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Towards deep learning models for automatic computer program grading
(2023-04-01)
Automatic grading of computer programs has a great impact on both computer science education and the software industry as it saves human evaluators a tremendous amount of time required for assessing programs. However, to ...
Palatable game development: lessons learned from Foodbot Factory, accessibility, and audio games
(2023-04-01)
To address a lack of serious game work focusing on the development itself, this thesis describes recommendations for developers based on the development of Foodbot Factory, a nutrition-based serious game. Additionally, to ...
Java lock contention antipatterns and their detection within Java code
(2023-04-01)
Java Based Multithreaded programs are used in a wide variety of applications and consequently many developers are required to create code designed for synchronized environments. However, finding problems in synchronized ...
Effects of per-and polyfluoroalkyl substances (PFAS) on the freshwater gastropod (Planorbella pilsbryi) in the laboratory and in situ integrating a multi-omic approach
(2023-09-01)
Per- and polyfluoroalkyl substances (PFAS) are anthropogenic chemicals that are globally used in consumer and industrial applications. Specifically, perfluorooctane sulfonate (PFOS) has been under scrutiny due to its ...
Towards improving the usability of system-assigned PINs: can implicit learning techniques help?
(2023-08-01)
Personal Identification Numbers (PINs) are widely used for automated teller machines (ATMs), computers, mobile devices, debit cards, and credit cards. People tend to choose easy-to-recall PINs that are related to important ...
PiXi: an approach to nudge secure password creation
(2023-04-01)
Passwords, a first line of defense against unauthorized access, must be secure and memorable. However, people often struggle to create secure passwords they can recall. To address this problem, we design Password inspiration ...
Subgraph classification through neighborhood pooling
(2023-06-01)
Subgraph classification is an emerging field in graph representation learning where the task is to classify a group of nodes (i.e., a subgraph) within a graph. Graph neural networks (GNNs) are the de facto solution for ...
Scalable subgraph representation learning through simplification
(2023-06-01)
Link prediction on graphs is a fundamental problem. Subgraph representation learning approaches (SGRLs), by transforming link prediction to graph classification on the subgraphs around the links, have achieved state-of-the-art ...
An investigation into the use of ConvNext within IICS/IIDS framework for person Re-ID
(2023-05-01)
In this thesis, we explore the integration of ConvNeXt, a CNN-based network inspired by vision transformers, into the Intra and Inter Camera Similarity (IICS) and Intra and Inter Domain Similarity (IIDS) frameworks for ...
Preferential proximal policy optimization in reinforcement learning
(2023-12-01)
The Proximal Policy Optimization (PPO), a policy gradient method, excels in reinforcement learning with its ”surrogate” objective function and stochastic gradient ascent. However, PPO does not fully consider the significance ...