Japanese Video Game Localization : A Case Study of Sony's Sairen Series

This thesis is a comparative case study in Japanese video game localization for the video games Sairen, Sairen 2 and Sairen Nyûtoransurêshon, and English-language localized versions of the same games as published in Scandinavia and Australia/New Zealand. All games are developed by Sony Computer Entertainment Inc. and published exclusively for Playstation2 and Playstation3 consoles. The fictional world of the Sairen games draws much influence from Japanese history, as well as from popular and contemporary culture, and in doing so caters mainly to a Japanese audience. For localization, i.e. the adaptation of a product to make it accessible to users outside the original market it was intended for in the first place, this is a challenging issue. Video games are media of entertainment, and therefore localization practice must preserve the games’ effects on the players’ emotions. Further, video games are digital products that are comprised of a multitude of distinct elements, some of which are part of the game world, while others regulate the connection between the player as part of the real world and the game as digital medium. As a result, video game localization is also a practice that has to cope with the technical restrictions that are inherent to the medium. The main theory used throughout the thesis is Anthony Pym’s framework for localization studies that considers the user of the localized product as a defining part of the localization process. This concept presupposes that localization is an adaptation that is performed to make a product better suited for use during a specific reception situation. Pym also addresses the factor that certain products may resist distribution into certain reception situations because of their content, and that certain aspects of localization aim to reduce this resistance through significant alterations of the original product. While Pym developed his ideas with mainly regular software in mind, they can also be adapted well to study video games from a localization angle. Since modern video games are highly complex entities that often switch between interactive and non-interactive modes, Pym’s ideas are adapted throughout the thesis to suit the particular elements being studied. Instances analyzed in this thesis include menu screens, video clips, in-game action and websites. The main research questions focus on how the games’ rules influence localization, and how the games’ fictional domain influences localization. Because there are so many peculiarities inherent to the medium of the video game, other theories are introduced as well to complement the research at hand. These include Lawrence Venuti’s discussions of foreiginizing and domesticating translation methods for literary translation, and Jesper Juul’s definition of games. Additionally, knowledge gathered from interviews with video game localization professionals in Japan during September and October 2009 is also utilized for this study. Apart from answering the aforementioned research questions, one of this thesis’ aims is to enrich the still rather small field of game localization studies, and the study of Japanese video games in particular, one of Japan’s most successful cultural exports.

Proektirovanie perevodčeskih slovarej special'noj leksiki

The methodology of designing normative terminological products has been described in several guides and international standards. However, this methodology is not always applicable to designing translation-oriented terminological products which differ greatly from normative ones in terms of volume, function, and primary target group. This dissertation has three main goals. The first is to revise and enrich the stock of concepts and terms required in the process of designing an LSP dictionary for translators. The second is to detect, classify, and describe the factors which determine the characteristics of an LSP dictionary for translators and affect the process of its compilation. The third goal is to provide recommendations on different aspects of dictionary design. The study is based on an analysis of dictionaries, dictionary reviews, literature on translation-oriented lexicography, material from several dictionary projects, and the results of questionnaires. Thorough analysis of the concept of a dictionary helped us to compile a list of designable characteristics of a dictionary. These characteristics include target group, function, links to other resources, data carrier, list of lemmata, information about the lemmata, composition of other parts of the dictionary, compression of the data, structure of the data, and access structure. The factors which determine the characteristics of a dictionary have been divided into those derived from the needs of the intended users and those reflecting the restrictions of the real world (e.g. characteristics of the data carrier and organizational factors) and attitudes (e.g. traditions and scientific paradigms). The designer of a dictionary is recommended to take the intended users' needs as the starting point and aim at finding the best compromise between the conflicting factors. When designing an LSP dictionary, much depends on the level of knowledge of the intended users about the domain in question as well as their general linguistic competence, LSP competence, and lexicographic competence. This dissertation discusses the needs of LSP translators and the role of the dictionary in the process of translation of an LSP text. It also emphasizes the importance of planning lexicographic products and activities, and addresses many practical aspects of dictionary design.

