Engineering Commons^™

Empowering Shipping Management Competence With Artificial Intelligence: A Strategic Approach To External Environmental Volatility, Yu-Kai Huang, Cheng-Hsien Hsieh, Chi-Chang Lin, Yu-Tzu Chang, Yu-Chao Cheng

Journal of Marine Science and Technology–Taiwan

The shipping industry is undergoing significant transformation with advancements in artificial intelligence (AI), yet challenges remain in effectively adopting AI technologies. This study addresses the key concerns influencing AI adoption in shipping management. Using the Analytic Hierarchy Process (AHP) integrated with the PEST model, an evaluation framework was developed to assess AI applications in shipping companies. Based on expert input collected through the Delphi method, four constructs and twelve criteria were identified, with the 'Technological' dimension being the most critical. 'Robustness,' 'Costs,' and 'Data quality' emerged as the top factors affecting AI implementation. The framework offers practical insights for shipping …

Comparative Evaluation Of Deep Learning Models For Predicting Skipjack Tuna (Katsuwonus Pelamis) Catch Based On Climatic Factors, Peng Ding, Hui Xu, Xin Zhuang, Yan-Lun Wu, Fengyuan Shen, Yujie Xiao, Jiensi Zhulidezi, Wei-Yu Lee

Journal of Marine Science and Technology–Taiwan

To investigate the impact of climatic factors on skipjack tuna catch, this study collected and analyzed annual global skipjack tuna catch data spanning from 1960 to 2021, along with corresponding monthly data for the key indicator of El Nino events (Niño1+2, Niño3, Niño4, and Niño3.4), the Southern Oscillation Index (SOI), the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), the North Pacific Index (NPI), and the global sea-air temperature anomaly index (dT). The optimal lag years of climatic factors were identified by selecting the maximum absolute cross- correlation coefficients. Subsequently, the predictive performance of LSTM, BiLSTM, and CNN-BiLSTM models …

Effects Of Train-Ship Direct Transshipment On Container Terminal Operational Efficiency And Energy Consumption: From A Scheduling Perspective, Yiying Du, Yaozong Wang, Zhongzhen Yang

Journal of Marine Science and Technology–Taiwan

On-dock rail integration positions terminals as critical hubs for rail-sea transshipment, which necessitates efficient scheduling for rapid container transfers. Given the strict schedules and batch arrival of railway containers, in this study, we propose a train-ship direct transshipment (TSDT) mode to eliminate nonproductive yard rehandling. To comprehensively evaluate the impact of the proposed mode on terminal handling operations, we developed an operational scheduling model for the entire process of the simultaneous loading of yard containers and railway-handling area (RHA) containers. The model comprises two stages. Stage 1 models the pre-reshuffling operations in the yard before loading, and Stage 2 implements …

Key Success Factors In Using The Lifting Method To Construct A Steel Bridge Pylon, Ming-Chao Su, Hui-Ping Tserng

Journal of Marine Science and Technology–Taiwan

Constructing the inclined steel pylon of cable-stayed bridges is challenging because of the pylon’s height, spatial limitations, and safety concerns. To address these challenges, this study developed a modular lifting method that can enhance the efficiency and precision of pylon construction. The proposed method involves using rotation jigs to temporarily assemble the pylon, horizontal positioning on temporary supports, and synchronized lifting through computer-controlled hydraulic systems. Field implementation on a large-span bridge project revealed that compared with the traditional method, the proposed method resulted in higher welding quality, lower risks associated with great-height operations, and a shorter on-site assembly time. The …

Deep Learning-Based Model For Automated Prediction Of Coastal Changes: A Robust Approach To Environmental Forecasting, Tsair-Fwu Lee, Chu-Ho Chang, Chin-Shiuh Shieh, Chih-Hsien Wu, Jen-Chung Shao, Chien-Liang Chiu

Journal of Marine Science and Technology–Taiwan

The coastline stands as a critical domain encompassing industry and the environment. The escalating global warming, leading to elevated sea levels and intensified wave-current interactions, has given rise to substantial coastal erosion. This predicament, in conjunction with excessive human development and Taiwan's coastal areas' extreme climatic impact, accentuates the perceptibility of coastal beach alterations. As a result, coastal erosion has emerged as a pressing issue necessitating resolution. Traditional methodologies for assessing coastline changes have conventionally relied on manual measurements. However, owing to the fluctuating distance of coastlines, influenced by tidal patterns, extended measurement processes over several months are susceptible to …

