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.
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Recent Submissions
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A Machine Learning Framework for Oncological Margin Detection
Cancer is the cause of one in four deaths in North America. A common phase of early-stage oncological treatment is the surgical resection of cancerous tissue. The presence of cancer cells on the resection margin, referred ... -
Modelling Human Behaviour Based on Similarity Measurements Between Event Sequences
From a set of sequences, individual’s behavioural patterns can be identified. Using these sequences of events, the metadata available can be processed into a weighted format to improve the meaningfulness of the sequence ... -
A Voice Interactive 3-Phase Hybrid Question Answering System
The technology of Artificial Intelligence (AI) makes it possible for machines to learn from experience through data and perform tasks in a human-like way. Deep learning is a subfield of AI, which is a machine learning ... -
Asm2Seq: Explainable Assembly Code Functional Summary Generation
Technology is at the forefront of nearly every aspect of the modern world. Humans write code for technology to function as we desire, but often times little is understood about the code needed to control the computer without ... -
Anomaly Detection via Latent Variables Learned by Variational Autoencoders
Modeling normality is a popular approach to anomaly detection. Learning good models of normality and choosing appropriate ways of identifying differences from normality are critical tasks for effective anomaly detection. ... -
Nondeterministic State Complexity of Site-Directed Operations
In this thesis, we consider the nondeterministic state complexity of PCR-inspired (polymerase chain reaction) operations. Site-directed operations are used to formally describe the behavior of certain DNA (deoxyribonucleic ... -
Incremental symbolic execution of evolving state machines
(Institute of Electrical and Electronics Engineers, 2015-11-30)This paper introduces two complementary techniques, memoization-based and dependency-based incremental symbolic execution, that aim to optimize the analysis of state machine models that undergo change. We implement the two ... -
State machine antipatterns for UML-RT
(Institute of Electrical and Electronics Engineers, 2015-11-30)Software development guidelines are a set of rules which can help improve the quality of software. These rules are defined on the basis of experience gained by the software development community over time. Software ... -
Automated service composition via supervisory control theory
(Institute of Electrical and Electronics Engineers, 2016-06-23)Web services play a major role in electronic businesses and allow organizations to perform certain business activities in a distributed fashion. In some circumstances, a single service is not able to perform certain tasks ... -
An executable formal semantics for UML-RT
(Software and Systems Modeling, 2014-02-20)Software development guidelines are a set of rules which can help improve the quality of software. These rules are defined on the basis of experience gained by the software development community over time. Software ... -
Security of Short-Range Wireless Technologies and an Authentication Protocol for IoT
The number of wireless IoT (Internet of Thing) infrastructures is considerably growing as thousands of new devices are being connected everyday. This has allowed the emergence of various smart applications that have changed ... -
Caching in VANETs for Social Networking
Social media traffic constitutes the highest percentage of Internet traffic. This social media traffic is largely facilitated by mobile devices, which imposes a huge traffic load on backhaul links in 5G networks, and can ... -
NLQ INTO SQL TRANSLATION USING COMPUTATIONAL LINGUISTICS
This research discusses an automatic translation of an unstructured Natural Language Question (NLQ) into a Structured Query Language (SQL) statement. SQL is used as a Relational DataBase (RDB) interaction language with ... -
The theory of and practical consideration for ultrasound guided interventions: from phantom data to clinical studies
Cancer is one of the leading causes of death in Canada. Research in early detection is essential for improving survival rates. The current standards for diagnosis include physical examinations, chemical tests, and biopsy. ... -
Modelling Stock Market Manipulation in Online Forums
Over the past several decades, advances in technology have significantly impacted all aspects of the financial system. While it has led to numerous benefits, it has also increased the methods for manipulating the market. ... -
INTELLIGENT FRAMEWORK FOR MONITORING CROPS IN GREENHOUSES
Wireless Sensor Networks (WSNs) and Wireless Visual Sensor Networks (WVSNs) are two monitoring technologies that have the potential for use in many application domains, and both are poised for growth in many markets from ... -
STUDYING THE USE OF EXTRINSIC INCENTIVES TO SUPPORT CROWDSOURCED SOFTWARE ENGINEERING ACTIVITIES
Extrinsic incentives help attract participants to Crowdsourced Software Engineering (SE) activities (e.g., open source development and Stack Overflow contributions). There are two types of extrinsic incentives: 1) monetary ... -
UNDERSTANDING THE IMPACT OF EXPERIMENTAL DESIGN CHOICES ON MACHINE LEARNING CLASSIFIERS IN SOFTWARE ANALYTICS
Software analytics is the process of systematically analyzing software engineering related data to generate actionable insights that help software practitioners make data-driven decisions. Machine learning classifiers lie ... -
A Bootstrapped Approach for Abusive Intent Detection in Social Media Content
The proliferation of Internet connected devices continues to result in the creation of massive collections of human generated content from websites such as social media. Unfortunately, some of these sites are used by ... -
On the Maintenance of Crowdsourced Knowledge on Stack Overflow
The enormous quantity of software artifacts (e.g., code, documentations, and online discussions) created by developers are in great need for maintenance. Among software artifacts built by developers, Stack Overflow, a ...
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