bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Model for Cybersecurity Education through Challenge Events
Authors: Daily Jeremy , Span Martin (Trae) 
Published: September 2024

AbstractThe INCOSE Vision 2035 sets an important Cybersecurity goal: “Cybersecurity will be as foundational a perspective in systems design as system performance and safety are today”. A critical enabler of achieving this vision is educating cyber informed engineers and professionals. Across industries, the demand for talented cybersecurity professionals is high, which means the personnel and students need inspirational education and training to fill these opportunities. This is particularly the case for complex systems in transportation, maritime, agriculture, aerospace, energy, and industries that rely on operational technology implemented with embedded systems. This broad category of sectors need talent and community to address cybersecurity concerns. Often these economic sectors have systems with long lifecycles, regulations, market forces, or other constraints that preclude security solutions envisioned for information technologies. To address the needs for cybersecurity personnel for these industries, a model for developing talent and building community is explained in general terms with specific examples as it relates to automotive, heavy duty, maritime, and agriculture. The model describes the CyberX Challenge, where X is an industry sector, such as the CyberAuto Challenge, CyberTruck Challenge, CyberBoat Challenge, and CyberTractor Challenge. These Challenge Events are described in detail with a focus on the characteristics of what makes those successful or difficult. The successful events have strong industry support, elite instructors, and motivated students. The model for the event is described in detail, with the intention that other industry verticals may inspire additional students and further build communities able to address cyberthreats to our modern way of life. This work directly contributes solutions to addressing the needed foundational concept of Security Education and Competency development as highlighted by the INCOSE FuSE working group.
The Electric Revolution: Fully Electric Transportation System on An Urban College Campus
Authors: Sharifi Zabi , Mansouri Mo 
Published: September 2024

AbstractThis paper offers a comprehensive exploration of the implementation of fully electric transportation systems within urban college campuses. Urbanization and environmental concerns have intensified the need for sustainable transportation solutions, and college campuses serve as ideal testbeds for innovative mobility initiatives. The paper begins by establishing the context through background research, which highlights the adverse effects of urban air pollution and the role of electric vehicles (EVs) in mitigating these issues. The driving forces behind the adoption of fully electric transportation systems are discussed, Benefits, challenges, and implications of implementing electric transportation systems are meticulously examined. The anticipated benefits encompass improvements in air and noise pollution, reduced operational costs, and enhanced campus reputation. Nevertheless, the challenges of infrastructure costs, charging management, and operational intricacies are acknowledged. The paper underscores that successful implementation goes beyond immediate advantages, positioning campus electric transportation systems as living laboratories for research and innovation in sustainable mobility. Additionally, these systems serve as models for neighboring communities and influence regional transportation policies. The paper concludes by laying the groundwork for forthcoming discussions. It highlights the subsequent sections' focus on planning, stakeholder engagement, technological integration, and operational management, which collectively shape the implementation. The paper will employ the application of Systems Thinking approaches, tools, and techniques in order to properly analyze and tackle the problem statement at hand.
Evaluating the Eco‐Efficiency of Urban Air Mobility: Understanding Environmental and Social Impacts for Informed Passenger Choices
Authors: Hoffmann Raquel , Silva Fabio , Nishimura Hidekazu 
Published: September 2024

AbstractFull electric aircraft with zero CO2 emissions during operations are a promising pathway towards achieving the Fly Net Zero by 2050 goal proposed by the International Air Transport Association (IATA). In this context, Urban Air Mobility (UAM) expects to offer an environmentally friendly alternative through electric Vertical Takeoff and Landing (eVTOL) aircraft. While eVTOLs produce no greenhouse gas emissions, the comprehensive eco‐efficiency of UAM goes beyond the flight phase. This paper delves into evaluating UAM operation's environmental and social impacts, considering the urban space, public perception, operational profiles, and power consumption. Employing causal loop analysis, the study uncovers the relationships that add value or increase impact, assessing UAM passenger transportation's eco‐efficiency. Moreover, the Unified Architecture Framework is used to model the UAM ecosystem and to propose strategies to balance values and impacts in achieving eco‐efficiency. By shedding light on the sustainability viewpoint, this study emphasizes the importance of holistically understanding UAM's operational impact and empowering users to make eco‐efficient choices when opting for UAM transportation. Finally, strategies to provide sustainability awareness to the user are discussed in the Mobility‐as‐a‐System (MaaS) context.
Impact Analysis of using Natural Language Processing and Large Language Model on Automated Correction of Systems Engineering Requirements
Authors: de Oliveira Arthur H. M. , Reis Pedro Almeida , Júnior Fernando Sarracini , Cavalcante Mairon Sena , de Lima Jonathan V. C. , Soares Luis F. C. , Marchiori Lucas Henrique 
Published: September 2024

