Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Electrical and Computer Engineering (4)
- Other Computer Engineering (4)
- Artificial Intelligence and Robotics (1)
- Biomedical Engineering and Bioengineering (1)
- Computer Sciences (1)
-
- Data Science (1)
- Digital Communications and Networking (1)
- Education (1)
- Educational Assessment, Evaluation, and Research (1)
- Educational Methods (1)
- Educational Technology (1)
- Electrical and Electronics (1)
- Mechanical Engineering (1)
- Medicine and Health Sciences (1)
- Other Electrical and Computer Engineering (1)
- Physical Sciences and Mathematics (1)
- Power and Energy (1)
- Robotics (1)
- Signal Processing (1)
- Software Engineering (1)
- Systems and Communications (1)
- Keyword
-
- Cybersecurity (2)
- Machine learning (2)
- 3D small cells (1)
- Anonymization (1)
- Assessment (1)
-
- Behavioral biometrics (1)
- Big Data (1)
- Computational Thinking (1)
- Conic systems (1)
- Continuous authentication (1)
- Coupled stability (1)
- Dataset Anonymization (1)
- Deep Learning (1)
- Deep learning (1)
- Distributed Learning (1)
- Dynamics estimation (1)
- Ensemble learning (1)
- Federated Learning (1)
- Force control (1)
- HetNets (1)
- Interaction control (1)
- Keystroke data (1)
- Learning Analytics (1)
- Lidar Point Clouds (1)
- Load Forecasting (1)
- Long Short-Term Memory Networks (1)
- Machine Learning (1)
- Motion control (1)
- Multimodal (1)
- Networking (1)
Articles 1 - 7 of 7
Full-Text Articles in Computer Engineering
Behavioral Biometrics-Based Continuous User Authentication, Sanket Vilas Salunke
Behavioral Biometrics-Based Continuous User Authentication, Sanket Vilas Salunke
Electronic Thesis and Dissertation Repository
The field of cybersecurity is exploring new ways to defend against cyber-attacks, including a technique called continuous user authentication. This method uses keystroke (typing) data to continuously match the user's typing pattern with patterns previously recorded using artificial intelligence (AI) to identify the user. While this approach has the potential to improve security, it also has some challenges, including the time it takes to register a user, the performance of machine learning algorithms on real-world data, and latency within the system. In this study, the researchers proposed solutions to these issues by using transfer learning to reduce user registration time, …
A Framework For Stable Robot-Environment Interaction Based On The Generalized Scattering Transformation, Kanstantsin Pachkouski
A Framework For Stable Robot-Environment Interaction Based On The Generalized Scattering Transformation, Kanstantsin Pachkouski
Electronic Thesis and Dissertation Repository
This thesis deals with development and experimental evaluation of control algorithms for stabilization of robot-environment interaction based on the conic systems formalism and scattering transformation techniques. A framework for stable robot-environment interaction is presented and evaluated on a real physical system. The proposed algorithm fundamentally generalizes the conventional passivity-based approaches to the coupled stability problem. In particular, it allows for stabilization of not necessarily passive robot-environment interaction. The framework is based on the recently developed non-planar conic systems formalism and generalized scattering-based stabilization methods. A comprehensive theoretical background on the scattering transformation techniques, planar and non-planar conic systems is presented. …
Efficient Discovery And Utilization Of Radio Information In Ultra-Dense Heterogeneous 3d Wireless Networks, Mattaka Gamage Samantha Sriyananda
Efficient Discovery And Utilization Of Radio Information In Ultra-Dense Heterogeneous 3d Wireless Networks, Mattaka Gamage Samantha Sriyananda
Electronic Thesis and Dissertation Repository
Emergence of new applications, industrial automation and the explosive boost of smart concepts have led to an environment with rapidly increasing device densification and service diversification. This revolutionary upward trend has led the upcoming 6th-Generation (6G) and beyond communication systems to be globally available communication, computing and intelligent systems seamlessly connecting devices, services and infrastructure facilities. In this kind of environment, scarcity of radio resources would be upshot to an unimaginably high level compelling them to be very efficiently utilized. In this case, timely action is taken to deviate from approximate site-specific 2-Dimensional (2D) network concepts in radio resource utilization …
Anonymization & Generation Of Network Packet Datasets Using Deep Learning, Spencer K. Vecile
Anonymization & Generation Of Network Packet Datasets Using Deep Learning, Spencer K. Vecile
Electronic Thesis and Dissertation Repository
Corporate networks are constantly bombarded by malicious actors trying to gain access. The current state of the art in protecting networks is deep learning-based intrusion detection systems (IDS). However, for an IDS to be effective it needs to be trained on a good dataset. The best datasets for training an IDS are real data captured from large corporate networks. Unfortunately, companies cannot release their network data due to privacy concerns creating a lack of public cybersecurity data. In this thesis I take a novel approach to network dataset anonymization using character-level LSTM models to learn the characteristics of a dataset; …
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Electronic Thesis and Dissertation Repository
Electricity load forecasting has been attracting increasing attention because of its importance for energy management, infrastructure planning, and budgeting. In recent years, the proliferation of smart meters has created new opportunities for forecasting on the building and even individual household levels. Machine learning (ML) has achieved great successes in this domain; however, conventional ML techniques require data transfer to a centralized location for model training, therefore, increasing network traffic and exposing data to privacy and security risks. Also, traditional approaches employ offline learning, which means that they are only trained once and miss out on the possibility to learn from …
Learning Analytics For The Formative Assessment Of New Media Skills, Negar Shabihi
Learning Analytics For The Formative Assessment Of New Media Skills, Negar Shabihi
Electronic Thesis and Dissertation Repository
Recent theories of education have shifted learning environments towards student-centred education. Also, the advancement of technology and the need for skilled individuals in different areas have led to the introduction of new media skills. Along with new pedagogies and content, these changes require new forms of assessment. However, assessment as the core of learning has not been modified as much as other educational aspects. Hence, much attention is required to develop assessment methods based on current educational requirements. To address this gap, we have implemented two data-driven systematic literature reviews to recognize the existing state of the field in the …
Autonomous Rock Segmentation From Lidar Point Clouds Using Machine Learning Approaches, Lauren E. Flanagan
Autonomous Rock Segmentation From Lidar Point Clouds Using Machine Learning Approaches, Lauren E. Flanagan
Electronic Thesis and Dissertation Repository
Rover navigation on planetary surfaces currently uses a method called blind drive which requires a navigation goal as input from operators on Earth and uses camera images to autonomously detect obstacles. Images can be affected by lighting conditions, are not highly accurate from far distances, and will not work in the dark; these factors negatively impact the autonomous capabilities of rovers. By improving a rover's ability to autonomously detect obstacles, the capabilities of rovers in future missions would improve; for example, enabling exploration of permanently shadowed regions, and allowing faster driving speeds and farther travel distances. This thesis demonstrates how …