Digital Commons Network^™

Techno-Economic Analysis Of Captive Solar Power Systems For Tanzania’S Manufacturing Sector: Barriers, Opportunities, And Feasibility, Edson Uhale, Sarah P. Ayeng'o

Tanzania Journal of Engineering and Technology (TJET)

This study provides a comprehensive techno-economic analysis of the barriers, opportunities, and feasibility of adopting captive solar photovoltaic (PV) systems in Tanzania’s industrial manufacturing sector. Despite Tanzania’s high solar irradiation potential, averaging 4.5 to 7.0 kWh/m²/day, the uptake of captive solar systems remains minimal, with only 2.3 percent of surveyed firms currently using solar energy, primarily for non-productive uses such as security lighting. Using a mixed-methods approach, data were collected from 43 manufacturing firms in the Dar es Salaam and Pwani regions through structured questionnaires, supported by PVSyst simulations and financial modelling to assess two system configurations: grid-connected PV systems …

A Proposed Urban Branding Strategy As Sustainable Urban Regeneration Policy, A Case Study Of Burj-Al Burullus City, Dalia S. Shebl, Kariman A. Shawky

Mansoura Engineering Journal

This study examines the importance of a branding strategy that can be applied in Burj Al-Burullus city to promote and catalyze cultural heritage branding and invest in these facilities for economic and tourism purposes. By measuring the indicators of how urban branding may be achieved. Burj Al-Burullus city is empirically examined using Identity-Based Approach. Based on profound theoretical and analytical studies, the branding concept was studied and analyzed composing a list of indicators for tangible and intangible elements that illustrate the urban branding value of cities. Followed by an analysis of Burj Al-Burullus city using GIS and city data base …

Towards Computational Methods In Medical Data Analysis: From Speech And Text To Imaging, Kristin Qi

Graduate Doctoral Dissertations

Early detection of cognitive decline and efficient medical image analysis remain critical challenges in healthcare. Traditional clinical assessments are infrequent and resource-intensive, while everyday speech data and unlabeled medical images remain largely unexploited. This dissertation develops computational methods integrating machine learning and artificial intelligence across speech, text, and imaging modalities to address challenges in medical data processing. For cognitive monitoring, this work first introduces methods using voice assistant systems to collect longitudinal speech data in home environments, demonstrating that incorporating historical session patterns significantly enhances detection of mild cognitive impairment. Building on this foundation, a framework combining large language model-driven …

Electrochemical Characterization And Modulation Of Biological Processes, Yue-Qi Li, Wei-Hua Huang, De-Chen Jiang, Bao-Hong Liu, Bin Su, Yang Tian, Jing-Juan Xu, Ping Yu, Feng Zhao, Huang-Xian Ju, Jing-Hong Li

Journal of Electrochemistry

Electrochemical processes lie at the core of biological function, governing energy transduction, metabolic flux, and molecular signaling. Recent advances in electrochemical science now allow these processes to be probed and controlled with unprecedented spatial, temporal, and chemical resolution. In this review, we present an integrated framework that progresses from fundamental mechanisms to analytical technologies and functional modulation. We begin by outlining electron transfer pathways in mitochondrial respiration, microbial extracellular electron transfer, and DNA- and protein-based charge conduction, followed by the principles of photon-electron conversion in photosynthesis and the central role of redox equilibrium in coordinating cellular responses. We then highlight …

Empirical Analysis Of Machine Learning Models For Predicting Equipment Failures Using Iot Sensor Data, Yusuf Shodiyevich Avazov

Chemical Technology, Control and Management

This article examines the problem of detecting and predicting industrial equipment faults using IoT sensor data through machine learning techniques. Sensor readings such as temperature, vibration, pressure, voltage, and current, as well as FFT-based features, were statistically analyzed. Class imbalance and low signal informativeness were identified as key factors limiting model accuracy. Results obtained from Logistic Regression, Random Forest, and XGBoost models were comparatively evaluated, showing that when ROC-AUC values remain around 0.5, distinguishing fault and non-fault states becomes challenging. Correlation and feature-importance analyses confirmed the absence of strong dominant indicators. The findings highlight the need to improve sensor architecture …

Using Machine Learning To Predict Women At Risk Having A Child With Congenital Heart Defects, Amany M. Abdo Prof., Asmaa M. Mosallam Ms., Laila M. Abdelhamid Assoc.Prof.

