Browsing by Discipline
Now showing items 21-40 of 70
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Elastic-based multi-scale graph drawing
(2012-11-10)Graph drawing is an important information visualization technique with applications in a variety of disciplines, including VLSI design, bioinformatics, geography, and social network analysis. We present a new force-directed, ... -
An enhanced passkey entry protocol for secure simple pairing in bluetooth
(2020)Bluetooth devices are being used very extensively in today's world. From simple wireless headsets to maintaining an entire home network, the Bluetooth technology is used everywhere. However, there are still vulnerabilities ... -
Enhancing machine vision using human cognition from EEG analysis
(2022)Visual classification is the perceptible/computational effort of arranging objects and visual contexts into distinct labels. Humans and machines have mastered this advanced problem in their own varied contexts. However, ... -
Exploiting semantic similarity models to automate transfer credit assessment in academic mobility
(2021)Student mobility or academic mobility involves students moving between institutions during their post-secondary education, and one of the challenging tasks in this process is to assess the transfer credits to be offered ... -
Exploration of contrastive learning strategies toward more robust stance detection systems
(2023)Stance Detection, in general, is the task of identifying the author’s position on controversial topics. In Natural Language Processing, Stance Detection extracts the author’s attitude from the text written toward an issue ... -
Exploring name-based bug detection in Python
(2024)Names of source code elements provide useful contextual information about the code and development tasks. Prior studies leverage the similarity between the names of arguments and method parameters to detect bugs that are ... -
Extracting specific text from documents using machine learning algorithms
(2018)Increasing use of Portable Document Format (PDF) files has promoted research in analyzing the files' layout for text extraction purpose. For this reason, it is important to have a system in place to analyze these documents ... -
Fairness, engagement, and discourse analysis in AI-driven social media and healthcare
(2023)This thesis addresses the critical concerns of fairness, accountability, transparency, and ethics (FATE) within the context of artificial intelligence (AI) systems applied to social media and healthcare domains. First, a ... -
Feature learning boosts network performance
(2020)Features are an important part of machine learning. Features are often the reduced-dimensional representation of input data, feature calculation, extraction, and fusion directly affect the final result of the network. ... -
Federated learning framework and energy disaggregation techniques for residential energy management
(2023)Residential energy use is a significant part of total power usage in developed countries. To reduce overall energy use and save funds, these countries need solutions that help them keep track of how different appliances ... -
From social media to expert reports: automatically validating and extending complex conceptual models using machine learning approaches
(2019)Given the importance of developing accurate models of any complex system, the modeling process often seeks to be comprehensive by including experts and community members. While many qualitative modeling processes can ... -
Harnessing generative AI for overcoming labeled data challenges in social media NLP
(2023)With the introduction of Transformers and Large Language Models, the field of NLP has significantly evolved. Generative AI, a prominent transformer-based technology for crafting human-like content, has proven powerful ... -
Hybrid deep learning with stacked dilated causal convolutions for health forecasting using multivariate time-series data
(2022)Health forecasting using time-series data facilitates preventive medicine and healthcare interventions by predicting future health events. This thesis introduces a novel hybrid deep-learning architecture for health ... -
Identifying variables affecting students' academic performance among engineering students
(2018)An essential consideration for campus administrators and faculty members is that students complete their degree with good academic grades. Being able to predict factors affecting students performance is necessary to help ... -
Improving cataract surgery procedure using machine learning and thick data analysis
(2023)Cataract surgery is one of the most frequent and safe Surgical operations are done globally, with approximately 16 million surgeries conducted each year. The entire operation is carried out under microscopical ... -
Intelligent vehicle-to-vehicle communications with importance of fairness and information freshness
(2023)Intelligent Transportation Systems (ITS) showcase cutting-edge services designed to revolutionize transportation and mobility, especially within future smart cities. These services play a pivotal role in bolstering traffic ... -
Light-weight federated learning with augmented knowledge distillation for human activity recognition
(2023)The field of deep learning has experienced significant growth in recent years in various domains where data can be collected and processed. However, as data plays a central role in the deep learning revolution, there are ... -
Lightweight deep learning for monocular depth estimation
(2021)Monocular depth estimation is a challenging but significant part of computer vision with many applications in other areas of study. This estimation method aims to provide a relative depth prediction for a single input ... -
Medical text simplification: bridging the gap between medical research and public understanding
(2023)Text Simplification is a subdomain of Natural Language Processing that focuses on applying computational techniques to modify the content and structure of the text to make it interpretable while retaining the main idea. ... -
Medical workflow design and planning using Node-Red data fusion
(2021)The space of clinical planning requires a complex arrangement of information, often not capable of being captured in a singular dataset. As a result, data fusion techniques can be used to combine multiple data sources ...
