Digital Commons Network^™

Exploring The Reduction Of Runway Incursions Through Training, Vasilios (Billy) Constaintine Metallinos

Journal of Aviation Technology and Engineering

Runway incursions are prevalent aviation safety issues that result in adverse outcomes. The focus of this qualitative case study was exploring the reduction of runway incursions through training for pilots. Applying social cognitive theory (SCT) provided this study with a theoretical underpinning. Conducting interviews and a focus group with 17 participants allowed for the collection of enough data and resulted in identifying the importance of training in preventing runway incursions. Based on the thematic analysis conducted, it was identified that evidence-based, scenario-based, and continuous training can be used to reduce runway incursions caused by pilot deviations. The results contribute to …

Direct Solar-Energy Powered Hydrothermal Treatment To Promote Biomethane Production From Anaerobic Digestion Of Rice Processing Waste, Kainat Rahnuma

Student Theses and Dissertations

Hydrolysis is a slow and energy-intensive process and a rate-limiting step in anaerobic digestion (AD). This research investigates performance strategies for integrating hydrothermal treatment (HT) with AD. HT-AD systems were less economically viable than AD-only options because of the high energy consumption of HT. Therefore, we used solar energy to conduct HT via either solar cookers or solar panels. The HT method significantly improved digestion performance, reducing the lag phase from 60 to 24 h, and increasing overall yield. Hydrothermally treated rice, rice bran, and rice hulls produced 22,932 mL, 13,136 mL, and 1283 mL, respectively. However, untreated rice, rice …

Methods For Gis-Driven Airspace Management: Integrating Unmanned Aircraft Systems (Uass), Advanced Air Mobility (Aam), And Crewed Aircraft In The Nas, Ryan P. Case, Joseph P. Hupy

Aviation Technology Graduate Student Publications

The rapid growth of Unmanned Aircraft Systems (UASs) and Advanced Air Mobility (AAM) presents significant integration and safety challenges for the National Airspace System (NAS), often relying on disconnected Air Traffic Management (ATM) and Unmanned Aircraft System Traffic Management (UTM) practices that contribute to airspace incidents. This study evaluates Geographic Information Systems (GISs) as a unified, data-driven framework to enhance shared airspace safety and efficiency. A comprehensive, multi-phase methodology was developed using GIS (specifically Esri ArcGIS Pro) to integrate heterogeneous aviation data, including FAA aeronautical data, Automatic Dependent Surveillance–Broadcast (ADS-B) for crewed aircraft, and UAS Flight Records, necessitating detailed spatial–temporal …

Can I Be An Engineer? Factors Influencing Women’S Decisions To Pursue Undergraduate Engineering Studies In The Middle East And North Africa, Rasha Malaeb, Elsa Maalouf, Aya Mouallem, Jana Sabra

Journal of Pre-College Engineering Education Research (J-PEER)

In the Middle East and North Africa (MENA), different institutional and cultural factors seemingly play a significant role in influencing women’s decisions to enroll in undergraduate engineering programs. In this work, we aim to uncover key influences that affect young women’s decisions to pursue undergraduate engineering studies in Lebanon, an Arab country in the MENA region. First, we conducted a survey during a student-led engineering summer program in 2024 at the Maroun Semaan Faculty of Engineering and Architecture at the American University of Beirut. The survey participants were 47 high school female students from diverse regions and backgrounds in Lebanon. …

Fostering Engineering Identities And Attitudes Through Place-Conscious Learning Introduction, Rebekah Hammack, Miracle Moonga, Nicholas Lux, Paul Gannon

Journal of Pre-College Engineering Education Research (J-PEER)

Limited research focuses on how participating in place-conscious engineering affects students’ engineering identities and attitudes toward engineering. This explanatory sequential mixed methods study investigated the effect of engaging elementary school students in place-conscious engineering activities on their engineering identities and attitudes toward engineering. Twenty fourth grade students enrolled in a rural elementary school in the northwestern United States completed two place-conscious engineering activities: (1) after a local wildfire polluted the air with smoke and made it unhealthy for breathing, students designed and built air filters to prevent smoke from entering the homes of affected families residing in a nearby community, …

Robert S. Frasure Murder Trails Collection, 1915-2017, Robert Silas Frasure

Morehead State University Manuscripts Collections

No abstract provided.