Routine Measurement of Health-Related Quality of Life in Assessing Cost-Effectiveness in Secondary Health Care

Aims: The aims of this study were 1) to identify and describe health economic studies that have used quality-adjusted life years (QALYs) based on actual measurements of patients' health-related quality of life (HRQoL); 2) to test the feasibility of routine collection of health-related quality of life (HRQoL) data as an indicator of effectiveness of secondary health care; and 3) to establish and compare the cost-utility of three large-volume surgical procedures in a real-world setting in the Helsinki University Central Hospital, a large referral hospital providing secondary and tertiary health-care services for a population of approximately 1.4 million. Patients and methods: So as to identify studies that have used QALYs as an outcome measure, a systematic search of the literature was performed using the Medline, Embase, CINAHL, SCI and Cochrane Library electronic databases. Initial screening of the identified articles involved two reviewers independently reading the abstracts; the full-text articles were also evaluated independently by two reviewers, with a third reviewer used in cases where the two reviewers could not agree a consensus on which articles should be included. The feasibility of routinely evaluating the cost-effectiveness of secondary health care was tested by setting up a system for collecting HRQoL data on approximately 4 900 patients' HRQoL before and after operative treatments performed in the hospital. The HRQoL data used as an indicator of treatment effectiveness was combined with diagnostic and financial indicators routinely collected in the hospital. To compare the cost-effectiveness of three surgical interventions, 712 patients admitted for routine operative treatment completed the 15D HRQoL questionnaire before and also 3-12 months after the operation. QALYs were calculated using the obtained utility data and expected remaining life years of the patients. Direct hospital costs were obtained from the clinical patient administration database of the hospital and a cost-utility analysis was performed from the perspective of the provider of secondary health care services. Main results: The systematic review (Study I) showed that although QALYs gained are considered an important measure of the effectiveness of health care, the number of studies in which QALYs are based on actual measurements of patients' HRQoL is still fairly limited. Of the reviewed full-text articles, only 70 reported QALYs based on actual before after measurements using a valid HRQoL instrument. Collection of simple cost-effectiveness data in secondary health care is feasible and could easily be expanded and performed on a routine basis (Study II). It allows meaningful comparisons between various treatments and provides a means for allocating limited health care resources. The cost per QALY gained was 2 770 for cervical operations and 1 740 for lumbar operations. In cases where surgery was delayed the cost per QALY was doubled (Study III). The cost per QALY ranges between subgroups in cataract surgery (Study IV). The cost per QALY gained was 5 130 for patients having both eyes operated on and 8 210 for patients with only one eye operated on during the 6-month follow-up. In patients whose first eye had been operated on previous to the study period, the mean HRQoL deteriorated after surgery, thus precluding the establishment of the cost per QALY. In arthroplasty patients (Study V) the mean cost per QALY gained in a one-year period was 6 710 for primary hip replacement, 52 270 for revision hip replacement, and 14 000 for primary knee replacement. Conclusions: Although the importance of cost-utility analyses has during recent years been stressed, there are only a limited number of studies in which the evaluation is based on patients own assessment of the treatment effectiveness. Most of the cost-effectiveness and cost-utility analyses are based on modeling that employs expert opinion regarding the outcome of treatment, not on patient-derived assessments. Routine collection of effectiveness information from patients entering treatment in secondary health care turned out to be easy enough and did not, for instance, require additional personnel on the wards in which the study was executed. The mean patient response rate was more than 70 %, suggesting that patients were happy to participate and appreciated the fact that the hospital showed an interest in their well-being even after the actual treatment episode had ended. Spinal surgery leads to a statistically significant and clinically important improvement in HRQoL. The cost per QALY gained was reasonable, at less than half of that observed for instance for hip replacement surgery. However, prolonged waiting for an operation approximately doubled the cost per QALY gained from the surgical intervention. The mean utility gain following routine cataract surgery in a real world setting was relatively small and confined mostly to patients who had had both eyes operated on. The cost of cataract surgery per QALY gained was higher than previously reported and was associated with considerable degree of uncertainty. Hip and knee replacement both improve HRQoL. The cost per QALY gained from knee replacement is two-fold compared to hip replacement. Cost-utility results from the three studied specialties showed that there is great variation in the cost-utility of surgical interventions performed in a real-world setting even when only common, widely accepted interventions are considered. However, the cost per QALY of all the studied interventions, except for revision hip arthroplasty, was well below 50 000, this figure being sometimes cited in the literature as a threshold level for the cost-effectiveness of an intervention. Based on the present study it may be concluded that routine evaluation of the cost-utility of secondary health care is feasible and produces information essential for a rational and balanced allocation of scarce health care resources.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Semantic Classes in Topic Detection and Tracking

