Physical Sciences and Mathematics Commons^™

Ethical Considerations Toward Protestware, Marc Cheong, Raula Kula, Christoph Treude

Research Collection School Of Computing and Information Systems

This article looks into possible scenarios where developers might consider turning their free and open source software into protestware. Using different frameworks commonly used in artificial intelligence (AI) ethics, we extend the applications of AI ethics to the study of protestware.

To Protect Or To Hide: An Investigation On Corporate Redacted Disclosure Motives Under New Fast Act Regulation, Yan Ma, Qian Mao, Nan Hu

Research Collection School Of Computing and Information Systems

China adopted amendments allowing companies to redact filings without prior approval in 2016. Leveraging this change as a quasi-nature experiment, we explore whether managers utilize redacted information to withhold bad information in the more lenient regulatory environment. Our investigation uncovers a significant shift in managerial behavior: Since 2016, managers incline to employ redactions to obscure negative news rather than safeguarding proprietary data. Furthermore, we find that the poorer firm performance and a higher cost of equity are associated with the redacted disclosures after 2016, suggesting that investors perceive an increase in firm-specific risk attributed to withholding bad news through redactions.

Unmasking The Lurking: Malicious Behavior Detection For Iot Malware With Multi-Label Classification, Ruitao Feng, Sen Li, Sen Chen, Mengmeng Ge, Xuewei Li, Xiaohong Li

Research Collection School Of Computing and Information Systems

Current methods for classifying IoT malware predominantly utilize binary and family classifications. However, these outcomes lack the detailed granularity to describe malicious behavior comprehensively. This limitation poses challenges for security analysts, failing to support further analysis and timely preventive actions. To achieve fine-grained malicious behavior identification in the lurking stage of IoT malware, we propose MaGraMal. This approach, leveraging masked graph representation, supplements traditional classification methodology, empowering analysts with critical insights for rapid responses. Through the empirical study, which took three person-months, we identify and summarize four fine-grained malicious behaviors during the lurking stage, constructing an annotated dataset. Our evaluation …

Diffusion Time-Step Curriculum For One Image To 3d Generation, Xuanyu Yi, Zike Wu, Qingshan Xu, Pan Zhou, Joo Hwee Lim, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Score distillation sampling (SDS) has been widely adopted to overcome the absence of unseen views in reconstructing 3D objects from a single image. It leverages pretrained 2D diffusion models as teacher to guide the reconstruction of student 3D models. Despite their remarkable success, SDS-based methods often encounter geometric artifacts and texture saturation. We find out the crux is the overlooked indiscriminate treatment of diffusion time-steps during optimization: it unreasonably treats the studentteacher knowledge distillation to be equal at all time-steps and thus entangles coarse-grained and fine-grained modeling. Therefore, we propose the Diffusion Time-step Curriculum one-image-to-3D pipeline (DTC123), which involves both …

Gts: Gpu-Based Tree Index For Fast Similarity Search, Yifan Zhu, Ruiyao Ma, Baihua Zheng, Xiangyu Ke, Lu Chen, Yunjun Gao

Research Collection School Of Computing and Information Systems

Similarity search, the task of identifying objects most similar to a given query object under a specific metric, has gathered significant attention due to its practical applications. However, the absence of coordinate information to accelerate similarity search and the high computational cost of measuring object similarity hinder the efficiency of existing CPU-based methods. Additionally, these methods struggle to meet the demand for high throughput data management. To address these challenges, we propose GTS, a GPU-based tree index designed for the parallel processing of similarity search in general metric spaces, where only the distance metric for measuring object similarity is known. …

Closest Pairs Search Over Data Stream, Rui Zhu Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng

Research Collection School Of Computing and Information Systems

��-closest pair (KCP for short) search is a fundamental problem in database research. Given a set of��-dimensional streaming data S, KCP search aims to retrieve �� pairs with the shortest distances between them. While existing works have studied continuous 1-closest pair query (i.e., �� = 1) over dynamic data environments, which allow for object insertions/deletions, they require high computational costs and cannot easily support KCP search with �� > 1. This paper investigates the problem of KCP search over data stream, aiming to incrementally maintain as few pairs as possible to support KCP search with arbitrarily ��. To achieve this, we …

Jollygesture: Exploring Dual-Purpose Gestures In Vr Presentations, Gun Woo Warren Park, Anthony Tang, Fanny Chevalier

