IT Licentiate theses
http://www.it.uu.se/research/publications/lic
Licentiate theses from the Department of Information Technology, Uppsala University, Sweden
20190417T08:39:23Z
Department of Information Technology, Uppsala University, Sweden
Copyright © 2005 Department of Information Technology, Uppsala University, Sweden
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Licentiate thesis 2019003: Volterra Modeling of the Human Smooth Pursuit System in Health and Disease
http://www.it.uu.se/research/publications/lic/2019003
20190513
Viktor Bro
<b>Abstract:</b> This thesis treats the identification of Volterra models of the human smooth pursuit system from eyetracking data. Smooth pursuit movements are gaze movements used in tracking of moving targets and controlled by a complex biological network involving the eyes and brain. Because of the neural control of smooth pursuit, these movements are affected by a number of neurological and mental conditions, such as Parkinson's disease. Therefore, by constructing mathematical models of the smooth pursuit system from eyetracking data of the patient, it may be possible to identify symptoms of the disease and quantify them. While the smooth pursuit dynamics are typically linear in healthy subjects, this is not necessarily true in disease or under influence of drugs. The Volterra model is a classical blackbox model for dynamical systems with smooth nonlinearities that does not require much a priori information about the plant and thus suitable for modeling the smooth pursuit system. The contribution of this thesis is mainly covered by the four appended papers. Papers IIII treat the problem of reducing the number of parameters in Volterra models with the kernels parametrized in Laguerre functional basis (VolterraLaguerre models), when utilizing them to capture the signal form of smooth pursuit movements. Specifically, a VolterraLaguerre model is obtained by means of sparse estimation and principal component analysis in Paper I, and a Wiener model approach is used in Paper II. In Paper III, the same model as in Paper I is considered to examine the feasibility of smooth pursuit eye tracking for biometric purposes. Paper IV is concerned with a VolterraLaguerre model that includes an explicit time delay. An approach to the joint estimation of the time delay and the finitedimensional part of the Volterra model is proposed and applied to timedelay compensation in eyetracking data.

Licentiate thesis 2019002: Inverse Factorization in Electronic Structure Theory: Analysis and Parallelization
http://www.it.uu.se/research/publications/lic/2019002
20190605
Anton G. Artemov
<b>Abstract:</b> This licentiate thesis is a part of an effort to run large electronic structure calculations in modern computational environments with distributed memory. The ultimate goal is to model materials consisting of millions of atoms at the level of quantum mechanics. In particular, the thesis focuses on different aspects of a computational problem of inverse factorization of Hermitian positive definite matrices. The considered aspects are numerical properties of the algorithms and parallelization. Not only is an efficient and scalable computation of inverse factors necessary in order to be able to run large scale electronic computations based on the HartreeFock or KohnSham approaches with the selfconsistent field procedure, but it can be applied more generally for preconditioner construction. Parallelization of algorithms with unknown load and data distributions requires a paradigm shift in programming. In this thesis we also discuss a few parallel programming models with focus on taskbased models, and, more specifically, the Chunks and Tasks model.

Licentiate thesis 2019001: An Invisible Burden: An ExperienceBased Approach to Nurses' Daily Work Life with Healthcare Information Technology
http://www.it.uu.se/research/publications/lic/2019001
20190322
Diane Golay
<b>Abstract:</b> Information and Communication Technology (ICT) has been an increasingly pervasive component of most workplaces throughout the past half century. In healthcare, the turn to the digital has resulted into the broad implementation of Healthcare Information Technology (HIT). The impacts of ICT on work life have been investigated predominantly through surveys, although some researchers have advocated for the use of a qualitative, experiencebased approach. Meanwhile, the existing body of research on the impacts of HIT on clinicians has painted a mixed picture of digitalization. Despite some clear benefits, HIT has indeed been found to have unexpected, unintended adverse consequences for hospital staff. Typical issues include loss in efficiency, extra effort to carry out routine tasks, and the creation of new, HITinduced work activities. Simultaneously, research outside of the healthcare domain has shown that ICT could require extra effort from some users in order for the sociotechnical system to function properly  extra work often invisible to developers. Based on observation, interview and focus group data collected at a large Swedish hospital, this thesis set out to investigate the impact of HIT on hospital nurses from an experiencebased perspective, resulting in four main contributions. First, a method supporting experiencebased data analysis, the HolisticUX method, is introduced. Second, 13 forms of HITinduced additional tasks in nurses' workload are identified, five of which are not acknowledged in previous research. Third, task avoidance is identified as a consequence of nurses' increased workload, negatively affecting patient safety, care quality and nurses' professional satisfaction. Finally, four factors are argued to contribute to a suggested invisibility of the HITinduced time burden in nurses' work life to management and developers: 1) lack of a holistic perspective, 2) the hidden cost of a single click, 3) the invisibility of nursing work, and 4) visible data, invisible work.

