Digital Commons Network^™

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 …

Examining Data Richness In Undergraduate Students’ Reflections: A Linguistic Analysis Of Three Data Collection Methods, Kirsten A. Davis, Anne Wrobetz

School of Engineering Education Faculty Publications

Researchers select data collection methods for a variety of reasons. In our research on experiential education programs, we perceived that when we collected students’ reflections using different methods, the data we received was different. However, we found few existing studies to help us characterize what was different across our data sets to inform our decisions about which methods to use. Thus, the purpose of our study was to compare data richness across three data sets from previous studies of engineering students studying abroad, each collected using a different method (written diaries, interviews, video diaries). We used linguistic inquiry as a …

System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project that seeks to enable the simulation and validation of sensors, actuators, and control logic related to spacecraft attitude control. The SADS platform rests atop a spher- ical air-bearing device which allows for nearly frictionless rotation in all three axes. The orientation of the platform is controlled by four reaction wheels arranged in a pyramidal configuration. Over the past few years, there have been significant updates to the reaction wheel subsystem, as well as requests for a more capable central com- puter. Therefore, a new system architecture for the …

Vehicle Autonomy To Ecosystem Intelligence: A Systematic Review Of Dynamic Vision Architectures In Surface Mining Operations, Nana Yaa Damtewaa Anti, Samuel Frimpong, Muhammad Azeem Raza

Mining Engineering Faculty Research & Creative Works

Autonomous Haulage Systems (AHS) have significantly transformed surface mining operations by improving safety, productivity, and operational consistency. Currently, AHS predominantly rely on vehicle-centric perception architectures. Onboard LiDAR, radar, cameras, and Global Navigation Satellite Systems (GNSS) perform sensing, interpretation, and decision-making within individual systems. These processes enable collision avoidance and path tracking. However, they are limited in their ability to consider the broader, dynamic mining environment characterized by dust, terrain degradation, geotechnical instability, heterogeneous traffic, and rapidly evolving operational conditions. This paper presents a systematic review of dynamic vision systems of AHS in surface mining. It critically analyzes the transition from …

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 …

Thiol-Based Neuroprotective Copolymers Acutely Restore Redox Metabolism And Mediate Vasogenic Edema In A Mouse Model Of Traumatic Brain Injury, Evan T. Curtis, Brandon Z. Mcdonald, Aria W. Tarudji, Aaron M. Priester, Anthony J. Convertine, Forrest M. Kievit

Materials Science and Engineering Faculty Research & Creative Works

Effective pharmaceutical interventions for treating the secondary damage associated with traumatic brain injury (TBI) are limited due to poor delivery into the brain, insufficient target engagement, and an incomplete understanding of the pathophysiological changes that occur post-impact. Thus, nanoparticles (NP), which have an enhanced permeation and retention-like effect within the perturbed blood-brain barrier, have grown as a potential candidate for treating TBI. We have investigated the antioxidant capacity of thiol-based NP, termed neuroprotective copolymers (NPC3), and their ability to neutralize reactive oxygen species (ROS) and lipid peroxidation products (LPOx). Here, we assessed the efficacy of NPC3 for alleviating the secondary …

Advancing Sensing And Structural Health Monitoring Of Non-Conventional Space Structures, Scott Bender

Doctoral Dissertations and Master's Theses

Future lunar and deep-space missions will require new structural concepts that reduce mass while maintaining reliability. Two technologies that have received significant attention are inflatable habitats and additively manufactured structures; however, challenges remain in their characterization, validation, and long-term monitoring. This dissertation investigates methods to improve the testing and sensing of these non-conventional aerospace structures through the use of advanced photogrammetry and embedded distributed fiber-optic sensors. A color-filtering digital image correlation technique was developed to isolate orthogonal strain directions in woven inflatable structures, providing improved characterization of biaxially loaded softgoods. In addition, methods were developed to embed distributed fiber-optic sensors …

A Systems Analysis Of Autonomous Uav Swarm Spraying For Precision Agriculture, Ryker Davis

