Digital Commons Network^™

Development And Experimental Validation Of A Non-Invasive Blood Group Detection System, Nurath K. Nurudini

Tanzania Journal of Engineering and Technology (TJET)

An individual's blood group consists of red blood cell antigens whose composition is determined by protein presence, antigen structure, and gene series. Persons aged above six months have significant anti-A and/or anti-B in their serum. During transplantation and transfusion, ABO blood group identification is the most essential factor. The conventional method involves drawing blood samples from patients, and the blood group is determined based on the antigen-antibody reaction. This method consists of adding chemical reagents. However, this requires time of operation, and throughput analysis is high, and the process is also challenging to interpret. Accurate and rapid identification of blood …

Towards Effective Academia-Industry Collaborations: The Case Of Higher Learning Institutions In Tanzania, Fatuma S. Ikuja

Tanzania Journal of Engineering and Technology (TJET)

Industries are the main consumers of products from higher learning institutions (HLIs); graduates for employment and research outputs for socio-economic development. Research outputs from HLIs are commercialized as services or products facilitated by academia-industry collaborations. The collaborations are expected to address mismatch between labour market needs and HLIs’ products, which has resulted in graduates’ employability challenges. Despite their importance, effective academia-industry collaborations remain challenging. This study explores the effectiveness of Academia-Industry collaborations established by HLIs in implementing the Higher Education Economic Transformation (HEET) project (2021-2026) in Tanzania. One of the project objectives is to build functional linkages between industry and …

The Impacts Of Renewable Energy Sources: A Review On Grid Inertia And Frequency Regulation, Sospeter Gabriel

Tanzania Journal of Engineering and Technology (TJET)

The power system is gradually transitioning into low inertia due to integrating substantial intermittency quantity of converter-based renewable energy sources, such as wind and photovoltaic power, into the current power grid network. This integration presents significant inertia and frequency control challenges to the network as a result of a decrease in the percentage of synchronous generators. Moreover, faster frequency deviations are posed by the mismatch between the supply and demand during contingencies, which creates difficulties in preserving the frequency stability of the power system. This research explores the impacts of renewable energy sources (RESs) on grid inertia and frequency management …

Calibration Of Measurement Tools In The Experimental Test Rig For Hydropower Performance Evaluation, Ombeni J. Mdee

Tanzania Journal of Engineering and Technology (TJET)

The demonstration of a typical hydropower plant requires the development of a test rig with the installation of tools to measure the performance parameters. The measurement tools require a calibration process to improve the quality of recorded data. This study involved the calibration of traditional and automated measurement tools connected to the hydropower test rig through an Arduino microprocessor. The automated measurement tools included a pressure transducer, flow meter, digital tachometer, and torque transducer, while traditional measurement tools, including a pressure gauge, concrete water tank, contact tachometer, and force lever arm balance, were connected in the same test rig during …

Review On Gas-To-Liquids Conversion Technology: Lessons From Case Studies And Potential Strategies For Implementation In Tanzania, Joseph H. Kihedu

Tanzania Journal of Engineering and Technology (TJET)

This review paper explores the transformative potential of Gas-to- Liquids (GTL) technology for harnessing Tanzania's vast natural gas resources. With significant discoveries of natural gas reserves totalling up to 57 Tcf in fields such as Songosongo, Mnazi Bay, Block 1, 2, 3 and 4. Tanzania is positioned to leverage GTL technology to convert these resources into high-value liquid fuels like gasoline, diesel and naphtha. Review of GTL process, its products and applications has been done. By analysing successful GTL projects globally and drawing lessons applicable to Tanzania, this paper provides strategic recommendations for policymakers and stakeholders to foster GTL development. …

A Review Of Lithium-Ion Battery Capacity Fade Deceleration At Power Fluctuations In Renewable Energy Systems, Isaac Gwayi

Tanzania Journal of Engineering and Technology (TJET)

Application of lithium-ion (Li-ion) batteries to store energy in renewable energy systems (RESs) is increasing due to their promising properties. Therefore, it is crucial to understand aging behaviours of Li-ion battery during RES life time as this directly affects cost of energy. Li-ion battery aging can be categorised into calendar aging and cycle aging. Calendar aging depends mainly on temperature and state of charge (SoC). In addition to temperature and SoC, cycle aging depends also on charge and discharge current rates and cut-off voltages. Higher current rates lead to faster Li-ion battery aging. It is necessary to identify appropriate battery …

