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A software component model is the cornerstone of any Component-based Software Development (CBSD) methodology. Such a model defines the modelling elements for constructing software systems. In software system modelling, it is necessary to capture the three elements of a system's behaviour: (i) control (ii) computation and (iii) data. Within a system, computations are performed according to the flow of control or the flow of data, depending on whether computations are control-driven or data-driven. Computations are function evaluations, assignments, etc., which transform data when invoked by control or data flow. Therefore a component model should be able to model control flow, data flow as well as computations. Current component models all model computations, but beside computations tend to model either control flow only or data flow only, but not both. In this thesis, we present a new component model which can model both control flow and data flow. It contains modelling elements that capture control flow and data flow explicitly. Furthermore, the modelling of control flow is separate from that of data flow; this enables the modelling of both control-driven and data-driven computations. The feasibility of the model is shown by means of an implementation of the model, in the form of a prototype tool. The usefulness of the model is then demonstrated for a specific domain, the embedded systems domain, as well as a generic domain. For the embedded systems domain, unlike current models, our model can be used to construct systems that are both control-driven and data-driven. In a generic domain, our model can be used to construct domain models, by constructing control flows and data flows which together define a domain model.

in English Abstract The thesis aims to fathom different aspects of the commodification of personal data. The topic is an issue of current interest. On one hand, due to the constant improvement of the technology of collecting and processing personal data, individuals are becoming very vulnerable. Techniques of influencing their thinking and decision-making based on their personal data have become so subtle and insidious that they often go unnoticed by the individuals. On the other hand, the development of the data economy can contribute to many goals that benefit society. This paper aims to answer two research questions. The first research question is how to guarantee the secure processing of personal data and to eliminate negative impacts on the subject and on society. The second research question concerns both ensuring adequate access of digital industry to personal data and empowering the data subject. Given the complexity of the issue and the confusion about the meaning and interpretation of basic concepts such as personal data and information, it is necessary to first briefly outline the nature and characteristics of personal data. The next two chapters analyse the legal means to achieve the objectives set out in the research questions. The final chapter provides a summary of recommendations on...

The main purpose of this project is to analyse used protocols in vehicles available under the OBD II specifications. In the project we will also focus on processing diagnostic data. We will design device for vehicle diagnostic. This device will be able to send processed data on external web server via Internet network. Obtained data will be saved on data server. Building of functional receiver will be the major part of master´s thesis.

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In food manufacturing, the quality control procedure is a critical activity that consists in organizing, measuring, tracking, and filing the conditions of the production process and the final product, with the goal of guaranteeing the designed quality standard. During the last 30 years, due to a mounting concern by both consumers and lawmakers, the definition of quality and the application of quality control improved drastically, and new methodologies have been developed to ensure better control of food production and to understand the effect of raw materials and the process condition on the final quality of the food product. This thesis discusses the approaches to quality control procedures in food manufacture, focusing on the relationship between the conditions of the process and the quality profile of the final product, testing in a real-case scenario of a complex production process advanced data analysis procedures. The statistical and analytical procedures proposed have been applied in a real case studio from Trentingrana cheese production, a dairy consortium in the northeast region of Italy producing a ripened semi-artisanal hard cheese under the Protected Denomination of Origin (PDO) of Grana Padano. The aim is developing tailored statistical procedures that infer the effect of the critical factors of production on quality properties of this PDO product considering its semi-artisanal production process and the presence of multiple confounding factors. The statistical analyses were applied to a dataset of measurements of physical, sensory, and chemical properties collected on cheese wheels sampled systematically to represent the variability of the production of the Trentingrana wheels over two years of production. In the first introductory chapter, after a review of the different definitions of quality, the most important quality parameters for a food product and the standard measurement techniques adopted in quality control are presented. Then, in the chapter 2, the standard procedures of data analysis are reviewed, as well as the new approaches derived from the context of the foodomic sciences and machine learning models for the analysis of quality control data in food manufacturing. Two implemented and tested practical statistical procedures in the context of the Trentingrana consortium are reported: the results are discussed according to the objectives of the quality control process, the type of data, and the organization of food production. In the first case, reported in chapter 3, Linear Mixed Model ANOVA Simultaneous Component Analysis (LMM-ASCA) was developed to investigate the effect of the dairy factory, the bimester of production, and the variability within a cheese wheel using colorimetric and textural measurements. In the second case, reported in chapter 4, a standard ASCA model with the addition of a blocking factor to include systematic error was developed to investigate the relationship between the dairy factory and bimester of production and the volatile organic compounds (VOCs) profile of Trentingrana cheese wheels. In addition, in chapter 5, an approach to relate physical measurements on Trentingrana samples with sensory evaluations of texture by a trained panel is presented. The objective of this procedure is to incorporate the quality control procedure information from different quality parameters. The development of the Partial Least Squares (PLS) predictive model, its validation, and the evaluation of its performances are discussed. In the last section (chapter 6), the development of an image analysis procedure to measure the visual quality of the rind thickness of cheese wheels is reported, comparing the performances of two different algorithms. The data analysis tools proposed in this thesis have been proved to be useful for exploring, inferring, and plotting the process quality properties and suitable for analyzing complex and unbalanced experimental designs. Furthermore, the data analysis procedures proposed improve quality control activity both at the process level and at the product level, increasing the information that is possible to extract from the measurement collected in a context where standard statistical approaches cannot infer significant information.

