Digital Commons Network^™

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 …

Pl-Mamba: A 3d Point Cloud Semantic Segmentation Network Based On Bimodal Fusion, He Zhu, Feng Zhou, Mengxiao Zhu, Ju Dai

Journal of System Simulation

Abstract: To enhance the semantic discrimination capability in point cloud semantic segmentation, a 3D point cloud semantic segmentation network named PL-Mamba is proposed, which is centered on the fusion of point cloud (P) and language (L) dual modalities. This method takes PointMamba as the backbone network, leveraging its excellent long-sequence modeling and global perception capabilities. It introduces a language prompt mechanism and uses a pretrained language model BERT to encode the context of category labels, obtaining semantically rich text features. The text information serves as a language guided token and is deeply integrated with point cloud features through cross modal …

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 …

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 …

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 …

Distribution System Reliability Evaluation Considering Protection Coordination Using Petri Nets, Rani Kumari, Bhukya Krishna Naick

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining reliable and high-quality power delivery becomes increasingly complex with expanding power grids. The lack of protection coordination poses a significant threat, compromising overall system reliability. This research addresses this challenge by proposing a method for coordinating protective devices within the distribution system, specifically during network faults. The proposed approach utilizes a stochastic timed Petri net (STPN) based methodology to model protective device coordination across various fault scenarios. This technique effectively captures the dynamic behavior and interactions of protective equipment, allowing for the anticipation of potential disturbances. This proactive insight facilitates preventative measures to address prewarning situations, thereby preventing cascading …

Why Agtech Startups Fail? Evidence From Global Shutdown Patterns In 2025 And The Cost-Adoption Mismatch Effect, Ankit Chandra, Ishani Lal

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural technologies are widely seen as a driver for sustainability, resilience, and food-system transformation. Yet in 2025, agtech startup across North America, Europe, Asia, and Africa experienced multiple shutdowns. Although each company closed for its own reasons, the failures highlight consistent underlying patterns. We analyze 18 publicly reported shutdowns across controlled-environment agriculture (CEA), robotics, insect protein, digital platforms, sensors, and ag-biotechnology. We find that most ventures struggled not with scientific feasibility but with economic and adoption dynamics at the farm level. We identify a Cost-Adoption Mismatch Effect, in which the capital and operational burden of a technology exceeds farmers’ capacity …

Distributed Model Predictive Control-Based Power Management Scheme For Grid-Integrated Microgrids, Sergio Escareno, Sijo Augustine, Liang Sun, Sathishkumar J. Ranade, Olga Lavrava, Enrico Pontelli, John Hedengren

Faculty Publications

Transitioning from traditional electrical grids to smart grids is currently an ongoing process that many nations are striving for due to their access to renewable resources. Energy management is one of the key parameters that decides the performance of such complex systems. Distributed Model Predictive Control (DMPC) is a promising technique that can be used to improve the energy management of grid-connected systems. This paper analyzes a grid-connected inverter system with DMPC that exchanges key operating parameters with the grid to optimize coordinated power sharing between its respective loads. The state-space model for the inverter is derived and verified to …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

Novel Repurposing Of Empagliflozin-Loaded Buccal Composite (Chitosan/Silk Fibroin/Poly(Lactic Acid)) Nanofibers For Alzheimer’S Disease Management Via Modulation Of Aβ–Ager–P-Tau Pathway, Samar A. Salim

Nanotechnology Research Centre

Background/Objectives: Empagliflozin (EMPA) was repurposed for Alzheimer’s disease (AD) treatment via buccal delivery, exploiting novel nanofibers (NFs) integrating chitosan (Cs), silk fibroin (Fb), and poly(lactic acid) (PLA). Methods: EMPA-loaded Cs/Fb/PLA NFs were electrospun in different formulations to optimize the formulation parameters. The optimized formulation was then investigated for its enhanced in vivo effect. Results: Optimized nanofiber diameters ranged from 459 ± 173 to 668 ± 148 nm, possessing bead-free morphology confirmed by SEM and satisfactory mechanical properties. EMPA was successfully well-dispersed in the polymer matrix as evidenced by FTIR, XRD, and drug content. The optimized NFs displayed a hydrophilic surface …

