Graduate Projects (Computer Science)
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Item TocabiLab: A mass parallel capable torque controlled robot training framework(2025) Fang, Zhixin; Haworth, BrandonRobotic deep RL tasks are intrinsically hard to parallelize, as they usually require cooperation between the RL agent, the simulator and the physics engine. Context barriers can be hard to cross between those systems, making device-host transfer costs during training a challenge. Furthermore, the rapidly evolving world of machine learning also makes integration increasingly difficult for researchers, as incorporating a new learning algorithm usually requires huge engineering effort. TocabiLab is developed as an extension to NVIDIA Isaac Lab with the capability of conducting GPU-native robotics deep RL tasks. Its unified API inherited from Isaac Lab reduces the difficulty of integration, as well as enabling data to be swiftly passed between components at a large scale, accelerating training under computation intensive scenarios. This project report describes the novel architecture applied in the proposed system and a set of experiments designed upon a previously published research to validate the system’s correctness, efficiency and versatility. Evaluation result shows that the system is capable of handling more than 300% load than the industry standard systems while providing comparable performance.Item A prototype architecture for interactive 3D maps on the web(2024) Liu, Ting; Coady, YvonneVirtual 3D city models offer detailed 3D representations of urban space and serve in various fields, such as urban planning, architecture, navigation, and environmental simulation. With the advancement of technologies such as photogrammetry and laser scanning, the scale of 3D city models has increased significantly, making it a challenge to transmit and visualize such large datasets for sharing purposes. The development of advanced web technologies and the emergence of WebGL has made it possible to render and share large-scale 3D city models on the Internet. In addition, the introduction of game engines has further enhanced the simulation and interactive functions of 3D GIS applications. In this project, the exploration focused on using and integrating WebGL-based rendering tools to visualize large 3D city models, providing a portal where users can navigate and interact with urban scenarios from different perspectives. The architecture utilized 3DCityDB for tiling and format conversion of 3D models, 3D Web Client/Cesium.js virtual globe for loading large-scale tiled data, and Babylon.js to achieve interactive functions and environmental simulation. A GridMap mechanism was proposed to solve the problem of loading a large number of models with geographic coordinates in the Babylon scene. Test results show that this mechanism can maintain effective loading efficiency. Especially when the size of the dataset grows significantly, loading time and memory consumption will not increase, and FPS can also be maintained at a high level to ensure smooth interaction. This study expands the feasibility of applying 3D GIS data in web-based game engines through enhanced interactivity and simulation.Item Design and analysis of GPU algorithms(2024) Zhao, Heng; Chester, SeanIn this industrial project, we summarized the main characteristics of CPU-GPU heterogeneous system architectures. we then developed an analysis model focused on GPU parallel algorithms. Lastly, we developed two novel GPU algorithms for the decremental reachability problem with different approaches and analyzed them in our model. After a thorough analysis by algorithm designers, the results can be compared within systems to determine which algorithms are practically efficient.Item k-edge Connected Components in Graphs(2024) Mousavi, Azadehsadat; Srinivasan, Venkatesh; Thomo, AlexA k-edge-connected component (KECC) is a group of vertices in a graph G(V, E) where every pair of vertices has at least k edge-disjoint paths between them. This research delves into the detection and analysis of KECCs within graphs, presenting algorithms and thoroughly evaluating their performance. The study introduces algorithms tailored to find KECCs for a given value of k. One such algorithm, known as the fix-k algorithm, exhibits a time complexity of O(V^2.E^2 ). By leveraging various maximum flow algorithms and exploiting properties of k-edge connectivity, we optimize this algorithm to perform E times faster, resulting in a new approach with time complexity of O(V^2.E). Further enhancements are achieved through randomization, leading to an algorithm with an improved time complexity of O(V^3.ln(V)^O(1)). Additionally, we identify another algorithm with a time complexity of O(V.E^{1+o(1)} ). Moreover, algorithms are proposed to find all KECCs in a graph G(V, E) for all values of 1 ≤ k ≤ V . It is demonstrated that for any graph G(V, E), there exists a threshold value h, where for all k ≥ h, KECCs are singletons. An efficient algorithm is devised to determine this h in O(log(V )) time, which significantly impacts the all-k problem, allowing us to focus solely on finding KECCs for 1 ≤ k < h. This approach yields an algorithm with a time complexity of O(h ∗ O(Fix-k algorithm)) to find all KECCs. Additionally, another algorithm with a time complexity of O(V^2.E^2) is presented, which can be further optimized to achieve time complexities of O(V^2.E), O(V^3.ln(V )^O(1)), and O(V.E^{1+o(1)}). The insights gained from meticulous implementation and experimentation shed light on the behavior of these algorithms across various graph structures and scenarios.Item An Exploratory Study of Data Physicalization Using Household