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Notes For Contributors, Editors Space And Defense

Space and Defense

No abstract provided.

Review Article: International Relations: State Of The Field. Paul R. Viotti’S Kenneth Waltz: An Intellectual Biography (Ny: Columbia University Press, 2023)., Damon Coletta

Space and Defense

In this review essay, Damon Coletta examines Paul R. Viotti’s Kenneth Waltz: An Intellectual Biography (Columbia University Press, 2023), positioning it as both a tribute to and a reexamination of one of International Relations’ most influential theorists. Viotti, a former student of Waltz, reconstructs the intellectual development of structural realism—tracing its philosophical and methodological roots from Man, the State, and War (1959) to Theory of International Politics (1979)—while situating Waltz’s scholarship within the geopolitical and academic transformations of the Cold War era. Coletta highlights Viotti’s skillful balance between biography and disciplinary analysis, showing how Waltz’s systemic approach to international politics …

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 …

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 …

Reproducibility In Modeling Of Knee Joint Mechanics, Maryam Nazem

Electronic Theses and Dissertations

Computational modeling of knee joint biomechanics can provide valuable insights into joint function, injury mechanisms, and patient outcomes, and can support surgical planning and informed clinical decision-making. However, achieving consistent and repeatable results, or reproducibility, is a significant challenge that affects the credibility of these models. This thesis addresses reproducibility through two studies related to the KneeHub Project, which is a multi-institutional collaboration designed to investigate reproducibility in finite-element modeling of the knee.

The first study involved model benchmarking, where predicted results of the calibrated models were compared with the experimental data to evaluate model reproducibility. While all models replicated …

Guardrail Design And Placement 101, Katherine Smutzer

Civil Engineering Professional Development Seminar

Not all “guardrail” is created equal. Within the last 10 years INDOT has adopted the MASH-compliant Midwest Guardrail System (MGS). While similar to the previous standard w-beam guardrail, there are nuances that aren’t well understood by designers. The presentation would reinforce the fundamentals of guardrail as a safety barrier, explain the function of various components of a guardrail system, and review important design considerations.

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 …

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 …

Bending Energy Schemes For Discrete-Spring-Network Structural Modelling Of Red Blood Cells, Osayomwanbor Ehi-Egharevba, Mingzhu Chen, Fergal Boyle

Articles

Red blood cells (RBCs) undergo large structural deformation, including bending, when passing through capillaries. They also exhibit a range of complex shapes such as stomatocytes, discocytes and echinocytes that form due to altered blood pH and salt levels, ingested drugs and adenosine triphosphate depletion. Discrete-spring-network structural models of RBCs employ different numerical treatments of the continuum bending energy. This affects bending accuracy and the prediction of accurate RBC shapes. This research compares three representations called bending energy scheme (BES) A, B and C to evaluate their accuracy in shape predictions. BES A, seen throughout the literature, is based on the …

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, …

Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang

Journal of System Simulation

Abstract: Evolutionary reinforcement learning currently suffers from low sample efficiency, a single coupling method, and poor convergence, which can affect its performance and scaling. To address this issue, an improved algorithm based on elite gradient instruction and double random search was proposed. The direction of the reinforcement strategy gradient update was corrected by introducing elite strategy gradient guidance carrying evolutionary information during reinforcement strategy training. Double stochastic search was used to replace the original evolutionary component, reducing the complexity of the algorithm while making the policy search meaningful and controllable in the parameter space. The introduction of complete replacement information …

Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang

Journal of System Simulation

Abstract: To solve the problem of misidentification of star maps due to time sequence mismatch in the hardware-in-the-loop simulation system of star navigation, where star trackers with different shutter types (global shutter and rolling shutter) and star simulators with varying refresh display methods (whole frame refresh and line sweep refresh) operated without synchronization, a time sequence design method of the dynamic simulation scene for starlight navigation without the need of external synchronization signals was proposed. The method could design the refresh frequency and duty cycle of the corresponding star simulators according to the detector integration time of the tested star …

Implementation Strategies For Microservice Architecture In The Banking Sector, Gururaj Achar

Walden Dissertations and Doctoral Studies

Information technology (IT) leaders in regulated banking face significant risks related to system complexity and cybersecurity when implementing large-scale systems. Although microservice architecture (MSA) offers enhanced scalability and agility, IT leaders lack specific strategic guidance for its effective adoption within highly regulated banking environments. Grounded in the Technology Acceptance Model, the purpose of this qualitative, pragmatic study was to explore effective MSA adoption strategies for IT architects and managers transitioning legacy systems to support risk and compliance management. Data were collected through semistructured interviews with seven banking IT leaders and were analysed using thematic analysis. Three themes emerged: adoption drivers …

