Digital Commons Network^™

Analysis Of Factors Influencing The Implementation Of Sustainable Project Management (Spm) In The Construction Industry In Indonesia, Ariq Farhan, Titi Sari Nurul Rachmawati

CSID Journal of Infrastructure Development

The construction industry contributes significantly to economic growth but also carries substantial environmental and social costs. Construction activities generate carbon emissions, consume natural resources, and produce large volumes of waste. Despite growing theoretical development of Sustainable Project Management (SPM) frameworks, empirical evidence on the actual level of SPM implementation in Indonesia's construction sector remains limited. This study aims to identify the factors that influence SPM implementation and measure the level of implementation as perceived by construction professionals. A quantitative survey was administered to 99 professionals across infrastructure, building, and industrial construction sectors in Indonesia. Data were collected through a Likert-scale …

Analysis Of The Implemetation Of Enterprise Resource Planning (Erp) Sap S/4 Hana In Cost Control Of Light Rail Transit (Lrt) Construction Projects, Rizki Zulkarnaini, Bernadette Detty Kussumardianadewi

CSID Journal of Infrastructure Development

Construction projects are expensive, complex, and difficult to keep on budget. Cost overruns are common. The consequences, including delays, disputes, and financial losses, appear repeatedly across the sector. Enterprise Resource Planning (ERP) systems have been widely adopted to address this challenge, but evidence on how SAP S/4HANA performs in Light Rail Transit (LRT) construction is limited. This study analyzed the critical success factors of SAP S/4HANA implementation and evaluated its effect on cost control performance in an LRT project in Jakarta. Data were collected from two sources: a questionnaire distributed to 50 respondents involved in the project, and cost records …

Summer Proceedings 2026, Computational Modeling Serving Portland, The Altreu Program, Portland State University, Teuscher Lab, Portland State University

altREU Projects

The 2026 Summer Proceedings bring together research conducted by undergraduate students participating in three complementary programs at Portland State University: the National Science Foundation Research Experiences for Undergraduates (NSF REU) site, Computational Modeling Serving Portland; the alternative Research Experiences for Undergraduates (altREU) program, Designing, Programming, and Using Computers to Benefit Society; and the Teuscher Lab internship program.

The NSF REU is a fully virtual, 10-week program centered on computational modeling that serves Portland and the greater region. Students begin with two weeks of intensive training in computational modeling, followed by eightweeks of mentored research with faculty, research collaborators, and community …

Nascent Titanium-/Silicon-Containing Particle Formation In Corona-Discharge-Assisted Combustion, Chanakya Bagya Ramesh, Frank Daoru Han, Yang Wang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Adding plasmas to a flame has been shown to introduce high concentrations of charges, ions, and radicals to the said flame. This technique of adding plasma to a flame is called plasma-assisted combustion (PAC), and this addition has been shown to make a flame more stable and efficient. At the same time, PAC has also been shown to alter particle formation during combustion. Here, we investigate the effect of a high-frequency (∼21 kHz) alternating current (AC) corona discharge on particle formation and growth in a premixed flame, especially at the initial stages (with particle sizes below 10 nm). We first …

Multi-Parametric Nonlinear Programming For Lossy Lmp Sensitivity Analysis Using Outer Progressive Cuts, Yuhan Huang, Tao Ding, Chenggang Mu, Rui Bo, Pengwei Du

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate sensitivity analysis of locational marginal price (LMP) is crucial for risk hedging and market management. This paper proposes multiparametric nonlinear programming for sensitivity analysis of LMP with nonlinear network loss, also known as lossy LMP. Global analytical solutions for lossy LMP and the corresponding critical regions are derived. An outer progressive cut algorithm is developed to constrain the network loss error within a specific range for the whole parametric domain. Case studies show the improved accuracy over methods with lossless or fixed loss factors, and a two-order-of-magnitude online speedup over Monte Carlo methods while maintaining lower total computational time.