Information Systems

Congenital heart defects (CHD) are heart malformations present at birth, affecting heart function and circulation, and are a leading cause of infant mortality. CHD can result from genetic, environmental, and maternal health factors, making early detection essential. Early diagnosis allows for timely intervention, reducing risks like heart failure or stroke. In countries like Egypt, CHD often remains undiagnosed due to limited healthcare resources. Artificial intelligence (AI) can improve early detection by analyzing risk factors. This study presents a predictive model for CHD using maternal and paternal health factors. Data was collected from 571 families: 260 with a CHD-affected child and …

Comprehensive Mechatronic Design Methodology For 6-Dof Stationary Lower Limb Rehabilitation Exoskeleton Robot With Safety-Integrated Control Architecture, Javlonbek Rakhmatillaev Mr., Nodirbek Kimsanboyev Mr., Umidjon Takabaev Mr., Zafar Juraev3 Dr.

Chemical Technology, Control and Management

This paper presents the mechatronic design of a proposed six-degree-of-freedom (6-DOF) stationary lower limb rehabilitation exoskeleton (SLLRE) robot, developed through a comprehensive mechatronic design methodology that includes mechanical design, actuator and sensor selection, and the development of a control structure based on a safety-oriented control approach. The proposed 6-DOF SLLRE mechanical design introduces a comprehensive mechanical structure comprising bilateral hip, knee, and ankle joints, degrees of freedom, joint ranges of motion, human parameters for rehabilitation training, as well as the frames and structural elements of the proposed system. Furthermore, the selection of appropriate sensors, actuators, and control architecture for the …

Development And Evaluation Of A Smart Vacuum-Assisted Suspension System For Transtibial Prostheses, Zahraa Kathem Ali, Wajdi Sadik Aboud

Al-Bahir

A prosthetic socket is essential for achieving comfort, gait symmetry, and overall satisfaction for amputees. Effective suspension systems are crucial for securely attaching prostheses, thereby optimizing comfort, functional performance, and long-term limb health. This study aimed to develop and evaluate an intelligent vacuum-assisted suspension system for transtibial prostheses to improve socket fit, gait stability, and reduce residual limb movement. The system integrates force-sensitive resistors (FSRs) and an inertial measurement unit (MPU6050) with accelerometer and gyroscope sensors, continuously monitoring interface pressure and limb motion. Real-time data from these sensors dynamically adjusts vacuum pressure based on the user's gait pattern .Quantitative gait …

Folding Architecture “Origami Art-Inspired” Applicability To Sustainable Architecture- Biomuseo As A Case Study, Vitta A. Ibrahim

Mansoura Engineering Journal

The growing need for sustainable architectural solutions in the contemporary era underscores the necessity for interactive architectural applications that can adapt to changing requirements. In architecture, folding systems refer to three-dimensional, foldable structural forms that create unique spatial configurations and possess a wide range of capabilities. Drawing inspiration from origami techniques, this study emphasizes the role of folding systems in generating innovative spatial designs. The research problem arises from the fact that the built environment is a significant contributor to greenhouse gas emissions and energy consumption, necessitating the implementation of smart solutions. The goal of this study is to identify …

Developing A Vietnamese Text Summarization Large Language Model On Limited Hardware, Tin Pho

Master's Theses

Text summarization models have achieved significant growth during the last few years because of major Large Language Model (LLM) technological advancements. The application of LLMs are widely used in news distribution (TL;DR news), translation tools (DeepL Translate), or virtual assistants (ChatGPT, DeepSeek, Claude, etc.). However, the progress has not yet reached all languages equally. The Vietnamese language is used by more than 90 million people, but the language is not as highly developed for LLM as it has many homophones, five different tones that affect meaning of words, and irregular grammar compared to other languages (e.g. English, Spanish, etc.). Also, …