Hydrographic Influences On Seasonal Variations In Zooplankton Communities Of Taiwan Bank (Southern Taiwan Strait), Bor-Shyr Chen, Frank Paolo Jay B. Albarico, Mark Ariel D. Malto, Aiza D. Gabriel, Chiu-Wen Chen, Cheng-Di Dong

Journal of Marine Science and Technology–Taiwan

Understanding the factors that control ocean productivity is crucial in fisheries management. Taiwan Bank, located between the Taiwan Strait and the South China Sea, is a highly productive ecosystem due to upwelling events. The total zooplankton community (holozooplankton and merozooplankton), diversity, seasonal changes, and environmental drivers remain unexplored despite its productivity. This study evaluates the seasonal and vertical environmental dynamics in the Taiwan Bank and their impacts on the zooplankton community structure. We collected zooplankton and basic water parameters in March, July, and September 2017 at 5, 25, and 50 meters. We recorded significant seasonal changes in zooplankton composition and …

Model Performance For Predicting Trends And Analyzing The Impacts Of Sea Surface Temperature Changes In The Gulf Of Thailand, Tanatpong Udomchaipitak, Nathaphon Boonnam

Journal of Marine Science and Technology–Taiwan

This study focuses on assessing and improving the predictive performance of sea surface temperature (SST) in the Gulf of Thailand under unique environmental challenges. Data from the Hybrid Coordinate Ocean Model (HYCOM) were utilized, covering the period from July 1994 to June 2024 at depths ranging from 0 to 30 meters. After cleaning the data using the Interquartile Range (IQR) method, the processed dataset was tested using four models: Recurrent Neural Network (RNN) architectures, including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), as well as Convolutional Neural Networks (CNNs). Model performance was enhanced by tuning the parameters over …

Multimodal Imaging Of Protein-Based Biomaterials For Delivering Chemo-Agent Cargo For Glioblastoma Treatment In A Murine Model, Orin Mishkit

Dissertations and Theses

Protein-based self-assembling biomaterials, known as Thermo-Responsive Assembled Proteins (TRAP), present meaningful potential as drug delivery carriers. These materials enable the controlled, slow release of poorly soluble chemotherapeutic agents, such as doxorubicin (Dox), while potentially reducing systemic off-target effects. In collaboration with multiple NYU labs, this study evaluated the efficacy of two TRAP variants—TRAP and F-TRAP—as drug delivery carriers in a xenograft mouse model of glioblastoma multiforme (GBM).

The primary objective was to compare the effectiveness of TRAP-loaded Dox (TRAP-DOX) to free Dox in achieving tumor extravasation and accumulation, facilitating sustained drug release. We hypothesized that the leaky vasculature of GBM …

Advancing Electrical Stimulation: Full-Head Mri Segmentation For Abnormal Brain Anatomy With Tdcs, Andrew Birnbaum

Dissertations and Theses

Evaluating the effectiveness of transcranial direct current stimulation (tDCS) is essential for guiding its integration into therapeutic and performance-enhancement applications. In our laboratory, we investigate the efficacy of tDCS across multiple experimental models, including both animal and human studies. I have contributed significantly to the execution and analysis of these experiments, which include studies in rats and healthy human participants aimed at evaluating whether electrical stimulation of the motor cortex can enhance motor learning. These studies assess improvements in fine motor performance resulting from tDCS. In stroke patients, I contribute to our investigation of tDCS as a rehabilitative intervention, particularly …

Design And Lab Implementation Of An Air Source Transcritical Co2 Heat Pump, Geoffrey Turbeville

Dissertations and Theses

A laboratory-scale air-source transcritical CO2 heat pump (TCHP) was developed to evaluate the performance of low-global-warming-potential (GWP) refrigerants for cold climate applications. A custom climate chamber was also constructed to simulate winter weather conditions typical of the northeastern United States. Both the TCHP and the chamber were fully instrumented to collect temperature, pressure, and mass flow data, which were used to calculate the co- efficient of performance (COP) in accordance with ASHRAE standard refrigerant enthalpy methods. Prior to testing the CO2 system, the experimental setup was benchmarked using a commercially available R410A heat pump manufactured by LG.

The climate chamber …

Cognitive Map Generation For Vision And Language Navigation, Alexander Sandoval Mesa

Dissertations and Theses

Visual-Language Navigation (VLN) presents significant challenges for autonomous agents, such as robots and virtual assistants, particularly in complex, dynamic environments where the seamless integration of visual perception and natural language understanding is critical. Traditional VLN systems often struggle with effectively aligning language instructions and visual scene understanding, limiting their adaptability and navigation efficiency.

