From an energy eciency viewpoint of improving the cellular access networks, the power consumption of the whole system needs to be tracked. In this project, a theoretical model is studied which jointly encompasses sleep control strategy and Base Station (BS) cooperation polices, our goal is to obtain a Pareto Op- timal tradeo between energy consumption and average delay time. Based on the trac load variation, the sleep control strategy is proposed by adjusting the BS working mode. This project focuses on the multi-cell network which is more close to the real world. In multi-cell scenario, except for the design of the sleep control, the issues of BS cooperation and the inter-cell interference also need to be covered. Furthermore, based on the multi-cell network, three types of energy saving strategies are considered: In case I, users only can be served by their own Base stations (BSs) which go to sleep mode when there is no ac- tive user and will not wake up until N users need to be served. This strategy leads to a good energy performance but the long delay. To reduce the average delay, therefore, in case II, we introduced the user association policies that the network handover the user to his adjacent BSs when his own BS is in the sleep mode. Furthermore, the relay-assisted network was studied in the case III. Fi- nally, Based on theoretical and simulation results, we compared these tree cases under the given trac conditions from the perspective of achieving the optimal average energy-delay tradeo . And also we found out that sacricing network throughput can yield the energy saving if we carefully design the network. / Ur energie ektivitetssynpunkt att frbttra de cellulra accessnten, mste e ekt- frbrukningen fr hela systemet som ska spras. I detta projekt r en teoretisk modell studerat vilka tillsammans omfattar smnkontrollstrategi och basstatio- nen (BS) samarbetspolitiken, r vrt ml att f en Pareto Optimal avvgning mellan energifrbrukning och genomsnittlig frdrjning. Baserat p trakbelastning varia- tionen r smnkontrollstrategi fresls genom att justera BS arbetslge. Detta projekt fokuserar p multicellntverk som r mer nra den verkliga vrlden. I ercells sce- nario, med undantag fr utformningen av smnkontroll, frgor om BS samarbete och intercell interferens mste ocks tckas. Dessutom bygger p ercellsntverk, r tre typer av sparenergistrategier beaktas: I fall jag, anvndarna endast kan betjnas av egna Basstationer (BSS) som gr till vilolge nr det inte nns ngon aktiv an- vndare och kommer inte vaknar tills N anvndare behver delges. Denna strategi leder till en god energiprestanda men den lnga frseningen. Fr att minska den genomsnittliga frseningen drfr ifall II infrde vi de anvndar freningens policy att ntverket lmnandet anvndaren att hans intilliggande BS nr hans egen BS r i vilolge. Vidare relet assisterade nt studerades i fallet III. Slutligen Baserat p teoretiska och simuleringsresultat, jmfrde vi dessa trd ml enligt de givna trak- frhllandena ur perspektivet att uppn den optimala genomsnittliga energifrdrjn- ings avvgning. Och ven vi ck reda p att o ra ntverksgenomstrmning kan ge energibesparingar om vi noggrant utforma ntverket.

A collisionless model for fast-ion transport in a tokamak reactor is derived from first principles, and a new orbitfollowing code is developed to simulate this model. Results from the model applied on two scenarios of DT fusion plasmas, one from ITER and one from JET, are compared, and the prompt losses as well as the effects of orbit shapes are quantified; it is shown that both the prompt losses and the orbit effect on confined particles are very small in both reactors. Although some problems are still present, the method presented shows potential for further investigating orbit effects. / En modell för kollisionsfri transport av högenergetiska joner i tokamaks har tagits fram, och en ny banlösande kod har utvecklads för att simulera denna model. Resultat från modellen applicerad på två scenarion med DTplasma, ett från ITER och ett från JET, jämförs, och omedelbara förluster samt effekter av inneslutna banors form kvantifieras; både ban- och omedelbara förluster visas vara mycket små i båda reaktorerna. Även om mindre problem återstår att lösa, har metodent pontential för att vidare undersöka baneffekter i fusionsplasman.

