Engineering Commons^™

Spin Coater Design With Pid Algorithm Using Polynomial Regression Approach And Bias Tuning For Tio2 Deposition Process, Geo Surya Andika, Nofrijon Sofyan, Donanta Dhaneswara, Akhmad Herman Yuwono

Journal of Materials Exploration and Findings

The thin-film deposition technique using spin coating offers a cost-effective alternative to Chemical Vapor Deposition (CVD) and Physical Vapor Deposition (PVD). The spin-coating process requires precise control of the motor drive system to ensure that the rotational speed, measured in rotations per minute (RPM), aligns with the set point and remains stable. This study presents the design and development of a spin coater prototype to achieve uniform thin-film deposition. The control method employed utilizes a Proportional-Integral-Derivative (PID) algorithm, incorporating a polynomial approach with bias tuning. The PID control was chosen to achieve stable operation in a non-linear system. The performance …

An Msbe–Driven Advanced Air Mobility Post–Disaster Response System, Olabode A. Olanipekun

Graduate Theses and Dissertations (2019 - present)

In this work, an overarching conceptual design model towards the realization of a proposed Advanced Air Mobility Post–Disaster Response System (AAMPDR system) was explored through the focal lenses of systems thinking (ST), socio–technical systems (STS) and model–based systems engineering (MBSE) paradigms. Initially aimed at providing intervention for casualties and aerial support to emergency rescue workers on the ground in the event of a hurricane disaster around the Gulf shore of the Mobile bay area, Mobile city, AL., the scope of this research subsequently expanded to include a global outlook. Thereafter, culminating in the development of a generalized AAMPDR system model …

Decision Space Decomposition For Multiobjective Programs, Emma Soriano

All Dissertations

Being inspired by the parametric decomposition theorem for multiobjective optimization problems (MOPs) of Cuenca and Miguel (2017), and by the block- coordinate descent for single objective optimization problems, we present a decom- position theorem for computing the set of minimal elements of a partially ordered set. This set is decomposed into subsets whose minimal elements are used to retrieve the overall minimal elements. We apply this approach to strictly convex MOPs de- composing their decision space into lines. The line decomposition benefits from the fact that a multiobjective line search problem is equivalent to solving a collection of single objective …

Hierarchical Frameworks For Scaling-Up Multi-Agent Coordination, Minghong Geng

Research Collection School Of Computing and Information Systems

Multi-agent reinforcement learning has emerged as a powerful framework for developing collaborative behaviors in autonomous systems. However, existing MARL methods often struggle with scalability in terms of both the number of agents and decision-making horizons. My research focuses on developing hierarchicalapproaches to scale up MARL systems through two complementary directions: structural scaling by increasing the number of coordinated agents and temporal scaling by extending planning horizons. My initial work introduced HiSOMA, a hierarchical framework integrating self-organizing neural networks with MARL forlong-horizon planning, and MOSMAC, a benchmark for evaluating MARL methods on multi-objective MARL scenarios. Building on these foundations, my recent …

Compartmental Disaggregation: Bridging Simulation And Sampling Methods For Synthetic Population Data Generation, Dylan Mack

McKelvey School of Engineering Graduate Student Theses & Dissertations

As agent-based models (ABMs) grow increasingly widespread in public health, their associated challenges have become all the more significant. Lauded for their ability to capture population heterogeneity, nonlinear dynamics, and emergent behaviors, disease ABMs are also computationally expensive and often require detailed inputs that describe each agent at the individual-level, known as synthetic population data. Current approaches for synthetic population data generation generally fall into one of two categories: sampling or simulation. These methods are both feasible only under restricted conditions and suffer from challenges surrounding data availability and computing power. This thesis proposes compartmental disaggregation, an intermediate method for …

Enhancing Patient Safety: Exploring Virtual Sitters' Role In Fall Prevention Through Remote Virtual Monitoring, Adama Diallo, Awatef Ergai Dr., Leeanna Spiva Dr., Meriel Mccollum Dr.

Symposium of Student Scholars

Remote Virtual Monitoring (RVM) technology enhances safety for both patients and care teams by reducing falls, improving the efficiency and effectiveness of continuous patient observation, and lowering costs associated with falls and staff support. The success of fall reduction efforts largely depends on the role of virtual sitters, individuals who remotely monitor high-risk patients to prevent falls. This study aims to explore the experiences of virtual sitters, identifying key themes, challenges, and opportunities to improve the intervention. Specifically, the research investigates how technology, work shifts, and institutional support impact the effectiveness and job satisfaction of virtual sitters.

