Software engineers and researchers in the field are constantly developing new technologies to manage the complexity of current software systems. There is an increasing need for mechanisms that can deal with dynamics in the systems’ environment, goals, and requirements. Self-adaptive software systems are a solution to manage the complexity caused by dynamics or runtime variations. Software reuse is a classical solution to deal with complexity and increase the quality of a system in a systematic and efficient way. Despite the large amount of research on self-adaptation, no systematic study has been found, which surveys and reports the application of reuse methods and techniques for the development of self-adaptive software systems. A systematic analysis of reuse methods and techniques for the development of self-adaptive systems is interesting as it provides useful insights for researchers and practitioners in the self-adaptive area. This study systematically reviews relevant research work published between the years 2000 and 2020 at eight well-known venues on self-adaptation and software engineering. By following the systematic litera-ture review method, 97 studies were reviewed and 40 primary studies identi-fied for addressing the research questions. The main objectives of the review are 1) to collect and analyse the reuse-based methods studied and applied for the design and development of self-adaptive software systems, 2) analyse the challenges in the application of reuse-based methods for the development of self-adaptive software systems. The review shows that most of the analysed studies support reuse with component-based software engineering. The pri-mary studies propose different reuse-based methods to allow faster and sim-pler development of self-adaptive systems. Furthermore, the analysis shows that the reviewed studies report several challenges related to the configura-tion process, design, performance and uncertainty in the application of reuse methods for the development of self-adaptive systems.

Connected aviation, the Internet of Flying Things and related emerging technologies, such as the System-Wide Information Management infrastructure of the FAA NextGen program, present numerous opportunities for the aviation sector. The ubiquity of aeronautical, flight, weather, aerodrome, and maintenance data accelerates the development of smarter software systems to cope with the ever increasing requirements of the industry sector. The increasing amount, frequency and variety of real-time data available to modern air transport and tactical systems, and their crews, creates exciting new challenges and research opportunities. We present an architectural approach toward the vision of increasingly self-separating and self-governed flight operations within the bigger picture of an evolving set of future Autonomous Flight Rules. The challenges in this field of research are manifold and include autonomic airborne trajectory optimization, data sharing, fusion and information derivation, the incorporation of and communication with rational actors—both human and machine—via a connected aviation infrastructure, to facilitate smarter decision making and support while generating economical, environmental and tactical advantages. We developed a concept and prototype implementation of our Smart Autoflight Control System. The concept and implemented system follow the design principle of an Autonomic Element, consisting of an Autonomic Manager and its Managed Element, acting within an Autonomic Context. The Managed Element concept embraces an infrastructure featuring suitable models of manageable environments, airborne agents, planners, applicable operational cost and risk policies, and connections to the System-Wide Information Management cloud as well as to relevant rational actors, such as Air Traffic Control, Command and Control, Operations or Dispatch. The Autonomic Manager concept incorporates the extraction, that is, short-term sensing, of features from operational scenarios and the categorization of these scenarios according to their level of criticality and associated flight phase. The Autonomic Manager component, furthermore, continuously tunes, that is, actuates, manageable items of its Managed Element, such as environments and planners, and triggers competitions to assess their performance under the various extracted and dynamically changing features of their Autonomic Context. The performance reputations of the tuned manageable items are collected in a knowledge base and may serve as a long-term sensor. Both the managed items of the Managed Element as well the managing items of the Autonomic Manager are extendable and may realize very different paradigms, including deterministic, non-deterministic, heuristically guided, and biologically inspired approaches. We assessed the extensibility and maintainability of our Smart Autoflight Control System infrastructure by including manageable environments and planners of the Classical Grid Search, Probabilistic Roadmaps, and Rapidly-Exploring Random Trees families into its core component. Furthermore, we evaluated the viability of a simple heuristic and a more sophisticated Sequential Model-Based Algorithm Configuration Autonomic Manager to adaptively select and tune manageable planners of the supported families based on the extracted features from very simple to highly challenging scenarios. We were able to show that a self-adaptive approach, that heuristically tunes and selects the best performing planner following a performance competition, produces suitable flight trajectories within reasonable deliberation times. Additionally, we discovered options for improving our heuristic Autonomic Manager through a series of evaluation runs of the Sequential Model-Based Algorithm Configuration Autonomic Manager. Our contributions answer how the manageable items, that is, environments and planners, of our Smart Autoflight Control System core component have to be modified in order to embed System-Wide Information Management data that feature both spatial and temporal aspects. We show how operational cost and risk policies help to assess environments differently and plan suitable flight trajectories accordingly. We identify and implement the necessary extensions and capabilities that have to be supported by manageable and managing items, respectively, to enable continuous feature extraction, adaptive tuning, performance competitions, and planner selection in dynamic flight scenarios. / Graduate