Supply Chain Network Based On Blockchain And Intelligent Agent, Hiba Hamdi Hassan, Rana Fareed Ghani

Journal of Soft Computing and Computer Applications

In agricultural supply chains, the complexity and indeterminacy pose serious challenges to traceability, reliability and confidence today. This challenge is especially acute in the olive oil industry where adulteration, wrong labeling, and uneven chemical quality threaten the actual well-being of producers and consumers. The project aims to design a blockchain-based hybrid architecture with intelligent agents (FNNs) to enhance transparency, reliability and responsiveness in the olive oil supply chain. The Blockchain component enables a completely open, tamper-proof ledger to be built in a very decentralized way and preserved as an archive of every account of its transactions. The intelligent agents contribute …

Mechanisms Underlying Sodium Enrichment In Coals In The Dananhu Mining Area, Turpan-Hami Basin, Qi Zhenghui, Sun Fanxing, Wang Wenlong, Huang Chunhui, Liang Kaihua, Huang Yangyang, Shao Longyi

Coal Geology & Exploration

Background The Dananhu mining area boasts abundant coal resources, serving as a significant coal-fired power generation base in Xinjiang, China. However, the high sodium (Na) content in coals within the mining area tends to cause fouling and slagging during coal combustion, severely affecting the clean and efficient utilization of coal resources in the area. Methods and Results epresentative samples collected from the major mineable coal seams were subjected to proximate and ash-composition analyses. The analytical results show that the coal samples had low ash and sulfur contents and high volatile content. SiO₂ predominated in the ash components, followed by …

Efektivitas Dan Keberterimaan Madcom Noise Protection Sebagai Alat Pelindung Pendengaran Berbasis Perlindungan Ganda, Ahmad Athif Wahyu Ramadhan, Yamtana Yamtana, Naris Dyah Prasetyawati, Sigid Sudaryanto

National Journal of Occupational Health and Safety

Industrial environments often generate high noise levels due to the continuous operation of machinery and production equipment. Persistent exposure to workplace noise exceeding the Threshold Limit Value (TLV) can lead to noise-induced hearing loss. According to the World Health Organization, an estimated 430 million people worldwide require rehabilitation for hearing impairment, with 109.4 million of these cases occurring in Southeast and Central Asia. As a critical component of Occupational Health and Safety (OHS) management, noise control is often implemented using Hearing Protection Devices (HPDs). This study aims to evaluate the effectiveness of an earplug-earmuff combination, developed as Madcom Noise Protection, …

Construction And Application Of Knowledge Graph For Quality Management In Bridge Pile Engineering, Fang Xiaofeng, Dong Runhao, Gu Yanke, Pan Yanran

Journal of China & Foreign Highway

To enhance the efficiency of quality management in bridge pile foundation construction,this study constructed a knowledge graph applicable to the construction field of bridge pile foundation engineering to enable systematic representation and intelligent organization of knowledge.A methodology combining top-down design and bottom-up design was adopted to develop a framework for constructing a knowledge graph for the quality management of bridge pile foundation construction that encompasses both the schema layer and the data layer.The schema layer was established through ontology modeling,clarifying the concept categories,hierarchical structure,and their attribute relationships.The data layer employed a bidirectional long short-term memory (BiLSTM ) network integrated with …

Bridge Damage Detection And Bim Localization Methods Based On Image Recognition, Li Yu, Guo Hongjun

Journal of China & Foreign Highway

To overcome insufficient information of 2D detection data in traditional bridge maintenance,which hinders precise decision-making,this study proposed an automated method based on deep learning and structure from motion (SfM ) technology,which realized the complete process from image recognition to the accurate mapping of damage information in a building information model (BIM ).First,the YOLOv 8 deep learning model was used to automatically detect bridge surface damage.Second,the SfM technology was applied for the local 3D reconstruction of the damage area and to determine the 3D coordinates of the damage.Then,the least squares method was used to align the local coordinate system with the …