AbstractThe increasing complexity of Electronic Control Units (ECUs) in the Automotive Industry due to the integration of more sophisticated vehicle features has made the Systems Engineering (SE) application a necessity to define and implement efficient solutions. In this context, requirements emerge as a critical part of the communication between cross‐functional teams. Thus, the more complex systems become, the more requirements are needed to define them. However, lack of information, misalignment and ambiguity on requirements impact the entire development process, resulting in issues later, harder to be fixed. Some studies are being applied to evaluate techniques using Natural Language Processing (NLP) and how it can replace extensive peer reviews, identifying weaknesses in requirements earlier in the process, avoiding wasted time and large financial losses. Normally, NLP is combined with templates such as Easy Approach Requirements to Syntax (EARS), or other rule‐based techniques such as INCOSE's requirements writing best practice rules to define metrics and assess the compliance of the requirements syntax automatically. The focus of this work is to enhance the use of requirements syntax assessment algorithm by combining NLP techniques with Large Language Models (LLMs) to provide automatically corrected requirements.
Role‐Based Structuring of Systems Engineering Teams
Authors: Wozniak Michael 
Published: September 2024

AbstractThere is little documented information on how Systems Engineering (SE) teams are structured with respect to the various SE subdisciplines. This paper provides five possible role‐based structures to aid in filling this knowledge gap and in helping projects structure their own SE teams for success. The five structures range from a simple, single‐role structure to an advanced embedded SE with lead. The paper defines, illustrates, and presents key advantages and disadvantages for the structures. It also presents two real‐world examples to show the value of organizing or reorganizing SE teams to these structures. One focuses on large‐sized and complex waterfall project with a separate SE team restructuring for efficiency and growth opportunities and the other focuses on a medium‐sized and complex Agile project where the SE team restructures for better design definition and schedule efficiencies. Both show how a restructuring helped improve the overall quality of work, the integration with others in the project, and the overall understanding of the systems.
Mean dependency length — a new metric for requirements quality
Authors: Barbosa Leonardo de Mello , de Oliveira Igor Cardozo Amaral , Cerqueira Christopher Shneider , da Cunha Antonio Eduardo Carrilho 
Published: September 2024

AbstractThis paper proposes the mean dependency length (MDL) as a metric for measuring natural language requirements quality. Dependency length is a linguistic feature based on dependency grammar, which natural language researchers have traditionally used to evaluate syntactic complexity in other contexts. In this study, aided by MATLAB‐based algorithms, the authors assessed MDL over a requirements set composed of 249 original statements, rephrased into five pattern systems. Null hypothesis and effect size testings revealed that MDL is sensitive to the application of pattern rules and to the differences among the patterns, both in an absolute approach and in comparison with other metrics. Furthermore, it was also demonstrated that MDL is aligned with users' values, especially for understandability issues, and can be measured automatically. Finally, the work concluded that MDL is a convenient metric for assessing the quality of natural language requirements.
Traceability – A vision for now and tomorrow
Authors: D'Souza Adriana , Wheatcraft Louis S. , Katz Tami , Gurule A. Larry , Ryan Michael J. , Przybylo Aleksander 
Published: September 2024

AbstractTraceability has been addressed in the past from the perspective of relationships between the digital artifacts within the data and the information model of the system of interest (SoI) being developed. This paper enhances this view from a project management (PM), systems engineering (SE), and a configuration management (CM) perspective. The paper discusses what traceability is today and how it can help PM and SE practitioners meet future needs to realize the INCOSE Vision 2035 and satisfy all needs and requirements baselined for a SoI, including compliance with standards and regulations. Provenance and pedigree are two aspects discussed of how traceability enhances the management of digital artifacts from a CM point of view. This paper provides a vision of how traceability can aid PM and SE practitioners to develop quality products that deliver what is needed, within cost and schedule, with the needed quality.
Model‐Based Systems Engineering (MBSE) Methodology for Integrating Autonomy into a System of Systems Using the Unified Architecture Framework
Authors: Torkjazi Mohammadreza , Raz Ali K. 
Published: September 2024