Soft Urea Nitridation Of Tantalum-Based Thin Films For Oxynitride Synthesis, Rishabh Srivastava

Graduate Theses and Dissertations

Rising global energy consumption and the transition toward low-carbon technologies place new demands on functional materials. Particularly, semiconductors that convert sunlight directly into chemical fuels with high efficiency and long operational lifetimes. The synthesis of visible light active tantalum oxynitride (TaON) thin films for photoelectrochemical (PEC) water splitting typically requires ammonolysis with pressurized NH3 gas, which presents persistent barriers in safety and phase selectivity. In this work, a soft urea ammonolysis route was employed in which solid urea was employed as an in-situ nitrogen source inside a vacuum-sealed reactor. The finite urea mass establishes a self-limiting nitrogen chemical potential that …

Autonomous Terrain-Mapping Robot For Search And Rescue, Soumil Joshi, Seann Calub

Electrical Engineering

This report documents the design, modular testing, and challenges faced while developing an autonomous terrain-mapping robot intended to navigate to a destination waypoint and deliver a small payload for search-and-rescue applications. The system combines a LiDAR sensor, an IMU sensor, and a Raspberry Pi 3B as the onboard processor, and an ESP32 microcontroller interfacing with motor drivers over a four-wheel chassis. A companion mobile application was developed to enable remote control and monitoring of the robot over a WiFi hotspot connection. A lithium-ion battery pack supplies power to all onboard components, with power budgets verified against component datasheets. Testing progresses …

Direct Ink Writing Of Functional Fiber/Granular Composites, Zhuoyuan Yang

Doctoral Dissertations and Master's Theses

Direct ink writing provides a versatile manufacturing route for fabricating functional fiber and granular composites with controlled architecture, tunable interfaces, and customized material distributions. Fiber reinforced composites offer high stiffness, strength, fatigue resistance, and functional anisotropy, while granular composites provide scalable access to particle based structures with high material efficiency and broad resource compatibility. However, the additive manufacturing of these composite systems remains challenging. For fiber based composites, precise control of fiber placement, matrix impregnation, interfacial bonding, and freestanding deposition is difficult to achieve during printing. For granular composites, stable particle flow, controllable packing, binder infiltration, and shape retention are …

Classification Of Aircraft Checklist Usability Problems Using Natural Language Processing, Borvorn Kasemtanakul

Doctoral Dissertations and Master's Theses

The use of checklists has been identified as a recurring issue in aviation accident investigations, highlighting the need for continued improvement in aircraft checklist design. However, existing aviation safety taxonomies do not systematically address checklist usability problems. Therefore, a systematic classification of these problems is needed to support the extension of existing aviation safety taxonomies and to facilitate safety data analysis for checklist design improvements. Furthermore, applications of Natural Language Processing (NLP) techniques in aircraft checklist research remain underexplored, despite their potential to identify meaningful patterns in textual safety data.

This exploratory research aimed to develop a data-driven classification of …

Experimental-Motion-Driven Cfd Investigation Of Slosh Dynamics In Propellant Tanks Of Spacecraft And Launch Vehicles, Priyanshu Savaliya

Doctoral Dissertations and Master's Theses

Liquid sloshing in partially filled propellant tanks can generate transient forces and moments that affect spacecraft and launch vehicle stability, guidance, and control. This research develops a one-way experimental-to-Computational Fluid Dynamics (CFD) integration framework to investigate free-surface slosh behavior under realistic excitation conditions.

