The enterprise systems are built with a monolithic way of software architecture which may not be the very suitable and realistic solutions, due to the quantity and diversity of Internet of Things (IOT) devices connected to the internet. The large code is based as a single deployable unit; making it cumbersome and difficult to change, test, and deploy – typically in the monthly deployment cycles. Which could potentially be a large impact and high-risk for updates and deployment build up between releases.  The thesis aims to exploit Microservices Architecture in context of the Internet of Things. Because of scalability and rapid deployment, Microservices Architecture (MSA) naturally fits for M2M and IOT developments. Therefore, it has become increasingly popular and highly suited as a design choice in the context of developing IOT applications. We have proposed various ontologies for conceptual architecture designs. Our conceptual model encompasses all the essential elements and entities that constitute IOT; describing various characteristics of microservices and consideration to be used as a basis for developing a Reference Architecture model. The reference architecture is effectively exploiting Microservices Architectural Style for a diverse set of things composition like sensor devices, connectivity and transportation protocols for IP enabled IOT smart objects.  The thesis will contribute to the conceptual space of more successful reference architectures. The goal is to provide features and deployment information with instantiation guidelines to derive the software architecture instances in a given IOT application domain. Thus, it promises to become a valuable framework in the derivation of the Microservices IOT architectures.

Project teams that deliver high risk, complex projects in the civil construction industry need tools to enable successful delivery. Construction Manager/General Contractor (CM/GC) is an innovative alternate delivery method, providing one such a tool. CM/GC furnishes public agencies with an attractive option for delivering projects in a less adversarial and more constructive manner by involving the contractor during design. The sophisticated public owner does not have to relinquish control of the details of the design in order to accelerate the schedule or see the benefits of real-time cost estimating data. There are also significant cost and schedule benefits with not degradation in quality. However, because CM/GC is relatively unknown to the civil construction industry much remains to be investigated about how CM/GC processes effect successful project delivery. This research investigated how CM/GC processes affect the three critical elements of construction process risks (including quality, schedule, cost and collaboration), project specific risks, and innovation. By identifying the processes that benefit these elements, successes can be repeated and increased. Additionally, an understanding of the differences in the perception of CM/GC processes, given by contractors, owners, and design engineers, provided perspective into improving the process. Analyzing data on current CM/GC projects and programs, as well as the compiled experience of field-experienced project teams, provided the information the industry needs to pursue implementation. Identified advantages of the process can be tied to strategies for successful delivery. Identified disadvantages expose barriers to implementation to be overcome by the project team. Project teams state that while the process does have disadvantages, many are perceptional and not fatal flaws to the method. Findings of this research link CM/GC processes to robust risk management results and the opportunity for successful innovation.

The first billion years from the beginning of the Universe is the focus of multiple astronomical facilities in the upcoming decade. This unique era is marked by the formation of the first stars and galaxies, which release ionising radiation into the intergalactic medium(IGM). As a result, these sources initiate a period during which the cold and dense IGM, primarily consisting of neutral hydrogen (HI ), is heated and ionised. We refer to this era as the Epoch of Reionisation (EoR). How the EoR transpired hence depends on the properties of these ionising sources, and this forms a vital piece to the puzzle of understanding the early Universe. This licentiate thesis aims to educate the reader on the power spectrum (PS) statistic of the 21-cm signal from HI during the EoR. The PS is a prospective observable by radio interferometers, such as the Low-Frequency Array (LOFAR) and the future Square Kilometre Array (SKA). It is an essential stepping stone in comprehending the dominant physical processes affecting the IGM at a given length scale during the EoR. In Paper I, we analyse the decomposition of the 21-cm PS from Lidz et al. (2007) (eq. 2)and study the evolution of its terms. We conduct our investigation for a set of C 2 -Ray and 21cmFAST simulations with volumes of (714 cMpc)3, concentrating on large-scales (k < 0.3 Mpc−1 ) as the signal-to-noise ratio of observing these scales will be high. We find that the 21-cm PS tracks the PS of neutral hydrogen fluctuations, which itself past a certain scale tracks the matter PS after a global ionisation fraction of x̄HII∼ 0.1. Hence, the 21-cm PS possesses a two-regime form for which the large-scale PS is a biased version of the cosmological density field and the small-scale PS depends on the astrophysics of the EoR. We construct a bias parameter to explore whether the 21-cm PS can be used as a probe of cosmology on large k-scales. We discover a transition feature for both simulations, following the ktrans ≈ 2/λMFP empirical formula. The transition scale between the scale-independent and scale-dependent bias regimes is directly related to the value of the mean free path of ionising photons (λMFP ).

