This work topic is development and history of intelligent wiring systems in Czech Republic as well as abroad. The firs paragraphs describe following: intelligent wiring systems, the differences between classic and intelligent wiring systems and consequently is described the intelligent wiring system itself (types, principles, advantages, disadvantages etc.). Detailed description of system Inels follows in the next chapters. This system is supposed to be the fundamental matter of this work and is used in consequent suggestions for intelligent wiring system that is defined at the end of the theoretical part of this work. At the conclusion the economic evaluation of various wiring options and assessment by the multicriteria analysis (MCA) will be provided.

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The Concurrent Design Platform 4 (CDP4®) is a collaborative Model-Based Systems Engineering (MBSE) software tool conceived for architecting complex systems. Nevertheless, there are limitations concerning the manageable number of system options. The upcoming Siemens tool for generative engineering, Simcenter™ Studio, is attempting to overcome this limitation by enabling automatic synthesis and evaluation of architecture variants. The motivation for the Generative Concurrent Design (GCD) project as a collaboration between RHEA, Siemens and OHB is to develop a combined prototype of these two tools. This thesis presents a modelling of Copernicus Next Generation (CNG) space component, using generative capabilities in a typical Phase-0 study. It represents the third step of the bottom-up GCD validation process, intended to investigate how architecting differs among “Sub-system”, “Systems” and “Systems of Systems (SoS)”. Therefore, this work provides an architecting strategy which is generalizable for other SoS use-cases and contributes to assess whether extensions to ECSS-E-TM-10-25 are necessary to successfully support GCD. / Concurrent Design Platform 4 (CDP4®) är ett samarbetsverktyg för modellbaserad systemteknik (MBSE) som utformats för att bygga komplexa system. Dock finns det begränsningar vad gäller det antalet hanterbara systemalternativ. Det kommande Siemens-verktyget för generativ teknik, Simcenter™ Studio, försöker övervinna denna begränsning genom att möjliggöra automatisk syntes och utvärdering av arkitekturvarianter. Motivationen för Generative Concurrent Design (GCD) -projektet som ett samarbete mellan RHEA, Siemens och OHB är att utveckla en kombinerad prototyp av verktygen CDP4® och Simcenter™. Detta examensarbete presenterar en modellering av rymdkomponenten Copernicus Next Generation (CNG) med användning av generativa funktioner i en typisk fas-0-studie. Den representerar det tredje steget i GCD-valideringsprocessen nedifrån och upp, avsedd att undersöka hur arkitekturen skiljer sig åt mellan "Sub-system", "Systems" och "Systems of Systems (SoS)". Detta arbete ger därför en arkitektonisk strategi som är generaliserbar för andra SoS-användningsfall och bidrar till att bedöma om förlängningar till ECSS-E-TM-10-25 är nödvändiga för att framgångsrikt stödja GCD.

Current models that assess infrastructure failure risk are "linear," and therefore, only consider the direct influence attributed to each factor that defines risk. These models do not consider the undeniable relationships that exist among these parameters. In reality, factors that define risk are interdependent and influence each other in a "non-linear" fashion through feedback effects. Current infrastructure failure risk assessment models are also static, and do not allow infrastructure managers and decision makers to evaluate the impacts over time, especially the long-term impact of risk mitigation actions. Factors that define infrastructure failure risk are in constant change. In a strategic manner, this research proposes a new risk-based infrastructure management framework and supporting system, Risk-Based Dynamic Infrastructure Management System (RiskDIMS), which moves from linear to non-linear risk assessment by applying systems engineering methods and analogs developed to address non-linear complex problems. The approach suggests dynamically integrating principal factors that define infrastructure failure risk using a unique platform that leverages Geospatial Information System services and extensions in an unprecedented manner. RiskDIMS is expected to produce results that are often counterintuitive and unexpected, but aligned to our complex reality, suggesting that the combination of geospatial and temporal analyses is required for sustainable risk-based decision making. To better illustrate the value added of temporal analysis in risk assessment, this study also develops and implements a non-linear dynamic model to simulate the behavior over time of infrastructure failure risk associated with an existing network of levees in New Orleans due to diverse infrastructure management investments. Although, the framework and RiskDIMS are discussed here in the context of levees, the concept applies to other critical infrastructure assets and systems. This research aims to become the foundation for future risk analysis system implementation. / Master of Science

