Digital Commons Network^™

Singapore's Ai Applications In The Public Sector: Six Examples, Steven M. Miller

Research Collection School Of Computing and Information Systems

Steven M. Miller describes six instances in which Singapore has applied AI in the public sector, illustrating different ways of improving its engagement with the public by making government services more accessible, anywhere, anytime, and speeding its responses to public processes and feedback. He illustrates how its leaders made the city a living lab for AI use, and what they learned.

Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai

Research Collection School Of Computing and Information Systems

Recent works using deep reinforcement learning (RL) to solve routing problems such as the capacitated vehicle routing problem (CVRP) have focused on improvement learning-based methods, which involve improving a given solution until it becomes near-optimal. Although adequate solutions can be achieved for small problem instances, their efficiency degrades for large-scale ones. In this work, we propose a newimprovement learning-based framework based on imitation learning where classical heuristics serve as experts to encourage the policy model to mimic and produce similar or better solutions. Moreover, to improve scalability, we propose Clockwise Clustering, a novel augmented framework for decomposing large-scale CVRP into …

Seed Selection For Testing Deep Neural Networks, Yuhan Zhi, Xiaofei Xie, Chao Shen, Jun Sun, Xiaoyu Zhang, Xiaohong Guan

Research Collection School Of Computing and Information Systems

Deep learning (DL) has been applied in many applications. Meanwhile, the quality of DL systems is becoming a big concern. To evaluate the quality of DL systems, a number of DL testing techniques have been proposed. To generate test cases, a set of initial seed inputs are required. Existing testing techniques usually construct seed corpus by randomly selecting inputs from training or test dataset. Till now, there is no study on how initial seed inputs affect the performance of DL testing and how to construct an optimal one. To fill this gap, we conduct the first systematic study to evaluate …

Adaptive Split-Fusion Transformer, Zixuan Su, Jingjing Chen, Lei Pang, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Neural networks for visual content understanding have recently evolved from convolutional ones to transformers. The prior (CNN) relies on small-windowed kernels to capture the regional clues, demonstrating solid local expressiveness. On the contrary, the latter (transformer) establishes long-range global connections between localities for holistic learning. Inspired by this complementary nature, there is a growing interest in designing hybrid models which utilize both techniques. Current hybrids merely replace convolutions as simple approximations of linear projection or juxtapose a convolution branch with attention without considering the importance of local/global modeling. To tackle this, we propose a new hybrid named Adaptive Split-Fusion Transformer …

Take A Break In The Middle: Investigating Subgoals Towards Hierarhical Script Generation, Xinze Li, Yixin Cao, Muhao Chen, Aixin Sun

Research Collection School Of Computing and Information Systems

Goal-oriented Script Generation is a new task of generating a list of steps that can fulfill the given goal. In this paper, we propose to extend the task from the perspective of cognitive theory. Instead of a simple flat structure, the steps are typically organized hierarchically — Human often decompose a complex task into subgoals, where each subgoal can be further decomposed into steps. To establish the benchmark, we contribute a new dataset, propose several baseline methods, and set up evaluation metrics. Both automatic and human evaluation verify the high-quality of dataset, as well as the effectiveness of incorporating subgoals …

Synthesizing Speech Test Cases With Text-To-Speech? An Empirical Study On The False Alarms In Automated Speech Recognition Testing, Julia Kaiwen Lau, Kelvin Kai Wen Kong, Julian Hao Yong, Per Hoong Tan, Zhou Yang, Zi Qian Yong, Joshua Chern Wey Low, Chun Yong Chong, Mei Kuan Lim, David Lo

Research Collection School Of Computing and Information Systems

Recent studies have proposed the use of Text-To-Speech (TTS) systems to automatically synthesise speech test cases on a scale and uncover a large number of failures in ASR systems. However, the failures uncovered by synthetic test cases may not reflect the actual performance of an ASR system when it transcribes human audio, which we refer to as false alarms. Given a failed test case synthesised from TTS systems, which consists of TTS-generated audio and the corresponding ground truth text, we feed the human audio stating the same text to an ASR system. If human audio can be correctly transcribed, an …

