Digital Commons Network^™

Measurement-Aware Zero-Phase Iterative Learning Control For Robust Regulation Of Nonideal Boost Converters In Electric Vehicle Fast Charging, Aytaç Altan, Mohammed S. Alzaidi, Cağfer Yanarateş

Turkish Journal of Electrical Engineering and Computer Sciences

Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise …

A Binary Multiobjective Hippopotamus Optimization Algorithm For Feature Selection In Phishing Website Detection, Fatima Belmessaoud, Sofiane Maza, Djaafar Zouache

Turkish Journal of Electrical Engineering and Computer Sciences

Phishing website detection remains a major challenge in cybersecurity as attackers continuously develop new techniques to deceive users. Identifying the most informative features from large datasets is essential to improve classification accuracy while reducing computational complexity. Feature selection is therefore widely addressed using metaheuristic optimization techniques due to their flexibility and global search capability. In this study, we propose a Binary Multiobjective Hippopotamus Optimization Algorithm (B-MOHOA) for feature selection in phishing website detection. The proposed method simultaneously optimizes two conflicting objectives: maximizing classification accuracy and minimizing the number of selected features. Unlike many existing studies that mainly focus on transfer …

Range–Angle-Dependent Oam Beamforming With A Concentric Helical Circular Fda, Uğur Yeşi̇lyurt

Turkish Journal of Electrical Engineering and Computer Sciences

Secure and spatially selective wireless transmission requires orbital angular momentum (OAM) beams that are confined to a specific range and angle, rather than propagating indefinitely along the beam axis. In this paper, a concentric helical circular frequency diverse array (CHCFDA) is proposed to generate range–angle-dependent OAM beams without requiring external phase shifters. The helical element positioning inherently provides the necessary interelement phase distribution through physical step height, while logarithmically increasing frequency offsets are applied across concentric rings—and optionally across individual elements—to eliminate range periodicity and achieve a single, well-focused OAM beam exclusively at the target location. Both linear and logarithmic …

Innovating Effective Engineering Designs For Hazard Risk Reduction In North Carolina, Daniella Hirschfeld

Funded Research Records

No abstract provided.

Cedar: Investigating The Mesosphere And Lower Thermosphere Neutral Temperature And Winds Responses To Geomagnetic Storms Equatorward Of The Auroral Zone, Tao Yuan

Funded Research Records

No abstract provided.

Pahdf: A Privacy-Aware Hybrid Detection Framework With Class-Aware Weighted Stacking Ensemble (Cawse) For Fake Instagram Account Detection, Sura Jasim Mohammed, Safa Saad Abbas, Suhad Hatem Jihad

Journal of Intelligent Informatics, Networking, and Cybersecurity

The rapid growth of social media platforms has intensified concerns regarding online privacy, data security, and fraudulent activities that driven by fake accounts. This paper proposes a Privacy-Aware Hybrid Detection Framework (PAHDF) to detect Instagram fake account that integrates privacy preservation with high-performance machine learning. Unlike existing approaches that treat privacy and detection as separated objectives, therefore, the proposed framework jointly addresses both objectives by relying exclusively on publicly available, low-sensitivity profile metadata. PAHDF combines a deep learning model for latent feature representation with a Random Forest classifier for behavioural pattern learning through a Class-Aware Weighted Stacking Ensemble (CAWSE), where …

From Detection To Segmentation: Adapting Yolo26 For Surface Crack Delineation, Mohammed Al-Mustafa, Israa H. Ali

Journal of Intelligent Informatics, Networking, and Cybersecurity

Surface crack delineation plays an important role in infrastructure inspection because accurate pixel-level mapping of cracks can support condition assessment, maintenance planning, and automated monitoring of roads and other civil surfaces. However, recent crack segmentation methods often depend on heavy network designs or prompt-based foundation models. It also remains unclear how a lightweight detection-oriented model behaves across different data organizations and unseen images. This study therefore investigates whether YOLO26m-seg, the medium segmentation variant of the recent YOLO26 family, can be adapted into an effective and practical pipeline for surface crack delineation. The proposed workflow has four main steps. First, binary …

Analysis Of The Influence Of Anthropometric Dimensions Of Postural Ergonomics Using Multiple Linear Regression, Gashbeen Faisal Najmaddin, Edrees Muhammed Tahir Harki