Licentiate thesis 2018004: Robustness in Low Power Wide Area Networks
http://www.it.uu.se/research/publications/lic/2018004
20180614
Charalampos Orfanidis
<b>Abstract:</b> During the past few years we have witnessed an emergence of Wide Area Networks in the Internet of Things area. There are several new technologies like LoRa, WiSUN, Sigfox, that offer long range communication and low power for lowbitrate applications. These new technologies enable new application scenarios, such as smart cities, smart agriculture, and many more. However, when these networks coexist in the same frequency band, they may cause problems to each other since they are heterogeneous and independent. Therefore it is very likely to have frame collisions between the different networks. In this thesis we first explore how tolerant these networks are to Cross Technology Interference (CTI). CTI can be described as the interference from heterogeneous wireless technologies that share the same frequency band and is able to affect the robustness and reliability of the network. In particular, we select two of them, LoRa and WiSUN and carry out a series of experiments with real hardware using several configurations. In this way, we quantify the tolerance of cross technology interference of each network against the other as well as which configuration settings are important. The next thing we explored is how well channel sensing mechanisms can detect the other network technologies and how they can be improved. For exploring these aspects, we used the default Clear Channel Assessment (CCA) mechanism of WiSUN against LoRa interference and we evaluated how accurate it is. We also improved this mechanism in order to have higher accuracy detection against LoRa interference. Finally, we propose an architecture for WSNs which will enable flexible reconfiguration of the nodes. The idea is based on Software Defined Network (SDN) principles and could help on our case by reconfiguring a node in order to mitigate the crosstechnology interference from other networks.

Licentiate thesis 2018003: Modeling and Assessment of Human Balance and Movement Disorders Using Inertial Sensors
http://www.it.uu.se/research/publications/lic/2018003
20180529
Fredrik Olsson
<b>Abstract:</b> Inertial sensors and magnetometers are abundant in today's society, where they can be found in many of our everyday electronic devices, such as smart phones or smart watches. Their primary function is to measure the movement and orientation of the device and provide this information for the apps that request it. This licenciate thesis explores the use of these types of sensors in biomedical applications. Specifically, how these sensors can be used to analyze human movement and work as a tool for assessment of human balance and movement disorders. The methods presented in this thesis deal with mathematical modeling of the sensors, their relationship to the biomechanical models that are used to describe the dynamics of human movement and how we can combine these models to describe the mechanisms behind human balance and quantify the symptopms of movement disorders. The main contributions come in the form of four papers. A practical calibration method for accelerometers is presented in Paper I, that deals with compensation of intrinsic sensor errors that are common for relatively cheap sensors that are used in e.g. smart phones. In Paper II we present an experimental evaluation and minor extension of methods that are used to determine the position of the joints in the biomecanical model, using inertial sensor data alone. Paper III deals with system identification of nonlinear controllers operating in closed loop, which is a method that can be used to model the neuromuscular control mechanisms behind human balance. In Paper IV we propose a novel method for quantification of hand tremor, a primary symptom of neurological disorders such as Parkinson's disease (PD) or Essential tremor (ET), where we make use of data collected from sensors in a smart phone. The thesis also contains an introduction to the sensors, biomechanical modeling, neuromuscular control and the various estimation and modeling techniques that are used throughout the thesis.

Licentiate thesis 2018002: Ammonium Based Aeration Control in Wastewater Treatment Plants  Modelling and Controller Design
http://www.it.uu.se/research/publications/lic/2018002
20180412
Tatiana Chistiakova
<b>Abstract:</b> Wastewater treatment involves many processes and methods which make a treatment plant a largescaled and complex system. A fundamental challenge is how to maintain a high process efficiency while keeping the operational costs low. The variety in plant configurations, the nonlinear behaviour, the large time delays and saturations present in the system contribute to making automation and monitoring a demanding task. The biological part of a wastewater treatment process includes an aeration of the water and this process has been shown to often result in the highest energy consumption of the plant. Oxygen supply is a fundamental part of the activated sludge process used for aerobic microorganisms growing. The concentration of the dissolved oxygen should be high enough to maintain a sufficient level of biological oxidation. However, if the concentration is too high the process efficiency is significantly reduced leading to a too high energy consumption. Hence, there are two motivations behind the aeration control task: process efficiency and economy. One of the possible strategies to adjust the dissolved oxygen level in a nitrifying activated sludge process is to use ammonium feedback measurements. In this thesis, an activated sludge process is modelled and analysed in terms of dissolved oxygen to ammonium dynamics. First, the data obtained from a simplified Benchmark Simulation Model no.1 was used to identify the system. Both linear and nonlinear models were evaluated. A model with a Hammerstein structure where the nonlinearity was described by a Monod function was chosen for a more thorough study. Here, a feedback controller was designed to achieve L2stability. The stability region was precomputed to determine the maximum allowed time delay for the closed loop system. Finally, a feedforward controller was added to the system, and shown to significantly improve the disturbance rejection properties.

