Oceanography Commons^™

Enhancing Underwater Imagery And Organism Detection Using Reinforcement Learning, K. Arul Deepa, P. Ramya, Karpaga Vinodha, Dharmaraja C

Journal of Marine Science and Technology–Taiwan

Underwater environments pose significant challenges in assessing image quality and organism detection due to light scattering and absorption, which limits visibility and color fidelity. Existing solutions often fail to effectively address these challenges, resulting in suboptimal image quality and hindering organism identification. This paper examines the problem through a dual-focused approach: enhancing underwater images and detecting organisms using the Underwater Image Enhancement Benchmark (UIEB) dataset. The first step introduces a state-of-the-art method for image enhancement by applying reinforcement learning (RL) principles. By formulating the enhancement process as a Markov Decision Process (MDP)—where states are represented by image features and actions …

Stability Analysis Of Thermohaline Convection With A Time-Varying Shear Flow Using The Lyapunov Method, Kalin Kochnev

Honors Scholar Theses

This work applies the Lyapunov method to identify instabilities and compute the growth rate of a linear time-varying system. The linear system studied describes cold fresh water on top of hot salty water with a periodically time-varying background shear flow. A time-dependent weighting matrix is employed to construct a Lyapunov function candidate. The resulting linear matrix inequalities are discretized in time using the forward Euler method. As the number of temporal discretization points increases, the growth rate predicted by the Lyapunov method or Floquet theory, used for comparison, will converge to the same value obtained from numerical simulations. Furthermore, the …

Locations Of Outfalls In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly M. Kibler, Melinda J. Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_Outfalls_IRL_LWL.shp was created under grants from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL).

The dataset presented here includes the location of outfalls identified throughout the study region and general characteristics of the shoreline where they were identified.

Seagrass Persistence In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly Kibler, Melinda Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_seagrasspersistence_IRL_LWL.shp was created with support from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL). The dataset presented herein represents persistence of seagrass throughout waters of the IRL and LWL.

Living Shoreline Prioritization And Hydrodynamic Habitat Suitability Models For Restoration In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly M. Kibler, Melinda J. Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_shorelinemodel_IRL_LWL.shp, was created with support from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon and Lake Worth Lagoon.

The dataset presented herein includes:

1. shoreline data from >15,000 transects collected in the field,
2. shoreline wave climate data created through hydrodynamic modeling and frequency analysis of historic data,
3. categorization of potential risk for shoreline boat wake impact,
4. persistence of seagrass within 210 m of the shoreline, …

Enhanced Point Cloud Generation From A Novel 360° Underwater Lidar, Olagoke E. Daramola

Dissertations

This dissertation presents novel algorithms to improve the mapping capabilities of a 360-degree underwater Pulsed Laser Line Scanner LiDAR (PLLS-360°). Due to its 360° field-of-view (FOV), the PLLS-360° is a compact full-waveform omnidirectional imager suitable for seafloor mapping, underwater asset inspection, object detection, ice-sheet mapping, and construction progress monitoring. The proposed methodology includes an improved waveform fitting technique for saturated waveform recovery, detection array response correction, radiometric corrections, and fusion of LiDAR and sonar bathymetric datasets. The first part of this dissertation assesses the LiDAR’s performance and describes how the data for this unique 360° FOV architecture is processed. The …

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 …

New Hydrographic Survey Specifications - Updates And Enhancements, Matt Wilson, Tyanne Faulkes, Giuseppe Masetti

Center for Coastal and Ocean Mapping

No abstract provided.

Raising Awareness About Hydrographic Careers Through Sea-Going Opportunities, Juliet Kinney, Rochelle Wigley, Sara Cardigos, Fahima Bellabad, Larissa Marques Freguette

Center for Coastal and Ocean Mapping

There is a worldwide shortage of hydrographic personnel (van Wegen, 2021, Hydro International 2008).  Calls for action to address this issue include the IHO’s Hydrography at Sea opportunities, while intiatiative such as Seabed 2030 are bringing broader attention to the field and helping to catalyze new discussions and partnerships in hydrography (IHO, 2024).  The global sea floor mapping community needs to develop a broader workforce pipeline.  We would like to highlight the importance of providing time at sea and leadership opportunities in developing a robust workforce.  We start with an overview of a selection of current exchange and training programs …

