Physical Sciences and Mathematics Commons^™

Intelligent Transition Of Automotive Industry Driven By Autonomous Driving Simulation Testing Technology, Jianping Wu, Guanzhou Li, Shuai Zhao, Ling Huang

Journal of System Simulation

Abstract: As a pivotal approach supporting the safety verification and commercial implementation of intelligent driving systems, autonomous driving simulation testing has achieved remarkable progress in technical methodologies and application scenarios. Conventional real-world road testing faces critical limitations including prohibitive costs, inadequate coverage of corner case scenarios, and efficiency bottlenecks, rendering it insufficient for safety validation of high-level autonomous driving systems (L4 and above). To address these challenges, simulation testing frameworks have evolved into a multi-layered verification system encompassing mathematical modeling, virtual scenarios, hardware-in-the-loop (HIL), mixed reality, and cloud-based simulation clusters. Specifically, mathematical modeling accelerates algorithm development; virtual scenario simulation enhances …

Digital Twinned Industrial Robot: Conceptual Framework, Key Technologies, And Case Study, Yongkui Liu, Kang Yang, Benben Tuo, Yaduo Pan, Xinyu Wang, Yihan Wang, Yongqian Gong, Lin Zhang, Lihui Wang, Tingyu Lin, Bin Zi, Yuan Li, Wei You, Xun Xu

Journal of System Simulation

Abstract: To effectively enhance the value and full life cycle management level of industrial robots, this paper integrated deeply digital twin with industrial robots and discussed a new concept, namely digital twinned industrial robot (DTIR). It defined the concept, composition, and typical characteristics of DTIRs and proposed their system architecture. From the perspective of the full life cycle of "design, manufacturing, operation and maintenance, and decommissioning", the key technologies of DTIRs were systematically sorted out. Furthermore, the validity of the proposed conceptual framework was verified through a case study. Finally, the paper summarized the findings and discussed the future development …

Large-Scale Social Simulator: Frontiers And Perspectives, Jinghua Piao, Chen Gao, Fang Zhang, Jun Su, Yong Li

Journal of System Simulation

Abstract: Social experiments, as a typical research method in social sciences, aim to study specific social phenomena or the impacts of policies by observing the behaviors of individuals, organizations, or social groups in real or simulated environments. However, traditional social experiment methods often face challenges such as random bias, high costs, and ethical risks, making them inadequate to address increasingly complex research demands. Against this backdrop, computational social experiments have emerged, enabling researchers to conduct social experiments within computational simulation environments that are free from random bias, cost-efficient, and ethically manageable. Meanwhile, China is currently undergoing a critical period of …

Life Cycle Assessment Of New Jersey Offshore Wind, Meghann Smith, Nawal Shoaib, Pankaj Lal

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

As offshore wind gains momentum within US (United States) renewable energy goals, New Jersey's ambitious targets for offshore wind development represent a significant opportunity to reduce emissions and transition towards cleaner energy sources. This study presents a life cycle assessment (LCA) of a planned offshore wind farm off of New Jersey's coast, emphasizing the implications of a domestic supply chain. Key findings suggest that the offshore wind farm is projected to produce 0.013 kg CO2 kWh−1 of electricity generated, reflecting a 98 % decrease in carbon emissions compared to natural-gas-derived electricity. Further, when compared to carbon emissions from other renewable …

Limited Soil Water Recharge In Summer Affects Seasonal Isotopic Signatures Of Tree Xylem Water, Marius G. Floriancic, Gregory R. Goldsmith, Harsh Beria, Scott T. Allen, James W. Kirchner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Recent studies have reported that xylem waters in forest trees during the summer growing season are often isotopically similar to winter, rather than summer, precipitation. Several hypotheses have been proposed to explain this observation, which can be viewed as a form of ecohydrological separation, but empirical tests spanning space and time remain limited. We hypothesise that variations in the seasonal origin of precipitation found in tree xylem waters can be explained by seasonal differences in soil water recharge. We test this hypothesis by evaluating to what extent climatic aridity can explain seasonal signals in extensive surveys of the isotope ratios …

