Computing, School of
The School of Computing has developed its program through research and scholarship and has become one of the leading establishments in its field. The School is in the process of expanding, particularly in the areas of software design and engineering, and biomedical computing.
This community includes research outputs produced by faculty and students. Submitting works to QSpace may enable compliance with the Tri-Agency Open Access Policy on Publications.
When you submit your work to QSpace, you retain copyright and grant the Library a non-exclusive license to distribute and preserve. Works are open access unless restricted by the creator.
Collections in this community
Recent Submissions
-
Towards Bridging the Navigation Gap in Ultrasound-Guided Prostate Biopsy
Global disparities in access to advanced imaging modalities and navigational systems have exacerbated existing differences in prostate cancer diagnosis and prognosis worldwide. As a result, a clear navigational gap has ... -
Automated classification of electrosurgical cautery state
Introduction: In computer assisted surgery, it is sometimes necessary to detect when an activated electrosurgical tool comes into contact with a patient, known as the energy event. By continuously tracking the electrosurgical ... -
Software Ecosystem Sustainability, a Socio-Technical Perspective
The last decade has seen a plethora of large-scale software ecosystems (SECOs) developed by distributed teams and organizations dispersed across the globe. Despite the growing success of these SECOs, many questions remain ... -
Enriching User Experience for Human-Vehicle Interactions using E-textiles
Future vehicles are envisioned to enable much more functions than mere transportation, and---with the rise of automated vehicles---cars will be living spaces that support an array of non-driving related activities (NDRAs) ... -
Automated Histological Labeling of Mass Spectrometry Imaging
Registration of histological images to mass spectrometry imaging is a way to automatically align histological structure and metabolic function in a single coordinate frame. In a mass spectrometry image, each pixel is a ... -
Survival Time Prediction with Radiographic Images for Primary and Metastatic Liver Cancers
Incidence and mortality of primary and metastatic liver cancers are rising worldwide, and have poor prognosis due to high recurrence rates. Prognostic biomarkers of specific patterns of disease progression are critical to ... -
TRACKED 3D ULTRASOUND NAVIGATED LIVER BIOPSY PROCEDURE WITH REGISTERED TOMOGRAPHIC SCANS
Purpose: When lumps are found in the liver a liver biopsy is commonly used to help diagnose and identify the lumps. A 2D ultrasound is often used to guide such a procedure as ultrasound guidance has been shown to improve ... -
Service Provisioning at the Network Edge - A VNF-Sharing Approach
The next generation of mobile networks (5G) is expected to address the performance requirements of various use cases in different industries, including ultra-reliable low latency communication (URLLC). The demand for URLLC ... -
Towards the Development of Cost-Effective Decentralized Applications: An Investigation of Transaction Processing Times on the Ethereum Blockchain Platform
Ethereum is one of the most popular blockchain platforms for the development of blockchain-powered applications (i.e. ÐApps). When engineering ÐApps, developers need to translate requests captured in the frontend of their ... -
Dynamic Reinforcement Learning-based Resource Allocation For Grant-Free Access
Cellular networks have evolved to deliver high-speed broadband services to support the requirements of IoT applications, which demand high speed, low latency, and massive capacity. A primary market goal is to provide support ... -
Avionics Network Anomaly Detection through True-Skip Learning
MIL-STD-1553 is a communication bus that has been used by many military avionics platforms such as the F-15 and F-35 fighter jets for almost 50 years. Recently, it has become clear that the lack of security on MIL-STD-1553 ... -
Spatiotemporal Analysis on Distributed Task Offloading in Extreme Edge Devices
With the rapid development of the Internet of Things (IoT), the number of smart devices connected to the Internet is exponentially increasing, resulting in large-scale data and inadequate resources, which has caused high ... -
STUDYING THE OVERHEAD AND CROWD-SOURCED RISK ASSESSMENT STRATEGY OF DEPENDENCY MANAGEMENT BOTS
As today's software systems are increasingly built with dependency relationships, where a client package makes use of a specific version of a provider package, these client packages must effectively manage their dependencies. ... -
Mobile Malware Detection and Mitigation
As the number of discovered mobile malicious programs increases every year, the pieces of malware are becoming more advanced, and attacks are becoming more complex. Hence, it is critical to enhance mobile malware mitigation ... -
Towards Physiologically-Responsive Interactive Garments with Machine Learning Techniques
Emotional experiences shape our lives every day. Negative emotions can impact not only our mood but also our biological signals, overall health, and wellness, especially if they are not addressed. Emotion-regulation and ... -
Multi-Orchestrator Mobile Edge Learning: Designing Energy-Efficient Task Allocation and Incentive Schemes
Mobile Edge Learning (MEL) is a decentralized collaborative learning paradigm that features distributed training of Machine Learning (ML) models over resource-constrained edge devices (e.g., Internet of Things (IoT) devices). ... -
Discrete Time-Series Clustering and Linear Temporal Logic Delineation
The collection of information in this data-driven world has become paramount to the way businesses and individuals interact with society. From personal wearable technology to weather prediction, sales forecasting, and ... -
ReViSe: An End-to-End Framework for Remote Measurement of Vital Signs
Photoplethysmography (PPG) is a fast, inexpensive and convenient method of collecting biometric data from fingertip videos. Remote Photoplethysmography (rPPG) is a contactless method to remotely calculate vital signs from ... -
Clustering Mass Spectrometry Data Using Variational Autoencoders
Mass spectrometry is an analysis technique used to investigate the molecular profile of both biological and non-biological samples. Mass spectrometry imaging (MSI) allows for the spatial mapping of these molecules directly ... -
Methods for Low Footprint Intrusion Detection Using Ensemble Learning
Machine learning has rapidly become the state-of-the-art solution to problems in many areas of computing such as vision and natural language processing. In the intrusion detection domain, machine learning-based techniques ...
RSS 1.0