Mitigating Adversarial Attacks On Data-Driven Invariant Checkers For Cyber-Physical Systems, Rajib Ranjan Maiti, Cheah Huei Yoong, Venkata Reddy Palleti, Arlindo Silva, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

The use of invariants in developing security mechanisms has become an attractive research area because of their potential to both prevent attacks and detect attacks in Cyber-Physical Systems (CPS). In general, an invariant is a property that is expressed using design parameters along with Boolean operators and which always holds in normal operation of a system, in particular, a CPS. Invariants can be derived by analysing operational data of various design parameters in a running CPS, or by analysing the system's requirements/design documents, with both of the approaches demonstrating significant potential to detect and prevent cyber-attacks on a CPS. While …

Transfer-Once-For-All: Ai Model Optimization For Edge, Achintya Kundu, Laura Wynter, Rhui Dih Lee, Luis Angel Bathen

Research Collection School Of Computing and Information Systems

Weight-sharing neural architecture search aims to optimize a configurable neural network model (supernet) for a variety of deployment scenarios across many devices with different resource constraints. Existing approaches use evolutionary search to extract models of different sizes from a supernet trained on a very large data set, and then fine-tune the extracted models on the typically small, real-world data set of interest. The computational cost of training thus grows linearly with the number of different model deployment scenarios. Hence, we propose Transfer-Once-For-All (TOFA) for supernet-style training on small data sets with constant computational training cost over any number of edge …

A Review On The Effects Of Chanting And Solfeggio Frequencies On Well-Being, Xuyu Yang, Fiona Fui-Hoon Nah, Fen Lin

Research Collection School Of Computing and Information Systems

This paper presents our literature review on how chanting and solfeggio frequencies affect brain activity, enhance well-being, and inform the design of sound therapy. We call for more scientific research to investigate and better understand the effects of chanting and solfeggio frequencies on well-being.

Norfolk Integrated Waste-Energy Framework, Emma Kurtz, Abigail Schroeder, Jonah Mcdowell

Project Energy Nebraska: Student Projects

Environmental Engagement in the Community projects, spring 2023 A poster titled Norfolk Integrated Waste-Energy Framework for client City of Norfolk, Nebraska and Nebraska Public Power District.

Faculty sponsor: David Gosselin

Automated Fiber Placement Through Thickness Defect Stacking Optimization, Noah Christopher Swingle

Theses and Dissertations

In its 2022 commercial market outlook, Boeing forecasted an 80% increase in the global fleet through 2041 compared to 2019 pre-pandemic levels. This sharp rise in demand will drive pressure onto airframe manufacturers to ramp up production and find more efficient ways to design and manufacture airplanes. Complicating this challenge is the industry’s recent transformation from traditional metal-based airframes towards hybrid composite-metal aircraft. While composites have been used in aviation for decades, aircraft manufacturers are still struggling to design and manufacture quality parts at a high rate. Automated Fiber Placement (AFP) is one of the main manufacturing techniques used to …

Improving Outcomes For Older Struggling Readers In Special Education Resource, Kathryn Stone

Education Theses and Dissertations

This research aimed to increase the reading achievement of sixth-grade special education students receiving interventions in a resource setting. This problem of practice was created in response to the theory of change made by a Network Improvement Community (NIC) rooted in the lack of professional development offered by the school district for special education teachers in teaching students foundational reading skills. The research questions used for this study this evaluation were 1) What percent of students made progress in each reporting category (word study, grammar, and comprehension) in the Lexia PowerUp literacy program? 2) To what extent did the teachers …

To What Extent Do 3- To -6-Year-Olds Demonstrate Connection To Nature At A Montessori School In The Upper Midwest, Natasha Yates

School of Education and Leadership Student Capstone Theses and Dissertations

Yates, N. (2023). To What Extent Do 3- to -6-Year-Olds Demonstrate Connection to Nature at a Montessori School in the Upper Midwest.