Study On Motion Prediction Analysis Of Large Vessels Entering Kaohsiung Port Second Harbor, Li-Heng Cheng, Hsing-Yu Wang

Journal of Marine Science and Technology–Taiwan

Pilotage is a primary service offered by ports, ensuring the safe passage of entering and exiting vessels. This study applied motion prediction analysis to large vessels navigating the constrained waterways of Kaohsiung Port’s second harbor. To address the needs of pilots and port operators, a simplified planar motion equation was developed that incorporated speed over ground and rate of turn (ROT) as primary variables. The model relied on inputs of limited navigational data, enabling pilots to predict changes in heading and position over time and determine the conditions for safe harbor entry. Vessel paths and turning angles were analyzed to …

Tidal Flooding Contributes To Eutrophication: Constraining Nonpoint Source Inputs To An Urban Estuary Using A Data Driven Statistical Model, Alfonso Macías-Tapia, Margaret R. Mulholland, Corday R. Selden, Sophie Clayton, Peter W. Bernhardt, Thomas R. Allen

OES Faculty Publications

In coastal urban areas, tidal flooding brings water carrying nutrients and particles back from land to estuarine and coastal waters. A statistical model to predict nutrient loads during tidal flooding events can help estimate nutrient loading from previous and future flooding events and adapt nutrient reduction strategies. We measured concentrations of dissolved inorganic nitrogen and phosphorus in floodwater at seven sentinel sites during 15 tidal flooding events from January 2019 to September 2020. The study area was the Lafayette River watershed in Norfolk, VA, USA, which is prone to tidal flooding and is predicted to experience more frequent and intense …

A Century Of Sediment Metal Contamination Of Mar Menor, Europe's Largest Saltwater Lagoon, Irene Alorda-Montiel, Valentí Rodellas, Ariane Arias-Ortiz, Albert Palanques, Andrea G. Bravo, Júlia Rodriguez-Puig, Aaron Alorda-Kleinglass, Carlos Green-Ruiz, Marc Diego-Feliu, Pere Masqué, Javier Gilabert, Jordi Garcia-Orellana

OES Faculty Publications

Coastal enclosed ecosystems, such as lagoons, are vulnerable to anthropogenic impacts because they favor the accumulation of contaminants from the surrounding watersheds, particularly in their sediments. Europe's largest saltwater lagoon, the Mar Menor (SE, Iberian Peninsula), is a highly impacted ecosystem and the first in the continent to be granted personhood rights. Based on a high-resolution spatial and temporal dataset, we present the historical reconstruction of metal contamination in this ecosystem during the last century. Our results highlight that sediment metal contamination has been mainly driven by the development of the mining industry in the nearby Sierra Minera de Cartagena-La …

Ensemble Machine Learning Approaches For Bathymetry Estimation In Multi-Spectral Images, Kazi A. Islam, Omar Abdul-Hassan, Hongfang Zhang, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

OES Faculty Publications

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs …

Using Post-Supercritical Co2-Assisted Method To Deposit Niep Alloy Coating On The Micro-Arc Oxidation Layer Of Az31 Magnesium Alloy And Its Corrosion Behavior Analysis, Kang-Yu Liao, Hung-Hua Sheu, Ming-Yuan Lin, Ming-Chih Kuo, Po-Hsun Wu, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

In this study, a Ni-P alloy coating was deposited on the micro arc oxidation (MAO) layer of AZ31 magnesium alloy to improve its corrosion resistance. The MAO layers were prepared under different operated voltages from 300 to 400 V. The results indicated that the optimize operated parameters for MAO layer is at 350 V, the MAO coatings had the most compact microstructure and superior corrosion resistance. In order to improve the corrosion resistance of MAO coating, this study chose to deposit Ni-P alloy coating on the surface of MAO coating via the post supercritical CO₂-assisted electroless plating (PSC-CO …

The Effect Of Feedback On A Remote Operator’S Maneuvering Control For Mass Remote Navigation Competency, Hyoseon Hwang, Ik-Hyun Youn

Journal of Marine Science and Technology–Taiwan

The rapid advancement of Maritime Autonomous Surface Ships (MASS) technology has highlighted the growing need for Remote Operators (ROs) to manage MASS effectively. ROs possess specialized competencies in areas such as situational awareness, crisis management, and system operation. Despite the introduction of competency-based training and assessment in the maritime sector through the international convention on standards of training, certification, and watchkeeping for seafarers convention, the framework's implementation remains incomplete, particularly in remote operator training for MASS. This study is purpose to identify which competencies improve rapidly with performance feedback and which improve slowly. This study conducted an experiment to quantitatively …