Quantitative Evaluation Of Tunnel Rock Mass Integrity Based On Mwd Technology, Zhang Kunmu, Peng Hao, Liang Ming, Han Yu, Song Guanxian

Journal of China & Foreign Highway

In tunnel construction,the quantitative evaluation of rock mass integrity heavily relies on information from the exposed face,and there are challenges when drilling data is used for integrity evaluation.To this end,this study introduced a novel method for quantitative evaluation of rock mass integrity during drilling,integrating numerical statistics with machine learning.A substantial dataset of digital drilling data was collected,covering three common types of rock mass integrity:relatively intact,relatively fractured,and fractured.Subsequently,a high-performance random forest model for the classification of rock mass integrity was developed through data preprocessing and hyperparameter optimization.The interpretability of the model ’s predictive results was enhanced using Shapley additive explanations (SHAP …

Green Ai-Enhanced Deep Learning Model For Breast Cancer Detection And Classification In Mammography Images: Bc-Net-512, Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

Mansoura Engineering Journal

This study champions a sustainable approach for developing a Deep Learning (DL) model for medical image analysis, specifically focusing on breast cancer (BC) detection in mammograms. By prioritizing low-computing algorithms to achieve high diagnostic accuracy while minimizing the model's environmental footprint, that aligns with the principles of Green AI. In this paper, an innovative architecture called BC-Net-512 was constructed for the classification of BC mammography. It is composed of lightweight Convolutional Neural Network (CNN) blocks for texture, density, and structure feature extraction and detection, a thin, fully connected layer for learning complex patterns and correlations in the extracted features, and …

A Decision Support Model For Building Material And Component Reuse In The Context Of Circular Buildings, Havva Aksel

Journal of Sustainable Construction Materials and Technologies

Construction activities cause significant environmental impacts such as waste generation, pollution, resource consumption, and land use, which are expected to increase with global construction demands. To mitigate these environmental problems, the circular building occurs as an emerging concept depending on in the circular economy, which aims to minimize waste and redefine the “end-of-life” concept by reducing, reusing, recycling, and recovering materials. The reuse of building materials and components (BMCs) from existing structures represents a crucial strategy for achieving circularity in the built environment. Within this framework, design plays a key role. However, designing with reclaimed BMCs remains complex due to …

Mixed Linear Equation–Inequality Systems Over The Pura Vida Neutrosophic Algebra, Muhammad Rayyanu Abdullahi, Abdulhadi Aminu

Neutrosophic Systems with Applications

This paper proposes a neutrosophic extension of max-plus algebra for solving mixed systems of linear equations and inequalities.Classical max-plus algebra is a powerful tool for modeling synchronization in discrete-event systems LastNatpreClose LastNatClose, but it assumes fully deterministic data.To incorporate uncertainty and indeterminacy, we reformulate the framework so that coefficients and variables are expressed as neutrosophic numbers

γ+λI,γ,λ∈ℝ,I∈[0,1],

where I quantifies the degree of indeterminacy.

We redefine the max-plus semiring in this neutrosophic setting, extend solvability and uniqueness results, and adapt the ONEMLP-EI algorithm LastNatpreClose LastNatClose to handle neutrosophic …

Mapping Sustainability To Cybernetic-Generative Artificial Intelligence-Based Education: An Innovative Neutrosophic Orbifold-Lattice Methodology, Mona Mohamed, Ahmed A. Metwaly

Neutrosophic Systems with Applications

The lightning-fast development of artificial intelligence (AI), notably generative artificial intelligence (Gen AI) technologies, has intrigued multiple disciplines, particularly education. In this context, Large Language Models (LLMs) serve as beneficial cognitive resources that address knowledge deficits and provide tailored educational support for learners and staff. For learners, LLMs are regarded as knowledgeable educators who offer prompt, focused responses and rationales to tricky queries. Whereby LLMs for staff, Strength enhancer, automating tedious tasks, and creating intelligent resources.Gen AI’s rapid growth offers enormous obstacles for educational systems, compelling them to discover solutions for these obstacles.

