Digital Commons Network^™

Forging The Future: Strategic Approaches To Quantum Ai Integration For Industry Transformation, Meng Leong How, Sin Mei Cheah

CCX Research

The fusion of quantum computing and artificial intelligence (AI) heralds a transformative era for Industry 4.0, offering unprecedented capabilities and challenges. This paper delves into the intricacies of quantum AI, its potential impact on Industry 4.0, and the necessary change management and innovation strategies for seamless integration. Drawing from theoretical insights and real-world case studies, we explore the current landscape of quantum AI, its foreseeable influence, and the implications for organizational strategy. We further expound on traditional change management tactics, emphasizing the importance of continuous learning, ecosystem collaborations, and proactive approaches. By examining successful and failed quantum AI implementations, lessons …

Meta-Interpretive Learning With Reuse, Rong Wang, Jun Sun, Cong Tian, Zhenhua Duan

Research Collection School Of Computing and Information Systems

Inductive Logic Programming (ILP) is a research field at the intersection between machine learning and logic programming, focusing on developing a formal framework for inductively learning relational descriptions in the form of logic programs from examples and background knowledge. As an emerging method of ILP, Meta-Interpretive Learning (MIL) leverages the specialization of a set of higher-order metarules to learn logic programs. In MIL, the input includes a set of examples, background knowledge, and a set of metarules, while the output is a logic program. MIL executes a depth-first traversal search, where its program search space expands polynomially with the number …

Health And Safety Plan (Hasp) Butte Priority Soils Operable Unit, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – First Quarter 2022, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Conservation and Survey Division: Faculty and Staff Publications

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (>40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as response variables …

First Egg Dates Of Tree Swallows (Tachycineta Bicolor) Nesting In Boxes In West Michigan Advanced With Increasing Spring Temperatures Between 1993 And 2018, Michael P. Lombardo, Nathaniel Wagner, Jared M. Laughlin, Sango Otieno, Levi Rosendall, Clara Voetberg, Alejandro Hoban

Open Access Publishing Support Funded Articles

Many bird species have advanced their first egg dates in response to recent milder winters and increases in spring temperatures. Tree Swallows (Tachycineta bicolor) begin egg laying earlier in warmer springs at most, but not all, study sites. We examined whether Tree Swallows that nested in boxes in west Michigan responded to an increase in spring temperatures from 1993 to 2018 by advancing their first egg dates. May, but not April, mean daily temperatures got significantly warmer from 1993 to 2018. We found that the first egg dates, but not mean first egg dates, of both second year …

A 2,000-Year Record Of Eelgrass (Zostera Marina L.) Colonization Shows Substantial Gains In Blue Carbon Storage And Nutrient Retention, Martin Dahl, Martin Gullström, Irene Bernabeu, Oscar Serrano, Carmen Leiva-Dueñas, Hans W. Linderholm, Maria E. Asplund, Mats Björk, Tinghai Ou, J. Robin Svensson, Elinor Andrén, Thomas Andrén, Sanne Bergman, Sara Braun, Anneli Eklöf, Zilvinas Ežerinskis, Andrius Garbaras, Petter Hällberg, Elin Löfgren, Malin E. Kylander, Pere Masqué, Justina Šapolaitė, Rienk Smittenberg, Miguel A. Mateo

Research outputs 2022 to 2026

Assessing historical environmental conditions linked to habitat colonization is important for understanding long-term resilience and improving conservation and restoration efforts. Such information is lacking for the seagrass Zostera marina, an important foundation species across cold-temperate coastal areas of the Northern Hemisphere. Here, we reconstructed environmental conditions during the last 14,000 years from sediment cores in two eelgrass (Z. marina) meadows along the Swedish west coast, with the main aims to identify the time frame of seagrass colonization and describe subsequent biogeochemical changes following establishment. Based on vegetation proxies (lipid biomarkers), eelgrass colonization occurred about 2,000 years ago after geomorphological changes …

