Year 10. Endorsed by Education Ministers in April 2022, the Western Australian School Curriculum and Standards Authority (SCSA) completed a detailed audit of the endorsed Australian Curriculum version 9.0 …

A Framework Of Lightweight Deep Cross-Connected Convolution Kernel Mapping Support Vector Machines, Qi Wang, Zhaoying Liu, Ting Zhang, Shanshan Tu, Yujian Li, Muhammad Waqas

Research outputs 2022 to 2026

Deep kernel mapping support vector machines have achieved good results in numerous tasks by mapping features from a low-dimensional space to a high-dimensional space and then using support vector machines for classification. However, the depth kernel mapping support vector machine does not take into account the connection of different dimensional spaces and increases the model parameters. To further improve the recognition capability of deep kernel mapping support vector machines while reducing the number of model parameters, this paper proposes a framework of Lightweight Deep Convolutional Cross-Connected Kernel Mapping Support Vector Machines (LC-CKMSVM). The framework consists of a feature extraction module …

Automatic And Fast Classification Of Barley Grains From Images: A Deep Learning Approach, Syed Afaq Ali Shah, Hao Luo, Putu Dita Pickupana, Alexander Ekeze, Ferdous Sohel, Hamid Laga, Chengdao Li, Blakely Paynter, Penghao Wang

Research outputs 2022 to 2026

Australia has a reputation for producing a reliable supply of high-quality barley in a contaminant-free climate. As a result, Australian barley is highly sought after by malting, brewing, distilling, and feed industries worldwide. Barley is traded as a variety-specific commodity on the international market for food, brewing and distilling end-use, as the intrinsic quality of the variety determines its market value. Manual identification of barley varieties by the naked eye is challenging and time-consuming for all stakeholders, including growers, grain handlers and traders. Current industrial methods for identifying barley varieties include molecular protein weights or DNA based technology, which are …

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 …

Asymmetrical Trusted Technology Networks In Developing Economies: A Case Study On Critical Infrastructure In Bhutan, Pratima Pradhan, Bal Subba, Thinley Jamtsho, Ganga Ram Ghimiray, David M. Cook

Research outputs 2022 to 2026

Developing Nations are subject to amplified challenges in terms of the integration of technology, and the exposure to non-domestic opportunism from larger neighboring economies. These challenges are recognizable as asymmetrical differences between what is seen as the normative list of critical infrastructures, and the specialisms that can dominate an emerging economy with early maturity technology networks. This paper discusses the case of Bhutan and demonstrates the need for strengthened approaches to trusted networks to ensure the reliability and continuity of the Nation's critical infrastructures. The paper also links the importance of trusted information sharing networks as part of an overarching …

Anatomy Of An Internet Hijack And Interception Attack: A Global And Educational Perspective, Ben A. Scott, Michael N. Johnstone, Patryk Szewczyk

Research outputs 2022 to 2026

The Internet’s underlying vulnerable protocol infrastructure is a rich target for cyber crime, cyber espionage and cyber warfare operations. The stability and security of the Internet infrastructure are important to the function of global matters of state, critical infrastructure, global e-commerce and election systems. There are global approaches to tackle Internet security challenges that include governance, law, educational and technical perspectives. This paper reviews a number of approaches to these challenges, the increasingly surgical attacks that target the underlying vulnerable protocol infrastructure of the Internet, and the extant cyber security education curricula; we find the majority of predominant cyber security …

A Review On Security Issues And Solutions Of The Internet Of Drones, Wencheng Yang, Song Wang, Xuefei Yin, Xu Wang, Jiankun Hu

Research outputs 2022 to 2026

The Internet of Drones (IoD) has attracted increasing attention in recent years because of its portability and automation, and is being deployed in a wide range of fields (e.g., military, rescue and entertainment). Nevertheless, as a result of the inherently open nature of radio transmission paths in the IoD, data collected, generated or handled by drones is plagued by many security concerns. Since security and privacy are among the foremost challenges for the IoD, in this paper we conduct a comprehensive review on security issues and solutions for IoD security, discussing IoD-related security requirements and identifying the latest advancement in …

On-Ice Detection, Classification, Localization And Tracking Of Anthropogenic Acoustic Sources With Machine Learning, Steven J. Whitaker

Dissertations, Master's Theses and Master's Reports

Arctic acoustics have been of concern in recent years for the US navy. First-year ice is now the prevalent factor in ice coverage in the Arctic, which changes the previously understood acoustic properties. Due to the ice melting each year, anthropogenic sources in the Arctic region are more common: military exercises, shipping, and tourism. For the navy, it is of interest to detect, classify, localize, and track these sources to have situational awareness of these surroundings. Because the sources are on-water or on-ice, acoustic radiation propagates at a longer distance and so acoustics are the method by which the sources …

