<p>This study focuses on Finnish transmen and their life stories. It goes through the practical reality of the gender re-assignment process, but focuses on the personal experiences of two individual men. The study is based on in-depth interviews with informants, material which has been analyzed with the help of Judith Butler’s theory on gender.</p> / <p>Den här uppsatsen handlar om två finska transmän och deras livshistorier. Studien går igenom den praktiska realiteten av könskorrigeringsprocessen, men fokuserar på de personliga erfarenheterna av dessa två individuella män. Den är baserad på djupintervjuer med informanter, material som har analyserats med hjälp av Judith Butlers teori om genus.</p>

The Birnbaum importance (BI) is a well-known measure that evaluates the relative contribution of components to system reliability. It has been successfully applied to tackling some reliability problems. This dissertation investigates two topics related to the BI in the reliability field: the patterns of component BIs and the BI-based heuristics and meta-heuristics for solving the component assignment problem (CAP).There exist certain patterns of component BIs (i.e., the relative order of the BI values to the individual components) for linear consecutive-k-out-of-n (Lin/Con/k/n) systems when all components have the same reliability p. This study summarizes and annotates the existing BI patterns for Lin/Con/k/n systems, proves new BI patterns conditioned on the value of p, disproves some patterns that were conjectured or claimed in the literature, and makes new conjectures based on comprehensive computational tests and analysis. More importantly, this study defines a concept of segment in Lin/Con/k/n systems for analyzing the BI patterns, and investigates the relationship between the BI and the common component reliability p and the relationship between the BI and the system size n. One can then use these relationships to further understand the proved, disproved, and conjectured BI patterns.The CAP is to find the optimal assignment of n available components to n positions in a system such that the system reliability is maximized. The ordering of component BIs has been successfully used to design heuristics for the CAP. This study proposes five new BI-based heuristics and discusses their corresponding properties. Based on comprehensive numerical experiments, a BI-based two-stage approach (BITA) is proposed for solving the CAP with each stage using different BI-based heuristics. The two-stage approach is much more efficient and capable to generate solutions of higher quality than the GAMS/CoinBonmin solver and a randomization method.This dissertation then presents a meta-heuristic, i.e., a BI-based genetic local search (BIGLS) algorithm, for the CAP in which a BI-based local search is embedded into the genetic algorithm. Comprehensive numerical experiments show the robustness and effectiveness of the BIGLS algorithm and especially its advantages over the BITA in terms of solution quality.

A review of recent literature and the research effort underlying this dissertation indicates that fractional order differential equations have significant potential to advance dynamical system methods broadly. Particular promise exists in the area of control and estimation, even for systems where fractional order models do not arise “naturally”. This dissertation is aimed at further building of the base methodology with a focus on robust feedback control and state estimation. By setting the mathematical foundation with the fractional derivative Caputo definition, we can expand the concept of the fractional order calculus in a way that enables us to build corresponding controllers and estimators in the state-space form. For the robust eigenstructure assignment, we first examine the conditioning problem of the closed-loop eigenvalues and stability robustnesss criteria for the fractional order system, and we find a unique application of an n-dimensional rotation algorithm developed by Mortari, to solve the robust eigenstructure assignment problem in a novel way. In contradistinction to the existing Fractional Kalman filter developed by using Gru ̈ndwald-Letnikov definition, the new Fractional Kalman filter that we establish by utilizing Caputo definition and our algorithms provide us with powerful means for solving practical state estimation problems for fractional order systems.

This study focuses on Finnish transmen and their life stories. It goes through the practical reality of the gender re-assignment process, but focuses on the personal experiences of two individual men. The study is based on in-depth interviews with informants, material which has been analyzed with the help of Judith Butler’s theory on gender. / Den här uppsatsen handlar om två finska transmän och deras livshistorier. Studien går igenom den praktiska realiteten av könskorrigeringsprocessen, men fokuserar på de personliga erfarenheterna av dessa två individuella män. Den är baserad på djupintervjuer med informanter, material som har analyserats med hjälp av Judith Butlers teori om genus.

We define an order cutoff for a retailer as a time in the day such that orders sent to the depot before this point will be delivered by tomorrow, and orders submitted after will be delivered by the day after tomorrow. The later a retailer’s cutoff, the sooner it receives its orders which helps it to maintain ideal inventory levels. Generally, not all retailers in a supply chain can have the latest cutoff since transportation takes a significant amount of time. This thesis tries to assign optimal order cutoffs to retailers. We call this an order cutoff assignment problem and we solve it using three different mathematical programming approaches. The approaches are exhaustive route generation and selection, a series of mixed integer programs, and branch-and-price. 60 sample problems were solved and results showed that branch-and-price is often the most effective method.

We define an order cutoff for a retailer as a time in the day such that orders sent to the depot before this point will be delivered by tomorrow, and orders submitted after will be delivered by the day after tomorrow. The later a retailer’s cutoff, the sooner it receives its orders which helps it to maintain ideal inventory levels. Generally, not all retailers in a supply chain can have the latest cutoff since transportation takes a significant amount of time. This thesis tries to assign optimal order cutoffs to retailers. We call this an order cutoff assignment problem and we solve it using three different mathematical programming approaches. The approaches are exhaustive route generation and selection, a series of mixed integer programs, and branch-and-price. 60 sample problems were solved and results showed that branch-and-price is often the most effective method.