Introducing Pour Points: Characteristics And Hydrological Significance Of A Rainfall-Concentrating Mechanism In A Water-Limited Woodland Ecosystem, Ashvath S. Kunadi, Tim Lardner, Richard P. Silberstein, Matthias Leopold, Nik Callow, Erik Veneklaas, Aryan Puri, Eleanor Sydney, Sally E. Thompson

Research outputs 2022 to 2026

The interception of rainfall by plant canopies alters the depth and spatial distribution of water arriving at the soil surface, and thus the location, volume, and depth of infiltration. Mechanisms like stemflow are known to concentrate rainfall and route it deep into the soil, yet other mechanisms of flow concentration are poorly understood. This study characterizes pour points, formed by the detachment of water flowing under a branch, using a combination of field observations in Western Australian banksia woodlands and rainfall simulation experiments on Banksia menziesii branches. We aim to establish the hydrological significance of pour points in a water-limited …

Pollinator Communities And Their Ecosystem Services At Conservation Grasslands And Adjacent Croplands, Araceli Gomez Villegas

Department of Entomology: Dissertations, Theses, and Student Research

Pollinators are intrinsically linked to the success of unmanaged and managed ecosystems by providing pollination services that aid in the reproduction of wildflowers and many crops. Land use change, habitat loss, fragmentation, and related landscape-level phenomena (for example, increased pesticide exposure) threaten pollinators and have been associated with population declines. In the Midwestern region of the United States, land conversion of native prairies and grasslands to row-crop agriculture has been one of the largest contributors to pollinator habitat loss. Conservation programs, such as the Conservation Reserve Program, have worked towards removing environmentally sensitive lands from agriculture production and enrolling them …

Weakly Supervised Attention-Based Recognition Under Spectral, Turbulence, And Resource Variations, Kshitij Naresh Nikhal

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

While supervised optimization paradigms are ubiquitous across diverse recognition systems, the risk of over-fitting and increasing bias have limited their applicability.

This dissertation focuses on unsupervised learning—learning without precisely curated data—and argues that unsupervised learning methods can enable both discriminability and generalizability. Through the use of attention-based machine learning and advanced clustering, unsupervised methods are able to focus on fine-grained information in images without any explicit supervision. The dissertation introduces a domain-bridging framework for tasks like cross-spectrum matching and long-range recognition, utilizing intra-domain clustering and inter-domain matching to generate pseudo-labels. Additionally, a hash-based network is proposed to accelerate the search …

Water Quality Assessment For San Luis Obispo Creek And Stenner Creek, Brent Flemmer

Master of Science in Environmental Sciences and Management Projects

Water quality was assessed in five stream segments in San Luis Obispo and Stenner Creeks in Spring of 2023. Two of the five sites were located along San Luis Obispo Creek, and three located along Stenner Creek. Criteria to evaluate these aquatic systems was provided by the Standard Operating Procedures of the Surface Water Ambient Monitoring Program, formulated by the State Water Resources Control Board. These procedures describe the methodology surrounding the collection of chemical, physical, and biological parameters of stream systems; streamflow, substrate, flow habitat, chemical water quality, and benthic macroinvertebrates are some of the criteria collected that allows …

Utilization Of Caputo Fractional Derivative In Mhd Nanofluid Flow With Soret And Thermal Radiation Effects, Harshad Patel, Gopal Nanda

Applications and Applied Mathematics: An International Journal (AAM)

In existence of heat diffusion and thermal radiation, an analytical equation is found for unsteady MHD flow past an exponentially accelerating vertical plate in optically thick water based nanofluid. The governing equations are made dimensionless by similarity transformation. A definition of Caputo fractional derivative is applied to generalize governing system of partial differential equations. Laplace transform techniques are applied and obtained the analytical solutions of proposed problems. For a physical point of view, numerical results are obtained using MATLAB software and presented via graphs. From the results, it is concluded that magnetic fields tend to reduce velocity. It is also …

Stability Of Predator-Prey Model For Worm Attack In Wireless Sensor Networks, Rajeev Kishore, Padam Singh

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we propose a predator-prey mathematical model for analyzing the dynamical behaviors of the system. This system is an epidemic model, and it is capable of ascertaining the worm's spreading at the initial stage and improving the security of wireless sensor networks. We investigate different fixed points and examine the stability of the projected model.