The overarching goal of this thesis is to develop and evaluate a one-way experimental-motion-driven computational framework for predicting liquid slosh response in a partially filled cylindrical tank. Rather than relying on idealized sinusoidal inputs, this work uses experimentally measured actuator-feedback motion as the prescribed excitation for high-fidelity CFD. The central objective is to establish the experimental and …

A Machine-Learning-Based Systematic Framework For Modeling Compression And Recompression Indices For Florida Soils, Michael Morales

Doctoral Dissertations and Master's Theses

This thesis develops a machine-learning framework for estimating the compression index and the recompression index of Florida soils from routinely measured index properties, and reports two studies that build it. Consolidation settlement design requires both indices, and both are obtained from the incremental-loading oedometer test, which occupies a specimen for one to two weeks; the index tests that accompany it are complete within hours. Empirical correlations have filled that interval since the 1950s, but their coefficients are calibrated on specific soil populations and transfer poorly between regions. The first study analyzes 376 consolidation tests compiled for the Florida Department of …

Evaluating The Safety Efficiency Of U.S. Air Traffic Control Tower Operations Using Data Envelopment Analysis, Kenneth James Gilbert Ii

Doctoral Dissertations and Master's Theses

Air traffic control (ATC) tower safety efficiency remains inadequately measured despite critical workforce challenges, including staffing shortages, training pipeline constraints, and geographic retention difficulties. This mixed-methods study developed and validated a comprehensive framework for measuring tower safety efficiency by integrating subject-matter expert insights with multi-model data envelopment analysis (DEA) across 66 Federal Aviation Administration (FAA) tower facilities from 2016 to 2024. Six focus group interviews with experienced professionals (100% with > 20 years of experience), averaging 96.4 minutes, identified critical efficiency factors through systematic coding, achieving substantial inter-rater reliability (Cohen's kappa 𝜅 = .68). Qualitative findings showed that staffing shortages don't …

Noise-Optimized Routes For Air Taxi, Waleed Raza

Doctoral Dissertations and Master's Theses

Community noise is a primary barrier to the public acceptance and deployment of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) air taxi operations. This dissertation develops a coupled siting, routing, and noise optimization framework that links vertiport placement to its downstream acoustic consequences, demonstrated through a Daytona Beach case study. Candidate vertiports are screened and selected using accessibility, safety, demand, and feasibility criteria, and the selected sites form a directed network of 20 routes. Each trajectory is evaluated with a physics-based acoustic pipeline reporting Lmax, SEL, and EPNL at school, hospital, and residential receptors, showing that received exposure …

Influence Of Stormwater Flooding Events On The Mobile County School District Student Population, Kadence Kali Johnston

Honors Theses

Mobile County, Alabama, receives among the highest annual rainfall totals in the United States resulting in frequent stormwater flooding that intersects with existing socioeconomic vulnerabilities. Within the Mobile County Public School System (MCPSS), 77% of students are economically disadvantaged and over 10% experience homelessness, creating heightened risk for educational disruption during flood events. This study investigates how stormwater flooding influences school attendance, closures, and academic performance across MCPSS, providing insight into how climate-driven hazards exacerbate educational inequities. The research integrates flood frequency, school performance metrics, and GIS flood-zone mapping and teacher perceptions to understand how flooding affects student learning opportunities. …

Decoration Of Lactic Acid Bacterium By Exploiting In Vitro Sortase A Transpeptidase, Faisal Hamd Alqhtani

Graduate Theses and Dissertations

Attaching a drug module to the surface of lactic acid bacteria was the main aim of this dissertation, and it was achieved. By using the Sortase A mechanism, the drug module (green fluorescent protein fused to the LPETG motif) was anchored to the LAB surface. To reach the final results, this dissertation will describe the process that I undertake to achieve the end goal. Modifying media, producing pure enzymes with less impurity, and reducing the protease activity in E. coli BL21 were all described in this five-chapter dissertation. Keywords: drug delivery, lactic acid bacteria, green fluorescent protein, sortase A, fusion …

Managing Risks Under Nuclear Power Plant Projects: A Latent Similarity-Guided Contract Customization, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Global energy is transforming, with nuclear power emerging as a pivotal player in achieving sustainable and low-carbon energy goals. The nature of nuclear technology introduces unique challenges, such as stringent safety and environmental requirements. Existing studies focus on general risk identification, such as supply chain delays, cost overruns, and public perception issues. However, these studies fail to address integrating these risks into tailored contractual provisions, which are critical for navigating the unique challenges of nuclear projects. The goal of this paper is to examine how standard construction contracts can be tailored to better accommodate the risks inherent in nuclear power …