Evaluation Of Carbon Sequestration In Seagrass Meadows Of Kenting: A Comparative Study With Penghu And Dongsha Island, Zih-Wei Tang, Huei-Fen Chen, Jordi Mahardika Puntu, Ping-Yu Chang, Li Lo, Jian-Jhih Chen, Wen-Chen Chou, Lan-Feng Fan, Ying-Ju Chang

Journal of Marine Science and Technology–Taiwan

This study investigates the controlling factors of carbon sequestration (CS) in seagrass bed sediments across three distinct environments in Taiwan: the Kenting (KT) coastal area, the Penghu (PH) open inner bay, and the Dongsha (DS) Atoll lagoon. Actual measurements of the substrate depth beneath the sediment and ground-penetrating radar (GPR) scans of the beach reveal that the coral reef bedrock in KT slopes landward. A field survey of the seagrass area in KT was conducted, and three cross-sectional profiles were analyzed to determine their topography, yielding a median sediment thickness of 88.2cm. Based on these measurements, the sediment volume was …

Calculation Of Aquifer Transmissivity From Borehole Resistance Measurements And Pumping Test Results, Fen-Rong Yang, Chien-Wei Huang, Tien-Kuen Huang

Journal of Marine Science and Technology–Taiwan

Transmissivity is a crucial hydrogeological parameter for evaluating groundwater resources. This parameter is conventionally evaluated using pumping tests; however, these tests are costly and can be conducted at few sites. Many researchers have used ground resistance and pumping test data to estimate various hydrogeological parameters. In this study, borehole resistance survey and pumping test data collected by the Taiwan Groundwater Monitoring Network were used to establish the relationship between transmissivity and formation factor for aquifers in the Zhuoshui River alluvial fan. This relationship was then used to estimate the water output of the aforementioned aquifers in a cost-effective manner from …

A Neural Network-Based Sliding Mode Adaptive Control System For Unmanned Surface Vehicles, Sun Qiaomei, An Liang, Jiang Linglin

Journal of Marine Science and Technology–Taiwan

Over the past decades, numerous studies have explored the use of autonomous unmanned surface vehicles (USVs). Successful USV operation requires a robust tracking control system to perform a range of tasks. However, USV dynamics are uncertain, time-varying, and nonlinear. This paper presents a neural network-based sliding mode adaptive control (NNSMAC) system to enhance USV tracking performance. Trajectories were generated using spline and polynomial interpolation based on a set of N predefined waypoints. Simulation results show that the proposed method outperforms traditional sliding mode control in error reduction, enabling more effective tracking.

A Blueprint To Greener Shorelines: Advancing The Effectiveness, Sustainability, And Widespread Adoption Of Coastal Nature-Based Solutions Through Transdisciplinary Research, Taylor M. Sloey, Sierra Hildebrandt, Rebecca L. Morris, Matthew V. Bilskie, Aaron Bland, David Bushek, Gabriella Dipetto, Daniel Elefant, Vincent Encomio, Ramin Familkhalili, Christine Hladik, Danielle Kreeger, Avery B. Paxton, Cindy M. Palinkas, Latina Steele, Andrew Scheld, Daisuke Taira, Jason D. Toft, Armando J. Ubeda, Christine Whitcraft, Donna Marie Bilkovic

Biological Sciences Faculty Publications

Coastal nature-based solutions (NbS) have emerged as powerful tools to enhance sustainable development and ecological restoration goals. As a rapidly growing field spanning across social, political, ecological, economic, and engineering disciplines, it is critical that researchers working in coastal NbS regularly attempt to identify emerging focal areas for scientific inquiry. Following the 27th Biennial meeting of the Coastal and Estuarine Research Federation, we provide a transdisciplinary perspective (including biologists, engineers, oceanographers, geoscientists, economists, and facilitators of workforce training programs) of pertinent research questions that, if answered, will advance the effectiveness, sustainability, and widespread adoption of coastal NbS. These suggestions for …

Foreign Object Detection System Development Using Edge Devices Integrated With Quadcopter Autonomous Tracking, Chi-Chia Huang, Ching-Hung Lee