AbstractStakeholders of Systems of Systems (SoSs) are seeking new capabilities provided by autonomous systems empowered by Artificial Intelligence (AI). This requires the integration of these autonomous systems into SoSs, resulting in Systems of Autonomous Systems (SoASs). SoAS architecting is different from SoS. An autonomous system can have various Levels of Autonomy (LoA) depending on its AI algorithm. Each LoA has a different impact on the organizational and technical aspects of SoAS architecting. The organizational aspect covers concerns such as managerial and operational policies, whereas the technical aspect highlights issues such as integration compatibility between systems. Failure to address the LoA impact on these aspects in the architecting phase results in an ineffective integration. In this paper, we propose a methodology that follows the SoS hierarchical lexicon, builds upon the steps of the Object‐Oriented Systems Engineering Method (OOSEM), and leverages the Unified Architecture Framework (UAF) for modeling autonomy integration. The proposed methodology adds detailed sub‐steps to OOSEM in order to make it suitable for SoS evolution into SoAS. We also introduce the required UAF views for modeling each aspect of the SoAS architecture. This methodology lays the foundation for the trade study analysis that helps stakeholders decide on suitable LoAs for SoAS. We also present an illustrative example to demonstrate the implementation and effectiveness of the proposed methodology.
One Model to Rule them All … and Through Emergence, Bind Them
Authors: Bhalla Jawahar , Cook Stephen C. , Harvey David J. 
Published: September 2024

AbstractModels are central to understanding systems and to the engineering of systems. Systems engineers employ various types of models to communicate shared understanding, through system life‐cycle models that enable the transformation of functional models to physical models, that are then realized as tangible systems of benefit to society. The recognition of the central nature of models to the engineering of systems resulted in the forming of Model Based Systems Engineering (MBSE) wherein the essence of the system of interest is contained within a system model in contrast to traditional documents. However, the evolution of model‐types employed, both to understand and to engineer systems, appears to largely have been a pragmatic activity driven by the needs of the numerous individual engineering and management subdisciplines. This paper briefly examines extant taxonomy of systems models used in the engineering of systems and in understanding operational systems and considers the question of whether there is a suitable system “meta‐model” that naturally “contains” all types of systems models used therein. It explores this question through a systems‐thinking lens, in conjunction with concepts on mental models from biology and philosophy. This analysis gives rise to framework for systems models and to the proposition that all (systems) models take on one of two forms: as reference models that aid in the engineering of systems or as representative models that aid in understanding operational systems. The paper concludes that it is possible to propose an emergent “model of systems models” that combines these two classes in an evolutionary way. This construct is offered for consideration and refinement by the systems community.
Modeling Principles to Moderate the Growth of Technical Debt in Descriptive Models
Authors: Noguchi Ryan A. 
Published: September 2024

AbstractModel‐Based Systems Engineering (MBSE) is the next step in the evolution of systems engineering (SE) in which documents are replaced by descriptive models as the authoritative embodiment of SE knowledge. These descriptive models possess a unique combination of the features and characteristics of documents, software, and data. Conscientiously applying appropriate modeling principles and practices is essential to make informed decisions to moderate the accumulation of model technical debt. This paper briefly explains the concept of technical debt and its adaptation to the domain of descriptive models for MBSE. The paper then describes 18 foundational modeling principles that model architects should consider when making architectural and implementation decisions about their models and describes some of the key model technical debt tradeoffs that result when these principles are not followed. These principles address commonly observed challenges regarding model federation architecture, the selection and use of model layers, the modeling of the domain, and the semantics of modeling constructs. Applying disciplined model architecting practices to conscientiously manage the accrual and payoff of technical debt can make the difference between an enduring model that provides substantial value throughout the life cycle of the modeled entity and a model whose value collapses under the weight of uncontrolled technical debt.
A Model‐Based Systems Engineering Approach for Trucking Fleet Replacement
Authors: Bumgarner Sean , Rudder Sarah , Daily Jeremy S. 
Published: September 2024

AbstractHeavy vehicles operating for less than truckload (LTL) carriers are utilized to the maximum extent possible for the operator to maximize vehicle return on investment. However, the decision to purchase new vehicles, reallocate the vehicle, or retire the vehicle is based on complex and interacting factors like performance degradation, total cost of ownership, new regulatory pressures, and maintenance costs. The problem of optimizing fleet capacity is well suited to a model‐based systems engineering approach. Using SysML as the language and MagicGrid as the method, a model for fleet vehicle replacement and utilization was built to understand the best way to maximize and grow shipping capacity. The process started with identifying stakeholders and their needs and ended with system parametric models capable of computing costs. This model has the potential to optimize operating costs for fleets and maximize the use of the vehicle assets. Not only do these optimizations improve company financial performance, they reduce the need to unnecessarily replace expensive equipment, which is a more sustainable business practice.
AI Systems Modeling Enhancer (AI‐SME): Initial Investigations into a ChatGPT‐enabled MBSE Modeling Assistant
Authors: Johns Brian , Carroll Kristina , Medina Casey , Lewark Rae , Walliser James 
Published: September 2024