The recent studies on sensor networks are causing a huge development of wire-less communications. These studies are motivated by the wide-range promisingapplications. However, this development faces multiple challenges. The privacyissue is one of these challenges. The study on the privacy-constrained sensornetworks is presented in previous works where the eavesdropping privacy risk istaken into account in the physical-layer distributed detection design. Nonethe-less, a rigorous study on the receiver operating characteristics (ROC) is missing.In this thesis, we will focus on a parallel distributed detection networkwith one fusion node that makes the final decision. We show how the fusionROC changes against different settings when considering the privacy constraints.First, a Bayesian detection scenario is considered. Second, some parameters aremodified for the purpose of studying the affect on the ROC. Finally, an otherscenario is analyzed where the eavesdropping is modeled a Neyman-Pearsondetection attach while the settings of the Bayesian distributed with detectionsystem is kept. / De senaste studierna om sensorn ̈atverk ̈ar f ̈oranledd av en snabb utveckling inomtr ̊adl ̈os kommunikation. Studierna motiveras av de lovande till ̈ampningar somfinns inom ett flertal omr ̊aden. Utvecklingen av sensorn ̈atverk st ̊ar dock inf ̈orett antal utmaningar. Den personliga integriteten ̈ar en utav dessa utmaningar.Studien om sekretessbegr ̈ansade sensorn ̈atverk finns presenterad i tidigare verkd ̈ar integritetsrisken vid avlyssnings tas i beaktning inom det f ̈ordelade fysiskalagrets detektionsdesign. Dock saknas en rigor ̈os under ̈okning p ̊a mottagarensdriftegenskaper (ROC).Denna avhandling kommer att fokusera p ̊a ett parallellt distribuerat detek-tionsn ̈atverk med en fusions nod som fattar det slutgiltiga beslutet. Vi visar hurfusions ROC ̈andras med olika inst ̈allningar n ̈ar man tar h ̈ansyn till begr ̈ansadsekretess. F ̈orst studeras ett Bayesianskt detekteringsscenario. Sedan kommervissa parametrar modifieras i syfte att studera dess inverkan p ̊a ROC. Slutligenanalyseras det andra scenariot d ̈ar avlyssningen modelleras som en Neyman-Pearson detektion medan inst ̈allningarna f ̈or det Bayesiansk distribuerade de-tekteringssystemet fortfarande h ̊aller.

Speech signal processing is an old research topic within the communication theory community. The continously increasing telephony market brought special attention to the discipline during the 80’s and 90’s, specially in speech coding and speech enhancement, where the most significant contributions were made. More recently, due to the appearance of novel signal processing techniques, the standard methods are being questioned. Sparse representation of signals and compessed sensing made significant contributions to the discipline, through a better representation of signals and more efficient processing techniques. In this thesis, standard speech modeling techniques are revisited. Firstly, a representation of the speech signal through the line spectral frequencies (LSF) is presented, with a extended stability analysis. Moreover, a new Bayesian framework to time-varying linear prediction (TVLP) is shown, with the analysis of different methods. Finally, a theoretical basis for speech denoising is presented and analyzed. At the end of the thesis, the reader will have a broader view of the speech signal processing discipline with new insights that can improve the standard methodology.

Visual analysis tasks, like detection, recognition and tracking, are com- putationally intensive, and it is therefore challenging to perform such tasks in visual sensor networks, where nodes may be equipped with low power CPUs. A promising solution is to augment the sensor network with pro- cessing nodes, and to distribute the processing tasks among the process- ing nodes of the visual sensor network. The objective of this project is to enable a visual sensor network testbed to operate with multiple cam- era sensors, and to implement an algorithm that computes the allocation of the visual feature tasks to the processing nodes. In the implemented system, the processing nodes can receive and process data from differ- ent camera sensors simultaneously. The acquired images are divided into sub-images, the sizes of the sub-images are computed through solving a linear programming problem. The implemented algorithm performs local optimization in each camera sensor without data exchange with the other cameras in order to minimize the communication overhead and the data computational load of the camera sensors. The implementation work is performed on a testbed that consists of BeagleBone Black computers with IEEE 802.15.4 or IEEE 802.11 USB modules, and the existing code base is written in C++. The implementation is used to assess the performance of the distributed algorithm in terms of completion time. The results show a good performance providing lower average completion time.

In this master thesis project, we study the problem in Visual Sensor Networks in which only limited bandwidth is provided. The task is to search for ways to decrease the transmitting data on the camera side, and distribute the data to dif- ferent nodes. To do so, we extract the interest points on the camera side by using BRISK in- terest point detector, and we distribute the detected interest points into di erent number of processing node by implementing proposed clustering methods, namely, Number Based Clustering, K-Means Clustering and DBSCAN Clustering. Our results show it is useful to extract interest points on the camera side, which can reduce almost three quarters of data in the network. A step further, by imple- menting the clustering algorithms, we obtained the gain in overhead ratio, interest point imbalance and pixel processing load imbalance, respectively. Specically, the results show that none of the proposed clustering methods is better than oth- ers. Number Based Clustering can balance the processing load between di erent processing nodes perfectly, but performs bad in saving the bandwidth resources. K-Means Clustering performs middle in the evaluation while DBSCAN is great in saving the bandwidth resources but leads to a bad processing balance performance among the processing nodes.