Mesopause-Region Gravity Wave Activity Due To Tropical Convection As Observed By Awe, Jeffrey M. Forbes, Xiaoli Zhang, Jiarong Zhang, Stephen D. Eckermann, Yucheng Zhao, Pierre-Dominique Pautet, Jun Ma, Ludger Scherliess, Michael J. Taylor

Space Dynamics Laboratory Publications

Mesopause-region (∼ 87 km) gravity waves (GWs) generated by tropical convection are investigated within the four longitude sectors encompassing Africa, the Indian Ocean, the Intertropical Convergence Zone, and South America during the Dec 2023– Feb 2024 Southern Hemisphere monsoon season. Variances (Q_v) in the OH Q-line emission measured by the Atmospheric Waves Experiment (AWE) capture GW activity, and precipitation rates (PR) from the Global Precipitation Measurement (GPM) Mission identify regions of convective activity. The zonal component of GWs comprising the Q_v between 10°S-10°N primarily propagate eastward. The Q_v distributions are latitudinally-shifted and more confined in …

Cybersecurity Risks Of Freight Rail As Critical Infrastructure, Kira Sun

Discovery Undergraduate Interdisciplinary Research Internship

Our project implements simulated train engineers to operate model train engines on a hybrid twin of a freight rail system. We can then use the model and simulate cyber-security attacks to demonstrate the risks and effects of the attacks. Using existing model train hardware and an Arduino running open-source software, DCC-EX and JMRI, we can control the train engines and various track components and sensors. We program each engine to make safe decisions about what speed and direction to take, using information provided by the various sensors and light signals around the track. When attacks occur, the engines can have …

Machine Learning Model For Detecting Masked Hypertension In Young Adults, Brendyn Miller, Samuel Coeyman, Annemarie Wentzel, Carina M.C. Mels, William J. Richardson

Chemical Engineering Faculty Publications and Presentations

Introduction Cardiovascular disease (CVD) remains the leading global cause of mortality, with hypertension (HT) being a significant contributor, responsible for 56% of CVD-related deaths. Masked hypertension (MHT), a condition where patients exhibit normotensive blood pressure (BP) in clinical settings but elevated BP in out-of-clinic measurements, poses an elevated risk for cardiovascular complications and often goes undiagnosed. Current diagnostic methods, such as ambulatory BP monitoring (ABPM) and home BP monitoring (HBPM), have limitations in feasibility and accessibility. Methods This study aimed to address these challenges by leveraging machine learning (ML) models to predict MHT based on clinical data from a single …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

Advanced Plant Growth Using Halloysite Nanotubes (Hnts) And Waste Extraction For Medical Applications, Zeinab Jabbari Velisdeh

Doctoral Dissertations

This dissertation presents an integrated research framework that bridges nanotechnology, green chemistry, and sustainable agriculture, aiming to address two critical global challenges: enhancing plant growth under resource-limited conditions and valorizing agricultural waste for bioactive compound extraction. The study is divided into three major projects that together highlight the innovative application of magnesium oxide-coated halloysite nanotubes (MgO-HNTs) and the development of environmentally conscious extraction methods for high-value phytochemicals. The first component of this work investigates the design, fabrication, and functional evaluation of MgO-HNTs as advanced nanocarriers for promoting seed germination and early root development in tomato plants. MgO-HNTs were synthesized via …

Investigation Of Electrochemical Corrosion Fatigue Mitigation Strategies For Mild Carbon Steel, Joel Andrew Hudson

Doctoral Dissertations

Corrosion fatigue remains a critical durability challenge for steels used in boiler tubes and other safety-critical components, where the interaction of cyclic stresses and corrosive environments accelerates material degradation. This dissertation comprises three experimental studies aimed at advancing mitigation strategies and test methodologies: (1) enhancing corrosion resistance through electrodeposited Fe-Ni anodic coatings, (2) inducing synthetic crack closure to suppress fatigue crack growth, and (3) developing an accessible, low-cost, automated testing system to investigate environmentally assisted cracking (EAC) under controlled laboratory conditions. The first study examined the corrosion behavior of Fe and Fe-Ni electrodeposits synthesized from sulfate-based baths and applied to …

Inverse Design For Generating Initial Conditions In Scientific Simulations, Leslie Horace, Christin Whitton, Vanessa Job, William Jones, Nathan A. Debardeleben

Computing Sciences

We propose a conditional normalizing flow (CNF) surrogate model to solve generative, many-to-one inverse problems in scientific simulations governed by partial differential equations (PDEs) with time-evolving interactions between heterogeneous materials. We present two case studies: electrostatic potential and heat diffusion, which serve as proxy simulations for generating diverse sets of initial conditions that can reproduce an observed output state (transient or steady). Finally, we provide a comprehensive overview of the synthetic datasets, the model specification, each stage of the experimental workflow, evaluation of training performance, and uncertainty quantification for the generated samples.