Topic detection and tracking (TDT) is an area of information retrieval research the focus of which revolves around news events. The problems TDT deals with relate to segmenting news text into cohesive stories, detecting something new, previously unreported, tracking the development of a previously reported event, and grouping together news that discuss the same event. The performance of the traditional information retrieval techniques based on full-text similarity has remained inadequate for online production systems. It has been difficult to make the distinction between same and similar events. In this work, we explore ways of representing and comparing news documents in order to detect new events and track their development. First, however, we put forward a conceptual analysis of the notions of topic and event. The purpose is to clarify the terminology and align it with the process of news-making and the tradition of story-telling. Second, we present a framework for document similarity that is based on semantic classes, i.e., groups of words with similar meaning. We adopt people, organizations, and locations as semantic classes in addition to general terms. As each semantic class can be assigned its own similarity measure, document similarity can make use of ontologies, e.g., geographical taxonomies. The documents are compared class-wise, and the outcome is a weighted combination of class-wise similarities. Third, we incorporate temporal information into document similarity. We formalize the natural language temporal expressions occurring in the text, and use them to anchor the rest of the terms onto the time-line. Upon comparing documents for event-based similarity, we look not only at matching terms, but also how near their anchors are on the time-line. Fourth, we experiment with an adaptive variant of the semantic class similarity system. The news reflect changes in the real world, and in order to keep up, the system has to change its behavior based on the contents of the news stream. We put forward two strategies for rebuilding the topic representations and report experiment results. We run experiments with three annotated TDT corpora. The use of semantic classes increased the effectiveness of topic tracking by 10-30\% depending on the experimental setup. The gain in spotting new events remained lower, around 3-4\%. The anchoring the text to a time-line based on the temporal expressions gave a further 10\% increase the effectiveness of topic tracking. The gains in detecting new events, again, remained smaller. The adaptive systems did not improve the tracking results.

Matrix Decomposition Methods for Data Mining : Computational Complexity and Algorithms

Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

Exploring privacy for ubiquitous computing: Tools, methods and experiments

Ubiquitous computing is about making computers and computerized artefacts a pervasive part of our everyday lifes, bringing more and more activities into the realm of information. The computationalization, informationalization of everyday activities increases not only our reach, efficiency and capabilities but also the amount and kinds of data gathered about us and our activities. In this thesis, I explore how information systems can be constructed so that they handle this personal data in a reasonable manner. The thesis provides two kinds of results: on one hand, tools and methods for both the construction as well as the evaluation of ubiquitous and mobile systems---on the other hand an evaluation of the privacy aspects of a ubiquitous social awareness system. The work emphasises real-world experiments as the most important way to study privacy. Additionally, the state of current information systems as regards data protection is studied. The tools and methods in this thesis consist of three distinct contributions. An algorithm for locationing in cellular networks is proposed that does not require the location information to be revealed beyond the user's terminal. A prototyping platform for the creation of context-aware ubiquitous applications called ContextPhone is described and released as open source. Finally, a set of methodological findings for the use of smartphones in social scientific field research is reported. A central contribution of this thesis are the pragmatic tools that allow other researchers to carry out experiments. The evaluation of the ubiquitous social awareness application ContextContacts covers both the usage of the system in general as well as an analysis of privacy implications. The usage of the system is analyzed in the light of how users make inferences of others based on real-time contextual cues mediated by the system, based on several long-term field studies. The analysis of privacy implications draws together the social psychological theory of self-presentation and research in privacy for ubiquitous computing, deriving a set of design guidelines for such systems. The main findings from these studies can be summarized as follows: The fact that ubiquitous computing systems gather more data about users can be used to not only study the use of such systems in an effort to create better systems but in general to study phenomena previously unstudied, such as the dynamic change of social networks. Systems that let people create new ways of presenting themselves to others can be fun for the users---but the self-presentation requires several thoughtful design decisions that allow the manipulation of the image mediated by the system. Finally, the growing amount of computational resources available to the users can be used to allow them to use the data themselves, rather than just being passive subjects of data gathering.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Architectural Solutions for Mobile RFID Services on Internet of Things

Mobile RFID services for the Internet of Things can be created by using RFID as an enabling technology in mobile devices. Humans, devices, and things are the content providers and users of these services. Mobile RFID services can be either provided on mobile devices as stand-alone services or combined with end-to-end systems. When different service solution scenarios are considered, there are more than one possible architectural solution in the network, mobile, and back-end server areas. Combining the solutions wisely by applying the software architecture and engineering principles, a combined solution can be formulated for certain application specific use cases. This thesis illustrates these ideas. It also shows how generally the solutions can be used in real world use case scenarios. A case study is used to add further evidence.

Where and how to conserve: Extending the scope of spatial reserve network design

Ongoing habitat loss and fragmentation threaten much of the biodiversity that we know today. As such, conservation efforts are required if we want to protect biodiversity. Conservation budgets are typically tight, making the cost-effective selection of protected areas difficult. Therefore, reserve design methods have been developed to identify sets of sites, that together represent the species of conservation interest in a cost-effective manner. To be able to select reserve networks, data on species distributions is needed. Such data is often incomplete, but species habitat distribution models (SHDMs) can be used to link the occurrence of the species at the surveyed sites to the environmental conditions at these locations (e.g. climatic, vegetation and soil conditions). The probability of the species occurring at unvisited location is next predicted by the model, based on the environmental conditions of those sites. The spatial configuration of reserve networks is important, because habitat loss around reserves can influence the persistence of species inside the network. Since species differ in their requirements for network configuration, the spatial cohesion of networks needs to be species-specific. A way to account for species-specific requirements is to use spatial variables in SHDMs. Spatial SHDMs allow the evaluation of the effect of reserve network configuration on the probability of occurrence of the species inside the network. Even though reserves are important for conservation, they are not the only option available to conservation planners. To enhance or maintain habitat quality, restoration or maintenance measures are sometimes required. As a result, the number of conservation options per site increases. Currently available reserve selection tools do however not offer the ability to handle multiple, alternative options per site. This thesis extends the existing methodology for reserve design, by offering methods to identify cost-effective conservation planning solutions when multiple, alternative conservation options are available per site. Although restoration and maintenance measures are beneficial to certain species, they can be harmful to other species with different requirements. This introduces trade-offs between species when identifying which conservation action is best applied to which site. The thesis describes how the strength of such trade-offs can be identified, which is useful for assessing consequences of conservation decisions regarding species priorities and budget. Furthermore, the results of the thesis indicate that spatial SHDMs can be successfully used to account for species-specific requirements for spatial cohesion - in the reserve selection (single-option) context as well as in the multi-option context. Accounting for the spatial requirements of multiple species and allowing for several conservation options is however complicated, due to trade-offs in species requirements. It is also shown that spatial SHDMs can be successfully used for gaining information on factors that drive a species spatial distribution. Such information is valuable to conservation planning, as better knowledge on species requirements facilitates the design of networks for species persistence. This methods and results described in this thesis aim to improve species probabilities of persistence, by taking better account of species habitat and spatial requirements. Many real-world conservation planning problems are characterised by a variety of conservation options related to protection, restoration and maintenance of habitat. Planning tools therefore need to be able to incorporate multiple conservation options per site, in order to continue the search for cost-effective conservation planning solutions. Simultaneously, the spatial requirements of species need to be considered. The methods described in this thesis offer a starting point for combining these two relevant aspects of conservation planning.

