Transforming Education Through the Cohort Model in Graduate Schools of Education

The cohort model has emerged as a transformative approach in graduate schools of education for fostering a collaborative learning environment, providing professional networking opportunities, increasing community, and fostering a sense of belonging. This analysis is framed within Mead, Vygotsky’s, and Wenger’s theoretical framework on the interconnectedness of social interaction and cognitive development. Increased engagement, learning opportunities, promoting student success, enhanced leadership development, and improved program components are noted benefits of utilizing the cohort model in graduate schools of education. These authors noted some challenges to the cohort model, such as group dynamics and cohesion, diversity and inclusion, rigid structure, pressure to conform, resources and faculty challenges, retention and attrition, and compatibility with adult learners. The future implications of graduate programs utilizing a cohort model are replete with leveraging student support, sharing of experiences, and social integration. The gaps that were identified resonated in the areas of intentional cohort design, faculty training, integrated support systems, and continuous assessment. More research is needed in these areas to augment the transformative aspect of the cohort model in graduate schools of education

Monetization Of Crowd-Sourced Fog Node Services Using Blockchain And Smart Contracts And The Adaptation Of Ml For Data Reduction

Fog computing is increasingly becoming the building block for the explosive growth in edge computing as it affords the edge all the capabilities of the cloud with low latency and more decongested internet traffic. It accounts for the limitations found in IoT and other edge devices regarding memory, CPU, and bandwidth. While firms are providing these fog nodes, there remains the issue of data ownership, pricing fairness, and the amounts charged to customers based on the quality of services received. Our work proposed a decentralized blockchain-based fog paradigm that addressed these issues and provides a platform for users to contribute devices (nodes) to the fog network and get incentives when their contributed nodes are used for fog services. Our experiment showed that fairness can be achieved between the users and fog nodes, with both submitting reports of the services rendered or received at the end of every connection. An independent smart contract reviews these reports, runs analysis, and the proper charge is levied on the user based on the services received. The system met the security core principle of confidentiality, integrity and availability. The feature of this system is enhanced by introducing a data reduction model that sits between the IoT and the fog nodes. This improves the performance of the fog network by reducing the noise and data size from IoT devices processed by the fog network. Our work introduced a system that efficiently handled this by building a machine learning model that utilized the math of principal component analysis and singular value decomposition (PCA/SVD) for data reduction. The unique value of this combination of data reduction and feature selection methods shows that while the data was greatly decreased, the feature of the data was retained. This was verified using standard benchmark datasets and a large private IoT dataset to verify the system\u27s effectiveness. Index terms - Blockchain, cloud, edge computing, Ethereum, fairness, fog, Internet of Things (IoT), Nodes, Principal Component Analysis (PCA), Quality of Service (QoS), Singular Value Decomposition (SVD)

Factors Influencing Healthcare Cybersecurity Effectiveness: An Empirical Investigation

The healthcare sector faces escalating cybersecurity risks due to its reliance on electronic health records, legacy systems, medical devices, and health information exchanges. These interconnected technologies expand attack surfaces and create vulnerabilities that threaten patient data, operational continuity, and public trust. These challenges cause many healthcare organizations to struggle to implement effective cybersecurity strategies. The purpose of this study was to investigate the factors that influence healthcare cybersecurity effectiveness by integrating Institutional Theory, Dynamic Capabilities Theory, Top Management Support, and IT Infrastructure Quality. A survey was administered to healthcare IT, cybersecurity, and executive professionals across the United States. The final dataset was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The guiding research question was: What are the factors that influence healthcare cybersecurity effectiveness? Factors included institutional pressures (mimetic, coercive, normative), top management support, IT infrastructure quality, and dynamic cybersecurity capabilities (sensing, seizing, transforming). Results revealed that mimetic pressures and normative pressures had a significant influence on top management support. Specifically, IT Infrastructure Quality had a significant influence on cybersecurity sensing capabilities, which further had a significant influence on cybersecurity seizing and cybersecurity transforming capabilities. Cybersecurity seizing capabilities had a significant influence on cybersecurity transforming capability, which further had a significant impact on perceived healthcare cybersecurity effectiveness. The model offered insight into how strategic alignment and institutional forces jointly shape cybersecurity effectiveness in complex healthcare environments. This study contributes to both theory and practice by presenting a validated model that integrates organizational, institutional, and technological factors. The findings may inform healthcare executives, policymakers, and IT leaders who seek to enhance cybersecurity readiness, improve system resilience, and mitigate breach-related risks. Keywords: healthcare cybersecurity, institutional theory, dynamic capabilities, top management support, IT infrastructure quality, sensing capabilities, seizing capabilities, transforming capabilities, PLS-SE

Sense Of Belonging Of Indian International Students At A Historically Black College And University