Graduate Theses and Dissertations

The application of Unmanned Aerial Vehicles (UAVs) in civilian sectors, particularly for precision agriculture and targeted aerial spraying, has rapidly evolved from passive monitoring to advanced, autonomous, multi-agent coordination. While deploying UAV swarms offers a promising solution to the payload and battery endurance limitations of single drone operations, realizing field-scale coverage introduces significant logistical and safety challenges. To evaluate the trajectory and viability of swarms, this study synthesizes bibliometric trends, operational simulation, and safety reporting analysis. First, because physical testing of complex swarms poses financial and safety risks, we developed an agent-based and discrete event simulation to evaluate autonomous spraying …

Monitoring And Short-Term Forecasting Of Atmospheric Air Pollutants Using Deep Neural Networks, Prasanjit Dey

Dissertations

Accurate forecasting of near-surface atmospheric air pollutants such as PM2.5, NO2, SO2, CO, and O3 remains a critical scientific and societal challenge. This difficulty arises from several factors, including nonlinear pollutant dynamics, sparse ground monitoring net works, heterogeneous satellite observations, and strong cross-pollutant interdependencies. Substantial advances have been achieved in temporal deep learning, probabilistic modeling, satellite-based estimation, physics-informed methods, and foundation models. However, these paradigms have largely evolved in isolation. As a result, existing systems are often station-dependent or pollutant-specific and optimized for a single forecasting task. This limits their robustness and generalizability across regions and heterogeneous data regimes.

This …

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 …

A Century Of Safer Skies: Statistical Insights Into Aviation Accidents And Death Rates, Abhijeet Regmi

Journal of Aviation Technology and Engineering

The purpose of this study is to determine whether the recent advancements in the technology used for aircraft maintenance and repair have resulted in an increase or decrease in the accident and fatality rates of aviation incidents and accidents. The primary concerns are the extremely low survival rates in aviation accidents and the necessity to determine whether or not the accident and fatality rates are declining in light of recent technological advancements. If the rate is rising, we must prioritize passenger and crew safety more and adhere to tight regulations when performing repairs and maintenance. The data were compared for …

The Open Wiki Of Electrochemical Methods (Owem): A Community-Driven Educational Resource, Anderson Fuller, Devin Rappleye

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

The traditional resources for learning electrochemical methods—textbooks, academic literature, and university coursework—remain essential but are limited in accessibility, update frequency, and practical usability. This paper introduces the Open Wiki of Electrochemical Methods (OWEM), an open-access, community-driven platform designed to complement these resources. OWEM organizes content into equations, definitions, methods, tutorials, and supplementary articles, with a heavy emphasis on experimental relevance. A case study on cyclic voltammetry demonstrates how OWEM consolidates foundational theory, lesser-known results, and practical guidance within a continuously maintainable framework to benefit the broader electrochemistry community.

Aspirational Mirrors: A Conceptual Model Of Alumni-Led Near-Peer Outreach For Precollege Engagement In Ocean Engineering, Habibi Palippui, Juswan Sade

Journal of Pre-College Engineering Education Research (J-PEER)

Precollege students in Indonesia, especially in rural and coastal regions, often lack exposure to engineering disciplines due to social, geographic, and informational barriers. This essay proposes a conceptual model of alumni-led near-peer outreach as an affective and culturally grounded mechanism to engage high school students in ocean engineering. Drawing from theories of social similarity, possible selves, and engineering identity, the model conceptualizes alumni as “aspirational mirrors” who influence students not merely through information but also through identification. The model outlines four primary mechanisms—social connection, narrative engagement, aspirational mirroring, and early identity activation—and also accounts for contextual variables such as school …

Detection And Diagnostic Screening Of Breast Cancer: A Systematic Review And Future Frontiers, Lama Yassine, Amira J. Zaylaa