Appropriate Institutions and Economic Growth - one size fits no-one

Modern-day economics is increasingly biased towards believing that institutions matter for growth, an argument that has been further enforced by the recent economic crisis. There is also a wide consensus on what these growth-promoting institutions should look like, and countries are periodically ranked depending on how their institutional structure compares with the best-practice institutions, mostly in place in the developing world. In this paper, it is argued that ”non-desirable” or “second-best” institutions can be beneficial for fostering investment and thus providing a starting point for sustained growth, and that what matters is the appropriateness of institutions to the economy’s distance to the frontier or current phase of development. Anecdotal evidence from Japan and South-Korea is used as a motivation for studying the subject and a model is presented to describe this phenomenon. In the model, the rigidity or non-rigidity of the institutions is described by entrepreneurial selection. It is assumed that entrepreneurs are the ones taking part in the imitation and innovation of technologies, and that decisions on whether or not their projects are refinanced comes from capitalists. The capitalists in turn have no entrepreneurial skills and act merely as financers of projects. The model has two periods, and two kinds of entrepreneurs: those with high skills and those with low skills. The society’s choice of whether an imitation or innovation – based strategy is chosen is modeled as the trade-off between refinancing a low-skill entrepreneur or investing in the selection of the entrepreneurs resulting in a larger fraction of high-skill entrepreneurs with the ability to innovate but less total investment. Finally, a real-world example from India is presented as an initial attempt to test the theory. The data from the example is not included in this paper. It is noted that the model may be lacking explanatory power due to difficulties in testing the predictions, but that this should not be seen as a reason to disregard the theory – the solution might lie in developing better tools, not better just better theories. The conclusion presented is that institutions do matter. There is no one-size-fits-all-solution when it comes to institutional arrangements in different countries, and developing countries should be given space to develop their own institutional structures that cater to their specific needs.