No description available.

Terminal models have been used for various power electronic applications. In this work a two- and three-terminal black box model is proposed for electro-magnetic interference (EMI) characterization. The modeling procedure starts with a time-variant system at a particular operating condition, which can be a converter, set of converters, sub-system or collection of components. A unique, linear equivalent circuit is created for applications in the frequency domain. Impedances and current / voltage sources define the noise throughout the entire EMI frequency spectrum. All parameters needed to create the model are clearly defined to ensure convergence and maximize accuracy. The model is then used to predict the attenuation caused by a filter with increased accuracy over small signal insertion gain measurements performed with network analyzers. Knowledge of EMI filters interactions with the converter allows for advanced techniques and design constraints to optimize the filter for size, weight, and cost. Additionally, the model is also demonstrated when the operating point of the system does not remain constant, as with AC power systems. Modeling of a varying operating point requires information of all the operating conditions for a complete and accurate model. However, the data collection and processing quickly become unmanageable due to the large amounts of data needed. Therefore, simplification techniques are used to reduce the complexity of the model while maintaining accuracy throughout the frequency spectrum. The modeling approach is verified for linear and power electronic networks including: a dc-dc boost converter, phase-leg module, and a simulated dc-ac inverter. The accuracy of the model is confirmed up to 100 MHz in simulation and at least 50 MHz for experimental validation. / Ph. D.

This dissertation is to focus on the development of modeling and simulation methodology to predict conductive electromagnetic interference (EMI) for high power converters. Conventionally, the EMI prediction relies on the Fast Fourier Transformation (FFT) method with the time-domain simulation result that requires long hours of simulation and a large amount of data. The proposed approach is to use the frequency-domain analysis technique that computes the EMI spectrum directly by decomposing noise sources and their propagation paths. This method not only largely reduces the computational effort, but also provides the insightful information about the critical components of the EMI generation and distribution. The study was first applied to a dc/dc chopper circuit by deriving the high frequency equivalent circuit model for differential mode (DM) and common mode (CM) EMIs. The noise source was modeled as the trapezoidal current and voltage pulses. The noise cut-off frequency was identified as a function of the rise time and fall time of the trapezoidal waves. The noise propagation path was modeled as lumped parasitic inductors and capacitors, and additional noise cut-off frequency was identified as the function of parasitic components. . Using the noise source and path models, the proposed method effectively predicts the EMI performance, and the results were verified with the hardware experiments. With the well-proven EMI prediction methodology with a dc/dc chopper, the method was then extended to the prediction of DM and CM EMIs of three-phase inverters under complex pulse width modulation (PWM) patterns. The inverter noise source requires the double Fourier integral technique because its switching cycle and the fundamental cycle are in two different time scales. The noise path requires parasitic parameter extraction through finite element analysis for complex-structured power bus bar and printed circuit layout. After inverter noise source and path are identified, the effects of different modulation schemes on EMI spectrum are evaluated through the proposed frequency-domain analysis technique and verified by hardware experiment. The results, again, demonstrate that the proposed frequency-domain analysis technique is valid and is considered a promising approach to effectively predicting the EMI spectrum up to tens of MHz range. / Ph. D.