Reconnecting A Stream Channel To Its Floodplain: Implications For Benthic Diatoms And Macroinvertebrate Trophic Structure, Patrick M. Edwards, Nicole C. Popp, Yangdong Pan, Christine L. Weilhoefer, Aspen Peterman, Lauren Mork, Matthew F. Johnson, Megan Colley, Multiple Additional Authors

Environmental Science and Management Faculty Publications and Presentations

Streams systems draining upland landscapes provide valuable ecosystem services, but they are vulnerable to incision and channelization caused by anthropogenic disturbance. Restoring a degraded stream to its pre-disturbance condition by reconnecting the channel to its historical floodplain aims to recover lost hydro-morphological processes and functions. Seeking evidence to indicate whether that aim is met in practice, we examined diatoms and the stream macroinvertebrate trophic structures in three reaches of Whychus Creek, Oregon, United States. Two reaches were reconnected to their pre-disturbance floodplains in 2012 and 2016. The third, control reach, was not restored and was selected to represent the degraded …

Soil Nitrate Prediction Using Ftir-Atr, Vis-Nir, And Raman Spectroscopy, Sabiha Ferdous

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Fourier transform infrared spectroscopy (FTIR) combined with Attenuated total reflectance (ATR), Visible-Near Infrared spectroscopy (Vis-NIR), and Raman spectroscopy (RS) are non-destructive techniques for rapid determination of nitrogen compounds in soil. Leveraging FTIR-ATR and Vis-NIR spectra using partial least squares regression (PLSR) modeling, the study aims to predict soil nitrate content and explored the feasibility of Raman spectroscopy to detect nitrate (NO₃^-), nitrite (NO₂^-), and ammonium (NH₄⁺) in soil. Soil samples were collected from four different fields, dried, sieved (2mm), and then used for collecting spectra (FTIR-ATR and Vis-NIR). Laboratory analysis was …

Gsword: Gpu-Accelerated Sampling For Subgraph Counting, Chang Ye, Yuchen Li, Shixuan Sun, Wentian Guo

Research Collection School Of Computing and Information Systems

Subgraph counting is a fundamental component for many downstream applications such as graph representation learning and query optimization. Since obtaining the exact count is often intractable, there have been a plethora of approximation methods on graph sampling techniques. Nonetheless, the state-of-the-art sampling methods still require massive samples to produce accurate approximations on large data graphs. We propose gSWORD, a GPU framework that leverages the massive parallelism of GPUs to accelerate iterative sampling algorithms for subgraph counting. Despite the embarrassingly parallel nature of the samples, there are unique challenges in accelerating subgraph counting due to its irregular computation logic. To address …

Transiam: Aggregating Multi-Modal Visual Features With Locality For Medical Image Segmentation, Xuejian Li, Shiqiang Ma, Junhai Xu, Jijun Tang, Shengfeng He, Fei Guo

Research Collection School Of Computing and Information Systems

Automatic segmentation of medical images plays an important role in the diagnosis of diseases. On single-modal data, convolutional neural networks have demonstrated satisfactory performance. However, multi-modal data encompasses a greater amount of information rather than single-modal data. Multi-modal data can be effectively used to improve the segmentation accuracy of regions of interest by analyzing both spatial and temporal information. In this study, we propose a dual-path segmentation model for multi-modal medical images, named TranSiam. Taking into account that there is a significant diversity between the different modalities, TranSiam employs two parallel CNNs to extract the features which are specific to …

Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch

Chemistry Faculty Research & Creative Works

Biomedical Datasets Distill Many Mechanisms Of Human Diseases, Linking Diseases To Genes And Phenotypes (Signs And Symptoms Of Disease), Genetic Mutations To Altered Protein Structures, And Altered Proteins To Changes In Molecular Functions And Biological Processes. It Is Desirable To Gain New Insights From These Data, Especially With Regard To The Uncovering Of Hierarchical Structures Relating Disease Variants. However, Analysis To This End Has Proven Difficult Due To The Complexity Of The Connections Between Multi-Categorical Symbolic Data. This Article Proposes Symbolic Tree Adaptive Resonance Theory (START), With Additional Supervised, Dual-Vigilance (DV-START), And Distributed Dual-Vigilance (DDV-START) Formulations, For The Clustering Of …

