Physical Sciences and Mathematics Commons^™

A Unified Multi-Task Learning Framework For Multi-Goal Conversational Recommender Systems, Yang Deng, Wenxuan Zhang, Weiwen Xu, Wenqiang Lei, Tat-Seng Chua, Wai Lam

Research Collection School Of Computing and Information Systems

Question generation (QG) aims to automatically generate fluent and relevant questions, where the two most mainstream directions are generating questions from unstructured contextual texts (CQG), such as news articles, and generating questions from structured factoid texts (FQG), such as knowledge graphs or tables. Existing methods for these two tasks mainly face challenges of limited internal structural information as well as scarce background information, while these two tasks can benefit each other for alleviating these issues. For example, when meeting the entity mention “United Kingdom” in CQG, it can be inferred that it is a country in European continent based on …

Learning To Ask Clarification Questions With Spatial Reasoning, Yang Deng, Shuaiyi Li, Wai Lam

Research Collection School Of Computing and Information Systems

Asking clarifying questions has become a key element of various conversational systems, allowing for an effective resolution of ambiguity and uncertainty through natural language questions. Despite the extensive applications of spatial information grounded dialogues, it remains an understudied area on learning to ask clarification questions with the capability of spatial reasoning. In this work, we propose a novel method, named SpatialCQ, for this problem. Specifically, we first align the representation space between textual and spatial information by encoding spatial states with textual descriptions. Then a multi-relational graph is constructed to capture the spatial relations and enable spatial reasoning with relational …

Duplicate Bug Report Detection: How Far Are We?, Ting Zhang, Donggyun Han, Venkatesh Vinayakarao, Ivana Clairine Irsan, Bowen Xu, Thung Ferdian, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Many Duplicate Bug Report Detection (DBRD) techniques have been proposed in the research literature. The industry uses some other techniques. Unfortunately, there is insufficient comparison among them, and it is unclear how far we have been. This work fills this gap by comparing the aforementioned techniques. To compare them, we first need a benchmark that can estimate how a tool would perform if applied in a realistic setting today. Thus, we first investigated potential biases that affect the fair comparison of the accuracy of DBRD techniques. Our experiments suggest that data age and issue tracking system choice cause a significant …

Testing Automated Driving Systems By Breaking Many Laws Efficiently, Xiaodong Zhang, Wei Zhao, Yang Sun, Jun Sun, Yulong Shen, Xuewen Dong, Zijiang Yang

Research Collection School Of Computing and Information Systems

An automated driving system (ADS), as the brain of an autonomous vehicle (AV), should be tested thoroughly ahead of deployment. ADS must satisfy a complex set of rules to ensure road safety, e.g., the existing traffic laws and possibly future laws that are dedicated to AVs. To comprehensively test an ADS, we would like to systematically discover diverse scenarios in which certain traffic law is violated. The challenge is that (1) there are many traffic laws (e.g., 13 testable articles in Chinese traffic laws and 16 testable articles in Singapore traffic laws, with 81 and 43 violation situations respectively); and …

Institute For Global Health And Development : Issue 5 - July 2023, Institute For Global Health And Development

IGHD Newsletter

• Research Highlights
• Key Publications
• IGHD in the News
• Webinars, Academics & Conferences
• ‘Choice’ Programme - Technical Advisory Group
• Welcome New Team Members
• Mark your Calendars: Upcoming Event
• Congratulations Team IGHD
• Collaborate With Us

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl

Faculty Publications

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …

Meet Me In The Middle: A Scoping Review On Understanding Adolescent Needs In Climate Communication, Gwendolyn Monica Hoff Anderson

Master's Projects and Capstones

The greatest effects of climate change are likely to be felt by youth. Young people are disproportionately affected by climate change due to their critical developmental stage and lack of power, and they experience both higher severity and prevalence of mental health issues related to climate change. Strong emotions have long been recognized as potential catalysts for action, or they may lead to paralyzing feelings of being overwhelmed. Climate communication is a critical tool to spark climate concern and encourage action. Activism, in turn, may help youth manage their anxiety about climate change. This scoping review examines emerging evidence on …

Nuclear Magnetic Resonance Studies Of Potential Environmental Contaminants Interacting With Dna, Anna Hopkins, Leah B. Casabianca

Chemistry Summer Research Program

No abstract provided.

Cryogrinding And Physical Analysis Of A Thermoplastic Polyurethane Elastomer, Timothy E. Whitesell, Marcia Reeves, David L. Helm, Joseph S. Thrasher

Chemistry Summer Research Program

No abstract provided.

Big Data For A Deep Problem: Exploring Natural Deep Eutectic Solvent (Nades) Properties Through Rdkit And Data Analytics, Grayson Weavil, Lucas B. Ayres, Carlos D. Garcia

Chemistry Summer Research Program

No abstract provided.