Advancements In Refreshable Braille Display Technology: A Comprehensive Survey, Maryam Etezad, Rajeev Joshi, Franceli L. Cibrian

Engineering Faculty Articles and Research

This paper provides a comprehensive mapping literature review of the advancements in refreshable Braille display (RBD) technology, which employs dynamically movable pins or dots to render Braille characters for individuals with blindness and visual impairment. This literature review, which includes 96 papers, aims to summarize the current evidence on six distinct types of RBDs: piezoelectric, electromagnetic, electroactive polymer (EAP), pneumatic, shape memory alloy (SMA), and microfluidic technologies. For each type, we discuss the underlying mechanisms, alongside the current trends and research opportunities. This comparative analysis aims to inform the selection of appropriate RBD technology based on specific user needs and …

Optimisation Of Astatic Controllers In Automatic Control Systems, Isamiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Chemical Technology, Control and Management

This article examines the influence of various factors on the efficiency of optimizing station controllers in automatic control systems. The main focus is on minimizing static errors and improving the reliability of controllers. Optimization methods for PID and PI²D controllers are discussed, including the use of modern approaches such as genetic algorithms. The necessity of compromise solutions to achieve high-quality system responses to various impacts is investigated. It was also suggested that there is a need for an integrated approach to setting up controllers in order to increase their reliability and flexibility in conditions of dynamically changing processes. …

The Dynamics Of Word-Of-Mouth Marketing: An Agent-Based Modeling Approach To Message Credibility And Consumer Engagement, Ali Nasirzonouzi, Carlos Gershenson

Northeast Journal of Complex Systems (NEJCS)

Word-of-mouth (WOM) marketing is a critical factor in the dissemination of information and adoption of products in social networks. This paper investigates the impact of two important factors message credibility and consumer engagement on WOM adoption dynamics using agent-based modeling (ABM). This study proposes a simple qualitative model to investigate how these factors influence adoption rates through both broadcast communication and peer-to-peer influence by simulating interactions on a spatially clustered network.

The findings show that increased message credibility significantly boosts adoption, achieving a balance between broadcast and social mechanisms. Also, consumer engagement primarily affects the adoption mechanism, shifting the effect …

A Yolo-Based Deep Learning Approach For Vibration-Based Rotating Shaft Imbalance Detection, Abdelhameed Zayed Dr., Ali Siam Dr.

Journal of Engineering Research

One of the prevailing causes of vibrations in machines is rotor imbalance. Rotor balancing can be used to fix the majority of rotating machinery issues. When it comes to high-speed running equipment, even a slight imbalance can lead to serious issues and decrease the operational efficiency of rotating machinery. This work proposed a deep learning approach for the detection of binary and multiclass imbalance in rotating shafts. A YOLOv11 model-based approach is developed to detect imbalance and identify unbalanced rotor positions. To precisely identify unbalanced positions, this method trains the YOLOv11 model using numerous sets of measured response data and …

Impact Of Gamma-Ray Dose On Indoor Visible Light Communication Link Performance: A Geant4 Study, Fayza Mohamed Elamrawy, Adel Mohamed Ismail, Hossm Kasem Prof, Salah Khamis Prof, Ahmed Abdelaziz Youssef Prof

Journal of Engineering Research

This research presents an extended performance analysis of an indoor Visible Light Communication (VLC) system by integrating experimental results with advanced GEANT4 simulations. Building on a prior empirical study that evaluated different LED configurations and photodetectors, this work explores critical environmental and spatial parameters that influence VLC efficiency and reliability. Parameters such as wall reflectivity, emission angles, photon energy, and photon travel time are systematically analyzed using a validated GEANT4 simulation framework. The results confirm the strong impact of narrow emission angles and high wall reflectivity on detection performance, while also highlighting the importance of time delay modeling in high-fidelity …

Multi-Modal Covid-19 Detection Using Cough Sounds And Medical Information With Attention-Enhanced Deep Learning, Mohamed Talaat Saidahmed, Reda Elbasiony, Marwa Reda Bastwesy, Asmaa Aly Hagar

