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Exploring the Role of Affordances and Constraints in Shaping Trust within the Mobile Money Ecosystem: A Case of Rural Communities in Sub-Saharan Africa
No full textThis study delves into the intricacies of mobile money technology (MMT) in rural areas of Low-Middle Income Countries (LMICs) and examines its ecosystem dynamics, affordances, constraints, and the role of trust in adoption and sustained usage. It aims to address the existing gaps in understanding the challenges and inconsistencies surrounding MMT interactions in rural communities. Emphasizing the importance of viewing MMT as an evolving ecosystem rather than just a platform, the study seeks to uncover new perspectives on the affordances and constraints shaping trust and adoption in rural communities. Primarily, the study seeks to contribute theoretically to the discourse on MMT in rural areas by conceptualizing contextual affordances and constraints. Furthermore, the findings of this research could offer valuable insights for policymakers and stakeholders seeking to understand and address the discrepancies in previous studies on MMT adoption in rural areas
Indigenous Finance and Women Empowerment: The Digital Transformation of Stokvel Systems in South Africa
No full textThis paper explores how the digital transformation of stokvels in South Africa is reshaping women’s empowerment. Stokvels, a form of indigenous savings or rotating savings clubs, have long served as a financial safety net for women, particularly for underserved rural and peri-urban communities. However, with the increasing integration of mobile technologies, fintech platforms, and digital communication tools, these systems are undergoing a significant shift. Drawing on qualitative data from South African women engaged in digitally transformed stokvels, the study examines how digital tools redefine women’s economic and social empowerment. Through the lens of Nego-feminism and Snail-sense feminism, the research highlights how women negotiate and adapt to digital solutions within their stokvel practices. An abductive thematic analysis revealed that, while digital tools enhance transparency and efficiency, there are still barriers to adoption, such as resistance to new technology, digital literacy and trust. The findings contribute to broader conversations about financial inclusion, digital equity and gendered technology adoption in the Global South. The paper concludes with practical recommendations for policymakers and fintech developers on inclusive fintech innovation
Beyond Rosie: Women in World War II
No full textRosie the Riveter is the iconic symbol of women\u27s involvement in World War II. She is one part of a larger story about the many ways women contributed to and were affected by war. World War II changed the everyday social, cultural, and economic realities of life in the United States, especially for women. Beyond Rosie: Women in World War II explores the lives of women in World War II.https://digitalcommons.kennesaw.edu/mhheexhibits/1001/thumbnail.jp
The Sky\u27s the Limit: Women Pilots of World War II
No full textMany people have heard of Amelia Earhart, but few know of the countless other women who were among the country’s earliest aviation experts. This exhibit explores the stories of these pioneering pilots.https://digitalcommons.kennesaw.edu/mhheexhibits/1012/thumbnail.jp
Legacies of Revolution: Persistence of Constructivism in Contemporary Architecture
No full textHow does the philosophy of past revolutionary movements persist into the modern age? Throughout the early 20th Century, liberation and revolution were defining aspects of several artistic movements and philosophies around the world. Questions arose concerning how this novel form of social consciousness could integrate industrial advancement into the fabric of contemporary society, technology, and everyday life. Stylization was struck down to foster a novel philosophy, one that would reflect the contemporary context and embrace the products of industrial society rather than idealizing what came before. Constructivism was that philosophy, taking cues from Futurism and Russian Avant-Garde, defining itself through abstraction and austerity in service of the ‘revolution’. The movement itself persisted for decades, shaping how the Soviets presented themselves to the rest of the world, a bastion of advanced technology with a communist social purpose, influencing several art and architectural movements from the 1940s into the modern age. Legacies of Constructivist thought continue to influence architectural philosophies, construction technologies, and the built environment. While not a direct descendant of the framework, Carla Juaçaba; a Brazilian architect known for the spatial clarity, material usage, and community engagement of her distinctive work; may be representative of one of its contemporary reinterpretations. Her architecture synthesizes the industrial and social principles of her community into a contemporary, human-centric context. The comparative framework of this paper will investigate how Juaçaba’s work reflects and reinterprets Constructivist ideals alongside architects such as Iakov Chernikov and others. It examines how these ideas persist through purpose-oriented design, austere abstraction, spatial dynamics, and social engagement. The case study of Humanidade2012, a collaborative project between Juacaba and Bia Lessa, shows how contemporary architecture can use historical philosophical thought as a conceptual tool to shape form, structure, and human experience across more formal, ideological, technological, and cultural lines
Two Visions of an Architectural Revolution: Archigram and Italian Futurism
No full textThe idea of a revolution in architecture is prevalent in both Archigram and Italian Futurism. Although Archigram was a group of architects that formed after World War II and Italian Futurism was a movement that pushed Italy closer to fascism before World War I, both reveal how architecture can promote new ways of living and new ways of seeing the world. The fundamental ideas behind their values differ in how they approach sociopolitical issues that appear eclectic throughout time. On one hand, Italian Futurism pushed a new age of propaganda that celebrated industrial progress which introduced a new architectural language—one that ultimately never took flight. The Futurist movement rejected historical references in favor of a future defined by speed and emerging technologies. On the other hand, Archigram, a collective of six architects, envisioned a revolution in architecture that embraced technological innovation while responding to the cultural conditions of its time and emphasizing community engagement. This paper explores the relationship between Archigram and Italian Futurism through the lenses of phenomenology, sociopolitical context, and formalism still relevant today. It argues that although Archigram and Italian Futurism emerged in different contexts, both generated similar visions for a new architectural vernacular that integrates technology and community
Bottoms Up, Beowulf
No full textThis project discusses the importance of adapting classic works of literature into more modern mediums. The totality of this project moves through research on the classic work, Beowulf, and addresses the best way to adapt that into a modern context. The script discussed in this piece evolves from a feature film to a television pilot, and discusses where the rest of the television series may move
Transferring Adversarial Robustness Across Architectures and Datasets
No full textRemote sensing is the science of extracting meaningful information from satellite imagery and plays a crucial role in environmental monitoring, land-use analysis, and disaster response. Traditional manual interpretation methods were often slow, labor-intensive, and error-prone, but the adoption of deep learning has significantly improved the accuracy and scalability of remote-sensing image classification. Deep learning image classification models have achieved state-of-the-art performance in terms of accuracy, greatly enhancing the scalability and reliability of remote-sensing analysis. However, despite these advances, such models remain vulnerable to adversarial attacks—deliberately crafted perturbations designed to mislead predictions. Adversarial patch attacks pose an even greater threat, as physically realizable patches can be placed directly on objects.