With GaN and SiC switching devices becoming more commercially available, higher switching frequency is being applied to achieve higher efficiency and power density in power converters. However, electro-magnetic interference (EMI) becomes a more severe problem as a result. In this thesis, the switching frequency effect on conducted EMI noise is assessed. As EMI noise increases, the EMI filter plays a more important role in a power converter. As a result, an effective EMI modeling technique of the power converter system is required in order to find an optimized size and effective EMI filter. The frequency-domain model is verified to be an efficient and easy model to explore the EMI noise generation and propagation in the system. Of the various models, the unterminated behavioral model can simultaneously predict CM input and output noise of an inverter, and the prediction falls in line with the measurement around 10 MHz or higher. The DM terminated behavioral model can predict the DM input or output noise of the motor drive higher than 20 MHz. These two models are easy to extract and have high prediction capabilities; this is verified on a 10 kHz-switching-frequency Si motor drive. It is worthwhile to explore the prediction capability of the two models when they are applied to a SiC-based power inverter with switching frequency ranges from 20 kHz to 70 kHz. In this thesis, the CM unterminated behavioral model is first applied to the SiC power inverter, and results show that the model prediction capability is limited by the noise floor of the oscilloscope measurement. The proposed segmented-frequency-range measurement is developed and verified to be a good solution to the noise floor. With the improved impedance fixtures, the prediction from CM model matches the measurement to 30 MHz. To predict the DM input and output noise of the SiC inverter, the DM terminated behavioral model can be used under the condition that the CM and DM noise are decoupled. With the system noise analysis, the DM output side is verified to be independent of the CM noise and input side. The DM terminated behavioral model is extracted at the inverter output and predicts the DM output noise up to 30 MHz after solving the noise floor and DM choke saturation problem. At the DM input side, the CM and DM are seen to be coupled with each other. It is found experimentally that the mixture of the CM and DM noise results from the asymmetric impedance of the system. The mixed mode terminated behavioral model is proposed to predict the DM noise when a mixed CM effect exists. The model can capture the DM noise up to to 30 MHz when the impedance between the inverter to CM ground is not balanced. The issue often happens in extraction of the model impedance and is solved by the curving-fitting optimization described in the thesis. This thesis ends with a summary of contributions, limitations, and some future research directions. / Master of Science

Purpose: This study aims to investigate the role of Control mechanisms in sustaining Change initiatives. Method: Following qualitative research with inductive approach, the data was collected through semi-structured interviews from 10 change practitioners of multinationals in various fields, including Information Technology, Project Management, Banking, Logistics, Manufacturing and Telecommunication. Grounded theory was used to analyse the empirical findings. Findings: The results show that control mechanism play a crucial role right from guiding and governing the entire process of change. On the other hand, findings reveal a wide range of control tools in context to change management. Also, change readiness is crucial step, it is critical to be well prepared before a change project is initiated. Moreover, new concepts such as design thinking, CAPA (corrective action preventive action) and PDSA (Plan, do, study, act) emerged as control tool throughout the process of change improving efficacy, mistake proofing and driving continuous improvement. Finally, control mechanisms can make contribute to sustenance of CM initiatives through its potential of continuous monitoring and indicating Implications: Theoretically, the study challenges established conceptions of CM by emphasizing the role of preparedness and adaptation. It proposes dynamic frameworks and proactive control methods to facilitate organizational transformation. Practically, it emphasizes the importance of extensive training, logical methods, and a variety of tools for effectively navigating change process.