Bridging The Gap: Care Team’S Perspectives On Technology And Ai Integration In Healthcare, Sarah Fernandes, Pranathi Boyina, Awatef Ergai Dr., Wellstar Health System, Mohammad Yousef Mousa Naser, Sylvia Bhattacharya Dr.

Symposium of Student Scholars

As healthcare systems increasingly integrate digital solutions, understanding the perspectives of frontline healthcare workers on technology adoption is critical. This study explores how Registered Nurses (RNs), Licensed Practical Nurses (LPNs), and Certified Nursing Assistants (CNAs), collectively referred to as the Care Team, interact with existing and emerging healthcare technologies, including artificial intelligence (AI). Given the growing reliance on digital tools for clinical and administrative tasks, this research examines the challenges and benefits perceived by healthcare professionals when incorporating AI-driven solutions into their workflows.

A cross-sectional research design was employed, involving 30 semi-structured interviews with Care Team members from an Intensive …

Algorithms For Feature Extraction And Optimisation Of Object Recognition Operator, Hudayberdiev Xakkulmirzayevich Mirzaakbar, Bobomurod Mamitjonovich Tojiboev, Feruza Komiljonovna Samadova

Chemical Technology, Control and Management

This paper deals with the development and analysis of feature extraction and optimisation algorithms for object recognition operators. Different algorithms are used to improve the efficiency of recognition operators in the automatic analysis of remote sensing images. The information model of objects and methods for selecting, extracting and optimising their features have been studied. The issue of extracting important features of objects using spectral, textural and statistical features and constructing optimal operators based on them has also been studied. Effective approaches based on the theory of convex hulls and multidimensional analysis methods have been proposed, taking into account the mutual …

Determination Of Optimal Parameters For Quality Drying Of Garlic Using The Vibro-Convective Method, Jasur Safarov, Shakhnoza Sultanova, Abdurakhmon Mirkomilov

Chemical Technology, Control and Management

This article examines the process of drying garlic using a low-temperature vibratory-convective drying system. At the "Service Technology" department of Tashkent State Technical University, a vibratory dryer was developed to ensure high-quality drying of garlic while maximizing the preservation of its biologically active compounds. Through experimental studies, optimal drying parameters were determined, including the degree of moisture removal, process duration, airflow velocity, and vibration acceleration. The results obtained contribute to enhancing the efficiency and quality of garlic drying, which holds practical significance for agricultural producers and consumers interested in healthy nutrition.

Detection Of Http Flood Attacks Based On Machine Learning Algorithms, Norbek Karimov, Furkat Rakhmatov, Oybek Xolmuminov

Chemical Technology, Control and Management

This paper analyzes the effectiveness of Random Forest and SVM models for detecting HTTP Flood attacks. Experimental results demonstrate that both models achieve high accuracy. Evaluation was conducted using Precision, Recall, and F1 Score metrics. Additionally, key features of network traffic were extracted through correlation analysis to enable real-time application of the models in attack detection. The findings provide important insights into detecting DDoS attacks using machine learning and improving model performance.

Security In Biometric Access Control Systems Based On Fingerprints, Elmurad Jamuradovich Qilichev, Baxodir Saydullaevich Achilov, Ismoil Ergash OʻGʻLi Isroilov, Mirshod Mirkomil O'G'Li Ahmadov

Chemical Technology, Control and Management

This article analyzes biometric access control systems using fingerprints. The article considers the advantages of using biometric technologies, including solutions aimed at ensuring security, protecting users' personal data, and increasing the efficiency of systems. A detailed explanation of the principles of operation of fingerprint biometric systems, their underlying algorithms, and technological advances is provided. Problems that arise when assessing the level of security, ease of use, and technological and social aspects of biometric access systems and methods for combating them are also covered. At the end of the article, opinions are expressed about the future of fingerprint-based biometric systems and …

Studying The Technology For Obtaining Zinc Chloride From Spent Supporter Waste In Ammonia Production, A.T. Dadaxo‘Jaev, Sodikjon Kadirov

Chemical Technology, Control and Management

This article presents the results of research on the recycling of spent zinc adsorbents formed during the ammonia production process, aimed at obtaining zinc chloride (ZnCl₂), which can be utilized in various industrial sectors, including electroplating. The research covers the optimization of technological parameters such as hydrochloric acid concentration, temperature, and reaction time to efficiently extract zinc chloride. The experiments revealed that the best results are achieved by using a 20% hydrochloric acid solution, at a temperature of 60°C, with a reaction time of 60 minutes. The resulting 40% zinc chloride solution was tested in electroplating production, where it met …