Journal of Engineering Research

The COVID-19 pandemic has highlighted the need for fast, non-invasive, and cost-effective diagnostic tools. Cough sounds, as a prominent symptom of respiratory diseases, present a promising modality for automated COVID-19 detection. In this study, we propose a novel multi-modal deep learning framework for COVID-19 detection that leverages cough sounds and patient-specific medical information. Our approach extracts two types of acoustic features—Mel-Frequency Cepstral Coefficients (MFCCs) and Mel spectrograms—and integrates them with clinical metadata to improve diagnostic ac-curacy. The MFCC branch employs 1D convolutional layers followed by Efficient Channel Attention mechanism. The Mel spectrogram branch utilizes ResNet-50 combined with ECA to capture …

Mutual Coupling Impedance Effect On Ris-Assisted Terahertz Communication, Radwa A. Roshdy Dr., Hossam M. Kasem Prof., Mohammed A. Salem Dr.

Journal of Engineering Research

Terahertz (THz) communication based on reconfigurable intelligent surfaces (RIS) is a promising technology in future wireless networks, with the capabilities of ultra-high data rates and energy-efficient beam communicating. Nevertheless, the mutual coupling impedance of the closely spaced RIS reveals the inefficacy in existing channel estimation schemes, while it is usually ignored in the literature. In this paper, we fill this gap by developing an EM-compliant channel model that integrates mutual coupling explicitly for RIS-assisted THz systems. We evaluate the performance of mutual impedance-induced influence to the accuracy of the root mean square error (RMSE), which is considered as a pivotal …

Performance Enhancement Of Ev Drive System Under Open-Phase Fault Using Reinforcement Learning With Mpc, Ahmed M. Hassan, Mohammed E. Metwally Dr.

Journal of Engineering Research

Improving the operation of electric vehicles (EVs) under fault is a very important subject because it increases their ability to operate in case of an emergency. This paper proposes a fault-tolerant control methodology for an EV drive system under open phase fault (OPF). The 5-ph interior permanent magnet synchronous motor (IPMSM) is employed in the drive system because it has several merits, such as high efficiency and reliability. The proposed technique is based on utilizing a reinforcement learning (RL) control algorithm, based twin-delayed deep deterministic policy gradient (TD3) algorithm, to operate the motor at maximum torque per ampere under OPF. …

Dynamic Resource Allocation For Wireless Networks And Radar Systems Via Deep Reinforcement Learning, Ziyang Lu

Dissertations - ALL

The rapid advancement of wireless communication technologies and the proliferation of smart devices have led to increasingly complex and dynamic network environments. These developments have posed significant challenges to traditional radio resource management (RRM) techniques, which often struggle with scalability, adaptability, and real-time decision-making. In response to these limitations, this dissertation explores the application of advanced machine learning, particularly deep reinforcement learning (DRL), to develop intelligent, adaptive, and data-efficient solutions for resource management in wireless networks and radar systems. We begin by addressing joint channel access and power control in wireless interference networks using centralized, distributed, and federated multi-agent DRL …

Grid Fragility, Blackouts, And Control Co-Design Solutions, Mario Garcia-Sanz

Faculty Scholarship

The grid is undergoing a large-scale transformation, including a significant reduction of synchronous generators, a high penetration of inverter-based resources and renewables, substantial demand growth, new extra-large loads, aging infrastructure and a concerning vulnerability to contingencies. Some of the recent massive blackouts in Spain/Portugal, Chile and Texas are exposing the fragility of the grid as we know it today. This paper introduces new solutions to stabilize the grid under undesired dynamic interactions and extreme contingencies, with the goal of avoiding cascading failures and blackouts. Using control co-design methodologies, the paper proposes three interdependent categories to improve the reliability and controllability …

Ai-Driven Emi Mitigation For Smart Healthcare: Generative Adversarial Networks And Edge Computing For Reliable Medical Systems, Mona Esmaeili

Electrical and Computer Engineering ETDs

Electromagnetic interference (EMI) from radio frequency (RF) sources poses a major challenge to digital systems, especially in high-electromagnetic environments. Tradi- tional electromagnetic compatibility (EMC) analysis often focuses on continuous wave (CW) interference and overlooks the effects of waveform modulation on EMI coupling. This thesis explores how modulated waveforms influence EMI coupling and introduces a Generative Adversarial Network (GAN)-based classification framework to distinguish between harmful and non-harmful EMI signals. The study extends conventional EMC analysis using machine learning (ML), showing that modulated EMI waveforms can in- crease coupling by up to 27% compared to CW signals. This highlights the need for …