Objects(2024-03-20) Ramesh, Shanker; Somanath, Sowmya; Perin, CharlesWe explore people’s perceptions and ideas regarding creating data physicalizations using household objects such as chairs, flower pots, and photo frames to enable data-driven self-reflection. By conducting a sketching-based qualitative study with 11 participants we identified styles of physical encoding participants used, strategies for creating physicalizations they employed, and techniques for constructing physicalizations they relied on. From the study results we contribute i) a bottom-up list of physical variables people might use for different data types, ii) a comparison between the theory about visual variables and the empirical use of physical variables, iii) an identification of the need for flexible taxonomies for physical representations, and iv) a discussion of the relationship between social pressure and the location of physical representations in the household.Item Unified User Interface Development for Cross- Disciplinary Scientific Computing Applications(2023-11-27) Shah, Prerak; Schneider, Dr. TeseoIn this study, we create a cross-platform unified user interface for general-purpose scientific computing. Our project work is guided by the intention to face the growing importance of scientific computing, especially in the field of geometric computing. Making user visual interfaces has remained a non-trivial task, even with the swift advancement of computational tools and their incorporation into other fields. The ability to combine developer integration features with user accessibility is something that many current systems struggle with. Finding out whether it is possible to create a single user interface that encompasses all of the primary paradigms of scientific computing and allows developers to easily integrate their code bases while still being understandable to users in unrelated professions is the main purpose of this project. In order to achieve this, the suggested user interface solution makes use of the cross-platform compatibility and stability offered by web-based applications. By leveraging a robust ecosystem of TypeScript and JavaScript libraries, the user interface (UI) operates within mainstream browsers and benefits from the stability of browsers such as Chrome. The project also presents a novel strategy utilising an on-site Representational State Transfer (REST) server and tackles the challenging problem of cross-platform functionality. This server is in charge of binary execution, shape conversion (particularly for geometric objects), file storage, and query handling. The ultimate goal is to create a general interface specification protocol and a user interface that can be customised to meet the specific needs of different scientific computing projects, even those that support dynamic components.Item A Conceptual Design: The Verification of QIR’s Generic Quantum Optimization Passes(2023-08-30) Naghavi, Paria; Weber, JensThis report outlines the design of a verification system for QIR quantum optimization passes using Vellvm interpreter, along with QWIRE semantics and memory model. The primary objective is to establish a foundation for future advancements in quantum optimization and verification techniques. The system focuses on a small circuit in a one-qubit system but can be scaled up for more complex analytics and optimization passes in QAT. The design includes three components: the QIR input, Vellvm parser, and verification tools of QWIRE. The input consists of the QIR quantum blocks before and after the optimization pass. The parser utilizes QWIRE semantics to map the QIR code to Coq objects and types, generating a Coq AST for analysis. The verification is performed by Coq's proof assistant, checking for well-formedness and equivalence of density matrices from the QIR code blocks corresponding to pre and post quantum optimization pass application. The design can be extended to other generic or targeted quantum transformations in QAT, including target-specific gate merging. The overall goal is to provide an agnostic and hybrid-compatible verification system that can improve the reliability of quantum computations on diverse hardware platforms.Item CADConverter-For Converting Complex CAD files into HDF5 Format(2023-08-29)In this paper, we offer a very effective approach for extracting data from Computer- Aided Design And Manufacturing (CAD/CAM) step files and converted them to the self-descriptive and open-source HDF5 format. This format provides for the seamless integration of data and metadata inside a single file, making it ideal for dealing with complex data. The difficulties associated with converting CAD files between applications and the sophisticated data organisation inside multiple CAD file formats have motivated our research. The International standard ISO 10303 or STEP (’STandard for the Exchange of Product Model data’) addresses the format complexity and CAD data conversion problem between different computer-aided design (CAD) systems. We reviewed current CAD datasets like ABC and Fusion360 for geometrical data processing and created an algorithm that converts CAD models to open-source a human-readable format to feed deep learning algorithms directly and hence eliminating the requirement for third-party software for file conversions will be boosting the efficiency of CAD data administration and processing. To do this, we employ a method that combines data pre-processing as well as the development of an algorithm that converts around one million CAD models to the HDF5 format and uses the derived data for a number of applications, including machine learning and data analysis. The findings of the study lead to a better understanding of CAD data processing procedures and