Digital Commons Network^™

Investigation Of The Production Technology Of Environmentally Safe Urethane Oligomers Based On Local Raw Materials, Bakhtiyor Kudratovich Shaykulov, Dilafruza Ruziboevna Akbarova Gulboeva, Fayzulla Nurmuminovich Nurqulov

Technical science and innovation

This paper investigates the step-by-step poly condensation pathway for synthesizing environmentally friendly, non-isocyanate urethane oligomers derived from local and safe raw materials: urea and ethylene glycol. The influence of thermodynamic parameters on the target product yield was systematically evaluated to determine the optimum technological matrix. Specifically, a 1:2 reactant mass ratio, a stable stationary temperature of 150-155 °C, and a reaction duration of 2 hours under an inert nitrogen atmosphere resulted in a sustainable and reproducible yield of 72%. Thermal degradation and competitive side-product condensations were activated above 160 °C, leading to a sharp drop in overall chemical efficiency. The …

Evaluation Of Level Measurement Uncertainty For Three Types Of Laser Level Meters Using The Gum Methodology: Calculated Uncertainty Budgets, Uncertainty Profile, And Hardware Component Requirements, Lazizbek Furkatjanovich Saidoripov, Barat Makhmudovich Akhmedov

Technical science and innovation

A methodology is presented for evaluating the uncertainty of liquid petroleum product level measurements using laser level meters based on different measurands’ informative parameters: propagation time, phase difference, and image coordinates. Based on analytical expressions for error components and a traceability chain to the national length standard, calculated uncertainty budgets are developed in accordance with JCGM 100 for time-of-flight, phase-based, and laser–television level meters. Under the assumed input conditions, the expanded uncertainties (k = 2) are 1.66, 0.73, and 1.02 mm, respectively. For the laser–television level meter budget, the Gaussian approximation is verified using the Monte Carlo method (JCGM 101): …

Effect Of Waste Cooking Oil And Tapioca Starch On Energy Content And Combustion Performance Of Coconut Shell-Rice Husk Briquettes, Satworo Adiwidodo, Wirawan Wirawan, Kris Witono, Moh. Hartono, Asrori Asrori, Fauzan Baananto, Suliono Suliono, Syahrul Mubarok, Norhafana Binti Mohamed

Journal of Mechanical Engineering Science and Technology (JMEST)

Agricultural waste, such as coconut shells and rice husks, is widely utilized as solid fuel. Tapioca starch serves as the binder, while waste cooking oil (WCO) is used as an additive. Briquette performance is influenced by the type of biomass, binder, and additives used. However, the individual and interactive effects of WCO and tapioca starch on the performance of coconut shell-rice husk briquettes remain insufficiently established. This research focused on evaluating the effects of WCO and tapioca starch on calorific value (CV)  and mass consumption rate. The briquettes' base composition consisted of 75% coconut shell charcoal and 25% rice husk …

Developing A Digital Facility Management Framework For Enhancing Operation And Maintenance Of Public Parks In Egypt, Alaa Ezzat, Alia Amer, Yasser M. El Sayed

HBRC Journal

Public parks in Cairo represent important urban assets, however, their operation and maintenance (O&M) face many challenges due to fragmented information, reactive maintenance practices, organizational constraints, and limited digital integration. Digital Facility Management discipline still lacks the tailored framework that adequately addresses the operational needs of public parks in Egypt with all its specific details. This study develops an integrated digital FM framework for improving the efficiency of the management process of public parks. A four-phase methodology was adopted, comprising a literature review, framework development, technical system specification, and expert assessment. The proposed framework integrates BIM, COBie, CMMS, IoT technologies, …

Machine Learning Models For Estimating The Consumed And Remaining Useful Life Of Haul Trucks In An Open-Pit Mine In Peru, Marco Cotrina, Jairo Marquina, Mario Sandoval, Jose Mamani, Johnny Ccatamayo