This thesis proposes a novel Cognitive Map-based framework that addresses these challenges by transforming natural language navigation instructions into structured graph representations. The Cognitive Map consists of nodes representing waypoints, landmarks, decision points, and edges encoding spatial relationships and navigational actions. These maps are generated using Large …

Experimental And Analytical Investigation Of Particle Dynamics In Newtonian And Non-Newtonian Fluids In A Taylor-Couette Cell, Andres F. Velez Mendoza

Dissertations and Theses

This doctoral dissertation investigates heavy particle sedimentation in Newtonian and non-Newtonian fluids, aiming to understand their behavior in Drilling Fluid (DF) systems used in oil and gas industry, where such phenomenon can lead to operational issues such as lost circulation, well control problems, and even blowouts. To simulate DF dynamics under operational conditions, this study utilizes a Taylor-Couette (TC) cell, which consists of a rotating inner cylinder and a stationary outer cylinder separated by a 9.0 mm annular gap. The TC cell allows for the investigation of the sedimentation behavior of spherical particles within both Newtonian fluids (deionized water and …

Celis: Compact Eyesafe Lidar System, A Portable 1.5 Μm Elastic Lidar System For Rapid Aerosol Concentration Measurement: Part 2, Retrieval Of Particulate Matter Concentration, Kori D. Moore, Alan W. Bird, Michael D. Wojcik, Robert Lemon, Jerry L. Hatfield

Space Dynamics Laboratory Publications

SDL Poster on the CELiS Compact Eyesafe Lidar System

Integrating Satellite-Based Precipitation Analysis: A Case Study In Norfolk, Virginia, Imiya M. Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

In many developing cities, the scarcity of adequate observed precipitation stations, due to constraints such as limited space, urban growth, and maintenance challenges, compromises data reliability. This study explores the use of satellite-based precipitation products (SbPPs) as a solution to supplement missing data over the long term, thereby enabling more accurate environmental analysis and decision-making. Specifically, the effectiveness of SbPPs in Norfolk, Virginia, is assessed by comparing them with observed precipitation data from Norfolk International Airport (NIA) using common bias adjustment methods. The study applies three different methods to correct biases caused by sensor limitations and calibration discrepancies and then …

Evaluating The Effectiveness Of Stay-In-Place Forms To Improve The Tosional Stability Of Box Beam Bridges During Erection, Karl E. Barth, Michael W. Seek, Gregory K. Michaelson, Dimitra Pyrialakou, Brook T. Woldegabriel

Engineering Technology Faculty Publications

Cold-formed tub girders provide an effective steel solution for short-span bridges. The girders are often delivered with an open top with stay-in-place forms installed on site. Walkways may be installed to the side of the girder that can induce significant torsion rotations in the open cross section. Full scale tests on girder specimens have shown that installing one or two panels of stay in place forms at the ends of the girder can significantly reduce the torsion rotation of the girder by providing warping resistance. Cantilever tests on the stay in place forms are performed to investigate the influence of …

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …

Integrating Sustainable Practices Into Lean Engineering: Applying The Engineering For One Planet Framework In Manufacturing Engineering Technology Education, Dalya Ismael, Vukica M. Jovanovic, Murat Kuzlu, Charles Lowe, Lisa Bosman

Engineering Technology Faculty Publications

A growing number of manufacturers are recognizing significant financial and environmental benefits from adopting sustainable business practices. Sustainable manufacturing refers to the production of goods through processes that are economically sound, minimize environmental impact, and conserve energy and natural resources. Lean engineering, a comprehensive approach to decision-making and leadership within manufacturing organizations, has proven effective in driving sustainable practices. Key strategies include waste elimination, value identification, value stream mapping, flow creation, pull system establishment, and continuous improvement. Both lean manufacturing and sustainability share a common focus on minimizing waste. Lean principles address seven types of waste: transport, inventory, motion, waiting, …

Using Quanser Platform To Introduce Engineering Technology Students To Autonomous Vehicles, Otilia Popescu, Logan Beaver, Murat Kuzlu, Krishnanand Kaipa