What Drives Weight Status Among Female University Students? A Machine Learning Analysis Of Sociodemographic, Dietary, And Lifestyle Determinants, Radwan Qasrawi, Abir Ajab, Leila Cheikh Ismail, Ayesha Al Dhaheri, Sharifa Alblooshi, Razan Abu Ghoush, Stephanny Vicuna Polo, Malak Amro, Suliman Thwib, Ghada Issa, Haleama Al Sabbah

All Works

Background: Obesity and underweight are increasingly common among young adult women, often resulting from complex interactions between diet, lifestyle, and socioeconomic factors. This study addresses that gap by applying machine learning to a wide range of behavioral, dietary, and demographic data. The main research question asks: What are the key factors influencing weight status among female university students, and how accurately can machine learning models identify them? We hypothesize that different factors are significantly associated with underweight, overweight, and obesity, and that machine learning can reliably detect these patterns. The aim is to identify the strongest predictors and support more …

Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai

Pepperdine Dispute Resolution Law Journal

Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …

Detecting Android Malware Based On Static Analysis Using Classification And Modified Clustering Techniques, Abdullah Allawi Al-Sraratee, Ahmed Habeeb Al-Azawei

Journal of Intelligent Informatics, Networking, and Cybersecurity

Because Android malware harms internet security, prior research proposes several different approaches to detect it accurately. However, such proposed models depend on numerous number of features to attain high accuracy. This could lead to high computation cost and potential overfitting. Furthermore, manual data labeling is labor-intensive, requiring significant human effort and skills. This research aims to: 1) extend previous literature on Android malware detection, 2) improve the accuracy of Android malware detection based on a low number of features, and 3) modify a clustering technique to group data into two different clusters to address the issue of unlabeled data. To …

Electrochemically-Assisted Low Power Density Laser Writing On Stainless Steel Via Enrichment Of Chromium Oxides, Zechariah Pfaffenberger, Lianlian Liu, Tae Kyong John Kim, Vignesh Venkataramani, Lydia Kisley

Faculty Scholarship

Laser color marking produces nearly permanent, environmentally friendly, vibrant colors on surfaces. However, previous work has used high-power-density pulsed lasers to induce the physicochemical reactions for marking. Here, laser color marking on stainless steel 304 (SS304) is performed with a less expensive continuous wave (CW) laser and a power density five orders of magnitude below that previously reported by combining an electrochemical cell with a fluorescence microscope. Using a combination of optical microscopy, x-ray photoelectron spectroscopy, and bulk electrochemistry, it is demonstrated that the laser-induced luminescence and colors are due to enrichment (32 ± 9% increase) of Cr2O3 in the …

2025 July 17 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Post-Wildfire Erosion And Sedimentation: An Escalating Threat For Utah Fisheries, Colton James, Kendall Becker, Scott Hotaling, Aish Chandrasekaran, Alex Fiedler, Timothy E. Walsworth, Patrick Belmont

All Current Publications

Wildfires are a natural part of the western U.S. landscape and provide numerous benefits, including enhanced nutrient cycling and habitat rejuvenation. Utah’s fish populations evolved with wildfire as a common disturbance. However, the increasing size and severity of wildfires, combined with Utah’s heavily engineered and fragmented stream networks, pose a contemporary risk to fish populations. This fact sheet reviews wildfire impacts on erosion and Utah's watersheds and fisheries. It outlines measures we can take to prevent post-wildfire fish die-offs.

Quantum Memory, Isabel Martinez-Robles

Physics and Astronomy Summer Fellows

Isolated quantum systems are almost always observed to achieve thermal equilibrium in experiments. Understanding cases where they do not thermalize, and therefore retain memory about the initial state, could lead to the development of a quantum memory. We excite atoms in a magneto-optical trap, where they are cold enough to treat as stationary. In our experiment, our atoms exchange energy via dipole-dipole interactions and fail to thermalize. We present a theoretical and computational analysis that suggests that our system starts in an exceptional initial state.

Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink

Theses

Background: Automated essay scoring (AES) is a challenging deep learning problem. The two most widely used methods for predicting essay quality scores, supervised learning-based and LLM-based, have their own limitations. Although supervised learning-based methods are more accurate, they only predict a score and do not offer descriptive feedback to students. On the other hand, LLM-based methods can offer rubric-guided feedback but are known to be less accurate.

Methods: This work focuses on improving the accuracy of state-of-the-art LLM-based AES methods. We began by thoroughly investigating why these methods were performing poorly for certain datasets and certain examples. This led us …

Numerical Simulation Of Frost Formation And Heat Transfer On Fin-And-Tube Heat Exchangers In Turbulent Cross-Flow, Mahsan Farzaneh, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050≤𝑅⁢𝑒𝐷,avg≤4800, with the characteristic …

Identifying The Desired Word Suggestion In Simultaneous Audio, Dylan Gaines, Keith Vertanen

Michigan Tech Publications

We explore a method for presenting word suggestions for non-visual text input using simultaneous voices. We conduct two perceptual studies and investigate the impact of different presentations of voices on a user's ability to detect which voice, if any, spoke their desired word. Our sets of words simulated the word suggestions of a predictive keyboard during real-world text input. We find that when voices are simultaneous, user accuracy decreases significantly with each added word suggestion. However, adding a slight 0.15 s delay between the start of each subsequent word allows two simultaneous words to be presented with no significant decrease …

Perceptions Of Blind Adults On Non-Visual Mobile Text Entry, Dylan Gaines, Keith Vertanen

Michigan Tech Publications

Text input on mobile devices without physical keys can be challenging for people who are blind or low-vision. We interview 12 blind adults about their experiences with current mobile text input to provide insights into what sorts of interface improvements may be the most beneficial. We identify three primary themes that were experiences or opinions shared by participants: the poor accuracy of dictation, difficulty entering text in noisy environments, and difficulty correcting errors in entered text. We also discuss an experimental non-visual text input method with each participant to solicit opinions on the method and probe their willingness to learn …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

Stokes-Dependent Droplet Collection Efficiency On A Naca 0012 Airfoil From Droplet-Informed Simulations With Statistical Overloading, Arash Shad, Hashnayne Ahmed, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60≤⁢𝑈≤⁢240 m s−1 and the chord length of the airfoil in the range 0.5≤⁢𝑐≤⁢2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision …

Correlated Sampling Of Parallel Partial And Linked Emulators For Geophysical Applications, Joseph Lyon

Dissertations (1934 -)

Computer models, or simulators, are mathematical representations of real world phenomena that, to run at new input settings, are often computationally intensive and prohibitively slow. Surrogate models, or emulators, provide a method of rapidly predicting simulator outputs with uncertainty at untested configurations by treating the computer model output as a single realization of a stochastic process, specifically a Gaussian Process (GP).In this dissertation, we consider three projects: Correlated Linked GP Emulation, Spatially Correlated Parallel Partial Emulation, and Optimizing the Zero-censored Gaussian Process with Spatially Correlated Sampling. First, the Correlated Linked Emulator, focuses on developing a model for the covariance of …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling Bres No. 30 – Atlantic 1 Site Evaluation Summary Report (Dated February 24, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Spatiotemporal Responses To A Rural Highway By Four Mammal Species, Caitlin K. Brett, Anna Rose Mehner, John H. Young Jr., Sarah E. Lehnen, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Roads can negatively impact the wildlife communities they transect. Road mortalities from wildlife-vehicle collisions are one direct effect, but roads may also indirectly affect wildlife behavior, movement, or local distribution. Quantifying the spatial extent of these road-effects is important for understanding how roads indirectly affect species of concern, identifying potential sources of disturbance, and for estimating the effectiveness of road mitigation structures. Farm-to-Market Road (FM)106, which transects part of the Laguna Atascosa National Wildlife Refuge in Cameron County, Texas, has been identified as a potential source of wildlife road mortalities, particularly for one of the two remaining breeding populations of …