Journal of Sustainable Mining

The purpose of this study was to develop a machine learning-based model to predict the consumed useful life and estimate the remaining useful life of haul trucks in an open-pit mining operation in Peru. A comparative analysis of multiple machine learning models was conducted, including multiple linear regression (MLR), random forest + PSO, support vector regression (SVR), gradient boosting machine (GBM), decision tree + PSO, and artificial neural networks (ANN-MLP). The models were evaluated using performance metrics such as R², RMSE, and MAE, selecting the optimal model to estimate the remaining useful life based on a theoretical lifespan …

Development Of A Spectral Index And Web Application For Automated Marble Quarry Monitoring: A Sentinel-2 Based Approach For Change Detection And Monitoring, Konstantinos Ntouros, Vasileios Drimzakas - Papadopoulos, Georgios Gkologkinas, Georgios Ntouros, Dimitrios Markou

Journal of Sustainable Mining

This study introduces an automated workflow to monitor marble quarry operations using Sentinel-2 satellite data, providing a cost-effective and efficient tool for regulatory oversight focused on environmental sustainability. At the core of this workflow is the Quarry Change Detection Index (QCDI), a new spectral index specifically developed to leverage the unique spectral characteristics of quarry sites, enhancing the detection of land cover changes associated with quarry expansion. To facilitate practical application, a web-based tool was developed using Google Earth Engine and Streamlit. The user-centric design of this platform features an intuitive interface, allowing users to easily select parameters, visualize data, …

Virtual Natural Lighting Solutions (Vnls) Inside Hospitals And Its Psychological Impact, Asmaa Alaa Hasanein Hasanein, Alaa Shams Al-Din Al-Aishi, Marwa Atef Abd Elhady

Mansoura Engineering Journal

This study examines the correlation between daylighting environments in hospitals, users evaluations, and ways of bringing virtual natural light into inner spaces, highlighting the importance of good daylighting design for physical and psychological well-being. Virtual Natural Lighting Solutions (VNLS) mimic the balanced spectrum of natural light, bridging the gap between natural and artificial light, and are crucial for tasks, circadian rhythm, and mood in healthcare settings. The research addresses the variability and limitations of natural light, proposing VNLS for healthcare lighting design, especially in hospitals lacking daylight. The study aims to develop a methodology for using VNLS in healthcare environments …

Reinforcement Learning: A Christian Perspective, Paul Griffioen

Faculty Work Comprehensive List

No abstract provided.

Data From: Physics-Data-Hybrid Modeling And Control For Vtol Aircraft, Samantha Dawn Burton

Browse all Datasets

The skeleton code corresponding to many of the results from the dissertation "Physics-Data-Hybrid Modeling and Control for VTOL Aircraft" By Samantha Dawn Burton.

Integrating Gis With Interim Payment Valuation In Road Construction Projects: A Conceptual Framework, Abdulrahman I. Iro, Juma M. Matindana, Julian Ijumulana

Tanzania Journal of Engineering and Technology (TJET)

Abstract

Interim Payment Valuation is a critical process in road construction contract administration, yet conventional valuation practices remain heavily dependent on manual measurements, fragmented documentation, spreadsheets, and professional judgement. These limitations can affect measurement accuracy, transparency, traceability, and the timeliness of payment certification. Although Geographic Information Systems have increasingly been applied to construction planning, quantity measurement, progress monitoring, infrastructure management, and decision support, their integration with contractual and financial processes for interim payment valuation remains insufficiently explored. This study therefore develops a conceptual framework for integrating GIS with Interim Payment Valuation in road construction projects. A PRISMA-guided structured literature review …

A Tool For Assessing The Effectiveness Of Speed Humps As Traffic Calming Measure, Abdulrazak Mzamiru Kachwamba, Enock W. Nshama

Tanzania Journal of Engineering and Technology (TJET)

Urban population growth and increasing motor vehicle usage continue to raise concerns regarding road safety in rapidly developing cities. Although previous studies have assessed traffic-calming effectiveness using multiple criteria, they have analysed the criteria separately and have not developed a composite tool for classifying overall effectiveness. This study develops a quantitative assessment tool designed to compute a weighted composite score for evaluating the effectiveness of speed humps as a traffic calming measure. Stakeholder questionnaire responses, complemented by descriptive analysis and exploratory factor analysis, were used to identify key indicators of effectiveness and the variables influencing them. Findings indicate that speed …