Licentiate thesis 2018001: Static Instruction Scheduling for High Performance on EnergyEfficient Processors
http://www.it.uu.se/research/publications/lic/2018001
20180117
KimAnh Tran
<b>Abstract:</b> New trends such as the internetofthings and smart homes push the demands for energyefficiency. Choosing energyefficient hardware, however, often comes as a tradeoff to highperformance. In order to strike a good balance between the two, we propose software solutions to tackle the performance bottlenecks of small and energyefficient processors. One of the main performance bottlenecks of processors is the discrepancy between processor and memory speed, known as the memory wall. While the processor executes instructions at a high pace, the memory is too slow to provide data in a timely manner, if data has not been cached in advance. Load instructions that require an access to memory are thereby referred to as longlatency or delinquent loads. Long latencies caused by delinquent loads are putting a strain on small processors, which have few or no resources to effectively hide the latencies. As a result, the processor may stall. In this thesis we propose compiletime transformation techniques to mitigate the penalties of delinquent loads on small outoforder processors, with the ultimate goal to avoid processor stalls as much as possible. Our code transformation is applicable for generalpurpose code, including unknown memory dependencies, complex control flow and pointers. We further propose a softwarehardware codesign that combines the code transformation technique with lightweight hardware support to hide latencies on a stallonuse inorder processor.

Licentiate thesis 2017003: Fault Detection in Water Resource Recovery Facilities
http://www.it.uu.se/research/publications/lic/2017003
20171020
Oscar Samuelsson
<b>Abstract:</b> Reliable sensor values are important for resourceefficient control and operations of wastewater treatment processes. Automatic fault detection methods are necessary to monitor the increasing amount of data produced in any modern water resource recovery facility (WRRF). Most online measurements exhibit large variations under normal conditions, due to considerable variations in the influent flow. The work reported in this licentiate thesis deals with fault detection in WRRFs. In the first paper, we studied how Gaussian process regression (GPR), a probabilistic machine learning method, could be applied for fault detection in WRRFs. The results showed that the standard parameter estimation method for GPR suffered from local optima which could be solved by instead estimating the distribution of the parameters with a sequential Monte Carlo algorithm (GPRSMC). The GPRSMC allowed for automatic estimation of missing data in a simulated influent flow signal with high noise, which is a representative signal for online sensors in WRRFs. In addition, the GPRSMC provided uncertainty predictions for the estimated data and accurate sensor noise estimates. Care should be taken in selecting a suitable kernel for GPR, since the results were in contrast to the general assumption that prior knowledge can easily be encoded by means of selecting a proper kernel. Here, the autocorrelation graph was found useful as diagnostic tool for selecting a proper kernel. In the second paper, we studied how active fault detection (AFD) could be used to reveal information about the sensor status. The AFD was implemented by evaluating the change in a dissolved oxygen (DO)signal caused by the sensor's automatic cleaning system. Fault signatures were obtained for fouling and several other sensor faults such as a worn out or mechanically damaged membrane. This demonstrates the potential of AFD, not only for fault detection, but also for fault diagnosis. Interestingly, the progression of the sensor bias due to organic biofilm fouling differed depending on the measurement technique used within the DOsensor. This is new knowledge that is valuable for process control and should be further studied. The AFD was implemented on a full scale system to demonstrate its applicability, which is rarely done in research papers in the field of WRRFs.

Licentiate thesis 2017002: Modeling the Interactions Between Tasks and the Memory System
http://www.it.uu.se/research/publications/lic/2017002
20171011
Germán Ceballos
<b>Abstract:</b> Making computer systems more energy efficient while obtaining the maximum performance possible is key for future developments in engineering, medicine, entertainment, etc. However it has become a difficult task due to the increasing complexity of hardware and software, and their interactions. For example, developers have to deal with deep, multilevel cache hierarchies on modern CPUs, and keep busy thousands of cores in GPUs, which makes the programming process more difficult. To simplify this task, new abstractions and programming models are becoming popular. Their goal is to make applications more scalable and efficient, while still providing the flexibility and portability of old, widely adopted models. One example of this is taskbased programming, where simple independent tasks (functions) are delegated to a runtime system which orchestrates their execution. This approach has been successful because the runtime can automatically distribute work across hardware cores and has the potential to minimize data movement and placement (e.g., being aware of the cache hierarchy). To build better runtime systems, it is crucial to understand bottlenecks in the performance of current and future multicore systems. In this thesis, we provide fast, accurate and mathematicallysound models and techniques to understand the execution of taskbased applications concerning three key aspects: memory behavior (data locality), scheduling, and performance. With these methods, we lay the groundwork for improving runtime system, providing insight into the interplay between the schedule's behavior, data reuse through the cache hierarchy, and the resulting performance.

