Physical Sciences and Mathematics Commons^™

Measuring The Misplacement Of Data From Multidimensional Scaling, Lucy Liu

Holster Scholar Projects

Multidimensional scaling (MDS), in which high-dimensional data is projected to a lower dimensional map, is often followed by clustering in the reduced plot. To examine the effect of MDS on clustering, we simulate several data structures and apply clustering methods, including topological data analysis. We first perform clustering using the data in the original, high-dimensional space, then perform MDS to scale the data down to a lower dimension, cluster on this scaled data, and compare differences in the results. We found that MDS can often decrease clustering performance, and is unable to correctly represent data structures with unique shapes or …

Bibliography For "Ai: The Next Chapter Display", Arianna Tillman, Isabella Piechota

Library Displays and Bibliographies

A bibliography created to support a display about artificial intelligence at the Leatherby Libraries during Fall 2024 at the Leatherby Libraries at Chapman University.

Hisoma: A Hierarchical Multi-Agent Model Integrating Self-Organizing Neural Networks With Multi-Agent Deep Reinforcement Learning, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Multi-agent deep reinforcement learning (MADRL) has shown remarkable advancements in the past decade. However, most current MADRL models focus on task-specific short-horizon problems involving a small number of agents, limiting their applicability to long-horizon planning in complex environments. Hierarchical multi-agent models offer a promising solution by organizing agents into different levels, effectively addressing tasks with varying planning horizons. However, these models often face constraints related to the number of agents or levels of hierarchies. This paper introduces HiSOMA, a novel hierarchical multi-agent model designed to handle long-horizon, multi-agent, multi-task decision-making problems. The top-level controller, FALCON, is modeled as a class …

Generative Ai In Software Engineering Must Be Human-Centered: The Copenhagen Manifesto, D. Russo, S. Van Berkel Baltes, Christoph Treude

Research Collection School Of Computing and Information Systems

The advent of Generative Artificial Intelligence—systems that can produce human-like content such as text, music, visual art, or source code—marks not only a significant leap for Artificial Intelligence (AI) but also a pivotal moment for software practitioners and researchers. The role of software engineering researchers and practitioners in adopting the technologies that shape our world is critical. Historically, the human aspects of developing software have been treated as secondary to more technical innovations. However, the emergence of Generative AI will simultaneously enhance human capabilities while surfacing complex ethical, social, legal, and technical challenges.While primarily aimed at software engineering (SE) researchers …

Does Ceo Agreeableness Personality Mitigate Real Earnings Management?, Shan Liu, Xingying Wu, Nan Hu

Research Collection School Of Computing and Information Systems

Despite efforts to mitigate aggressive financial reporting, earnings management remains challenging to parties interested in inhibiting its dysfunctional effects. Using linguistic algorithms to assess CEO agreeableness personality from their unscripted texts in conference calls, we find that it is a determinant that mitigates a firm's real earnings management. Furthermore, such an effect is more pronounced when firms confront intensive market competition and financial distress and have weaker managerial entrenchment or when CEOs face stronger internal governance. Our findings persist even after we utilize several alternative real earnings management metrics and control other confounding personalities in prior earnings management studies. The …

Ocapo: Fine-Grained Occupancy-Aware, Empirically-Driven Pdc Control In Open-Plan, Shared Workspaces, Ravi Anuradha, Dulaj Sanjaya Weerakoon, Archan Misra

Research Collection School Of Computing and Information Systems

Passive Displacement Cooling (PDC) is a relatively recent technology gaining attention as a means of significantly reducing building energy consumption overheads, especially in tropical climates. PDC eliminates the use of mechanical fans, instead using chilled-water heat exchangers to perform convective cooling. In this paper, we identify and characterize the impact of several key parameters affecting occupant comfort in a 1000m2 open-floor area (consisting of multiple zones) of a ZEB (Zero Energy Building) deployed with PDC units and tackle the problem of setting the temperature setpoint of the PDC units to assure occupant thermal comfort and yet conserve energy. We tackle …

On The Lossiness Of 2k-Th Power And The Instantiability Of Rabin-Oaep, Haiyang Xue, Bao Li, Xianhui Lu, Kunpeng Wang, Yamin Liu