Artificial Neural Network-Based Modelling And Prediction Of Key Performance Indicators In Road Construction Projects, Hussein Mativila, John M. Kafuku, Beatus A. T. Kundi

Tanzania Journal of Engineering and Technology (TJET)

Road construction projects in developing countries including Tanzania experience several challenges including cost overruns, schedule delays and poor quality. The causes of these challenges include complex interdependencies project’s uncertainty factors. This makes traditional methods for predicting Key Performance Indicators (KPIs) less effective. This study has developed a robust Artificial Neural Network (ANN) model for accurate modelling and predicting KPIs for road construction projects in Tanzania. The analysis was based on data obtained from 281 projects implemented by TANROADS in 11 regions from 2015 to 2025. Fourteen uncertainty factors were measured on a five-point Likert scale and screened using Principal Component …

Voltage-Related Power Quality Issues And Impacts On Distribution Networks With Sensitive Loads - A Review, Godwin Elinazi Mnkeni, Jackson Justo, Aviti Thadei Mushi, Bakari M. M. Mwinyiwiwa

Tanzania Journal of Engineering and Technology (TJET)

Voltage disturbances are the most important power quality (PQ) complications that customers and power utilities face in this smart era. The growing adoption of sophisticated electronic equipment and integration of renewable energy sources (RES) into power grids has increased the susceptibility of power distribution networks (PDNs) to voltage sags, swells, interruptions, flicker, and voltage imbalance. These disturbances, mainly caused by upstream faults, switching operations, and RES integration, compromise voltage PQ and system reliability. Consequently, they accelerate equipment degradation, increase electronic waste (e-waste), raise reactive power demand and maintenance costs, increase power losses, and impose substantial economic losses on customers and …

Applications Of Nanotechnology In Building Envelopes: An Analytical Study Of Environmental Performance And Architectural Form, Essam Salah Said Abdelmagid

Mansoura Engineering Journal

Contemporary architecture has witnessed a rapid evolution in the integration of nanotechnology within the design of building envelopes, due to its significant capability to enhance the physical and environmental properties of materials and to redefine the relationship between functional performance and architectural form. The building envelope is considered one of the most influential components affecting energy efficiency, indoor environmental quality,  and visual identity, which has made it a primary field for the application of nanomaterials and nanotechnologies.

This research aims to investigate and analyze the impact of nanotechnology applications in building envelopes on both environmental performance and architectural form through …

Direct Electrochemical Detection Of Carbaryl In Water Using Boron-Doped Diamond Electrodes, Natasha Fransisca, Chico Permana Putra, Salma Nur Zakiyyah, Muhammad Ihda Hamlu Liwaissunati Zein, Yeni Wahyuni Hartati, Irkham Irkham

Chimica et Natura Acta

Carbaryl (1-naphthyl methylcarbamate) is a carbamate pesticide used to cause adverse environmental and health effects when misused through water contamination. Therefore, this research aimed to develop a direct electrochemical detection method for carbaryl in aqueous media using boron-doped diamond (BDD) electrodes. In this context, BDD electrodes exhibited superior electrochemical performance compared to conventional materials such as gold (Au), platinum (Pt), and glassy carbon electrodes (GCE) due to a wide potential window, low background current, and excellent chemical stability. Cyclic and differential pulse voltammetry reported a well-defined oxidation peak for carbaryl at 1.30 V, with significantly enhanced sensitivity. The results showed …

Willingness To Pilot Under Varying Weather And Tower System Conditions: Mediating Effects Of Risk, Nathan Royal Schultz

