Digital Commons Network^™

Determining The Effects Of Glycocalyx Modifications On The Electrophysical Properties Of Human Mesenchymal Stem Cells, Rominna E. Valentine Ico

Electronic Theses, Projects, and Dissertations

Human mesenchymal stem cells (hMSCs) have gained popularity in clinical trials due to their multipotent differentiation characteristics, ability to secrete bioactive molecules, migrate into diseased or damaged tissues, and their immunosuppressive properties. HMSC cultures are heterogeneous, containing stem cells, partially differentiated progenitor cells, and fully differentiated cells. One of the major challenges with hMSCs therapeutic potential is the inability to select specific cell subpopulations due to an insufficient number of biomarkers. Often the biomarkers used, like those for fluorescence-activated cell sorting, are not sufficient to define hMSCs because they overlap with other cell types. Consequently, there is a need to …

Analysis Of Online Platforms’ Free Trial Strategies For Digital Content Subscription, Li Chen

College of Business and Economics

Adopting subscription models has become a popular trend in e-commerce. Digital content platforms often use free trials to attract potential subscribers. However, rigorous research on platforms’ free trial strategies is lacking. Our paper aims to fill this gap using a horizontal duopoly framework. We investigate both the scenario of market symmetry and of market asymmetry. We study the benchmark case with no free trial for each scenario and derive equilibrium results with free trial promotion. We find that the platform will not benefit from free trials unless consumers’ learning rate exceeds a threshold. When a free trial is introduced in …

Kape: Knn-Based Performance Testing For Deep Code Search, Yuejun Guo, Qiang Hu, Xiaofei Xie, Cordy Maxime, Mike Papadakis, Yves Le Traon

Research Collection School Of Computing and Information Systems

Code search is a common yet important activity of software developers. An efficient code search model can largely facilitate the development process and improve the programming quality. Given the superb performance of learning the contextual representations, deep learning models, especially pre-trained language models, have been widely explored for the code search task. However, studies mainly focus on proposing new architectures for ever-better performance on designed test sets but ignore the performance on unseen test data where only natural language queries are available. The same problem in other domains, e.g., CV and NLP, is usually solved by test input selection that …

Estimating Propensity For Causality-Based Recommendation Without Exposure Data, Zhongzhou Liu, Yuan Fang, Min Wu

Research Collection School Of Computing and Information Systems

Causality-based recommendation systems focus on the causal effects of user-item interactions resulting from item exposure (i.e., which items are recommended or exposed to the user), as opposed to conventional correlation-based recommendation. They are gaining popularity due to their multi-sided benefits to users, sellers and platforms alike. However, existing causality-based recommendation methods require additional input in the form of exposure data and/or propensity scores (i.e., the probability of exposure) for training. Such data, crucial for modeling causality in recommendation, are often not available in real-world situations due to technical or privacy constraints. In this paper, we bridge the gap by proposing …

Monocular Depth Estimation For Glass Walls With Context: A New Dataset And Method, Yuan Liang, Bailin Deng, Wenxi Liu, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Traditional monocular depth estimation assumes that all objects are reliably visible in the RGB color domain. However, this is not always the case as more and more buildings are decorated with transparent glass walls. This problem has not been explored due to the difficulties in annotating the depth levels of glass walls, as commercial depth sensors cannot provide correct feedbacks on transparent objects. Furthermore, estimating depths from transparent glass walls requires the aids of surrounding context, which has not been considered in prior works. To cope with this problem, we introduce the first Glass Walls Depth Dataset (GW-Depth dataset). We …

Robust Test Selection For Deep Neural Networks, Weifeng Sun, Meng Yan, Zhongxin Liu, David Lo

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNNs) have been widely used in various domains, such as computer vision and software engineering. Although many DNNs have been deployed to assist various tasks in the real world, similar to traditional software, they also suffer from defects that may lead to severe outcomes. DNN testing is one of the most widely used methods to ensure the quality of DNNs. Such method needs rich test inputs with oracle information (expected output) to reveal the incorrect behaviors of a DNN model. However, manually labeling all the collected test inputs is a labor-intensive task, which delays the quality assurance …

Benchmarking Foundation Models With Language-Model-As-An-Examiner, Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Yijia Xiao, Haozhe Lyu, Jiayin Zhang, Juanzi Li, Lei Hou