Al-Bahir

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary …

Can Artificial Seagrass Meadows Reduce Pathogenic Bacteria In Coral Reef Ecosystems- A Mesocosm Study, Hewa Pathirannahelage Athri Thathsarani Weerakoon, Jimmy Kuo, Pi-Jen Liu, Kwee Siong Tew

Journal of Marine Science and Technology–Taiwan

Seagrass meadows provide essential coastal ecosystem functions by stabilizing sediments, enhancing water quality, and shaping nutrient and microbial dynamics. With global seagrass losses accelerating due to climate change and anthropogenic pressures, artificial seagrass (ASG) has been proposed as a nature-based alternative to mimic these functions. However, its ability to replicate biological interactions, particularly microbial regulation and pathogen suppression, remains unclear. In this study, we conducted a six-week mesocosm experiment comparing natural Thalassia hemprichii and ASG within coral reef-associated habitats in southern Taiwan. Physicochemical parameters, sedimentation rates, nutrient concentrations, and planktonic and benthic bacterial communities were analyzed. Sedimentation rates and nutrient …

Differential Equation Modeling For Sustainable Resource Management: A Steady-State Optimal Harvesting Approach, Iordanka N. Panayotova, Aleksei Talonov

CODEE Journal

Mathematical models based on differential equations provide a powerful framework for connecting real-world data to informed decision-making. In this work, we present a student-accessible project that uses an optimal-control framework to study the sustainable management of biological resources.

Motivated by fisheries management, we examine a predator--prey system in which harvesting decisions must balance ecological and economic considerations. The model is formulated as an optimal control problem that seeks to maximize the total discounted net revenue from harvesting. Rather than solving for the complete time-dependent harvesting trajectory, we restrict the analysis to positive controlled coexistence equilibria and characterize an interior stationary …

Spatiotemporal Variations Of Tidal Asymmetry Along The Coast Of Taiwan: Characteristics And Implications, Ting-Chieh Lin, Tai-Wen Hsu, Tzu-Chun Huang, Chun-Yuan Lin

Journal of Marine Science and Technology–Taiwan

This study presents the first systematic investigation into the spatiotemporal characteristics and evolutionary trends of tidal asymmetry along the coast of Taiwan from 2003 to 2022, employing a moving window method combined with the S_TIDE toolbox.  By quantifying the skewness of the Main Tidal Asymmetry Combinations (MTAC) and their temporal variations, the study reveals significant regional disparities between the eastern and western coasts.  The western coast is primarily dominated by the M2-M4 combination, with the northwestern region exhibiting a flood dominance pattern and the southwestern region characterized by ebb dominance.  Conversely, the eastern coast, attributed to its open topography and …

Reliable Performance Analysis Of Polyurea Coatings Used In Offshore Wind Turbines, Yu-Chang Lin, Yen-Fu Liu, I-Ming Pan, Ming-Yuan Lin, Kang-Yu Liao, Hung-Hua Sheu, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

This study explores the weather resistance, mechanical properties and corrosion resistance of polyurea coatings in marine environments. The relevant analysis results can be used as a reliability assessment of offshore wind turbine structural coatings during their service life under the influence of marine environments. The long-term experiment uses seawater and 70°C thermal aging conditions as coating reliability assessment items. The microstructure of the samples that have been immersed in seawater for a long time and thermally aged is observed using a scanning electron microscope (SEM). The results show that the surface of the 100 and 125 series polyurea coatings is …

Identifying The Causality And Criticality Of Factors Influencing The Promotion Of Asian Island-Hopping Cruise Tourism In Taiwan, Hsiao-Chuan Liu, Gin-Shuh Liang, Feng-Ming Tsai, Yu-Ling Lien

Journal of Marine Science and Technology–Taiwan

Following the COVID-19 pandemic, the global tourism industry has steadily recovered since 2022. Island-hopping cruises have gained increasing attention for enhancing regional connectivity and diversifying marine travel experiences; however, their development in Asia remains limited compared with that in Europe and the Caribbean due to fragmented policy coordination, inadequate port infrastructure, and uneven technological readiness. Although Taiwan possesses a geographic advantage and can serve as a strategic hub linking Asian island destinations, systematic planning and stakeholder coordination remain insufficient, resulting in unclear mechanisms that drive or constrain island-hopping cruise tourism. Existing studies mainly focus on market demand or passenger behavior, …

