Refine
Year of publication
Document Type
- Article (22)
- Postprint (12)
- Doctoral Thesis (5)
- Part of a Book (1)
- Master's Thesis (1)
- Other (1)
Is part of the Bibliography
- yes (42) (remove)
Keywords
- performance (42) (remove)
Institute
- Strukturbereich Kognitionswissenschaften (10)
- Department Sport- und Gesundheitswissenschaften (7)
- Humanwissenschaftliche Fakultät (5)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (4)
- Fachgruppe Betriebswirtschaftslehre (3)
- Wirtschaftswissenschaften (3)
- Department Psychologie (2)
- Institut für Biochemie und Biologie (2)
- Department Musik und Kunst (1)
- Department für Inklusionspädagogik (1)
In this cartography, I examine M.K. Gandhi’s practice of fasting for political purposes from a specifically aesthetic perspective. In other words, to foreground their dramatic qualities, how they in their expressive repetition, patterning and stylization produced a/effected heightened forms of emotions. To carry out this task, I follow the theater scholar Erika Fischer-Lichte’s features that give name to her book Äesthetik des Performativen (2004). The cartography is framed in a philosophical presentation of Gandhi’s discourse as well as of his historical sources. Moreover, as a second frame, I historicize the fasts, by means of a typology and teleology in context.
The historically and discoursively framed cartography maps four main dimensions that define the aesthetics of the performative: mediality, materiality, semioticity and aestheticity. The first part analyses the medial platforms in which the fasts as events have been historically recorded and in which they have left their traces and inscriptions. These historical sources are namely, newspapers, images, newsreels and a documentary film. Secondly, the material dimension depicts Gandhi’s corporeal condition, as well as the spatiality and temporality of the fasts. In the third place, I revise and reformulate critically Fischer-Lichte’s concepts of “presence” and “representation” with resonating concepts of G. C. Spivak and J. Rancière. This revision illustrates Gandhi’s fasts and shows the process of how an individual may become the embodiment or representation of a national body-politic. The last chapter of the cartography explores the autopoetic-feedback loop between Gandhi and the people and finishes with a comparison of the mise en scène of the hunger artists with the fasts of the Indian the politician, social reformer, and theologian. The text concludes interpreting Gandhi’s practice of fasting under the light of the concepts of “intellectual emancipation” and “de-subjectivation” of the philosopher J. Rancière.
The four main concerns of this cartography are: Firstly, in the field of Gandhi’s reception, to explore the aesthetic dimension as both alternative and complementary to the two hegemonic interpretative lenses, i.e. a hagiographic or a secular political understanding of the fasts. From a theoretical perspective, the cartography pursues to be a transdisciplinary experiment that aims at deploying concepts that have been traditionally developed, derived from and used in the field of the arts (theater, film, literature, aesthetic performance, etc.) in the field of the political. In brief, inverting an expression of Rancière, to understand politics as aesthetics. Thirdly, from a thematic point of view, the cartography inquires the historical forms of staging and perception of hunger. Last yet importantly, it is an inquiry of the practice of fasting as nonviolence, what Gandhi, its most sophisticated modern theoretician and practitioner considered its most radical expression.
Evaluating the performance of self-adaptive systems is challenging due to their interactions with often highly dynamic environments. In the specific case of self-healing systems, the performance evaluations of self-healing approaches and their parameter tuning rely on the considered characteristics of failure occurrences and the resulting interactions with the self-healing actions. In this paper, we first study the state-of-the-art for evaluating the performances of self-healing systems by means of a systematic literature review. We provide a classification of different input types for such systems and analyse the limitations of each input type. A main finding is that the employed inputs are often not sophisticated regarding the considered characteristics for failure occurrences. To further study the impact of the identified limitations, we present experiments demonstrating that wrong assumptions regarding the characteristics of the failure occurrences can result in large performance prediction errors, disadvantageous design-time decisions concerning the selection of alternative self-healing approaches, and disadvantageous deployment-time decisions concerning parameter tuning. Furthermore, the experiments indicate that employing multiple alternative input characteristics can help with reducing the risk of premature disadvantageous design-time decisions.