Journal of Marine Science and Technology–Taiwan

This study proposes an all-weather autonomous foreign-object detection system capable of operating in low-light environments. We used a highly mobile quadcopter equipped with an edge-computing device as the inspection platform. On the software side, we integrated a low-light image enhancement model, a path-tracking algorithm, and a foreign object detection model to achieve rapid object detection. A lightweight, low-light image-enhancement model reduces the need for additional lighting equipment, thereby enabling reliable detection under low-light conditions. The path-tracking algorithm integrates a lightweight semantic segmentation model with traditional image-processing techniques to establish flight paths efficiently and reliably. The foreign-object detection component employs state-of-the-art …

Optimization Of Underactuated Ship Sliding Mode Controller Based On The Ddpg Algorithm, Lin Ma, Mingzhe Qi, Shicai Chen, Hongwei Bian, Jian Zhang

Journal of Marine Science and Technology–Taiwan

Due to the development of ship intelligence, the demand for precise controllers is increasing day by day. In traditional design, the trial-and-error method often leads to the use of inaccurate controller parameters, causing oscillations when environmental disturbances are present. To address these issues, this study introduces deep learning to optimize the controller parameters, particularly those used for sliding mode controllers in underactuated ships. We adopt the Deep Deterministic Policy Gradient (DDPG) algorithm based on the Actor Critic framework. By freely setting the reward function to match the control objective, the trained model can output more accurate controller parameters, with the …

Experiments On Aluminum Alloy Additive Layer Waam Lamination Using The Arc Current Reduction Technique, Jukkapun Greebmalai, Eakkachai Warinsiriruk, Chao-Hsiang Hsiao, Yin-Tien Wang

Journal of Marine Science and Technology–Taiwan

Recent advancements in additive manufacturing have been propelled by innovations in processes, materials, and fabrication techniques. This study specifically focuses on the optimizing Wire and Arc Additive Manufacturing (WAAM) within the Gas Metal Arc Welding (GMAW) process. The goal is to build laminated layers using aluminum alloy from the five-thousand series. In this research, a novel technique is introduced that employs a reduced arc-current during the additive layer progress for aluminum alloys, along with a double pulse current in the GMAW process to enhance weldability. The material used for addition is ER5356 aluminum wire, which is applied to an Al-5083 …

An Optimization Model For Supporting Bunkering Decisions In Bulk Shipping, Chung-Cheng Lu, Hui-Chieh Li, Hung-Yu Chen

Journal of Marine Science and Technology–Taiwan

This study addresses a bunkering optimization problem for bulk shipping carriers that explores route deviation to find optimal bunkering locations and amounts. A mixed integer linear programming (MILP) model is developed to determine optimal bunkering decisions that minimize total operating costs, including total daily operating costs, bunkering costs, port charges and surcharges, while observing time window constraints at loading/unloading ports. The proposed model is evaluated using instances generated from real data provided by H company with its operational headquarters in Taipei, Taiwan, which operates a fleet of handysize ships in East and South Asia. The results indicate that optimization models …

Assessment Of Coastal Navigation Safety: A Case Study Of Boka Bay With Stakeholder Perspectives, Ivan Mraković, Rino Bošnjak

Journal of Marine Science and Technology–Taiwan

The navigational safety of Boka Bay, i.e., a critical maritime area along the Adriatic coast, is of great importance owing to its ecological sensitivity, diverse marine traffic, and significant economic activity. This study provides a comprehensive assessment by analyzing the perspectives of various stakeholders, including seafarers, local pilots, skippers, regulatory authorities, and others engaged in maritime activities within the bay. Using a structured questionnaire survey, both quantitative and qualitative data were collected in formats such as descriptive responses, Yes/No choices, and Likert scale ratings, ensuring a well-rounded understanding of navigational practices and challenges. The data were analyzed using descriptive statistics, …

A Hybrid Model To Assess Commercial Port Resilience In Taiwan, Po-Hsing Tseng, James J.H. Liou

Journal of Marine Science and Technology–Taiwan

Since 2021, international commercial ports have faced unprecedented challenges (e.g., COVID-19 pandemic, Suez Canal congestion), impacting daily life, work, human well-being, properties, the environment, and socio-economic activities. The adaptation capability resilience of international commercial ports to respond to external changes has become crucial. This study develops an expert knowledge-based hybrid multi-criteria decision-making model integrating Best-Worst Method (BWM), Rough Dombi Aggregator, and Combined Compromise Solution (CoCoSo) to evaluate port resilience capabilities, using Taiwan's international commercial ports as a case study. We propose four evaluation dimensions encompassing 13 indicators: detection capability, resistance capability, resource integration capability, and recovery capability. The BWM determined …