White Shark Occurrence In Flower Garden Banks National Marine Sanctuary Revealed From Acoustic Telemetry In An Offshore Mpa, Michael A. Dance, Jay R. Rooker, R. J. David Wells, Megan V. Winton, Landes L. Randall, Marissa F. Nuttall, Brondum M. Krebs, Creed C. Branham, Brett B. Sweezey, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

The outer continental shelf of the Gulf of Mexico (Gulf) is characterized by unique bathymetric features that provide critical habitat for marine fauna. Here, we demonstrate the utility of large-scale acoustic telemetry for monitoring an oceanic marine protected area (MPA) and document the first known occurrences of white sharks (Carcharodon carcharias) within Flower Garden Banks National Marine Sanctuary (FGBNMS). White sharks were tagged with acoustic transmitters in the western North Atlantic Ocean off the east coast of the United States and Canada. Nine white sharks were detected along the outer shelf ecosystem associated with FGBNMS over a three-year …

Technical Analysis And Market Liquidity In Sale-And-Purchase Transactions Of Second-Hand Oil Tankers, Chih-Chung Cheng, Po-Yin Wang, Heng-Chih Chou

Journal of Marine Science and Technology–Taiwan

In addition to using second-hand oil tankers to fulfil immediate shipping needs, shipowners can leverage price fluctuations in the tanker market to make vessel sale-and-purchase (S&P) transactions. Given that the profitability of vessel S&P transactions depends primarily on timing decisions, in this study, technical analysis was applied to identify the optimal transaction timing for 5-, 10-, and 15-year-old second-hand Aframax tankers. In a simulation, an S&P strategy based on technical analysis outperformed a benchmark buy-and-hold strategy, particularly for newer tankers, possibly due to the higher price volatility and lower market efficiency in the markets for these vessels. However, the lack …

Synchronous Deep Reinforcement Learning For Optimized Storage Assignment Of Ship Blocks, Gawon Lee, Jaehyeon Heo, Misung Kim, Hyerim Bae

Journal of Marine Science and Technology–Taiwan

This paper presents a deep reinforcement learning (RL) framework for optimizing block storage allocation in shipbuilding yards. During the shipbuilding process, vessels are constructed in block units to maximize the operational efficiency. Following assembly, these blocks must be stored in limited yard spaces, creating a complex variant of the binary packing problem. This storage allocation problem is further complicated by operational constraints, including the barge capacity and transportation time restrictions. Moreover, poor storage decisions can lead to redundant block movements, which can adversely affect downstream processes and increase operational costs. To resolve this problem, a policy-gradient-based synchronous RL model was …

A Resilience Early Warning Assessment Of The Maritime Supply Chain: A Case Study Of China’S New Energy Vehicle Exports, Xiuqian Chen, Liangyong Chu, Mengyao Wang, Jiayin Du, Yiming Zhang, Xiyao Xu

Journal of Marine Science and Technology–Taiwan

Enhancing resilience through early warning is a critical strategy for mitigating disruption risks in the maritime supply chain (MSC). This study proposes a novel early warning assessment framework to determine the resilience of the MSC. It is referred to as a resilience early warning system. An evaluation index system for shipping enterprises is developed based on four dimensions: withstand capacity, adaptive capacity, learning capability, and the external environment. A resilience assessment model that uses the Bayesian best-worst method (BBWM) and the extension cloud model (ECM) is established to quantify MSC resilience. An early warning evaluation model based on a Bayesian …

Public-Port Throughput As An Activity Proxy For Near-Port Air Quality And Health: A Transferable Two-Scale Framework (Kaohsiung, 2017–2024), Ping-Jen Wang, Ying-Lin Hsu, Shih-Hao Chang, Bao-Tzung Wu

Journal of Marine Science and Technology–Taiwan

We developed a two-scale time series framework using monthly container throughput (20-foot equivalent units, TEU) as a port activity indicator. Applied to Kaohsiung, Taiwan (2017–2024), we related TEU to near-port NO₂ and PM₂.₅ (monthly) and air quality to outpatient respiratory diagnoses (weekly) across the 2019–2020 sulfur rules and the COVID-19 pandemic. Transfer-function models indicate TEU tends to lead near-port NO₂ by 6–9 months. Structural break tests at policy dates indicate nonsignificant changes in levels and slopes, suggesting gradual rather than abrupt shifts in the activity–pollution linkage. Weekly two-pollutant distributed-lag Poisson models estimated relative risks (lags 0–8) per interquartile range (IQR) …

