This work addresses the operational conflicts between visibility-driven mobilization and cost efficiency in disaster management scenarios involving wildfires. Using official wildfire reporting on the social media platform Twitter (now X), we develop a temporal gravity model to extract a signal of public attention for California wildfires (2007-2021) without the "noise" of spurious content. Interpreting this signal through the lens of behavioral disaster management operations, our analysis finds a "Visibility-Efficiency Paradox." This paradox shows that while social media visibility functions as a potent mobilization signal to the general public during wildfires and is associated with greater resource deployment, it simultaneously correlates with reduced cost efficiency under high resource use loads. We identify resource saturation as a boundary condition where heuristic signals appear to shift from valuable inputs to potential stressors. These findings challenge the assumption that high visibility of responders in a wildfire emergency is a direct proxy for operational urgency and effectiveness. We propose actionable strategies, including reverse audits and decoupling, in order to help counteract salience bias; thus, highlighting the potential for algorithmic governance to align public attention with sustainable resource management.

This paper presents a scalable instructional model for embedding generative artificial intelligence (GenAI) ethics, responsible tool use, and cybersecurity governance into graduate-level cybersecurity curricula. The model emphasizes the development of executive-level reporting skills through structured use of AI writing tools, including Grammarly and ChatGPT. An IRB-approved Qualtrics survey provides empirical evidence of enhanced student writing quality, confidence, and reflective practice. In addition, we propose a Cybersecurity Executive Report Writing Maturity Model, a five-level framework informed by student writing patterns and survey insights. Although not deployed during the course, the model offers a forward-looking scaffold to help students progress from raw technical reporting toward strategic, executive-ready communication. This trajectory is critical for professional effectiveness and advancement in cybersecurity roles. The study's small, descriptive sample highlights the need for further research and broader validation.

Among many functionalities, Generative Artificial Intelligence (GenAI) can model the topology and semantics of user-supplied datasets - a functionality required to evaluate learning levels through mind maps. Since GenAI evolves by orchestrated changes to the underlying algorithms and, organically, by learning, we need to understand this evolution's speed and reliability. We conducted two experiments tasking ChatGPT with scoring mind maps drawn by 113 undergraduate students describing their motivation and deterrence towards entrepreneurship. Scoring used a five-dimensional model consisting of self-efficacy, internal locus of control, need for growth, intrinsic motivation, and resilience. We repeated the analysis on the original dataset after eight months to time the evolving pace and sophistication of the tools used. The results show that we should not fall into the "hype" curve typical of the beginning of any emerging technology. While the pace of learning in GenAI is unprecedented, caution is necessary when rechecking data and analytical techniques.

The growing demand for cybersecurity professionals has led to a proliferation of educational initiatives across the United States (US) and the European Union (EU). This survey examines efforts spanning K-12 programs, higher education, and industry certifications. While colleges and universities offer increasingly diverse undergraduate and graduate programs. The rise of online learning and the involvement of for-profit education providers further broaden access. Despite this growth, educational efforts remain fragmented and have not kept pace with workforce needs. This paper highlights key trends and challenges across the cybersecurity education ecosystem and underscores the need for greater coordination to strengthen the talent pipeline.

Vehicle sharing is an environmentally friendly and economically efficient way to provide personal transportation on an ad hoc basis for the populations of cities and suburban areas. Such transportation is necessary for doctor and hospital visits, to purchase necessities, and for other daily needs. The relocation problem is one of the managerial issues that arises in vehicle sharing and it involves the movement of vehicles after use to lots, depots, or areas where it is anticipated they will be needed in the next time period. The work described here was part of a project that sought to investigate the creation of a novel nonprofit vehicle sharing organization that would be manned mostly by volunteers and serve the residents of a U.S. city where over 30% of its population lives at or below the poverty line. The easy-to-use spreadsheet model described in this paper focused on providing nontechnical employees and volunteers in a such a nonprofit with a means of making optimal decisions regarding lot inventories of vehicles without formal optimization training.

Generative Artificial Intelligence (GenAI) is reshaping business operations across industries, enabling new efficiencies in automation, decision support, and cybersecurity. However, small and mediumsized enterprises (SMEs) often lack the technical expertise, financial resources, and implementation support needed to adopt GenAI effectively. At the same time, undergraduate Information Technology (IT) programs tend to focus on enterprise-scale AI development, creating a gap in preparing graduates to support GenAI deployment in small business contexts. This paper presents a curriculum proposal informed primarily by a literature review, supported by a Pennsylvania-based SME needs assessment survey to examine GenAI adoption challenges and identify key curriculum gaps. The model proposed is anchored in applied AI literacy, cybersecurity, ethical governance, and experiential engagement with small businesses. The model aligns with national workforce initiatives such as NICE and NSA CAE, helping to prepare IT graduates to bridge the AI readiness gap and drive local innovation through secure and practical GenAI adoption.