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The Control System Analysis and Design Package (CSADP) is a computer-aided design package for applying classical control system analysis and design tools to experimental frequency response measurements. CSADP allows the user to analyze and manipulate measured frequency response data, design control systems using these measurements, and determine the operational amplifier hardware required to implement the design. To perform these tasks, CSADP provides tools that allow the user to define problems using both frequency response data files and transfer function descriptions; generate Bode, Nyquist, and root-locus plots; and curve-fit frequency response data. The curve-fitting program uses novel data-scanning techniques for conditioning the data, and for predicting the model form and starting parameters. CSADP also allows the user to design compensators interactively using Bode and root-locus methods, and aids the user in selecting the required resistor and capacitor values needed for implementing the compensator using op-amp circuits. In addition, CSADP provides coefficients required to implement the compensator using selected digital algorithms. CSADP was used in the design of a velocity loop compensator for a precision diamond turning machine. Open loop frequency response data gathered from the machine was used as the basis for compensator design using Bode methods. The required compensator coefficients generated by the program were programmed into the servo for testing. Results showed that the closed loop response predicted by the program accurately matched the measured response. Estimates of natural frequencies provided by the model prediction program were within 5 percent of the actual values. Errors in estimates of the damping ratios for very lightly damped complex poles ranged from only 10 percent to 30 percent. CSADP is written in FORTRAN 77 and provides Tektronix (TEK) 4010/4014 compatible graphics output. / Master of Science

