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Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …

Evolving Towards Efficient Technologies In Power Systems: The Paradigm Of Energy Internet Survey, Dina Emad, Omar Abdel-Rahim, Tanemasa Asano, Sobhy M. Abdelkader

Mansoura Engineering Journal

The Energy Internet represents a significant advancement in the modernization and automation of electricity systems, offering a framework for future smart grids where all electrical devices are interconnected through energy routers. This system integrates advanced power electronics, information technology, and smart control technologies, enabling the accommodation of diverse energy sources and storage devices. With its bidirectional energy flow and sharing capabilities, the Energy Internet holds great promise for the future. However, several challenges must be addressed to fully realize this potential. This review provides an overview of the Energy Internet framework and explores key challenges, particularly those related to energy …

Blockchain In Smart Cities, Shamma Alnuaimi

Thesis/ Dissertation Defenses

This thesis explores the integration of blockchain technology with smart cities to enhance efficiency, transparency, and reliability. The basic principles of blockchain, its layered architecture, consensus protocols, and decentralized security are first reviewed. The thesis then highlights how blockchain features can be integrated with urban and energy systems. The research focuses on how token economy can be used with smart cities to promote individuals to engage in desired behaviors by employing blockchain-based incentive mechanisms that can encourage responsible energy consumption.

The FairChain test system was developed and tested using blockchain technology and the Internet of Things (IoT) to demonstrate the …

A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani

Turkish Journal of Electrical Engineering and Computer Sciences

Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …

Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed

Turkish Journal of Electrical Engineering and Computer Sciences

Spoken digit recognition (SDR), a type of supervised automatic speech recognition, is essential for various human-machine interaction applications, including banking operations, dialing systems, price extraction, and airline reservation systems. However, designing an effective SDR system presents several challenges, such as developing labeled audio data, selecting appropriate feature extraction methods, and creating high-performance models. To overcome these challenges, a novel approach for robust spoken digit recognition using an integrated log spectrogram convolutional neural network (ILS-CNN) has been proposed. The proposed work presents an efficient SDR method by taking advantage of a log spectrogram layer directly within the neural network to enhance …

Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev

Turkish Journal of Electrical Engineering and Computer Sciences

Monitoring the condition of engineering objects is one of the urgent tasks of industry, construction, and transport infrastructure. This article describes a system for condition monitoring and diagnostics of rail tracks in real time. Compared with other similar studies, the proposed system has the advantages of compactness, usability, scalability and versatility of application. The proposed monitoring system is based on an Nvidia Jetson Nano embedded computing board and also includes inertial sensor modules, a microphone, a geolocation module, communication modules, an SSD storage device, and a battery. The prototype of the diagnostic module is a portable device that can be …

Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power …

Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len

Turkish Journal of Electrical Engineering and Computer Sciences

A modernist technique, reconfigurable intelligent surface (RIS) provides outstanding signal reflection and amplification, making it highly valuable for upcoming communication systems. Besides, a major contributor is index modulation (IM), attaining superior spectral and energy efficiency, and achieving hardware sufficiency. The primary and novel contribution of this work is the derivation of a highly accurate, closed-form approximate expression for the average bit error rate (ABER) of an orthogonal frequency division multiplexing (OFDM)-IM system operating in the complex and challenging environment characterized by joint transmitter/receiver (Tx/Rx) in-phase and quadrature phase imbalance (IQI) and Weibull fading. This essential analytical achievement is facilitated by …

Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …

Predicting Simulation Times For Multiphase Thermal-Hydraulic Models, Andrew Yule, Andrew Taylor

SMU Data Science Review

Addressing the challenge of computationally intensive OLGA

simulations in the oil and gas industry, a machine learning framework is

developed for accurate runtime prediction. A specialized feature extraction

pipeline identifies key parameters—such as simulation time, time step,

number of branches, and section count—from OLGA input files that serve as

high-impact predictors. Multiple predictive models, including regression,

tree-based ensembles, and neural networks, are implemented to validate

accuracy and robustness. Results reveal that prioritizing simulations based on

predicted runtimes optimizes licensing resources and reduces operational

costs, making real-time scheduling more efficient. This research demonstrates

the effectiveness of data-driven runtime prediction in enhancing …

Ai-Driven Optimization Of Wind Energy Distribution In Texas Using Multi-Agent Reinforcement Learning, Waleed Amer, Owolabi Oluwadamilola, Bassey Ogbonnaya

