Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems

Following the classical work of Norbert Wiener, Ross Ashby, Ludwig von Bertalanffy and many others, the concept of System has been elaborated in different disciplinary fields, allowing interdisciplinary approaches in areas such as Physics, Biology, Chemistry, Cognitive Science, Economics, Engineering, Social Sciences, Mathematics, Medicine, Artificial Intelligence, and Philosophy. The new challenge of Complexity and Emergence has made the concept of System even more relevant to the study of problems with high contextuality. This Special Issue focuses on the nature of new problems arising from the study and modelling of complexity, their eventual common aspects, properties and approaches—already partially considered by different disciplines—as well as focusing on new, possibly unitary, theoretical frameworks. This Special Issue aims to introduce fresh impetus into systems research when the possible detection and correction of mistakes require the development of new knowledge. This book contains contributions presenting new approaches and results, problems and proposals. The context is an interdisciplinary framework dealing, in order, with electronic engineering problems; the problem of the observer; transdisciplinarity; problems of organised complexity; theoretical incompleteness; design of digital systems in a user-centred way; reaction networks as a framework for systems modelling; emergence of a stable system in reaction networks; emergence at the fundamental systems level; behavioural realization of memoryless functions

Foundations of Multi-Paradigm Modelling for Cyber-Physical Systems

This open access book coherently gathers well-founded information on the fundamentals of and formalisms for modelling cyber-physical systems (CPS). Highlighting the cross-disciplinary nature of CPS modelling, it also serves as a bridge for anyone entering CPS from related areas of computer science or engineering. Truly complex, engineered systems—known as cyber-physical systems—that integrate physical, software, and network aspects are now on the rise. However, there is no unifying theory nor systematic design methods, techniques or tools for these systems. Individual (mechanical, electrical, network or software) engineering disciplines only offer partial solutions. A technique known as Multi-Paradigm Modelling has recently emerged suggesting to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s), and then weaving the results together to form a representation of the system. If properly applied, it enables, among other global aspects, performance analysis, exhaustive simulation, and verification. This book is the first systematic attempt to bring together these formalisms for anyone starting in the field of CPS who seeks solid modelling foundations and a comprehensive introduction to the distinct existing techniques that are multi-paradigmatic. Though chiefly intended for master and post-graduate level students in computer science and engineering, it can also be used as a reference text for practitioners

xDEVS: A toolkit for interoperable modeling and simulation of formal discrete event systems

Employing Modeling and Simulation (M&S) extensively to analyze and develop complex systems is the norm today. The use of robust M&S formalisms and rigorous methodologies is essential to deal with complexity. Among them, the Discrete Event System Specification (DEVS) provides a solid framework for modeling structural, behavior and information aspects of any complex system. This gives several advantages to analyze and design complex systems: completeness, verifiability, extensibility, and maintainability. DEVS formalism has been implemented in many programming languages and executable on multiple platforms. In this paper, we describe the features of an M&S framework called xDEVS that builds upon the prevalent DEVS Application Programming Interface (API) for both modeling and simulation layers, promoting interoperability between the existing platform-specific (C++, Java, Python) DEVS implementations. Additionally, the framework can simulate the same model using sequential, parallel, or distributed architectures. The M&S engine has been reinforced with several strategies to improve performance, as well as tools to perform model analysis and verification. Finally, xDEVS also facilitates systems engineers to apply the vision of model-based systems engineering (MBSE), model-driven engineering (MDE), and model-driven systems engineering (MDSE) paradigms. We highlight the features of the proposed xDEVS framework with multiple examples and case studies illustrating the rigor and diversity of application domains it can support

A framework to study the resilience of organizations: a case study of a nuclear emergency plan

El desarrollo de la resiliencia es un campo de investigación importante en ámbitos como el Management, la Ingeniería, la Psicología o la Ecología. La importancia del estudio de la resiliencia se ha visto desarrollada por el aumento tanto de desastres naturales como antropogénicos, así como por el desarrollo de conciencia acerca de sus efectos. Estas razones de peso han influido en que los Gobiernos estén invirtiendo recursos en la mejora de la resiliencia de organizaciones, infraestructuras, ciudades, individuos, etc. Sin embargo, a pesar de su importancia, el número de trabajos de investigación que se centran en el desarrollo de metodologías específicas para el diseño de organizaciones resilientes es reducido. El principal objetivo de esta investigación es mejorar este aspecto introduciendo un marco para el diseño de organizaciones resilientes. Para alcanzar este objetivo, se explica cómo emplear el Modelo de Sistemas Viables para el diseño de estas organizaciones. Nos hemos centrado en uno de los aspectos clave de la resiliencia: las comunicaciones. Para ello, se ha usado el caso de estudio del plan de emergencia de una central nuclear en España. Las comunicaciones en una organización pueden modelarse como un proceso de difusión en redes multiplex. Buscamos arquitecturas aplicables a nuestro caso de estudio. Sin embargo, no se ha encontrado ninguna que cumpliera con los requisitos que se necesitaban. Este hecho, nos ha llevado a proponer una nueva arquitectura, que además de permitir estudiar la difusión de información en una organización, permite estudiar otros procesos de difusión en redes multiplex.Departamento de Organización de Empresas y Comercialización e Investigación de MercadosDoctorado en Ingeniería Industria