When Disasters Trigger Cyber Vulnerabilities: Mapping Physical-Digital Interdependencies In Critical Infrastructure Systems, Dikshya Panta, Sicheng Wang, Aditya Sapkota, Prakash Ranganathan

Faculty Publications

Critical infrastructure (CI) systems such as power, water, communications, and emergency services are increasingly exposed to compound risks in which natural disasters and cyber incidents interact and amplify one another. Traditional risk assessments often isolate physical and digital threats, overlooking the cascading dependencies that emerge when operational stress, emergency reconfiguration, and adversarial exploitation coincide. This study conducts a 2019–2025 scoping review and introduces a Geographic Information System (GIS) driven six-stage disaster cyber compounding framework that characterizes, maps, and operationalizes compound risk across interdependent CI sectors. The framework integrates a common operating picture, analytic situational understanding, exposure mapping, threat-fingerprint encoding, detection …

Crystal Structures, Optical Behavior, And Magnetic Properties In Hydrated Lanthanide Iron Sulfates, Chole Jones, Silu Huang, Tyler L. Spano, Eric A. Gabilondo, Mohammed Al-Fahdi, Kara Trim, Mary Douglas, Rongying Jin, Andrew Miskowiec, P. Shiv Halasyamani, Ming Hu, Jie Ling

Faculty Publications

Single crystals of LnFe(SO₄)₃(H₂O)₂ (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Ho, Er, Tm; compounds 1–11) and LnFe(SO₄)₃(H₂O) (Ln = Tm, Yb, Lu; compounds 12–14) were synthesized under hydrothermal conditions. Single-crystal X-ray diffraction (SCXRD) analysis revealed that the dihydrated compounds (1–11) crystallize in centrosymmetric (CS) structures, with the lanthanide ions adopting eight-coordinate geometries. In contrast, the monohydrated compounds (12–14) exhibit noncentrosymmetric (NCS) structures, where the lanthanide ions are seven-coordinated. Vibrating sample magnetometry (VSM) confirmed that compounds 2, …

Raw Data Files Contributing To "Changes In Apoe And Timp-1 Expression Correlate With Outer Blood-Retinal Barrier Disruption In An In Vitro Model Of Retinal Aging", Elizabeth Vargis

Browse all Datasets

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. Unfortunately, the early stages of this disease are poorly understood, which has led to limited treatment options. Investigating normal changes in tissues eventually affected by AMD can further elucidate the mechanisms of disease progression and lead to novel therapeutic targets. The primary cell layer affected in AMD is the retinal pigment epithelium (RPE), which forms the outer blood-retinal barrier (oBRB). Beneath the RPE lies Bruch’s membrane, a proteinaceous layer that naturally thickens and stiffens with age. These changes to Bruch’s membrane are also implicated in RPE dysfunction and AMD …

Biopcm-Integrated Smart Façade For Hospitals: Thermal Performance Across Floor Levels In A Hot-Arid Climate, Aia A. Qindil, Esraa Elazab, Mohamed M. Shawky Abou Liela

Mansoura Engineering Journal

Hospitals are among the most energy-intensive building types because they operate around the clock and must maintain strict indoor environmental conditions, especially in hot-arid climates. Improving their performance calls for façade solutions that can store thermal energy effectively and help cut carbon emissions. This study evaluates the use of macro-encapsulated BioPCM® within the south façade of a high-rise hospital in Mansoura, Egypt, using dynamic simulations in DesignBuilder (EnergyPlus). The analysis focuses on two vertical levels, the third floor as a typical ward and the seventh floor as a rooftop ward, to investigate how elevation influences PCM performance, an aspect rarely …