This convergent mixed methods study composed of autoethnography and ethnography, explored the experiences of six Indian international students at a Historically Black College and University (HBCU). While rich research exists regarding challenges faced by international students in terms of their sense of belonging in American colleges and universities, relatively little research had been conducted related to challenges specifically experienced by Indian international students. Furthermore, no studies looked at challenges experienced by Indian international students specifically at HBCUs. Instead, the studies focused on Indian international students at Predominately White Institutions (PWIs). Drawing upon Tinto’s (1993) Model of Institutional Departure, the present study contended that, in addition to formal academic elements, Indian international students at HBCUs required informal academic elements in the form of healthy faculty/staff interactions and peer-group interactions for success in the classroom. This perspective aligned with Goodenow’s (1993) perspective, who highlighted the prime importance of a healthy sense of belonging in all students, and a need to feel accepted by, included by, and connected to their institutions. Open coding of the six interview transcripts, one of which included my own, yielded four themes regarding the experiences that influenced the sense of belonging at a HBCU: (1) With respect to “being accepted,” half of the respondents reported clique-like behavior by African American classmates; (2) With respect to “being valued,” the majority of respondents exclusively or primarily reported having African American classmates who were supportive and friendly and valued their input; (3) With respect to “being encouraged,” two-thirds of respondents exclusively reported that the HBCU’s instructors supported their efforts and made them feel welcome; and (4) With respect to “being included,” two-thirds of respondents mentioned strategies for making connections with classmates and instructors within the HBCU classroom. The themes and subthemes indicated potential areas of further improvement for this HBCU in terms of supporting the sense of belonging of its Indian international student population. Keywords: sense of belonging, Indian international students, HBCU, Historically Black College or University, culturally responsive teaching, diversit

Identification, Removal, And Characterization Of Microplastics From Pvamu Wwtp Effluent Using Ceramic Membranes

This study evaluated a 1.4 µm ceramic membrane\u27s effectiveness in removing microplastics from wastewater, focusing on characterization via FTIR spectroscopy. Microplastics, including fibers, fragments, and microbeads (1-2500 µm), were visually identified and counted under an electron microscope, achieving a 94% TSS reduction and a 35.4% microplastic recovery rate. FTIR analysis identified key polymers like polyethylene, polypropylene, and polystyrene, with distinctive peaks for polyester (1624 cm−1, 1737 cm−1) and cotton (1095 cm−1, 1119 cm−1, 1151 cm−1), indicating polymer degradation through spectral signs of carbonyl groups. Micro-FTIR imaging, enhanced by dyes like DANs under fluorescence and Rose Bengal, pinpointed polymer sources and degradation effects. Post-filtration, microplastic composition shifted, with microbeads decreasing to 35%, fragments increasing to 50%, and fibers at 14%, highlighting the influence of shape and size on filtration efficiency. This work also highlights the need for sophisticated FTIR for in-depth microplastic analysis in wastewater treatment, indicating that although ceramic membranes show promise, particular approaches are required to handle various microplastic forms. Keywords: microplastic, membranes, wastewater, m-FTIR, microscopy, dy

(SI14-12) Some Novel Fractional Discrete Inequalities of Gronwall-Bellman Type and Their Applications to Fractional Difference Equations

In this study, we develop multiple power nonlinear generalizations of Gronwall-Bellman type fractional discrete inequalities and fractional sum inequalities through combining functions with powered unknown functions.We have employed technique of reducing power non-linearity into linearity to furnish these refinements. These novel findings present a broader framework for dealing with wider range of nonlinear fractional difference equations and fractional sum-difference equations. The utilization of these inequalities enables to study certain crucial classes of fractional difference equations that arise in the realm of fractional difference calculus, both quantitatively and qualitatively. Several illustrations are provided to examine the boundedness of initial value problems of fractional difference equations, demonstrating the reliability and effectiveness of our findings

Aligning Remote Work Preferences With Workplace Outcomes: Investigating The Impact Of Person-Environment Fit

Remote work gained steady popularity in all sectors after the COVID-19 pandemic. This study examined how matching employees\u27 preferred remote work setup with their actual work environment affected job satisfaction, engagement, stress, and the desire to leave the company. Framed by Person-Environment Fit, the research examined how the match between individual preferences and work arrangements influenced these outcomes. Participants were surveyed using a 4x4 factorial design to capture responses across various remote work scenarios. Data regression analyses indicated that alignment between remote work preferences and actual work arrangements significantly improved job satisfaction and reduced stress and turnover intention. The expected impact on engagement was unclear, with the results partially confirming the hypothesis. These findings show the difficulty of creating remote work policies that meet all employees\u27 needs. Keywords: Remote work, person-environment fit, virtuality, job satisfaction, job engagement, job-related stress, turnover intentio

Off-Grid Renewable Energy Generation Supervisory And Data Acquisition (Sada) Using Extended Reality

Supervisory and Data Acquisition (SADA) systems are an imperative component for the operation of intelligent power systems. In this study, control room duties were performed remotely through extended reality (XR) technology. Multiple monitor setups can be eliminated, and the use of peripheral devices was reduced. XR technology allows for the combination of real and digital environments, which will help to eliminate physical control room setups while enhancing the mobility and comfort of operators. The implementation of XR technology will provide enhancements in communications through built-in text chats, voice calls, video calls, and screen casting capabilities. The XR SADA system proposed utilized the Apple Vision Pro. For the SADA system to function properly, the off-grid power generation system must have the appropriate supporting infrastructure. This includes devices such as smart meters, inverters, sensors, and battery storage systems that can transmit grid data via Internet connectivity. The Apple Vision Pro headset accesses the online data servers of the Internet of Things (IoT) devices through an Internet web browser or device applications. Once accessed, the data windows may be configured according to the operator’s preference. That data is then exported and analyzed for the creation of real-time grid alerts, which provide notifications within the operator’s vision. The XR SADA system is designed to be easily setup and utilized, which will lead to faster response times, and improve the protection of the off-grid system. Index Terms—Extended Reality (XR), solar power generation, Supervisory and Data Acquisition (SADA)