Research Collection School Of Computing and Information Systems

Numerous benchmarks have been established to assess the performance of foundation models on open-ended question answering, which serves as a comprehensive test of a model’s ability to understand and generate language in a manner similar to humans. Most of these works focus on proposing new datasets, however, we see two main issues within previous benchmarking pipelines, namely testing leakage and evaluation automation. In this paper, we propose a novel benchmarking framework, Language-Model-as-an-Examiner, where the LM serves as a knowledgeable examiner that formulates questions based on its knowledge and evaluates responses in a reference-free manner. Our framework allows for effortless extensibility …

Efficient Meta Neural Heuristic For Multi-Objective Combinatorial Optimization, Jinbiao Chen, Zizhen Zhang, Te Ye, Zhiguang Cao, Siyuan Chen, Jiahai Wang

Research Collection School Of Computing and Information Systems

Recently, neural heuristics based on deep reinforcement learning have exhibited promise in solving multi-objective combinatorial optimization problems (MOCOPs). However, they are still struggling to achieve high learning efficiency and solution quality. To tackle this issue, we propose an efficient meta neural heuristic (EMNH), in which a meta model is first trained and then fine-tuned with a few steps to solve corresponding single-objective subproblems. Specifically, for the training process, a (partial) architecture-shared multi-task model is leveraged to achieve parallel learning for the meta model, so as to speed up the training; meanwhile, a scaled symmetric sampling method with respect to the …

Truncated Affinity Maximization: One-Class Homophily Modeling For Graph Anomaly Detection, Hezhe Qiao, Guansong Pang

Research Collection School Of Computing and Information Systems

We reveal a one-class homophily phenomenon, which is one prevalent property we find empirically in real-world graph anomaly detection (GAD) datasets, i.e., normal nodes tend to have strong connection/affinity with each other, while the homophily in abnormal nodes is significantly weaker than normal nodes. However, this anomaly-discriminative property is ignored by existing GAD methods that are typically built using a conventional anomaly detection objective, such as data reconstruction. In this work, we explore this property to introduce a novel unsupervised anomaly scoring measure for GAD – local node affinity – that assigns a larger anomaly score to nodes that are …

A Closer Look At The Security Risks In The Rust Ecosystem, Xiaoye Zheng, Zhiyuan Wan, Yun Zhang, Rui Chang, David Lo

Research Collection School Of Computing and Information Systems

Rust is an emerging programming language designed for the development of systems software. To facilitate the reuse of Rust code, crates.io, as a central package registry of the Rust ecosystem, hosts thousands of third-party Rust packages. The openness of crates.io enables the growth of the Rust ecosystem but comes with security risks by severe security advisories. Although Rust guarantees a software program to be safe via programming language features and strict compile-time checking, the unsafe keyword in Rust allows developers to bypass compiler safety checks for certain regions of code. Prior studies empirically investigate the memory safety and concurrency bugs …

Extending The Horizon By Empowering Government Customer Service Officers With Acqar For Enhanced Citizen Service Delivery, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

A previous study on the use of the Empath library in the prediction of Service Level Agreements (SLA) reveals the quality levels required for meaningful interaction between government customer service officers and citizens. On the other hand, past implementation of the Citizen Question-Answer system (CQAS), a type of Question-Answer model, suggests that such models if put in place can empower government customer service officers to reply faster and better with recommended answers. This study builds upon the research outcomes from both arenas of studies and introduces an innovative system design that allows the officers to incorporate the outputs from Empath …

Benefits Of Primary Grade Dual Language Immersion Programs, Karen Green Mesa

Walden Dissertations and Doctoral Studies

No abstract provided.

Video Sentiment Analysis For Child Safety, Yee Sen Tan, Nicole Anne Huiying Teo, Ezekiel En Zhe Ghe, Jolie Zhi Yi Fong, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

The proliferation of online video content underscores the critical need for effective sentiment analysis, particularly in safeguarding children from potentially harmful material. This research addresses this concern by presenting a multimodal analysis method for assessing video sentiment, categorizing it as either positive (child-friendly) or negative (potentially harmful). This method leverages three key components: text analysis, facial expression analysis, and audio analysis, including music mood analysis, resulting in a comprehensive sentiment assessment. Our evaluation results validate the effectiveness of this approach, making significant contributions to the field of video sentiment analysis and bolstering child safety measures. This research serves as a …

Software Architecture In Practice: Challenges And Opportunities, Zhiyuan Wan, Yun Zhang, Xin Xia, Yi Jiang, David Lo

Research Collection School Of Computing and Information Systems

Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice. Despite past efforts, we have little understanding of how practitioners perform software architecture related activities, and what challenges they face. Through interviews with 32 practitioners from 21 organizations across three continents, we identified challenges that practitioners face in software architecture practice during software development and maintenance. We reported on common software architecture activities at software requirements, design, construction and testing, and maintenance stages, as well as corresponding …