Engineering Technology Faculty Publications

The area of autonomous vehicles is not new, but the latest advances in various technologies gave it a new boost in the last decade and it keeps growing in interest. However, undergraduate curricula rarely include courses specific to this area, which is considered mostly an interdisciplinary graduate field. While various programs introduce students to the background needed to understand and approach the field, specific work on autonomous vehicle projects is left for extra curriculum activities or student clubs, and eventually for senior (capstone) projects. This paper presents the work of a team of electrical engineering technology students on an autonomous …

5g-Enabled Iot Gateway For Educational Purposes, Murat Kuzlu

Engineering Technology Faculty Publications

The project aims to develop and implement a 5G-IoT gateway for efficient management and interconnection of IoT devices through advanced sensing and communication technologies. Sensing technologies encompass modern approaches for detecting and measuring physical properties with high accuracy across manufacturing, smart grids, healthcare, smart cities, and other domains. Communication technologies represent the latest developments in high-speed data transmission, offering enhanced reliability and network capacity. This 5G-IoT gateway functions as an educational platform, providing students and educators with hands-on experience in emerging technologies. The system creates opportunities for practical learning and research in telecommunication technologies by enabling direct engagement with 5G …

Differential Equations' Coverage In Circuits And Heat Transfer Courses In An Engineering Technology Curricula, Otilia Popescu, Orlando Ayala

Engineering Technology Faculty Publications

Differential equations are at the core of any undergraduate engineering as well as of science programs. While a course in differential equations is required by any engineering degree, it is not a requirement for engineering technology programs, which usually require mathematics up to calculus I. This paper discusses the undergraduate engineering technology curricula, focusing on how differential equations are taught to engineering technology students and how they are covered in the programs. In particular, the paper will discuss the treatment of differential equations in electrical circuits and heat transfer courses.

Building Obsolescence: Key Factors Influencing Demolition Decisions For Commercial Buildings, Azlan Shah Ali, Zakaria Norhanim, Zulkifly Umi-Kalsum, Zaki Faiz

Research Publications (2021 to 2025)

Buildings, while primarily serving to provide shelter, can deteriorate over time without proper maintenance and planning, leading to obsolescence, a significant threat to their functionality. This study investigates the factors contributing to building obsolescence and how they influence the selection of adaption strategies, focusing on commercial buildings as a case study. Questionnaire data were gathered from 386 business owners and occupants of obsolete buildings in Klang Valley, Malaysia, to capture their perspectives on the issue. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were employed to rank obsolescence factors and solution options on strategies on obsolescence factors. PCA results …

Improving Visual Inspection Performance During Pre-Flight Visual Inspections By Aircraft Maintenance Technicians., Patrick Codd

Doctoral

Visual inspection is a critical task in aircraft maintenance and is the predominant inspection technique used in the global aviation sector. For safety reasons, visual inspections by Aircraft Maintenance Technicians are routinely conducted on a daily basis during pre-flight inspections. Its significance becomes evident when considering the potential consequences of Aircraft Maintenance Technicians not seeing observable defects during visual inspections. For example, an aircraft crash landing in 1989 resulted in 111 fatalities and was attributed to a visual inspection failure. The industrial quality control literature also illustrates the varying accuracy for the observation of defects and hazards, underscoring the inherent …

Waveforms For Next Generation Non-Stationary Channels, Zhibin Zou

Electronic Theses & Dissertations (2024 - present)

Waveform design aims to achieve orthogonality among data signals/symbols across all available Degrees of Freedom (DoF) to avoid interference while transmitted over the channel. Precoding involves the decomposition of the channel matrix into orthogonal components for the purpose of constructing a precoding matrix that is then combined with the data signal to achieve orthogonality in the spatial dimension. On the other hand, modulation uses orthogonal carriers in a certain signal space to carry data symbols with minimal interference from other symbols. However, it is widely evident that next Generation (xG) wireless systems will experience very high mobility, density and time-varying …

Interfacing Neural Models: Biocompatibility And Fabrication Of A Flexible, Self-Folding Microelectrode Array, Fernando A. Pesantez Torres

Electronic Theses & Dissertations (2024 - present)

Neurodegenerative diseases pose a formidable challenge in modern medicine, necessitating the development of advanced research tools that can elucidate their complex pathophysiology. Recent advancements in neurodegenerative disease research have led to the development of three-dimensional (3D) neurodegenerative organoids using human induced pluripotent stem cells (hiPSCs). These organoids closely mimic human brain architecture and functionality, providing a valuable tool for understanding complex diseases. Additionally, the ability to generate and study brain organoids consistently and in large quantities holds potential for a controlled in vitro setting and high-throughput drug screening. However, these models are complex systems requiring specialized maintenance, analysis, and manipulation …

Novel Silicon Anodes For Improved Lithium Ion Battery, Amir Hegazy

Electronic Theses & Dissertations (2024 - present)

Li-ion battery (LIB) have been dominating the development of electronics shaping our daily life owing to their good specific and volumetric energy densities. However, the technological advancement calls for higher energy, safer, lower cost, and large-scale manufacturing batteries.