Continuous-Time Quantum Markov Chains And Discretizations Of P-Adic Schrödinger Equations: Comparisons And Simulations, Wilson A. Zuniga-Galindo, L. F. Chacón-Cortés

School of Mathematical & Statistical Sciences Faculty Publications

Continuous-time quantum walks (CTQWs) are a fundamental tool in the development of quantum algorithms. Recently, it was shown that discretizations of p-adic Schrödinger equations give rise to continuous-time quantum Markov chains (CTQMCs); this type of Markov chain includes the CTQWs constructed using adjacency matrices of graphs as a particular case. Unlike classical continuous-time Markov chains (CTMCs), the CTQMCs studied here do not satisfy the classical Chapman–Kolmogorov equation; this is a genuine quantum effect, due to the fact that the underlying unitary evolution composes at the level of probability amplitudes rather than probabilities, and we make precise the sense in …

Urban Spatial Development Control In Tanzania: Analysis Of Factors Influencing Gis Application Using Structural Equation Modelling (Sem)., Happiness Protas Mmanda, Nestory Yamungu

Tanzania Journal of Engineering and Technology (TJET)

Rapid urbanization in developing countries has intensified urban expansion, creating challenges for sustainable development. Geographic Information Systems (GIS) enhance spatial planning, but empirical evidence on factors influencing their effectiveness remains limited. This study examines determinants of GIS application in Urban Spatial Development Control (USDC). The objectives are to (1) identify and categorize factors affecting GIS use, (2) assess relative strength, and (3) develop a validated structural model explaining GIS adoption in USDC. Data were collected from 103 LGAs by a mixed sampling method. Exploratory and Confirmatory Factor Analysis classified influencing factors into technology-related (α = 0.869, CR = 0.881), process-related …

Decision Support Tool For The Maintenance Of Meter Gauge Railway Permanent-Way Infrastructures: A Concept Paper, Hamisi J. Maulid, Beatus A.T Kundi, Juma M. Matindana, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

A Decision Support Tool (DST) represents a transformative way of modernising maintenance practice on the permanent-way infrastructure of Meter Gauge Railway (MGR). Maintenance practice remains largely reactive, as the MGR plays a strategic role in transporting both freight and passengers, resulting in inefficient resource allocation, high operational risk, and growing Lifecycle expenses. This concept paper explores the potential and the design challenges for a DST that combines fuzzy analytic hierarchy process (Fuzzy-AHP) modelling, multi-criteria decision analysis (MCDA), Geographic Information Systems (GIS) and predictive machine learning (ML) analytics for evidence-based, future-oriented maintenance management. The paper draws on peer-reviewed studies from …

Hydro-Chemical And Bacteriological Assessment Of Zanzibar Groundwater Resources, Subira Munishi, Andrew Kimati

Tanzania Journal of Engineering and Technology (TJET)

Groundwater is the primary freshwater source in Zanzibar, sustaining domest ic, agricultural, and tourism needs. Increasing demand has intensified the pressure on this limited resource and has led to over-abstraction and contamination. Amid the growing demand and contamination pressures, this study examines the quality of groundwater in Zanzibar to clarify current conditions and emerging risks, and inform resource management and public health priority interventions. Particularly, the present hydro-chemical and bacteriological quality and variability was examined for both Unguja and Pemba Islands. A total of seventy-two samples were collected using a stratified random sampling approach, with the first field campaign focusing …

Kanmultisign: Multi-Scale Sequence-Based Pose Animation From Sign Language Notation With Kolmogorov-Arnold Networks, Guanyi Du, Lintao Wang, Kun Hu, Ziyang Wang

Research outputs 2022 to 2026

Sign language production from symbolic notation offers a scalable route to accessible sign animation. We present KANMultiSign, a multi-scale sequence generator that translates HamNoSys notation into two-dimensional human pose sequences. Our framework makes two complementary contributions. First, we introduce a coarse-to-fine generation strategy with multi-scale supervision: the model is first guided by an intermediate body–hand–face scaffold to encourage global structural coherence, and then refines fine-grained hand articulation to improve finger-level detail. Second, we investigate integrating Kolmogorov–Arnold Network modules into a Transformer backbone, using learnable univariate function primitives to model the highly non-linear mapping from discrete phonological symbols to continuous body …

