Physical Sciences and Mathematics Commons^™

“Use” As A Conscious Thought: Towards A Theory Of “Use” In Autonomous Things, Gohar Khan, A Karim Feroz

All Works

The way users perceive and use information systems artefacts has been mainly studied from the notion of behavioral beliefs, deliberate cognitive efforts, and physical actions performed by human actors to produce certain outcomes. The next generation of information systems, however, can sense, respond, and adapt to environments without necessitating similar cognitive efforts, physical contact, or explicit instructions to operate. Therefore, by leveraging theories of consciousness and technology use, this research aims to advance an alternative understanding of the "use" associated with the next generation of IS artefacts that do not require deliberate cognitive efforts, physical manipulation, or explicit instructions to …

Embodied Visions: Interactive Installations That Reimagine Bodily Presence In Digital Imaging Apparatuses As Shadows, Yunzi Shi

Dartmouth College Master’s Theses

Contextualized within a history of technological development, the evolution of imaging devices and technologies is accompanied by the abstraction of spatial relationships between the body of the observer, the apparatus, and physical reality, which leads to disembodying experiences for the observing subject. Compared with devices and interactive experiences, critical reflection on the epistemological impact of digital imaging devices has less priority in computational imaging and human-computer interaction research. Taking an artistic approach, this thesis describes Embodied Visions, an exhibition featuring three interactive installations exploring the technical infrastructure for imaging and reflecting on the (dis)embodied experiences in the digital age. …

Improving 2–5 Qubit Quantum Phase Estimation Circuits Using Machine Learning, Charles Woodrum [*], Torrey J. Wagner, David E. Weeks

Faculty Publications

Quantum computing has the potential to solve problems that are currently intractable to classical computers with algorithms like Quantum Phase Estimation (QPE); however, noise significantly hinders the performance of today’s quantum computers. Machine learning has the potential to improve the performance of QPE algorithms, especially in the presence of noise. In this work, QPE circuits were simulated with varying levels of depolarizing noise to generate datasets of QPE output. In each case, the phase being estimated was generated with a phase gate, and each circuit modeled was defined by a randomly selected phase. The model accuracy, prediction speed, overfitting level …

Conceptualising And Enacting Pathways To Transformative Climate Justice: Examples From The Philippines, Justin See, Anne Shangrila Fuentes, Emma Porio, Brooke Wilmsen

Sociology & Anthropology Department Faculty Publications

Scholarship on climate change adaptation is increasingly moving from incremental responses to climate injustice towards transformative approaches that deliberately change systems to achieve just and equitable outcomes. A transformative understanding of climate justice is relatively new and evidence of how this could be achieved is in its infancy. In this paper, we conceptualise transformative climate justice as comprised of three subcomponents: (1) inclusive justice (seeking to ensure that no one, especially the most vulnerable, is left behind), (2) epistemological justice (drawing upon diverse knowledges and worldviews), and (3) restorative justice (healing and restoration of communities and the environment). We then …

Implementation And Numerical Simulation On Object-Oriented Elastic-Plastic Finite Element Method Based On Python, Henghui Li, Yingxiong Xiao

Journal of System Simulation

Abstract: With the continuous expansion of the application fields of finite element methods, higher requirements are put forward for the scalability of finite element methods. In order to overcome the defects of the traditional finite element methods, a simple and easily extensible object-oriented elasticplastic finite element program framework is proposed based on Python. Combined with the characteristics of Python, we design some finite element classes such as the pre-processing class, the post-processing class, the linear solution class, the stress integration class and the analysis class. By applying the resulting framework to several typical elastic-plastic mechanical problems and comparing the results …

Hierarchical Guided Enhanced Multi-Objective Firefly Algorithm, Jia Zhao, Zhizhen Lai, Runxiu Wu, Zhihua Cui, Hui Wang

Journal of System Simulation

Abstract: The multi-objective firefly algorithm is easy to produce oscillation and aggregation phenomenon in the solution process, which leads to weak development ability and poor solution accuracy. This paper proposes a hierarchical guided enhanced multi-objective firefly algorithm (HGEMOFA). HGEMOFA builds a hierarchical guidance model, uses non-dominated sorting to obtain different levels of individuals. The individuals in the dominant layer are used to guide the evolution of the individuals in the inferior layer, the guidance direction is clear, the oscillation in the evolution process is solved, the aggregation phenomenon is reduced, and the convergence of the algorithm is enhanced. The Lévy …