Tor is a very popular anonymisation software and network. For which we created Torminator, a fingerprinting suite written in the Java programming language. Fingerprinting is an attack type applicable to Tor utilising side-channel information from the network packets. With side-channel data, we can analytically access information that purportedly been hidden by design by Tor. Because Tor is a low-latency, low-overhead by design, it will leak communication patterns with intermediate (thus total) communication size. In our case this may able us figure out to which site/service the Tor user is using. This means that anyone with access to user’s traffic can use the fingerprinting attack to partly compromise the provided anonymity. By investigating such attacks, it may help us to better understand how to withstand and resist attacks from powerful adversaries such as state agencies. Torminator automatises the process for gathering fingerprints. It uses the official Tor Browser through its GUI to enter websites to recreate the real world scenario. This gives us real and reliable fingerprints without having to employ a human to do anything, as Torminator simulates user interaction on Tor Browser for us. We can also give Torminator a list of websites to fingerprint, making it easy to generate lots of fingerprints for a great number given sites. A contribution of Torminator, is that we improved on the previous de facto standard of the fingerprints collected from the available tools from previous works. We have gathered fingerprints and have now a dataset of 65792 fingerprints. Fingerprints like these can be used with machine learning techniques to teach a machine to recognise web-pages by reading the packet size and directions saved in the fingerprint files.

In order to make the electricity supply more reliable and with the development of electricity trading, electric power systems have been steadily growing these last decades. The interconnection of formerly isolated networks has resulted in very large and complex power systems. The drawback of this evolution is that these very large systems are now more vulnerable to stability issues like inter-area oscillations where one area oscillates against one or many others. These instabilities may be particularly dangerous if they lead to a blackout (North America, 2003) which is why stability analysis has to be performed so as to prevent these phenomena. The modal analysis, which is a frequency domain approach, is a very powerful tool to characterize the small signal stability of a power system and will be the one presented in this report. This report is the result of a master thesis project performed in September 2014 to February 2015 at the Network Studies Department of the Power System & Transmission Engineering Department of the EDF group. Over the years, EDF has developed a considerable experience in the diagnostic of inter-area oscillations and the tuning of power system stabilizers by taking repeating actions in electrical networks worldwide. The main task of this report is to formalize this expertise and widen the services offer of the Network Studies Department. Indeed as explained above the development of large electrical networks has increased the need for dynamic stability studies with particular attention to inter-area oscillations. The work done during this project was then organized to guarantee the durability of this expertise and can be divided into two parts: the first one deals with the theory behind modal analysis and how it can be applied to power systems to diagnose eventual stability issues regarding inter-area oscillations; and a second part which tries to give a method to follow to neutralize the impact of an eventual diagnosed inter-area oscillation. Then, of course, a case study based on an actual network has been used to illustrate most of the theory and finally, last but not least in the engineering scope, a sensitivity analysis has been performed. It is actually very important to know which parameters have to be known precisely and which one can be estimated with standard values because in such a study the time required for the data collection can be unreasonably long. It appears from this project that the modal analysis, with its frequency domain approach, is a very convenient tool to characterize the dynamic evolution of a power system around its operating point. It allows to clearly identify the role of each group and to gather groups with the same behavior easily. However, the method used to eliminate the effect of any undesired inter-area oscillation is not easy to implement on an actual power system as a many things have to be taken into consideration if one want to avoid unwanted side effects and it necessitates important precision in the data.

In this thesis work the manufacturing of through glass vias (TGVs) is presented. The TGVs were manufactured by adapting technique based on magnetic assembly developed at KTH for creating through silicon vias (TSVs). TGVs were fabricated by introducing nickel wires in via-holes that were pre-made on a glass substrate and applying a spin-on polymer to isolate the nickel wires from the walls of the via-holes. Another focus of this work was improving the TGV and TSV manufacturing process. This was done by investigating the inuence of the assembly speeds on the yield of the assembly process. Two methods for removing the excess wires left on the surface of the wafer after the magnetic assembly of the nickel wires were tested. Also the inuence the pitch between the via-holes has on the yield of the process was investigated.

With the rapid development of new technologies during the last decades, the demand of complex algorithms to work in real-time applications has increased considerably. To achieve the real time expectations and to assure the stability and accuracy of the systems, the application of numerical methods and matrix decompositions have been studied as a trade-off between complexity, stability and accuracy. In the first part of this thesis, a survey of state-of-the-art QR Decomposition methods applied to matrix inversion is done. Stability and accuracy of these methods are analyzed analytically and the complexity is studied in terms of operations and level of parallelism. Besides, a new method called Modified Gaussian Elimination (MGE) is proposed. This method is shown to have better accuracy and less complexity than the previous methods while keeping good stability in real time applications. In the second part of this thesis, different techniques of extended Kalman Filter implementations are discussed. The EKF is known to be numerically unstable and various methods have been proposed in the literature to improve the performance of the filter. These methods include square-root and unscented versions of the filter that make use of numerical methods such as QR, LDL and Cholesky Decomposition. At the end of the analysis, the audience/reader will get some idea about best implementation of the filter given some specifications.