The doctoral thesis proposes a synchronization event detection method suitable for establishing a common time base across devices using power-line communication. The technique facilitates the creation of a synchronization procedure for smart grid terminal devices, thus bringing to the low-voltage segment new functionalities already known from the higher voltage levels of the distribution network. High-precision, zero-cross line voltage detection was employed as the synchronization event. The use of the PLL (phase-locked loop) was considered and analyzed as a potentially applicable option; however, such a solution proved to be insufficiently robust against interference. Further, an FFT-based approach was designed and reviewed. The technique performs zero-cross detection, but only for the fundamental harmonic component that remains the same across the entire network. The influence of incoherent sampling on the FFT, too, was tested during the development of the method; in this context, coherent sampling was found to constitute an essential prerequisite for accurate detection as it allows us to eliminate the spectral leakage error. The impact of an AD converter on the detection accuracy was also evaluated. The proposed approach ensures the accuracy required for all common measurements and operations to improve the production, distribution, and consumption of electricity through smart grids.

In a wireless communication system, synchronization is one of the most critical functions. Good timing and synchronization can prevent messages of the communication system from interfering with each other and enable a smooth message transfer. For 5G (the fifth generation of telecommunication network), the timing and synchronization requirements are even more strict. To synchronize the communication system, the first thing is to detect the connection quality and find the faults’ positions. This thesis aims to investigate a machine learning or deep learning approach to predict the connection quality called ”Hearability” between cells and to find the base stations whose cells have an absolute time error larger than a configurable threshold. The results show that the random forest classifier can obtain the highest accuracy while requiring less computing time than k-Nearest-Neighbors, Support Vector Machine, and Graph Neural Network. Additionally, we found the base stations with faults and offered suggestions for detecting the faults in complicated cases. / I ett trådlöst kommunikationssystem är synkronisering en av de mest kritiska funktionerna. Bra timing och synkronisering kan förhindra meddelanden från kommunikationssystemet från att störa varandra och möjliggöra en smidig meddelandeöverföring. För 5G (den femte generationens telekommunikationsnätverk) är kraven på timing och synkronisering ännu strängare. För att synkronisera kommunikationssystemet är det första att detektera anslutningskvaliteten och hitta felens positioner. Denna avhandling syftar till att undersöka en maskininlärning eller djupinlärning för att förutsäga anslutningskvaliteten som kallas ”Hörbarhet” mellan celler och att hitta de basstationer vars celler har ett absolut tidsfel som är större än en konfigurerbar tröskel. Resultaten visar att den slumpmässiga skogsklassificeraren kan få högsta noggrannhet samtidigt som den kräver mindre beräkningstid än k-Nearest-Neighbors, Support Vector Machine och Graph Neural Network. Dessutom hittade vi basstationerna med fel och gav förslag för att upptäcka felen i komplicerade fall.

A key input parameter to governor feedback control and stability protection of generators is the angle of the induced voltage internal to the generator. Current practice is to estimate this value using measurements from the terminals of the generator and mathematical models. This project aims to develop a system that would directly measure the internal angle of the generator using a rotary encoder on the shaft of the machine. This document describes the theory and experimental setup of this proposed system and outlines the test procedure of experimentation. / Master of Science

The following thesis consists of two main contributions to the fields of network coding and resource allocation. The first is a quantitative analysis of the effects of channel estimation errors and time synchronization errors on the performance of different network coding algorithms. It is shown that the performance improvement gained by a relay-based network scheme is significant for small number of users and when the quality of the relay link is better than that of the direct link. However, it is shown that potential performance improvement resulting from the considered relay-based network coding scheme could be negated by channel estimation errors. To consider the effects of time synchronization errors, we study a digital network coding (DNC) system and a physical-layer network coding (PNC) system with non-coherent frequency shift keying (FSK) modulation. For each of these two systems, we investigate the effects of received Eb/N0, unequal link quality, and time synchronization errors. The second contribution is an analysis of the value and cost of cognition obtained by investigating three resource allocation algorithms with different levels of channel knowledge in the context of ad hoc networks. The performance (quantified in terms of "percentage of users reaching target data rate" and "average effective data rate") and cost ("power consumption" and "number of channel estimations") of these algorithms are analyzed. Results show that a resource allocation algorithm with a higher level of channel knowledge results in better performance, but greater cost in terms of number of channel estimations, as expected. In addition, a resource allocation algorithm with a higher level of channel knowledge converges quicker when channel adaptation are necessary. Both an ideal medium access control (MAC) protocol and a non-ideal MAC protocol (dedicated control channel) are considered. / Master of Science

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / Synchronized video is crucial for data acquisition and telecommunication applications. For real-time applications, out-of-sync video may cause jitter, choppiness and latency. For data analysis, it is important to synchronize multiple video channels and data that are acquired from PCM, MIL-STD-1553 and other sources. Nowadays, video codecs can be easily obtained to play most types of video. However, a great deal of effort is still required to develop the synchronization methods that are used in a data acquisition system. This paper will describe several methods that TTC has adopted in our system to improve the synchronization of multiple data sources.