Credit Card Fraud Detection Using Metaheuristic Techniques, Narges Sabry Anwer Mohammed, Mohammed Sabry Saraya, Amr M. Thabet, Labib M. Labib

Mansoura Engineering Journal

Credit Card Fraud Detection (CCFD) has become a critical challenge to financial security due to increasingly sophisticated fraudulent activities. This study investigates the effectiveness of Meta-Heuristic (MHT) optimization techniques in improving fraud detection (FD) through feature selection (FS) and model optimization. To address class imbalance, Random Under-Sampling (RUS) was applied. The selected feature subsets were evaluated using three machine learning (ML) classifiers—Decision Tree (DT), KNearest Neighbours (KNN), and XGBoost (Xgb-Tree)—across four benchmark datasets: European, Statlog (Australian Credit Approval), PaySim, and Credit Card Transactions Fraud Detection (CCTFD). Eleven binary MHT algorithms were implemented and compared. The comparative analysis shows that the …

Design And Analysis Of A Hybrid Energy Storage System For A Bldc Motor In Lightweight Electric Vehicles, Mohammed Turki Baidar, Yasir M. Y. Ameen

AUIQ Technical Engineering Science

Internal Combustion Engine (ICE) vehicles are being replaced by electric vehicles to decrease fossil fuel depletion, pollution, and the effects of global warming. However, in electric vehicles, the primary concern is battery power consumption and lifespan, which affects the driving range. This study presents a hybrid energy storage system (HESS) comprising a lithium-ion battery and super capacitor array, designed and simulated in MATLAB/Simulink to enhance the range and performance of lightweight electric motorcycles powered by 2.5 kW BLDC motors. A 16-cell super capacitor module (3V, 3000F per cell) achieving 187F total capacitance was integrated with a 44.4V battery through a …

Intrusion Detection In Cloud Computing Using Support Vector Machine And Fast Firefly Algorithm, Ayobami Taiwo Olusesi, Ignatius Kema Okakwu, Ayodeji Akinsoji Okubanjo, Ayo Isaac Oyedeji, Oluwaseyi Olawale Bello

AUIQ Technical Engineering Science

Cloud computing has become popular due to the ongoing developments in the Internet and technical advancements. Users are increasingly storing their Web resources and data in the cloud environment due to the convenience and reduced cost of cloud computing services. Data security is crucial to the development of communication systems in cloud computing. Since data in cloud storage environments needs to be protected from intruders, network security in cloud environment has grown significantly in importance in recent years. In order to address these challenges, there is a need for an intrusion detection system (IDS) that can effectively identify malicious attack …

Visual Relocalization Method Combining Region Classification And Local Feature Enhancement, Yining Wang, Yanli Liu, Guanyu Xing

Journal of System Simulation

Abstract: Visual relocalization tasks have important application value in fields such as digital twin and augmented reality. The current mainstream methods still face challenges such as mismatch between coordinate regression scale and receptive field and insufficient attention to local information. A visual relocalization method that combines region classification and local feature enhancement is proposed. The coordinate regression problem in large space is transformed into a multi-region classification problem and a coordinate regression problem inside a small scene, which significantly reduces the uncertainty of coordinate regression and makes the network globally have a large receptive field. A conditioning layer using deep …

Inverse Kinematics 3d Human Modeling Simulation Based On Multi-View Vision, Guoyu Fang, Yanze Li, Kai Chen, Xiaodong Zhao, Zizhuo Hu, Mingshi Yang, Wanqing Wu, Zichen Wang, Wenkai Guo