BAU Journal - Science and Technology

A comprehensive evaluation of current and novel diagnostic techniques is necessary since the diagnosis of breast cancer is essential for improving treatment efficacy and raising long-term survival. Evidence from conventional imaging methods including mammography, ultrasonography, and magnetic resonance imaging is combined in this systematic review with advancements in liquid biopsies and current AI-based diagnostic tools. Using specific keywords related to breast cancer, early detection, imaging, biomarkers, and artificial intelligence, a thorough search was conducted in PubMed, Scopus, Web of Science, and IEEE Xplore. Reviews, case reports, and studies unrelated to breast cancer were excluded; only clinical, experimental, and computational research …

Emerging Technologies For Safety Risks Management On Nigerian Road Construction Projects, Ranti Taibat Adebiyi, Mujidat Olubola Babalola, Richard Olushola Olupeka, Ganiyu Amuda Yusuf, Lukman Olarewaju Olorunoje, Amina Damola Amuda

BAU Journal - Science and Technology

High level of safety risk on road construction projects remains a major concern for all industry stakeholders, as safety of workers is paramount to achieving project success. Managing construction safety requires a more comprehensive approach. New technologies have recently emerged to enhance construction safety. This study examines the level of adoption and barriers to the implementation of these technologies in safety risk management on road construction sites in Lagos, Nigeria, with a view to improving the safe delivery of the road projects. A questionnaire was designed and administered to two engineers and one worker randomly selected on each of sixty-one …

Compound Role Of Using Advanced Materials And Design Procedures On Improving The Performance Of Baghdad Buildings Facades, Abeer Qasim Jbur

Al-Esraa University College Journal for Engineering Sciences

The research idea addresses improving the thermal performance of buildings in Baghdad by selecting and employing facade materials to reduce heat gain and energy consumption associated with cooling in a hot-dry climate. The study discusses the pivotal role of facade materials in interacting with solar radiation, heat transfer, and inward thermal transmittance, as well as their capacity to store and release heat in ways that maintain thermal comfort within architectural spaces and reduce reliance on mechanical cooling systems. A range of traditional materials such as stone, earth, and concrete is presented alongside modern materials like high-performance glass and thermal storage …

Real-Time Adaptive Control Of Machining Parameters In Cnc Milling Using An Ensemble Digital Twin And In-Process Vibration Monitoring For Enhanced Surface Integrity, Ali Qasim Abdulwahid

Al-Esraa University College Journal for Engineering Sciences

Achieving consistent surface integrity in CNC milling under varying materials and degraded tool conditions remains a critical challenge because fixed cutting parameters often induce regenerative chatter, accelerate tool wear, and cause surface and subsurface damage. This paper presents an integrated solution that combines an Ensemble Digital Twin (EDT), real-time in-process vibration monitoring, and a hybrid adaptive controller to maintain high surface quality while preserving productivity. The EDT fuses a physics-based milling dynamics model with a recurrent LSTM surrogate through a context-aware meta-learner that weights model outputs by process state (e.g., tool wear, engagement). A compact real-time monitoring pipeline computes a …

Effect Of Nano-Additives On Fracture Toughness Of Engineering Materials: An Experimental Study, Humam Ahmed Awad

Al-Esraa University College Journal for Engineering Sciences

Structural integrity and service life of engineering components is based on fracture resistance. The paper presents an experimental study on the nano-additive that can be added to the locally-produced Iraqi engineering materials in order to enhance their fracture toughness. The research was inspired by the increasing demand in high-performance materials in the main sectors of the country such as infrastructure and energy besides the need to improve the properties of local resources. The tested material systems were two Portland cement composites and epoxy-based polymers. Nano-silica (n-SiO₂ nano-alumina (n-Al₂O₃) and multi-walled carbon nanotubes (MWCNTs) were added …

An Intelligent System For Managing High-Priority Vehicle Routing In Smart Cities Using Artificial Intelligence And Spatial Data Analytics, Bahjat Abdulelah Madhloom