Research Collection School Of Computing and Information Systems

Seurin PKC 2014 proposed the 2-ï /4-hiding assumption which asserts the indistinguishability of Blum Numbers from pseudo Blum Numbers. In this paper, we investigate the lossiness of 2 k -th power based on the 2 k -ï /4-hiding assumption, which is an extension of the 2-ï /4-hiding assumption. And we prove that 2 k -th power function is a lossy trapdoor permutation over Quadratic Residuosity group. This new lossy trapdoor function has 2 k -bits lossiness for k -bits exponent, while the RSA lossy trapdoor function given by Kiltz et al. Crypto 2010 has k -bits lossiness for k -bits …

D2sr: Decentralized Detection, De-Synchronization, And Recovery Of Lidar Interference, Darshana Rathnayake, Hemanth Sabbella, Meera Radhakrishnan, Archan Misra

Research Collection School Of Computing and Information Systems

We address the challenge of multi-LiDAR interference, an issue of growing importance as LiDAR sensors are embedded in a growing set of pervasive devices. We introduce a novel approach named D2SR, enabling decentralized interference detection, mitigation, and recovery without explicit coordination among nearby LiDAR devices. D2SR comprises three stages: (a) Detection, which identifies interfered frames, (b) Mitigation, which performs time-shifting of a LiDAR’s active period to reduce interference, and (c) Recovery, which corrects or reconstructs the depth values in interfered regions of a depth frame. Key contributions include a lightweight interference detection algorithm achieving an F1-score of 92%, a simple …

What Do We Know About Hugging Face? A Systematic Literature Review And Quantitative Validation Of Qualitative Claims, Jason Jones, Wenxin Jiang, Nicholas Synovic, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Background: Collaborative Software Package Registries (SPRs) are an integral part of the software supply chain. Much engineering work synthesizes SPR package into applications. Prior research has examined SPRs for traditional software, such as NPM (JavaScript) and PyPI (Python). Pre-Trained Model (PTM) Registries are an emerging class of SPR of increasing importance, because they support the deep learning supply chain.
Aims: Recent empirical research has examined PTM registries in ways such as vulnerabilities, reuse processes, and evolution. However, no existing research synthesizes them to provide a systematic understanding of the current knowledge. Some of the existing research includes qualitative …

The P -Adic Schrödinger Equation And The Two-Slit Experiment In Quantum Mechanics, Wilson A. Zuniga-Galindo

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

p-Adic quantum mechanics is constructed from the Dirac-von Neumann axioms identifying quantum states with square-integrable functions on the N-dimensional p-adic space, Q_{p}^{N}. This choice is equivalent to the hypothesis of the discreteness of the space. The time is assumed to be a real variable. p-Adic quantum mechanics is the response to the question: what happens with the standard quantum mechanics if the space has a discrete nature? The time evolution of a quantum state is controlled by a nonlocal Schrödinger equation obtained from a p-adic heat equation by a temporal Wick rotation. This p-adic heat equation describes a particle performing …

Retrofitting A Legacy Cutlery Washing Machine Using Computer Vision, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Industry 4.0, the digitalization of manufacturing promises to lead to lowered cost, efficient processes and even discovery of new business models. However, many of the enterprises have huge investments in legacy machines which are not 'smart'. In this study, we thus designed a cost-efficient solution to retrofit a legacy conveyor belt-based cutlery washing machine with a commodity web camera. We then applied computer vision (using both traditional image processing and deep learning techniques) to infer the speed and utilization of the machine. We detailed the algorithms that we designed for computing both speed andutilization. With the existing operational constraints of …

Irrigation Companies And The Great Salt Lake: Managing Water In Utah Amidst Climate Change, Chloe Francis, Kendall Becker, Matt Yost, Scott Hotaling

All Current Publications

The Great Salt Lake, a key ecosystem and major component of Utah’s identity and economy, is threatened by rapidly declining water levels. This problem has caused widespread and ongoing concern from the public, and the Utah Legislature is faced with making water allocation and management decisions to adapt to the state’s growing population and changing environment. One important group in this discussion is irrigation companies. Here, we examine how irrigation companies receive and maintain water rights in Utah, their significant role in water management, and recent legislative efforts to incentivize efficient water use so more water reaches the Great Salt …

Regulating Shipping Of Carbon Dioxide For Sequestration, Carolina Arlota, Michael B. Gerrard

Faculty Scholarship

A number of facilities intended for permanent sequestration of carbon dioxide are being developed in the United States. Several will be located on or near the coast of the Gulf of Mexico, making them easily accessible to ships. Meanwhile, in Europe there is substantial interest in capturing carbon dioxide from industrial operations, but currently inadequate sequestration facilities, and growing interest in shipping carbon dioxide for sequestration in the United States. This Article reviews the main U.S. federal laws applicable to transportation and geologic storage of carbon dioxide, including laws enacted to implement relevant international treaties. The Article also contextualizes its …