Doctoral Dissertations and Master's Theses

The implementation of Remote Tower Systems (RTS) within the National Airspace System (NAS) offers potential improvements in operational efficiency, cost-effectiveness, and scalability; however, its success depends on pilots' willingness to operate in such environments. This study examined the effects of tower system type (RTS vs. Traditional Tower Systems [TTS]) and weather conditions (visual meteorological conditions [VMC], marginal visual meteorological conditions [MVMC], and instrument meteorological conditions [IMC]) on pilots’ willingness to pilot (WTP), while also evaluating the mediating role of perceived risk (PR). Grounded in Paul Slovic’s Risk Perception Theory (RPT), this research employed a quantitative experimental design using a factorial …

Heavy-Duty Diesel Vehicle Deterioration: Impact Of Vehicle Age And Emission Control Technology On Nox Emissions - Preprint, Amber L. Gurecki Allen, Andrew R. Colman, Max D. Sommer, William D. Waddoups, Darrell B. Sonntag

FEAT Publications

Pre-print manuscript.

Abstract

This study examines the effect of aging and deterioration on NO_x emissions from heavy-duty diesel trucks (HDDTs) with different emission control technologies, including Engine Control only, exhaust gas recirculation (EGR), and selective catalytic reduction (SCR). In-use tailpipe emissions were measured from 12,023 HDDTs from 13 roadside measurement campaigns conducted in California and Utah between 2008 and 2024. Vehicle registration records and the Environmental Protection Agency’s (EPA) engine certification database were used to identify engine NO_x control technology. At younger ages, SCR-equipped HDDTs generally emitted significantly less NO_x than non-SCR-equipped HDDTs. However, after several years …

Factors Influencing Enterprise Adoption Of Ai-Enabled Computers: An Expert Judgment Quantification Approach Across Multiple Sectors, Yu Shan Su, Tugrul Daim, Chia-Hao Hung, Leong Chan, Dana Bakry

Engineering and Technology Management Faculty Publications and Presentations

This study examines the key factors influencing the adoption of Artificial Intelligence Personal Computers (AIPCs) by enterprises, exploring both the benefits and challenges of their business applications. As enterprises increasingly require real-time computing, autonomous decision-making, and improved cybersecurity, AIPC—combining artificial intelligence and edge computing—has become a strategic technology for boosting competitiveness. Particularly in scenarios with less reliance on cloud services, businesses are more likely to adopt devices with local processing and standalone AI capabilities to meet the dual needs of operational efficiency and data privacy. Through an extensive review of the literature, this study identifies four main dimensions and sixteen …

Size-Tunable Tellurium Quantum Dots By Glancing Angle Deposition, S. M. Sayem, Salim Hussain, Fernando Maia De Oliveira, Ranjitha Kumarapuram Hariharalakshmanan, Gregory Guisbiers, Tansel Karabacak

Faculty Scholarship

Tellurium has a unique helical crystal arrangement and pronounced anisotropy that influence its electronic and optical properties at the nanoscale. This study reports the synthesis of pure tellurium quantum dots (Te QDs) on silicon wafer using glancing angle deposition (GLAD). Quasi-hemispherical dots with lateral sizes ranging from 9 to 28 nm and vertical dimensions of 6 to 10 nm were produced as a function of the deposition duration. A comparison of the dot sizes with the Bohr radii of the charge carriers indicated a regime of strong to intermediate confinement. Structural analyses confirmed the polycrystalline nature and trigonal phase of …

Aidws1: Building With Llms And Ai Agent, Olivier Kepler Francois

Paul English Applied Artificial Intelligence (AI) Institute Publications

The Paul English Applied Artificial Intelligence Institute (PEAAII) at the University of Massachusetts Boston hosted the first session of its AI Demo Workshop Series, “Building with LLMs and AI Agents,” on October 5, 2026, led by Olivier Kepler Francois, Founder and Researcher of WebAIAgent. This hands-on workshop introduced participants to developing AI-powered web applications using Large Language Models (LLMs), Next.js, React, HTTP communication, and the OpenAI API. Through guided demonstrations and practical exercises, participants explored frontend and backend development, API integration, user interaction, and the end-to-end process of building an interactive AI application. The session provided foundational knowledge and practical …