Young children are born into a world today with a drastically changing environmental climate. When young people develop an emotional attachment and sense of identity with nature, they may be more likely to behave in less destructive ways towards the planet and possibly live with a sense of responsibility and respect for nature. This mixed method study aimed to measure to what extent 3- to 6-year-olds demonstrated environmental sensitivity, awareness, and preferences at a nature-based Montessori school in …

Density-Mediated Spin Correlations Drive Edge-To-Bulk Flow Transition In Active Chiral Matter, Alexander P. Petroff, Christopher Whittington, Arshad Kudrolli

Physics

We demonstrate that edge currents develop in active chiral matter due to boundary shielding over a wide range of densities corresponding to a gas, fluid, and crystal. The system is composed of spinning disk-shaped grains with chirally arranged tilted legs confined in a circular vibrating chamber. The edge currents are shown to increasingly drive circulating bulk flows with area fraction as percolating clusters develop due to increasing spin-coupling between neighbors mediated by frictional contacts. Edge currents are observed even in the dilute limit. While, at low area fraction, the average flux vanishes except within a distance that is of the …

Er Translocon Inhibitor Ipomoeassin F Inhibits Triple-Negative Breast Cancer Growth Via Blocking Er Molecular Chaperones, Shishi Tao, Eun Ju Yang, Guanghui Zong, Pui Kei Mou, Guowen Ren, Liang Chen, Ho Jeong Kwon, Jianhong Zhou, Zhijian Hu, Arman Khosravi, Qingyang Zhang, Yuchun Du, Wei Q. Shi, Joong Sup Shim

Biological Sciences Faculty Publications and Presentations

Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer where no effective therapy has been developed. Here, we report that the natural product ER translocon inhibitor ipomoeassin F is a selective inhibitor of TNBC cell growth. A proteomic analysis of TNBC cells revealed that ipomoeassin F significantly reduced the levels of ER molecular chaperones, including PDIA6 and PDIA4, and induced ER stress, unfolded protein response (UPR) and autophagy in TNBC cells. Mechanistically, ipomoeassin F, as an inhibitor of Sec61α-containing ER translocon, blocks ER translocation of PDIA6, inducing its proteasomal degradation. Silencing of PDIA6 or PDIA4 by RNA interferences …

Surveillance And The Future Of Work: Exploring Employees’ Attitudes Toward Monitoring In A Post-Covid Workplace, Jessica Vitak, Michael Zimmer

Computer Science Faculty Research and Publications

The future of work increasingly focuses on the collection and analysis of worker data to monitor communication, ensure productivity, reduce security threats, and assist in decision-making. The COVID-19 pandemic increased employer reliance on these technologies; however, the blurring of home and work boundaries meant these monitoring tools might also surveil private spaces. To explore workers’ attitudes toward increased monitoring practices, we present findings from a factorial vignette survey of 645 U.S. adults who worked from home during the early months of the pandemic. Using the theory of privacy as contextual integrity to guide the survey design and analysis, we unpack …

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 …

Antitrust And Sustainability: A Landscape Analysis, Columbia Center On Sustainable Investment, Sabin Center For Climate Change Law

Columbia Center on Sustainable Investment

Competition policy and antitrust law are experiencing a global renaissance. New market realities such as digital market gatekeepers, the financialization of firms, highly concentrated markets, a rising labor movement, industrial policy, and trade wars, among others, are radically reshaping how this policy area is understood and applied.

Sustainability concerns have also been a driving force for reconstituting antitrust to meet twenty-first century challenges. It is now widely accepted that competition policy – both its aims and its enforcement – has wider societal impacts beyond competition, including effects on democracy, economic inequality, growth and innovation, racial and gender imbalances, privacy, geopolitical …

An Evolutionary Comparative Study Of Congenital Stationary Night Blindness-Associated Trpm1 Genetic Variants Of Uncertain Significance In Horses And Humans Utilizing Caenorhabditis Elegans, Gabrielle Davis

