Engineering Commons^™

Data Provenance Via Differential Auditing, Xin Mu, Ming Pang, Feida Zhu

Research Collection School Of Computing and Information Systems

With the rising awareness of data assets, data governance, which is to understand where data comes from, how it is collected, and how it is used, has been assuming evergrowing importance. One critical component of data governance gaining increasing attention is auditing machine learning models to determine if specific data has been used for training. Existing auditing techniques, like shadow auditing methods, have shown feasibility under specific conditions such as having access to label information and knowledge of training protocols. However, these conditions are often not met in most real-world applications. In this paper, we introduce a practical framework for …

Setransformer: A Transformer-Based Code Semantic Parser For Code Comment Generation, Zheng Li, Yonghao Wu, Bin Peng, Xiang Chen, Zeyu Sun, Yong Liu, Paul Doyle

Conference Papers

Automated code comment generation technologies can help developers understand code intent, which can significantly reduce the cost of software maintenance and revision. The latest studies in this field mainly depend on deep neural networks, such as convolutional neural networks and recurrent neural network. However, these methods may not generate high-quality and readable code comments due to the long-term dependence problem, which means that the code blocks used to summarize information are far from each other. Owing to the long-term dependence problem, these methods forget the previous input data’s feature information during the training process. In this article, to solve the …

Modeling The Effect Of The Covid-19 Pandemic On Azithromycin Prescription In General Practices Across The Uk, Oluwasegun Isaac Daramola

altREU Projects

In the early months of the COVID-19 pandemic, it was reported that some antibiotics were prescribed as a remedy for viral treatment and prophylaxis based on non-randomized, uncontrolled short clinical trials. A major antibiotic consulted being Azithromycin; a broad-spectrum macrolide selected based on its immunomodulatory effects in chronic inflammatory lung diseases, with a seasonal prescription increase of 21.5% in March 2020 compared to March 2019.

To analyze the effect and possible antimicrobial resistance impact of the pandemic on Azithromycin prescription across general practices in the United Kingdom (UK), this study uses a time series decomposition modeling method to compare a …

Multi-Agent Radiation Localization, Teresa Nguyen

REU Final Reports

Advancement of radiation detection technology is an ongoing process, and adjustments are made based on pre-existing conditions of radiation presence--both natural and man made. Tools that are currently used for safely detecting radiation in urban environments exist in several forms: drones, robots, or handheld radiation detection devices. This is a harm reductive way to explore radiation-infected environments while preserving human health as best as possible. In order for these autonomous platforms to successfully detect radiation sources, an algorithm needs to be created that is capable of gathering crucial data on its own with little to no human interference. Machine learning …

Computationally Efficient Strand Eddy Current Loss Calculation In Electric Machines, Alireza Fatemi, Dan M. Ionel, Nabeel Demerdash, Dave A. Staton, Rafal Wrobel, Yew Chuan Chong

Electrical and Computer Engineering Faculty Research and Publications

A fast finite element (FE) based method for the calculation of eddy current losses in the stator windings of randomly wound electric machines is presented in this paper. The method is particularly suitable for implementation in large-scale design optimization algorithms where a qualitative characterization of such losses at higher speeds is most beneficial for identification of the design solutions that exhibit the lowest overall losses including the ac losses in the stator windings. Unlike the common practice of assuming a constant slot fill factor s _f for all the design variations, the maximum s _f in the developed method is …

Computational Modeling Of Trust Factors Using Reinforcement Learning, C. M. Kuzio, A. Dinh, C. Stone, L. Vidyaratne, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

As machine-learning algorithms continue to expand their scope and approach more ambiguous goals, they may be required to make decisions based on data that is often incomplete, imprecise, and uncertain. The capabilities of these models must, in turn, evolve to meet the increasingly complex challenges associated with the deployment and integration of intelligent systems into modern society. Historical variability in the performance of traditional machine-learning models in dynamic environments leads to ambiguity of trust in decisions made by such algorithms. Consequently, the objective of this work is to develop a novel computational model that effectively quantifies the reliability of autonomous …

Generalizing Effective Spatial Bandwidth For Pole Location In Mas: The Elliptic Cylinder, James Richie

Electrical and Computer Engineering Faculty Research and Publications

The location of poles in the method of auxiliary sources for 2-D scatterers can be assisted using the effective spatial bandwidth (EBW) of the incident and scattered fields. Previously, only circular boundaries were considered. Here, EBW is extended to noncircular boundaries. Calculations presented for a cylinder with elliptical cross section verify EBW as an additional tool for pole placement for more general geometries.

A Computationally Efficient Method For Calculation Of Strand Eddy Current Losses In Electric Machines, Alireza Fatemi, Dan M. Ionel, Nabeel Demerdash, Dave A. Staton, Rafal Wrobel, Yew Chuan Chong

Electrical and Computer Engineering Faculty Research and Publications

In this paper, a fast finite element (FE)-based method for the calculation of eddy current losses in the stator windings of randomly wound electric machines with a focus on fractional slot concentrated winding (FSCW) permanent magnet (PM) machines will be presented. The method is particularly suitable for implementation in large-scale design optimization algorithms where a qualitative characterization of such losses at higher speeds is most beneficial for identification of the design solutions which exhibit the lowest overall losses including the ac losses in the stator windings. Unlike the common practice of assuming a constant slot fill factor, sf, for all …

Kicm: A Knowledge-Intensive Context Model, Fredrick Mtenzi, Denis Lupiana

Conference papers

A context model plays a significant role in developing context-aware architectures and consequently on realizing context-awareness, which is important in today's dynamic computing environments. These architectures monitor and analyse their environments to enable context-aware applications to effortlessly and appropriately respond to users' computing needs. These applications make the use of computing devices intuitive and less intrusive. A context model is an abstract and simplified representation of the real world, where the users and their computing devices interact. It is through a context model that knowledge about the real world can be represented in and reasoned by a context-aware architecture. This …