Analysis And Design Of Multi-Winding Current Ballasted Magnetics For Integrated Dc-Dc Conversion, Kishalay Datta

Dartmouth College Ph.D Dissertations

Power conversion circuits have become a bottleneck in terms of reducing the size and cost of modern electronic systems in a vast number of applications ranging from personal devices, to automotive systems, to data centers. This has motivated designs at higher frequencies where smaller passive components can be used. Unfortunately, magnetic components scale poorly to smaller dimensions. In addition, the AC resistance of magnetic components deteriorates due to current crowding effects at high frequencies. This has resulted in fully- integrated power converters with planar magnetic components having efficiencies lower than what may be theoretically achieved. In this work, we investigate …

Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe, Homayoon Soleimani Dinani, Bohong Zhang, Maryam Karimi, Rex E. Gerald, Shelley D. Minteer, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We report a dual-modal fiber-optic probe that integrates electrochemical quantification of hydrogen peroxide (H₂O₂) with co-localized fluorescent pH sensing for pH-indexed interpretation of the H₂O₂ response. H₂O₂ is a reactive oxygen species involved in oxidative stress, inflammation, and cellular signaling, and local pH modulates both its production and electrochemical response. Many electrochemical H₂O₂ sensors exhibit pH-dependent sensitivity, creating ambiguity unless pH is measured and used for compensation, which is difficult in small, heterogeneous, or rapidly changing microenvironments. A three-electrode configuration—working (WE), counter (CE), and Ag/AgCl pseudo-reference (pRE) electrodes—is fabricated directly on the cylindrical surface of a 710-µm-diameter optical fiber using …

Domain Knowledge-Informed Machine Learning Model To Study Weather-Induced Flight Delays, Gurvir Bawa

Doctoral Dissertations and Master's Theses

Weather-induced Traffic Management Initiatives (TMIs) occur rarely relative to normal air traffic operations. This scarcity produces severe class imbalance that limits predictive models of flight delay. To address it, this dissertation leverages a physics- and domain- knowledge informed Variational Autoencoder (VAE), conditioned on airport identity, that generates physically plausible synthetic weather events for underrepresented TMI categories. The fidelity of the model is assessed with a calibrated discrepancy measure disclosed along- side the results rather than described in free-form terms. A multitask Graph Neural Network (GNN) is then trained on the augmented dataset to jointly classify airport-level TMI status and predict …

Disturbance-Learning Inertia Estimation Using Artificial Neural Networks For Power System Stability, Sospeter Igaanja Gabriel, Francis Mwasilu, Peter Makolo Dr.

Tanzania Journal of Engineering and Technology (TJET)

ABSTRACT

Power systems are progressively shifting towards low inertia as a result of incorporating significant amounts of intermittent and converter-based renewable energy sources, such as wind and solar power, into the current power grid network. This integration poses considerable problems to inertia and frequency control within the network due to a reduction in the proportion of synchronous generators. Furthermore, rapid frequency deviations occur due to the disparity between supply and demand during contingencies, complicating the maintenance of frequency stability within the power system. The disturbance-learning inertia estimation method for power system stability is presented. The simulation analysis is performed using …

The Algorithmic Narcissus: Ai Validation And The Atrophy Of The 'Athletic' Social Self, Ilham Phalosa Reswara, Anggi Mayangsari

Jurnal Psikologi Sosial

Artificial intelligence systems designed around continuous affirmation and minimal friction are becoming increasingly prominent as social and relational partners in everyday life. This article examines how sustained interaction with such frictionless AI systems may reshape the developmental conditions under which social selfhood forms and is maintained. Drawing on Cooley's (1902) looking glass self, Kohut's (1971) concept of optimal frustration, and the developmental literature on social competence, the article argues that frictionless AI may distort the social mirror through which identity forms, remove the manageable frustration that appears necessary for psychological growth, weaken empathic capacity, and erode the social stakes that …

Decision Support System For The Selection Of Thumbprint Recognition Algorithms In Biometric Security Systems, Toqeer Jameel, Muhammad Riaz