Models of Dispersal and Diversification

Ecology and evolutionary biology is the study of life on this planet. One of the many methods applied to answering the great diversity of questions regarding the lives and characteristics of individual organisms, is the utilization of mathematical models. Such models are used in a wide variety of ways. Some help us to reason, functioning as aids to, or substitutes for, our own fallible logic, thus making argumentation and thinking clearer. Models which help our reasoning can lead to conceptual clarification; by expressing ideas in algebraic terms, the relationship between different concepts become clearer. Other mathematical models are used to better understand yet more complicated models, or to develop mathematical tools for their analysis. Though helping us to reason and being used as tools in the craftmanship of science, many models do not tell us much about the real biological phenomena we are, at least initially, interested in. The main reason for this is that any mathematical model is a simplification of the real world, reducing the complexity and variety of interactions and idiosynchracies of individual organisms. What such models can tell us, however, both is and has been very valuable throughout the history of ecology and evolution. Minimally, a model simplifying the complex world can tell us that in principle, the patterns produced in a model could also be produced in the real world. We can never know how different a simplified mathematical representation is from the real world, but the similarity models do strive for, gives us confidence that their results could apply. This thesis deals with a variety of different models, used for different purposes. One model deals with how one can measure and analyse invasions; the expanding phase of invasive species. Earlier analyses claims to have shown that such invasions can be a regulated phenomena, that higher invasion speeds at a given point in time will lead to a reduction in speed. Two simple mathematical models show that analysis on this particular measure of invasion speed need not be evidence of regulation. In the context of dispersal evolution, two models acting as proof-of-principle are presented. Parent-offspring conflict emerges when there are different evolutionary optima for adaptive behavior for parents and offspring. We show that the evolution of dispersal distances can entail such a conflict, and that under parental control of dispersal (as, for example, in higher plants) wider dispersal kernels are optimal. We also show that dispersal homeostasis can be optimal; in a setting where dispersal decisions (to leave or stay in a natal patch) are made, strategies that divide their seeds or eggs into fractions that disperse or not, as opposed to randomized for each seed, can prevail. We also present a model of the evolution of bet-hedging strategies; evolutionary adaptations that occur despite their fitness, on average, being lower than a competing strategy. Such strategies can win in the long run because they have a reduced variance in fitness coupled with a reduction in mean fitness, and fitness is of a multiplicative nature across generations, and therefore sensitive to variability. This model is used for conceptual clarification; by developing a population genetical model with uncertain fitness and expressing genotypic variance in fitness as a product between individual level variance and correlations between individuals of a genotype. We arrive at expressions that intuitively reflect two of the main categorizations of bet-hedging strategies; conservative vs diversifying and within- vs between-generation bet hedging. In addition, this model shows that these divisions in fact are false dichotomies.

Inventory Routing - A Strategic Management Accounting Perspective

This dissertation develops a strategic management accounting perspective of inventory routing. The thesis studies the drivers of cost efficiency gains by identifying the role of the underlying cost structure, demand, information sharing, forecasting accuracy, service levels, vehicle fleet, planning horizon and other strategic factors as well as the interaction effects among these factors with respect to performance outcomes. The task is to enhance the knowledge of the strategic situations that favor the implementation of inventory routing systems, understanding cause-and-effect relationships, linkages and gaining a holistic view of the value proposition of inventory routing. The thesis applies an exploratory case study design, which is based on normative quantitative empirical research using optimization, simulation and factor analysis. Data and results are drawn from a real world application to cash supply chains. The first research paper shows that performance gains require a common cost component and cannot be explained by simple linear or affine cost structures. Inventory management and distribution decisions become separable in the absence of a set-dependent cost structure, and neither economies of scope nor coordination problems are present in this case. The second research paper analyzes whether information sharing improves the overall forecasting accuracy. Analysis suggests that the potential for information sharing is limited to coordination of replenishments and that central information do not yield more accurate forecasts based on joint forecasting. The third research paper develops a novel formulation of the stochastic inventory routing model that accounts for minimal service levels and forecasting accuracy. The developed model allows studying the interaction of minimal service levels and forecasting accuracy with the underlying cost structure in inventory routing. Interestingly, results show that the factors minimal service level and forecasting accuracy are not statistically significant, and subsequently not relevant for the strategic decision problem to introduce inventory routing, or in other words, to effectively internalize inventory management and distribution decisions at the supplier. Consequently the main contribution of this thesis is the result that cost benefits of inventory routing are derived from the joint decision model that accounts for the underlying set-dependent cost structure rather than the level of information sharing. This result suggests that the value of information sharing of demand and inventory data is likely to be overstated in prior literature. In other words, cost benefits of inventory routing are primarily determined by the cost structure (i.e. level of fixed costs and transportation costs) rather than the level of information sharing, joint forecasting, forecasting accuracy or service levels.