Journal of System Simulation

Abstract: In autonomous driving simulation and industrial virtual reality simulation, there is a high demand for accuracy and robustness in 3D human body modeling. However, current joint-based human modeling approaches suffer from issues such as continuous modeling jitter, local distortion, and poor adaptability to occlusion, which degrade model quality and limit the development of practical applications such as intelligent driving and digital factories. To address these challenges, this paper proposes a multi-view vision-based inverse kinematics 3D human modeling method using a vector quantized variational autoencoder(IK-VQ-VAE). By integrating joint training with an automatic variational gradient descent approach, the proposed method achieves …

Pdr-Stgcn: An Enhanced Stgcn With Multi-Scale Periodic Fusion And A Dynamic Relational Graph For Traffic Forecasting, Jie Hu, Bingbing Tang, Langsha Zhu, Yiting Li, Jianjun Hu, Guanci Yang

Faculty Publications

Accurate traffic flow prediction is a core component of intelligent transportation systems, supporting proactive traffic management, resource optimization, and sustainable urban mobility. However, urban traffic networks exhibit heterogeneous multi-scale periodic patterns and time-varying spatial interactions among road segments, which are not sufficiently captured by many existing spatio-temporal forecasting models. To address this limitation, this paper proposes PDR-STGCN (Periodicity-Aware Dynamic Relational Spatio-Temporal Graph Convolutional Network), an enhanced STGCN framework that jointly models multi-scale periodicity and dynamically evolving spatial dependencies for traffic flow prediction. Specifically, a periodicity-aware embedding module is designed to capture heterogeneous temporal cycles (e.g., daily and weekly patterns) and …

Cross-Domain Crowd Counting Model Based On Frequency Domain Enhancement, De Zhang, Zishan Liang, Ningning Liu

Journal of System Simulation

Abstract: Crowd counting takes video surveillance data as input and can be applied to the construction of city digital twin platforms, virtual city modeling and smart city management, etc. However, when there are data domain differences between the application scenario and training scenario, counting performance often significantly decreases. A cross-domain crowd counting model based on frequency domain enhancement is proposed. To alleviate the distribution differences between domains, a frequency domain feature enhancement module and a domain invariant frequency domain adapter module are constructed: the former uses discrete cosine transform to extract key statistical features to enhance spatial representation ability, while …

Fatigue Crack Length Estimation Using Acoustic Emissions Technique-Based Convolutional Neural Networks, Asaad Migot, Ahmed Saaudi, Roshan Joseph, Victor Giurgiutiu

Faculty Publications

Fatigue crack propagation is a critical failure mechanism in engineering structures, requiring meticulous monitoring for timely maintenance. This research introduces a deep learning framework for estimating fatigue fracture length in metallic plates through acoustic emission (AE) signals. AE waveforms recorded during crack growth are transformed into time-frequency images using the Choi–Williams distribution. First, a clustering system is developed to analyze the distribution of the AE image-based dataset. This system employs a CNN-based model to extract features from the input images. The AE dataset is then divided into three categories according to fatigue lengths using the K-means algorithm. Principal Component Analysis …

Acknowledgement Of Reviewers

Journal of Sustainable Mining

No abstract provided.

Assessing The Student Awareness To Age Friendly Design: The Case Of Ain Shams University- Architecture Students, Shorouk Saleh Ali Kabel, Samah Mohamed Elsayed Atteia Elkhateb, Rowaida M. O. Mohamed Rashed, Wesam M. El-Bardisy

HBRC Journal

With Egypt’s rapid urbanization and projected demographic shift, where individuals aged 60 and above are expected to constitute more than 15% of the population by 2050, addressing the needs of older adults in urban design has become increasingly urgent. Despite global recognition of the importance of age-friendly design, its integration into Egyptian architectural education remains limited, particularly concerning accessibility, safety, and inclusivity.