Advective And Diffusive Gas Phase Transport In Vadose Zones: Importance For Defining Vapour Risks And Natural Source Zone Depletion Of Petroleum Hydrocarbons, Kaveh Sookhak Lari, Greg B. Davis, John L. Rayner, Trevor P. Bastow

Research outputs 2022 to 2026

Quantifying the interlinked behaviour of the soil microbiome, fluid flow, multi-component transport and partitioning, and biodegradation is key to characterising vapour risks and natural source zone depletion (NSZD) of light non-aqueous phase liquid (LNAPL) petroleum hydrocarbons. Critical to vapour transport and NSZD is transport of gases through the vadose zone (oxygen from the atmosphere, volatile organic compounds (VOCs), methane and carbon dioxide from the zone of LNAPL biodegradation). Volatilisation of VOCs from LNAPL, aerobic biodegradation, methanogenesis and heat production all generate gas pressure changes that may lead to enhanced gas fluxes apart from diffusion. Despite the importance of the gaseous …

Testing Hadronic-Model Predictions Of Depth Of Maximum Of Air-Shower Profiles And Ground-Particle Signals Using Hybrid Data Of The Pierre Auger Observatory, A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, K. Nguyen, D. Nitz, Et Al.

Michigan Tech Publications, Part 2

We test the predictions of hadronic interaction models regarding the depth of maximum of air-shower profiles, Xmax, and ground-particle signals in water-Cherenkov detectors at 1000 m from the shower core, S(1000), using the data from the fluorescence and surface detectors of the Pierre Auger Observatory. The test consists of fitting the measured two-dimensional (S(1000), Xmax) distributions using templates for simulated air showers produced with hadronic interaction models epos-lhc, qgsjet-ii-04, sibyll 2.3d and leaving the scales of predicted Xmax and the signals from hadronic component at ground as free-fit parameters. The method relies on the assumption that the mass composition remains …

Engineering And Geological Zoning Of The Distribution Areas Of The Eocene Clays Of Northern Tamdytau, Mirabbas Mirsaatovich Zakirov, Inobat Abduvaxidovna Agzamova, Dilshod Kalandarovich Begimkulov, Golibjon Ernazar Ogli Ochilov, Temur Makhmarajabovich Khudoyberdiyev, Dastan Jamal Uli Madiyarov

Technical science and innovation

The article discusses scientific research on the integrated assessment of the problem of ensuring the sustainability of buildings and structures for industrial and civil purposes. The relevance is due to the development of various zoning methods to establish territories with reliable results on the spread of special soils. Especially in cases where swelling clays are common in the territory, characterized by high sensitivity to weather and climatic conditions. Based on the above, the purpose of engineering and geological zoning of the areas of distribution of Eocene clays of Northern Tamdytau was to identify areas of new construction, to ensure the …

Loneliness And Parental Relationships Among College Students, Alanna James, Charlie Barna

Symposium of Student Scholars

The transition to adulthood is a unique developmental period that involves rapid changes in youths’ individual development and social contexts, which can involve leaving behind familiar support networks (Eeske et al,. 2015). Common experiences during the transition to adulthood, like leaving home, pursuing college, and entering the workforce can leave individuals feeling marginalized and cutoff (Mathews et al,. 2022). Loneliness is a subjective feeling experienced by individuals in all age demographics (Matthews et al,. 2022). Despite a wide array of research on social connectedness interventions for older adults and people with physical disabilities (Zagic et al,. 2021), there is little …

Generating Channel Morphology Data Through Arcgis Pro, Ethan Manigbas

Symposium of Student Scholars

River cross-sections are often extracted using field surveys at measured intervals. This field-oriented approach allows for a tangible relationship between the data and its collector but at the expense of finance, time, labor, and potentially the environment. With the advancement of geospatial tools, such data can be found online, extracted, and even analyzed with contemporary Geographic Information Systems (GIS) in a completely virtual setting, transcending the need for fieldwork in select project topics. We tested this approach with the help of ArcGIS Pro software on the Vishnu Springs headwater stream located in the Western Illinois region of the Upper Mississippi …

The Classification Of Internet Memes Through Supervised And Unsupervised Machine Learning Algorithms, William H. Little

Symposium of Student Scholars

Memes, those captivating internet phenomena, effortlessly deliver online entertainment. By leveraging time-series data from Google Trends, we can vividly illustrate and dissect the dynamic trends in meme popularity. Previous studies have discerned four distinct post-peak popularity patterns— "smoothly decaying," "spikey decaying," "leveling off," and "long-term growth"—and elegantly modeled these using ordinary differential equations.