A Rapid Method For Identifying Plant Oxidative Stress And Implications For Riparian Vegetation Management, Mizanur Rahman, Takashi Asaeda, Kiyotaka Fukahori, Md Harun Rashid, Hideo Kawashima, Junichi Akimoto, Refah Tabassoom Anta

School of Earth, Environmental, & Marine Sciences Faculty Publications

Native and invasive plants of the riverain region undergo a range of environmental stresses that result in excess reactive oxygen species (ROS). Hydrogen peroxide (H2O2) is a relatively stable and quickly quantifiable way among different ROS. The herbaceous species including Artemisia princeps, Sicyos angulatus, and Solidago altissima were selected. The H2O2 and photosynthetic pigment of leaves were measured, soil samples were analyzed to quantify macronutrients such as total nitrogen (TN), total phosphorus (TP), and soil moisture, and photosynthetic photon flux density (PPFD) was also recorded at different observed sites of Arakawa Tarouemon, Japan. The H2O2 concentration of S. altissima significantly …

Using Confidence Scores To Improve Eyes-Free Detection Of Speech Recognition Errors, Sadia Nowrin, Keith Vertanen

Michigan Tech Publications

Conversational systems rely heavily on speech recognition to interpret and respond to user commands and queries. Despite progress on speech recognition accuracy, errors may still sometimes occur and can significantly affect the end-user utility of such systems. While visual feedback can help detect errors, it may not always be practical, especially for people who are blind or low-vision. In this study, we investigate ways to improve error detection by manipulating the audio output of the transcribed text based on the recognizer's confidence level in its result. Our findings show that selectively slowing down the audio when the recognizer exhibited uncertainty …

A Rigorous Framework For An Improved Messinger/Myers Model Of Ice Accretion Under Conditions Of Variable Property And Unsteady Aircraft Icing, Hashnayne Ahmed, Arash Shad, ‪Nadim Zgheib, S. A. Sherif, S. Balachandar

Mechanical Engineering Faculty Publications

We analyse the Messinger/Myers model by critically evaluating simplifying assumptions through a rigorous formulation of the rime ice accretion process. We explore the effects of both constant and variable ice density and thermal conductivity, along with the effects of sublimation from the ice surface. The effects of key factors such as droplet impact rate, ambient temperature relative to the freezing temperature and the temperature difference between the ambient air and the airfoil surface are examined. Under these varying conditions, the present rigorous formulation is used to assess the significance of unsteady effects, variable ice properties and sublimation. We observe that …

The Response Of Mitochondrial Position To Glucose Stimulation In The Min6 Model System, Luis Perez

Arts & Sciences Graduate Student Theses and Dissertations

The compartmentalization of eukaryotic cells into membrane-bound organelles with specific subcellular positioning enables precise spatial and temporal control of cellular functions. While functionally significant mitochondrial localization has been demonstrated in cells such as neurons, it remains unclear how general these cell principles are. Here, we examine the spatial organization of mitochondria within MIN6 pancreatic beta cells under variable glucose conditions. We observe glucose-dependent redistributions of mitochondria, favoring peripheral localization at elevated glucose levels when insulin secretion is also elevated. Our results suggest that active mitochondrial transport along microtubules and calcium activity, but not ATP synthesis, are critical regulators of this …

Synthesis Of Cancrinite Zeolite From Toraja Natural Bentonite For Heavy Metal Removal From Wastewater, Yuli Astuti, Paulina Taba, Siti Fauziah, Syarifuddin Liong, Yusafir Hala, Nur Umriani Permatasari, Satria Putra Jaya Negara, Fadliah Fadliah