This study evaluates the level of awareness of Age-Friendly Design (AFD) principles among architecture students at Ain Shams University using a mixed-methods approach. Quantitative data were collected through an online questionnaire assessing students’ familiarity with the concept, while …

Performance-Based Seismic Design And Retrofitting Via Drift And Strain Criteria, Tharwat A. Sakr, Hanaa E. Abd-El-Mottaleb, Shrouk S. Kamel

HBRC Journal

In recent decades, the demand for seismic code updates has significantly increased. Performance-based seismic design (PBSD) is a modern approach to earthquake-resistant building construction. By using this technique, the designers can establish performance targets that satisfy the owner. Most codes rely on strength design that utilizes a design response spectrum, highlighting serviceability without addressing performance levels. In this paper, an appraisal for the incorporation of PBSD into the Egyptian Code is proposed using nonlinear static and dynamic analysis. At first, response spectrum charts for 72, 475, and 2475 years return periods (RP) were developed based on the Egyptian seismicity information. …

Place Personality And User Behaviour: Insights From Cairo’S Streets, Sara Sabahy, Zeina Elzein, Doaa Abouelmagd

HBRC Journal

A place’s personality is beyond the sum of its characteristics. It’s how people perceive it on a human level, hoping for a better understanding and seeking connection. This study aims to understand how people connect with public spaces to enhance the quality of urban life.

A place’s personality extends beyond its physical attributes—it reflects how people emotionally perceive and connect with it. This study investigates the relationship between the perceived personality of urban streets and users’ behaviour to enhance the quality of urban life in Cairo. Focusing on Downtown Cairo and New Cairo, it addresses a gap in destination personality …

Theoretical Analysis Of Mir-Based Differential Photoacoustic Spectroscopy For Noninvasive Glucose Sensing, Tasnim Ahmed, Khan Mahmud, Md Rejvi Kaysir, Shazzad Rassel, Dayan Ban

Electrical and Computer Engineering Faculty Research

Diabetes is a developing global health concern that cannot be cured, necessitating frequent blood glucose monitoring and dietary management. Photoacoustic Spectroscopy (PAS) in the mid-infrared (MIR) region has recently emerged as a viable noninvasive blood glucose monitoring technique. However, MIR-PAS confronts significant challenges: (i) Water absorption, which reduces light penetration, and (ii) interference from other blood components. This paper systematically analyzes the background of photoacoustic signal generation and proposes a differential PAS (DPAS) in the MIR region for removing the background signals arising from water and other interfering components of blood, which improves the overall detection sensitivity. A detailed mathematical …

Exploitation Prioritization And Residual Risk Assessment Based On Hybrid Mcdm Model, Zibo Wang, Yaofang Zhang, Sicai Lv, Yingzhou Wang, Hongri Liu, Bailing Wang

Turkish Journal of Electrical Engineering and Computer Sciences

Exploitation is one of the most significant ways to launch attacks using vulnerabilities. The increasing number of vulnerabilities and limited allocation of security resources make it impossible to eliminate all exploitations. Because not every vulnerability can be fixed, it is necessary to rank exploitations and subsequently assess the residual risk, which is defined as the remaining threat potential after each elimination. In this paper, a structured and flexible decision support framework based on a hybrid multicriteria decision-making model is proposed for prioritizing exploitations and assessing residual risk. Metrics are treated as criteria in the model. The hybrid model is developed …

A Deep Learning-Based Real-Time No-Reference Image Decolorization Network With Perceptual Preservation, Mengjuan Zhao, Yitao Liang, Weiya Shi, Juan Xia

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, grayscale images are preferred as input data for some specific vision tasks. Decolorization is the transformation of a color image into a grayscale image. Efficient decolorization algorithms can improve the overall task efficiency, while perceptual preservation in decolorization can provide more information for further processing. In recent research, traditional methods focus on preserving contrast or detail information with little attention to perceptual features. Deep-learning methods are beginning to consider perceptual preservation, but they run inefficiently. In addition, the decolorization methods lack the optimal target grayscale images for reference. Therefore, we propose a new deep learning-based real-time no-reference decolorization network …