SMU Data Science Review

Abstract. The integration of large-scale wind power into modern electrical grids presents persistent challenges due to variability, curtailment, and compliance with operational constraints. This study proposes a multi-agent reinforcement learning (MARL) framework for optimizing wind energy distribution within the Texas power grid. The system employs three specialized agents—managing wind curtailment, storage utilization, and load adjustments—to collaboratively balance supply and demand under dynamic grid conditions. Using historical operational data from the Electric Reliability Council of Texas (ERCOT), the framework was trained and evaluated on a range of scenarios encompassing both typical and extreme operating conditions. Results demonstrate substantial performance improvements compared …

Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud

Faculty Articles

Hybrid energy storage systems (HESS) integrating batteries and supercapacitors offer a promising solution to overcome the limitations of battery-only architectures in electric vehicles (EVs). By leveraging the high energy density of batteries and the high power density of supercapacitors, HESS can enhance power delivery, improve energy efficiency, and extend battery lifespan. The effectiveness of HESS, however, is largely determined by the energy management system (EMS) that coordinates power flow under dynamic driving conditions. Unlike existing reviews, this work addresses common gaps in the literature, including the lack of industrial energy storage component examples, limited coverage of recently developed EMS strategies, …

2025 - The Sixth Annual Fall Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Fall 2025 Symposium of Student Scholars, held in November 2025. Includes abstracts from the presentations and posters.

Yolo-Based Marine Search And Rescue Using Uav Multi-Dataset In Challenging Weather Conditions, Aysha Alshebli

Thesis/ Dissertation Defenses

Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.

Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …

Plan To Fail By Failing To Plan: Deterring Prc Nuclear Force Expansion, Mark Tang, Grace Buettner

Space and Defense

This article argues that the United States must adapt its nuclear deterrence strategy to counter the People’s Republic of China’s (PRC) accelerating nuclear force expansion. As Beijing seeks to achieve nuclear parity with Washington—projecting up to 1,500 warheads by 2035—the authors contend that U.S. strategy must evolve from Cold War-era models to meet the Indo-Pacific’s unique strategic challenges. They propose the establishment of a Pacific Air Forces (PACAF) A-10 Strategic Deterrence and Nuclear Integration Division, modeled after its European counterpart, to enhance regional nuclear planning, integration, and allied assurance. The paper emphasizes the concept of escalation domination, arguing …

Earth’S Orbital Prison: Codifying Customary Law To Prevent Environmental Catastrophe In Space, Jacob Cook

Space and Defense

This article argues that the accelerating proliferation of space debris in low Earth orbit (LEO) poses an existential threat to the sustainability of the orbital environment—one comparable in strategic gravity to nuclear deterrence during the Cold War. Drawing on liberal internationalist theory and the concept of Mutually Assured Destruction (MAD), the paper asserts that deliberate satellite destruction through anti-satellite (ASAT) testing and negligent debris generation risk triggering a self-sustaining cascade of collisions known as the Kessler Syndrome. Existing treaties, including the Outer Space Treaty and the Artemis Accords, lack enforceable mechanisms to prevent such catastrophic harm. To fill this …

Enabling The Decisive Advantage, Mallory Stewart

Space and Defense

In her keynote address at the 2025 USSPACECOM Legal Conference, former Assistant Secretary of State Mallory Stewart argues that law, norms, and international cooperation are central to maintaining the United States’ “decisive advantage” in outer space. She emphasizes that rules and standards—far from constraining innovation or strategic flexibility—enhance predictability, reduce risk, and empower responsible competition. Stewart highlights the success of initiatives such as the Artemis Accords, the U.S. commitment to forgo destructive direct-ascent anti-satellite (ASAT) tests, and the global expansion of Space Situational Awareness (SSA) agreements as examples of how legal and normative frameworks reinforce stability and collaboration. She …

Space, Law, And National Security, Stephen Whiting

Space and Defense

In his address to the 2025 USSPACECOM Legal Conference, General Stephen Whiting underscores the indispensable role of legal professionals in shaping the future of military space operations and maintaining the rules-based international order in an increasingly contested domain. He outlines the rapid transformation of the space environment driven by commercial innovation, technological proliferation, and the accelerating threat landscape posed by adversaries such as China and Russia. The speech highlights U.S. Space Command’s three “moral responsibilities”: ensuring the delivery of space capabilities to the joint force and allies, protecting and defending critical space assets, and safeguarding the joint force from space-enabled …