Adversarial training is a common defense, where models are trained using adversarial examples to improve robustness. However, this process is computationally heavy because adversarial examples must be generated throughout training. These challenges motivate the need for robustness-transfer strategies that reduce training cost while maintaining or improving resistance to adversarial patch attacks.
This study investigates robustness transfer as a defense strategy, aiming to strengthen the resilience of remote-sensing classifiers against adversarial patch attacks. To address this challenge, we propose two complementary approaches. The first is a transfer learning–based method that leverages pretrained adversarially robust models, enabling the reuse of robustness without the heavy computational cost typically associated with adversarial training. This approach significantly reduces training time while still providing meaningful improvements in robustness.
The second contribution is a novel Multi-Teacher Feature Matching (MTFM) framework, designed to align the feature representations of a student model with those of both clean and adversarially robust teacher models. By jointly distilling knowledge from multiple teachers, the MTFM framework encourages the student model to learn feature spaces that balance discriminative power and robustness. This results in an improved trade-off between clean accuracy and defense performance against adversarial patch attacks.
Across diverse datasets and model architectures, the MTFM method consistently outperform standard, non-robust baselines and closely match—or in several cases surpass—existing defense strategies. Notably, these gains are achieved with substantially lower training effort than conventional adversarial defenses. Overall, the findings underscore the promise of robustness-aware knowledge transfer as a scalable, efficient, and practical pathway toward building resilient geospatial AI systems
Religion, Identity, and Conflict in Christian-Muslim Interfaith Families Living in the U.S.
No full textThe influx of Muslim immigrants and changing attitudes towards interfaith marriages in American society has contributed to an increase in unions between Muslim and non-Muslims, especially Christians. This study seeks to understand how contemporary Christian-Muslim families living in the U.S. negotiate their differences and interpret and resolve conflicts. Based on 30 in-depth interviews with adults currently in interfaith relationships and adult children of such unions, this research uses narratives to understand how religious identity, belonging, and conflict are managed within these relationships. Using Social Identity Theory, Intersectionality Theory, and the Tomas-Kilmann Conflict Management Model as guiding principles, this study examines how Christian-Muslim families manage conflict and develop hybrid identities, filling the gap in the literature on conflict and the role of religion in modern Christian-Muslim families. Findings reveal that religion is rarely a direct source of conflict. Instead, cultural practices and external pressures more often contribute to family conflict. Most participants consist of Muslim immigrant fathers and Christian mothers, a dynamic that influences how conflicts are managed. Muslim fathers often display more competitive conflict styles, while their Christian wives are more compromising or avoidant, suggesting that at least one compromising or avoidant style has a stabilizing effect on the relationships. Religious identity development for adult children also follows two dominant paths: rejecting religion or identifying as Muslim. This aligns with broader demographic trends of rising numbers of religiously unaffiliated individuals and Muslims. This research contributes to scholarship on Christian-Muslim family dynamics in the U.S., social development, and identity negotiation
Region-based Object Recognition and Detection Under Constrained Resolution
No full textTraditional object recognition pipelines often show substantial performance degradation when operating on low to medium resolution imagery, particularly when the target objects are small and take random irregular shapes. Likewise, common small object detection models suffer in detecting objects that are not more than a few pixels in extent. This is primarily due to the limited spatial context available for feature extraction, compounded by the loss of discriminative information at lower resolutions.
This research has focused on two primary objectives. (1) region-based object recognition for local explanations produced by explainability techniques used in image classification. (2) very small object detection using a lightweight and efficient approach. The key contributions are provided as follows. (I) A novel method for explainability auditing using LIME and superpixel classification; (II) A regression-free detection pipeline that identifies 8×8 pixel objects by upscaling unsupervised region proposals via SRGAN and applying cascade classification; (III) Novel fully convolutional object recognition networks: U-Net for Region Proposal Network (URPNet), to extract 16×16 regions of interest, and Region-Based Fully Convolutional Detection Network (RFCDet), a FCOS-inspired detection model enhanced with optional multi-head attention, and a novel IoU loss with convex penalty for tiled detection; and (IV) An integrated lightweight inference framework combining URPNet and RFCDet with a dedicated postprocessing pipeline for very small object detection. Experimental evaluation on a dataset of small objects derived from the AI-TOD v2 dataset demonstrates that our approach achieves improved performance in average precision and recall, outperforming the state-of-the-art models, in detecting very small and rare objects