Mermaid: A Dataset And Framework For Multimodal Meme Semantic Understanding, Shaun Toh, Adriel Kuek, Wen Haw Chong, Roy Ka Wei Lee

Research Collection School Of Computing and Information Systems

Memes are widely used to convey cultural and societal issues and have a significant impact on public opinion. However, little work has been done on understanding and explaining the semantics expressed in multimodal memes. To fill this research gap, we introduce MERMAID, a dataset consisting of 3,633 memes annotated with their entities and relations, and propose a novel MERF pipeline that extracts entities and their relationships in memes. Our framework combines state-of-the-art techniques from natural language processing and computer vision to extract text and image features and infer relationships between entities in memes. We evaluate the proposed framework on a …

Evaluating Transfer Learning For Simplifying Github Readmes, Haoyu Gao, Christoph Treude, Mansooreh Zahedi

Research Collection School Of Computing and Information Systems

Software documentation captures detailed knowledge about a software product, e.g., code, technologies, and design. It plays an important role in the coordination of development teams and in conveying ideas to various stakeholders. However, software documentation can be hard to comprehend if it is written with jargon and complicated sentence structure. In this study, we explored the potential of text simplification techniques in the domain of software engineering to automatically simplify GitHub README files. We collected software-related pairs of GitHub README files consisting of 14,588 entries, aligned difficult sentences with their simplified counterparts, and trained a Transformer-based model to automatically simplify …

Lessons From The Long Tail: Analysing Unsafe Dependency Updates Across Software Ecosystems, Supatsara Wattanakriengkrai, Raula Kula, Christoph Treude, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

A risk in adopting third-party dependencies into an application is their potential to serve as a doorway for malicious code to be injected (most often unknowingly). While many initiatives from both industry and research communities focus on the most critical dependencies (i.e., those most depended upon within the ecosystem), little is known about whether the rest of the ecosystem suffers the same fate. Our vision is to promote and establish safer practises throughout the ecosystem. To motivate our vision, in this paper, we present preliminary data based on three representative samples from a population of 88,416 pull requests (PRs) and …

A Critical Analysis Of The Fulbright Program From A World Systems Perspective, Marisa Lally, Shadman Islem

Journal of Comparative & International Higher Education

No abstract provided.

Ethical Considerations For Artificial Intelligence In Educational Assessments, Lim Ming Soon Tristan, Gottipati Swapna, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

In the vital context of education, the application of artificial intelligence (AI) to assessments necessitates a nuanced examination of the boundaries between ethically permissible and impermissible practices. In this chapter, the authors applied a systematic literature mapping methodology to scour extant research, so as to holistically structure the landscape into explicit topical research clusters. Through topic modelling and network analyses, research mapped key ethical principles to different assessment phases in a triadic ontological framework. The chapter looks to provide researchers and practitioners the insights into the ethical challenges that exist across an end-to-end assessment pipeline.

Providing Optimal Resident Sleep Hygiene In Assisted Living Communities; Opportunities For Design And Operation Teams To Collaborate And Share Their Unique Knowledge, Beverly B. J. Miller

Architecture Masters of Science Program: Theses

Research is emerging relating sleep hygiene to disease pathogenesis including Parkinson's, dementia, Alzheimer’s disease and increased cardiovascular risk. The application of circadian science as it relates to human wellness has intensified as a result. The quality of sleep significantly impacts the wellness of residents living in long term care, however sleep hygiene research is lacking in assisted living (AL) communities.

The thesis question inquires; How can operation and design teams collaborate to optimize sleep health for residents in assisted living communities? The research methodology utilized a two-phase process. Phase I identified three AL communities as test sites, providing case studies …

Butte Priority Soils Operable Unit Uncontrolled Surface Flow Areas Draft Remedial Design Work Plan (Rdwp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Uncontrolled Surface Flow Areas Pre-Design Investigation Work Plan, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Bpsou 2023 Uncontrolled Surface Flow Area Soil Characterization Quality Assurance Project Plan (Qapp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Rabrs For Use In Biologically Enhanced Precipitation Of Struvite In Anaerobic Digester Effluent (Municipal Wastewater), Parker R. Goldsberry

