Self-Healing in Cyber–Physical Systems Using Machine Learning:A Critical Analysis of Theories and Tools

The rapid advancement of networking, computing, sensing, and control systems has introduced a wide range of cyber threats, including those from new devices deployed during the development of scenarios. With recent advancements in automobiles, medical devices, smart industrial systems, and other technologies, system failures resulting from external attacks or internal process malfunctions are increasingly common. Restoring the system’s stable state requires autonomous intervention through the self-healing process to maintain service quality. This paper, therefore, aims to analyse state of the art and identify where self-healing using machine learning can be applied to cyber–physical systems to enhance security and prevent failures within the system. The paper describes three key components of self-healing functionality in computer systems: anomaly detection, fault alert, and fault auto-remediation. The significance of these components is that self-healing functionality cannot be practical without considering all three. Understanding the self-healing theories that form the guiding principles for implementing these functionalities with real-life implications is crucial. There are strong indications that self-healing functionality in the cyber–physical system is an emerging area of research that holds great promise for the future of computing technology. It has the potential to provide seamless self-organising and self-restoration functionality to cyber–physical systems, leading to increased security of systems and improved user experience. For instance, a functional self-healing system implemented on a power grid will react autonomously when a threat or fault occurs, without requiring human intervention to restore power to communities and preserve critical services after power outages or defects. This paper presents the existing vulnerabilities, threats, and challenges and critically analyses the current self-healing theories and methods that use machine learning for cyber–physical systems

Dissolving boundaries among applied disciplines: a narrative study of transdisciplinary collaboration during a charrette

2021 Spring.Includes bibliographical references.Charrettes have a long history of use in medical, architectural, and planning professions. An extensive literature search found little application of the charrette model implemented to advance, support, and identify transdisciplinarity (TD) research, transdisciplinary teaming models (TDM), transdisciplinary learning (TDL) supporting transformative learning (TL) among participants. This study highlighted differing approaches among teams as they navigated ideation and proposed solutions advancing comprehension among students of applied disciplines and how each approached, negotiated, and solved community-based problems. I implemented a TDM charrette to address TDL in educational settings. This two charrette case study implemented 1) an exploratory investigation joined a competition to create a high school of the future in underserved Montbello, Colorado, and 2) a proposal to renovate and develop a historic homestead on a working cattle ranch and wildlife reserve to support a multi-generational educational program, in Sedalia, Colorado. Charrettes included college students from architectural design, construction management, education, environmental sciences, and fish and wildlife. High school students were joined by POs from education, business and ranching professions, artists, and authors. Participants were challenged to create programs using site attributes. Charrette's culminated with team project proposals shared with invited stakeholders. Using Hall's four-phases of TD team based experiential learning and Kolb's Learning Style Models I used visual narrative and a sustainability lens to reflect and incorporate participant experiences and outcomes. Findings identified how students experienced charrettes, how they interacted with other disciplines, participant observers (PO)/facilitator observers (FO), and project stakeholders. TDM emphasized the importance of self-reflection revealed by mutual learning of transferable solutions, synthesis of results, and the visibility and relevance to problem solving. Outcomes showed how participants explored, described discipline knowledge; how shared skills shaped and influenced information sharing, leading to transformative learning (TL). Key findings identified knowledge derived from multiple modes of inquiry gained from TDL addressed problems, contributed to transferability. Challenges identified recruitment of participants from more than three disciplines. This study described and shared how participation advanced knowledge production and integration to solve unstructured problems. The TDM charrette supported TDL and knowledge production that bridged solution oriented approaches among participants leading to TL

Developing and Implementing Self-Direction Programs and Policies: A Handbook

Provides a guide to designing, implementing, and evaluating service delivery models that allow public program participants to manage their own care services and supports. Outlines elements of employer and budget authorities, enrollment, and counseling

RTD Evaluation Toolbox. Assessing the Socio-Economic Impact of RTD-Policies

Abstract not availableJRC.J-Institute for Prospective Technological Studies (Seville