Evaluating the performance of self-adaptive systems (SAS) is challenging due to their complexity and interaction with the often highly dynamic environment. In the context of self-healing systems (SHS), employing simulators has been shown to be the most dominant means for performance evaluation. Simulating a SHS also requires realistic fault injection scenarios. We study the state of the practice for evaluating the performance of SHS by means of a systematic literature review. We present the current practice and point out that a more thorough and careful treatment in evaluating the performance of SHS is required.
Improving scalability and reward of utility-driven self-healing for large dynamic architectures
(2020)
Self-adaptation can be realized in various ways. Rule-based approaches prescribe the adaptation to be executed if the system or environment satisfies certain conditions. They result in scalable solutions but often with merely satisfying adaptation decisions. In contrast, utility-driven approaches determine optimal decisions by using an often costly optimization, which typically does not scale for large problems. We propose a rule-based and utility-driven adaptation scheme that achieves the benefits of both directions such that the adaptation decisions are optimal, whereas the computation scales by avoiding an expensive optimization. We use this adaptation scheme for architecture-based self-healing of large software systems. For this purpose, we define the utility for large dynamic architectures of such systems based on patterns that define issues the self-healing must address. Moreover, we use pattern-based adaptation rules to resolve these issues. Using a pattern-based scheme to define the utility and adaptation rules allows us to compute the impact of each rule application on the overall utility and to realize an incremental and efficient utility-driven self-healing. In addition to formally analyzing the computational effort and optimality of the proposed scheme, we thoroughly demonstrate its scalability and optimality in terms of reward in comparative experiments with a static rule-based approach as a baseline and a utility-driven approach using a constraint solver. These experiments are based on different failure profiles derived from real-world failure logs. We also investigate the impact of different failure profile characteristics on the scalability and reward to evaluate the robustness of the different approaches.
Data stream processing systems (DSPSs) are a key enabler to integrate continuously generated data, such as sensor measurements, into enterprise applications. DSPSs allow to steadily analyze information from data streams, e.g., to monitor manufacturing processes and enable fast reactions to anomalous behavior. Moreover, DSPSs continuously filter, sample, and aggregate incoming streams of data, which reduces the data size, and thus data storage costs.
The growing volumes of generated data have increased the demand for high-performance DSPSs, leading to a higher interest in these systems and to the development of new DSPSs. While having more DSPSs is favorable for users as it allows choosing the system that satisfies their requirements the most, it also introduces the challenge of identifying the most suitable DSPS regarding current needs as well as future demands. Having a solution to this challenge is important because replacements of DSPSs require the costly re-writing of applications if no abstraction layer is used for application development. However, quantifying performance differences between DSPSs is a difficult task. Existing benchmarks fail to integrate all core functionalities of DSPSs and lack tool support, which hinders objective result comparisons. Moreover, no current benchmark covers the combination of streaming data with existing structured business data, which is particularly relevant for companies.
This thesis proposes a performance benchmark for enterprise stream processing called ESPBench. With enterprise stream processing, we refer to the combination of streaming and structured business data. Our benchmark design represents real-world scenarios and allows for an objective result comparison as well as scaling of data. The defined benchmark query set covers all core functionalities of DSPSs. The benchmark toolkit automates the entire benchmark process and provides important features, such as query result validation and a configurable data ingestion rate.
To validate ESPBench and to ease the use of the benchmark, we propose an example implementation of the ESPBench queries leveraging the Apache Beam software development kit (SDK). The Apache Beam SDK is an abstraction layer designed for developing stream processing applications that is applied in academia as well as enterprise contexts. It allows to run the defined applications on any of the supported DSPSs. The performance impact of Apache Beam is studied in this dissertation as well. The results show that there is a significant influence that differs among DSPSs and stream processing applications. For validating ESPBench, we use the example implementation of the ESPBench queries developed using the Apache Beam SDK. We benchmark the implemented queries executed on three modern DSPSs: Apache Flink, Apache Spark Streaming, and Hazelcast Jet. The results of the study prove the functioning of ESPBench and its toolkit. ESPBench is capable of quantifying performance characteristics of DSPSs and of unveiling differences among systems.
The benchmark proposed in this thesis covers all requirements to be applied in enterprise stream processing settings, and thus represents an improvement over the current state-of-the-art.
The objective of this study was to investigate the effect of dietary citric acid (CA) on the performance and mineral metabolism of broiler chicks. A total of 1720 Ross PM3 broiler chicks (days old) were randomly assigned to four groups (430 in each) and reared for a period of 35 days. The diets of groups 1, 2, 3 and 4 were supplemented with 0%, 0.25%, 0.75% or 1.25% CA by weight respectively. Feed and faeces samples were collected weekly and analysed for acid insoluble ash, calcium (Ca), phosphorus (P) and magnesium (Mg). The pH was measured in feed and faeces. At the age of 28 days, 10 birds from each group were slaughtered; tibiae were collected from each bird for the determination of bone mineral density, total ash, Ca, P, Mg and bone-breaking strength, and blood was collected for the measurement of osteocalcin, serum CrossLaps (R), Ca, P, Mg and 1,25(OH)(2)Vit-D in serum. After finishing the trial on day 37, all chicks were slaughtered by using the approved procedure. Birds that were fed CA diets were heavier (average body weights of 2030, 2079 and 2086 g in the 0.25%, 0.75% and 1.25% CA groups, respectively, relative to the control birds (1986 g). Feed conversion efficiency (weight gain in g per kg of feed intake) was also higher in birds of the CA-fed groups (582, 595 and 587 g/kg feed intake for 0.25%, 0.75% and 1.25% CA respectively), relative to the control birds (565 g/kg feed intake). The digestibility of Ca, P and Mg increased in the CA-fed groups, especially for the diets supplemented with 0.25% and 0.75% CA. Support for finding was also indicated in the results of the analysis of the tibia. At slaughter, the birds had higher carcass weights and higher graded carcasses in the groups that were fed the CA diets. The estimated profit margin was highest for birds fed the diet containing 0.25% CA. Birds of the 0.75% CA group were found to have the second highest estimated profit margin. Addition of CA up to a level of 1.25% of the diet increased performance, feed conversion efficiency, carcass weight and carcass quality, but only in numerical terms. The addition of CA up to 0.75% significantly increased the digestibility of macro minerals, bone ash content, bone mineral density and bone strength of the broiler chicks. It may, therefore, be concluded that the addition of 0.75% CA in a standard diet is suitable for growth, carcass traits, macromineral digestibility and bone mineral density of broiler chicks.
Findings in the extant literature are mixed concerning when and how gender diversity benefits team performance. We develop and test a model that posits that gender-diverse teams outperform gender-homogeneous teams when perceived time pressure is low, whereas the opposite is the case when perceived time pressure is high. Drawing on the categorization-elaboration model (CEM; van Knippenberg, De Dreu, & Homan, 2004), we begin with the assumption that information elaboration is the process whereby gender diversity fosters positive effects on team performance. However, also in line with the CEM, we argue that this process can be disrupted by adverse team dynamics. Specifically, we argue that as time pressure increases, higher gender diversity leads to more team withdrawal, which, in turn, moderates the positive indirect effect of gender diversity on team performance via information elaboration such that this effect becomes weaker as team withdrawal increases. In an experimental study of 142 four-person teams, we found support for this model that explains why perceived time pressure affects the performance of gender-diverse teams more negatively than that of gender-homogeneous teams. Our study sheds new light on when and how gender diversity can become either an asset or a liability for team performance.
Findings in the extant literature are mixed concerning when and how gender diversity benefits team performance. We develop and test a model that posits that gender-diverse teams outperform gender-homogeneous teams when perceived time pressure is low, whereas the opposite is the case when perceived time pressure is high. Drawing on the categorization-elaboration model (CEM; van Knippenberg, De Dreu, & Homan, 2004), we begin with the assumption that information elaboration is the process whereby gender diversity fosters positive effects on team performance. However, also in line with the CEM, we argue that this process can be disrupted by adverse team dynamics. Specifically, we argue that as time pressure increases, higher gender diversity leads to more team withdrawal, which, in turn, moderates the positive indirect effect of gender diversity on team performance via information elaboration such that this effect becomes weaker as team withdrawal increases. In an experimental study of 142 four-person teams, we found support for this model that explains why perceived time pressure affects the performance of gender-diverse teams more negatively than that of gender-homogeneous teams. Our study sheds new light on when and how gender diversity can become either an asset or a liability for team performance.
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.
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km x 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.