In Defense Of Space Offense, Alexander R. Kleitz

Space and Defense

This article argues that in the unique physical and operational environment of outer space, offensive operations hold intrinsic advantages over defensive ones. Drawing upon classical military theorists such as Clausewitz and Corbett, the author contends that the traditional dominance of the defensive form of war—rooted in terrestrial conditions—does not extend to celestial conflict. The transparency and remoteness of the space domain neutralize key defensive benefits, such as proximity to supply bases, concealment, and fortified positions, while also diminishing the factors that typically cause terrestrial offensives to culminate. Consequently, space conflict favors the side that seizes and maintains the initiative through …

Raising Public Awareness On Space Themes: Analysis Of Brazilian Space Policy Using Data From Google Trends, Andrea Felippe Cabello, Michele Melo

Space and Defense

This study examines whether Brazil’s national space policy goal of increasing public awareness of space activities has been met, using Google Trends data as a proxy for public interest. While public perception surveys are scarce outside the United States, web-based data provide a cost-effective and timely alternative for gauging public engagement. The authors analyzed two decades (2004–2024) of Brazilian search activity related to space topics, institutions, technologies, companies, and missions. Results show no clear upward trend in public interest, suggesting that Brazil’s stated policy objectives of raising awareness have not yet translated into measurable outcomes. Although searches related to government …

Costly Signals In Space: Increasing Credibility Via Strategic Disclosure, Wendy N. Whitman Cobb

Space and Defense

As space becomes an increasingly vital domain for national security, debates persist about how much secrecy should surround U.S. military space programs. This article argues that the strategic declassification and disclosure of selected space capabilities can strengthen U.S. deterrence by enhancing the credibility of deterrent threats. Drawing from theories of costly signaling and audience costs, the paper introduces strategic disclosure as a novel form of costly signal. Such disclosure imposes bureaucratic and operational costs while exposing capabilities to potential adversary countermeasures—thereby demonstrating resolve and seriousness of intent. In tandem, greater public transparency about space programs cultivates informed domestic audiences capable …

Space & Defense Volume 16 Issue 2 Fall 2025 (Whole Issue), Editors Space And Defense

Space and Defense

No abstract provided.

Turboindex: Making A Page-Based Db Index Both Memory-Space And Disk-I/O Efficient, Sujit Maharjan, Shuaihua Zhao, Song Jiang

Computer Science and Engineering Faculty Publications - Archive

Traditional Database (DB) systems use a DB buffer, a page-based cache management system, to load data and indexes from block storage devices into byte-addressable main memory. However, this approach is inefficient in terms of space and I/O when key-value pair sizes are significantly smaller than the page size. Inserting a single key-value pair results in reading and writing an entire page, consuming a full page's worth of memory in the buffer. Moreover, the entire page is immediately loaded even when just a single key-value pair is inserted into the page. Also, an infrequently accessed page is likely to be evicted …

Mechanisms Of Correlated Neuronal Activity In The Globus Pallidus, Hamza Albawaliz

Electronic Theses and Dissertations

This thesis investigates the mechanisms of correlated neuronal activity in the globus pallidus externus (GPe), a key structure in the basal ganglia. Neuronal activity in the GPe is reportedly decorrelated in healthy subjects but can become highly correlated in Parkinson’s disease. However, high-density neuronal recordings in the GPe of healthy rats reveal a surprising degree of correlated activity. This raises the question of whether intrinsic properties or network connectivity alone can account for such patterns. To explore this, a computational model was developed in which GPe neurons are represented as coupled phase oscillators influenced by experimentally derived phase-response curves and …

Parentcoach: Designing An Mhealth Parenting App To Enhance Parental Involvement In Adhd Support, Franceli L. Cibrian, Nancy Herrera, Jesus A. Beltran, Lucas M. Silva, Mikaela Pulse, Kayla Anderson, Cassie Zeiler, Luc Rieffel, Daniel I. Lee, Sabrina E. B. Schuck, Kimberley D. Lakes

Engineering Faculty Articles and Research

Introduction: Parents play a vital role in supporting self-regulation and managing behaviors in children with Attention-Deficit/Hyperactivity Disorder (ADHD). However, many face barriers to accessing consistent, evidence-based support. Mobile health (mHealth) technologies offer a promising way to deliver flexible, low-burden guidance for parents on best practices and strategies to support their children's self-regulation. However, designing them is non-trivial.