establish the framework for future research and development and integrate the converted dataset with PyTorch and TensorFlow to address current CAD system constraints,such as the limitations of standard neutral 3D CAD file formats that are difficult to understand. It opens the way for more efficient and simplified procedures in CAD-intensive sectors.Item CrowdLabs: A platform for human behaviour and perception studies(2023-08-29) Parikh, Kunal; Haworth, BrandonAdvancements in technology encourage researchers to decipher several intricate conceptions such as human perception and behavioral studies. Though engineering science supports scientists, it in turn demands enormous efforts from them. Therefore, the necessity for a system that reduces the academicians’ time and toil becomes inevitable. The proposed system – CrowdLabs allows the researchers to conduct a wide variety of human experiments and simulations and can scale up to capture fast-flowing data streams without them worrying about most of the underlying engineering concerns. The apparatus consists of two major traits: The experimenter who creates new trials and collects several forms of data for their studies, and the participants who take part in these experiments. This modular framework offers a minimal backend for different perspective controllers, data collection, and control to the scientists for loading and managing their experimental designs, repetition of scenes, randomizing sequences, and integrating training through a simple interface. The system was assessed for an interactive experiment to determine the system's capability to conduct a wide variety of complex human perception and behavior experiments. Subsequently, the system’s performance was evaluated for CPU, GPU, memory, and frame rates. This analysis indicated that the apparatus was responsive and robust for all the experiment scenarios. Furthermore, the system was evaluated extensively and several avenues for future work have been identified.Item Zero Trust Network Architecture(2023-07-04) Srinivasan, Priyadharsini; Wu, KuiIn light of the rapid advancement of digital technology and the increasing popularity of cloud- based services, it has become necessary to revisit traditional approaches to cybersecurity. Businesses are facing ever-more sophisticated cyberthreats, both from within and outside their networks, which have exposed the limitations of perimeter-based security solutions. The zero-trust architecture (ZTA) has emerged as a promising model for cybersecurity, fo- cusing on resource security instead of network perimeter protection. This project provides a comprehensive overview of ZTA, including its fundamental principles and the Zero Trust Network Access (ZTNA) architecture. The project focuses on an in-depth analysis of Cisco Duo’s Multi-Factor Authentica- tion (MFA) system using Wireshark to capture network traffic on a local PC. This analysis provides a comprehensive understanding of the user identity verification process using mul- tiple authentication factors. Additionally, the project discusses the driving forces behind the adoption of ZTA, as well as the challenges and opportunities that it presents. The project explores real-world ZTA implementations, including Google’s BeyondCorp and Microsoft’s Zero Trust Network Architecture. The application of ZTA in various fields, including big data, cloud computing, and the Internet of Things (IoT), is also investigated. The project concludes by discussing potential future research directions in ZTA, empha- sizing the need for more complex trust algorithms, continuous verification and authentication techniques, and standardized frameworks for applying ZTA in various sectors and use cases. Overall, this project provides a comprehensive and detailed examination of the zero-trust architecture, its applications, and its potential for improving cybersecurity in an increasingly digitized world.Item Agile Requirements Change Management Model For Global Software Development(2023-05-22) Koulecar, Neha Sheilesh; Damian, DanielaWe propose a comprehensive and robust agile requirements change management (ARCM- GSD) model that addresses the limitations of existing models and is tailored for agile software development in the global software development paradigm. To achieve this goal, we conducted an exhaustive literature review and an empirical study with RCM industry experts. Our study evaluated the effectiveness of the proposed RCM model in a real-world setting and identified any limitations or areas for improvement. The results of our study provide valuable insights into how the proposed ARCM-GSD model can be applied in agile global software development environments to improve software development practices and optimize project success rates.Item SmartCAD For Exploring Complex CAD files in YAML Format(2023-04-28) Madduri, Vamsi Naga Sai Chandra; Schneider, TeseoIn this study, we develop an efficient approach for sampling and extracting data from Computer-Aided Design And Manufacturing (CAD/CAM) files using an open-source YAML format. Our project is driven by the challenges encountered while performing file conversions between multiple CAD software and the complex data organization within CAD file structures, including proprietary, Model-Based Definition (MBD), and non-MBD CAD files. By employing the YAML format for CAD files, our approach eliminates the need for third-party software for file conversions, reduces compatibility issues, and improves the efficiency of CAD data management and processing. To achieve this, we implement a methodology involving preprocessing, feature extraction, and computing winding numbers from the YAML-formatted CAD files. The proposed method serves as a foundation