IEEE Open Journal of Systems Engineering最新文献

{"title":"Transition From Scenario-Based to Outcome-Based Engineering in SE4AI","authors":"Niloofar Shadab;Alejandro Salado;Tyler Cody;Peter A. Beling","doi":"10.1109/OJSE.2024.3464495","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3464495","url":null,"abstract":"As intelligent systems become increasingly integrated into our daily lives, it has become evident that there is a mismatch between traditional systems engineering (SE) practices and the nature of intelligent systems. In this article, we posit that the current SE practices need to change their hyperfocus on scenario-based engineering to a process that is more focused on engineering outcomes in the presence of changing environment. To help enabling such transition, we incorporate closed systems precepts from systems theory into formal SE practices. The concept of closed systems is based on the idea that a system is an entity that is bounded by a physical or conceptual boundary and is isolated from its environment. Closed systems are self-contained and self-regulating, and their behavior can be predicted and controlled based on the system's internal rules and mechanisms. In our previous paper, we formalized different types of closed systems and explored how SE practices can utilize these types for various applications. However, there is a need to transition from theorizing about these types of closure to implementing them in SE processes. In this article, we will demonstrate how closed system precepts can be applied to SE practices using a simple example of an intelligent system. We will explore different aspects of applying closed system formalization from our previous effort, including how to define a system's boundary when there is an intelligent property, how to perform problem formulation, and how to address a system's causal dependencies, in order to build a more scalable and well-scoped system.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"190-202"},"PeriodicalIF":0.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142518005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Defects in Sequential Inputs to Digital Twins Using Machine Learning","authors":"Nathaniel Brown;Steven Simske","doi":"10.1109/OJSE.2024.3458841","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3458841","url":null,"abstract":"This article presents a method for detecting defects in sequential data inputs for digital twins (DTs) during simulations, emphasizing the importance of input validation for ensuring the accuracy and reliability of the simulation results. By thoroughly validating input data, researchers and practitioners can have confidence in the validity of their models, ultimately leading to better decision-making processes and outcomes that are more successful. As DTs continue to expand in complexity, there are an increasing number of mechanisms that may produce undesirable output. An external data stream is just one such potential source of faulty DT behavior and must be analyzed during simulation execution. The proposed framework for validating inputs in real time offers a way to improve the quality and credibility of DTs, guiding future research in the evolving field of modeling and simulation. The case study described in this article involves using second-order polynomial regression to detect defects in rocket trajectory data streams, highlighting the effectiveness of validation techniques. This method shows promise, as it successfully identified defects in trajectories in real time using only historical data without knowledge of the future of the data stream. The novelties in this article include using machine learning to validate DT inputs, and performing this validation on sequential data in real time to protect modeled results. This research contributes valuable insights to the field, emphasizing the significance of input validation for enhancing the quality and accuracy of simulation models.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"179-189"},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10675423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review on Integrating Autonomy Into System of Systems: Challenges and Research Directions","authors":"Mohammadreza Torkjazi;Ali K. Raz","doi":"10.1109/OJSE.2024.3456037","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3456037","url":null,"abstract":"Artificial intelligence and machine learning (AI/ML) technologies convert conventional engineered systems into autonomous systems that are capable of performing tasks in their operational environment with limited to no human involvement. These technologies can reduce demands for human workload while enabling a suite of new capabilities such as autonomous vehicles and smart cities. However, a major challenge is the integration of these autonomous systems into a system of systems (SoSs), essentially resulting in a system of autonomous systems (SoASs). SoASs are fraught with new challenges that compound issues from the founding domains of SoS, AI/ML, and autonomous systems. To understand the new set of challenges for SoAS, this article conducts an extensive review of both theoretical and application-based literature published in the founding domains. The goal is to examine how individual challenges in each domain intersect and exacerbate when multiple independent systems with AI/ML are integrated into an SoAS. A particular emphasis is placed on highlighting how interactions across these domains manifest at the SoAS level. As a result, four overarching challenges for SoASs are identified that must be addressed by systems engineers to ensure a successful realization of the SoAS in the future: 1) SoAS foundation; 2) emergence, safety, and performance; 3) architecture and integration; and 4) test and evaluation. Each challenge is comprehensively examined in the three founding domains by discussing domain-specific state-of-the-art methods and tools that different engineering disciplines have proposed to address. For each challenge, we also investigated how the existing tools and methods apply to addressing the challenge for SoAS and highlighted the remaining gaps that still need to be addressed. Furthermore, this article identifies systems engineering research needs for improving SoAS foundations, analysis of autonomy impacts, and enabling SoAS architecture, integration, and evaluation methods. Conducting research studies in these fields will improve systems engineering practices for a successful and effective realization of SoAS.