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Bad governance causes economic, social, developmental and environmental problems in many developing countries. Developing countries have adopted a number of reforms that have assisted in achieving good governance. The success of governance reform depends on the starting point of each country – what institutional arrangements exist at the out-set and who the people implementing reforms within the existing institutional framework are. This dissertation focuses on how formal institutions (laws and regulations) and informal institutions (culture, habit and conception) impact on good governance. Three characteristics central to good governance - transparency, participation and accountability are studied in the research.
A number of key findings were: Good governance in Hanoi and Berlin represent the two extremes of the scale, while governance in Berlin is almost at the top of the scale, governance in Hanoi is at the bottom. Good governance in Hanoi is still far from achieved. In Berlin, information about public policies, administrative services and public finance is available, reliable and understandable. People do not encounter any problems accessing public information. In Hanoi, however, public information is not easy to access. There are big differences between Hanoi and Berlin in the three forms of participation. While voting in Hanoi to elect local deputies is formal and forced, elections in Berlin are fair and free. The candidates in local elections in Berlin come from different parties, whereas the candidacy of local deputies in Hanoi is thoroughly controlled by the Fatherland Front. Even though the turnout of voters in local deputy elections is close to 90 percent in Hanoi, the legitimacy of both the elections and the process of representation is non-existent because the local deputy candidates are decided by the Communist Party.
The involvement of people in solving local problems is encouraged by the government in Berlin. The different initiatives include citizenry budget, citizen activity, citizen initiatives, etc. Individual citizens are free to participate either individually or through an association.
Lacking transparency and participation, the quality of public service in Hanoi is poor. Citizens seldom get their services on time as required by the regulations. Citizens who want to receive public services can bribe officials directly, use the power of relationships, or pay a third person – the mediator ("Cò" - in Vietnamese).
In contrast, public service delivery in Berlin follows the customer-orientated principle. The quality of service is high in relation to time and cost. Paying speed money, bribery and using relationships to gain preferential public service do not exist in Berlin.
Using the examples of Berlin and Hanoi, it is clear to see how transparency, participation and accountability are interconnected and influence each other. Without a free and fair election as well as participation of non-governmental organisations, civil organisations, and the media in political decision-making and public actions, it is hard to hold the Hanoi local government accountable.
The key differences in formal institutions (regulative and cognitive) between Berlin and Hanoi reflect the three main principles: rule of law vs. rule by law, pluralism vs. monopoly Party in politics and social market economy vs. market economy with socialist orientation.
In Berlin the logic of appropriateness and codes of conduct are respect for laws, respect of individual freedom and ideas and awareness of community development. People in Berlin take for granted that public services are delivered to them fairly. Ideas such as using money or relationships to shorten public administrative procedures do not exist in the mind of either public officials or citizens.
In Hanoi, under a weak formal framework of good governance, new values and norms (prosperity, achievement) generated in the economic transition interact with the habits of the centrally-planned economy (lying, dependence, passivity) and traditional values (hierarchy, harmony, family, collectivism) influence behaviours of those involved.
In Hanoi “doing the right thing” such as compliance with law doesn’t become “the way it is”.
The unintended consequence of the deliberate reform actions of the Party is the prevalence of corruption. The socialist orientation seems not to have been achieved as the gap between the rich and the poor has widened.
Good governance is not achievable if citizens and officials are concerned only with their self-interest. State and society depend on each other. Theoretically to achieve good governance in Hanoi, institutions (formal and informal) able to create good citizens, officials and deputies should be generated. Good citizens are good by habit rather than by nature.
The rule of law principle is necessary for the professional performance of local administrations and People’s Councils. When the rule of law is applied consistently, the room for informal institutions to function will be reduced.
Promoting good governance in Hanoi is dependent on the need and desire to change the government and people themselves. Good governance in Berlin can be seen to be the result of the efforts of the local government and citizens after a long period of development and continuous adjustment.
Institutional transformation is always a long and complicated process because the change in formal regulations as well as in the way they are implemented may meet strong resistance from the established practice. This study has attempted to point out the weaknesses of the institutions of Hanoi and has identified factors affecting future development towards good governance. But it is not easy to determine how long it will take to change the institutional setting of Hanoi in order to achieve good governance.