Finding Geodesics Joining Given Points, Lyle Noakes, Erchuan Zhang

Research outputs 2022 to 2026

Finding a geodesic joining two given points in a complete path-connected Riemannian manifold requires much more effort than determining a geodesic from initial data. This is because it is much harder to solve boundary value problems than initial value problems. Shooting methods attempt to solve boundary value problems by solving a sequence of initial value problems, and usually need a good initial guess to succeed. The present paper finds a geodesic γ: [0 , 1] → M on the Riemannian manifold M with γ(0) = x0 and γ(1) = x1 by dividing the interval [0,1] into several sub-intervals, preferably just …

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 …

Edge-Iiotset: A New Comprehensive Realistic Cyber Security Dataset Of Iot And Iiot Applications For Centralized And Federated Learning, Mohamed A. Ferrag, Othmane Friha, Djallel Hamouda, Leandros Maglaras, Helge Janicke

Research outputs 2022 to 2026

In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection systems in two different modes, namely, centralized and federated learning. Specifically, the dataset has been generated using a purpose-built IoT/IIoT testbed with a large representative set of devices, sensors, protocols and cloud/edge configurations. The IoT data are generated from various IoT devices (more than 10 types) such as Low-cost digital sensors for sensing temperature and humidity, Ultrasonic sensor, Water level detection sensor, pH Sensor Meter, Soil Moisture sensor, Heart Rate Sensor, Flame …

Synthetic Augmentation Methods For Object Detection In Overhead Imagery, Nicholas R. Hamilton

Dissertations, Master's Theses and Master's Reports

The multidisciplinary area of geospatial intelligence (GEOINT) is continually changing and becoming more complex. From efforts to automate portions of GEOINT using machine learning, which augment the analyst and improve exploitation, to optimizing the growing number of sources and variables, there is no denying that the strategies involved in this collection method are rapidly progressing. The unique and inherent complexities involved in imagery analysis from an overhead perspective--—e.g., target resolution, imaging band(s), and imaging angle--—test the ability of even the most developed and novel machine learning techniques. To support advancement in the application of object detection in overhead imagery, we …

Poor Man’S Trace Cache: A Variable Delay Slot Architecture, Tino C. Moore

Dissertations, Master's Theses and Master's Reports

We introduce a novel fetch architecture called Poor Man’s Trace Cache (PMTC). PMTC constructs taken-path instruction traces via instruction replication in static code and inserts them after unconditional direct and select conditional direct control transfer instructions. These traces extend to the end of the cache line. Since available space for trace insertion may vary by the position of the control transfer instruction within the line, we refer to these fetch slots as variable delay slots. This approach ensures traces are fetched along with the control transfer instruction that initiated the trace. Branch, jump and return instruction semantics as well as …

Detecting Road Intersections Automatically From Satellite Images Using A Deep Learning Approach, Fatmaelzahraa Eltaher Ph.D, Luis Miralles-Pechuán, Jane Courtney, Susan Mckeever

Datasets

Automatic detection of road intersections is an important task in various domains such as navigation, route planning, traffic prediction, and road network extraction. Road intersections range from simple three-way T-junctions (degree 3) to complex large-scale junctions with many branches. The location of intersections and their complexity is an important consideration in route planning, such as the requirement to avoid complex intersections on pedestrian journeys. This is relevant to vulnerable road users such as People with Blindness or Visually Impairment (PBVI) or children. Route planning applications, however, do not give information about the location or complexity of intersections as this information …

Drivers Of Environmental Degradation In Turkey: Designing An Sdg Framework Through Advanced Quantile Approaches, Tomiwa Sunday Adebayo, Ephraim Bonah Agyekum, Salah Kamel, Hossam Zawbaa, Mehmet Altuntaş

Articles

Turkey is a laggard in terms of the achievement of its Sustainable Development Goals (SDGs), and one of the primary issues it faces is environmental deterioration. Therefore, a policy-level reorientation may be needed to address this relevant issue. From this standpoint, this research assesses the impact of renewable energy (RE) use and financial development on the emissions of CO2 as well as the role of urbanization and agriculture, utilizing a dataset stretching between 1985 and 2019. By applying the innovative quantile-on-quantile regression (QQR) and non-parametric Granger causality in quantiles techniques, the study assesses the ways in which the quantiles of …

Image-Based Malware Classification Hybrid Framework Based On Space-Filling Curves, Stephen O Shaughnessy, Stephen Sheridan