Supramolecular Π-Donor/Acceptor Arrays Based On Metal-Organic Cage Inclusion Complexes, Sean Hannigan, Evan Thibodeaux, Sourav Saha

Chemistry Summer Research Program

No abstract provided.

Tuning Oxo Formation Energies Using Spectator Ligands In The Mil-100 Metal Organic Framework, Victoria E. Lee, Stephen P. Vicchio, Rachel B. Getman

Chemistry Summer Research Program

No abstract provided.

Using Alginate Beads Modified With Graphite As An Effective Electrode, Madeline Mchugh, Barbara G. S. Guinati, Carlos D. Garcia

Chemistry Summer Research Program

No abstract provided.

Polymersomes As Chemotherapeutic Agents For Non-Invasive Treatment Of Glioblastoma, Tj Fletcher, Molli Garifo, Jessica Larsen, Jessica Larsen

Chemistry Summer Research Program

No abstract provided.

Effects Of Low-Energy X-Rays And Uv Radiation On Fibroblast Cells, Michelle Gorodisky, Congyue Peng, Arianna Csiszer, Delphine Dean

Chemistry Summer Research Program

No abstract provided.

Accessing Rare Heterocycles From Alkynyl Ethers And Nitrogenous Electrophiles & The Development Of Small Molecule Inhibitors Against Naegleria Fowleri Infection, James W. D. Morris, Samuel Kwain, Daniel C. Whitehead

Chemistry Summer Research Program

No abstract provided.

Dynamics Of Ionizable Polymers In Ionic Liquid (Il) Using Nuclear Magnetic Resonance Spectroscopy, Sophie Ntipouna, Hayden Sasko, Shalika D. K. Meedin, Dvora Perahia

Chemistry Summer Research Program

No abstract provided.

Halogen Bonding In Nitrogen And Iodine Compounds To Form Novel Cocrystals, Dahlia Griffin, Ann Jiang, Colin D. Mcmillen, William T. Pennington

Chemistry Summer Research Program

No abstract provided.

Stimuli-Responsive Self-Folding Bilayer Polymer Thin Films, Astrid Garcia, Dimuthu Edirisinghe, Bogdan Oliy, George Chumanov

Chemistry Summer Research Program

No abstract provided.

Combining Alginate Beads With Methylene To Create A Biosensor To Assess The Quality Of Milk, Vivien Zheng, Barbara Guinati, Carlos D. Garcia

Chemistry Summer Research Program

No abstract provided.

Development And Testing Of A New Method For Velocity-Selecting White Dwarfs From Gaia By Galactic Population, Joseph Hammill

Doctoral Dissertations and Master's Theses

The detailed processes by which spiral galaxies form remains an open question in modern cosmology. Observations of the current configuration of spiral galaxies including the Milky Way reveal thin and thick disk and halo populations which must all be accounted for in formation theories and likely have distinct ages. Using the Milky Way as an example to probe this question, we are studying the formation history of these structures.

This work details our approach to age-dating the galaxy, velocity-selecting targets from a sample of white dwarfs from the Gaia DR3 catalog that have also been age-analysed using BASE-9. BASE-9 uses …

Applications Of Environmental Dna (Edna) To Detect Subterranean And Aquatic Invasive Species: A Critical Review On The Challenges And Limitations Of Edna Metabarcoding, Sakib Tahmid Rishan, Richard Kline, Md Saydur Rahman

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

The world is struggling to solve a devastating biodiversity loss that not only affects the extinction of treasured species and irreplaceable genetic variation, but also jeopardizes the food production, health, and safety of people. All initiatives aimed to conserve biodiversity rely heavily on the monitoring of both species and populations to get accurate spatial patterns and overall population assessments. Conventional monitoring techniques, such as visual surveys and counting individuals, are problematic due to challenges in identifying cryptic species or immature life stages. Environmental DNA (eDNA) is a relatively new technology that has the potential to be a faster, non-invasive, and …

Elucidating The Structure And Regulatory Interactions Of The Hotair Non-Coding Rna And The Bacterial Rnase P. Holoenzyme, Ainur Abzhanova

Dissertations (1934 -)

RNA structures and RNA-protein interactions are studied as potential drug targets, biomarkers in cancer, and can be administered as vaccines. The cancer associated HOTAIR (HOX transcript antisense RNA) exists in higher vertebrates and interacts with chromatin remodeling enzymes. We examined the thermodynamic folding properties and structural propensity of the exonic regions of HOTAIR using biophysical methods and NMR spectroscopy. Different exons of HOTAIR contain variable degrees of structural heterogeneity. We identify one exonic region, exon 4, that adopts a stable and compact fold under low magnesium concentrations. Close agreement of NMR spectroscopy and chemical probing confirm conserved base pair interactions …

Advanced Prognostic Modeling For Breast Cancer Patients: Leveraging Data-Driven Approaches For Survival Analysis, Theophilus Gyedu Baidoo