In many applications one is faced with the problem of inferring some functional relation between input and output variables from given data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class spam or non-spam. Building such a predictive model based on observed training inputs (e.g., emails) with corresponding outputs (e.g., spam labels) is a major goal of machine learning. Many learning methods assume that these training data are governed by the same distribution as the test data which the predictive model will be exposed to at application time. That assumption is violated when the test data are generated in response to the presence of a predictive model. This becomes apparent, for instance, in the above example of email spam filtering. Here, email service providers employ spam filters and spam senders engineer campaign templates such as to achieve a high rate of successful deliveries despite any filters. Most of the existing work casts such situations as learning robust models which are unsusceptible against small changes of the data generation process. The models are constructed under the worst-case assumption that these changes are performed such to produce the highest possible adverse effect on the performance of the predictive model. However, this approach is not capable to realistically model the true dependency between the model-building process and the process of generating future data. We therefore establish the concept of prediction games: We model the interaction between a learner, who builds the predictive model, and a data generator, who controls the process of data generation, as an one-shot game. The game-theoretic framework enables us to explicitly model the players' interests, their possible actions, their level of knowledge about each other, and the order at which they decide for an action. We model the players' interests as minimizing their own cost function which both depend on both players' actions. The learner's action is to choose the model parameters and the data generator's action is to perturbate the training data which reflects the modification of the data generation process with respect to the past data. We extensively study three instances of prediction games which differ regarding the order in which the players decide for their action. We first assume that both player choose their actions simultaneously, that is, without the knowledge of their opponent's decision. We identify conditions under which this Nash prediction game has a meaningful solution, that is, a unique Nash equilibrium, and derive algorithms that find the equilibrial prediction model. As a second case, we consider a data generator who is potentially fully informed about the move of the learner. This setting establishes a Stackelberg competition. We derive a relaxed optimization criterion to determine the solution of this game and show that this Stackelberg prediction game generalizes existing prediction models. Finally, we study the setting where the learner observes the data generator's action, that is, the (unlabeled) test data, before building the predictive model. As the test data and the training data may be governed by differing probability distributions, this scenario reduces to learning under covariate shift. We derive a new integrated as well as a two-stage method to account for this data set shift. In case studies on email spam filtering we empirically explore properties of all derived models as well as several existing baseline methods. We show that spam filters resulting from the Nash prediction game as well as the Stackelberg prediction game in the majority of cases outperform other existing baseline methods.
Education in knowledge society is challenged with a lot of problems in particular the interaction between the teacher and learner in social networking software as a key factor affects the learners’ learning and satisfaction (Prammanee, 2005) where “to teach is to communicate, to communicate is to interact, to interact is to learn” (Hefzallah, 2004, p. 48). Analyzing the relation between teacher-learner interaction from a side and learning outcome and learners’ satisfaction from the other side, some basic problems regarding a new learning culture using social networking software are discussed. Most of the educational institutions pay a lot of attentions to the equipments and emerging Information and Communication Technologies (ICTs) in learning situations. They try to incorporate ICT into their institutions as teaching and learning environments. They do this because they expect that by doing so they will improve the outcome of the learning process. Despite this, the learning outcome as reported in most studies is very limited, because the expectations of self-directed learning are much higher than the reality. Findings from an empirical study (investigating the role of teacher-learner interaction through new digital media wiki in higher education and learning outcome and learner’s satisfaction) are presented recommendations about the necessity of pedagogical interactions in support of teaching and learning activities in wiki courses in order to improve the learning outcome. Conclusions show the necessity for significant changes in the approach of vocational teacher training programs of online teachers in order to meet the requirements of new digital media in coherence with a new learning culture. These changes have to address collaborative instead of individual learning and ICT wiki as a tool for knowledge construction instead of a tool for gathering information.
Cargo transport by molecular motors is ubiquitous in all eukaryotic cells and is typically driven cooperatively by several molecular motors, which may belong to one or several motor species like kinesin, dynein or myosin. These motor proteins transport cargos such as RNAs, protein complexes or organelles along filaments, from which they unbind after a finite run length. Understanding how these motors interact and how their movements are coordinated and regulated is a central and challenging problem in studies of intracellular transport. In this thesis, we describe a general theoretical framework for the analysis of such transport processes, which enables us to explain the behavior of intracellular cargos based on the transport properties of individual motors and their interactions. Motivated by recent in vitro experiments, we address two different modes of transport: unidirectional transport by two identical motors and cooperative transport by actively walking and passively diffusing motors. The case of cargo transport by two identical motors involves an elastic coupling between the motors that can reduce the motors’ velocity and/or the binding time to the filament. We show that this elastic coupling leads, in general, to four distinct transport regimes. In addition to a weak coupling regime, kinesin and dynein motors are found to exhibit a strong coupling and an enhanced unbinding regime, whereas myosin motors are predicted to attain a reduced velocity regime. All of these regimes, which we derive both by analytical calculations and by general time scale arguments, can be explored experimentally by varying the elastic coupling strength. In addition, using the time scale arguments, we explain why previous studies came to different conclusions about the effect and relevance of motor-motor interference. In this way, our theory provides a general and unifying framework for understanding the dynamical behavior of two elastically coupled molecular motors. The second mode of transport studied in this thesis is cargo transport by actively pulling and passively diffusing motors. Although these passive motors do not participate in active transport, they strongly enhance the overall cargo run length. When an active motor unbinds, the cargo is still tethered to the filament by the passive motors, giving the unbound motor the chance to rebind and continue its active walk. We develop a stochastic description for such cooperative behavior and explicitly derive the enhanced run length for a cargo transported by one actively pulling and one passively diffusing motor. We generalize our description to the case of several pulling and diffusing motors and find an exponential increase of the run length with the number of involved motors.