for a future project that will convert approximately one million CAD models into the YAML format and leverage the extracted data for various purposes, such as model learning and data analysis. The findings of this study contribute to a deeper understanding of CAD data processing techniques and provide a foundation for further research and development. Our work addresses the current limitations of CAD systems, including the restrictions of conventional neutral 3D CAD file formats. It paves the way for more effective and streamlined workflows in industries that rely heavily on CAD technology.Item IoT Security Using Machine Learning Methods(2023-04-17) Hosseini Goki, Seyedamiryousef; Wu, KuiThe rapid growth of internet-connected devices has made robust cybersecurity measures essential to protect against cyber threats. IoT cybersecurity includes various methods and technologies to secure internet-connected devices and systems from cyber attacks. The unique nature of IoT devices and systems poses several challenges to cybersecurity, including limited processing power, minimal security features, and vulnerability to attacks like DoS and DDoS. Cybersecurity strategies for IoT include encryption, authentication, access control, and threat detection and response, which utilize machine learning and artificial intelligence technologies to identify and respond to potential cyber attacks in real-time. The report discusses two projects related to cybersecurity in IoT environments, one focused on developing an intrusion detection system (IDS) based on deep learning algorithms to detect DDoS attacks, and another focused on identifying potential abnormalities in IoT networks using a fingerprint. These projects highlight the importance of prioritizing cybersecurity measures to protect against the growing number of cyber threats facing IoT devices and systems.Item An exploratory study regarding the ease-of-use, comprehensibility, and usefulness of the Empirical Standards Checklists(2022-12-21) Cupryk, Cassandra; Storey, Margaret-Anne; Larios, EnriqueContext/Background: Novice researchers have stated that being provided with guidelines for reviewing empirical research papers would be helpful. The Empirical Standards Checklist Generator is a tool that can generate a variety of Empirical Standards Checklists. An Empirical Standards Checklist contains the core criteria that can be used to review Software Engineering empirical papers. Moreover, my exploratory study aims to determine whether novice researchers could benefit from using the Empirical Standards Checklists to help them review Software Engineering empirical papers. Objective: To investigate whether novice researchers perceive the Empirical Standards Checklists as easy to understand, easy to use, and useful for reviewing empirical papers. Methods: Seven participants completed a survey to evaluate the Empirical Standards Checklists and then participated in a group discussion. During the survey, the participants used the appropriate Empirical Standard Checklists to review a qualitative survey paper and a repository mining paper. They then highlighted the items from the Empirical Standards Checklists that were difficult to comprehend. The participants also answered survey questions that exposed their perceptions of the Empirical Standards Checklists' comprehensibility, ease-of-use, and usefulness. Results: The majority of the participants had positive perceptions of the Empirical Standards Checklists' comprehensibility, ease-of-use, and usefulness. Conclusion: This exploratory study demonstrates that the Empirical Standards Checklist is a promising new tool for reviewing Software Engineering empirical research papers.Item Data Visualization of COVID-19 in Canada(2022-09-30) Pan, Suyin; Wu, Kui; Thomo, AlexData visualization has been essential in fighting the COVID-19 pandemic in the past two years. Interactive dashboards helped people track, analyze, and predict the spread of the disease effectively. In this project, we created tools for visualizing the COVID-19 data in Canada to demonstrate how vaccination helped combat the pandemic, what group of people were impacted the most, and what the variant of concern was in each wave.Item User Concern in App Reviews, a study of perceived privacy violation among user sentiments and other contribute factors(2022-05-02) Cheng, Yue; Damian, Daniela; Ernst, NeilPrivacy, a significant factor in software usage, also provides software developers with additional insights into how applications can be improved. However, it is a delicate matter that peeks into user behaviour to the amount of information they are willing to share. With the rise of mobile applications, another concerning factor of user information collection also became prominent. The existence of user chatter on the Google app store can help identify whether privacy concern is problematic or not. However, little research has been conducted to study privacy violations and their contributing factors. In this project, we proposed using an LDA based privacy identification model that assesses the factors relating to user concerns with privacy matters on the Google App Store user reviews. A total of 45,114,727 rows of data were scraped from the Google play store, which were later filtered and processed into workable data. With the help of the Gensim LDA library, we can identify a coherence score of 0.604 and eight topics of various subjects. We later arranged these subjects into their corresponding categories, which could be used to analyze why specific privacy terms are more sensitive while others are not.Item Abstract and Metaphoric visualization of emotionally sensitive data(2022-04-28) Malik, MonaStandard visualizations such as