Digital Commons Network^™

Robust Load Frequency Control For Multiarea Electrical Power Systems Via Analytical Proportional-Integral-Derivative Plus Second Order Derivative Controller Design, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This research presents a proportional-integral-derivative plus second order derivative (PIDD2) controller design based on the Direct Synthesis Method (DSM) for load frequency control (LFC) of interconnected power systems. The parameters of the proposed PIDD2 controller are determined using the DSM, which offers an analytical approach for tuning. The design approaches have been developed specifically for single, two, and three-area power systems, encompassing nonreheated and reheated thermal turbines. In the proposed design method, the best values of PIDD2 controller parameters were found by using a multicriteria objective function that includes the integral of absolute error (IAE) and settling time. In response …

Boundary Layer Sliding Mode Control Strategy For Variable-Speed Compressor In Deep Freezers: Experimental Validation Of Energy Efficiency And Freezing Capacity, Sertan Aksoy, Kami̇l Çeti̇n, Sezai̇ Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the design and experimental validation of a nonlinear sliding mode controller developed for a deep freezer equipped with a variable-speed compressor. The proposed control strategy aims to minimize energy consumption while maintaining rapid and stable cooling performance under varying ambient conditions. A detailed thermal model of the deep freezer was established using an equivalent resistance–capacitance network representation, enabling precise analysis of temperature dynamics. The sliding mode-based control algorithm dynamically adjusts the compressor’s operating frequency according to temperature deviation, ambient conditions, and time-dependent factors, providing robust performance without requiring parameter retuning for different models. Beyond theoretical-based analysis, a …

Empowering Edge Intelligence Through Reparameterized Lightweight Transformers And Distributed Inference, Hosein Esmaeili, Mohammad Ali Afshar Kazemi, Reza Radfar, Nazanin Pilevari

Turkish Journal of Electrical Engineering and Computer Sciences

Deploying advanced transformer-based models on resource-constrained edge devices remains a significant challenge due to their high memory footprint and substantial compute requirements. In this paper, we propose a reparameterized transformer framework that integrates High-Rank Factorization (HRF) during training, layer merging at inference, and dynamic, load-balanced distributed inference across multiple devices. To further reduce resource usage, our framework supports mixed-precision quantization down to 4-bit, enabling flexible accuracy–latency–energy trade-offs. Experimental evaluations on the ESC-50 environmental sound dataset demonstrate that our method matches or exceeds the performance of larger baseline models while using 20–30% fewer parameters, achieving up to 48% latency reduction in …

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.

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 …

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 …

Relationship Between Aleks Use, Implementation Models, And Grade 9 Students’ Achievement On Algebra 1 Summative Assessments, Deneen Alfordburke

Walden Dissertations and Doctoral Studies

The problem that was addressed through this study was Grade 9 students’ achievement on the Algebra 1 New Jersey Student Learning Assessment (NJSLA) continued to be below the proficiency level that is defined by the state, despite implementation of Assessment and Learning in Knowledge Spaces (ALEKS) Algebra 1 software. The study was grounded in Doignon and Falmagne’s knowledge space theory (KST) which evaluates students’ current knowledge levels and guides them along individualized learning paths based on what they are ready to learn next. The purpose of this nonexperimental quantitative study was to determine whether the predictor variables Grade 9 students’ …

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, …

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) …

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 …

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 …

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

This article explains …

Bitseat: Reimagining The Financing For Airliners Using Nonfungible Tokens (Blockchain Technology), Edwin S. Ongola

Journal of Aviation Technology and Engineering

This essay describes how blockchain technology, particularly nonfungible tokens, can be used to raise funding for airliners. The essay begins with a brief overview on the costs, categories, and acquisition methods of airliners. After that, the essay introduces concepts on blockchain technology, tokens, and smart contracts. The essay then touches on how nonfungible tokens can be used to facilitate fractional ownership of airliners. From there, the essay discusses Bitseat, a conceptual nonfungible token for fractional ownership of airliners, covering its overall design, appeal, marketplace alternatives, and challenges. Finally, in the discussion, the essay summarizes the overall concept and outlines its …

Toxicity Ahead: Forecasting Conversational Derailment On Github, Mia Mohammad Imran, Robert Zita, Rahat Rizvi Rahman, Preetha Chatterjee, Kostadin Damevski

Computer Science Faculty Research & Creative Works

Toxic interactions in Open Source Software (OSS) communities reduce contributor engagement and threaten project sustainability. Preventing such toxicity before it emerges requires a clear understanding of how harmful conversations unfold. However, most proactive moderation strategies are manual, requiring significant time and effort from community maintainers. To support more scalable approaches, we curate a dataset of 159 derailed toxic threads and 207 non-toxic threads from GitHub discussions. Our analysis reveals that toxicity can be forecast by tension triggers, sentiment shifts, and specific conversational patterns.We present a novel Large Language Model (LLM)-based framework for predicting conversational derailment on GitHub using a two-step …

Re: Approval Letter For The Butte Priority Soils Operable Unit, Draft Final Unreclaimed Sites: Ur-31 Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-42 Site Evaluation Summary Report (Sesr) (Dated July 22, 2026), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2026 Final Backfill And Cover Soil Quality Assurance Project Plan (Qapp) Dated August 26, 2026, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Representing Post-Fire Reality: An Empirically Informed Temperature Index Approach To Post-Fire Hydrologic Modeling In Oregon's Western Cascades, Logan Hastings

Dissertations and Theses

The invaluable water resources stored in snowpack face mounting threats from rising temperatures, drought, shifts in precipitation regimes, and increased fire frequency, which pose challenges to operational hydrologic modeling in Oregon's sensitive maritime snowpacks. The gridded temperature index (GTI) approach in operational models like the Hydrological Engineering Center's Hydrologic Modeling System (HEC-HMS) from the U.S. Army Corps of Engineers remains in common use for its minimal data requirements, but how GTI parameterizations should adapt to post-fire conditions is largely unknown.

This research assessed the impact of the 2020 Lionshead Fire on HEC-HMS performance in the North Santiam River basin across …