Στην εργασία αυτή αναλύεται θεωρητικά ένα σύστημα ηλεκτρονικής ψηφοφορίας και προσδιορίζονται πειραματικά οι κυριότεροι παράμετροι απόδοσής του. Αρχικά προτείνεται ένα πρωτόκολλο για ασφαλή επικοινωνία και στη συνέχεια το σύστημα μοντελοποιείται σαν ένα κλειστό δίκτυο αναμονής. Χρησιμοποιώντας τη τεχνική της Ανάλυσης Μέσης Τιμής μπορέσαμε να υπολογίσουμε μέσες τιμές για το χρόνο απόκρισης του συστήματος, τη διεκπεραιωτική του ικανότητα, το μήκος ουράς αναμονής των επιμέρους υποσυστημάτων καθώς και να προσδιορίσουμε τις ανάγκες σε τεχνολογικό εξοπλισμό. Στο θεωρητικό κομμάτι περιγράφονται και επεξηγούνται αναλυτικά όλες οι έννοιες που αφορούν τα δίκτυα αναμονής και παρουσιάζονται οι βασικοί μαθηματικοί νόμοι που διέπουν τη λειτουργία τους. Επίσης παρουσιάζεται αναλυτικά ο αλγόριθμός της μέσης τιμής καθώς και μια δημοφιλής προσέγγιση σε αυτόν. Στο πρακτικό κομμάτι έχει γίνει μια προγραμματιστική υλοποίηση του αλγόριθμου σε γλώσσα C. Με το πρόγραμμα αυτό μπορούμε εισάγοντας τις τιμές εισόδου για το μοντέλο μας να μελετήσουμε την απόδοσή του. / In this paper we analyze the performance of a large-scale e-voting system. To do so, we develop a performance model based on a closed queuing network and solve it using an Exact Mean Value Analysis technique. From the solution of our model we can estimate several performance parameters of the system ( such as throughput, response time, utilization and queue length) and define its main bottlenecks .In Chapter 1 we present the theory of queuing networks and their operational laws. In chapter 2, we present the algorithm of Mean Value Analysis and a very popular approximation of the algorithm. Finally we present the program we developed based on the MVA algorithm, in order to analyze the proposed e-voting system and its results.

Submitted by Leonardo Cavalcante (leo.ocavalcante@gmail.com) on 2018-05-02T17:17:30Z No. of bitstreams: 1 Arquivototal.pdf: 2997918 bytes, checksum: 9c78aa0c6413ddc4d5817a001a4fe338 (MD5) / Made available in DSpace on 2018-05-02T17:17:30Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 2997918 bytes, checksum: 9c78aa0c6413ddc4d5817a001a4fe338 (MD5) Previous issue date: 2017-08-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Analysis is one of the most fertile branches of mathematics, with its rigor brings foundation for new concepts developed. The objective of this work is to study of the n-variables real functions, providing the reader a rst contact with the matter. We have introduced important concepts and theorems, emphasizing the notions of topology. Moving on to studying some continuous and di erentiable applications, reaching the mean value inequality. / A análise é um dos ramos mais férteis da matemática, com seu rigor traz fundamento para novos conceitos desenvolvidos. O presente trabalho tem como objetivo principal, o estudo das funções de n-variáveis reais, fornecendo ao leitor um primeiro contato com a matéria. Introduzimos definições e teoremas importantes para o seu estudo, dando ênfase às noções de topologia. Passando a estudar algumas aplicações contínuas e diferenciáveis, chegando à desigualdade do valor médio. .

The emission legislations and the new On Board Diagnostics (OBD) legislations are becoming more strict and making the demands on control and fault detection higher. One way to control and diagnose the engine is to use a control/diagnose strategy based on physical models and therefore better models are necessary. Also, to be competitive and meet the markets demand of higher power, longer durability and better fuel economy, the models needs to be improved continuously. In this thesis a mean value model of the intake system that predicts the charge air temperature has been developed. Three models of different complexity for the intercooler heat-exchanger have been investigated and validated with various results. The suggested intercooler heat-exchanger model is implemented in the mean value model of the intake system and the whole model is validated on three different data sets. The model predicts the intake manifold temperature with a maximum absolute error of 10.12 K.