The Evolution Of Global Gold And Copper Trade Networks, Oleksandr Hulianskyi

Northeast Journal of Complex Systems (NEJCS)

Gold and copper have emerged as two of the most vital commodities in global trade. Despite serving distinct purposes, their international trade networks reveal interconnected patterns, critical to understanding the dynamics of global economics. This paper studies these attributes and their evolution during the last 36 years for both metals and finds correlations between them. The first part of the research is focused on the sustainability of networks through efficiency and robustness indexes; the second part is dedicated to interconnectedness – the Louvain and Bayesian SBM algorithms, partition, and modularity instruments are used. Community detection algorithms provide valuable insights into …

Exploring The Potential Of Large Language Models (Llms) To Simulate Social Group Dynamics: A Case Study Using The Board Game "Secret Hitler", Kaj Hansteen Izora, Christof Teuscher

Northeast Journal of Complex Systems (NEJCS)

This study explores the capacity of large language model-powered agents to simulate human-like behavior in multi-agent social systems. Using Secret Hitler — a hidden-role board game centered on trust, deception, and strategic communication — we evaluate how LLM agents navigate dynamic group interactions. Our findings show that agents exhibit human-like behaviors, including strategic temporal adaptation, contextual reasoning, and complex social cognition such as theory of mind and implicit coordination. Notably, 85% of agent decisions factored in at least two other players’ mental states, highlighting their capacity for multi-agent mental state inference. However, they struggled with key aspects of human gameplay, …

Replicating Associative Learning Of Rodents With A Neuromorphic Robot In An Open-Field Arena, Tianze Liu, Kang Jun Bai, Hongyu An

Michigan Tech Publications

This study emulates associative learning in rodents by using a neuromorphic robot navigating an open-field arena. The goal is to investigate how biologically inspired neural models can reproduce animal-like learning behaviors in real-world robotic systems. We constructed a neuromorphic robot by deploying computational models of spatial and sensory neurons onto a mobile platform. Different coding schemes—rate coding for vibration signals and population coding for visual signals—were implemented. The associative learning model employs 19 spiking neurons and follows Hebbian plasticity principles to associate visual cues with favorable or unfavorable locations. Our robot successfully replicated classical rodent associative learning behavior by memorizing …

Development Of A Near Terahertz Backward Wave Oscillator Using Standard Waveguide, Alexander Glick

Electrical and Computer Engineering ETDs

There is a demand for terahertz (THz) frequency radiation sources. Applications include, but are not limited to, imaging for medical and security purposes, biochemical and organic spectroscopy, and velocimetry. Historically, there was a limited supply of THz devices due to technological limitations. In recent years much progress has been made to reduce this “gap” in supply and demand for THz sources. This work proposes a vacuum electronic device that produces high power, extremely high frequency radiation in the G-band, by utilizing a backward wave oscillator (BWO) based on WR3 standard waveguide. This device is compact, fundamentally simple, and has great …

Networking For Power Grid And Smart Grid Communications: Structures, Security Issues, And Features, Biswash Basnet, Varsha Sen

Graduate Student Scholarship

The evolution from traditional to smart grid systems has radically changed communication architectures. It enables secure, efficient, and resilient energy infrastructures. Unlike the centralized, unidirectional communication practices typical of traditional grids with minimal automation, modern smart grids use tiered, bidirectional networks allowing real-time control, integration of distributed energy resources (DER), and active consumer participation. The drive for this development arises from the growing use of renewable energy resources, electric vehicles, and sophisticated digital metering technologies. End-to-end communication architectures now underpin grid reliability, interoperability, and cybersecurity. This research explores the end-to-end architecture of traditional and smart grids, including access technologies, protocol …

How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael

Dartmouth College Ph.D Dissertations

September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …

Development Of An Embedded Iot Board For Real-Time Floor Estimation Of Autonomous Robots, Carter J. Sorensen

Electronic Theses and Dissertations

As service robots become more prevalent in multi-story environments such as hospitals, hotels, and laboratories, accurate floor-level detection is critical to ensuring operational reliability. Consider a robot tasked with delivering medical samples in a multi-story laboratory. Without accurate feedback, a robot exiting on the wrong floor could introduce delays, disrupt workflows, or compromise sample integrity. Internet of Things (IoT) technologies offer a way to address these risks by providing real-time error detection and corrective capability. However, current IoT-based floor estimation systems often require invasive modifications to building infrastructure—particularly elevator control panels. These approaches introduce challenges related to cost, liability, backward …