Theses and Dissertations

Breast cancer is the second most prevalent form of cancer in women in the United States. Each year, about 264,000 cases of breast cancer are diagnosed in women and of this number, about 42,000 women lose their lives as reported by the Centers for Disease Control and Prevention. Early detection and effective treatment are crucial for improving survival rates and reducing mortality. This study aimed to explore the influential factors that may risk the survival of women with the disease and compare their predictive abilities using several error and performance metrics. The study uses a dataset from the National Cancer …

Analyzing The On Source Window Of Supernova Sn2019ejj With A Multi Layered Signal Enhancement Algorithm With Coherent Waveburst And A Convolutional Neural Network, Michael Gale Benjamin

Theses and Dissertations

Core collapse supernovae (CCSN) are highly anticipated sources of gravitational waves during the fourth observation run (O4). CCSN signals are weak and unmodeled and the rate of occurrence in our galaxy is very low. Because of this, they provide a greater challenge to detect than previously detected GW sources. CCSN simulations are used to test the detection pipeline in the event a CCSN is detected. CCSN GW signals are often indistinguishable from the noise sources present in GW data. We present a multi layered signal enhancement pipeline which we have applied Machine Learning (ML) techniques. We have used a Convolutional …

Optimizing Convolutional Neural Networks For Transient Detection In Optical Astronomy With Augmented Datasets, Wendy Mendoza

Theses and Dissertations

We present a technique for optical transient detection using artificial neural networks, particularly a Convolutional Neural Network (CNN), a deep learning algorithm. This method analyzes images of the same area of the sky captured by several telescopes, with one image serving as a reference for a probable transient’s epoch and the other as an image from a previous epoch. We train the CNN on simulated sources and test it on actual image data samples using data from the Dr. Cristina V. Torres Memorial Astronomical Observatory and Sloan Digital Sky Survey. This autonomous detection method replaces the standard procedure, which involves …

Study Of Digital Algan Alloy Based Heterostructures Using Aln/Gan Short Period Superlattice, Mohammad Kamal Hussain

Theses and Dissertations

Ultrawide Bandgap (UWBG) and Extreme Bandgap (EBG) AlxGa1-xN (x > 0.40) alloys with EG > 4.2 eV are potential candidates for high temperature and high voltage applications, compared to Wide Bandgap (WBG) GaN-based lateral channel devices. Since critical electric field (Ec) scales as (Eg)^2.5, theoretically AlGaN alloys can sustain large electric field before breaking down. However, achieving linear ohmic contacts to the 2-dimensional electron gas (2DEG) formed at the interface of AlyGa_1-xN/ Al_xGa_1-xN (y – x ≥ 0.20) High Electron Mobility Transistors (HEMTs) is challenging. Direct contact through the AlGaN barrier is difficult due …

The Impact Of A Continuous Integration Service On The Delivery Time Of Merged Pull Requests, João Helis Bernardo, Daniel Alencar Da Costa, Uirá Kulesza, Christoph Treude

Research Collection School Of Computing and Information Systems

Continuous Integration (CI) is a software development practice that builds and tests software frequently (e.g., at every push). One main motivator to adopt CI is the potential to deliver software functionalities more quickly than not using CI. However, there is little empirical evidence to support that CI helps projects deliver software functionalities more quickly. Through the analysis of 162,653 pull requests (PRs) of 87 GitHub projects, we empirically study whether adopting a CI service (TRAVISCI) can quicken the time to deliver merged PRs. We complement our quantitative study by analyzing 450 survey responses from participants of 73 software projects. Our …

Rethinking Education In The Age Of Ai: The Importance Of Developing Durable Skills In The Industry 4.0, James Hutson, Jason Ceballos

Faculty Scholarship

This article discusses the pressing need to integrate artificial intelligence (AI) into education to facilitate customizable, individualized, and on-demand learning pathways. At the same time, while AI has the potential to expand the learner base and improve learning outcomes, the development of NACE Competencies and durable skills – communication, critical thinking, creativity, leadership, adaptability, and emotional intelligence - must be purposefully integrated in curriculum design now more than ever. Recent studies have shown that AI-driven learning pathways can achieve outcomes more quickly, but this comes at the cost of the development of durable skills. Therefore, traditional student-to-student and student-to-teacher interactions …

Socialz: Multi-Feature Social Fuzz Testing, Francisco Zanartu, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems

Online social networks have become an integral aspect of our daily lives and play a crucial role in shaping our relationships with others. However, bugs and glitches, even minor ones, can cause anything from frustrating problems to serious data leaks that can have farreaching impacts on millions of users. To mitigate these risks, fuzz testing, a method of testing with randomised inputs, can provide increased confidence in the correct functioning of a social network. However, implementing traditional fuzz testing methods can be prohibitively difficult or impractical for programmers outside of the network’s development team. To tackle this challenge, we present …