One of the most exciting predictions of Einstein's theory of gravitation that have not yet been proven experimentally by a direct detection are gravitational waves. These are tiny distortions of the spacetime itself, and a world-wide effort to directly measure them for the first time with a network of large-scale laser interferometers is currently ongoing and expected to provide positive results within this decade. One potential source of measurable gravitational waves is the inspiral and merger of two compact objects, such as binary black holes. Successfully finding their signature in the noise-dominated data of the detectors crucially relies on accurate predictions of what we are looking for. In this thesis, we present a detailed study of how the most complete waveform templates can be constructed by combining the results from (A) analytical expansions within the post-Newtonian framework and (B) numerical simulations of the full relativistic dynamics. We analyze various strategies to construct complete hybrid waveforms that consist of a post-Newtonian inspiral part matched to numerical-relativity data. We elaborate on exsisting approaches for nonspinning systems by extending the accessible parameter space and introducing an alternative scheme based in the Fourier domain. Our methods can now be readily applied to multiple spherical-harmonic modes and precessing systems. In addition to that, we analyze in detail the accuracy of hybrid waveforms with the goal to quantify how numerous sources of error in the approximation techniques affect the application of such templates in real gravitational-wave searches. This is of major importance for the future construction of improved models, but also for the correct interpretation of gravitational-wave observations that are made utilizing any complete waveform family. In particular, we comprehensively discuss how long the numerical-relativity contribution to the signal has to be in order to make the resulting hybrids accurate enough, and for currently feasible simulation lengths we assess the physics one can potentially do with template-based searches.
The dissertation examines the use of performance information by public managers. “Use” is conceptualized as purposeful utilization in order to steer, learn, and improve public services. The main research question is: Why do public managers use performance information? To answer this question, I systematically review the existing literature, identify research gaps and introduce the approach of my dissertation. The first part deals with manager-related variables that might affect performance information use but which have thus far been disregarded. The second part models performance data use by applying a theory from social psychology which is based on the assumption that this management behavior is conscious and reasoned. The third part examines the extent to which explanations of performance information use vary if we include others sources of “unsystematic” feedback in our analysis. The empirical results are based on survey data from 2011. I surveyed middle managers from eight selected divisions of all German cities with county status (n=954). To analyze the data, I used factor analysis, multiple regression analysis, and structural equation modeling. My research resulted in four major findings: 1) The use of performance information can be modeled as a reasoned behavior which is determined by the attitude of the managers and of their immediate peers. 2) Regular users of performance data surprisingly are not generally inclined to analyze abstract data but rather prefer gathering information through personal interaction. 3) Managers who take on ownership of performance information at an early stage in the measurement process are also more likely to use this data when it is reported to them. 4) Performance reports are only one source of information among many. Public managers prefer verbal feedback from insiders and feedback from external stakeholders over systematic performance reports. The dissertation explains these findings using a deductive approach and discusses their implications for theory and practice.
This thesis contains several theoretical studies on optomechanical systems, i.e. physical devices where mechanical degrees of freedom are coupled with optical cavity modes. This optomechanical interaction, mediated by radiation pressure, can be exploited for cooling and controlling mechanical resonators in a quantum regime. The goal of this thesis is to propose several new ideas for preparing meso- scopic mechanical systems (of the order of 10^15 atoms) into highly non-classical states. In particular we have shown new methods for preparing optomechani-cal pure states, squeezed states and entangled states. At the same time, proce-dures for experimentally detecting these quantum effects have been proposed. In particular, a quantitative measure of non classicality has been defined in terms of the negativity of phase space quasi-distributions. An operational al- gorithm for experimentally estimating the non-classicality of quantum states has been proposed and successfully applied in a quantum optics experiment. The research has been performed with relatively advanced mathematical tools related to differential equations with periodic coefficients, classical and quantum Bochner’s theorems and semidefinite programming. Nevertheless the physics of the problems and the experimental feasibility of the results have been the main priorities.