Interpretable Machine Learning Of Plasma Proteomics Reveals Stage-Specific Signatures Across The Alzheimer's Disease Continuum, Hemshankar Laugi

2026 Spring Honors Capstones Projects

Alzheimer’s pathology begins years before clinical symptoms, starting early with amyloid-β accumulation, followed by tau deposition and neurodegeneration. Although existing tools, such as cerebrospinal fluid (CSF) screening and PET/MRI imaging, can accurately track disease progression, they are invasive, expensive, and not scalable for population-level screening. So, there is a growing interest in using blood-based plasma biomarkers as a scalable alternative. While recent studies demonstrate strong predictive performance with plasma biomarkers, most rely on a small set of canonical blood-based protein biomarkers such as amyloid-β, p-tau, and neurofilament light. These biomarkers primarily reflect downstream brain pathology and may fail to capture …

Understanding The Structural Drivers Of Useful Exergy Intensity, João Santos, Tiago Domingos, Tânia Sousa, Matthew Kuperus Heun, André Serrenho

University Faculty Publications and Creative Works

Energy-Economy Decomposition Analysis Across 112 Countries 1971-2020

Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers

Electrical and Computer Engineering Faculty Research & Creative Works

Background/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated …

Jme 4110: Drill-Powered Beach Umbrella Anchor, Matthew Barton, Tanin Ramnath, Marquan Bailey, Zachary Van-Horn, Kaelin Mendoza

Washington University / UMSL Mechanical Engineering Design Project JME 4110

A common and potentially hazardous situation faced by beachgoers is when standard umbrella anchors fail to hold during wind gusts, causing the umbrella to potentially go airborne and injure nearby people. Existing anchors require manual operation, leading to inconsistent grip and no resistance to different wind directions. Our project is a motorized three anchor system that drives augers into the sand to ensure a consistent grip and security against the wind.

Jme 4110: Drill Powered Pressure Washer, Kathryn Keele, Ashley Givance, Reagan Grass, Andrew Ellis, Jacob Thebeau

Washington University / UMSL Mechanical Engineering Design Project JME 4110

This project focuses on developing a drill-powered pressure washer attachment that connects to a standard cordless drill and garden hose. The device uses the drill as its only power source to pressurize water for cleaning applications. This portable design provides a convenient, low-cost alternative to traditional electric or gas-powered pressure washers.

Life Cycle Of Lithium-Ion Battery Recycling Systems Enable Carbon Capture, Utilization, And Storage: A Review, Nabeel Al-Qirim, Mohammad Kamrul Hasan, Hussam Al Hamadi, Akm Ahasan Habib, Shayla Islam

All Works

The lithium-ion battery (LIB) is the primary component of electric vehicles (EVs), and its environmental consequences are significant for the eventual widespread adoption of EVs. Recycling used LIBs protects the environment and allows for the reuse of valuable materials. To achieve the goal of a circular economy, LIB recycling processes that conserve environmentally friendly resources and maintain sustainability need to be developed. The critical technology for achieving global climate goals is carbon capture, utilization, and storage (CCUS), which makes it possible to significantly lower carbon dioxide (CO2) emissions across power and industrial systems. The LIB recycling and CCUS are becoming …

Explainable And Hybrid Machine Learning For Predicting Fatal Crash Risk, Hussein Khanjar, Abdolmajid Erfani

Michigan Tech Publications

Road traffic fatalities remain one of the most persistent public safety challenges, demanding predictive models that are not only accurate but also reliable and interpretable. While numerous machine-learning models have been developed for crash severity prediction, most remain limited in three critical dimensions: they simplify the unit of analysis by focusing only on the driver or the most severe occupant per crash, they emphasize predictive performance while neglecting model confidence and probability calibration, and they often function as black boxes lacking interpretability for real-world decision support. To address these gaps, this study proposes a calibrated hybrid machine-learning framework for nationwide, …