bar charts and scatterplots, especially those representing qualitative, emotionally sensitive issues, fail to build a connection between the data that the visualization represents and the viewer of the visualization. To address this challenge, the information visualization community has become increasingly interested in exploring creative visualization techniques that could potentially help viewers relate to the suffering and pain in emotionally sensitive data. We contribute to this open question by investigating whether visualizations that rely on metaphors (i.e., that involve existing mental images such as a tree or a person image) with some emotional connection can foster viewers’ empathy and engagement with the data. Specifically, we conducted an empirical study in which we compare the effect of visualization type (metaphoric and abstract) on people’s engagement and empathy when exposed to emotionally sensitive data (data about sexual harassment in academia). We designed a metaphoric visualization that relies on the metaphor of a flower symbolizing life, beauty, and fragility which might help the viewers to relate to the victim, build some emotional connection, and an abstract visualization that relies on purely geometric forms with which people should not have any existing emotional connection. In our study, we found no clear difference in engagement and empathy between metaphoric and abstract visualization. Our findings indicate that female participants were slightly more engaged and empathic with both visualizations compared to other participants. Additionally, we learned that measuring empathy in a data visualization is a complex task. Informed by these findings on how people engage and empathize with metaphoric and abstract visualization, newer and improved visualization and experiences can be developed for similar emotionally sensitive topics that are emotionally charged and fear-provoking.Item Mining GitHub Issues for Bugs, Feature Requests and Questions(2021-12-14) Jokhio, Marvi; Ernst, Neil A.The maintenance and success of software projects highly depend on updated and bug-free code. To effectively process hundreds of daily new issues in big software projects, tools like issue tracking systems (ITS) play an important role but the critical aspect for issue processing and triaging needs assignment of accurate labels to determine their type (e.g., bug, feature, question and so on). This labelling is a time-consuming and tedious task and hence needs automated solutions. Automatic classification of issues is a challenging task due to semantically ambiguous text which contains code, links, package and method names, commands etc. In this work, we propose supervised and unsupervised mining techniques for GitHub issues using text only. In the supervised machine learning technique, we show that our model can classify issues in the bug, feature, and question classes with 86.7% AUC scores. We also proposed a technique to extract topics from GitHub issues using Latent Dirichlet Allocation (LDA) to analyze the type of development issues faced by developers.Item Research on modern computer architecture optimization techniques: implementation and measurements for big data processing(2021-09-11) He, Yan; Weber, JensWith the rapid development of big data computing, our programmers need to improve the efficiency of big data processing. In our daily development process, we normally focus on bug-free deployment and often overlook another aspect of software engineering, performance optimization. Actually, a great deal of programming effort is required to achieve good performance. Many techniques are having the potential to significantly improve software performance. To achieve efficiency, I firstly conclude some optimization techniques dealing with memory-bound issues then moving to parallel programming to deal with compute-bound problems. As an example, we apply as many techniques that I mention in the report to a popular algorithm implementation, PageRank based on C++17. By providing constant feedback from performance measurement and profiling, we can see a drastic speed up after implementing all these optimization techniques. I also experiment with a real-world graph dataset provided by IMDb which can rank the top movies, and also evaluate performance before and after optimization. This report hopefully can provide potential future direction towards applying different optimization techniques to various big data processing applications.Item Design and implementation of a safe bi-directional document exchange system in health information systems.(2021-04-27) Tyagi, Aakash; Weber, JensPresent-day health care systems are information-dense and progressively relying on computer- based information systems. Unfortunately, many of these information system’s use is predominantly restricted to the collection and retrieval of patient records. The failure to digitally communicate and transfer medical record information to other health information systems is undoubtedly a major barrier to efficient patient care and other clinical decision making, and the interoperability between heterogeneous systems still remains a challenge even with decades of investment. The implementation of a safe bi-directional document exchange system is a part of enhancing interoperability by providing a safe messenger system to support some of the core interaction medical documents. Lack of interoperability can also jeopardize patient safety and led to technology-related medical accidents. Hence, the project also focuses on the safety aspect of the system and provides an in-depth hazard analysis along with the implementation of a safety monitoring system to notify users about unexpected system failures.