Mean Value Engine Modeling (MVEM) is used to make engine control development less expensive. With more and more cars equipped with turbocharged engines good turbo MVEM models are needed. A turbocharger consists of two major parts: turbine and compressor. Whereas the turbine is relatively durable, there exist phenomenons on the compressor that can destroy the turbocharger. One of these is surge. Several compressor models are developed in this thesis. Methods to determine the compressor model parameters are proposed and discussed both for the stable operating range as well as for the surge region of a compressor map. For the stationary region methods to automatically parameterize the compressor model are developed. For the unstable surge region methods to get good agreement for desired surge properties are discussed. The parameter sensitivity of the different surge properties is also discussed. A validation of the compressor model shows that it gives good agreement to data, both for the stationary region as well as the surge region. Different open loop and closed loop controllers as well as different performance variables are developed and discussed. A benchmark is developed, based on a measured vehicle acceleration, and the control approaches are compared using this benchmark. The best controller is found to be a open loop controller based on throttle and surge valve mass flow.

Engine control becomes increasingly important in newer cars. It is therefore interesting to investigate if a relatively new control method as Model Predictive Control (MPC) can be useful in engine control in the future. One of the advantages of MPC is that it can handle contraints explicitly. In this thesis basics on turbocharged engines and the underlying theory of MPC is presented. Based on a nonlinear mean value engine model, linearized at multiple operating points, we then implement both a linear and a nonlinearMPC strategy and highlight implementation issues. The implemented MPC controllers calculate optimal wastegate position in order to track a requested torque curve and still make sure that the constraints on turbocharger speed and minimum and maximum opening of the wastegate are fulfilled.

Multi-disciplinary ship synthesis models and multi-objective optimization techniques are increasingly being used in ship design. Multi-disciplinary models allow designers to break away from the traditional design spiral approach and focus on searching the design space for the best overall design instead of the best discipline-specific design. Complex design problems such as these often have high levels of uncertainty associated with them, and since most optimization algorithms tend to push solutions to constraint boundaries, the calculated "best" solution might be infeasible if there are minor uncertainties related to the model or problem definition. Consequently, there is a need to address uncertainty in optimization problems to produce effective and reliable results. This thesis focuses on adding a third objective, uncertainty, to the effectiveness and cost objectives already present in a multi-disciplinary ship synthesis model. Uncertainty is quantified using a "confidence of success" (CoS) calculation based on the mean value method. CoS is the probability that a design will satisfy all constraints and meet performance objectives. This work proves that the CoS concept can be applied to synthesis models to estimate uncertainty early in the design process. Multiple sources of uncertainty are realistically quantified and represented in the model in order to investigate their relative importance to the overall uncertainty. This work also presents methods to encourage a uniform distribution of points across the Pareto front. With a well defined front, designs can be selected and refined using a gradient based optimization algorithm to optimize a single objective while holding the others fixed. / Master of Science

Automated gear-shifts are critical procedures for the driveline as they are demanded to work as fast and accurate as possible. The torque control of a driveline is especially important for the driver’s feeling of driveability. In the case of gear-shifts and torque control in general, the boost pressure is key to achieve good response and thereby a fast gear-shift. An experimental study is carried out to investigate the phenomena of boost pressure drop during gear-shift and gather data for the modelling work. Results confirm the stated fact on the influence of boost pressure drop on gear-shift completion time and also indicate a clear linear dependence between initial boost pressure and the following pressure drop. A dynamic predictive model of the engine is developed with focus on implementation in a heavy duty truck, considering limitations computational complexity and calibration need between truck configurations. The resulting approach is based on a mean value modelling scheme that uses engine control system parameters and functions when possible. To be able to be predictive, a model for demanded torque and engine speed during the gear-shift is developed as reference inputs to the simulation. The simulation is based on a filling and emptying process throughout the engine dynamics, and yields final values of several engine variables such as boost pressure. The model is validated and later evaluated in comparison to measurements gathered in test vehicle experiments and in terms of robustness to input and model deviations. Computer simulations yield estimations of the boost pressure drop within acceptable limits. Consid- ering estimations used prior to this thesis the performance is good. Input deviations and modelling inaccuracies are found to inflict significant but not devastating deviations to the model output, possibly more over time with ageing of hardware taken into account. Final implementation in a heavy duty truck ecu is carried out with results indicating that the current implementation of the module is relatively computationally heavy. At the time of ending the thesis it is not possible to analyse its performance further, and it is suggested that the module is optimized in terms of computational efficiency.