Articles

There exists a never-ending “arms race” between malware analysts and adversarial malicious code developers as malevolent programs evolve and countermeasures are developed to detect and eradicate them. Malware has become more complex in its intent and capabilities over time, which has prompted the need for constant improvement in detection and defence methods. Of particular concern are the anti-analysis obfuscation techniques, such as packing and encryption, that are employed by malware developers to evade detection and thwart the analysis process. In such cases, malware is generally impervious to basic analysis methods and so analysts must use more invasive techniques to extract …

Adopting Scenario-Based Approach To Solve Optimal Reactive Power Dispatch Problem With Integration Of Wind And Solar Energy Using Improved Marine Predator Algorithm, Noor Habib Khan, Raheela Jamal, Mohamed Ebeed, Salah Kamel, Hamed Zeinoddini-Meymand, Hossam Zawbaa

Articles

The penetration of renewable energy resources into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. The wind and photovoltaic (PV) based systems are the most applied technologies in electrical systems compared to other technologies of renewable energy resources. However, there are some complications and challenges to incorporating these resources due to their stochastic nature, intermittency, and variability of output powers. Therefore, solving the optimal reactive power dispatch (ORPD) problem with considering the uncertainties of renewable energy resources is a challenging task. Application of the Marine Predators …

Effect Of Cryogenic Treatment On Drill Tool For Enhancing Metal Cutting Operation Of Aluminium Alloy Is737.Gr19000, G. Navaneethakrishnan, B. Sureshkumar, R. Palanisamy, Mohit Bajaj, Hossam Zawbaa, Salah Kamel

Articles

Drilling is the hole making process on the component face with the aid of a twisted drillbit. Normal drill bits easily wear out through penetration of drill bit into the workpiece material due to force generated in the drilling operation. So this work tries to investigate the machining parameters with cryogenically treated drill bits on various responses. Cryogenic treatment is one of the thermal engineering processes, which is used to cool the material from the temperature of −150 °C to −273 °C. This research work utilizes cryogenically treated drill tools for investigating the drilling performance on aluminium alloy (IS737.Gr19000) workpiece …

Does Information And Communication Technology Impede Environmental Degradation? Fresh Insights From Non-Parametric Approaches, Tomiwa Sunday Adebayo, Ephraim Bonah Agyekum, Mehmet Altuntas, Sadriddin Khudoyqulov, Hossam Zawbaa, Salah Kamel

Articles

Although ICT has played a critical role in the socio-economic growth of human cultures, it has also brought with it significant environmental risks. Nevertheless, scholars remain divided on this topic; some believe that ICT has had a positive influence on the quality of the environment, while others believe that ICT has created major environmental issues. Hence, this research is another effort to assess the effects of ICT on CO2 emissions in the top 10 ICT nations (Denmark, Japan, Luxemburg, South Korea, Netherlands, Iceland, Norway, Sweden, Switzerland, and the United Kingdom) using a dataset from the period between 1986Q1 and 2019Q4. …

Automated Extraction Of Genes Associated With Antibiotic Resistance From The Biomedical Literature, Andre Brincat, Markus Hofmann

Articles

The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Whole-genome sequencing is emerging as a fast alternative to resistance prediction, by considering the presence/absence of certain genes. A lot of research has focused on determining which bacterial genes cause antibiotic resistance and efforts are being made to consolidate these facts in knowledge bases (KBs). KBs are usually manually curated by domain experts to be of the highest quality. However, this limits the pace at which new facts …

Towards An Inclusive Co-Design Toolkit: Perceptions And Experiences Of Co-Design Stakeholders, Eamon Aswad, Emma Murphy, Claudia Fernandez-Rivera, Sarah Boland

Articles

Participatory design holds great potential for the creation of inclusive technology but existing toolkits and resources to support co-design are not always accessible to designers and co-designers with disabilities. In this paper we present two studies to assist in facilitating the creation of a sustainable, accessible, inclusive co-design toolkit for individuals with intellectual disabilities i) exploration of the perceptions and experiences of lecturers (n =5) and students (n= 5) involved in co-design activities via individual interviews and ii) a protocol and initial findings from focus groups with men and women with intellectual disabilities to inform on best co-design practices (n=15). …

Virtual Machine Introspection Tool Design Analysis, Justin Martin

Dissertations, Master's Theses and Master's Reports

Virtual machines are an integral part of today’s computing world. Their use is widespread and applicable in many different computing fields. With virtual machines, the ability to introspect and monitor is often overlooked or left unimplemented. Introspection is used to gather information about the state of virtual machines as they operate. Without introspection, verbose log data and state information is unavailable after unexpected errors or crashes occur. With introspection, this data can be analyzed further to determine the true cause of the unexpected crash or error. Therefore, introspection plays a critical role in portraying accurate historical information regarding the operating …