Theses

Congenital stationary night blindness (CSNB) is a heterogeneous collection of genetic diseases affecting the eyes and vision in horses and humans. Current research has implicated several genetic mutations impacting different genes involved in phototransduction and signal transmission, including TRPM1. In horses, genetic mutations in TRPM1 also result in a leopard spotting pattern or leopard complex. The goal of this study is to examine the potential impact of CSNB associated TRPM1 missense variants of uncertain significance (VUS). Previous research in Caenorhabditis elegans have revealed an orthologous TRPM1 gene known as gon-2 that allows for comparative studies. The evolutionary relationship of …

Enhancing And Securing Wireless Medical Technology For Diagnosis And Treatment Of Lower Urinary Tract Dysfunction, Farhath Zareen

USF Tampa Graduate Theses and Dissertations

Lower urinary tract dysfunction (LUTD) is a debilitating medical condition that affects millions of individuals worldwide. Urodynamics is the current gold standard for diagnosing LUTD but uses non-physiologically fast, retrograde cystometric filling to obtain a brief snapshot of bladder function. Current state-of-the-art research in bladder monitoring includes ambulatory urodynamics using wireless implantable devices to evaluate bladder function during natural filling for long-term monitoring. However, there are various challenges and limitations to this multi-sensor approach. This research focuses on developing frameworks for automated event detection, data analysis, and optimization of long-term bladder recordingsto improve the diagnosis and treatment of LUTD. In …

2022 Survey Of Illinois Law: Family Law, Stephanie L. Tang

Southern Illinois University Law Journal

In 2022, there were significant changes to both family law legislation and case law. Relevant legislative changes include allowing litigants to seek attorney’s fees to retain a lawyer, allowing for temporary relocation, and clarifying when a change in circumstances is “contemplated” for purposes of modifying child support. Illinois courts also adjudicated cases across all areas of family law. These areas ranged from expanding on prior case precedent in areas like property division and allocation of parental responsibilities to establishing new precedent in others, including COVID-19 restrictions and allocation of frozen embryos.

This Article is a continuation of the 2017-2018 and …

Edge Covers Of Joined Cycle And Path Graphs, Rowan Kennedy

Mathematics Undergraduate Research

A graph is a mathematical structure consisting of vertices, representing objects, and edges that connect pairs of vertices, representing relationships between objects. When a specific graph structure can be extended in a consistent pattern we get a graph family, such as the families of path and cycle graphs. An edge cover of a graph is a subset of the graph's edges chosen so that each vertex is an endpoint of at least one edge in this subset. The edge cover counts of certain graph families, such as the path and cycle graphs, correspond to known sequences, the Fibonacci and Lucas …

Encoding And Storage Of Information In Mechanical Metamaterials, Zhiqiang Meng, Hujie Yan, Mingchao Liu, Wenkai Qin, Guy M Genin, Chang Qing Chen

2020-Current year OA Pubs

Information processing using material's own properties has gained increasing interest. Mechanical metamaterials, due to their diversity of deformation modes and wide design space, can be used to realize information processing, such as computing and storage. Here a mechanical metamaterial system is demonstrated for material-based encoding and storage of data through programmed reconfigurations of the metamaterial's structured building blocks. Sequential encoding and decoding are achieved in the three-dimensional (3D) printed pixelated mechanical metamaterial via kirigami-based "pixels" with programmable, temperature-dependent bistability. The mechanical metamaterial is demonstrated via a multistep deformation of encoding messages of texts and surfaces with arrays of binary data, …

Revisiting The Properties Of X-Ray Active Galactic Nuclei In The Ssa22 Protocluster: Normal Supermassive Black Hole And Host-Galaxy Growth For Agns In A Z=3.09 Overdensity, Erik B. Monson, Keith Doore, Rafael T. Eufrasio, Bret D. Lehmer, David M. Alexander, Chris M. Harrison, Mariko Kubo, Cristian Saez, Hideki Umehata

Physics Faculty Publications and Presentations

We analyze the physical properties of eight X-ray-selected active galactic nuclei (AGNs) and one candidate protoquasar system (ADF22A1) in the z = 3.09 SSA22 protocluster by fitting their X-ray-to-IR spectral energy distributions (SEDs) using our SED-fitting code, Lightning (https://www.github.com/rafaeleufrasio/lightning). We recover star formation histories (SFHs) for seven of these systems which are well fit by composite stellar population plus AGN models. We find indications that four out of nine of the SSA22 AGN systems we study have host galaxies below the main sequence, with SFR/SFRMS ≤ −0.4. The remaining SSA22 systems, including ADF22A1, are consistent with obscured supermassive black hole …