Noninvasive Condition Monitoring For Eccentricity Fault Detection In Large Hydro Generators, Atena Tazikeh Lemeski, Di̇dem Tekgün, Ozan Keysan, Kemal Leblebi̇ci̇oğlu, Murat Göl

Turkish Journal of Electrical Engineering and Computer Sciences

Eccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in Türkiye. The effects of DE faults on the SPSG’s magnetic equivalent circuit parameters are then examined under various fault severities. A …

A Deep Learning Model For Accurate Tomato Leaf Disease Identification, Maheen Shahzad, Muhammad Abdullah Javed, Erum Ashraf, Hafiz Ishfaq Ahmad, Sabeen Masood

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in machine learning and deep learning have greatly improved how we detect plant diseases, making diagnoses more accurate, faster, and easier to scale. However, many existing solutions depend on large, pretrained models that need powerful hardware, which limits their use in the field, especially in areas with limited resources. To tackle this, we designed a custom lightweight convolutional neural network (CNN) built from scratch using 20,000 carefully selected images from the PlantVillage tomato dataset. Our model uses Squeeze-and-Excitation (SE) blocks and Swish activation functions to boost performance, reaching an accuracy of 97.7% while using far fewer computing resources …

Influence Of Sinr And Noise Variance On Outage Probability For Mimo-Noma System In 5g And Beyond, Sadiq Ur Rehman, Jawwad Ahmed, Muhammad Zubair, Syed Sajjad Hussain Rizvi

Turkish Journal of Electrical Engineering and Computer Sciences

Nonorthogonal multiple access (NOMA) communication presents a promising solution to the limitations of traditional orthogonal multiple access techniques, offering potential improvements in achievable rates. Multiple-input multiple-output (MIMO), when combined with NOMA (MIMO-NOMA), further enhances these benefits by leveraging the diversity advantages of multiple antennas. Looking ahead, the future of wireless communication hinges on deploying heterogeneous networks (HetNets), facilitating the coexistence of various wireless access networks in a hierarchical fashion. However, the advent of 5G and 6G communications brings shorter channel coherence times, rendering channel reciprocity unreliable. Consequently, conventional channel estimation methods relying on uplink (UL) pilots for downlink (DL) transmission …

A Novel Approach To Maximum Weighted Traffic Flow Method For Effective Signal Control, Zülal Hi̇lal Yildiz Budak, Seyi̇t Alperen Çeltek, Aki̇f Durdu

Turkish Journal of Electrical Engineering and Computer Sciences

Traffic signal management is a critical challenge due to its environmental, economic, and public health impacts. The maximum weighted flow method (MaxWeightedFlow) was developed to optimize traffic flow at isolated and coordinated urban intersections. This study proposes a new method, the novel MaxWeightedFlow, which includes two key strategies to enhance the classical approach. The first strategy reduces computational burden by estimating vehicle approach times based on instantaneous speeds, improving real-time performance. The second employs regression analysis to optimize the alpha parameter, representing the vehicle waiting coefficient. The proposed approach, the novel MaxWeightedFlow, was evaluated using real-world traffic data from Kilis, …

Improving Rail System Signaling Efficiency Through Ai-Based Driving Profile Generation: A Comparative Performance Analysis, Mehmet Taci̇ddi̇n Akçay, Abdurrahi̇m Akgündoğdu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a dataset comprising 3600 discrete operational snapshots (rather than continuous time-series data) derived from real-field operations is used to obtain a high-accuracy driving profile equation using a second-degree Polynomial Regression method. This equation demonstrates the model’s interpretability. The performance metrics obtained with the second-degree polynomial regression model’s equation are as follows: a coefficient of determination (R2) of 0.84, a Pearson Correlation Coefficient of 0.91, and an RMSE of 11.13. These results indicate the effectiveness of artificial intelligence-based approaches in improving the efficiency of the railway signaling system. The same dataset is also utilized with other machine learning …