An Evaluation Of The Possibility And Effectiveness Of Renewable Energy In Container Terminal At Jinhae New Port, Min-Seop Sim, Yul-Seong Kim, Chang-Hee Lee

Journal of Marine Science and Technology–Taiwan

The international goals of combating climate change and reducing greenhouse gas emissions are driving container terminal operators to adopt renewable energy solutions. This study evaluated the feasibility and effectiveness of introducing renewable energy and eco-fuels for energy independence at the Jinhae New Port Container Terminal, South Korea. Using portfolio analysis, eight renewable energy technologies (solar power, solar thermal energy, wind energy, hydropower, marine energy, geothermal energy, bioenergy, and waste-to-energy) and seven eco-friendly fuels (electricity, liquefied natural gas, liquefied petroleum gas, hydrogen fuel cells, ammonia fuel cells, bioenergy, and hybrid systems) were assessed. Survey data from stakeholders identified solar, wind, and …

Predictive Maintenance In Naval Vessel Propulsion Systems For Enhanced Marine Operations Using A Bigmm-Hmm Framework With Divergence-Based Clustering, Farshid Javadnejad, Hyoshin John Park, Samuel Kovacic, Andres Sousa-Poza

Engineering Management & Systems Engineering Faculty Publications

This study introduces a BiGMM-HMM Integration Framework designed to improve predictive maintenance strategies for naval vessel propulsion systems, addressing the need for efficient and reliable operation in marine engineering applications. The framework effectively manages multimodal sensor data by leveraging a unique combination of Gaussian Mixture Models (GMMs) and Hidden Markov Models (HMMs) in a bidirectional architecture. It analyses the dynamic interactions between sensors and subsystems. Two preprocessing methods are evaluated: Method 1 focuses on subsystem interactions, employing divergence-based root cause analysis to identify key sensor variables by clustering of sensors and subsystems. In contrast, Method 2 processes the entire dataset …

Numerical Simulation Of The Fracture Resistance Of A Flame Deflector Under Impact And High Temperature By Using The Extended Finite-Element Method, Guangzhong Liu, Yuqing Feng, Tong Lin, Zhixin Xiong, Zhenting Chen

Journal of Marine Science and Technology–Taiwan

During the launch of rockets at sea, the flame deflector of the launch platform is subject to transient impact loads and high temperatures, which can result in the fracturing of the flame deflector, thereby endangering the platform and launch safety. In this study, dynamic crack propagation in a flame deflector under the aforementioned conditions was numerically investigated using the extended finite-element method (XFEM). The bulk of the flame deflector was modeled using shell elements, the local area in which the crack evolves was modeled using solid elements, and discontinuities were modeled using enrichment functions in the XFEM. The degrees of …

Overseas Agent Selection For International Logistics Companies: A Case Study, Hung-Ta Lin, Hua-An Lu

Journal of Marine Science and Technology–Taiwan

International logistics companies (ILCs) have aggressively participated in the supply chain systems of production industries as part of global trade development. They have adopted diversified and multinational models by expanding their overseas services to align with the various characteristics of regional economic patterns. Assigning specific local agents for their forwarding operations has been one of the key strategies for overseas services. Notably, the performance of these selected agents has significantly influenced service quality in their respective regions. In collaboration with the top management of an ILC, this study proposes an evaluation framework comprising 4 criteria and 16 subcriteria for selecting …

Cfrp Retrofitting For Enhancing Damping In Cushion Mounts For Marine Applications, Chih-Lung Hou, Guang-Min Luo, Sheng-Yuan Chen

Journal of Marine Science and Technology–Taiwan

Reducing vibration transmission and dynamic response is critical for data processing devices, precision instruments, and machinery in environments with frequent shocks, such as naval applications. These devices are often mounted to ships with cushion mounts. This study presents a cost-effective and rapid method for retrofitting mounts with carbon fiber reinforced polymers; the method greatly improved damping and effectively reduced vibration transmission. Specimens were produced and subjected to experimental modal analysis, and finite element models were developed for comparison. The frequency response functions and modes of the structural components from both methods were compared to assess the improvement in the damping …