Silicon is considered an excellent candidate for anode material for higher energy LIB. This thesis examines the potential of silicon as an anode in high-capacity LIBs where the role of silicon is studied at the frontside (FS) and the backside (BS) of the anode. At the frontside, the effect of deposition of silicon on graphite on the battery performance was studied. Graphite …

Epitaxial Quantum Dot Scintillators With Monolithic Photodetector Integration: Physics, Fabrication And Characterization Of Materials And Devices, Allan Oreave Minns

Electronic Theses & Dissertations (2024 - present)

This dissertation discloses the physics, fabrication, and characterization of high-performance scintillator detectors based on epitaxial InAs quantum dots (QDs) in GaAs. The detector crystals grown include monolithically integrated In_0.35GaAs photodetectors with Al_0.92-0.6In_0.03-0.35Ga_0.05As metamorphic buffer layers (MBL). A device fabrication process was developed for the lithographic patterning, chemical etching, contact metallization and readout integration of materials grown by means of molecular beam epitaxy (MBE) on 3-inch GaAs (001) wafers. Low capacitance integration with readout electronics was achieved through wire bonds to custom printed circuit boards (PCBs) with commercial components.

The relationship between device …

A Fault-Tolerant Exchange-Coupled Spin-Ensemble Qubit At Elevated-Temperatures, Aniruddha Chakraborty

Theses and Dissertations

This thesis introduces a novel qubit architecture: the ferromagnetic exchange-coupled spin ensemble qubit (E-qubit), designed to address the noise-induced instability. In this work, the time evolution of the ensemble’s density matrix is studied using the Liouville–von Neumann equation. To benchmark against a single-spin qubit, the gate fidelity of an E-qubit is computed in the presence of thermal noise. Coherence time is also analyzed under identical thermal condition and a linear scaling is observed with qubit size . The results show that, at 6 K , the gate fidelity error (0.7 % ) of the seven- spin ensemble is an order …

Modeling Synergistic Effects Of Integrin And Tgf-Β Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar

Theses and Dissertations

The induction of Epithelial Mesenchymal Transition (EMT) is initiated by a

number of protiens and growth factors, one of which is the profibrotic cytokine Trans-

forming Growth Factor β (TGF-β). Within the extracellular matrix (ECM), TGF-β

is found in a latent, inactive form bound to proteins such as fibronectin (FN). For

TGF-β to contribute to EMT induction, it has to be extracted from the latent com-

plexes into a soluble form. This soluble, activated TGF-β can then bind to receptors

on the cell membrane, which causes the transduction of signals that begin EMT. Re-

search has shown that the release …

Strength Imbalances And Shoulder Pain In Manual Wheelchair Users Stratified By Age Of Spinal Cord Injury/Disorder (Sci/D) Onset, Ashlyn M. Jones

Theses and Dissertations

Introduction The majority of manual wheelchair users (MWUs) with spinal cord injury or disorder (SCI/D) develop shoulder pain. In adults with SCI/D, there is evidence that upper limb strength imbalances are associated with shoulder pain. However, strength imbalances may indicate protective compensatory strategies, and other factors may be important contributors to pain. Currently, personalized prevention and management of pain is limited, little is known about joint strength imbalances and pain in children who use manual wheelchairs, and the effect of the age of SCI/D onset is poorly understood. The purpose of this study was to assess the effect of age …

Machine Learning-Driven Optimization For Utility-Scale Quantum Optimization, Bao Tran

Theses and Dissertations

Hard combinatorial optimization problems, often mapped to Ising models, promise potential solutions with quantum advantage but are constrained by limited qubit counts in near-term devices. We present an innovative quantum-inspired framework that dynamically compresses large Ising models to fit available quantum hardware of different sizes. Thus, we aim to bridge the gap between large-scale optimization and current hardware capabilities. Our method leverages a physics-inspired GNN architecture to capture complex interactions in Ising models and accurately predict alignments among neighboring spins (aka qubits) at ground states. By progressively merging such aligned spins, we can reduce the model size while preserving the …