An Investigation Of A Mach 15 Flow Over A Blunt Wedge Using First-Principles Potential Energy Surfaces: Influence Of Wall Temperature, Paolo Valentini, Zach Davis, Maninder S. Grover, Nicholas J. Bisek

Space Dynamics Laboratory Publications

The simulation of a Mach 15 air flow over a blunt wedge is conducted using the direct molecular simulation (DMS) method. Due to partial dissociation of the air mixture at the imposed free stream conditions, the shock layer contains N₂, O₂, NO, N, and O. All potential energy surfaces (PESs) used to model the various molecular interactions only describe electronic ground states energetics. Thus, no electronic excitation is modeled. An isothermal wall boundary condition is imposed, with full momentum and energy accommodation. Two wall temperatures are considered in this work, namely 1,000 K and 2,000 K. …

Combinatorial Synthesis Of Protein-Polymer Conjugates By Post-Polymerization Modification Of Poly(Pentafluorophenyl Acrylate)S, Emily W. Kish, Thatcher M. Lee, Alexis M. Ziemba, Ama Boamah, Bianca Figueroa, Margherita Piccardi, Carey E. Dougan, Sarah J. Moore, Maren E. Buck

Chemistry: Faculty Publications

Combinatorial methods for preparing polymeric biomaterials enable the rapid identification of materials useful for many applications in science, medicine, and engineering. In the work described here, we demonstrate that side-chain reactive polymers can be used as templates for the rapid preparation of a small library of diversely functionalized protein–polymer conjugates. The activated ester polymer poly(pentafluorophenyl acrylate) (PPFPA) was modified postpolymerization with substoichiometric equivalents of three hydrophilic primary amines to yield a library of amphiphilic, side-chain reactive copolymers. These copolymers were then conjugated to two receptor-targeting proteins, holotransferrin (hTF) and an engineered fibronectin-based protein (Fn3), through amine-activated ester coupling. We investigated …

A Contextual Attention-Based Transformer Model For Enhanced Hate Speech Detection On Twitter, Mira Mansour, Nancy Akoum, Seifedine Kadry

Iraqi Journal for Computer Science and Mathematics

Hate speech on social media poses significant societal challenges, necessitating accurate and context-sensitive automated detection. Traditional machine learning (ML) models typically rely on lexical or superficial features, limiting their ability to capture nuanced or contextually ambiguous expressions of hate speech. Recent transformer-based methods (e.g., RoBERTa) provide improved contextual understanding but often lack explicit mechanisms guiding the model’s attention to critical semantic tokens, thereby reducing interpretability and sensitivity to nuanced linguistic contexts. This paper introduces a novel contextual attention-guided transformer model that explicitly incorporates lexicon-guided attention supervision into RoBERTa fine-tuning, significantly enhancing semantic precision in hate speech detection on Twitter. Evaluations …

Numerical Solution Of A Coupled Nonlinear Dynamic Problem Of Thermoviscoelasticity, Abdali Abdukarimov, Ibodat Turabekovna Khaldybaeva, Askarova Shamshetdinovna Ayjamal

Technical science and innovation

This paper presents a numerical solution of a coupled nonlinear dynamic problem of thermoviscoelasticity. A Duffing-type oscillator with temperature-dependent properties is used to model nonlinear hereditary deformable systems. After specifying the temperature dependences of the elastic modulus 𝐸 and viscosity parameter 𝜂 and introducing dimensionless variables, the problem is reduced to a system of nonlinear integro-differential equations. A numerical procedure for solving this system is developed, and representative examples are computed. The results are presented in graphical form for various values of the governing parameters.