This research introduces a programmatic approach that harnesses both supervised and unsupervised machine learning algorithms. The dataset, now expanded to over 2000 elements, becomes the canvas for exploration. The K-means algorithm identifies clusters, which then serve as labels for the supervised SVC algorithm. The overarching goal is …

Tree Recovery By Dynamic Programming, Gustavo Alberto Gratacos

McKelvey School of Engineering Theses & Dissertations

Tree-like structures are common, naturally occurring objects that are of interest to many fields of study, such as plant science and biomedicine. Analysis of these structures is typically based on skeletons extracted from captured data, which often contain spurious segments or cycles that need to be removed. We propose a dynamic programming algorithm which seeks to recover directed trees from these noisy skeletons. Our method recovers trees by removing edges and duplicating nodes while adhering to edge-label constraints. Our algorithm proceeds by iteratively merging graph nodes, such that the solution on the original graph can be obtained from those on …

Latent Auto-Recursive Composition Engine: A Generative System For Creative Expression In Human-Ai Collaboration, Yenkai Huang

Computer Science Senior Theses

This thesis investigates the shifting boundaries of art in the era of Generative AI, crit-
ically examining the essence of art and the legitimacy of AI-generated works. Despite
significant advancements in the quality and accessibility of art through generative
AI, such creations frequently encounter skepticism regarding their status as authentic
art. To address this skepticism, the study explores the role of creative agency in var-
ious generative AI workflows and introduces an ”artist-in-the-loop” system tailored
for image generation models like Stable Diffusion. This system aims to deepen the
artist’s engagement and understanding of the creative process. Additionally, a novel
tool, …

Constructible Sandwich Cut, Philip A. Son

FIU Undergraduate Research Journal

In mathematical measure theory, the “Ham-Sandwich” theorem states that any n objects in an n-dimensional Euclidean space can be simultaneously divided in half with a single cut by an (n-1)-dimensional hyperplane. While it guarantees its existence, the theorem does not provide a way of finding this halving hyperplane, as it is only an existence result. In this paper, we look at the problem in dimension 2, more in the style of Euclid and the antique Greeks, that is from a constructible point of view, with straight edge and compass. For two arbitrary regions in the plane, there is certainly no …

An Examination Of The Ways In Which Transdisciplinary Research Could Be Used To Incentivize Local Communities To Combat The Illegal Wildlife Trade, Jessica Rios

FIU Undergraduate Research Journal

The illegal wildlife trade (IWT) is currently one of the most critical conservation concerns, given its direct impact on biodiversity loss, endangering local ecosystems, and adding pressure to all species at a point when they face dangers like deforestation and mass extinctions. This industry also significantly impacts local communities, many of which are compelled to engage in it as a result of their precarious socioeconomic conditions. While effective countermeasures to this global issue have been identified, successful implementation of these countermeasures require diverse disciplines and collaborators. This paper argues that a transdisciplinary approach that converges knowledge and skills from social …

The State Of Knowledge Of Cca Diversity In The Caribbean Coral Reefs, Danielle Macias, Alain Duran, Fabio Nauer

FIU Undergraduate Research Journal

Crustose coralline algae (CCA) are a diverse and ecologically important species found in most of the world’s oceans. The current lack of taxonomic knowledge and relative abundance compromises our ability to predict species diversity numbers and, thus, their ecological roles and impacts on coral reefs. To gather a better understanding of the state of knowledge of crustose coralline algae taxonomy in the Caribbean, 107 different research papers, and other primary and secondary literature were studied; any source with taxonomical information, species identification, or genetic markers for identification was recorded. All Genebank codes were collected and sorted by supposed species marker …

Understanding The Health Impacts Of Vehicular Emissions In South Florida: A Comprehensive Analysis, Janelle Ducheine, Noah Horesh, Jason C. Quinn

FIU Undergraduate Research Journal

South Florida is famous for its diverse cultural scene and year-round sunshine. This success, however, has not been without its consequences. While the region enjoys economic prosperity, the hidden cost of deteriorating air quality and adverse health effects from vehicle emissions necessitates urgent attention. Electric vehicles (EVs) have emerged as a potential solution, promising reduced emissions, and increased energy efficiency. However, the intricate life cycle emissions associated with EV energy production raise questions about their net benefits. Using predictive modeling and historical data, the study forecasts emissions trajectories and assesses their health implications. Results indicate a substantial reduction in pollutants …

Using Geochemical Tracers To Determine Seasonal Inputs Of Freshwater To A Coastal Estuary: Biscayne Bay, Fl, Melaney Lara, Rene M. Price