When Does Global Search Pay For Itself? A Measured Exploration Cost And Energy Break-Even Analysis Of A Metaheuristic Search Controller In Solar Energy Systems, Mohamed Ali Muammar Ezgour

Communications of the IIMA

Autonomous energy systems increasingly delegate the choice of operating point to embedded search algorithms, trading a fast local optimizer that can settle on a wrong point against a slower global search that guarantees the right one at a measurable cost. This paper reframes maximum power point tracking under partial shading as that decision and measures its economics on a fixed photovoltaic plant in MATLAB/Simulink. A Hippopotamus Optimization global search handed over to incremental conductance is compared with incremental conductance alone across seventeen initial duty cycles and thirty random seeds. The hybrid reached the global peak in all thirty seeds, whereas …

Hydrothermal Alteration Mapping Of The Northern Coongan Greenstone Belt Using Remote Sensing Imagery, Meaza Bogale, Elias Woldeyohanis

Journal of Sustainable Mining

Archean greenstone belts are well known for their ore deposits, diverse lithostratigraphy, and well-preserved evidence from the early Earth. The Northern Coongan Greenstone Belt is an Archean greenstone belt that is part of the Eastern Pilbara Craton of Western Australia. The rock units of this area have the potential to be sources of valuable mineral deposits, which could be economically beneficial for extraction. Studies have been conducted in the northern Coongan greenstone belt, mostly using geological field methods and geophysical interpretations, excluding remote sensing methods for mapping mineral indices. Therefore, this study aims at providing surface mineral distribution maps and …

Sedimentary Dynamics In Tubular Sandstone Caves, Porto União, Southern Brazil, Leandro Bianchini, Julio Cesar Paisani

International Journal of Speleology

Clastic sedimentation in sandstone caves remains poorly understood, particularly in systems with tubular morphology. This study investigates sedimentation, reworking, and sediment removal dynamics in the Legru Cave system, southern Brazil, based on the integrated analysis of sedimentary facies, microstructures, and microfeatures, combined with optically stimulated luminescence dating. The results indicate that conduit infilling is dominated by high-density flows, including cohesive debris flows, partially diluted multiphase flows, and flows with intermediate rheological behavior between mud flow and hyperconcentrated flow, in addition to shallow flow alternations. Sediment supply is predominantly allochthonous, related to hillslope-derived material delivered by overland flow and mud flows, …

Cyberspace Collaborative Awareness: A Model For Unity Of Effort In Homeland Defense, Mike Knapp, Sean Atkins, Matthew Mclaughlin

Joint Force Quarterly

The increasing frequency and severity of cyberattacks against U.S. critical infrastructure continue to confound homeland defense efforts. Defending against state cyber campaigns that threaten the nation’s most critical systems requires a new awareness model that can enable unity of effort across public and private actors. Examining homeland defense awareness in other domains reveals principles and approaches that can inform the development of a collaborative awareness model in cyberspace. This new framework acknowledges the interconnectedness of government and commercial networks and the independent goals of each player in the domain. Doing so provides a viable path to achieving shared domain awareness …

From Data To Victory: The Race For Analytic Superiority In Warfare, Robert Grossman, Emily Goldman

Joint Force Quarterly

Artificial intelligence technologies have reached a tipping point after decades of development. They are diffusing widely across defense and national security applications. Twenty-first century warfighters rely on analytic models in all systems, at all echelons, and in all domains. As more powerful models built on ever larger data sets become ubiquitous, militaries are in a new competition to deploy artificial intelligence. Operational art must embrace “analytic superiority.” This is the operational advantage from collecting and ingesting data, building robust models and computing infrastructure, deploying the models into operational systems, and denying adversaries' ability to do the same

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A Note On Euler's Definition Of The Sum Of A Divergent Series, Alexander Aycock

Euleriana

We outline Euler's theory of divergent series and present another approach he could have taken to sum his ``factorial series". Finally, we address the contradictions that arise from his concept of a sum of a divergent series.

Euler's Explorations Of Extremal Ellipses, Jonathan David Evans

Euleriana

In the 1770s, Euler wrote a series of papers (E563, E691 and E692) about finding the ellipse with minimal area or perimeter in the family of all ellipses passing through a fixed set of points. This is a translation of all three papers from the original Latin, together with a commentary which discusses Euler's results and an appendix which addresses a question from E691 which Euler left for others to consider.