Research Collection School Of Computing and Information Systems

Virtual reality (VR) offers new opportunities for presenters to use expressive body language to engage their audience. Yet, most VR presentation systems have adopted control mechanisms that mimic those found in face-to-face presentation systems. We explore the use of gestures that have dual-purpose: first, for the audience, a communicative purpose; second, for the presenter, a control purpose to alter content in slides. To support presenters, we provide guidance on what gestures are available and their effects. We realize our design approach in JollyGesture, a VR technology probe that recognizes dual-purpose gestures in a presentation scenario. We evaluate our approach through …

Criticality Aware Canvas-Based Visual Perception At The Edge, Ila Gokarn

Research Collection School Of Computing and Information Systems

Efficient and effective machine perception remains a formidable challenge in sustaining high fidelity and high throughput of perception tasks on affordable edge devices. This is especially due to the continuing increase in resolution of sensor streams (e.g., video input streams generated by 4K/8K cameras and neuromorphic event cameras that produce ≥ 10 MEvents/second) and computational complexity of Deep Neural Network (DNN) models, which overwhelms edge platforms, adversely impacting machine perception efficiency. Given the insufficiency of the available computation resources, a question then arises on whether selected regions/components of the perception task can be prioritized (and executed preferentially) to achieve highest …

Understanding The Impact Of Microplastic Contamination On Soil Quality And Eco-Toxicological Risks In Horticulture: A Comprehensive Review, N. P. Gayathri, Geena Prasad, Vaishna Prabhakaran, Vishnu Priya

Research outputs 2022 to 2026

The horticulture sector, essential for global food production, confronts significant challenges with prevalent pollutants, mainly microplastics. The presence of microplastics in the food chain has induced physiological stress and a multifactorial food safety concern. The complexity of the problem, arising from intricate interactions among microplastics, organisms, and ecosystems, poses a substantial challenge to food safety, necessitating an immediate strategic perspective due to the associated risks to human health and eco-toxicology. Significant knowledge gaps persist regarding their impact on terrestrial ecosystems, especially in horticulture. This study addresses the urgent need to comprehend the implications of microplastics on soil health, eco-toxicological risks, …

Automated Sensor Node Malicious Activity Detection With Explainability Analysis, Md Zubair, Helge Janicke, Ahmad Mohsin, Leandros Maglaras, Iqbal H. Sarker

Research outputs 2022 to 2026

Cybersecurity has become a major concern in the modern world due to our heavy reliance on cyber systems. Advanced automated systems utilize many sensors for intelligent decision-making, and any malicious activity of these sensors could potentially lead to a system-wide collapse. To ensure safety and security, it is essential to have a reliable system that can automatically detect and prevent any malicious activity, and modern detection systems are created based on machine learning (ML) models. Most often, the dataset generated from the sensor node for detecting malicious activity is highly imbalanced because the Malicious class is significantly fewer than the …

High Rates Of Erosion On A Wave-Exposed Fringing Coral Reef, Damian P. Thomson, Shannon Dee, Christopher Doropoulos, Melanie Orr, Shaun K. Wilson, Andrew S. Hoey

Research outputs 2022 to 2026

Erosion is a key process in shaping the physical structure of coral reefs, yet due to erosion being semi-cryptic and difficult to quantify, information remains limited. Here, we investigate erosional processes along Ningaloo Reef, an extensive fringing coral reef in Western Australia. We employed both direct and indirect methods to measure erosion in wave-exposed reef slopes and protected lagoonal habitats. Direct measurements of erosion on coral blocks were among the highest found globally, with total erosion of 3.07 kg m−2 yr−1 (4% from micro, 0.6% from macro, and 94% from external), whilst indirect rates were estimated at 2.4 ± 0.20 …

Cyberbullying Detection On Twitter Data Using Machine Learning Classifiers, Pradip Dhakal

Data Science and Data Mining

This study compares some of the popular machine learning techniques like Logistic Regression, Multinomial Naive Bayes, K-Nearest Neighbor, and Extreme Gradient Boosting to classify the tweets into three different categories: cyberbullying based on religion, cyberbullying based on ethnicity, or no cyberbullying. First, various data-cleaning approaches are used to clean the tweet data. After the data is clean and ready, the word embedding techniques, such as a bag of words and term frequency-Inverse document frequency, are used to convert the words into mathematical vectors. Finally, the model will be fitted using the combination of the above-mentioned word embedding techniques and machine …

Nonlinear Classifiers For Wet-Neuromorphic Computing Using Gene Regulatory Neural Network, Adrian Ratwatte, Samitha Somathilaka, Sasitharan Balasubramaniam, Assaf A. Gilad