Identifying Environmental And Genetic Risk Factors Of Diseases In Case-Control Studies, Siting Li

Dartmouth College Ph.D Dissertations

In response to the increasing efforts in disease prevention and treatment, this thesis applies statistical methods to investigate environmental and genetic risk factors associated with two diseases: bladder cancer and amyotrophic lateral sclerosis (ALS). For bladder cancer, we investigated the association between toenail metal mixture and bladder cancer risk, along with gene expression levels associated with bladder cancer risk. For ALS, our investigation involves identifying genetic variants and gene expression levels associated with ALS risk and exploring gene-smoking interactions linked to ALS risk.

In chapter two, we developed an adaptive-mixture-categorization (AMC)-based g-computation method combining g-computation with optimized exposure categorization. We …

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2022, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Limonene Enantiomeric Ratios From Anthropogenic And Biogenic Emission Sources, Shan Gu, Wentai Luo, Avisa Charmchi, Kevin J. Mcwhirter, Todd Rosenstiel, James F. Pankow

Chemistry Faculty Publications and Presentations

Emissions from volatile chemical products (VCPs) have been identified as contributors to air quality degradation in urban areas. Limonene can be a tracer compound for VCPs containing fragrances in densely populated regions, but limonene is also emitted from conifers that are planted in urban areas. This creates challenges for using limonene to estimate VCP emissions. In this study, the −/+ enantiomeric ratios of limonene from VCP and conifer emission sources were quantified to evaluate if this measurement could be used to aid in source apportionment and emission inventory development. Samples were analyzed using a gas chromatograph equipped with a chiral …

Using Flipped Classroom Modules To Facilitate Higher Order Learning In Undergraduate Organic Chemistry, Lauren R. Holloway, Tabitha Miller, Bryce Da Camara, Paul M. Bogie, Briana L. Hickey, Jack Barbera, Angie L. Lopez, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

In an ongoing effort to incorporate active learning and promote higher order learning outcomes in undergraduate organic chemistry, a hybrid (“flipped”) classroom structure has been used to facilitate a series of collaborative activities in the first two courses of the lower division organic chemistry sequence. An observational study of seven classes over a five-year period reveals there is a strong correlation between performance on the in-class activities and performance on the final exam across all classes; however, a significant number of students in these courses continue to struggle on both the in-class activities and final exam. The Activity Engagement Survey …

The Α-Crystallin Chaperones Undergo A Quasi-Ordered Co-Aggregation Process In Response To Saturating Client Interaction, Kirsten Lampi, Adam P. Miller, Susan E. O'Neill, Steve L. Reichow

Chemistry Faculty Publications and Presentations

Small heat shock proteins (sHSPs) are ATP-independent chaperones vital to cellular proteostasis, preventing protein aggregation events linked to various human diseases including cataract. The α-crystallins, αA-crystallin (αAc) and αB-crystallin (αBc), represent archetypal sHSPs that exhibit complex polydispersed oligomeric assemblies and rapid subunit exchange dynamics. Yet, our understanding of how this plasticity contributes to chaperone function remains poorly understood. This study investigates structural changes in αAc and αBc during client sequestration under varying degree of chaperone saturation. Using biochemical and biophysical analyses combined with single-particle electron microscopy (EM), we examined αAc and αBc in their apo-states and at various stages of …

Exploitation Of Environmental Dna (Edna) For Ecotoxicological Research: A Critical Review On Edna Metabarcoding In Assessing Marine Pollution, Sakib Tahmid Rishan, Richard Kline, Md Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Highlights

• eDNA describes the genetic material of organisms present in aquatic environments.

• eDNA metabarcoding characterizes DNA of various marine species from a single sample.

• eDNA has enormous promise for ecotoxicological research in marine environments.