Pengujian High Fidelity Prototipe Media Pembelajaran Interaktif Bahasa Inggris Dengan Gamifikasi Menggunakan User Experience Questionare, Adhitya Prastyadi, Meizano Muhammad Ardhi, Daniel Rinaldi, Margaretha Karolina Sagala

Jurnal Sosial Humaniora Terapan

Abstract

Testing a Hi-Fi Prototype of Interactive English Learning Media with Gamification Using UEQ

This study aims to test and evaluate the User Experience (UX) quality of a High-Fidelity prototype for interactive English learning media integrating gamification elements. The research is motivated by the low English proficiency and motivation among Indonesian students, and the potential of digital media and gamification to enhance learning engagement. Inspired by the success of the Duolingo application, this prototype was designed to create an enjoyable and effective learning experience. A quantitative research methodology was employed, involving high school students as participants selected via purposive sampling. …

Exploring The Role Of Occupational Therapy In The Delivery Of Trauma-Informed Services To Hospital-Based Clients Ot, Frank Czuba

Journal of Applied Disciplines

Hospitalization can traumatize clients and impact overall health outcomes, leading to increased hospital readmission rates and resulting in a negative impact for both clients and providers. Limited information exists regarding how hospital-based occupational therapists evaluate and address trauma, even though incorporating trauma-informed principles into professional practice can enhance the occupational therapy process. The study explored the comprehension and perceived significance of trauma-informed tenets among occupational therapists delivering services in hospital-based settings. A quantitative research study with an exploratory design was implemented to explore how occupational therapists (OT) understand and utilize trauma-informed practices with their clients in a hospital setting. An …

Multivariate Stochastic Mine Scheduling Targeting Stationary Grades Considering Risk Uncertainty And Hierarchical Variables, Augusto A. T. Toledo, Joao F. C. L. Costa, Diego M. Marques, Luciano N. Capponi

Journal of Sustainable Mining

In short-term mine planning for deposits characterized by multiple variables, sequential diglines are generated with an emphasis on maintaining consistent grade distributions across mining periods. This research integrates an array of mineral variables, including deleterious elements, to facilitate the establishment of excavation geometries that enable precise grade and volume control within operational production zones. Through the systematic application of geostatistical analysis coupled with process optimization, geological risks associated with grade uncertainties are minimized, and an optimized operational sequence for the extraction of mineral blocks is pursued. The main point of this approach is maintaining grade distributions aligned with the historical …

Assessment Of Heavy Metal Contamination In Surface Water Near Tailings Dam, Gera Techane Mengistu, Tesema Kebede, Enatfenta Melaku, Engdasew Temere

Journal of Sustainable Mining

Elevated levels of heavy metals in surface water can lead to the degradation of water quality, especially in mining areas where tailing dams are sources of heavy metal pollution. This study focuses on evaluating the concentrations of heavy metals in surface water near the Legadembi tailings dams. The mean concentrations (in µg/L) of various heavy metals including: arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), molybdenum (Mo), nickel (Ni), lead (Pb), antimony (Sb), selenium (Se), thallium (Tl), uranium (U), vanadium (V), tungsten (W), zinc (Zn), and zirconium (Zr) were determined: 79.7, 0.15, 162.3, 0.66, 18.1, 0.01, …

Investigating Frozen Paste Surface Disposal As A Climate Change Adaptation Strategy: Case Study Of Mont-Wright Mine, Khalil Hashem, Agus P. Sasmito, Laxmi Sushama, Ferri Hassani, Mehrdad Kermani

Journal of Sustainable Mining

The mining industry faces evolving challenges in adapting to the impacts of climate change. Among these challenges is the management of tailings. This study focuses on investigating surface disposal of non-cemented paste tailings, particularly the effect of water content, freeze-thaw cycles (FTC, defined as freezing the sample to –20°C and thawing it to +20°C), and ambient temperature on the mechanical characteristics and thermophysical properties of paste tailings. The potential for maintaining non-cemented tailings in a frozen state year-round is also investigated through field-scale numerical simulations. Experiment results of thermophysical properties of tailings with water content, freeze-thaw cycles and ambient temperatures …