Adaptive Solar Energy Collection Fenestration Systems; Measured Performance On Test Cell Under Real Weather Conditions., Noel O’Neill

Doctoral

Buildings account for a significant share of global energy use, and improving façade performance is critical to achieving nearly zero-energy building targets. This research addresses the challenge of integrating multiple adaptive functions into a single façade system to reduce heat loss, harness solar energy, and provide dynamic environmental control. The aim was to design, construct, and evaluate an adaptive Multi-Functional Façade (MFF) that integrates vacuum glazing, switchable opacity glazing, and a ventilated cavity with active airflow control to provide façade insulation, heated fresh air, recirculated air, or exhaust ventilation.

A Solar Thermal Test Cell (STTC) designed to Passive House standard, …

Late-Night And Early-Morning Train Scheduling With Non-Traffic Hour Maintenance Window In Urban Rail Transit Systems, Yaochen Ma, Hai Yang, Hai Wang

Research Collection School Of Computing and Information Systems

Regular maintenance during non-traffic hours (NTH) is vital for the resilience of urban rail transit (URT) systems, yet an insufficient NTH maintenance window poses a challenge for URT systems in various cities. For instance, the Hong Kong MTR Corporation has noted that the required NTH maintenance time often exceeds the available window, prompting service adjustments such as earlier late-night closures and/or later early-morning starts. To address this challenge, this study develops an optimal scheduling framework that links late-night and early-morning URT services through the NTH maintenance window requirement to maximize public welfare. A Decoupled Optimization Model (DOM) first derives closed-form …

Robot Remote Control Utility, Jeremy Cantu, Paul Uhlig

Systems Manuals - 2026

The purpose of this document is to describe the Robot Control Management Utility developed in the course of this graduate project. Information included in this document will include the background of the developed product, as well as the functional requirements, data structures, software modules, interface design, installation guide, and sample and troubleshooting guides.

Confidenceai: A Wearable And Predictive Ai Ecosystem, Denzil Paul, Xuejun Kong, Raymond Wang, Flora Fleith Lopes, Zhengjia Yang, Brain Chu, Weijian Wang, Leo Chen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This group project presents ConfidenceAI, a conceptual wearable and predictive artificial intelligence ecosystem designed to help teenagers build confidence and manage stress in high-pressure situations such as classroom participation and public speaking. The system combines wrist-based biosensing with a personalized machine-learning model that uses physiological signals, including heart rate and heart rate variability, electrodermal activity, skin temperature, and movement, to learn an individual's baseline patterns and anticipate heightened stress responses. Rather than relying on universal thresholds, ConfidenceAI is designed to personalize the timing, method, and delivery of interventions based on each user's physiological patterns and prior responses. The proposed ecosystem …

How Do Different Food Influents Affect Biogas Production, Process And Operational Stability, And System Performance In The Armfield W8, A Bench-Scale Anaerobic Digester, Jarko Rumbaoa, Anahita Adhikari

Rose-Hulman Undergraduate Research Publications

No abstract provided.

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

A System Dynamics Model For Analyzing Customer Satisfaction Drivers In A Manufacturing Context, Mahnaz Asgari Sooran, Venkat Allada, Adewole Adegbola

Engineering Management and Systems Engineering Faculty Research & Creative Works

Customer satisfaction offers economic benefits and competitive advantage to manufacturing enterprises. However, a gap exists in understanding how to achieve customer satisfaction due to the complexities involved in coordinating various subsystems of an enterprise in an efficient manner. In this paper, we identified four internal and external-to-the-firm customer satisfaction drivers which include: government policies, supply chain reliability, knowledge management, and manufacturing performance criteria such as on-time delivery, quality and cost. We then developed a conceptual framework to define the non-linear mathematical relationships between drivers using system dynamics modeling. We conducted "what-if "scenario analyses for a base case, optimistic case and …