The rise of generative artificial intelligence (GenAI) challenges the design, delivery, and integrity of assessments in undergraduate cybersecurity programs. While GenAI offers opportunities for enhancing instruction and learning, it also disrupts traditional written and authentic assessments, enabling students to bypass critical thinking and skill development. This paper examines institutional policies, pedagogical models, and assessment strategies to help instructors and programs adapt effectively. Drawing on recent studies, case examples, and curricular frameworks, the paper presents a rubric for addressing the use of GenAI by students in courses. These strategies can help maintain both the integrity and the relevance of cybersecurity education in a rapidly evolving technological context.

This paper examines the role of non-traditional sectors in integrating and advancing Generative Artificial Intelligence (GenAI) across diverse industries, extending beyond the traditional boundaries of the technology sector. Non-traditional sector players in GenAI have recently enabled a foothold in both industry and education to rapidly expand. With a focus on healthcare, agriculture, education, and finance, we highlight case studies that demonstrate the innovative applications of GenAI, illustrating its capability to drive significant industry transformations. Through this exploration, the paper emphasizes the crucial role of interdisciplinary collaboration in catalyzing technological progress and broadening the impact of GenAI. By providing a comprehensive analysis of the current and potential future states of GenAI applications, this research aims to deepen understanding of its broader societal and economic implications. This study not only captures GenAI's transformative potential but also addresses the dual narrative of GenAI as both a promising tool, particularly for education, and a formidable challenge, underscoring its growing influence in non-traditional sectors.

This study proposes the integration of specific social media analytics (SMA) metrics into existing U.S. wildfire management systems to enhance their ability to accurately predict, monitor, and respond to wildfires in a timely manner. In addition, the examination of SMA's influence on shaping wildfire-related policies is addressed in our analysis with respect to the mitigation of the extent and effects of such disasters. Furthermore, the potential of Web 3.0 technologies in achieving these objectives is analyzed as part of this work. The results highlight that advaa analytics (SMA) metrics to wildfire management and along with Web 3.0 integration.

Confining wireless signals (WiFi) in specific areas of indoor spaces is an efficient way to protect these networks against unwanted access. Unfortunately, these same WiFi signals can be utilized to track the location of mobile handsets. There is an apparent tradeoff between securing the range of such signals and their use for indoor geolocation purposes. The modeling of wireless signal coverage for both security and geolocation purposes in areas where measurements are difficult to record can be a daunting task. We utilized a deep autoregressive model and a convolutional neural network model trained on a synthetic floor plan dataset to accurately extrapolate signal coverage across such spaces without using specific information about antennae placements or floor plan designs. Computational experiments showed that these data-driven approaches were able to fill the gaps in signal coverage maps accurately.

The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including “hyflex” where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students add/drop, or the number of course sessions is changed. The creation of these reports is tedious and error-prone, so they need to be automated. However, the nature of the task precludes traditional Excel programming approaches. We use Excel’s new “dynamic array” capabilities (which are available only in Excel 365) to automate the creation and updating of the reports needed to manage the hyflex course. We show how to program the reports, and we discuss the importance of taking an iterative approach to creating effective, error-free cell formulas. To help the reader acquire genuine access to the dynamic array functions, we provide a practical tutorial on the principles and new concepts of dynamic arrays, explain how they relate to legacy array functions, and present selected dynamic array functions including SEQUENCE, FILTER, and XLOOKUP.

As the popularity of Cybersecurity-related curricula grows both among students and institutions at the higher education level, there exist many questions regarding how degree programs should be structured and what specific content should be taught in them. Many areas of study that were once thought to be somewhat removed from a networking or information security focus have created new courses, or adapted existing ones, to create degree programs based on some aspect of Cybersecurity. Whether the program is titled Information Security, Information Governance, Business Systems Security, Network Security, or a host of other variations and terms, the heart of all of them is Cybersecurity. In other words, all of these programs revolve around the securing of data, systems, networks, and their physical footprints in organization. This work seeks to review the various types of master's level programs related to Cybersecurity in the U.S.

This is the third edition of the mini track on innovation and entrepreneurship theory and practice, and we are pleased that the number of submissions continues to grow, showing the importance of this topic in a system science conference. Of particular importance to this track is the connection with knowledge management, creation and sharing. Entrepreneurs often create knowledge but fail to capture it for future use. This track continues to explore drivers of innovation and entrepreneurial startup activities in emerging industries, geographical and cultural elements. It brings an international perspective by focusing on cross-country comparisons and studying initiatives in many different regions of the world.