With the intensively increasing of digital media new challenges has been created for authentication and protection of digital intellectual property. A hash function extracts certain features of a multimedia object e.g. an image and maps it to a fixed string of bits. A perceptual hash function unlike normal cryptographic hash is change tolerant for image processing techniques. Perceptual hash function also referred to as robust hash, like any other algorithm is prone to errors. These errors are false negative and false positive, of which false positive error is neglected compared to false negative errors. False positive occurs when an unknown object is identified as known. In this work a new method for raising false alarms in robust hash function is devised for evaluation purposes i.e. this algorithm modifies hash key of a target image to resemble a different image’s hash key without any significant loss of quality to the modified image. This algorithm is implemented in MATLAB using block mean value based hash function and successfully reduces hamming distance between target image and modified image with a good result and without significant loss to attacked imaged quality.

<p>Legislators steadily increase the demands on lowered emissions from heavy duty vehicles. To meet these demands it is necessary to integrate technologies like Exhaust Gas Recirculation (EGR) and Variable Geometry Turbochargers (VGT) together with advanced control systems. A control structure with PID controllers and selectors is proposed and investigated for coordinated control of EGR valve and VGT position in heavy duty diesel engines. Main control goals are to fulfill the legislated emission levels, to reduce the fuel consumption, and to fulfill safe operation of the turbocharger. These goals are achieved through regulation of normalized oxygen/fuel ratio and intake manifold EGR-fraction. These are chosen as main performance variables since they are strongly coupled to the emissions, compared to manifold pressure or air mass flow, which makes it easy to adjust set-points depending on e.g. measured emissions during an emission calibration process. In addition a mechanism for fuel efficient operation is incorporated in the structure, this is achieved by minimizing the pumping work. To design a successful control structure, a mean value model of a diesel engine is developed and validated. The intended applications of the model are system analysis, simulation, and development of model-based control systems. Model equations and tuning methods for the model parameters are described for each subsystem in the model. Static and dynamic validations of the entire model show mean relative errors that are less than 12%. Based on a system analysis of the model, a key characteristic behind the control structure is that oxygen/fuel ratio is controlled by the EGR-valve and EGR-fraction by the VGT-position, in order to handle a sign reversal in the system from VGT to oxygen/fuel ratio. For efficient calibration an automatic controller tuning method is developed. The controller objectives are captured in a cost function, that is evaluated utilizing a method choosing representative transients. The performance is evaluated on the European Transient Cycle. It is demonstrated how the weights in the cost function influence behavior, and that the tuning method is important in order to improve the control performance compared to if only a standard method is used. It is also demonstrated that the controller structure performs well regarding all control objectives. In combination with its efficient tuning, the controller structure thus fulfills all requirements for successful application.</p> / Report code: LiU-TEK-LIC-2006:52.

In the base station system of the GSM mobile network there are a large number of counters tracking the behaviour of the system. When the software of the system is updated, we wish to find out which of the counters that have changed their behaviour. This thesis work has shown that the counter data can be modelled as a stochastic time series with a daily profile and a noise term. The change detection can be done by estimating the daily profile and the variance of the noise term and perform statistical hypothesis tests of whether the mean value and/or the daily profile of the counter data before and after the software update can be considered equal. When the chosen counter data has been analysed, it seems to be reasonable in most cases to assume that the noise terms are approximately independent and normally distributed, which justies the hypothesis tests. When the change detection is tested on data where the software is unchanged and on data with known software updates, the results are as expected in most cases. Thus the method seems to be applicable under the conditions studied.