FIU Undergraduate Research Journal

Biscayne Bay is a coastal estuary that historically relied on rainfall and groundwater inputs from the karst Biscayne aquifer. The construction of major canals along the coastline has released point-source freshwater inputs into the bay, detrimentally affecting the Bay’s ecosystem balance. This project investigates the proportional inputs of freshwater between the wet and dry seasons in Deering Estate, adjacent to Biscayne Bay. The objective of this project was accomplished by analyzing the water chemistry of the bay using naturally occurring geochemical tracers. Water sampling occurred from May to August (wet season 2022) and January to March (dry season 2023); at …

Implications Of Microplastic Pollution For The Conservation Of Marine Protected Areas, Estefany D. Carvajal, Amanda Di Perna, Alain Duran

FIU Undergraduate Research Journal

Marine Protected Areas (MPAs) function as a tool for the protection and conservation of marine ecosystems. These designated areas should be free of any environmentally harmful pollutants. Microplastics (MPs) are plastic fragments measuring less than 5 mm (about 0.2 in). These fragments are an emerging threat to our oceans, and we are investigating the effectiveness of MPAs against these pollutants. We analyzed data gathered from research conducted on microplastic concentrations in MPAs and non-MPAs around the world. 53 MPAs and 53 non-MPAs around the world were used and the microplastic concentrations were deemed low, medium, or high by using the …

Exploring Neural Networks For Breast Cancer Tissue Classification, Stephen Jacobs, Md Abdullah Al Hafiz Khan

Symposium of Student Scholars

Last year, more than 240 thousand women in the United States were diagnosed with breast cancer. These patients are benefitting from decades of data that have been collected by cancer research institutions around the world. Tissue samples are analyzed and cataloged by these institutions, and several facilities like the University of Wisconsin are sharing this historical data to promote the advancement of new cancer treatments. Deep learning and neural network models are being built for this data to help doctors diagnose faster and design treatment options for patients by comparing their tissue samples with these historical datasets. We will use …

05-13--2024 Orsp Newsletter, Liz Williamson

ORSP Newsletter

Distinguished Research and Creative Achievement Award, Center for Practical Ethics, DARPA Connect, Air Force Internship

Analysis And Computation Of Constrained Sparse Coding On Emerging Non-Von Neumann Devices, Kyle Henke

Mathematics & Statistics ETDs

This dissertation seeks to understand how different formulations of the neurally inspired Locally Competitive Algorithm (LCA) represent and solve optimization problems. By studying these networks mathematically through the lens of dynamical and gradient systems, the goal is to discern how neural computations converge and link this knowledge to theoretical neuroscience and artificial intelligence (AI). Both classical computers and advanced emerging hardware are employed in this study. The contributions of this work include:

1. Theoretical Work: A comprehensive convergence analysis for networks using both generic Rectified Linear Unit (ReLU) and Rectified Sigmoid activation functions. Exploration of techniques to address the binary …

Thermal Physiology Of Sceloporus Olivaceus And Sceloporus Variabilis In South Texas, Ian Rockel

Masters Theses

This study explores the thermal physiology of two sympatric lizard species, Sceloporus olivaceus (Texas spiny lizard) and Sceloporus variabilis (rose-bellied lizard), in South Texas. I document the metabolic rate and its temperature sensitivity, thermal limits, and performance at different temperatures to better understand the impact of rising temperatures and urbanization on these ectotherms, whose body temperature and, consequently, metabolic rate, activity level, and reproductive success depend on their thermal environment. We hypothesize that S. olivaceus will exhibit greater thermal resilience owing to its broader latitudinal range, variable habitat usage within Texas, and presumed more versatile thermoregulatory strategies. Scelorporus olivaceus's higher …

Effects Of Ti Addition On The Characteristics Of Al-10zn-6mg-2si/Zro2 Composites Produced By Squeeze Casting, Qesha Diva Prameshvara, Pipin Indah Lestari, Bondan Tiara Sofyan

Journal of Materials Exploration and Findings

Metal matrix composite (MMC) with 7xxx aluminum matrix is potential for ballistic applications due to the combination of strength, toughness, and light weight. Previous study successfully produced aluminum-based composites with SiC particles which were able to stop type III bullet, however cracks remained on back of the plate. Therefore, in this research, SiC was replaced by zirconia (ZrO₂) due to its high fracture toughness. Ti-B grain refiner was added to further improve toughness through grain boundary strengthening mechanism. This research developed 5 vol.% ZrO₂ strengthened Al-10Zn-6Mg-2Si composite with addition of Al-5Ti-1B grain refiner produced through squeeze casting …