The usage of information technology (IT) systems has become an integral part of assembly manufacturing. Supervisory control and data acquisition (SCADA) systems are widely used in order to control production cycles and monitor equipment such as conveyor belts. Other common IT systems are related to logistics, data analysis, or organizing of incoming and outgoing orders. In this thesis we create a model for the IT systems at the fuel pump and fuel injector manufacturer Scania XPI. One model is developed for the current state of the IT systems at Scania XPI, and one model is developed detailing the future state. The current state model consists of charts showing where in the production process that data is transmitted between which IT systems. This thesis utilizes the current state model in order to suggest improvements to the IT systems. These improvements are detailed in the model for the future state of IT systems at Scania XPI. Overall equipment efficiency (OEE) is a measurement of the performance of an industrial operation based on the percentage of up time running at full capacity compared to the available run time. Measurement of OEE requires that only downtimeduetointernal circumstances within the operation is taken into account, and that any potential quality deviations due to the operation are accounted for. Taking into account the variability of manufacturing processes, this thesis proposes solutions to issues in data processing required to measure the efficiency of operations in assembly manufacturing, such as identifying if process breakdowns are caused by external factors. The proposed solution is a system called "Process data analysis system" (PDAS), which uses the recorded machine statuses throughout operation in order to calculate process downtime and OEE. PDAS was implemented using the incremental waterfall model as a software development methodology. PDAS was evaluated by conducting four groups of experiments and a comparison to the PUS (processuppföljnings system) at Scania XPI. Automatically classifying downtime events as planned or unplanned allows PDAS to give an accurate view on the efficiency of the assembly production. The software can be used at Scania XPI and it’s functionality has been verified on assembly production running in ordinary conditions. We show that software can be developed to process industrial data in order to measure assembly line efficiency. Eventually, design and implementation of a downtime management system for assembly production is achieved as a final product of this thesis. / Användningen av informationsteknik (IT) system har blivit en viktig del av monteringstillverknings industrin. Supervisory control and data acquisition (SCADA) system är ofta implementerade i syfte att kontrollera produktionens takt och för att övervaka eller styra produktionens utrustning. Andra vanliga IT-system är relaterade till logistik, data analys, eller hantering av ingående och utgående beställningar. I detta examensarbete skapar vi en modell för IT-systemen på dieselpump och dieselinjektor tillverkaren Scania XPI. Denna modell visar både hur IT-systemen fungerar idag och hur de kan förbättras. Current state modellen består av diagram som visar var i produktionsprocessen som data skickas mellan IT-systemen. Vi använder oss av current state modellen i syfte att föreslå förbättringar till IT-systemen. Dessa förbättringar beskrivs i en modell för future stateäv IT-systemen hos Scania XPI. Overall equipment efficiency (OEE) är ett mått på prestandan på effektiviteten av industriell verksamhet baserat på procentandelen av drifttiden utan kvalitets avvikelser utan stopp jämfört med den totala drifttiden. Mätning av OEE kräver att driftstopp på grund av externa omständigheter ej tillräknas stopp tiden, och att kvalitets avvikelser kan mätas. Detta examensarbete föreslår lösningar på problem inom databehandling som krävs för att mäta produktionens effektivitet vid monteringstillverkning, exempelvis att identifiera om driftstopp som orsakas av externa omständigheter. Lösningen som presenteras är utveckling av Process Data Analysis System"(PDAS), som använder sig av automatiskt rapporterad maskinstatusdata för att beräkna stopp tid och OEE. PDAS implementerades med "incremental waterfall modelsom metodologi för mjukvaruutveckling. PDAS utvärderades genom att genomföra fyra grupper av experiment och med hjälp av en jämförelse med PUS (processuppföljnings system) hos Scania XPI. Genom att automatiskt klassificera planerad och oplanerad stopp tid ger PDAS en mer ackurat bild av effektiviteten för monterings produktionen. Mjukvaran kan användas av Scania XPI och funktionen av PDAS har verifierats för monteringstillverkningen under vanliga produktionsomständigheter. Vi visar att mjukvaran kan användas för att bearbeta industriell data i syfte att mäta effektiviteten av monterings tillverkningen. Slutligen uppnås design och implementation av ett system för stopptids hantering för monterings produktion som en produkt av denna uppsats.

Power system protection is important for service reliability and quality assurance. Various faults may occur due to natural and artificial calamity. To reduce the outage duration and promptly restore power services, fault section estimate has to be done effectively and accurately with fault alarms. Dispatchers study the changed statuses of protection devices from the Supervisory Control and Data Acquisition (SCADA) system to identify the fault. Single and multiple faults could coexist with the failed operation of relays and circuit breakers, or with the erroneous data communication. It needs a long time to process a large number of alarms under various conditions involving multiple faults and many uncertainties. To cope with the problem, an effective tool is helpful for the fault section estimation and alarm processing. Besides, power transformer plays a major role in a power system. For a better service quality, it is important to be routinely examined for detecting incipient faults inside transformers. Preventive techniques for early detection can find out the incipient faults and avoid outages. Power quality is another issue to considerable attentions from utilities and customers due to the popular uses of many sensitive electronic equipment. Harmonics, voltage swell, voltage sag, and, power interruption could downgrade the service quality. To ensure the power quality, detecting harmonic and voltage disturbances becomes important. A detection method with classification capability will be helpful for detecting disturbances. This dissertation developed various algorithm for detection including fault section detection, alarm processing, transformer fault diagnosis, and power quality detection. For a well-dispatched power system, the adaptive detection idea will be used, and the existing SCADA/EMS will be integrated without extra devices.