Due to increased expectations as well as advances in technology, the interest in Self-adaptive Systems has increased in the last few years. As a consequence of this, thebody of work has also dramatically expanded, and it is essential to have an overviewin order to identify common problems and knowledge gaps. This paper introduces avisualization tool for the state of the art of Self-adaptive Systems. The tool shouldprovide all the needed insights into the body of work in the field of Self-adaptiveSystems.

Military conflicts have become nonlinear and the interrelated political and socio-economic changes within these conflicts have created new challenges for American policymakers. A tool called Wallis' Propositional Analysis (PA) suggests a new paradigm that includes thinking about complexity and robustness/systemicity in a policy. The purpose of this single case study was to determine how the PA paradigm adds heuristic value to complex policy decision-making. A backdrop of Wallerstein's complexity theory and complex adaptive systems (CAS) guided this study. This study examined policy statements from the Obama administration on the Afghanistan and Pakistan conflicts in late December 2009. Data were coded and analyzed using Wallis' specific methodological approach that includes a systematic analysis of the policy's propositions and complexity and robustness/systemicity. Key findings indicated that the PA paradigm offers a heuristic method for how to think about the interrelated propositions within a policy that reflect the expected changes the policy intends to make. Specifically, this study demonstrated that an interwoven PA structural approach to policymaking affords the policymaker a method to consider the complex and nonlinear changes in the policy environment. By applying the PA paradigm, policymakers can positively impact social change by exploring policy options that consider a range of possible outcomes from the policy proposal, prior to policy implementation.

Health care providers in the United States expend more than $400 million in unnecessary direct costs annually managing the effects of widespread drug shortages. Based on the theory of complexity and complex adaptive systems, the purpose of this exploratory multiple case study was to identify the strategies that health care pharmaceutical procurement leaders from the Eastern region of the United States use to address widespread drug shortages. Data were collected from 5 semistructured interviews with pharmaceutical procurement leaders, recorded field notes, and a review of public documents from company websites. Data analysis included deductive and open coding techniques. Emergent themes included: (a) proactive planning for supply chain and distribution channel disruptions, (b) creating strategic processes for alternative procurement methods, and (c) relying on proven sources of actionable information. Findings may influence business practices for health care procurement leaders by contributing new knowledge to develop strategies to address disruptions and drug shortages. Health care policy makers may use the findings to assess key strategies in delivering pharmaceutical products from manufacturers to end users.

No description available.

No description available.

Drawing upon the theories of complexity and complex adaptive systems and the Singerian Inquiring System from C. West Churchman's seminal work The Design of Inquiring Systems the dissertation herein develops a systems design theory for continuous auditing systems. The dissertation consists of discussion of the two foundational theories, development of the Theory of Complex Adaptive Inquiring Organizations (CAIO) and associated design principles for a continuous auditing system supporting a CAIO, and instantiation of the CAIO theory. The instantiation consists of an agent-based model depicting the marketplace for Frontier Airlines that generates an anticipated market share used as an integral component in a mock auditor going concern opinion for the airline. As a whole, the dissertation addresses the lack of an underlying system design theory and comprehensive view needed to build upon and advance the continuous assurance movement and addresses the question of how continuous auditing systems should be designed to produce knowledge--knowledge that benefits auditors, clients, and society as a whole.