Generating Adversarial Malware Examples Using Particle Swarm Optimization, Sirapat Thianphan

Theses

Adversaries develop adversarial malware examples that are designed to evade detection systems, which can significantly decrease the performance of malware classifiers. To defend against adversarial malware examples, a technique called adversarial training is implemented by additionally train the detection models with adversarial examples, making the models more robust to such attacks. This thesis discusses an approach to generating adversarial examples using Particle Swarm Optimization (PSO). We explore a technique called AdversarialPSO proposed by Rayan Mosli [1], which crafts adversarial malware examples by replacing API calls with alternative APIs that have equivalent functionality leveraging PSO to navigate substitutions. In this thesis, …

Inter-Procedural Program Synthesis For Automatic Architectural Tactic Implementation, Ali Shokri

Theses

Software architectural tactics are design decisions made by software architects to address important quality attributes of software systems such as security, availability, and reliability. Software developers incorporate API of software frameworks, as building blocks, for implementing architectural tactics in a software system to achieve the mentioned quality attributes. The correct implementation of such tactics is a challenging and error-prone task, especially for novice programmers. Component-based program synthesis aims to help such programmers by automatically constructing a code snippet from a given set of components, e.g., APIs, as well as the specification of the desired code. However, despite the advances in …

Applying Homomorphic Encryption To A Cross Domain Problem, Cheyenne Dailey

Theses

The Cross Domain Problem (CDP) strives to ensure protected data transference across varying security domains. In order to accomplish this, a Cross Domain Solution (CDS) is needed. A common method to protect data is to focus on risk management between trusted parties; however, untrusted parties pose ongoing concern. The problem is determining a method that transfers classified data through various security domains without exposing any information to intermediary parties. Attempts to mitigate this problem have been made utilizing Homomorphic Encryption (HE), a type of encryption that allows for computations to be executed on encrypted data without needing to decrypt it. …

Continual Domain Adaptation Through Knowledge Distillation, Georgi Thomas

Theses

Domain Adaptation (DA) techniques aim to overcome the domain shift between a source domain used for training and the target domain used for testing and deployment. Domain adaptation methods assume the entire target domain is accessible during the adaptation process. We use efficient architectures in the continual data-constrained DA paradigm where the unlabeled data in the target domain is received continually in batches. In recent years, Vision Transformers have emerged as an alternative to traditional Convolutional Neural Networks (CNNs) as the feature extraction backbone for image classification and other computer vision tasks. Within the field of DA, these attention-based architectures …

Diffractive Light And Solar Sails, Prateek Ranjan Srivastava

Theses

In the realm of space exploration, humanity has achieved remarkable feats like landing humans on the moon. However, our progress in venturing beyond our solar system has been limited. Light sails, which utilize photon momentum from laser or solar radiation, o↵er a promising propulsion technology. Unlike traditional rockets, light sails carry no fuel and can achieve high velocities and precise orbital maneuvers. In this research, we propose using an elementary space variant di↵ractive film to design passively stable light sails propelled by laser radiation. We also explore applying this concept to solar sails, enabling spiral trajectories and high orbital inclination …

A Privacy Safeguarding Framework For The Smart Grid, Gaurav Shivaji Wagh

Theses

The smart grid is an outcome of integrating communication technologies with traditional electrical systems. This enables the collection of granular metering data from the customer domain for providing grid and billing functionalities. However, the data collection process exposes the grid to various cyberattacks, posing a significant threat to customer privacy. This is a critical concern for the smart grid community and has hindered the global adoption of the smart grid technology. Although aggregation-based frameworks show promise for sharing metering data with the Electrical Service Provider while maintaining customer privacy, existing aggregation-based frameworks have several limitations. Some of these limitations include …