School of Computing: Faculty Publications

The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational principles resemble an artificial neural network (ANN), which can pave the way for the development of wet-neuromorphic computing systems. Genes are integrated into gene-perceptrons with transcription factors (TFs) as input, where the TF concentration relative to half-maximal RNA concentration and gene product copy number influences transcription and translation via weighted multiplication before undergoing a nonlinear activation function. This process yields protein concentration as the …

Internet-Based Data Platforms Re-Define The Distributions Of Some Large Crabronid Wasps In Arkansas (Hymenoptera: Crabronidae), David E. Bowles

Insecta Mundi

The geographic distributions of three large wasps, Sphecius speciosus (Drury), Stictia carolina Fabricius, and Stizus brevipennis Walsh (Hymenoptera: Crabronidae), occurring in Arkansas are defined using museum specimens and three internet-based data platforms. The internet-based data platforms generally provided more county location records than museum records. Using data from internet sources for easily identified species can better serve to illustrate the known distributions for some species thus making for a powerful tool elucidating distributional patterns and conservation planning.

ZooBank registration. urn:lsid:zoobank.org:pub:DCAE9192-1765-40CD-952B-0A094F413991

A Qualitative Exploration Of Factors Associated With Covid-19 Vaccine Uptake And Hesitancy In Selected Rural Communities In Kenya, Fletcher J. Njororai, Walter Amulla, Caleb Kogutu Nyaranga, Wilberforce Cholo, Toluwani Adekunle

Kinesiology Faculty Publications and Presentations

Purpose: The post-pandemic management of COVID-19 infections and any emergent outbreaks is because this endemic disease remains a public health concern. Vaccine hesitancy may continue to hamper efforts to respond to any new disease outbreaks and future epidemics. This qualitative study aimed to explore the factors influencing COVID-19 vaccine acceptance and hesitancy in Kenya to gain deeper insights into this issue. Methods: This study was implemented in western Kenya using key informant interviews. Fourteen (14) key informants were purposively selected for this study. All interviews were transcribed and analyzed using thematic analysis. The interpretation of findings was conducted within the …

Plas 439: Organic Farming And Food Systems Faculty-Led Inquiry Into Reflective Scholarly Teaching Benchmark Portfolio, Christian Stephenson

UNL Faculty Course Portfolios

Organic Farming and Food Systems is a senior and graduate level course for students in the Department of Agronomy and Horticulture. This course was previously offered but has been significantly modified as I have taken on responsibility for the course. Goals for the course include student comprehension of the methods of organic and regenerative farming and the impacts of those methods on economic, environmental, and social sustainability. An additional goal is to build student competency in the evaluation of primary, secondary, and tertiary information resources and critical thinking surrounding issues in food production. Assessment for the course was through diverse …

Morphometric Analysis And Taxonomic Re-Evaluation Of Pepsis Cerberus Lucas And P. Elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini), Frank E. Kurczewski, Akira Shimizu, Diane H. Kiernan

Insecta Mundi

Hurd (1952) separated Pepsis cerberus Lucas from P. elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini) based on external morphology and biogeography. Vardy (2005) synonymized the familiar and historically well-documented P. cerberus and P. elegans, combining these Nearctic taxa with several Neotropical variants in an extremely broad definition of P. menechma Lepeletier. In doing so, Vardy (2005) breached the principle of nomenclatural stability. He ignored the prevailing usage and clearly violated articles 23.2, 23.3 and 23.9.1.2 of the ICZN (1999). Morphological differences, ecological divergence, and narrow sympatric geographic distribution of P. cerberus and P. elegans …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites Field Sampling Plan (Fsp) Package #11: Ur-49 And Ur-50 (Dated May 6, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Borrow Amendment Submittal #1 (Dated May 9, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Request For Change (Rfc-Rmap-2024-001) (Dated May 9, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Charting A Path To The Quintuple Aim: Harnessing Ai To Address Social Determinants Of Health, Yash Shah, Zachary Goldberg, Erika Harness, David Nash

College of Population Health Faculty Papers

The Quintuple Aim seeks to improve healthcare by addressing social determinants of health (SDOHs), which are responsible for 70-80% of medical outcomes. SDOH-related concerns have traditionally been addressed through referrals to social workers and community-based organizations (CBOs), but these pathways have had limited success in connecting patients with resources. Given that health inequity is expected to cost the United States nearly USD 300 billion by 2050, new artificial intelligence (AI) technology may aid providers in addressing SDOH. In this commentary, we present our experience with using ChatGPT to obtain SDOH management recommendations for archetypal patients in Philadelphia, PA. ChatGPT identified …

Size-Constrained Weighted Ancestors With Applications, Philip Bille, Yakov Nekrich, Solon P. Pissis