Al-Esraa University College Journal for Engineering Sciences

In developing metropolises, there is a risk to public safety in addition to the usual traffic jams. Traffic delays can have life-altering effects every second that fire trucks and ambulances are delayed. Large cities like Baghdad, which suffer from haphazard road sealing and incompetent traffic management, are especially affected, creating daily emergency crisis problems. We create a new intelligent routing system for these top priority vehicles in order to solve this life-or-death problem. Our method uses a trained model with real-time spatial information instead of outdated static maps. A Long Short-Term Memory (LSTM) neural network at its core constantly forecasts …

Objective Biomarker Development For Parameter Optimization In Neuromodulation Using High-Density Emg Temporal And Spatial Features, Shirin Madarshahian, Nikoo Javadpour, Michael Trakhtorchuck, Tatiana Guerrero-David, Kristin Gustafson, James Harrop, Caio Matias, M. J. Mulcahey, Alessandro Naopli, Alex R. Vaccaro, Mijail Serruya

Farber Institute for Neuroscience Faculty Papers

Transcutaneous spinal cord stimulation (tSCS) is a promising neuromodulation approach for motor recovery after spinal cord injury (SCI), yet clinical programming remains largely dependent on subjective parameter selection. This study evaluated high-density surface EMG (HD-sEMG)–derived spatial and temporal features as objective biomarkers for tSCS optimization in three adults with chronic cervical SCI. A 64-channel electrode array recorded stimulation-evoked responses across five cervical stimulation levels, four pulse widths, and graded amplitudes. Features describing activation magnitude, spatial distribution, cluster morphology, and temporal dynamics were extracted from epoch-based activation maps. Of the three enrolled participants, two demonstrated measurable stimulation-evoked responses and contributed to …

Cfd Optimization Using Ansys Fluent For Advanced Thermal Energy Conversion, A Case Study On Heat Recovery Systems In Iraqi Power Plants, Basim Mohammed Abid Ali

Al-Esraa University College Journal for Engineering Sciences

The energy sector in Iraq has lots of potential but the infrastructures are old and lack optimum thermal efficiency resulting in high consumption of fuel and environmental degradation. The study focuses on the urgent necessity of modernization of the thermal energy conversion systems in the industrial plants of Iraq by means of the further development of numerical simulation. The paper applies the Computational Fluid Dynamics(CFD) through ANSYS Fluent to model and optimize a shell-and-tube heat exchanger, which is similar to the ones employed in heat recovery units in Iraqi thermal power plants like the Al-Dora power plant in Baghdad. The …

Design And Development Of Solar-Powered Water Desalination Systems, Salam Ali Hassoon Alabooda

Al-Esraa University College Journal for Engineering Sciences

Background: Freshwater scarcity and growing energy demand have promoted interest in sustainable desalination technologies, particularly in arid areas like Iraq which has high solar resource and decentralized water supply becomes a key factor. Aim: The purpose of this study was to design and test a solar powered water desalination system that could enhance fresh water productivity, thermal efficiency and quality of water under the climatic conditions of Iraq. Methodology: It was designed as hypothetical pilot-scale system that comprised of a single-slope solar still combined with a flat-plate solar collector, a 200 W photovoltaic-driven circulation pump and 18 kg of phase …

Experimental Analysis Of Diesel Engine Combustion Chamber Performance Using Field Measurements At The State Company For Heavy Engineering Equipment, Mohammed Kanaan Sedeeq

Al-Esraa University College Journal for Engineering Sciences

The current paper provides a detailed experiment and numerical study of the performance of the combustion chamber of a heavy-duty diesel engine in the common Iraqi industrial conditions at the State Company of Heavy Engineering Equipment (HEESCO). The main goal is to close the difference between what is specified by the manufacturers concerning the performance data, which is usually assumed to be under ideal conditions of the ISO standard, and the real efficiency of operation as witnessed in the field. The methodology is based on a hybrid approach that combines direct field measurements of in-cylinder pressure, temperature and fuel flow …

An Ai And Iot Framework For Dynamic Optimization And Sustainability In Smart Cities, Zeinab E. Ahmed, Rashid A. Saeed, Salah Hagahmoodi, Mamoon M. Saeed, Khalid Hamid, Sally D. Abugasim, Eyman F. A. Elsmany