A model-based approach to System of Systems risk management

The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies

Integrated Simulation and Optimization for Decision-Making under Uncertainty with Application to Healthcare

Many real applications require decision-making under uncertainty. These decisions occur at discrete points in time, influence future decisions, and have uncertainties that evolve over time. Mean-risk stochastic integer programming (SIP) is one optimization tool for decision problems involving uncertainty. However, it may be challenging to develop a closed-form objective for some problems. Consequently, simulation of the system performance under a combination of conditions becomes necessary. Discrete event system specification (DEVS) is a useful tool for simulation and evaluation, but simulation models do not naturally include a decision-making component. This dissertation develops a novel approach whereby simulation and optimization models interact and exchange information leading to solutions that adapt to changes in system data. The integrated simulation and optimization approach was applied to the scheduling of chemotherapy appointments in an outpatient oncology clinic. First, a simulation of oncology clinic operations, DEVS-CHEMO, was developed to evaluate system performance from the patient and managements perspectives. Four scheduling algorithms were developed for DEVS-CHEMO. Computational results showed that assigning patients to both chairs and nurses improved system performance by reducing appointment duration by 3%, reducing waiting time by 34%, and reducing nurse overtime by 4%. Second, a set of mean-risk SIP models, SIP-CHEMO, was developed to determine the start date and resource assignments for each new patients appointment schedule. SIP-CHEMO considers uncertainty in appointment duration, acuity levels, and resource availability. The SIP-CHEMO models utilize the expected excess and absolute semideviation mean-risk measures. The SIP-CHEMO models increased throughput by 1%, decreased waiting time by 41%, and decreased nurse overtime by 25% when compared to DEVS-CHEMOs scheduling algorithms. Finally, a new framework integrating DEVS and SIP, DEVS-SIP, was developed. The DEVS-CHEMO and SIP-CHEMO models were combined using the DEVS-SIP framework to create DEVS-SIP-CHEMO. Appointment schedules were determined using SIP-CHEMO and implemented in DEVS-CHEMO. If the system performance failed to meet predetermined stopping criteria, DEVS-CHEMO revised SIP-CHEMO and determined a new appointment schedule. Computational results showed that DEVS-SIP-CHEMO is preferred to using simulation or optimization alone. DEVSSIP-CHEMO held throughput within 1% and improved nurse overtime by 90% and waiting time by 36% when compared to SIP-CHEMO alone

Arquitectura de un sistema integrado para diseño dirigido por modelos en el contexto de internet de las cosas con aplicaciones en medicina

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 14-10-20222Over the past few years, we have seen how processing and storage architectures become cheaper and more efficient, communication infrastructures become faster and more scalable, and many new ways of interacting with the world around us are being developed. Every day more devices are connected to the network, and the generation of data worldwide is growing exponentially. In this context, the Internet of Things promises to be the new technological revolution, as was the introduction of the network of networks or universal mobile accessibility in tis day...A lo largo de los últimos años hemos visto cómo las arquitecturas de procesamiento y almacenamiento se vuelven más baratas y eficientes, las infraestructuras de comunicación se hacen más rápidas y escalables, y se desarrollan multitud de nuevas formas de interactuar con el mundo que nos rodea. Cada día más dispositivos se conectan a la red, y la generación de datos a nivel mundal está creciendo exponencialmente. En este contexto, el Internet de las cosas promete ser la nueva revolución tecnológica, como en su día lo fue la introducción de la red de redes o la accesibilidad móvil universal...Fac. de InformáticaTRUEunpu

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration

Intelligent System for Generating and Analysis of Trading Recommendations on Financial Markets

Táto diplomová práca sa zaoberá predikciou a problematikou vývoja cien na finančných trhoch. Popisuje automatické obchodné systémy založené na technickej analýze a diskutuje možnosti použitia softcomputingu pri konštrukcií takýchto systémov. Diplomová práca okrem toho kombinuje bežné obchodné stratégie s fuzzy logikou. Praktická časť tejto práce obsahuje framework pre návrh, simuláciu a analýzu automatických obchodných stratégií. Príslušný simulátor je implementovaný v jazyku Java a založený na DEVS formalizme. Vďaka tomu framework umožnuje do obchodného modelu zahrnúť real-time komponenty. V diplomovej práci je obsiahnutá aj databáza historických finančných dát a nástroje pre jej automatickú synchronizáciu.This master thesis deals with the price prediction on financial markets. It describes automated trading systems based on technical analysis and discusses a soft computing approach to construction of such systems. Also, this thesis combines conventional trading strategies with the fuzzy logic. The practical part of this thesis contains also a framework for composing, simulation and analysis of the automated trading strategies. The simulator contained in this framework is implemented in the Java language and based on DEVS formalism. Because of this, there is a possibility to embed real-time components into the trading model. This work contains also a database of historical financial data and tools for their automatic actualization.