AbstractAs artificial intelligence (AI) becomes integral across industries, there is a growing opportunity to transform the generation of models for systems engineering. This research investigates the integration of OpenAI's GPT‐4 Turbo into CATIA Magic for Model‐Based Systems Engineering (MBSE), resulting in the creation of AI Systems Modeling Enhancer (AI‐SME). This study explores the comparison between models generated by AI, specifically OpenAI's GPT, and those crafted by human systems engineers. While recognizing challenges in AI‐generated models, this research underscores the potential of AI assistants to enhance the speed and accuracy of SysML model creation. Results demonstrate AI‐SME's successes in generating requirements, block definition diagrams, and internal block diagrams. Despite identified limitations such as redundancy and lack of cohesiveness in AI‐generated models, the study concludes that AI‐SME represents a notable advancement in AI‐assisted systems engineering.
A Technical Approach to the Digital Signature of MBSE Models
Authors: Gorospe Risa , Dubicki Shannon 
Published: September 2024

AbstractTo fully realize the benefits of Model‐Based Systems Engineering (MBSE), users of an MBSE model need to be able to verify its authenticity and integrity. A digital signature is a common cryptographic technique that enables users to sign digital content and verify the integrity of the signed content. This enables users to verify that the signed content is truly from the author who signed the content and is a common practice in digital documentation. MBSE models have unique qualities that separate themselves from other digital documentation, thus specific digital signature approaches need to be implemented for MBSE models.This paper describes an approach to apply digital signatures to MBSE models. The approach explores some characteristics of MBSE models and enables the digital signing of a portion of a model using a signer's digital certificate. The approach allows for the verification of the signed model content against the signature and indicates if information is altered from what the signer intended. This paper captures the technical challenges and lessons learned applying this approach as a prototype to an existing MBSE modeling tool. These findings from this paper can be used to guide the development of a digital signature capability in MBSE modeling tools.
A System Dynamics Model of Organizational Resilience
Authors: Taylor Ivan W. , Hossain Niamat Ullah Ibne 
Published: September 2024

AbstractResilience is the ability to avoid, withstand, and recover from adversity. In this paper, we examine organizational resilience using a case study of an organization that suffers from a series of scandals that lead to problems with its reputation as an inclusive organization, which results in difficulties in recruiting and retaining employees. We suggest some policies involving leadership efforts to change the culture in the organization and thereby restore its reputation. Based on the results of a System Dynamics Model that mixes quantitative and qualitative measures, we find that changing organizational culture is difficult. There can be inertia and long delays before the leadership sees results in improved recruiting and retention statistics.
Architecture of Nature‐Based Smart City Introducing BaaS by Utilizing UAF
Authors: Chen Weiwei , Iwamura Atsushi , Nishimura Hidekazu 
Published: September 2024

AbstractSmart cities collaborate with various technological systems, including Internet of Things (IoT), artificial intelligence (AI), and drones, to fulfil the expectations of stakeholders and the needs of individuals and society. The use of such advanced technological systems may impose a burden on the natural environment, posing a risk to the sustainability of nature. We have already proposed the concept of biophilia as a service (BaaS) that is a service contributing to human well‐being and the sustainability of nature by emphasizing the relationship between humans and nature, promoting actions that safeguard nature, and collaborating with various organizations. In this paper, a smart, sustainable, and resilient city in harmony with nature is referred to as a nature‐based smart city (NBSC) and BaaS is introduced to NBSC. We define the architecture of NBSC introducing BaaS using the Unified Architecture Framework (UAF) and extract drivers, opportunities, and challenges of the NBSC. Requirements of BaaS for NBSC are derived from the goals and the capabilities. Also, the iterating operational processes of BaaS in the context of NBSC are described and defined. Furthermore, we discuss some findings from description of the architecture of NBSC introducing BaaS to promote the nature safeguard activity, and necessity to make a balance between human well‐being and sustainable natural environment.
Synergizing Structure and Agility: A Comprehensive Analysis of SAFe Agile Framework through the Lens of Stafford Beer's Viable System Model
Authors: Cadena Juan M. , Kenley C. Robert 
Published: September 2024

AbstractThis paper presents a novel examination of the SAFe® (Scaled Agile Framework®) through the theoretical framework of Stafford Beer's Viable System Model (VSM). By applying the principles of VSM, renowned for its systemic and cybernetic approach to organizational management, we offer a unique perspective on the structural and functional aspects of SAFe® in its various configurations: Essential, Large Solution, Portfolio, and Full. The study employs functional modeling to delineate the congruencies and divergences between VSM and SAFe®, aiming to illuminate how VSM's systemic insights can enhance the implementation and efficacy of SAFe® practices. This interdisciplinary approach not only contributes to a deeper understanding of SAFe's® capabilities and limitations but also demonstrates the practical applicability of VSM in contemporary agile environments. The findings propose actionable insights for organizations seeking to optimize their agile practices through a more structured, systemic lens, thus bridging a crucial gap in agile and systems thinking literature. This paper is poised to benefit practitioners and theorists alike, offering a fresh perspective in the agile systems domain.