All Graduate Theses and Dissertations, Fall 2023 to Present

Rotating Algae Biofilm Reactor (RABR) technology has been researched in studies over the past decade directed at nutrient management for water resource recovery facilities (WRRFs). This study investigated the growth of slow-release fertilizer crystals, referred to as struvite, in the algae biofilms of Rotating Algae Biofilm Reactors (RABRs) at the Central Valley Water Reclamation Facility, the largest water resource recovery facility in the State of Utah. RABRs used anaerobic digester (AD) filtrate as their nutrient source. AD effluent is high in nutrients like nitrogen and phosphorus. The levels of both phosphorus and nitrogen (in the form of ammonia) are regulated …

Student Reliance On Simulations: The Extent That Engineering Students Rely On The Outcomes Of Their Simulations, Jonathan Anderson

All Graduate Theses and Dissertations, Fall 2023 to Present

The purpose of this research was to investigate the factors that contributed to engineering education students’ reliance on technology while learning new concepts. The researcher hypothesized that students would give reliance to their technology, even in the face of evidence that the technology was not working as intended. This research used a mixed-methods approach to answer the research questions. Three questions guided the research: (1) How are the participant’s level of automation complacency and the correctness of the simulation that participant is using related?; (2) How is automation bias related to a participant’s ability to recognize errors in a simulation?; …

An Overview Of Sustainability Content In Higher Education: Applications For University Landscape Architecture Programs, Hye Yeon Park

All Graduate Theses and Dissertations, Fall 2023 to Present

Higher education institutions worldwide have recognized the importance of integrating sustainability into their programs, with over 600 universities offering courses focused on sustainable development. This trend has led to the emergence of Education for Sustainable Development (ESD). This multidimensional approach aims to empower individuals to create a sustainable future by integrating environmental, social, and economic systems. In particular, ESD has been implemented in various aspects of higher education, such as course content, teaching methodologies, curriculum design, and faculty roles.

Design and planning education are critical components of shaping future decision-makers who will positively and negatively impact society and the environment. …

Understanding The Impact Of Physicochemical Modifications On The Cold Gelling Behavior Of Micellar Casein Concentrate Dispersions, Nathan Pougher

All Graduate Theses and Dissertations, Fall 2023 to Present

When skim milk is filtered via microfiltration, the amount of casein (one of the major milk proteins) in solution can be concentrated. When casein content is high enough (>15%), the solution forms a gel at cold temperatures. With growing trends in the food industry towards simplistic ingredient labels, commonly used gums and stabilizers in the dairy industry are becoming less preferred. In the future, there is potential for the gelling properties of micellar casein to be applied to dairy products as a thickener or stabilizer, but the mechanism behind gel formation isn’t understood well. In this study, the gel …

Gps-Denied Navigation Using Synthetic Aperture Radar, Tucker Hathaway

All Graduate Theses and Dissertations, Fall 2023 to Present

In most modern navigation systems, GPS is used to determine the precise location of the vehicle; however, GPS signals can easily be blocked, jammed, or spoofed. These signals can be blocked by canyons or tall buildings. Additionally, adversaries can transmit signals that either make GPS signals difficult to interpret or that imitate real GPS signals and cause a navigation system to think it is somewhere other than its true location. GPS-denied (GPS-D) navigation is the process of navigating in the absence of GPS.

Many methods of performing GPS-D navigation have been proposed and explored. One such method is to use …

Dusky Grouse Population Ecology And Thermal Landscape Ecology In The Great Basin Ecosystem, Stephanie M. Landry

All Graduate Theses and Dissertations, Fall 2023 to Present

Dusky Grouse are a mountainous forest grouse found throughout the western, inland mountain ranges of the United States and Canada. While a few studies have looked at Dusky Grouse in the Rocky Mountain Ecosystem of their range, there have been no prior studies of the Dusky Grouse in the Great Basin Ecosystem aside from a brief survey by Zwickel and Bendell in 2004 in the Duck Creek Range of Nevada. With the available habitats differing in both species diversity and availability on the landscape between the two Ecosystems, I wanted to assess characteristics about the Dusky Grouse populations at the …

Understanding The Pizza Baking Properties Of Low Moisture Part Skim (Lmps) Mozzarella Cheese, Anjali Verma

All Graduate Theses and Dissertations, Fall 2023 to Present

Mozzarella cheese is expected to melt, stretch, release free oil and exhibit browning and blistering when baked on pizza. This research aimed to investigate the effects of different starter cultures (based on lactose and galactose utilizing ability) and calcium levels on the functionality of Mozzarella cheese when baked on pizza. Four combinations of starter cultures using S. thermophilus (STI 06)-control, Lac⁺ Gal⁺ L. helveticus (LH 32), and Lac^- Gal⁺ adjunct culture L. helveticus (LH 7995) were used to make the cheese samples. Various tests were conducted over a seven-week period to evaluate their baking properties. The …