This thesis studies the problem of measuring freedom of choice. It analyzes the concept of freedom of choice, discusses conditions that a measure should satisfy, and introduces a new class of measures that uniquely satisfy ten proposed conditions. The study uses a decision-theoretical model to represent situations of choice and a metric space model to represent differences between options. The first part of the thesis analyzes the concept of freedom of choice. Different conceptions of freedom of choice are categorized into evaluative and non-evaluative, as well as preference-dependent and preference-independent kinds. The main focus is on the three conceptions of freedom of choice as cardinality of choice sets, representativeness of the universal set, and diversity of options, as well as the three conceptions of freedom of rational choice, freedom of eligible choice, and freedom of evaluated choice. The second part discusses the conceptions, together with conditions for a measure and a variety of measures proposed in the literature. The discussion mostly focuses on preference-independent conceptions of freedom of choice, in particular the diversity conception. Different conceptions of diversity are discussed, as well as properties that could affect diversity, such as the cardinality of options, the differences between the options, and the distribution of differences between the options. As a result, the diversity conception is accepted as the proper explication of the concept of freedom of choice. In addition, eight conditions for a measure are accepted. The conditions concern domain-insensitivity, strict monotonicity, no-choice situations, dominance of differences, evenness, symmetry, spread of options, and limited function growth. None of the previously proposed measures satisfy all of these conditions. The third part concerns the construction of a ratio-scale measure that satisfies the accepted conditions. Two conditions are added regarding scale-independence and function growth proportional to cardinality. Lastly, it is shown that only one class of measures satisfy all ten conditions, given an additional assumption that the measures should be analytic functions with non-zero partial derivatives with respect to some function of the differences. These measures are introduced as the Ratio root measures.

Social media data is used for analytics, e.g., in science, authorities or the industry. Privacy is often considered a secondary problem. However, protecting the privacy of social media users is demanded by laws and ethics. In order to prevent subsequent abuse, theft or public exposure of collected datasets, privacy-aware data processing is crucial. This dissertation presents a concept to process social media data with social media user’s privacy in mind. It features a data storage concept based on the cardinality estimator HyperLogLog to store social media data, so that it is not possible to extract individual items from it, but only to estimate the cardinality of items within a certain set, plus running set operations over multiple sets to extend analytical ranges. Applying this method requires to define the scope of the result before even gathering the data. This prevents the data from being misused for other purposes at a later point in time and thus follows the privacy by design principles. This work further shows methods to increase privacy through the implementation of abstraction layers. An included case study demonstrates the presented methods to be suitable for application in the field.:1 Introduction 1.1 Problem 1.2 Research objectives 1.3 Document structure 2 Related work 2.1 The notion of privacy 2.2 Privacy by design 2.3 Differential privacy 2.4 Geoprivacy 2.5 Probabilistic Data Structures 3 Concept and methods 3.1 Collateral data 3.2 Disposable data 3.3 Cardinality estimation 3.4 Data precision 3.5 Extendability 3.6 Abstraction 3.7 Time consideration 4 Summary of publications 4.1 HyperLogLog Introduction 4.2 VOST Case Study 4.3 Real-time Streaming 4.4 Abstraction Layers 4.5 VGIscience Book Chapter 4.6 Supplementary Software Materials 5 Discussion 5.1 Prevent accidental data disclosure 5.2 Feasibility in the field 5.3 Adjustability for different use cases 5.4 Limitations of HLL 5.5 Security 5.6 Outlook and further research 6 Conclusion Appendix References Publications

This paper explores strategies in portfolio optimization, focusing on integrating mean-variance optimization (MVO) frameworks with cardinality constraints to enhance investment decision-making. Using a combination of quadratic programming and mixed-integer linear programming, the Gurobi optimizer handles complex constraints and achieves computational solutions. The study compares two mathematical formulations of the cardinality constraint: the Complementary Model and the Big M Model. As cardinality increased, risk decreased exponentially, converging at higher cardinalities. This behavior aligns with the theory of risk reduction through diversification. Additionally, despite initial expectations, both models performed similarly in terms of root relaxation risk and execution time due to Gurobi's presolve transformation of the Complementary Model into the Big M Model. Root relaxation risks were identical while execution times varied slightly without a consistent trend, underscoring the Big M Model's versatility and highlighting the limitations of the Complementary Model.

