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41	Applying Artificial Neural Networks to Reduce the Adaptation Space in Self-Adaptive Systems : an exploratory work Buttar, Sarpreet Singh January 2019 (has links) Self-adaptive systems have limited time to adjust their configurations whenever their adaptation goals, i.e., quality requirements, are violated due to some runtime uncertainties. Within the available time, they need to analyze their adaptation space, i.e., a set of configurations, to find the best adaptation option, i.e., configuration, that can achieve their adaptation goals. Existing formal analysis approaches find the best adaptation option by analyzing the entire adaptation space. However, exhaustive analysis requires time and resources and is therefore only efficient when the adaptation space is small. The size of the adaptation space is often in hundreds or thousands, which makes formal analysis approaches inefficient in large-scale self-adaptive systems. In this thesis, we tackle this problem by presenting an online learning approach that enables formal analysis approaches to analyze large adaptation spaces efficiently. The approach integrates with the standard feedback loop and reduces the adaptation space to a subset of adaptation options that are relevant to the current runtime uncertainties. The subset is then analyzed by the formal analysis approaches, which allows them to complete the analysis faster and efficiently within the available time. We evaluate our approach on two different instances of an Internet of Things application. The evaluation shows that our approach dramatically reduces the adaptation space and analysis time without compromising the adaptation goals. Self-Adaptive Systems Self-Adaptation Architecture-Based Adaptation Autonomous Systems Cyber-Physical Systems CPS DeltaIoT IoT ActivFORMS MAPE-K Feedback Loop Runtime Uncertainties Adaptation Space Analysis Machine Learning Artificial Neural Network ANN Online Learning Deep Learning Online Supervised Learning Incremental Learning Classification Multi-Layer Perceptron MLP Computer Sciences Datavetenskap (datalogi) Control Engineering Reglerteknik Software Engineering Programvaruteknik
42	An investigation into the integration of qualitative and quantitative techniques for addressing systemic complexity in the context of organisational strategic decision-making McLucas, Alan Charles, Civil Engineering, Australian Defence Force Academy, UNSW January 2001 (has links) System dynamics modelling has been used for around 40 years to address complex, systemic, dynamic problems, those often described as wicked. But, system dynamics modelling is not an exact science and arguments about the most suitable techniques to use in which circumstances, continues. The nature of these wicked problems is investigated through a series of case studies where poor situational awareness among stakeholders was identified. This was found to be an underlying cause for management failure, suggesting need for better ways of recognising and managing wicked problem situations. Human cognition is considered both as a limitation and enabler to decision-making in wicked problem environments. Naturalistic and deliberate decision-making are reviewed. The thesis identifies the need for integration of qualitative and quantitative techniques. Case study results and a review of the literature led to identification of a set of principles of method to be applied in an integrated framework, the aim being to develop an improved way of addressing wicked problems. These principles were applied to a series of cases in an action research setting. However, organisational and political barriers were encountered. This limited the exploitation and investigation of cases to varying degrees. In response to a need identified in the literature review and the case studies, a tool is designed to facilitate analysis of multi-factorial, non-linear causality. This unique tool and its use to assist in problem conceptualisation, and as an aid to testing alternate strategies, are demonstrated. Further investigation is needed in relation to the veracity of combining causal influences using this tool and system dynamics, broadly. System dynamics modelling was found to have utility needed to support analysis of wicked problems. However, failure in a particular modelling project occurred when it was found necessary to rely on human judgement in estimating values to be input into the models. This was found to be problematic and unacceptably risky for sponsors of the modelling effort. Finally, this work has also identified that further study is required into: the use of human judgement in decision-making and the validity of system dynamics models that rely on the quantification of human judgement. accidents adaptive toolbox Black Hawk business process re-engineering bounded rationality BPR CATWOE causality causal loop diagram cognition complexity complex strategic problems cognitive mapping combat training centre concept mapping decision-making decision support systems defence preparedness double loop learning dynamic behaviour dynamic complexity feedback feedback loop feedback structure helicopter crash heuristic influence diagram IISD learning Katie Bender knowledge managerial cognition defence materiel naturalistic decision making project management qualitative modelling quantitative modelling recognition-primed decision making risk risk management root definition Royal Canberra Hospital situation awareness soft systems methodology strategy strategy development system dynamics front-end tool system dynamics modelling systems theory systems thinking systemic problems wicked problems
43	Enhanching the Human-Team Awareness of a Robot Wåhlin, Peter January 2012 (has links) The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot. / Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot. / <p>The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.</p> robotics Artificial Intelligence AI System Dynamics Wireless Body Area Network WBAN sensors Psychology physiology human behavior Human-Robot-Interaction HRI robot Human-Team awareness human-robot RapidMiner Vensim JaHMM hidden markov models HMM eclipse rcp ARFF recognizer classification cross-validation human behavior stress detection Galvanic Skin Response Heart Rate Skin Temperature Finger Temperature Electrocardiogram ECG GSR ST Pupil Diameter PD Patient monitoring GPS Data acquisition dataset data set MODERE Yerkes-Dodson SD model SD Confusion matrix spatial MOUT Java Agent robotic agent Machine Learning activity recognition team oriented robot Evaluation Decoding Learning Forward Algorithm Backward Algorithm Baum-Welch feedback loop Situation Awareness SA Shared Mental Models SMM