A reactive architecture for cloud-based system engineering

PhD ThesisSoftware system engineering is increasingly practised over globally distributed locations. Such a practise is termed as Global Software Development (GSD). GSD has become a business necessity mainly because of the scarcity of resources, cost, and the need to locate development closer to the customers. GSD is highly dependent on requirements management, but system requirements continuously change. Poorly managed change in requirements affects the overall cost, schedule and quality of GSD projects. It is particularly challenging to manage and trace such changes, and hence we require a rigorous requirement change management (RCM) process. RCM is not trivial in collocated software development; and with the presence of geographical, cultural, social and temporal factors, it makes RCM profoundly difficult for GSD. Existing RCM methods do not take into consideration these issues faced in GSD. Considering the state-of-the-art in RCM, design and analysis of architecture, and cloud accountability, this work contributes: 1. an alternative and novel mechanism for effective information and knowledge-sharing towards RCM and traceability. 2. a novel methodology for the design and analysis of small-to-medium size cloud-based systems, with a particular focus on the trade-off of quality attributes. 3. a dependable framework that facilitates the RCM and traceability method for cloud-based system engineering. 4. a novel methodology for assuring cloud accountability in terms of dependability. 5. a cloud-based framework to facilitate the cloud accountability methodology. The results show a traceable RCM linkage between system engineering processes and stakeholder requirements for cloud-based GSD projects, which is better than existing approaches. Also, the results show an improved dependability assurance of systems interfacing with the unpredictable cloud environment. We reach the conclusion that RCM with a clear focus on traceability, which is then facilitated by a dependable framework, improves the chance of developing a cloud-based GSD project successfully

Road Management System and Road Safety in Uganda

Traffic collisions cost Uganda millions of dollars each year. The purpose of this descriptive case study was to describe the strategies and processes needed to implement a road management system. Such a system would significantly reduce the fatalities and accidents in Uganda, improve the transportation within Kampala\u27s business district, and increase business profitability. Three conceptual theories framed the research study: management theory, strategic management theory, and criminology theory. Using a snowball sampling strategy, data were collected from open-ended interviews, questionnaires, observations, and archived documents from 20 administrative participants in the government and organizational leaders involved in the transport operations and transport services in the Kampala business district in Uganda. Data were analyzed using 3 phases: (a) interpretational analysis, coding, and grouping segments; (b) structural analysis, consistency, and quality; and (c) reflective analysis, consequences, what, when, where, and how. Five themes or action requirements emerged from the data analysis: to improve transport operations and transport services profitability, reduce traffic jams and fatalities, provide sufficient driving training, maintain road infrastructure, and maintain traffic law enforcement. The findings and recommendations from this study may improve the profitability of businesses, reduce the traffic jams and fatalities, and improve the gross domestic product of Uganda, thereby contributing to positive social change

Complexity within the Air Force acquisition system gaining insight from a theory of collapse

Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 122-129).Joseph Tainter's theory of societal collapse is applied in an examination of the U.S. Air Force's aircraft acquisition system in order to gain insight into the enterprise's lagging performance. Theories of collapse at both the societal level and the organizational level are reviewed. Tainter's interrelationship between increasing system complexity and diminishing marginal returns is highlighted as especially relevant to the performance of the Air Force aircraft acquisition enterprise. Using Tainter's theory as a framework, evidence is gathered leading to the conclusions that the Air Force aircraft acquisition enterprise is highly complex and as a result is experiencing diminishing marginal returns. Tainter's framework is then also used to explain why past attempts to reform the enterprise have fallen short of their goals. Previous reform efforts, in the form of reorganizations and senior leader initiatives, have been ineffectual beyond the short term because they fail to reduce the underlying level of complexity within the enterprise. The use of workarounds by stakeholders within the enterprise are shown to be efforts to increase marginal returns and avoid overcomplexity. The primary implication of viewing the Air Force aircraft acquisition enterprise through the lens of Tainter's theory of collapse is that in order to be effective, any effort undertaken to improve the performance of the enterprise must reduce the overall level of complexity within the system. Additional insights include the use of current workarounds as leading indicators of complexity or overly burdensome processes. Lastly, senior acquisition leaders should be prepared should a collapse of the enterprise occur. A vision of a much less complex enterprise should be advocated.by Daniel Nicholas Marticello Jr.S.M.in Engineering and Managemen

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii