This thesis presents a mobile instrumentation middleware, AWARE, aimed at facilitating our understanding of human behavior. We demonstrate how to use AWARE to build context-aware applications, collect data, and study human behavior. Mobile phones are resource-constrained and several considerations need to be taken into account to create a research tool that ensures problem-free data collection. AWARE can mitigate researchers’ effort when building mobile data-logging tools and context-aware applications. By encapsulating implementation details of sensor data retrieval and exposing the sensed data as higher-level abstractions, researchers spend less time developing software and save more time for doing research and analyzing the collected data, both quantitative and qualitative. This thesis demonstrates AWARE’s use in a number of case studies. These vary in the research methods we have used: prototype-building; large-scale deployment; surveys; interviews; cognitive walkthroughs; heuristic evaluation; laboratory & field studies data logs; Day Reconstruction Method (DRM); and Experience Sampling Method (ESM). Together with these methods, we demonstrate how AWARE helps study human behavior in different research scenarios, such as: enabling human-smartphone awareness, understanding concerns on battery life, modeling the proximity of users to their smartphones, and capturing location sharing concerns. The thesis’ contributions are: the design, implementation and evaluation of a novel mobile instrumentation middleware to facilitate an understanding of human behavior.

/pdf/aware-a-mobile-context-instrumentation-middleware-to-3hvgm4pfbz.pdf

AWARE : a mobile context instrumentation middleware to collaboratively understand human behavior

Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied combustion variables. The potentiality of flue gas temperatures to monitor the quality and efficiency of combustion allows development toward cost effective control systems. Moreover, the uniformity of the presented signal correlations could enable straightforward copies of such systems. This would cumulatively impact the reduction of emissions and fuel consumption in small-scale biomass combustion.

/pdf/signal-correlations-in-biomass-combustion-an-information-2ca8m1thry.pdf

Signal correlations in biomass combustion – an information theoretic analysis

Tiivistelmä Preface 9 Acknowledgements 11 Symbols and abbreviations 13

/pdf/analysis-of-the-spatial-throughput-in-interference-networks-33sk9bhpuw.pdf

Analysis of the spatial throughput in interference networks

The releases of chlorinated volatile organic compounds (CVOCs) are controlled by strict regulations setting high demands for the abatement systems. Low temperature catalytic oxidation is a viable technology to economically destroy these often refractory emissions. Catalysts applied in the oxidation of CVOCs should be highly active and selective but also maintain a high resistance towards deactivation. In this study, a total of 33 different γ-Al2O3 containing metallic monoliths were studied in dichloromethane (DCM) and 25 of them in perchloroethylene (PCE) oxidation. The active compounds used were Pt, Pd, Rh or V2O5 alone or as mixtures. The catalysts were divided into three different testing sets: industrial, CVOC and research catalysts. ICP-OES, physisorption, chemisorption, XRD, UV-vis DRS, isotopic oxygen exchange, IC, NH3-TPD, H2-TPR and FESEM-EDS were used to characterise the catalysts. Screening of the industrial catalysts revealed that the addition of V2O5 improved the performance of the catalyst. DCM abatement was easily affected by the addition of VOC or water, but the effect on the PCE oxidation was only minor. Based on these screening tests, a set of CVOC catalysts were developed and installed into an industrial incinerator. The comparison between the laboratory and industrial scale studies showed that DCM oxidation in an industrial incinerator could be predicted relatively well. Instead, PCE was always seen to be oxidised far better in an industrial unit indicating that the transient oxidation conditions are beneficial for the PCE oxidation. Before starting the experiments with research catalysts, the water feed was optimised to 1.5 wt.%. Besides enhancing the HCl yields, water improved the DCM and PCE conversions. In the absence of oxygen, i.e. during destructive adsorption, the presence of water was seen to have an even more pronounced effect on the HCl formation and on the catalysts’ stability. In the DCM oxidation, the addition of the active compound on the catalyst support improved the selectivity, while the enhancing effect on the DCM conversion was only small. The high acidity together with the increased reducibility was seen to lead to an active catalyst. Among the research catalysts Pt/Al2O3 was the most active in the DCM oxidation. With PCE the addition of the active compound proved to be very beneficial also for the PCE conversion. Now Pt and Pd supported on Al2O3-CeO2 were the most active. The enhanced reducibility was seen to be the key feature of the catalyst in PCE oxidation.