Licentiate thesis 2017001: Hybrid Observers for Systems with Intrinsic PulseModulated Feedback
http://www.it.uu.se/research/publications/lic/2017001
20170303
Diana Yamalova
<b>Abstract:</b> This licentiate thesis deals with a special class of hybrid systems, where the continuous linear part is controlled by an intrinsic impulsive feedback that contributes discrete dynamics. The impacting pulsatile feedback signal is not available for measurement and, therefore, has to be reconstructed. To estimate all the elements of the hybrid state vector, an observation problem is considered. The motivation for the research performed in this thesis comes from mathematical modelling of pulsatile endocrine regulation, where one of the hormones (a releasing hormone) is secreted in pulses from neurons in the hypothalamus of the brain. Thus a direct measurement of the concentration of this hormone in the human is not possible for ethical reasons and has to be estimated. Several hybrid observer structures are proposed and evaluated. The observer design is reduced to a problem of synchronizing the impulsive sequence produced by the observer with that of the plant. It utilizes a local approach of assigning, through the output error feedback in both the discrete and continuous parts of the plant model, a guaranteed convergence rate to the local dynamics of a synchronous mode. Performance of the proposed observer schemes is analyzed by means of pointwise discrete (Poincare) maps. The first two papers of the thesis address the effects of observer design degrees of freedom on the convergence of the hybrid state estimation error. A generalization of the proposed observation scheme to hybrid impulsive systems with a time delay in continuous part of the plant is investigated in Paper III and Paper IV.

Licentiate thesis 2016012: New Techniques for Handling Quantifiers in Boolean and FirstOrder Logic
http://www.it.uu.se/research/publications/lic/2016012
20161212
Peter Backeman
<b>Abstract:</b> The automation of reasoning has been an aim of research for a long time. Already in 17th century, the famous mathematician Leibniz invented a mechanical calculator capable of performing all four basic arithmetic operators. Although automatic reasoning can be done in different fields, many of the procedures for automated reasoning handles formulas of firstorder logic. Examples of use cases includes hardware verification, program analysis and knowledge representation. One of the fundamental challenges in firstorder logic is handling quantifiers and the equality predicate. On the one hand, SMTsolvers (Satisfiability Modulo Theories) are quite efficient at dealing with theory reasoning, on the other hand they have limited support for complete and efficient reasoning with quantifiers. Sequent, tableau and resolution calculi are methods which are used to construct proofs for firstorder formulas and can use more efficient techniques to handle quantifiers. Unfortunately, in contrast to SMT, handling theories is more difficult. In this thesis we investigate methods to handle quantifiers by restricting search spaces to finite domains which can be explored in a systematic manner. We present this approach in two different contexts. First we introduce a function synthesis based on templatebased quantifier elimination, which is applied to gene interaction computation. The function synthesis is shown to be capable of generating smaller representations of solutions than previous solvers, and by restricting the constructed functions to certain forms we can produce formulas which can more easily be interpreted by a biologist. Secondly we introduce the concept of Bounded Rigid EUnification (BREU), a finite form of unification that can be used to define a complete and sound sequent calculus for firstorder logic with equality. We show how to solve this bounded form of unification in an efficient manner, yielding a firstorder theorem prover utilizing BREU that is competitive with other stateoftheart tableau theorem provers.