Neutrosophic Systems with Applications

This study investigates fingerprint recognition in immigration operations, emphasizing the role of biometric verification in enhancing security, fairness, and operational efficiency in international mobility. To address the uncertainty, vagueness, and imprecision inherent in fingerprint identification, a novel decision-making framework is proposed by integrating interval-valued picture fuzzy (IVPF) information. Fairly aggregation operators are introduced to combine decision makers' evaluations, while extracted fingerprint features are modeled using positive, neutral, and negative membership degrees within the IVPF environment. Objective criterion weights are determined using the criteria importance through intercriteria correlation (CRITIC) method, and individual ranking is performed via the alternative ranking order method …

A Data-Driven Neutrosophic Multi-Criteria Intelligent System For Functional Disability Severity Assessment, Ehab Abdel Aziz Al-Beblawi, Mirna Samy, Abduallah Gamal

Neutrosophic Systems with Applications

Functional disability assessment is a multidimensional problem because individuals may experience different levels of difficulty across daily activities such as walking, standing, dressing, eating, grasping objects, and social participation. This paper proposes NIFDA, a data-driven neutrosophic multi-criteria intelligent system for functional disability severity assessment. The proposed framework represents each functional response through three components: confirmed limitation, indeterminacy, and preserved functional ability. This allows the model to handle valid responses, uncertain information, and missing or non-informative data without forcing them into a single crisp score. To reduce dependence on subjective expert weighting, NIFDA derives criterion weights objectively using a hybrid CRITIC–MEREC …

Thermal Displacement Quantification And Dynamic Disparity Compensation For Automotive Stereo Cameras, Bisheng Wang, Xiyuan Hu, Ran Meng, An Jiang

Journal of System Simulation

Abstract: This paper presents a full-field thermal displacement inversion and dynamic disparity compensation method to address the disparity drift issue in mass-produced automotive-grade stereo cameras induced by thermal expansion and rigid-body displacement of image sensors under wide-temperature-range operating conditions. The proposed method leverages a high-precision static speckle pattern and digital image correlation (DIC) technique to achieve quantitative characterization of the nonuniform horizontal thermal deformation fields of the left and right image sensors. On this basis, a dynamic disparity compensation model is established, integrating a temperature-dependent quadratic polynomial translation term and a radial thermal expansion correction term. Experiments were conducted by …

Vehicle Cross-Modal Trajectory Prediction Model Based On Driving Style Hypergraphs, Guozhu Cheng, Changyuan Wang, Wenzhi Wang, Yifan Zhang, Tianjun Feng

Journal of System Simulation

Abstract: To address the shortcomings of existing motorway vehicle trajectory prediction methods which overlook differences in driving styles and the future interactions between trajectories of different modes. This paper proposes a cross-modal trajectory prediction model based on a dual-hypergraph Transformer for driving styles. The method first quantifies driving styles by extracting vehicle kinematic features and calculates a similarity matrix between vehicles; it then constructs a dual-hypergraph Transformer, using a homogeneous hypergraph to model the group interactions of vehicles with similar driving styles, and a heterogeneous hypergraph to capture the interaction relationships between spatially neighbouring but stylistically dissimilar vehicles; Finally, a …

Long-Tail Object Detection Method In Transportation Scene Images Based On Improved Rt-Detr, Mingjun Deng, Peihua Nie, Junhua Guo, Ningbo Gao

Journal of System Simulation

Abstract: Detecting rare objects in transportation environments is crucial for the safety and reliability of autonomous driving systems. To address the challenges of limited detection capability on rare objects that appear only a few times during training, we propose an improved long-tailed object detection method for traffic scene images named TF-DETR (tail free DETR) based on RT-DETR model. First, the lightweight CSP-EDA (CSP-efficient depthwise aggregation) was constructed to reconstruct the backbone network. Its core unit, the efficient depthwise aggregation, integrated the pooled-transpose attention and convolutional gated linear unit to enhance feature representations for tail-class samples. Second, the spatially-adaptive dynamic cognitive …