Patterns in permuted binary matrices

Reorganizing a dataset so that its hidden structure can be observed is useful in any data analysis task. For example, detecting a regularity in a dataset helps us to interpret the data, compress the data, and explain the processes behind the data. We study datasets that come in the form of binary matrices (tables with 0s and 1s). Our goal is to develop automatic methods that bring out certain patterns by permuting the rows and columns. We concentrate on the following patterns in binary matrices: consecutive-ones (C1P), simultaneous consecutive-ones (SC1P), nestedness, k-nestedness, and bandedness. These patterns reflect specific types of interplay and variation between the rows and columns, such as continuity and hierarchies. Furthermore, their combinatorial properties are interlinked, which helps us to develop the theory of binary matrices and efficient algorithms. Indeed, we can detect all these patterns in a binary matrix efficiently, that is, in polynomial time in the size of the matrix. Since real-world datasets often contain noise and errors, we rarely witness perfect patterns. Therefore we also need to assess how far an input matrix is from a pattern: we count the number of flips (from 0s to 1s or vice versa) needed to bring out the perfect pattern in the matrix. Unfortunately, for most patterns it is an NP-complete problem to find the minimum distance to a matrix that has the perfect pattern, which means that the existence of a polynomial-time algorithm is unlikely. To find patterns in datasets with noise, we need methods that are noise-tolerant and work in practical time with large datasets. The theory of binary matrices gives rise to robust heuristics that have good performance with synthetic data and discover easily interpretable structures in real-world datasets: dialectical variation in the spoken Finnish language, division of European locations by the hierarchies found in mammal occurrences, and co-occuring groups in network data. In addition to determining the distance from a dataset to a pattern, we need to determine whether the pattern is significant or a mere occurrence of a random chance. To this end, we use significance testing: we deem a dataset significant if it appears exceptional when compared to datasets generated from a certain null hypothesis. After detecting a significant pattern in a dataset, it is up to domain experts to interpret the results in the terms of the application.

The Enlightenment Idea of History as a Legitimation Tool of Kemalism in Turkey

The study analyzes the effort to build political legitimacy in the Republic of Turkey by ex-ploring a group of influential texts produced by Kemalist writers. The study explores how the Kemalist regime reproduced certain long-lasting enlightenment meta-narrative in its effort to build political legitimacy. Central in this process was a hegemonic representation of history, namely the interpretation of the Anatolian Resistance Struggle of 1919 1922 as a Turkish Revolution executing the enlightenment in the Turkish nation-state. The method employed in the study is contextualizing narratological analysis. The Kemalist texts are analyzed with a repertoire of concepts originally developed in the theory of narra-tive. By bringing these concepts together with epistemological foundations of historical sciences, the study creates a theoretical frame inside of which it is possible to highlight how initially very controversial historical representations in the end manage to construct long-lasting, emotionally and intellectually convincing bases of national identity for the secular middle classes in Turkey. The two most important explanatory concepts in this sense are di-egesis and implied reader. The diegesis refers to the ability of narrative representation to create an inherently credible story-world that works as the basis of national community. The implied reader refers to the process where a certain hegemonic narrative creates a formula of identification and a position through which any individual real-world reader of a story can step inside the narrative story-world and identify oneself as one of us of the national narra-tive. The study demonstrates that the Kemalist enlightenment meta-narrative created a group of narrative accruals which enabled generations of secular middle classes to internalize Kemalist ideology. In this sense, the narrative in question has not only worked as a tool utilized by the so-called Kemalist state-elite to justify its leadership, but has been internalized by various groups in Turkey, working as their genuine world-view. It is shown in the study that secular-ism must be seen as the core ingredient of these groups national identity. The study proposes that the enlightenment narrative reproduced in the Kemalist ideology had its origin in a simi-lar totalizing cultural narrative created in and for Europe. Currently this enlightenment project is challenged in Turkey by those who are in an attempt to give religion a greater role in Turkish society. The study argues that the enduring practice of legitimizing political power through the enlightenment meta-narrative has not only become a major factor contributing to social polarization in Turkey, but has also, in contradiction to the very real potentials for crit-ical approaches inherent in the Enlightenment tradition, crucially restricted the development of critical and rational modes of thinking in the Republic of Turkey.