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"157-178"},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669760","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing System Models for Multicriteria Decision-Making—A Systematic Literature Review on the Current State of the Art","authors":"Dennis Horber;Jessica Pickel;Stefan Goetz;Sandro Wartzack","doi":"10.1109/OJSE.2024.3434310","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3434310","url":null,"abstract":"The rising system complexity of modern products requires new approaches within model-based systems engineering to manage the upcoming challenges. System development is characterized by a wide variety of decisions to be made. These situations have to be modeled within a holistic system model to ensure traceability. Motivated by lack of a comprehensive overview of approaches, this article presents the results of a systematic literature study focusing on utilizing system models in decision-making. By that, the existing gap between theoretical foundations and implementation in practical use is intended to be closed through providing practitioners insights to relevant approaches. Apart from that, researchers are enabled to derive new research directions from the corpus of literature. Relevant reports use different diagrams to model a decision situation or its processes and reuse those diagrams as well as their contents to feed methods from multicriteria decision-making. By that, new objectives are added to those diagrams, namely to enable extensive decision-making, which is understood as their utilization. Thus, this article provides an overview of applied decision-making approaches, languages used to model the decision context, and the use of external tools, where the decision-making algorithms are executed. The findings show that the majority of existing approaches only cover certain aspects of the decision-making situation in the system model and especially the formalization of the decision-making process is hardly considered. Besides that, future research fields including the analysis of potentials coming along with the introduction of systems modeling language v2 and especially its API are identified.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"135-147"},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10612218","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Architecture, Analysis, and Design of Systems Using Extensions of Category Theory","authors":"Charles E. Dickerson;Michael K. Wilkinson","doi":"10.1109/OJSE.2024.3432570","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3432570","url":null,"abstract":"The engineering of systems has lacked the scientific and mathematical underpinnings enjoyed by traditional engineering disciplines. Earlier work of the authors formulated advanced mathematical methods for architecture definition and the use of model theory in engineering. In this article, an extension of the category of relations is defined by a semantically richer algebraic logic, denoted as CoR, suitable for analysis and design. This complements and extends the rigorous basis for our earlier work. CoR uses category theory coupled with the semantically richer logic as an architectural language for specifying structural views of concepts with concordant graphical and algebraic relational views for analysis and design. A radar case study is used to demonstrate methods for the application of these views to everyday engineering practice. CoR also addresses and can improve the expressiveness of modeling languages, such as SysMLv2. Schemata are defined to provide mathematical blueprints of the views. The intent is that CoR can be implemented in systems tools that are well-suited for engineering practitioners. This article offers a rigorous but practical platform for establishing a new generation of systems engineering methodologies, tools, and languages.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"105-118"},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10607870","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141991508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Model-Based Reverse System Engineering Methodology for Analyzing Complex Biological Systems With a Case Study in Glycolysis","authors":"Gerald L. Fudge;Emily Brown Reeves","doi":"10.1109/OJSE.2024.3431868","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3431868","url":null,"abstract":"We propose a model-based reverse systems engineering (MBRSE) methodology for biological systems that relies on requirements analysis in conjunction with model-based systems engineering (MBSE). The goal of this methodology is to better understand complex multiscale biological systems, discover knowledge gaps, and make testable predictions. The similarities between human-engineered and biological systems motivate this approach. Furthermore, traditional reductionist paradigms in biology have proven insufficient for understanding and accurately predicting complex biological systems, as opposed to systems engineering approaches that have proven effective in supporting the design and analysis of complex engineered systems spanning multiple spatiotemporal scales. We employ our MBRSE methodology to analyze glycolysis in a biological case study using object process methodology as the primary MBSE language for conceptual qualitative modeling, in conjunction with SysML use case modeling. Using the MBRSE methodology, we derive twenty-two requirements, uncover five gaps in knowledge, and generate six predictions for the core metabolic pathway of glycolysis. One significant prediction is that the Warburg effect associated with cancer is the result of a natural response to tissue injury that has become unstable due to a failure in the feedback mechanism of the tissue injury control system.