Objective: This paper introduces ParentCoach, a mobile application designed to support parents of children with ADHD through brief daily lessons, reflection prompts, and skill-building activities.

Methods: ParentCoach was developed in two phases: (1) secondary analysis of qualitative data from over 30 families …

Characterization And Evaluation Of Next-Generation Photon-Counting Image Sensors For Space Applications, Nicholas Shade, Gillian Kyne, Shouleh Nikzad, Edoardo Charbon, Eric R. Fossum

Dartmouth Scholarship

Astronomers’ pursuit of imaging light from increasingly faint and distant objects in the expanse of space necessitates continuous improvement in the signal-to-noise ratio of camera technology. Recent advancements in solid-state detector technologies have enabled the determination of photon number, including single-photon events, enabling observations at the fundamental limits of physics. We present an evaluation of three next-generation silicon-based detectors capable of photon-counting with deep-sub-electron input-referred read noise: the electron-multiplying charge-coupled device (EMCCD), the single-photon avalanche diode (SPAD), and the CMOS quanta image sensor (QIS). The EMCCD is built using a CCD sensor design that additionally employs repeated impact ionization to …

Experiential Learning And The Revitalization Of Manufacturing Education At The University Of Dayton, Sean Cahill

Research and Reflection on Learning and Teaching in Higher Education

This perspective paper explores the role of experiential learning in preparing future-ready manufacturing engineers at the University of Dayton, set against the backdrop of Dayton’s legacy as an industrial innovator and the broader national movement to revitalize domestic manufacturing. As automation, cyber-physical systems, and Industry 4.0 technologies reshape the manufacturing landscape, there is a growing need for engineers who possess both technical fluency and systems-thinking capabilities. To meet this need, the manufacturing engineering technology department implemented hands-on, integrated lab-and-lecture modules through support from the Experiential Learning Innovation Fund for Faculty (ELIFF). Grounded in Kolb’s Experiential Learning Theory and constructivist learning …

Microgrid Black Start Challenges: The Role Of Grid-Forming Inverters, Gab-Su Seo, Wenzong Wang, Behrooz Mirafzal

Faculty Publications

Grid-forming (GFM) inverters are becoming increasingly important for future power systems, particularly in establishing and restarting microgrids after blackouts. The use of GFM inverters enables microgrids to operate independently of utility power and provide key advantages over synchronous generators in black start scenarios, including rapid startup and stable voltage and frequency support for critical loads. However, inverter-driven black start introduces unique challenges and operational considerations. This article examines key challenges and solutions, emphasizing inverter design, control strategies, and microgrid system requirements. Drawing on analysis, simulation, and experimental results, this article highlights the central role of GFM inverters in ensuring reliable …

Recognition Of Bangla And English Words In Bengali Texts Using A Modified Bert-Base-Ner Model, Md Parvez Hossain, Ohidujjaman Ohidujjaman, Mohammad Shorif Uddin, Mohammad Nurul Huda, Tetsuya Shimamura

Iraqi Journal for Computer Science and Mathematics

A fusion of Bangla and English words is frequently utilized, especially on social media. This phenomenon significantly hampers the learning and preservation of the Bengali language among future generations. This paper proposes a model to recognize Bangla and English words in Bengali texts. In addition, this study converts the detected English words into standard Bangla words. In this work, we redesign the BERT-base-NER model using the training input dataset. BERT is chosen for its strong contextual representation capabilities, which are well-suited to noisy and informal text. BERT-base-NER provides strong contextual embeddings but treats token labels independently, lacking explicit modeling of …

Data-Centric Ai For Eeg-Based Emotion Recognition: Noise Filtering And Augmentation Strategies, Nadieh Moghadam, Rana Hegazy

School of Engineering: Faculty Scholarship

Research in the biomedical field often faces challenges due to the scarcity and high cost of data, which significantly limit the development and application of machine learning models. This paper introduces a data-centric AI framework for EEG-based emotion recognition that emphasizes improving data quality rather than model complexity. Instead of proposing a deep architecture, we demonstrate how participant-guided noise filtering combined with systematic data augmentation can substantially enhance system performance across multiple classification settings: binary (high vs. low arousal), four-quadrant emotions, and seven discrete emotions. Using the SEED-VII dataset, we show that these strategies consistently improve accuracy and F1 scores, …