Conceptually, cybernetics is leveraged for bridging the …

Integrated Chitosan-Based Coagulation And Microbubble Pre-Treatment For Improved Microplastic Fibre Removal From Water, Nimesha Thathsarani, Mohadeseh Najafi, Mehdi Khiadani, Muhammad Rizwan Azhar, Masoumeh Zargar

Research outputs 2022 to 2026

Microplastic fibres (MPFs) dominate treatment plant influents but are difficult to remove due to their morphology, composition and low density, limiting the effectiveness of coagulation flocculation pre-treatment. Integrating coagulation-flocculation with microbubble introduction offers a sustainable route to improve MPF removal, yet conventional inorganic coagulants often require high dosages, show strong pH dependence, and pose environmental risks. Chitosan is a biodegradable and non-toxic green alternative, but its application is limited due to its low solubility and pH sensitivity. In this study, two amphoteric derivatives of Chitosan have been successfully developed: CMC-CTA, produced by modifying carboxymethyl Chitosan (CMC) with 3-chloro-2-hydroxypropyl trimethyl ammonium …

Flood Prediction With Sentinel-1 Synthetic Aperture Radar From Hurricane Helene, Jingyu Xiao, Jessica Li

The Journal of Purdue Undergraduate Research

Floods are the most common natural disaster globally, causing thousands of deaths every year. Timely and accurate flood forecasts are crucial for developing early warning systems, evacuation plans, and effective strategies to enhance community resilience. Soil moisture is an important parameter in flood forecasting. Unfortunately, existing soil moisture sensor networks and optical remote sensing–based techniques for soil moisture estimation lack the spatial resolution needed for accurate flood forecasting. This study presents an approach for flood prediction using Sentinel-1 C-band synthetic aperture radar (SAR) data. SAR offers high spatial resolution and operates day and night under all weather conditions, making it …

Validation Of Innovative Method Of Murine Vertebral Compression Testing, Sarah Staller

The Journal of Purdue Undergraduate Research

Murine vertebral compression testing is a common technique to quantify trabecular bone biomechanics. Having a precise method of vertebral compression is important for aiding researchers in making clinically relevant discoveries in musculoskeletal research. While many methods exist in literature, there has yet to be established a universal protocol for this procedure. Many challenges exist in vertebral compression, such as the irregular shape of the vertebral body (trabecular region of interest), uneven endplate surface morphology, and surrounding cortical processes. Therefore, the aim of this study was to develop a new method of vertebral compression that accounts for these factors and to …

The Automation Of Lamp Biomolecular Assays Using The Eppendorf Epmotion™ 5075 Robotic Pipettor, Shamalaa Sathiasealan

The Journal of Purdue Undergraduate Research

Loop-mediated isothermal amplification (LAMP) is a nucleic acid amplification technique known for its specificity and efficiency in less controlled environments than laboratories. Designing novel LAMP reagents requires strict contamination control, and unlike the more commonly automated polymerase chain reaction, LAMP’s heightened sensitivity poses unique challenges to automation. To address this, we optimized automation procedures for LAMP using a robotic pipettor without altering the core assay itself. This project focuses on minimizing contamination using sealed plates, reducing operator intervention by automating pipetting, and preventing enzyme degradation using cooling plates. Our approach employs pre-slit pierceable seals and cooling blocks to prevent cross-contamination …

Implications Of Noninvasive Blood Pressure Pumps On Mean Arterial Pressure, Sammie Miller