Research Of The Dynamic Characteristics Of A Time-Pulse Ultrasonic Sensor, Aliev Ravshan, A.U. Djalilov

Chemical Technology, Control and Management

This article investigates the dynamic characteristics of a time-pulsed ultrasonic sensor used to measure water flow in open channels. The operating principle of the sensor, its response time in various hydrodynamic conditions, speed, and factors affecting measurement accuracy are analyzed. In the process of research, the improved ultrasonic sensor was tested and its effectiveness in measuring water flow in real time was evaluated. The results obtained showed that the sensor adapts to the velocity, temperature and turbulence level of the water flow. Based on the results of the research, the possibilities of working of time-impulse ultrasound sensors in open channels …

Application Of Quantum Algorithms In Optimization Of Cognitive Decision-Making Systems, Noilakhon Yakubova

Chemical Technology, Control and Management

The article analyzes the potential of quantum algorithms for optimizing cognitive decision-making systems in production processes in the energy sector. Compared with traditional algorithms, quantum algorithms allow high-speed processing of large amounts of variable data in real time and solving multiparameter problems based on an integrated approach. The study considers uncertainties and issues of increasing efficiency in the processes of production and distribution of electricity using a cognitive model. The integration of quantum algorithms into this model allows developing optimal strategies for using resources in production. A heating boiler was taken as a control object, and taking into account its …

Algorithms For Fast Fire Risk Prediction And Real-Time Data Processing, Mirzoyan Mirzaaxmedovich Kamilov, Tolaniddin Ramziddinovich Nurmukhamedov, Oybek Zokirovich Koraboshev, Bakhodir Saydullayevich Achilov

Chemical Technology, Control and Management

Ensuring fire safety in facilities with high fire risk is one of the pressing problems of modern society. Nowadays, there is a great need for accurate and effective prediction systems for fire prevention and rapid response. Since traditional methods do not provide the ability to quickly analyze and predict in real time, the development of algorithms and modern approaches using modern technologies is of great importance. This article analyzes fire risk prediction algorithms, their principles of operation and effectiveness, and considers methods for assessing and predicting fire risk using Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies. The …

Influence Of Substrate Temperature On The Properties Of Reactive Dc Magnetron Co-Sputtered Ag-Doped Tio2 Thin Films, Hezekiah B. Sawa

Tanzania Journal of Engineering and Technology (TJET)

This study reports on the influence of substrate temperature on the properties of Ag-doped TiO2 thin films. The films were deposited by reactive DC co-sputtering of Ti and Ag targets at different substrate temperatures and Ag target sputtering powers. Grazing incident X-ray diffractometer confirmed that all films were polycrystalline with dominant peak oriented along (101) planes representing the anatase TiO2 phase. The average grain size of the samples improved with increase in deposition temperature. At a substrate temperature of 450 ℃, the samples had a dominant peak representing the rutile phase, suggesting partial transformation from anatase to rutile phase. The …

A Critical Realist Erp Implementation In Zimbabwean Mining Industry Organisations, Jairos Mukwenha

Tanzania Journal of Engineering and Technology (TJET)

This research uses a critical realist framework to examine the factors influencing the success of enterprise resource planning (ERP) system implementation in Zimbabwean mining industry organisations. From the perspective of critical realism, the mining industry in Zimbabwe faces a complex interplay of opportunities and obstacles while implementing ERP systems. The deployment of ERP in mining firms is critically examined in this paper, emphasising how these systems might improve operational efficiency while considering Zimbabwe's particular socioeconomic circumstances. By exploring underlying structures, mechanisms, and outcomes, the research aims to identify critical challenges and opportunities and develop practical recommendations for improving ERP adoption …

Cellulose Recovery From Waste Denim Fabrics Through Indigo Vat Dye Reduction And Spandex Dissolution, Tito N. Venance

Tanzania Journal of Engineering and Technology (TJET)

This study addresses environmental conservation by tackling end-of-life management for post-consumer denim garments through the recycling of cotton fibres from waste denim. The purification process involved dithionite reduction of vat dyes in the presence of an alkali followed by selective dissolution of spandex using N,N-dimethylformamide (DMF). Optimal conditions for dye removal were determined at 90°C for 120 minutes with sodium hydroxide at 25 g/L, sodium dithionite at 6 g/L and PVP at 4.5 g/L, while spandex extraction was achieved using a 5% DMF solution at 70°C for 4 hours. Ultraviolet (UV)-vis spectrophotometric analysis indicated a significant increase in whiteness (DL*). …