Michigan Tech Publications, Part 2

The weighted ancestor problem on a rooted node-weighted tree T is a generalization of the classic predecessor problem: construct a data structure for a set of integers that supports fast predecessor queries. Both problems are known to require Ω(log log n) time for queries provided O(n poly log n) space is available, where n is the input size. The weighted ancestor problem has attracted a lot of attention by the combinatorial pattern matching community due to its direct application to suffix trees. In this formulation of the problem, the nodes are weighted by string depth. This research has culminated in …

What Climate Change Means For Nebraska

United States Environmental Protection Agency: Publications

Nebraska’s climate is changing. In the past century, most of the state has warmed by at least one degree (F). The soil is becoming drier, and rainstorms are becoming more intense. In the coming decades, flooding is likely to increase, yet summers are likely to become increasingly hot and dry, which would reduce yields of some crops, require farmers to use more water, and amplify some risks to human health.

Our climate is changing because the earth is warming. People have increased the amount of carbon dioxide in the air by 40 percent since the late 1700s. Other heat-trapping greenhouse …

Singleadv: Single-Class Target-Specific Attack Against Interpretable Deep Learning Systems, Eldor Abdukhamidov, Mohammed Abuhamad, George K. Thiruvathukal, Hyoungshick Kim, Tamer Abuhmed

Computer Science: Faculty Publications and Other Works

In this paper, we present a novel Single-class target-specific Adversarial attack called SingleADV. The goal of SingleADV is to generate a universal perturbation that deceives the target model into confusing a specific category of objects with a target category while ensuring highly relevant and accurate interpretations. The universal perturbation is stochastically and iteratively optimized by minimizing the adversarial loss that is designed to consider both the classifier and interpreter costs in targeted and non-targeted categories. In this optimization framework, ruled by the first- and second-moment estimations, the desired loss surface promotes high confidence and interpretation score of adversarial samples. By …

Unveiling The Metaverse: A Survey Of User Perceptions And The Impact Of Usability, Social Influence And Interoperability, Mousa Al-Kfairy, Ayham Alomari, Mahmood Al-Bashayreh, Omar Alfandi, Mohammad Tubishat

All Works

This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this analysis highlights the Metaverse's significant impact across various sectors, emphasizing its potential to reshape digital interaction paradigms. The investigation reveals usability as a cornerstone for user engagement, demonstrating how social dynamics profoundly influence user behaviors and choices within virtual environments. Furthermore, the study outlines interoperability as a paramount challenge, advocating for establishing unified protocols and technologies to facilitate seamless experiences across disparate Metaverse platforms. It advocates for the adoption …

Detecting Drifts In Data Streams Using Kullback-Leibler (Kl) Divergence Measure For Data Engineering Applications, Jeomoan Francis Kurian, Mohamed Allali

Engineering Faculty Articles and Research

The exponential growth of data coupled with the widespread application of artificial intelligence(AI) presents organizations with challenges in upholding data accuracy, especially within data engineering functions. While the Extraction, Transformation, and Loading process addresses error-free data ingestion, validating the content within data streams remains a challenge. Prompt detection and remediation of data issues are crucial, especially in automated analytical environments driven by AI. To address these issues, this study focuses on detecting drifts in data distributions and divergence within data fields processed from different sample populations. Using a hypothetical banking scenario, we illustrate the impact of data drift on automated …

Collisional Damping In Plasmonic Wakefield Accelerators, Maxime Pindrys

Honors Scholar Theses

We investigate the previously proposed role of collisional damping in plasmonic wakefield accelerators. Wakefields driven in a doped semi-conductor will exist in differing regimes dependent on the driving beam’s intensity. At low intensities, the mobility of free carrier electrons is limited. Here, wakefields will be small if the mean free path of an electron is short compared to the quiver amplitude of a free electron. After reaching a threshold intensity, conduction electrons in the semiconductor will be driven to such high speeds that their coulomb cross section will drop sharply. Here the resulting wakes will resemble those in a hollow …

Engineering Thermodynamics, Paul J. Marchese

Open Educational Resources

This collection of assignments is designed for an introductory thermodynamics class. It includes comprehensive readings that cover the fundamental concepts, problem sets to reinforce learning through practical application, and YouTube videos that provide detailed explanations and visual demonstrations of the material. These resources can be utilized in a regular classroom setting or for independent study, offering flexibility to accommodate different learning environments and preferences.

Re: Silver Bow Creek Conservation Area Repository Data Gap Quality Assurance Project Plan (Qapp), Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Annual Operations And Maintenance (O&M) Report: Butte Treatment Lagoon (Btl) System – 2023, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.