An Advanced Hexacopter For Autonomous Exploration Of Mars: Attitude Control And Navigation Strategies, Laura Sopegno

Electronic Theses and Dissertations

Mars exploration has recently witnessed major interest within the scientific community. Unmanned robotic platforms offer reliable solutions to acquire and collect data and information from the Red Planet. Particularly, rovers, landers, and orbiters have significantly shaped planetary exploration on the Moon and Mars, contributing significantly to past missions while also highlighting limitations in their capacity to cover diverse terrains over wide ranges. Given current advances in Unmanned Aircraft Systems (UASs), Unmanned Aerial Vehicles (UAVs) offer promising alternatives for future scientific missions.

It is argued that hexacopters, with their relatively compact design and redundancy, present a promising …

Piloted Autonomous Crisis Reconnaissance Robot 2.0 (Pacrr 2.0), Awawu Alimi, Urmika Ghosh, Marissa Kuo, Jonathan Santosa, Ethan Wyrick

Electrical and Computer Engineering Senior Theses

PACRR 2.0 (Piloted Autonomous Crisis Reconnaissance Robot, version 2) builds upon the original low-cost, autonomous-capable quadruped platform by enhancing both mobility and environmental perception for first-responder applications such as search and rescue, gas leak detection, and mapping of confined or hazardous areas. In PACRR 2.0, we integrate an RGB-D camera with analytic inverse kinematics and frame-based motion planning to achieve precise foot placement and stable quasi-static gaits even on sloped or uneven terrain. An NVIDIA Jetson processor runs high-level control and mapping alongside a Raspberry Pi 4 to manage motor control. Through simulation, we demonstrate robust 3D map generation and …

Online Hyperparameter Tuning For Llm Optimization, Ethan Lin, Nathan Yu, Jeromy Chang

Computer Science and Engineering Senior Theses

Large Language Models (LLMs) are becoming increasingly popular in modern society. However, despite their popularity, the deployment of LLMs in real-world scenarios is extremely challenging due to substantial computational costs and memory constraints. Edge devices, like smartphones and IoT devices, lack resources needed to run these models locally, instead offloading computations for cloud computing. Cloud computing requires users to send their data over the internet leading to numerous privacy and security concerns. In some domains, such as health and finances, sending such sensitive information is not an option. Existing solutions to compress or increase inference speed include Small Language Models …

Measurement Of Moisture Levels In Oils And Lubricants Using A Novel Moisture Sensor, Aaron Swartz, Ronak Ali

Electrical and Computer Engineering Graduate Research

It is very challenging to measure moisture levels in oils. There is not a good method to measure it. Using the novel moisture sensor invented by Dr. Zhi David Chen, we tried various methods to measure the moisture levels in oils. The initial trials are to immerse the sensor chip into the oils to see any sensor reading changes with the change of moisture levels in oils. It was observed that the sensor reading was unstable even after immersion into the oil for two weeks. The idea for immersion of the sensor chip into the oils failed due to the …

Resilience Oriented Dynamic Bayesian Network For Time Dependent Power Distribution System During Hurricanes, Kehkashan Fatima

Thesis/ Dissertation Defenses

In this dissertation, the overhead line failure due to extreme winds was investigated. The objective of the overhead line failure analysis was to evaluate the failure probability of line due to hurricane. The standard IEEE 33 bus test system was utilized to analyze the impact of hurricane wind speed intensity at distinct time and location on the grid. The test system was divided into four regions based on the number of buses and hurricane category (according to Saffire Simpson Hurricane Wind Scale). Regions 1, 2, and 3 cover 8 buses while region 4 covers 9 buses. Regions 1, 2, 3, …

Llm Music Creation And Recommendation Applications, Curtis Robinson, Allan Yang, Thomas Liu

Electrical and Computer Engineering Senior Theses

This thesis explores the application of large language models (LLMs) in music analysis, creation, and interaction, focusing on their potential to reshape traditional workflows in the music domain. The study begins by contextualizing the role of artificial intelligence in music technology, particularly emphasizing the emergence of LLMs like GPT and their unique capabilities in multimodal and musical contexts. A comprehensive survey of current research and toolsets highlights both creative and analytical implementations, ranging from text-based music generation to music information retrieval. The core contribution is an experimental framework that integrates LLMs with music processing libraries, enabling novel interactions such as …