The need for cybersecurity competence has become a strategic area for all types of organizations, be it large or small, for profit or nonprofit. This is an area of particular concern for smaller nonprofit organizations; and especially for those in rural areas with limited resources to address their cybersecurity risks. Cyber-attacks wreak havoc on the networks and systems for services provided to nonprofit consumers. The problems associated with various types of attacks, from outside nefarious individuals/groups or internal personnel, are particularly difficult for nonprofits in rural communities with limited resources for cybersecurity infrastructure and limited staff proficient in cybersecurity knowledge and skills. We have developed a cybersecurity assessment process to ascertain key needs and weaknesses with respect to cybersecurity for nonprofits in such rural communities in Pennsylvania. Additionally, this grant-sponsored work-in-progress research aims to provide guidance to rural nonprofits with “best practices” and related content that can be easily implemented despite their limitations.

The spread of the COVID-19 virus across the globe has permanently changed life for billions of people. Manual contact tracing has been utilized to assist in limiting the spread of contagious diseases for many years. The ubiquitous use of smartphones and similar wireless devices has allowed this process to become digital in nature through contact tracing applications installed on these devices. Various countries, and even various regional units within those countries, developed contact tracing applications. Such applications relied on location and short-range communication technologies associated with wireless devices and found varying degrees of success. This work reviews research conducted by universities, governmental organizations, and other entities with respect to the adoption, use, and ultimate success of, digital contact tracing applications across various countries and points to their rather limited success in fighting the spread of the disease. The authors also briefly discuss some implications regarding privacy and security that affected their use in certain countries.

Higher education is increasingly called upon to enhance cyber education, including hands-on "experiential" training. The good news is that additional tools and techniques are becoming more available, both in-house and through third parties, to provide cyber training environments and simulations at various features and price points. However, the training thus far has only focused on "traditional" Cybersecurity that lightly touches on wireless in undergraduate and master’s degree programs, and certifications. The purpose of this research is to identify and recognize nascent cyber training emphasizing a broader spectrum of wireless security and encourage curricular development that includes critical experiential training. Experiential wireless security training is important to keep pace with the growth in wireless communication mediums and associated Internet of Things (IoT) and Cyber Physical System (CPS) applications. Cyber faculty at a university offering undergraduate and master’s Cybersecurity degrees authored this paper; both degrees are offered to resident as well as online students.

Low altitude platform (LAP) architectures are an emerging platform for providing temporary wireless network connectivity to areas with a damaged fixed wireless network infrastructure. The authors propose a spreadsheet-based approach for practitioners to locate LAP nodes in the field. This approach does not require radio frequency propagation expertise and incorporates standard models to display the coverage areas for the placement of LAP aerial devices. The proposed tool allows the transmission range for a given aerial device to be visually optimized during deployment. The spreadsheet-based tool the authors are proposing is expressly suited for battery-powered LAP architecture devices with payload weight restrictions, such as those utilizing balloons or kites, that can be quickly deployed by emergency responders. An additional contribution of this work is the development of a hybrid propagation model for LAP device transmissions for deployments above 200 meters which is absent in the literature. This model is a linear combination of two existing models for free space radio propagation.

This paper provides a cross-boundary process to guide colleges and universities creating undergraduate cyber curriculum or reviewing established programs. There is growing demand for academic institutions to help close the skills gap by developing cyber curriculum preparing students for careers in cybersecurity. The cross-boundary process in this paper builds on a multi-level, multi-discipline approach previously used to launch a new undergraduate cyber program. This expanded approach recommends evaluating advisory consortium feedback, master's degree programs, certifications, and internal considerations (e.g., faculty expertise). This paper is prepared by cyber faculty at a university offering both residential and online general education courses as well as undergraduate and master's degrees in cybersecurity. This paper further advances the call for discussion on the topic of cyber education.

A contentious merger seems to characterize the relationship between entrepreneurship, defined as the process of bringing new products and services to the market, and knowledge management. Even when discussed from the perspective of dynamic knowledge creation and innovation rather than from the codification and organization of a firm's knowledge base, the knowledge management process of new ventures often fails to keep pace with best practices. This is particularly puzzling as the competitive advantage of new ventures stems from exploiting tacit knowledge, which is at the heart of successful knowledge creation and management. This chapter investigates this contradiction and discusses challenges and opportunities to both the practitioner and the researcher.

This mini-track examines both the theory and practice of knowledge management in organizations where innovation and an entrepreneurial structure require its successful application. Entrepreneurs often create knowledge but fail to capture it for future use. Organizations that have the ability to innovate in their early stages of existence and capture the knowledge they create are far better positioned to survive in the long run.