Yes / This correspondence presents an investigation into the comparative performance of an active vibration control (AVC) system using a number of intelligent learning algorithms. Recursive least square (RLS), evolutionary genetic algorithms (GAs), general regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS) algorithms are proposed to develop the mechanisms of an AVC system. The controller is designed on the basis of optimal vibration suppression using a plant model. A simulation platform of a flexible beam system in transverse vibration using a finite difference method is considered to demonstrate the capabilities of the AVC system using RLS, GAs, GRNN, and ANFIS. The simulation model of the AVC system is implemented, tested, and its performance is assessed for the system identification models using the proposed algorithms. Finally, a comparative performance of the algorithms in implementing the model of the AVC system is presented and discussed through a set of experiments.

The realm of the nano-world begins when things start getting smaller in size than one thousandth of the thickness of the human hair. Surface patterning at the nanoscale has started to find applications in information storage, self-cleaning of surfaces due to the "lotus effect", biocompatible materials based on surface roughness and many more. Several methods such as particle-beam writing, optical lithography, stamping and various kinds of self-assembly are widely used to serve the purpose of patterning smaller surface structures. However, globally much research is going into developing more efficient, reproducible and simple methods of patterning surfaces and in better controlling the order of these nanostructures. Researchers have always looked upon Nature to get inspiration and to mimic its model in engineering novel architectures. One of the methods used by this greatest artist (Nature) to make beautiful patterns around is through reaction diffusion based non-linear processes. Non-linear systems driven away from equilibrium sustain pattern only during the continuous dissipation of a regular flow of energy and are different from equilibrium processes that are converging towards a minimum in free energy (a. k. a. self-assembly). Dissipative pattern formation from micrometer to kilometers scale has been known but ordered patterns at nanoscale have never been achieved. In the process of thoroughly characterizing suitable substrates for nanoelectronics applications, we came across a remarkable process leading to the formation of highly ordered arrays of dimples on tantalum. The pattern formation happens in a narrow electrochemical windows which are functions of many parameters such as concentration, external applied voltage, temperature etc. After investigating the formation of dimples by performing spatio-temporal studies, we found that the underlying principles behind this unique way of engineering nano-structures have their roots in nonlinear interaction/reaction electro-hydrodynamics. We then have demonstrated the generality of this process by extending it to titanium, tungsten and zirconium surfaces. The pattern similar to Rayleigh-Bernard convection cells originates inside the electrochemical solution due to coupling among electrolyte ions during their migration across the electrochemical double layer (Helmholtz layer) and simultaneously imprints on the surface due to dissolution of metal oxide via etching. Based on these results we further postulate that, given appropriate electropolishing chemistry; these patterns can be formed on virtually any metal or semiconductor surface. The application of these nanostructures as nanobeakers for placing metal nanoparticles is also elucidated Highly porous materials such as mesoporous oxides are of technological interest for catalytic, sensing, optical and filtration applications: the mesoporous materials (with pores of size 2-50 nm) in the form of thin films can be used as membranes due large surface area. In the second part of this thesis, a new technique of making detachable ultrathin membranes of transition metal oxides is presented. The underlying concepts behind the detachment of membranes from the underlying substrate surface are discussed. The control on the size of the pores by modulating the voltage and concentration is also elucidated. The method is generalized by showing the similar detachment behavior on other metal oxide membranes.Thus, the results of this work introduces new techniques of engineering nanostructures on surfaces based on reaction-diffusion adaptive systems and contribute to the better understanding of electrochemical self-organization phenomena due to migration coupling induced electro-hydrodynamics. / Thesis / Doctor of Philosophy (PhD)