No / PURPOSE. To determine the effects of blurring vision on whole-body center-of-mass (CM) dynamics and foot-clearance parameters in elderly individuals performing a single step up to a new level. METHODS. Twelve healthy subjects (mean age, 72.3 ±4.17 years) performed a single step up to a new level (heights of 73 and 146 mm). Trials were undertaken with vision optimally corrected and with vision diffusively blurred by light-scattering lenses (cataract simulation). CM and foot-clearance parameter data were assessed by analyzing data collected by a five-camera, three-dimensional (3-D) motion analysis system. RESULTS. When vision was blurred, subjects took 11% longer to execute the stepping task (P < 0.05), mediolateral displacement of the point of application of the ground reaction force vector (i.e., weighted average of all pressures over the area in contact with the ground; the so called center of pressure, CP) decreased from 37.6% of stance width to 28.3% (P < 0.01), maximum distance between the mediolateral position of the CM and CP decreased by 9.8 mm (P < 0.01), and toe clearance (distance between tip of shoe and edge of step) increased in both the horizontal (28%) and vertical (19%) direction (P < 0.05). CONCLUSIONS. These findings suggest that when vision was blurred, subjects used a twofold safety-driven adaptation: First, to increase dynamic stability they ensured that the horizontal position of their CM was kept close to the center of the base of support and second, they increased horizontal and vertical toe clearance while swinging their lead limb forward to reduce the risk of tripping.

Im Rahmen der Item-Response-Theorie evaluiert die kumulative Dissertationsschrift verschiedene Methoden und Modelle zur Identifikation von Kontexteffekten in Large-Scale Assessments. Solche Effekte können etwa in quantitativen empirischen Schulleistungsstudien auftreten und zu verzerrten Item- und Personenparametern führen. Um in Einzelfällen abschätzen zu können, ob Kontexteffekte auftreten und dadurch die Gefahr verzerrter Parameter gegeben ist (und falls ja, in welcher Weise), müssen IRT-Modelle entwickelt werden, die zusätzlich zu Item- und Personeneffekten Kontexteffekte parametrisieren. Solch eine Parametrisierung ist im Rahmen Generalisierter Allgemeiner Linearer Modelle möglich. In der Dissertation werden Positionseffekte als ein Beispiel für Kontexteffekte untersucht, und es werden die statistischen Eigenschaften dieses Messmodells im Rahmen einer Simulationsstudie evaluiert. Hier zeigt sich vor allem die Bedeutung des Testdesigns: Um unverfälschte Parameter zu gewinnen, ist nicht nur ein adäquates Messmodell, sondern ebenso ein adäquates, also ausbalanciertes Testdesign notwendig. Der dritte Beitrag der Dissertation befasst sich mit dem Problem fehlender Werte auf Hintergrundvariablen in Large-Scale Assessments. Als Kontexteffekt wird in diesem Beispiel derjenige Effekt verstanden, der die Wahrscheinlichkeit eines fehlenden Wertes auf einer bestimmten Variablen systematisch beeinflusst. Dabei wurde das Prinzip der multiplen Imputation auf das Problem fehlender Werte auf Hintergrundvariablen übertragen. Anders als bisher praktizierte Ansätze (Dummy-Codierung fehlender Werte) konnten so in einer Simulationsstudie für fast alle Simulationsbedingungen unverfälschte Parameter auf der Personenseite gefunden werden. / The present doctoral thesis evaluates various methods and models of the item response theory to parametrize context effects in large-scale assessments. Such effects may occur in quantitative educational assessments and may cause biased item and person parameter estimates. To decide whether context effects occur in individual cases and lead to biased parameters, specific IRT models have to be developed which parametrize context effects additionally to item and person effects. The present doctoral thesis consists of three single contributions. In the first contribution, a model for the estimation of context effects in an IRT framework is introduced. Item position effects are examined as an example of context effects in the framework of generalized linear mixed models. Using simulation studies, the statistical properties of the model are investigated, which emphasizes the relevance of an appropriate test design. A balanced incomplete test design is necessary not only to obtain valid item parameters in the Rasch model, but to guarantee for unbiased estimation of position effects in more complex IRT models. The third contribution deals with the problem of missing background data in large-scale assessments. The effect which predicts the probability of a missing value on a certain variable, is considered as a context effect. Statistical methods of multiple imputation were brought up to the problem of missing background data in large-scale assessments. In contrast to other approaches used so far in practice (dummy coding of missing values) unbiased population and subpopulation estimates were received in a simulation study for most conditions.