Abstract

The rise in worldwide population has led to a noticeable spike in the production, consumption, and transportation of energy and food, contributing to elevated environmental pollution. Marine pollution is a significant global environmental issue with ongoing challenges, including plastic waste, oil spills, chemical pollutants, and nutrient runoff, threatening marine ecosystems, biodiversity, and human health. Pollution detection and assessment are crucial to understanding the state of …

Design Considerations For The Use Of The Julia Programming Language In Future Quantum Networking Simulation Software, Takashi Joubert

Theses and Dissertations

Given the prevalence of Python-based packages in the existing quantum network simulation ecosystem, we attempt to assess what might be realistically gained by switching to Julia. We focus our experimental activities on three areas: 1) surveying the characteristics of Julia as they tie into robust framework development, 2) presenting benchmarks that compare Julia and Python with respect to elements of possible simulation workloads, and 3) producing a tangible lightweight Julia architecture for modeling components in a manner similar to SeQUeNCe. Our analysis suggests that while Julia does o.er performance advantages over Python over certain workloads, knowing the reasons for why …

On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo

Theses and Dissertations

The concept of Intrinsic Dimensionality (ID) is of special interest in the field of Neural Networks (NNs) since it promotes both (a) a deeper understanding of the underlying mechanisms, and (b) embraces parsimonious modeling (that is, building the right-sized model for the task) with associated benefits to processing speed and storage requirements. This thesis explores the concept of ID via two separate, but related, questions. First, we study the potential of NN ID prediction by exploiting easily obtained quantities measured on the data. We then explore NN ID as an independent concept by comparing the results of different methods for …

An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge

Theses and Dissertations

This research examines China and derives insights specific to it and the First Island Chain and the Second Island Chain. In doing so, this research demonstrates a methodology to examine other competitors and their geostrategic interests. In the first phase of analysis, it develops a value hierarchy to depict objectives within subregions of the area of interest and considers four alternative weightings of the value hierarchy. In the second phase of analysis, it applies four location-covering models to assess how the competitor would emplace a range of limited resources to deter and/or control points of interest. Results indicate that land-based …

Artificial Intelligence And Perception: An Empirical Study, Anthony J. Neil

Theses and Dissertations

This thesis investigates the impact of adjusting artificial intelligence explainability levels’ outputs on user perception. The overarching study extends within the Explainable Artificial Intelligence (XAI) domain. It examines a spectrum of variables, including performance, cognizance, familiarity, transparency, system bias, and the overall impact of AI, to understand their collective and individual effects that enable effective professional use in an organization. The study aims to illuminate the relationship between the degree of explainability provided by large language models such as ChatGPT, Bard, and Bing AI and the performance of these models when tasked with XAI adjustments.

Single Particle Analysis Of Operation Roller Coaster Environmental Samples, Caleb J. Sapp

Theses and Dissertations

The release of plutonium and other actinides into the environment following a nuclear detonation or accident, poses a health risk to biological systems. The spread, or transportation of that plutonium and its daughter products through environmental and meteorological means increases the potential affect and inherent danger within the surrounding area. In the 1960’s, a study was conducted in a joint effort by the US and Great Britain to collect information regarding the spread of plutonium released into the environment through a sub-critical detonation. Soil samples from these tests were collected by the USAF in 2015, approximately 50 years after these …

Voice Synthesis Improvement By Machine Learning Of Natural Prosody, Joseph Kane, Michael N. Johnstone, Patryk Szewczyk

Research outputs 2022 to 2026

Since the advent of modern computing, researchers have striven to make the human–computer interface (HCI) as seamless as possible. Progress has been made on various fronts, e.g., the desktop metaphor (interface design) and natural language processing (input). One area receiving attention recently is voice activation and its corollary, computer-generated speech. Despite decades of research and development, most computer-generated voices remain easily identifiable as non-human. Prosody in speech has two primary components—intonation and rhythm—both often lacking in computer-generated voices. This research aims to enhance computer-generated text-to-speech algorithms by incorporating melodic and prosodic elements of human speech. This study explores a novel …