Al-Esraa University College Journal for Engineering Sciences

Smart cities are emerging as a critical solution for creating more efficient, sustainable, and comfortable urban environments. This transformation is primarily driven by the synergistic integration of the Internet of Things (IoT) and Artificial Intelligence (AI). The IoT provides a pervasive network of connected sensors that collect real-time urban data, while AI serves as the analytical engine that processes this information to optimize city-wide systems. This paper presents a comprehensive framework that leverages this AI-IoT convergence for dynamic optimization to achieve long-term urban sustainability. The framework focuses on enabling intelligent, data-driven decision-making across core urban domains. The discussion and analysis …

Interval-Valued Neutrosophic Dombi Bonferroni Mean Aggregation Operators In Medical Diagnosis And Sustainable Energy, Maryam Faisal, Muhammad Nadeem, Muhammad Kamran

Neutrosophic Systems with Applications

Medical diagnosis is one of the most difficult fields in which decisions must be made due to the fact that medical information often has characteristics of uncertainty, incompleteness, imprecision and even contradiction. Traditional aggregation and decision-making methods are often not well suited to such complexities, and may result in less reliable diagnostic outcomes. In order to overcome these drawbacks, the authors propose a new approach using a novel representation of Interval-Valued Neutrosophic Sets (IVNSs), the Dombi operational laws, and Bonferroni Mean (BM) aggregation operators. The proposed framework is specifically aimed at coping with uncertainty, indeterminacy and falsity all at once …

Architecture Of The Information System Supporting Information Processing And Decision-Making In Medicine, Isamidin Sidikov, Sanjarbek Bekturdiev

Chemical Technology, Control and Management

This article examines the architecture of an information system that supports information processing and clinical decision-making in the field of medicine. The system is described using a multilayer functional model that enables the integration, analysis, and efficient utilization of heterogeneous data. The utilization of the BioBERT and XGBoost neural network models at data collection, preparation and analysis, as well as decision-making steps using machine learning and expert systems are summarized. The use of IDEF methodology for modeling medical information system is reviewed and the importance of IDEF0, IDEF1, IDEF1X, IDEF2, and IDEF3 models is emphasized. An efficient paradigmatic model for …

Integration Of Adaptive Kalman Filter And Bayesian Models For Diagnostics And Reliability Assessment Of Vision Sensors, Rustam Tulkunovich Khamdamov, Marjona Jasubek Qizi Xoliqova

Chemical Technology, Control and Management

Vision-based sensors constitute a cornerstone of contemporary automation, robotics, and intelligent transportation systems, where their reliability directly determines operational safety and efficiency. Conventional Kalman filtering achieves optimal state estimation under linear dynamics and stationary noise assumptions, yet its performance deteriorates in the presence of sensor malfunctions or nonstationary environments. This study proposes an innovative framework that couples an adaptive Kalman filter with Bayesian inference to strengthen diagnostic capabilities and reliability evaluation of vision sensors. The Kalman filter provides dynamic state tracking, while Bayesian reasoning enables probabilistic fault identification and reliability quantification. The methodological novelty lies in the real-time adjustment of …

Research On Dic Monitoring Of Dynamic Deflection And Damage Identification Method For Small And Medium-Span Bridges, Wang Yong, Li Derui, Tang Haotian, Yan Xingfei, Cheng Bin

Journal of China & Foreign Highway

A large number of built small and medium-span bridges in China are facing the problem of increasingly degrading structural performance. Therefore, it is of great significance to carry out lightweight intelligent monitoring and realize damage identification and early warning, so as to ensure the safe operation of these bridges. For typical small and medium-span simply supported beam bridges, a damage analysis method based on measured dynamic deflection data was established by combining the influence line theory and mechanical constitutive equations. Furthermore, based on the high-precision monitoring algorithm and instruments of digital image correlation (DIC), the real-time dynamic deflection data of …