How Can Smart Resilience Cities Provide Sdgs? An Integrative Framework Regarding Climate Change Mitigation, Asmaa M. Hassan, Manar A. Kotb

Mansoura Engineering Journal

Urbanization and climate change influence public health and wellbeing, which presents challenges facing architects and urban planners towards providing sustainable and resilient cities. In this context, smart city concept has been adopted to contribute to mitigating such influence. This study aims to conduct a bibliometric analysis within the previous scope. Then an integrative framework for climate change mitigation towards resilient smart cities based on SDGs is accomplished. The results indicate that further efforts are needed to develop “smart tools”, “urban economy”, and “carbon footprint. In addition, the proposed framework provides a significant paradigm shift towards mitigation of climate change impacts, …

A Novel Hybrid Intrusion Detection Model: A New Metaheuristic Approach For Feature Selection Based On Ai Techniques For Cyber Threat Detection, Maryam Mahdi Alhusseini, Alireza Rouhi

Iraqi Journal for Computer Science and Mathematics

The rapid increase in internet usage, digital transformation, and the rise of interconnected devices have greatly expanded the attack surface, introducing new and evolving cybersecurity challenges. Conventional security solutions frequently have difficulty adjusting to complex threats and the vast dimensionality of network traffic data, particularly in the case of imbalanced datasets. To tackle these challenges, this research introduces a Hybrid Intrusion Detection System (HyIDS-EVO) that combines the Energy Valley Optimizer (EVO) for feature selection and dimensionality reduction with machine learning classifiers, which include Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN). The system’s effectiveness …

Interfacial Gap Prediction In Laser Welding Of Pure Copper Overlap Joints Using Multiple Sensors., Hyeonhee Kim, Cheolhee Kim, Minjung Kang

Mechanical and Materials Engineering Faculty Publications and Presentations

In this study, a novel approach was proposed for predicting the interfacial gap in copper overlap joints by using deep learning and multi-sensor fusion. In this method, an image sensor, a spectrometer, and optical sensors tomography (OCT) sensors were used to develop and validate deep learning models under various gap conditions. The results revealed that the variation in melt pool dimensions, changes in keyhole behavior, intensity variations at specific wavelengths, and keyhole depth derived from the OCT data could be used to accurately predict the interfacial gap. Among the proposed models, a binary gap classification model achieved the highest accuracy …

Treatment Intensification Of Digester Dewatering Sidestreams Via Pilot- And Demonstration-Scale Revolving Algal Biofilms At Municipal Water Resource Recovery Facilities, Audrey E. Kocher, Hunter W. Schroer, Christopher A. Marks, Craig L. Just

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

As water resource recovery facilities (WRRFs) pursue decarbonization, the treatment of concentrated side streams from anaerobic digestion offers a critical opportunity to reduce energy use and greenhouse gas emissions. This study evaluated the intensification potential of revolving algal biofilms (RAB) for side stream nutrient removal via partial nitrification at pilot- and demonstration-scales. RAB systems were deployed at municipal WRRFs in Boulder and Iowa City, treating real dewatering side streams across a range of ammonium (NH4⁺–N) surface area loading rates (SALR) reaching up to 196 g N m^–2d^–2. The results demonstrated that RAB systems can …

Promoting Leadership To Enhance Safety In Aircraft Maintenance: A Phenomenological Study Of Aviation Technical Operations, Komi Tete

Doctoral Dissertations and Projects

The purpose of this qualitative phenomenological study was to explore how leadership styles affect the safety practices and overall performance of aircraft maintenance technicians (AMTs) in aviation Technical Operations (TechOps) environments. The study built on previous research indicating that safe and efficient aircraft operations depend on numerous technical and social processes. It focused on the comprehensive lived experiences of AMTs as they related to leadership influence on safety. The transformational leadership theory and safety culture theory guided the study, aligning with the inquiry by explaining how leaders could influence the behavior, motivation, and safety practices of AMTs. Ensuring the safety …