Les systèmes neuromusculaires et musculo-squelettique sont considérés comme un système de systèmes complexe. En effet, le mouvement du corps humain est contrôlé par le système nerveux central par l'activation des cellules musculaires squelettiques. L'activation du muscle produit deux phénomènes différents : mécanique et électrique. Ces deux activités possèdent des propriétés différentes, mais l'activité mécanique ne peut avoir lieu sans l'activité électrique et réciproquement. L'activité mécanique de la contraction du muscle squelettique est responsable du mouvement. Le mouvement étant primordial pour la vie humaine, il est crucial de comprendre son fonctionnement et sa génération qui pourront aider à détecter des déficiences dans les systèmes neuromusculaire et musculo-squelettique. Ce mouvement est décrit par les forces musculaires et les moments agissant sur une articulation particulière. En conséquence, les systèmes neuromusculaires et musculo-squelettique peuvent être évalués avec le diagnostic et le management des maladies neurologiques et orthopédiques à travers l'estimation de la force. Néanmoins, la force produite par un seul muscle ne peut être mesurée que par une technique très invasive. C'est pour cela, que l'estimation de cette force reste l'un des grands challenges de la biomécanique. De plus, comme dit précédemment, l'activation musculaire possède aussi une réponse électrique qui est corrélée à la réponse mécanique. Cette résultante électrique est appelée l'électromyogramme (EMG) et peut être mesurée d'une façon non invasive à l'aide d'électrodes de surface. L'EMG est la somme des trains de potentiel d'action d'unité motrice qui sont responsable de la contraction musculaire et de la génération du mouvement. Ce signal électrique peut être mesuré par des électrodes à la surface de la peau et est appelé I'EMG de surface {sEMG). Pour un muscle unique, en supposant que la relation entre l'amplitude du sEMG et la force est monotone, plusieurs études ont essayé d'estimer cette force en développant des modèles actionnés par ce signal. Toutefois, ces modèles contiennent plusieurs limites à cause des hypothèses irréalistes par rapport à l'activation neurale. Dans cette thèse, nous proposons un nouveau modèle de relation sEMG/force en intégrant ce qu'on appelle le sEMG haute définition (HD-sEMG), qui est une nouvelle technique d'enregistrement des signaux sEMG ayant démontré une meilleure estimation de la force en surmontant le problème de la position de l'électrode sur le muscle. Ce modèle de relation sEMG/force sera développé dans un contexte sans fatigue pour des contractions isométriques, isotoniques et anisotoniques du Biceps Brachii (BB) lors une flexion isométrique de l'articulation du coude à 90°. / The neuromuscular and musculoskeletal systems are complex System of Systems (SoS) that perfectly interact to provide motion. This interaction is illustrated by the muscular force, generated by muscle activation driven by the Central Nervous System (CNS) which pilots joint motion. The knowledge of the force level is highly important in biomechanical and clinical applications. However, the recording of the force produced by a unique muscle is impossible using noninvasive procedures. Therefore, it is necessary to develop a way to estimate it. The muscle activation also generates another electric phenomenon, measured at the skin using electrodes, namely the surface electromyogram (sEMG). ln the biomechanics literature, several models of the sEMG/force relationship are provided. They are principally used to command musculoskeletal models. However, these models suffer from several important limitations such lacks of physiological realism, personalization, and representability when using single sEMG channel input. ln this work, we propose to construct a model of the sEMG/force relationship for the Biceps Brachii (BB) based on the data analysis of a High Density sEMG (HD-sEMG) sensor network. For this purpose, we first have to prepare the data for the processing stage by denoising the sEMG signals and removing the parasite signals. Therefore, we propose a HD-sEMG denoising procedure based on Canonical Correlation Analysis (CCA) that removes two types of noise that degrade the sEMG signals and a source separation method that combines CCA and image segmentation in order to separate the electrical activities of the BB and the Brachialis (BR). Second, we have to extract the information from an 8 X 8 HD-sEMG electrode grid in order to form the input of the sEMG/force model Thusly, we investigated different parameters that describe muscle activation and can affect the relationship shape then we applied data fusion through an image segmentation algorithm. Finally, we proposed a new HDsEMG/force relationship, using simulated data from a realistic HD-sEMG generation model of the BB and a Twitch based model to estimate a specific force profile corresponding to a specific sEMG sensor network and muscle configuration. Then, we tested this new relationship in force estimation using both machine learning and analytical approaches. This study is motivated by the impossibility of obtaining the intrinsic force from one muscle in experimentation.