Assessment Of Factors Contributing On Early Rotting Of Chromated Copper Arsenate Treated Utility Power Distribution Wood Poles In Tanzania, Innocent J. Macha

Tanzania Journal of Engineering and Technology (TJET)

The study aimed to assess the factors contributing to the premature decay of Chromated Copper Arsenate (CCA) treated utility power distribution wooden poles in Tanzania. Deteriorated poles samples from various regions in Tanzania were analyzed using handheld X-ray spectrometry to quantify the retention of CCA preservative chemicals. The ages of these poles were estimated based on annual growth rings. The findings indicated that premature failure of CCA treated wooden poles is attributed to an imbalance in the chemical composition of the preservative solution. The study found that CuO retention in most samples ranged between 10-18 kg/m3, significant lower that the …

Developing Predictive Mathematical Model For Optimizing Coating Weight Variation In Galvalume Production: A Case Study Of A Metal Industry, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

Variations in coating weight for galvanized steel sheets can result in notable differences between batches. Such variations may cause various issues, such as diminished corrosion resistance, lower mechanical strength, and visual defects, which can ultimately drive-up costs, lead to customer dissatisfaction, and pose safety risks. Even with attempts to manage elements like air knife pressure and line speed, coating weight inconsistencies remain challenging. The research focuses on developing a predictive mathematical model designed to optimize variations in coating weight during Galvalume production. The critical parameters influencing coating weight variation were identified and analysed using a systematic literature review, primary data …

Design And Performance Analysis Of Fiber Bragg Grating Temperature Sensor For Industrial Processes Sensing Applications, Paul Stone Stone Brown Macheso S.B.

Tanzania Journal of Engineering and Technology (TJET)

The Fiber Bragg Grating (FBG) sensor has become a widespread sensing device because of its small size, passive design, immunity to electromagnetic interference, and direct ability to measure physical properties like temperature and strain. Recently, femtosecond infrared laser processing and regeneration techniques have resulted in the development of stable high-temperature gratings, which are a powerful tool in smart factories, an aspect of the fourth Industrial Revolution (4IR), and show promise for application in harsh environments like high pressure, high temperature, or ionizing radiation. The development of stable high-temperature gratings that can withstand harsh environmental factors like high temperatures, pressures, and …

Application Of Artificial Neural Network Models For Predicting Diesel And Petrol Prices In The Geographically Sparsed Regions In Tanzania, John M. Kafuku

Tanzania Journal of Engineering and Technology (TJET)

Fuel consumption in Tanzania, mainly diesel and petrol, accounts for 82 percent of the energy consumption in the country, with significant price volatility affecting market stability, availability of fuel, and investment decisions. This study uses an artificial neural network (ANN) with a backpropagating algorithm to predict fuel prices in four regions of Tanzania. Key input parameters include the currency inflation rate (CIR), the petrol fuel inventory (PFI), the diesel fuel inventory (DFI), and the fuel transport costs (FTC). The study selected the 6-10-10-2 ANN structures for Sumbawanga-Rukwa, Mpanda-Katavi, and Mbeya-Mbeya as well as 6-10-9-2 for the Songea-Ruvuma region. The results …

Production Of Potassium-Rich Biofertilizer From Composted Banana Peels And Watermelon Rinds, Neema O. Msuya

Tanzania Journal of Engineering and Technology (TJET)

This study investigated the production of biofertilizer from composted banana peels and watermelon rinds, focusing on the mineral content and its impact on plant growth. The process involved characterizing raw materials, producing biofertilizer, analyzing mineral concentrations (potassium, nitrogen and phosphorus), and evaluating its quality through Spiny Amaranth seed growth. A compost bin with three compartments was designed, testing three composting ratios of banana peels to watermelon rinds (2:1, 1:2 and 1:1). Composting was monitored on moisture content, pH, organic matter, and temperature for 37 days. The 1:1 ratio had the lowest temperature (33.45°C) and highest pH (7.08), while the 2:1 …

A Fuzzy Based Framework For Sustainable Technology Selection In Small-Scale Gold Mining Operations, John M. Kafuku

Tanzania Journal of Engineering and Technology (TJET)