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"119-134"},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10605905","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142084482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Design Structure Matrices Using Markov Chain Modeling and Community Detection","authors":"Rami Al Khatib;Armando Chacon","doi":"10.1109/OJSE.2024.3431468","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3431468","url":null,"abstract":"This article proposes a new method to enhance the efficiency of the design process in systems engineering. Our approach involves utilizing a Markov chain based on the design structure matrix (DSM). By creating a transformation matrix using the DSM and converting it into a Markov chain, we enable faster convergence of process iterations and improved decoupling between modules or clusters. The Markov chain is plotted as a tree using a layered layout algorithm and partitioned into communities using the Louvain algorithm. We applied our method to two types of DSM data, i.e., component-based and parameter-based, and the results showed valuable insights into the design process. Our approach is a valuable tool for managing complex systems, especially as systems become increasingly complex and challenging for engineers to manage during the design process.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"148-156"},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10605078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Current Practices and Challenges of HIPAA Compliance in Software Engineering: Scoping Review","authors":"Farah Elkourdi;Chenhao Wei;LU Xiao;Zhongyuan YU;Onur Asan","doi":"10.1109/OJSE.2024.3392691","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3392691","url":null,"abstract":"Healthcare systems and applications are increasingly used to improve patient care. However, these applications face data security, privacy, and regulatory compliance challenges. The health insurance portability and accountability act (HIPAA) regulates the use and disclosure of patient health information. Ensuring HIPAA compliance in the software engineering process poses critical challenges to software engineering practitioners. This review focuses on understanding the state-of-the-art in the current literature for ensuring HIPAA compliance in the software development life cycle, namely, requirement gathering, software design, implementation, software testing, and evolution. The findings of this study shed light on software engineers in creating HIPAA compliance healthcare systems and applications. This literature review presents the key themes and trends in this research area. Also, it provides recommendations for future research in the intersection of software engineering methods and HIPAA compliance.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"94-104"},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10506964","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141068962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic Mapping Study of Systems Security Engineering for Modular Open Systems","authors":"Giselle Bonilla-Ortiz;Dinesh Verma;James N. Head;Lu Xiao;Koduvayur Subbalakshmi","doi":"10.1109/OJSE.2024.3391734","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3391734","url":null,"abstract":"Modular Open Systems Approach (MOSA), a recent initiative to increase competition in the defense market, has become a directive to new acquisition programs. It is a United States Department of Defense (DoD) initiative for designing composable systems with open standards that can be acquired from independent vendors, while allowing an adaptive response to evolving threats. Implementation of MOSA was signed into law in the National Defense Authorization Act for Fiscal Year 2021, requiring regulations to facilitate DoD's access to and utilization of modular system interfaces and implementation of openness across major acquisition programs. MOSA's objectives include interoperability, technology refresh, increased competition, innovation, and cost savings. Determining an effective strategy to realize this intent is of paramount importance to industry. Current MOSA research focuses on developing guidelines for incorporating modularity and open standards into DoD acquisition. Given the concurrent priority regarding system security and cyber-resilience, there is a gap in open literature regarding architectural and design guidelines focused on security and cyber-resilience requirements for MOSA. This systematic mapping resulted in the selection of 33 relevant research papers. A hybrid approach of inductive and deductive qualitative coding was used as a method of rigor in extracting answers to the research questions.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"83-93"},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10506332","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ViSnow: Snow-Covered Urban Roads Dataset for Computer Vision Applications","authors":"Mohamed Karaa;Hakim Ghazzai;Lokman Sboui","doi":"10.1109/OJSE.2024.3391315","DOIUrl":"https://doi.org/10.1109/OJSE.2024.3391315","url":null,"abstract":"Road surface condition estimation is an important task in fields related to transportation systems and road maintenance, especially in adverse weather conditions, such as snowfall. In this article, we introduce an image dataset for snow-covered roads in an urban context. The dataset is an extensive collection of images captured by traffic monitoring cameras in Montreal, QC, Canada, during the winters of 2022 and 2023. We detail the process of acquiring the dataset, including the source and the methodology to enable the replication of such a process. We also present an exploratory dataset description to showcase its rich contextual representation of the urban winter scene at different times, locations, and weather conditions. We also establish a benchmark problem for the dataset that consists of automating its annotation process. This process should add value to the dataset by attributing a label describing the snow level covering the road for each image. Finally, we discuss potential applications the dataset can enable in fields, such as transportation and winter road maintenance.","PeriodicalId":100632,"journal":{"name":"IEEE Open Journal of Systems Engineering","volume":"2 ","pages":"62-70"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10505763","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}