Digital Commons Network^™

2026 September 17 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Resilient Ethical Governance By Design: Building Resilience For Future-Ready Smart Cities Against Emerging Technology Disruptions In Public Sector – A Case Study Of Dallas Smart City, Emmanuel Asamoah Asare

Doctoral Dissertations and Projects

This dissertation examines how Dallas’s smart city strategic policies foster resilience against disruptions associated with emerging technologies, particularly artificial intelligence and Internet of Things systems. Using a convergent mixed-methods comparative case study, Dallas serves as the primary case, Austin serves as a U.S. municipal comparator, and Barcelona serves as a qualitative benchmark for ethical and trust-centered smart city governance. The study integrates document analysis, broadband and digital equity indicators, stakeholder engagement evidence, and exploratory quantitative comparisons to assess how governance adaptability, preparedness, functionality, equity, and stakeholder trust shape resilience outcomes.

The findings provide partial support for the study’s hypotheses. Dallas …

Re: Conditional Approval Letter For Butte Priority Soils Operable Unit (Bpsou) Final Diggings East Dewatering Treatability Study Pre-Design Investigation Work Plan (Pdiwp) (Dated September 8, 2026) And The 2026 Final Diggings East Dewatering Treatability Study Quality Assurance Project Plan (Qapp) (Dated September 8, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Uncontrolled Surface Flow Areas Drainage C 95% Design Remedial Action Work Plan, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Comparison Of Gravity Separation And Flotation For Pyrite Recovery From Tailings, Gülay Bulut, Gönül Göksu Gökçe, Dilruba Karamanlı, Oğuzhan Mert Gürkan, Ergin Sarp Zenzirci, Binnur Kırım, Alim Gül

Journal of Sustainable Mining

Tailings generated during the production of lead, zinc, and copper concentrates contain significant amounts of sulfide minerals, particularly pyrite. Pyrite, which remains in tailings after the recovery of other metals, is one of the main contributors to acid mine drainage (AMD). Therefore, recovering pyrite from tailings is environmentally and economically an important issue. In this study, pyrite recovery from tailings was investigated using flotation and gravity separation methods. Mineralogical characterization and liberation analyses were conducted by Mineral Liberation Analysis (MLA), indicating that pyrite is the major sulfide mineral with over 76% liberation degree even in the coarsest fractions. Flotation tests …

Portrait: Holistic Data Visualization Using Neural Networks, Chayan Maitra

Doctoral Theses

With the exponential growth of complex data across domains, effective visualization has become increasingly crucial for understanding relationships hidden within high-dimensional spaces. However, existing visualization techniques often struggle to effectively capture and represent such high-dimensional data. Motivated by this challenge, we have developed NeuroDAVIS, a neural network model designed to visualize high-dimensional data by extracting meaningful latent representations through deep feature extraction. While NeuroDAVIS has successfully addressed the visualization aspect, we have soon recognized the necessity of identifying the most relevant features that contribute to the visualization and downstream analysis. To address this issue, we have extended our framework and …

Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod

Turkish Journal of Electrical Engineering and Computer Sciences

The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …

Dynamic Focal Loss Adjustment For Railway Defect Detection, Mehmet Koç, Ridvan Özdemi̇r, Ömer Gerek

Turkish Journal of Electrical Engineering and Computer Sciences

Railway infrastructure is critical to the safe and efficient operation of transportation systems, and the early detection of defects is essential for preventing catastrophic failures. Automated defect detection methods are therefore crucial for maintaining continuous safety while reducing maintenance costs. Although Focal Loss is widely used in object detection under class-imbalanced conditions, its fixed α parameter may limit its effectiveness in detecting rare defects. In this study, we propose an adaptive α-tuned Focal Loss approach that dynamically adjusts class weights based on average precision (AP) values. By iteratively optimizing α without relying on gradient-based optimization, the proposed method improves the …

Relative Rate Observer-Based Online Tuning Mechanism For Single-Input Interval Type-2 Fuzzy Pid Controllers, Oqba Aldreiei, Cenk Ulu, Mert Can Kurucu, Müjde Güzelkaya

Turkish Journal of Electrical Engineering and Computer Sciences

The characteristics of the footprint of uncertainty (FOU) in interval type-2 membership functions (IT2-MFs) are crucial to the performance and robustness of interval type-2 fuzzy controllers (IT2-FCs). However, existing IT2-FC design approaches mostly use fixed FOU structures. This study proposes an online membership function (MF) adjustment mechanism for a single-input interval type-2 fuzzy PID controller (SIT2-FPID)  that adjusts the FOU of the antecedent MFs and weights of the consequent MFs, respectively, to achieve high performance and robustness. The proposed online adjustment mechanism consists of a relative rate observer (RRO), a two-input rule-base adjustment system, and a first-order smoothing filter. The …

Cuip-X25: A Real-World Network Intrusion Dataset For Next-Generation Ai-Driven Security, Arshad Iqbal, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

The efficacy of artificial intelligence (AI) in intrusion detection systems (IDS) is critically dependent on high-fidelity training data. However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape. To bridge this gap, this study introduces CUIP-X25, a novel real-world cyber-attack dataset captured over a four-month period using a dionaea honeypot deployed on a public network. Unlike synthetic alternatives, this dataset provides an authentic representation of modern adversarial tactics, techniques, and procedures, encompassing 3.16 million real events across ten distinct attack categories, including …

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 …

Non-Gradient Quaternion Training Matrix Modifications For Color-Image Distillation, Tahsin Shahnewaz, Megdam Ahmed Chowdhury, Nikolay Metodiev Sirakov

Student Publications

This paper develops a new multi-stage image distillation method that combines two well known techniques. In the first stage, our method creates a matrix from all training images. In the next stage, it adapts a modified principal component analysis (M-PCA) approach to transform the training matrix. In the third stage, Singular Value Decomposition (SVD) fur ther refines the training-image matrix through low-rank reconstruction and controlled row selection. In the fourth stage, rotation of small 2 ×2 matrix blocks on the entire left singular matrix is conducted. The upper m (user-selected number) rows of the reconstructed matrix are selected and transformed …

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.

"The Course Of The Tennessee River", William Lindsey Mcdonald

Research Articles

The article describes the usual course of the Tennessee River and various geological theories for the direction of its course. In addition, it explores the specific geomorphology of the Muscle Shoals and its impact on North Alabama.

Uae Audiences' Reliance On Social Media As A Source Of Information On Complementary And Alternative Medicine: A Study Of Al Ain City Residents Based On Media System Dependency Theory, Abdul Rahman Al-Toum, Mohammed Al-Kaabi, Najoud Al-Mansouri, Ahmed Bin Ishaq, Amer Khaled Ahmad, Maram Manajrah

Middle East Journal of Communication Studies

This study examined the extent to which UAE audiences rely on social media as a source of information on complementary and alternative medicine (CAM) and the resulting effects of this reliance. Grounded in Media System Dependency Theory, the study employed an audience survey using a questionnaire administered to a sample of (132) Emirati citizens in Al Ain. The findings revealed that the combined medium and high reliance reached (53%). Regarding the effects, cognitive effects recorded the highest arithmetic means, followed by affective and behavioral effects at comparable levels. Hypothesis testing showed no statistically significant differences in the degree of reliance …

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 …

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’ …

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, …