University, Diss., 2005--Kassel.

Zugl.: Kassel, Univ., Diss., 2005 / Download lizenzpflichtig

Universiẗat, Diss., 2005--Kassel. / Download lizenzpflichtig.

Techn. Universiẗat, Diss., 2005--Chemnitz.

Diss. Univ. Zürich, 2007. / Diss. phil. I Zürich, 2007. Im Buchh.: Konstanz : UVK-Verlagsgemeinschaft. Register. Literatur: S. 279-294. Index.

We explore the political acceptance of taxation in commodity markets. Participants in our experiment earn incomes by trading and must collectively choose one of two tax regimes to raise a given tax revenue. A "uniform tax" (UT) imposes the same tax rate on all markets and is fair in that it yields the same - but low - income to participants in all markets. The "discriminatory tax" (DT) imposes a higher burden on markets with inelastic demand and is therefore efficient but it is also unfair in that incomes are unequal across markets. We find that DT are unpopular, as predicted. Surprisingly, however, DT remain unpopular when they are both efficient and produce a fair (equal) distribution. We conclude that non-discrimination (equal treatment) is a salient fairness principle in taxation that shapes voting on commodity taxes above and beyond concerns for efficiency and equal distribution. (authors' abstract) / Series: WU International Taxation Research Paper Series

As databases accumulate growing amounts of data at an increasing rate, adaptive indexing becomes more and more important. At the same time, applications and their use get more agile and flexible, resulting in less steady and less predictable workload characteristics. Being inert and coarse-grained, state-of-the-art index tuning techniques become less useful in such environments. Especially the full-column indexing paradigm results in lot of indexed but never queried data and prohibitively high memory and maintenance costs. In our demonstration, we present Self-Managing Indexes, a novel, adaptive, fine-grained, autonomous indexing infrastructure. In its core, our approach builds on a novel access path that automatically collects useful index information, discards useless index information, and competes with its kind for resources to host its index information. Compared to existing technologies for adaptive indexing, we are able to dynamically grow and shrink our indexes, instead of incrementally enhancing the index granularity. In the demonstration, we visualize performance and system measures for different scenarios and allow the user to interactively change several system parameters.

Wie beheimatet sich Menschen in einer Stadt fühlen, hängt davon ab, wie politisch eingebunden sie sich begreifen. Die Entstehung von Mitbestimmungsformen in Chemnitz verlief – wie in vielen anderen Städten – nicht reibungslos. Auch die Inhalte variierten über die Jahrhunderte: Wollten die Bürger bis zum Ende der mittelalterlichen Stadtverfassung Anfang des 19. Jahrhunderts vor allem über die Besteuerung, die Gerichtsbarkeit und elementare Sicherheitsfragen mitbestimmen, ging es bis 1919 um die Durchsetzung des allgemeinen Wahlrechts, das Frauen einschloss, um sozialen Ausgleich und die großen Infrastrukturprojekte der Gründerzeit. Nach Rückschritten in der Zeit des Nationalsozialismus und der DDR bekam Chemnitz mit der Gemeindeordnung Sachsens von 1994 eine freiheitliche Kommunalverfassung, die auch Raum für weitere Neuerungen lässt – wie etwa Einwohnerversammlungen in den Stadtvierteln. Zwischen mehr Mitbestimmung und effizienten Entscheidungen entsteht dabei ein gewisser Gegensatz. Dieses Bändchen bringt die Hintergründe einer aktuellen Debatte auf den Tisch. / Forms and content of political participation in Chemnitz

Optimization is omnipresent in our world. Its numerous applications spread from industrial cases, such as logistics, construction management or production planning; to the private sphere, filled with problems of selecting daycare or vacation planning. In this thesis, we concentrate on expensive black-box optimization (EBBO) problems, a subset of optimization problems (OPs), which are characterized by an expensive cost of evaluating an objective function. Such OPs are reoccurring in various domains, being known as: hyperpameter optimization in machine learning, performance configuration optimization or parameter tuning in search-based software engineering, simulation optimization in operations research, meta-optimization or parameter tuning in the optimization domain itself. High diversity of domains introduces a plethora of solving approaches, which adhere to a similar structure and workflow, but differ in details. The software frameworks stemming from different areas possess only partially intersecting manageability points, i.e., lack manageability. In this thesis, we argue that the lack of manageability in EBBO is a major problem, which leads to underachieving optimization quality. The goal of this thesis is to study the role of manageability in EBBO and to investigate whether improving the manageability of EBBO frameworks increases optimization quality. To reach this goal, we appeal to software product line engineering (SPLE), a methodology for developing highly-manageable software systems. Based on the foundations of SPLE, we introduce a novel framework for EBBO called BRISE. It offers: 1) a loosely-coupled software architecture, separating concerns of the experiment designer and the developer of EBBO strategies; 2) a full coverage of all EBBO problem types; and 3) a context-aware variability model, which captures the experiment-designer-defined OP with the content model; and manageability points including their variants and constraints with the cardinality-based feature model. High manageability of the introduced BRISE framework enables us: 1) to extend the framework with novel efficient strategies, such as adaptive repetition management; and 2) to introduce novel EBBO mechanisms, such as multi-objective compositional surrogate modeling, dynamic sampling and hierarchical surrogate modeling. The evaluation of the novel approaches with a set of case studies, including: the WFG benchmark for multi-objective optimization, combined selection and parameter control of meta-heuristics, and energy optimization; demonstrated their superiority over the state-of-the-art competitors. Thus, it supports the research hypothesis of this thesis: Improving manageability of an EBBO framework enables to increase optimization quality.

Univ., Diss.--Saarbrücken, 2003.