Network-on-chip (NoC) based multi-processor systems-on-chip (MPSoCs) are promising candidates for future multi-processor embedded platforms, which are expected to be composed of hundreds of heterogeneous processing elements (PEs) to potentially provide high performances. However, together with the performances, the systems complexity will increase, and new high level design techniques will be needed to efficiently model, simulate, debug and synthesize them. System-level design (SLD) is considered to be the next frontier in electronic design automation (EDA). It enables the description of embedded systems in terms of abstract functions and interconnected blocks. A promising complementary approach to SLD is the use of models of computation (MoCs) to formally describe the execution semantics of functions and blocks through a set of rules. However, also when this formalization is used, there is no clear way to synthesize system-level models into software (SW) and hardware (HW) towards a NoC-based MPSoC implementation, i.e., there is a lack of system design automation (SDA) techniques to rapidly synthesize and prototype system-level models onto heterogeneous NoC-based MPSoCs. In addition, many of the proposed solutions require large overhead in terms of SW components and memory requirements, resulting in complex and customized multi-processor platforms. In order to tackle the problem, a novel model-based SDA flow has been developed as part of the thesis. It starts from a system-level specification, where functions execute according to the synchronous MoC, and then it can rapidly prototype the system onto an FPGA configured as an heterogeneous NoC-based MPSoC. In the first part of the thesis the HeartBeat model is proposed as a model-based technique which fills the abstraction gap between the abstract system-level representation and its implementation on the multiprocessor prototype. Then details are provided to describe how this technique is automated to rapidly prototype the modeled system on a flexible platform, permitting to adjust the system specification until the designer is satisfied with the results. Finally, the proposed SDA technique is improved defining a methodology to automatically explore possible design alternatives for the modeled system to be implemented on a heterogeneous NoC-based MPSoC. The goal of the exploration is to find an implementation satisfying the designer's requirements, which can be integrated in the proposed SDA flow. Through the proposed SDA flow, the designer is relieved from implementation details and the design time of systems targeting heterogeneous NoC-based MPSoCs on FPGA is significantly reduced. In addition, it reduces possible design errors proposing a completely automated technique for fast prototyping. Compared to other SDA flows, the proposed technique targets a bare-metal solution, avoiding the use of an operating system (OS). This reduces the memory requirements on the FPGA platform comparing to related work targeting MPSoC on FPGA. At the same time, the performance (throughput) of the modeled applications can be increased when the number of processors of the target platform is increased. This is shown through a wide set of case studies implemented on FPGA. / <p>QC 20140609</p>

In this thesis, a conceptual framework and related methodological approaches for complex system design are developed and tested. The approaches are based on insights from the fields of Systems Engineering (SE) and System-of-Systems Engineering (SoSE), as well as Natural Resources Management (NRM). The focus of this thesis is on: 1) the development of the System-of-Systems Design Framework “FRESCO”, 2) the development of a methodological framework for participatory systems design, 3) the application of the framework in two case studies, and 4) the development of an evaluation scheme to qualitatively measure the effectiveness of the methodological framework. The overall objectives of this doctoral dissertation are to highlight synergies between SE and NRM and to develop a methodological framework for designing decision making processes in a human-nature-technology context. The complexity of coupled and complex adaptive systems (CAS) such as the Water-Energy-Food Nexus (WEF-Nexus) and sustainability strategies, influences the design of decision-making processes and strategy building. Integrated process design which is promoted by the developed frameworks can assist in such tasks on an urban, regional, and national level.

Thesis (M.S. in Systems Engineering)--Naval Postgraduate School, June 2010. / Thesis Advisor(s): Goshorn, Rachel ; Goshorn, Deborah. "June 2010." Description based on title screen as viewed on June 24, 2010. Author(s) subject terms: Anomaly Detection, Artificial Intelligence, Automation, Behavior Analysis, Distributed Artificial Intelligence, Intelligence-Surveillance-Reconnaissance, Maritime Domain Awareness, Maritime Force Protection, Multi-agent Systems, Network-centric Operations, Network-centric Systems Engineering, Network-centric Warfare, Smart Sensor Networks, Systems Engineering, Systems Integration, System of Systems. Includes bibliographical references (p. 209-212). Also available in print.