/pdf/catalytic-oxidation-of-chlorinated-volatile-organic-4f2cpasuft.pdf

Catalytic oxidation of chlorinated volatile organic compounds, dichloromethane and perchloroethylene : new knowledge for the industrial CVOC emission abatement

Doppler optical coherence tomography (DOCT) provides a non-disruptive, high resolution and real-time method for imaging flow velocity profiles inside small channels and capillaries. DOCT has been mostly used in the biomedical field to image blood flow. However, applications in the field of rheology have been rare. In this thesis, the time domain DOCT (TD-DOCT) was utilized to measure flow velocity profiles inside capillaries with high resolution. Time domain configuration was chosen due to the ability to implement dynamic focusing and, in addition, to have sufficient velocity range, especially at high speeds. The accuracy and reliability of the laboratory-built DOCT device was verified with Newtonian suspension and, further, the performance was compared to the commercial DOCT. In vivo measurements with slime mould Physarum polycephalum showed the versatility of DOCT to measure the flow velocity profile of a different kind of scattering suspension even with very low flow rates. The effects of multiple scattering on the accuracy of the measured flow velocity profiles were experimentally studied with two phantom configurations. The first case consisted of the static superficial layer, where the plain glass capillary with flowing Intralipid suspension was embedded into a cuvette. In the second case the moving superficial layer was made by introducing a second glass capillary in front of the studied flow. The results showed that multiple scattering has noticeable effect on the accuracy of the measured flow velocity profiles, especially at the deeper regions. Novel application of the DOCT technique is presented by implementing it to a capillary viscometer. As a result, the absolute viscosity of the Newtonian suspension is derived with high precision directly from the measured flow velocity profile and pressure drop without making any assumption of the flow under study. The results are consistent with the reference values measured with the commercial viscometer.

/pdf/doppler-optical-coherence-tomography-in-determination-of-7aqfp84e18.pdf

Doppler optical coherence tomography in determination of suspension viscosity

The aim of this thesis is to devise novel cooperative paradigms that allow small base stations (SBSs) to perform joint optimizations in the field of interference and spectral resource management, in an automated, self-organizing way. Fostering cooperation requires a careful negotiation process and incurs additional operational costs that can ultimately limit the scalability of such an approach. Hence, we design cooperative models around the self-organizing functions of small cell networks, through which each SBS dynamically adapts its own cooperative strategy to the current network status. In the first part of the thesis, we study the co-tier interference in the downlink of an underlay small cell tier. Showing that mutual interference is a limiting factor, we propose a cooperative scheme based on the concept of interference alignment. Thereby, the SBSs autonomously devise their cooperative strategy, select partner small base stations and suppress the mutual interference via alignment. In the second part, we extend the above problem by considering additional constraints posed by non-cooperative macro cell users sharing the spectrum with the SBSs. Due to the dimension of such a problem, we show that interference alignment solutions do not often exist, hence, we propose a distributed solution based on the concept of interference draining for solving the interfering signals in the space-frequency domain. Finally, we focus on inter-tier cooperation and propose an adaptive hybrid access policy based on spectrum leasing, which jointly enhances the SBSs' transmission capacity and the macro cell users' QoS . In the studied scenarios, we highlight how SBSs' individual performance is networkdependent, due to the shared nature of the spectrum and the network infrastructure. For addressing such issues, we use novel concepts from coalitional games in partition form in which the strategic decisions are optimized by accounting for external effects, such as interference or dynamic spectrum allocation. Based on the properties of optimality of coalitional games in partition form, the proposed cooperative solutions show two key features. First, by leveraging on decentralized strategic decisions, complex interference management techniques, such as interference alignment or draining, can be implemented in practical, scalable way. Second, although notable cooperative solutions exists for certain problem dimensions, the proposed algorithms are shown to be effective for a wide range of network sizes, by achieving significant data rate enhancement and low overhead.

/pdf/cooperative-interference-and-radio-resource-management-in-1p3tvecpr2.pdf

Cooperative interference and radio resource management in self-organizing small cell networks

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Cooperative interference and radio resource management in self-organizing small cell networks