This thesis consists of four self-contained essays in economics, all concerned with different aspects of subjective well-being. The abstracts of the four studies are as follows. Beyond Income: The Importance for Life Satisfaction of Having Access to a Cash Margin. We study how life satisfaction among adult Swedes is influenced by having access to a cash margin, i.e. a moderate amount of money that could be acquired on short notice either through own savings, by loan from family or friends, or by other means. We find that cash margin is a strong and robust predictor of life satisfaction, also when controlling for individual fixed effects and socio-economic conditions, including income. Decomposing Variation in Daily Feelings: The Role of Time Use and Individual Characteristics. I explore the potential of using time-use data for understanding variation in affective well-being. Using the Princeton Affect and Time Survey, I decompose variation in daily affect into explained and unexplained within- and between person variation. Time use is found to mostly account for within-variation. Hence, its explanatory power is largely additive to that of individual characteristics. The explanatory power of time use is small, however. Activities only account for 1–7% of the total variation and this is not increased much by adding contextual variables. The Association Between Life Satisfaction and Affective Well-Being. We estimate the correlation between life satisfaction and affect — two conceptually distinct dimensions of subjective well-being. We propose a simple model that distinguishes between a stable and a transitory component of affect, and which also accounts for measurement error in self-reports of both variables, including current-mood bias effects on life satisfaction judgments. The model is estimated using momentarily measured well-being data, from an experience sampling survey that we conducted on a population sample of Swedes aged 18–50 (n=252). Our main estimates of the correlation between life satisfaction and long-run affective well-being range between 0.78 and 0.91, indicating a stronger convergence between these variables than many previous studies that do not account for measurement issues. Do OLS and Ordinal Happiness Regressions Yield Different Results? A Quantitative Assessment. Self-reported subjective well-being scores are often viewed as ordinal variables, but the conventional wisdom has it that OLS and ordered regression models (e.g. ordered probit) produce similar results when applied to such data. This claim has rarely been assessed formally, however, in particular with respect to quantifying the differences. I shed light on this issue by comparing the results from OLS and different ordered regression models, in terms of both statistical and economic significance, and across data sets with different response scales for measuring life satisfaction. The results are mixed. The differences between OLS, probit and logit estimates are typically small when the response scale has few categories, but larger, though not huge, when an 11-point scale is used. Moreover, when the error term is assumed to follow a skewed distribution, larger discrepancies are found throughout. I find a similar pattern in simulations, in which I assess how different methods perform with respect to the true parameters of interest, rather than to each other.

In the era of "big data revolution," marked by an exponential growth of information, extracting value from data enables analysts and businesses to address challenging problems such as drug discovery, fraud detection, and earthquake predictions. Multi-Criteria Decision Support (MCDS) queries are at the core of big-data analytics resulting in several classes of MCDS queries such as OLAP, Top-K, Pareto-optimal, and nearest neighbor queries. The intuitive nature of specifying multi-dimensional preferences has made Pareto-optimal queries, also known as skyline queries, popular. Existing skyline algorithms however do not address several crucial issues such as performing skyline evaluation over disparate sources, progressively generating skyline results, or robustly handling workload with multiple skyline over join queries. In this dissertation we thoroughly investigate topics in the area of skyline-aware query evaluation. In this dissertation, we first propose a novel execution framework called SKIN that treats skyline over joins as first class citizens during query processing. This is in contrast to existing techniques that treat skylines as an "add-on," loosely integrated with query processing by being placed on top of the query plan. SKIN is effective in exploiting the skyline characteristics of the tuples within individual data sources as well as across disparate sources. This enables SKIN to significantly reduce two primary costs, namely the cost of generating the join results and the cost of skyline comparisons to compute the final results. Second, we address the crucial business need to report results early; as soon as they are being generated so that users can formulate competitive decisions in near real-time. On top of SKIN, we built a progressive query evaluation framework ProgXe to transform the execution of queries involving skyline over joins to become non-blocking, i.e., to be progressively generating results early and often. By exploiting SKIN's principle of processing query at multiple levels of abstraction, ProgXe is able to: (1) extract the output dependencies in the output spaces by analyzing both the input and output space, and (2) exploit this knowledge of abstract-level relationships to guarantee correctness of early output. Third, real-world applications handle query workloads with diverse Quality of Service (QoS) requirements also referred to as contracts. Time sensitive queries, such as fraud detection, require results to progressively output with minimal delay, while ad-hoc and reporting queries can tolerate delay. In this dissertation, by building on the principles of ProgXe we propose the Contract-Aware Query Execution (CAQE) framework to support the open problem of contract driven multi-query processing. CAQE employs an adaptive execution strategy to continuously monitor the run-time satisfaction of queries and aggressively take corrective steps whenever the contracts are not being met. Lastly, to elucidate the portability of the core principle of this dissertation, the reasoning and query processing at different levels of data abstraction, we apply them to solve an orthogonal research question to auto-generate recommendation queries that facilitate users in exploring a complex database system. User queries are often too strict or too broad requiring a frustrating trial-and-error refinement process to meet the desired result cardinality while preserving original query semantics. Based on the principles of SKIN, we propose CAPRI to automatically generate refined queries that: (1) attain the desired cardinality and (2) minimize changes to the original query intentions. In our comprehensive experimental study of each part of this dissertation, we demonstrate the superiority of the proposed strategies over state-of-the-art techniques in both efficiency, as well as resource consumption.