Toward Sustainable Water Security: A Novel Assessment And Recharge Strategy For North Bekaa Plain, Rida Tadmouri, Amin Shaban, Mohamad Soliman

BAU Journal - Science and Technology

The demand for water in the northern Bekaa Plain is of utmost significance, especially given the substantial portion of land dedicated to irrigated agriculture. Additionally, the region experiences population growth, further exacerbating the water supply challenge. Understanding the groundwater potential zones and identifying appropriate recharge areas are crucial steps towards sustainable water resource management. The study focuses on reaching the best solutions for the study area, by utilizing advanced Geographic Information System (GIS) tools, including overlying slope, rainfall, lithology, attitude, soil, fracture, and stream maps, a Groundwater Potential (GWP) map was generated using ArcGIS. This map serves as a valuable …

Ai In Society: A Regulatory Framework For Responsible Integration, Ziad Doughan, Sari Itani, Hadi Al Mubasher

BAU Journal - Science and Technology

This review paper studies the influence of Artificial Intelligence (AI) and Machine Learning (ML) on society in various categories in detail. AI and ML have developed rapidly in the past two decades, thus changing our lifestyles. These developments have various positive and negative impacts on society. This paper explores the many societal impacts of AI and ML, in economics, social aspects, ethics, and policy, shedding light on the opportunities and challenges that arise. An interdisciplinary insight is capable of understanding the challenges society faces when it uses AI and ML, locking opportunities that lie ahead and identifying promising paths towards …

Data-Driven Prediction Of Concrete Bridge Deck Corrosion Using Ground Penetrating Radar (Gpr), Nafisa Shafiullah

Civil Engineering Theses

Corrosion detection remains a crucial factor in the proper maintenance of Reinforced Concrete (RC) structures. While several studies have used Ground Penetrating Radar (GPR) for corrosion detection, quantitative models for prediction are still limited. This study presents an approach for the quantitative prediction of rebar corrosion in concrete using GPR data obtained from a prior experimental program involving accelerated corrosion. A total of 36 RC samples were cast, varying in cover depth, rebar diameter, and concrete porosity. The samples were subjected to an impressed current of 0.65 A in a 5% NaCl solution over three phases: 10, 20, and 30 …

Comparative Finite Element Method-Based Optimisation Of Coir Fibre Laminates: Aluminium Skins Versus Carbon Cloth Skins, Muhamed Swaleh Ahmed, Bernard Wamuti Ikua, Abel Nyakundi Mayaka

Mansoura Engineering Journal

Natural fibre composites offer a sustainable alternative to conventional composite materials. Their mechanical efficiency is influenced by laminate structure and skin material selection. This study presents a comparative finite element analysis and optimisation of coir fibre-reinforced laminates employing either aluminium skins or carbon cloth skins. COMSOL Multiphysics was used to determine their mechanical response. Optimisation was performed using the BOBYQA algorithm to enhance load sharing between the coir core and skin materials. Results indicated that aluminium-skinned laminates achieve superior compressive and flexural performance, achieving a peak compressive strength of 210 MPa and sustaining a flexural load of 0.65 kN at …

Teleoperated Robotic Arm With Vision-Based Imitation Learning, Favour E. Emmanuel, Hunter J. Donahue

Williams Honors College, Honors Research Projects

This report presents the design, development, and deployment of a teleoperated robotic arm system capable of vision-based imitation learning. The system uses a leader-follower architecture with myArm C650 and myArm M750 robots manufactured by Elephant Robotics. The leader arm movement is controlled by the operator, whereas the follower performs actions acquired from demonstrations. Data collection included synchronized joint-angle recording and multi- camera video streams capturing human demonstrations.

These demonstrations were processed with a deep learning imitation algorithm called Action Chunking with Transformers (ACT). The main capability of this algorithm is its ability to make future action predictions based solely on …