Licentiate thesis 2016011: Learning Probabilistic Models of Dynamical Phenomena Using Particle Filters
http://www.it.uu.se/research/publications/lic/2016011
20161216
Andreas Svensson
<b>Abstract:</b> Dynamical behavior can be seen in many reallife phenomena, typically as a dependence over time. This thesis studies and develops methods and probabilistic models for statistical learning of such dynamical phenomena. A probabilistic model is a mathematical model expressed using probability theory. Statistical learning amounts to constructing such models, as well as adjusting them to data recorded from reallife phenomena. The resulting models can be used for, e.g., drawing conclusions about the phenomena under study and making predictions. The methods in this thesis are primarily based on the particle filter and its generalizations, sequential Monte Carlo (SMC) and particle Markov chain Monte Carlo (PMCMC). The model classes considered are nonlinear statespace models and Gaussian processes. The following contributions are included. Starting with a Gaussianprocess statespace model, a general, flexible and computationally feasible nonlinear statespace model is derived in Paper I. In Paper II, a benchmark is performed between the two alternative stateoftheart methods SMCs and PMCMC. Paper III considers PMCMC for solving the statespace smoothing problem, in particular for an indoor positioning application. In Paper IV, SMC is used for marginalizing the hyperparameters in the Gaussianprocess statespace model, and Paper V is concerned with learning of jump Markov linear statespace models. In addition, the thesis also contains an introductory overview covering statistical inference, statespace models, Gaussian processes and some advanced Monte Carlo methods, as well as two appendices summarizing some useful technical results.

Licentiate thesis 2016010: Approximations and Abstractions for Reasoning about Machine Arithmetic
http://www.it.uu.se/research/publications/lic/2016010
20161014
Aleksandar Zeljic
<b>Abstract:</b> Safetycritical systems rely on various forms of machine arithmetic to perform their tasks: integer arithmetic, fixedpoint arithmetic or floatingpoint arithmetic. The problem with machine arithmetic is that it can exhibit subtle differences in behavior compared to the ideal mathematical arithmetic, due to fixedsize representation in memory. Failure of safetycritical systems is unacceptable, because it can cost lives or huge amounts of money, time and effort. To prevent such incidents, we want to formally prove that systems satisfy certain safety properties, or otherwise discover cases when the properties are violated. However, for this we need to be able to formally reason about machine arithmetic. The main problem with existing approaches is their inability to scale well with the increasing complexity of systems and their properties. In this thesis, we explore two alternatives to bitblasting, the core procedure lying behind many common approaches to reasoning about machine arithmetic. In the first approach, we present a general approximation framework which we apply to solve constraints over floatingpoint arithmetic. It is built on top of an existing decision procedure, e.g., bitblasting. Rather than solving the original formula, we solve a sequence of approximations of the formula. Initially very crude, these approximations are frequently solved very quickly. We use results from these approximations to either obtain a solution, obtain a proof of unsatisfiability or generate a new approximation to solve. Eventually, we will either have found a solution or a proof that solution does not exist. The approximation framework improves the solving time and can solve a number of formulas that the bitblasting cannot. In the second approach, we present a novel method to reason about the theory of fixedwidth bitvectors. This new decision procedure is called mcBV and it is based on the model constructing satisfiability calculus (mcSAT). The procedure uses a lazy representation of bitvectors and attempts to avoid bitblasting altogether. It is able to reason about bitvectors on both bit and wordlevel, leveraging both Boolean constraint propagation and native arithmetic reasoning. It also features a greedy explanation generalization mechanism and is capable of more general learning compared to existing approaches. mcBV is able to reason about bitvectors with sizes that significantly exceed the usual 32, 64 and 128 bits. Evaluation of mcBV shows an improvement in performance (compared to bitblasting) on several classes of problems.

Licentiate thesis 2016009: Inflow Generation for ScaleResolving Simulations of Turbulent Boundary Layers
http://www.it.uu.se/research/publications/lic/2016009
20160930
Timofey Mukha
<b>Abstract:</b> Generating inflow fields for scaleresolving simulations of turbulent flow is crucial for a wide range of applications and is an active area of research. In this thesis, a method for inflow generation employing a precursor turbulent channel flow simulation is proposed. A procedure for determining the parameters of the precursor simulation based on the properties of the inflow is given. To evaluate the performance of the method, results from a simulation of a flatplate zeropressuregradient turbulent boundary layer are analysed. The adaption length is quantified in terms of the development of integral quantities and the statistical moments of the velocity field. The performance is also compared with that of a stateoftheart rescaling method for the generation of inflow data. It is shown that both approaches result in adaption lengths of comparable sizes, which makes the proposed method an attractive alternative due to its conceptual simplicity and robustness. As part of the work on inflow generation, a Python package, eddylicious, was developed. The purpose of the package is to be a framework within which various generation methods can be implemented. The package is available online under an opensource license. An overview of the architecture and currently implemented functionality of the package is given in this thesis. Furthermore, the results of a preparatory study on largeeddy simulation of wallbounded turbulent flows are discussed. Fullydeveloped turbulent channel flow is used as a model problem, and the generalpurpose computational fluid dynamics solver OpenFOAM is employed. The accuracy of the results with respect to the resolution of the computational mesh is analysed. Several modelling approaches for the subgrid scale stresses are considered.