Exhaustible resource rents are an important taxable base in many countries, with revenue sharing often part of the scheme. In some cases large shares are retained for the central government. Generally, the discussions of exhaustible resource taxation consider assignment of resource rent tax base and revenue sharing from the limited perspectives of efficiency and stability. Tax assignment and sharing arrangements are assumed to have a neutral effect on investment of resource rents in long-lived public goods. We attempt to demonstrate that this may not be the case, specifically looking at the question of whether rent assignment is neutral to effects on investment of rents in long-lived public goods, a normative policy objective, and under what conditions it occurs. We test the theoretical propositions with data from the Russian Federation to derive empirical results. The results from the Russian Federation point toward an important dimension of rent tax assignment in a federation. They results show that ceteris paribus, higher share of rent for the federation may lead to lower investment in long-lived public goods and may be constrained by stability. Another argument has been made for reconsidering rent tax assignment using assertive ethnic identity as a manifestation strong ownership claims. Communities with strongly valued identities value ownership over land and exhaustible resource endowments in their areas. This may be the case especially if ethnic identity is important to the resource owning community. The empirical results show that a decrease in the regional share of rent resulted in a fall in investments in the republics and regions with strong ethnic identity. Republics among the producing regions have historical claims to a distinct identity and may have a preference for preserving their identity. This preference is manifested as higher levels of rent investment. Following this line of argument, it can be concluded that rent assignment, through rent tax or revenue assignment, should favor producing regions within the range of stability in a federation, if the objective is achieving higher investment in long-lived public goods.

Sustainable transportation aims encouragement of non-motorized (pedestrian and bicyclist) and shared-ride transportation modes instead of car-dependent travels. This is important for university campuses, as they have better chance to implement such policies in a rather controlled traffic network, and can set an example to other communities. Most of sustainable campus transportation programs boil down to reduction of car-based emission cost of campus mobility, which is always the first step in developing more sustainable transportation policies. Middle East Technical University (METU), Ankara has a large campus area and a population over 30,000 people. To develop sustainable campus transportation policies, it was important to quantify the current levels of mobility and vehicle emissions within the campus, which was the main motivation behind this study. This required determination of i) campus origin-destination matrix, ii) in-campus vehicle-km-travelled (vehicle-km), and iii) carbon emissions. Travel data obtained from different sources, including the gate entry with RFID systems enabled analysis of different user groups, such as academic and administrative personnel and students, separately. The traffic simulations were prepared in PTV VISUM, which provided both speed and vehicle-km values for road segments, and could represent multi-user group demand matrices in a single traffic assignment. Based on the base case mobility and emission values, more sustainable campus transportation policies were simulated in PTV VISUM, and assessed in terms of carbon emission impacts. Discouraging of private car usage by students seemed the first and simplest action.

Much research has been undertaken to gain insight into business alignment of IT. This alignment basically aims to improve a firm’s performance by an improved harmonization of the business function and the IT function within a firm. The thesis discusses previous approaches and constructs an overall framework, which a potential approach needs to fit in. Being in a highly regulated industry, for airports there is little space left to increase revenues. However, the retailing business has proven to be an area that may contribute towards higher income for airport operators. Consequently, airport management should focus on supporting this business segment. Nevertheless, it needs to be taken into account that smooth airport operations are a precondition for successful retailing business at an airport. Applying the concept of information intensity, the processes of gate allocation and airport retailing have been determined to appraise the potential that may be realized upon (improved) synchronization of the two. It has been found that the lever is largest in the planning phase (i.e. prior to operations), and thus support by means of information technology (for information distribution and improved planning) may help to enable an improved overall retail performance. In order to determine potential variables, which might influence the output, a process decomposition has been conducted along with the development of an appropriate information model. The derived research model has been tested in different scenarios. For this purpose an adequate gate allocation algorithm has been developed and implemented in a purposewritten piece of software. To calibrate the model, actual data (several hundred thousand data items from Frankfurt Airport) from two flight plan seasons has been used. Key findings: The results show that under the conditions described it seems feasible to increase retail sales in the magnitude of 9% to 21%. The most influential factors (besides the constraining rule set and a retail area’s specific performance) proved to be a flight’s minimum and maximum time at a gate as well as its buffer time at gate. However, as some of the preconditions may not be accepted by airport management or national regulators, the results may be taken as an indication for cost incurred, in case the suggested approach is not considered. The transferability to other airport business models and limitations of the research approach are discussed at the end along with suggestions for future areas of research.

The question of how to design a congestion pricing scheme is difficult to answer and involves a number of complex decisions. This thesis is devoted to the quantitative parts of designing a congestion pricing scheme with link tolls in an urban car traffic network. The problem involves finding the number of tolled links, the link toll locations and their corresponding toll level. The road users are modeled in a static framework, with elastic travel demand. Assuming the toll locations to be fixed, we recognize a level setting problem as to find toll levels which maximize the social surplus. A heuristic procedure based on sensitivity analysis is developed to solve this optimization problem. In the numerical examples the heuristic is shown to converge towards the optimum for cases when all links are tollable, and when only some links are tollable. We formulate a combined toll location and level setting problem as to find both toll locations and toll levels which maximize the net social surplus, which is the social surplus minus the cost of collecting the tolls. The collection cost is assumed to be given for each possible toll location, and to be independent of toll level and traffic flow. We develop a new heuristic method which is based on repeated solutions of an approximation to the combined toll location and level setting problem. Also, a known heuristic method for locating a fixed number of toll facilities is extended, to find the optimal number of facilities to locate. Both heuristics are evaluated on two small networks, where our approximation procedure shows the best results. Our approximation procedure is also employed on the Sioux Falls network. The result is compared with different judgmental closed cordon structures, and the solution suggested by our method clearly improves the net social surplus more than any of the judgmental cordons.