Small-scale gold mining (SSGM) operations in Tanzania has been operating inefficiently due to inadequate mining processing technologies, poor working tools, lack of enough capital, and insufficient electricity. Despite the efforts made by different stakeholders in boosting the sustainability of SSGM yet the sector has not reached the expected goal. This paper proposes a framework for appropriate technology selection to help small scale gold miners in evaluating various gold mineral processing technologies. The framework utilizes the fuzzy logic set theory for technology evaluation and selection. The developed framework for technology selection upon validation provided results that technology adequacy of more than …

Factors Affecting Adoption Of Industry 4.0 Predictive Maintenance By Manufacturing Industries: Tanzania Food And Beverage Manufacturing Industries, Fred E. Peter

Tanzania Journal of Engineering and Technology (TJET)

Industry 4.0 has increasingly become a focal point of scholarly inquiry. Nonetheless, there remains a noticeable lack of comprehensive research on the diverse and systematic factors that influence the adoption of Industry 4.0 Predictive Maintenance (PdM 4.0) in manufacturing sectors within developing regions, particularly in East Africa. This study seeks to bridge this research gap by investigating the key determinants affecting the actual implementation of PdM 4.0 in Tanzania’s food and beverage manufacturing industries. To achieve this objective, a mixed-methods research design was adopted, combining both qualitative and quantitative approaches. Qualitative data were obtained through in-depth interviews with ten industry …

Microwave Ore Pre-Treatment Review And Process Flowsheet Conceptualization, Baker F. Giyani

Tanzania Journal of Engineering and Technology (TJET)

The global demand for mineral commodities has increased dramatically over the years, and this is largely due to several factors, including technological advancements, industrialization, and a rise in population. Further, the demand keeps increasing because the ore being mined is becoming more complex, and the feed grade is declining over the years, prompting the need for innovative technologies to treat such ores more efficiently. Microwave ore pre-treatment is one of the potential technologies that can be employed to improve process performance. This is possible because ores are composed of both good-microwave heaters and poor microwave heaters, which creates thermal stresses …

Kennesaw State University Student Managed Investment Fund Sector Sensitivity Analysis, John Kiersznowski, Joe Johnson, Kyler Howell, Geranger Lewis

Senior Design Project For Engineers

The Kennesaw State University Student Managed Investment Fund (SMIF) Sector Sensitivity Analysis focuses on improving the fund’s decision-making and performance through data science. The SMIF is a diversified index fund designed to outperform indices like the S&P 500. This project investigates how macroeconomic variables—such as GDP growth, inflation, interest rates, and commodity prices—impact sector performance. By structuring data, developing a sustainable data pipeline, and leveraging advanced statistical techniques and predictive modeling, our team was able to provide the framework and proof of actionable insights that enhance the fund's ability to manage risks and optimize returns.

Compression Strength Prediction Of Regular-Slotted-Container Corrugated Fiberboard Boxes Based On Artificial Neural Network Using Multiple Materials And Design Parameters, Tita Archaviboonyobul, Ravipim Chaveesuk, Jay Singh, Tunyarut Jinkarn

Industrial Technology and Packaging

Importance of the work: An accurate compression strength prediction model of RSC corrugated boxes could be used as an effective packaging design tool for industry.

Objectives: This research applied the material and design parameters for RSC corrugated box strength prediction using artificial backpropagation neural network modelling (BPN).

Materials and Methods: Total of 17 material and design factors from 630 commercially corrugated box samples in Thailand were recorded as input parameters along with their box compression test (BCT) values as output parameter. Data was randomly grouped as 80:10:10 during the model development for training set, testing set and validating set, respectively. …

Carbon Accountability Scores: A Process-Oriented Approach For Carbon Offsetting Using Ai Agents, Joshit Mohanty, Vaishali Vaishali

Graduate Student Government Association Research Conference

Conventional carbon offset programs rely on quantified emissions to determine balancing requirements. While this approach offers a standardized means of measuring carbon output, it often provides industries with a loophole—allowing them to offset their emissions by purchasing equivalent credits for activities such as tree planting rather than tackling inefficiencies at the source. This research proposes a process-based framework called Carbon Accountability Scores (CA scores) to offer a proactive strategy for assessing and reducing carbon footprints. Instead of focusing on the mere balancing of emitted and sequestered carbon, CA scores integrate an organization’s operational processes into the calculation, thereby offering the …

Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty

Graduate Student Government Association Research Conference

Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.

This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the …