Karbala International Journal of Modern Science

This study explores the production of cancrinite (CAN) zeolite from bentonite found in Toraja (a place in South Sulawesi Province, Indonesia) and its effectiveness in removing Pb²⁺ and Fe³⁺ ions from wastewater. The synthesis was carried out using a hydrothermal method with varying NaOH concentrations, where a single phase of zeolite was formed at 5 M, as confirmed through XRD analysis. FTIR results showed the characteristics of CAN zeolite with typical absorption peaks at 676, 622, and 565 cm^-1, as well as the presence of carbonate groups (CO₃^2-) at 1300-1400 cm^-1. SEM …

Machine Learning Crime Prediction Models And The Gap Between Research And Implementation: A Systematic Review, Ricardo Huamantingo, Miguel Cano-Lengua, Ciro Rodriguez

Karbala International Journal of Modern Science

A crime is an illegal or violent act committed by one individual against another. The increasing crime rate has become a major concern as it negatively affects people's quality of life and generates significant social and economic costs. This study aims to identify the most widely used machine learning (ML) models for crime prediction, determine evaluation metrics for assessing model performance, and analyze key data characteristics to enhance real-world implementation. The study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A search string was formulated using the population, intervention, comparison, and outcomes (PICO) framework and applied …

Psilostachyin B As Potential Immune Checkpoint Inhibitor Targeting Ctla-4 And Pd-L1 In The Development Of Cancer Immunotherapy: A Computational Investigation, Moh Dliyauddin, Nabila Shafa Yumna Salsabila, Noviana Dwi Lestari, Sapti Puspitarini, Mansur Ibrahim, Sri Rahayu, Muhammad Sasmito Djati, Muhaimin Rifa’I

Karbala International Journal of Modern Science

Immunotherapy is a promising treatment approach by targeting immune checkpoints such as CTLA-4 and PD-L1 to overcome cancer progression. The utilization of Curcuma longa and Phyllanthus niruri as potential immune checkpoint inhibitors offers an alternative cancer therapy. Computational analyses including molecular docking and molecular dynamics with validation using Molecular Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA), Dynamic Cross-Correlation Matrix (DCCM), and Principal Component Analysis (PCA), were performed in this study. Results show that Psilostachyin B is the most promising inhibitor candidate against CTLA-4 and PD-L1, with binding affinity values of -6.9 and -6.8 kcal/mol, respectively. Molecular dynamics simulation results indicated that Psilostachyin B …

Survey Of Possible Magnetic Field Sources Around The Intragroup Medium Of Ngc 2563, Edward A. Wallace, Anna Williams

Macalester Journal of Physics and Astronomy

The origin and evolution of magnetic fields in space is an ongoing mystery in astronomy. Previous work has concluded the existence of magnetic fields in galaxy clusters, and to build an evolutionary model, the motivation behind this project is to determine how these magnetic fields form. In order to answer this question, we want to search for magnetic fields in galaxy group NGC 2563. To do this, our project determines the contribution to observed rotation measures of the galaxy group that come from the Milky Way and from the sources themselves.

Modelling Of The Overcontact Eclipsing Binary V826 Aur, Kalev T. Murray-Rouse, John M. Cannon, Anna Williams, Wes Tobin

Macalester Journal of Physics and Astronomy

We present a model of the eclipsing binary system V826 Aur using differential photometric data from the Robert L. Mutel Telescope (RLMT) at the Winer Observatory in Sonoita, Arizona. The calculated time of superconjunction was found to be 60648.7658534 and the period was 0.361701 d. These values were used to generate a best-fit model of the eclipsing binary with the PHOEBE program. The best-fit modelled parameters were found to be: mass ratio (𝑞) is equal to 2.769, the inclination (𝑖) is equal to 80.45◦, the fillout factor (𝑓) equals 0.0961, and the temperature ratio (𝑇2∕𝑇1) is 0.9740. Although not statistically …