Resilient Tcp Variant Enabling Smooth Network Updates For Software-Defined Data Center Networks, Abdul Basit Dogar, Sami Ullah, Yiran Zhang, Hisham Alasmary, Muhammad Waqas, Sheng Chen

Research outputs 2022 to 2026

Network updates have become increasingly prevalent since the broad adoption of software-defined networks (SDNs) in data centers. Modern TCP designs, including cutting-edge TCP variants DCTCP, CUBIC, and BBR, however, are not resilient to network updates that provoke flow rerouting. In this paper, we first demonstrate that popular TCP implementations perform inadequately in the presence of frequent and inconsistent network updates, because inconsistent and frequent network updates result in out-of-order packets and packet drops induced via transitory congestion and lead to serious performance deterioration. We look into the causes and propose a network update-friendly TCP (NUFTCP), which is an extension of …

Computational And Experimental Data For Undoped And Er-Doped Lithium Tantalate Nanofluorescent Probes, Mkhitar A. Hobosyan, Andrea Pelayo Carvajal, Bhupendra B. Srivastava, Tamanna Zakia, Mohammed Jasim Uddin, Karen S. Martirosyan, Eric Rodriguez, Kofi Nketia Ackaah-Gyasi, Nicholas Dimakis

Physics and Astronomy Faculty Publications and Presentations

The density functional theory (DFT) and experimental data presented in this paper refer to the research article “Computational and experimental study on undoped and Er-doped lithium tantalate nano fluorescent probes”. The DFT data contain electronic and optical properties for both LiTaO3 and LiTaO3:Er+3, with Er+3 occupying either Li or Ta sites at 4.167 mol. %. All these properties were calculated at the generalized gradient approximation (GGA) limit. Additionally, electronic information was calculated using the hybrid functional by Heyd, Scuseria, and Ernzerho (HSE06), which accurately predicts the location in energy for all Er-4f orbitals. We also include simulated X-ray near edge …

Satellite Observations Indicate That Chia Uses Less Water Than Other Crops In Warm Climates, Brian Kirsch, Joshua B. Fisher, Thomas Piechota, Mohammad Hassani, Diego C. Suardiaz, Radhika Puri, Joseph Cahill, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Many parts of the world face severe and prolonged drought conditions, stressing the sustainability of water resources and agriculture. Transitioning to water-efficient crops is one strategy that can help adapt to water scarcity. An emerging drought-tolerant crop of interest is chia (Salvia hispanica). Yet, no study has compared its large-scale water use dynamics to those of widely established crops across the globe. Here, we use satellite data over multiple years to assess the water use efficiency of chia, alfalfa, corn, and soybean globally. Results show that chia consumed 13-38% less water than alfalfa, corn, and soy and assimilated …

Information-Theoretic Modeling Of Categorical Spatiotemporal Gis Data, David Percy, Martin Zwick

Geology Faculty Publications and Presentations

An information-theoretic data mining method is employed to analyze categorical spatiotemporal Geographic Information System land use data. Reconstructability Analysis (RA) is a maximum-entropy-based data modeling methodology that works exclusively with discrete data such as those in the National Land Cover Database (NLCD). The NLCD is organized into a spatial (raster) grid and data are available in a consistent format for every five years from 2001 to 2021. An NLCD tool reports how much change occurred for each category of land use; for the study area examined, the most dynamic class is Evergreen Forest (EFO), so the presence or absence of …

Multi-Agent System-Based Framework For An Intelligent Management Of Competency Building, Fatma Outay, Nafaa Jabeur, Fahmi Bellalouna, Tasnim Al Hamzi

All Works

To measure the effectiveness of learning activities, intensive research works have focused on the process of competency building through the identification of learning stages as well as the setup of related key performance indictors to measure the attainment of specific learning objectives. To organize the learning activities as per the background and skills of each learner, individual learning styles have been identified and measured by several researchers. Despite their importance in personalizing the learning activities, these styles are difficult to implement for large groups of learners. They have also been rarely correlated with each specific learning stage. New approaches are, …

Optimal Radar Ranging Pulse To Resolve Two Reflectors, Andrew N. Jordan, John C. Howell, Achim Kempf, Shunxing Zhang, Derek White