In this work, we investigate the application of Bayesian filtering techniques such as Kalman Filtering and Particle filtering to the problems of network time synchronization, self-localization and radio-frequency (RF) tomography in wireless networks. Networks of large numbers of small, cheap, mobile wireless devices have shown enormous potential in applications ranging from intrusion detection to environmental monitoring. These applications require the devices to have accurate time and position estimates, however traditional techniques may not be available. Additionally RF tomography offers a new paradigm to sense the network environment and could greatly enhance existing network capabilities. While there are some existing works addressing these problems, they all suffer from limitations. Current time synchronization methods are not energy efficient on small wireless devices with low quality oscillators. Existing localization methods do not consider additional sources of information available to nodes in the network such as measurements from accelerometers or models of the shadowing environment in the network. RF tomography has only been examined briefly in such networks, and current algorithms can not handle node mobility and rely on shadowing models that have not been experimentally verified. We address the time synchronization problem by analyzing the characteristics of the clocks in small wireless devices, developing a model for it, and then applying a Kalman filter to track both clock offset and skew. In our investigation into RF tomography, we present a method using a Kalman filter which jointly estimates and tracks static and dynamic objects in the environment. We also use channel measurements collected from a field test of our RF tomography testbed to compare RF shadowing models. For the localization problem, we present two algorithms incorporating additional information for improved localization: one based on a distributed extended Kalman filter that combines local acceleration measurements with signal strength measurements for improved localization, and another that uses a distributed particle filter to incorporate a model of the channel environment.

This thesis proposes an implementation of battery-powered, time-synchronized wireless nodes that can be deployed in a wireless network topology. Wireless sensor networks are used in a wide variety of scenarios where emphasis is placed on the wireless nodes’ battery life. The main area of focus in this thesis is to examine how wireless nodes can save battery power by utilizing a deep sleep mode and wake up simultaneously using time synchronization to carry out their data communication. This was achieved by deploying five time-synchronized, battery-powered nodes in a wireless network topology. The difference in battery current draw between continuously running nodes and sleep-enabled nodes were measured, as well as the time duration needed by the nodes to successfully send their payloads and route other nodes’ data. The nodes needed between 1502 ms and 3273 ms on average to carry out their data communication, depending on where they were located in the network topology. Measurements show that sleep-enabled nodes on average draw substantially less current than continuously running nodes during a complete data communication cycle. When sleep-enabled nodes were powered by two AA batteries, an increase in battery life of up to 1800% was observed.

I denna uppsats undersöker vi hur tre olika tidpunkter för visning av information på en secondscreen uppfattas av personer. Målet med undersökningen är att få en inblick i hur tittare upplever information som visas på en second-screen. Vi hoppas att resultatet ska kunna bidra till utformingen av kommande second-screenapplikationer. Dessutom har vi undersökt om tidpunkten av när information visas påverkar minnet av det personer ser på second-screenen. Vi utförde tester på totalt 18 personer med hjälp av tre stycken prototyper och varje testperson blev intervjuad efteråt. / In this paper, we examine how three different times for displaying information on a second-screen is perceived by people. The goal of the survey is to get an insight in how viewers perceive information displayed on a second-screen. We hope that the results will contribute to the design of future second-screen applications. In addition, we investigated whether the timing of when the information is displayed, affects the memory of the people using the second-screen. We performed tests on a total of 18 people with the help of three prototypes, each subject was interviewed afterwards.

The master's thesis deals with design of a solution for time synchronization in computer networks that is a crucial problem of many network applications. Based on analysis of protocols for time synchronization, PTP protocol was chosen as an appropriate candidate. The thesis describes the implementation of the design for a special network interface card and demonstrates features of the solution in several tests. A part of the solution processing precise timestamps was implemented in FPGA chip on the network card while PTP messages are processed in a software application. Values of configurable parameters of the application were determined based on analysis of the network card properties and results of particular tests. It was achieved accuracy in order of tens of nanoseconds.

Nowadays due to advancements in Computer Vision algorithms, there is an increasing demand for cost effective and reliable performance evaluation of its algorithms. For objective evaluation of camera object and lane detection algorithms, generation of ground truth is important. Ground truth refers to the set of measurements known to be accurate thereby acting as reference. In context of Computer Vision, it includes a set of labeled images. However, obtaining it by direct observation is not possible. Thus, its generation is an intriguing challenge and numerous efforts have been made in accordance to that. Most commonly, it is generated manually thereby consuming lot of time, effort and money. The existing or proposed semi-automatic approaches fail to address the issues of manual ground truth generation. Currently in the Bosch Validation toolchain, synchronized reference ground truth for Bosch Camera sensor is not present and the annotation is done manually. The term 'reference ground truth' in this thesis refers to the information provided by the reference sensors. Hence, this thesis focuses on the feasibility of Ibeo reference sensors and Ibeo tool chain to obtain synchronized reference GT for enabling automatic preannotation process. The report thus highlights the details related to research, formulated concepts, employed synchronization approach and the developed label toolbox for facilitating fullautomatic pre-annotation process with Reference Sensors System. Upon visualizing the results, the need for cross calibration between Bosch camera and reference sensors is specified. Moreover, with the help of results and findings, requirements are derived to improve the proposed annotation process and to obtain more accurate reference ground truth for evaluation of Front Camera algorithms.