The Journal of Purdue Undergraduate Research

Noninvasive blood pressure pumps are recommended as the primary form of acquiring patient blood pressure to test for blood poisoning. The Philips IntelliVue Patient Monitor MP5, the Philips SureSigns VS4/VS3 Vital Signs Monitor, the Philips EarlyVue VS30 Vital Signs Monitor, the Philips IntelliVue Patent Monitor MP2/X2, the Philips IntelliVue Patent Monitor MMS, and the Philips IntelliVue Patent Monitor MP3/X3 were tested for accuracy. The control condition for hypotension was 95/55 (68) mmHg, normal blood pressure was 120/80 (93) mmHg, and hypertension was 155/85 (108) mmHg. The order of values is arrayed according to diastolic, systolic, and mean arterial pressure. The …

A Parallel Interval Modeling Framework For Nonlinear Systems: Application To A Modified Duffing Oscillator, Roman Voliansky, Nina Volianska

Northeast Journal of Complex Systems (NEJCS)

The paper presents a mathematical framework for converting nonlinear dynamical systems into parallel forms. This framework replaces the exact system motion equations with interval equations, enabling the representation of nonlinear functions over piecewise linear domains. Such representation enables the description of system motions using linear-like differential equations, which can be analyzed and manipulated using well-known control methods. One such method is eigenvalue analysis, a powerful tool in classical control theory since many techniques rely on the system’s characteristic polynomial and its eigenvalues. We apply this method to define interval system eigenvalues and track their variation during system operation. These eigenvalues …

Control Techniques And Design Of Load-Side Controls For The Mitigation Of Late-Time High-Altitude Electromagnetic Pulse, Connor A. Lehman, Rush Robinett, Wayne Weaver, David G. Wilson

Michigan Tech Publications

This paper introduces a novel control archetype designed to mitigate high-altitude electromagnetic pulse (HEMP) (Formula presented.) disturbances on the power grid, as well as information on performance and specifications of different control laws for the controller archetype. This method of protection has been overlooked in the literature until now. A controlled voltage supply is placed on the load-side of a transformer, diverting unwanted power from the transformer core to prevent saturation. The controlled voltage source is modeled using four control laws: an integral controller (capacitor), Linear Quadratic Regulator (LQR), an energy storage minimized feedforward control law, and a Hamiltonian feedback …

Evaluation And Calibration Of Coupled Low-Cost Particulate Matter Sensors, Tyler Cargill

McKelvey School of Engineering Graduate Student Theses & Dissertations

Low-cost sensors (LCS), if used appropriately, are useful instruments to elucidate human exposure to particles suspended in the air (i.e. particulate matter, PM). Characterizing this exposure is crucial, as exposure to PM2.5 (i.e. particles with aerodynamic diameter ≤ 2.5 μm) negatively affects the respiratory, cardiovascular, and other organ systems and is the leading environmental burden for global mortality. Similarly, exposure to particles with aerodynamic diameters greater than 2.5 μm and less than or equal to 10 μm, here forth termed as PMCoarse, is known to cause health ailments for the upper respiratory system. This dissertation focuses on the MODULAIRTM-PM (MOD-PM), …

Optimal Sizing Of Battery Energy Storage Systems For Peak Shaving And Demand Response Using A Degradation-Aware Bayesian Optimization-Mixed-Integer Linear Programming Framework, Jiwei Yao, Blake Billings, Tao Gao, John Hedengren, Kody M. Powell

Faculty Publications

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction …

An Integrated Multivariate Econometric Modeling Framework For Risky Driving Behavior Related Crashes: Evaluating Crash Risk And Severity Across Zones, Pabitra Kumar Roy

Dissertations and Theses

Rapid advancements in crash modeling have yet to fully integrate multiple behavior-driven crash types and their severity outcomes within a single, scalable framework, specially in a way that captures the sequential nature of these behaviors where one risky action may amplify another. This study proposed an integrated multivariate econometric framework to jointly model crash frequency and severity outcomes for three major behaviorally driven crash types: alcohol-related, distraction-related, and aggressive-driving-related crashes. Specifically, using Oregon's 2022 census block group-level crash data, we propose an Integrated Multivariate Negative Binomial – Generalized Ordered Probit Fractional Split (IMNB–GOPFS) model to analyze these dimensions simultaneously while …