Mathematics, Physics, and Computer Science Faculty Articles and Research

Previous work established fundamental bounds on subwavelength resolution for the radar range resolution problem, called superradar [Phys. Rev. Appl. 20, 064046 (2023)]. In this work, we identify the optimal waveforms for distinguishing the range resolution between two reflectors of identical strength, leveraging results in quantum metrology. We discuss both the unnormalized optimal waveform as well as the best square-integrable pulse and their variants. Using orthogonal function theory, we give an explicit algorithm to optimize the wave pulse in finite time to have the best performance. We also explore range resolution estimation with unnormalized waveforms with multiparameter methods to …

Policies And Programs For Water-Wise Residential Landscaping In Utah, Charlotte Clark, Kendall Becker, Scott Hotaling

All Current Publications

Water-wise landscaping is the practice of using plants in a landscape that are adapted to local conditions and only need small amounts of water. Converting yards to water-wise landscaping conserves water and is a climate adaptation action residents can take to benefit Utah as temperatures rise and drought becomes more common. Many policies and programs in Utah help residents use water conscientiously and make changes. This fact sheet provides information regarding current and future water-wise landscaping policies and programs in Utah.

Climate Smart Agriculture, J. David Aiken

Cornhusker Economics

There are several programs encouraging producers to reduce their carbon intensity, including United States Department of Agriculture climate-smart agriculture programs, the 2024 Nebraska Climate Action Plan, and the 2024 Nitrogen Reduction Incentive Act. The hope is that producers with lower carbon intensity (CI) scores will receive a premium for their products. Producers would be well advised to learn more about these programs, as reducing carbon intensity in agriculture seems to be an emerging agricultural policy trend that will be with us for some time to come.

2024 Draft Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Phase Iii Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Enhancing Resilience And Reducing Waste In Food Supply Chains: A Systematic Review And Future Directions Leveraging Emerging Technologies, Asmaa Seyam, May Ei Barachi, Cheng Zhang, Bo Du, Jun Shen, Sujith Samuel Mathew

All Works

The sustainability of food supply chains is gaining increasing attention, particularly after the COVID-19 pandemic. A food supply system that simultaneously prioritises resilience and minimises wastage is crucial. It is found that many studies have explored reducing food waste and increasing supply chain resilience as separate objectives, but research is scarce investigating both objectives in conjunction. This paper presents a comprehensive systematic review focusing on existing solutions to reducing food waste and enhancing resilience. It discusses future directions, particularly leveraging emerging technologies such as the Internet of Things, blockchain, artificial intelligence, and machine learning. The studies are categorised into three …

Re: Comment Letter For Draft Bpsou 2023 Groundwater Data Summary Report (Dated May 31, 2024), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Recent Climate Change In Utah, 1870-2023, Scott Hotaling, Kendall Becker

All Current Publications

Climate change is impacting Utah. Forty-five years of temperature data show that Utah is steadily warming, which, in turn, is driving declines in winter snowpack, shifting the timing and amount of available water, increasing fire risk, and causing ecological change. This fact sheet addresses changes in Utah's temperature, precipitation and snowpack, streamflow, wildfire, and ecology.

A Generalized Machine Learning Model For Long-Term Coral Reef Monitoring In The Red Sea, Justin J. Gapper, Surendra Maharjan, Wenzhao Li, Erik Linstead, Surya Prakash Tiwari, Mohamed A. Qurban, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El Niño, poses a significant threat to these ecosystems. This study focuses on the Red Sea, proposing a generalized machine learning approach to detect and monitor changes in coral reef cover over an 18-year period (2000–2018). Using Landsat 7 and 8 data, a Support Vector Machine (SVM) classifier was trained on depth-invariant indices (DII) derived from the Gulf of Aqaba and validated against ground …

Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp) Bres No. 52 – Moscow Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp) Bres No. 78 – Original Mine Yard, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp) Bres No. 34e – Eveline Dump East, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Limited-Preemption Scheduling Model Inspired By Security Considerations, Benjamin Standaert, Fatima Raadia, Marion Sudvarg, Sanjoy Baruah, Thidapat Chantem, Nathan Fisher, Christopher Gill

Computer Science and Engineering Publications and Presentations

Safety-critical embedded systems such as autonomous vehicles typically have only very limited computational capabilities on board that must be carefully managed to provide required enhanced functionalities. As these systems become more complex and inter-connected, some parts may need to be secured to prevent unauthorized access, or isolated to ensure correctness.

We propose the multi-phase secure (MPS) task model as a natural extension of the widely used sporadic task model for modeling both the timing and the security (and isolation) requirements for such systems. Under MPS, task phases reflect execution using different security mechanisms which each have associated execution time costs …