44	An investigation into the integration of qualitative and quantitative techniques for addressing systemic complexity in the context of organisational strategic decision-making McLucas, Alan Charles, Civil Engineering, Australian Defence Force Academy, UNSW January 2001 (has links) System dynamics modelling has been used for around 40 years to address complex, systemic, dynamic problems, those often described as wicked. But, system dynamics modelling is not an exact science and arguments about the most suitable techniques to use in which circumstances, continues. The nature of these wicked problems is investigated through a series of case studies where poor situational awareness among stakeholders was identified. This was found to be an underlying cause for management failure, suggesting need for better ways of recognising and managing wicked problem situations. Human cognition is considered both as a limitation and enabler to decision-making in wicked problem environments. Naturalistic and deliberate decision-making are reviewed. The thesis identifies the need for integration of qualitative and quantitative techniques. Case study results and a review of the literature led to identification of a set of principles of method to be applied in an integrated framework, the aim being to develop an improved way of addressing wicked problems. These principles were applied to a series of cases in an action research setting. However, organisational and political barriers were encountered. This limited the exploitation and investigation of cases to varying degrees. In response to a need identified in the literature review and the case studies, a tool is designed to facilitate analysis of multi-factorial, non-linear causality. This unique tool and its use to assist in problem conceptualisation, and as an aid to testing alternate strategies, are demonstrated. Further investigation is needed in relation to the veracity of combining causal influences using this tool and system dynamics, broadly. System dynamics modelling was found to have utility needed to support analysis of wicked problems. However, failure in a particular modelling project occurred when it was found necessary to rely on human judgement in estimating values to be input into the models. This was found to be problematic and unacceptably risky for sponsors of the modelling effort. Finally, this work has also identified that further study is required into: the use of human judgement in decision-making and the validity of system dynamics models that rely on the quantification of human judgement. accidents adaptive toolbox Black Hawk business process re-engineering bounded rationality BPR CATWOE causality causal loop diagram cognition complexity complex strategic problems cognitive mapping combat training centre concept mapping decision-making decision support systems defence preparedness double loop learning dynamic behaviour dynamic complexity feedback feedback loop feedback structure helicopter crash heuristic influence diagram IISD learning Katie Bender knowledge managerial cognition defence materiel naturalistic decision making project management qualitative modelling quantitative modelling recognition-primed decision making risk risk management root definition Royal Canberra Hospital situation awareness soft systems methodology strategy strategy development system dynamics front-end tool system dynamics modelling systems theory systems thinking systemic problems wicked problems
45	Cantilever properties and noise figures in high-resolution non-contact atomic force microscopy Lübbe, Jannis Ralph Ulrich 03 April 2013 (has links) Different methods for the determination of cantilever properties in non-contact atomic force microscopy (NC-AFM) are under investigation. A key aspect is the determination of the cantilever stiffness being essential for a quantitative NC-AFM data analysis including the extraction of the tip-surface interaction force and potential. Furthermore, a systematic analysis of the displacement noise in the cantilever oscillation detection is performed with a special focus on the thermally excited cantilever oscillation. The propagation from displacement noise to frequency shift noise is studied under consideration of the frequency response of the PLL demodulator. The effective Q-factor of cantilevers depends on the internal damping of the cantilever as well as external influences like the ambient pressure and the quality of the cantilever fixation. While the Q-factor has a strong dependence on the ambient pressure between vacuum and ambient pressure yielding a decrease by several orders of magnitude, the pressure dependence of the resonance frequency is smaller than 1% for the same pressure range. On the other hand, the resonance frequency highly depends on the mass of the tip at the end of the cantilever making its reliable prediction from known cantilever dimensions difficult. The cantilever stiffness is determined with a high-precision static measurement method and compared to dimensional and dynamic methods. Dimensional methods suffer from the uncertainty of the measured cantilever dimensions and require a precise knowledge its material properties. A dynamic method utilising the measurement of the thermally excited cantilever displacement noise to obtain cantilever properties allows to characterise unknown cantilevers but requires an elaborative measurement equipment for spectral displacement noise analysis. Having the noise propagation in the NC-AFM system fully characterised, a proposed method allows for spring constant determination from the frequency shift noise at the output of the PLL demodulator with equipment already being available in most NC-AFM setups. non-contact atomic force microscopy NC-AFM cantilever eigenfrequency resonance frequency spring constant stiffness Q-factor quality factor thermal excitation noise mounting loss tip mass ambient pressure feedback loop filter noncontact atomic force microscopy spectral analysis PLL FM-AFM 07.79.Lh - Atomic force microscopes 68.37.Ps - Atomic force microscopy (AFM) 46.70.De - Beams, plates and shells 62.20.Dc - Elasticity, elastic constants ddc:530

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