Integration Of The Ashby Technique And Pahl-Beitz Quantitative Ranking For Railway Axle Material Selection, Helya Chafshoh Nafisah, Jaka Fajar Fatriansyah, Siti Norasmah Surip

Journal of Materials Exploration and Findings

Railway axle serves as a vital connection between the train's wheels and its body. However, cyclic loading and high speed can induce fatigue in railway axle, which potentially leads to damage human safety. Therefore, it is important to find materials that have good mechanical properties with the lowest weight and cost. In this paper, a comprehensive method using Ashby chart has been performed to select candidate materials of railway axle. The methods begin with analyzing function by determining the problem, objective function, and constraints. After that, the results obtained are ranked using Pahl and Beitz quantitative weighting method. The results …

Toward Intuitive 3d Interactions In Virtual Reality: A Deep Learning- Based Dual-Hand Gesture Recognition Approach, Trudi Di Qi, Franceli L. Cibrian, Meghna Raswan, Tyler Kay, Hector M. Camarillo-Abad, Yuxin Wen

Engineering Faculty Articles and Research

Dual-hand gesture recognition is crucial for intuitive 3D interactions in virtual reality (VR), allowing the user to interact with virtual objects naturally through gestures using both handheld controllers. While deep learning and sensor-based technology have proven effective in recognizing single-hand gestures for 3D interactions, research on dual-hand gesture recognition for VR interactions is still underexplored. In this work, we introduce CWT-CNN-TCN, a novel deep learning model that combines a 2D Convolution Neural Network (CNN) with Continuous Wavelet Transformation (CWT) and a Temporal Convolution Network (TCN). This model can simultaneously extract features from the time-frequency domain and capture long-term dependencies using …

Characteristics Based Factor Models - Comparison Of Estimation Procedures, Henri Ohl

McKelvey School of Engineering Theses & Dissertations

Understanding cross-sectional and time series variation of asset returns is fundamental in finance, particularly in asset pricing. This thesis explores the integration of factor theory with machine learning to deepen our comprehension of these dynamics. Characteristics based factor models offer a systematic framework for quantifying an asset's underlying risk-return structure, leveraging time-varying conditional information on model parameters carried by firm-specific characteristics. These models serve as valuable tools for discerning the driving components of an asset's expected excess return. Recent research established a novel methodology for consistent parameter estimation within this framework, only requiring a large cross-section but not a long …

Assessing Reproducibility Of Brain-Behavior Associations Using Bootstrap Aggregation Methods, Zhetao Chen

Arts & Sciences Electronic Theses and Dissertations

在本论文中，随着越来越多地利用静息态功能连接 MRI (rs-fcMRI) 将神经活动与病理状况联系起来，我们面临着对此类数据可靠性的普遍担忧。我们的探索集中于提高人类连接组计划（HCP）数据集框架内大脑行为关联的可重复性。我们采用两种不同的引导聚合方法来研究功能连接可靠性的增强：使用循环块引导（CBB）的单独时间序列装袋和使用线性支持向量回归（LSVR）模型的主题级装袋。我们对 CBB 个体时间序列 bagging 的调查表明，这种方法并不能显着增强大脑行为关联的可重复性。这一发现指出了实现可靠的功能连接措施的复杂性以及某些聚合方法在克服这一挑战方面的局限性。相比之下，我们的学科水平考试 通过 LSVR 模型装袋呈现出更有希望的结果。这种方法显着增强了分析之间模型权重的可靠性，证明了其在提高数据稳健性和可重复性方面的功效。两种方法的这种不同影响强调了适当的分析策略在提高神经影像数据可靠性方面的关键作用。通过描述这两种方法的结果，本论文有助于对神经影像领域的数据可靠性进行更广泛的讨论。它强调了在不同数据集上持续进行方法创新和验证的必要性，以提高 rs-fcMRI 研究的可靠性和可解释性。

Analysis Of The Effect Of Different Surface Preparation Methods On Corrosion Resistance And Adhesion Strength Of Astm A36 Steel Substrate With Surface Tolerant Epoxy Paint As Coating Material, Irwan Wijaya Santoso, Daffa Aqila, Rini Riastuti, Rizal Tresna Ramadhani

Journal of Materials Exploration and Findings

In the industrial world, to extend the service life of materials, protection methods are carried out to slow down the material's corrosion rate. The protection method that is often used is the coating method. The coating method is a protection method by coating the substrate material using a coating material to prevent contact between the substrate material and the environment. In this research, the substrate material used is ASTM A36 steel and the coating material used is Surface Tolerant Epoxy paint. The independent variable used in this study lies in the surface preparation method which consists of: solvent cleaning, hand …