<p>To take advantage of the high speed in an optic fiber, one of the basic concept in fiber optic communication is to allow several users to simultaneously transmit data over the channel. One technique that provides multiple access is it fiber optic-code division multiple access (FO-CDMA). In FO-CDMA each user is assigned one or more signature sequences called codewords, which are subsets of a type of optical orthogonal code (OOC). The channel input/output consists of the superposition of several users codewords and at the receiver end an optical correlator extracts the information. </p><p>In the parallel code constructions, presented in this report, each user j is assigned a subset Cj from a code C. The subsets are disjoint and their union is the whole set C. A new way to map the information bits is to insert up to L zeros before each codeword from Cj and let this represent information aswell. This gives high rates for active users but an investigation is needed to ensure that this does not compromise the systems wanted property of sending information with a small probability of errors for all users. Therefore a simulation environment has been implemented in Matlab. </p><p>The result from these simulations shows that BER for the L parallel codes is acceptable and not much higher than for the traditional constructions. Because of the higher rate these construction should be preferred but an analysis if a hardware implementation is possible.</p>

We study in this thesis three well known global constraints. The All-Different constraint restricts a set of variables to be assigned to distinct values. The <em>global cardinality constraint</em> (GCC) ensures that a value <em>v</em> is assigned to at least <em>l_v</em> variables and to at most <em>u_v</em> variables among a set of given variables where <em>l_v</em> and <em>u_v</em> are non-negative integers such that <em>l_v</em> &le; <em>u_v</em>. The Inter-Distance constraint ensures that all variables, among a set of variables <em>x</em>₁, . . . , <em>x_n</em>, are pairwise distant from <em>p</em>, i. e. |<em>x_i</em> - <em>x_j</em>| &ge; <em>p</em> for all <em>i</em> &ne; <em>j</em>. The All-Different constraint, the GCC, and the Inter-Distance constraint are largely used in scheduling problems. For instance, in scheduling problems where tasks with unit processing time compete for a single resource, we have an All-Different constraint on the starting time variables. When there are <em>k</em> resources, we have a GCC with <em>l_v</em> = 0 and <em>u_v</em> = <em>k</em> over all starting time variables. Finally, if tasks have processing time <em>t</em> and compete for a single resource, we have an Inter-Distance constraint with <em>p</em> = <em>t</em> over all starting time variables. We present new propagators for the All-Different constraint, the GCC, and the Inter-Distance constraint i. e. , new filtering algorithms that reduce the search space according to these constraints. For a given consistency, our propagators outperform previous propagators both in practice and in theory. The gains in performance are achieved through judicious use of advanced data structures combined with novel results on the structural properties of the constraints.

We study in this thesis three well known global constraints. The All-Different constraint restricts a set of variables to be assigned to distinct values. The <em>global cardinality constraint</em> (GCC) ensures that a value <em>v</em> is assigned to at least <em>l_v</em> variables and to at most <em>u_v</em> variables among a set of given variables where <em>l_v</em> and <em>u_v</em> are non-negative integers such that <em>l_v</em> &le; <em>u_v</em>. The Inter-Distance constraint ensures that all variables, among a set of variables <em>x</em>₁, . . . , <em>x_n</em>, are pairwise distant from <em>p</em>, i. e. |<em>x_i</em> - <em>x_j</em>| &ge; <em>p</em> for all <em>i</em> &ne; <em>j</em>. The All-Different constraint, the GCC, and the Inter-Distance constraint are largely used in scheduling problems. For instance, in scheduling problems where tasks with unit processing time compete for a single resource, we have an All-Different constraint on the starting time variables. When there are <em>k</em> resources, we have a GCC with <em>l_v</em> = 0 and <em>u_v</em> = <em>k</em> over all starting time variables. Finally, if tasks have processing time <em>t</em> and compete for a single resource, we have an Inter-Distance constraint with <em>p</em> = <em>t</em> over all starting time variables. We present new propagators for the All-Different constraint, the GCC, and the Inter-Distance constraint i. e. , new filtering algorithms that reduce the search space according to these constraints. For a given consistency, our propagators outperform previous propagators both in practice and in theory. The gains in performance are achieved through judicious use of advanced data structures combined with novel results on the structural properties of the constraints.

This paper is about basic set theory and cardinalities for infinite sets. One of the results are that the line R and the plane R2 contains exactly the same number of points. Because of that the set theory is described with a formal language this the paper has an appendix about formal languages. / Denna uppsats behandlar grundläggande mängdlära och inriktar sig sedan på kardinaliteter för oändliga mängder. Bland de resultat som redovisas finns bland annat resultatet som säger att linjen R och planet R2 innehåller precis lika många punkter. Då mängdläran beskrivs av ett formellt språk så innehåller uppsatsen en bilaga om formella språk.

<p>This paper is about basic set theory and cardinalities for infinite sets. One of the results are that the line R and the plane R2 contains exactly the same number of points. Because of that the set theory is described with a formal language this the paper has an appendix about formal languages.</p> / <p>Denna uppsats behandlar grundläggande mängdlära och inriktar sig sedan på kardinaliteter för oändliga mängder. Bland de resultat som redovisas finns bland annat resultatet som säger att linjen R och planet R2 innehåller precis lika många punkter. Då mängdläran beskrivs av ett formellt språk så innehåller uppsatsen en bilaga om formella språk.</p>