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Wikipedia is the biggest, free online encyclopaedia that can be expanded by any-one. For the users, who create content on a specific Wikipedia language edition, a social network exists. In this social network users are categorised into different roles. These are normal users, administrators and functional bots. Within the networks, a user can post reviews, suggestions or send simple messages to the "talk page" of another user. Each language in the Wikipedia domain has this type of social network.
In this thesis characteristics of the three different roles are analysed in order to learn how they function in one language network of Wikipedia and apply them to another Wikipedia network to identify bots. Timestamps from created posts are analysed to reveal noticeable characteristics referring to continuous messages, message rates and irregular behaviour of a user are discovered. Through this process we show that there exist differences between the roles for the mentioned characteristics.
The present thesis gives an overview of the general conditions for the programming of graphics cards. For this purpose, the most important Application Programming Interfaces (APIs) available on the market are presented and compared. Subsequently, two standard algorithms from the field data processing, prefix sum and radixsort are presented and examined with regard to the implementation with parallel programming on the GPU. Both algorithms were implemented using the OpenGL-API and OpenGL compute shaders. Finally, the execution times of the two algorithms were compared.
The purpose of this thesis is to explore the sentiment distributions of Wikipedia concepts.
We analyse the sentiment of the entire English Wikipedia corpus, which includes 5,669,867 articles and 1,906,375 talks, by using a lexicon-based method with four different lexicons.
Also, we explore the sentiment distributions from a time perspective using the sentiment scores obtained from our selected corpus. The results obtained have been compared not only between articles and talks but also among four lexicons: OL, MPQA, LIWC, and ANEW.
Our findings show that among the four lexicons, MPQA has the highest sensitivity and ANEW has the lowest sensitivity to emotional expressions. Wikipedia articles show more sentiments than talks according to OL, MPQA, and LIWC, whereas Wikipedia talks show more sentiments than articles according to ANEW. Besides, the sentiment has a trend regarding time series, and each lexicon has its own bias regarding text describing different things.
Moreover, our research provides three interactive widgets for visualising sentiment distributions for Wikipedia concepts regarding the time and geolocation attributes of concepts.
This thesis addresses the automated identification and localization of a time-varying number of objects in a stream of sensor data. The problem is challenging due to its combinatorial nature: If the number of objects is unknown, the number of possible object trajectories grows exponentially with the number of observations. Random finite sets are a relatively new theory that has been developed to derive at principled and efficient approximations. It is based around set-valued random variables that contain an unknown number of elements which appear in arbitrary order and are themselves random. While extensively studied in theory, random finite sets have not yet become a leading paradigm in practical computer vision and robotics applications. This thesis explores random finite sets in visual tracking applications. The first method developed in this thesis combines set-valued recursive filtering with global optimization. The problem is approached in a min-cost flow network formulation, which has become a standard inference framework for multiple object tracking due to its efficiency and optimality. A main limitation of this formulation is a restriction to unary and pairwise cost terms. This circumstance makes integration of higher-order motion models challenging. The method developed in this thesis approaches this limitation by application of a Probability Hypothesis Density filter. The Probability Hypothesis Density filter was the first practically implemented state estimator based on random finite sets. It circumvents the combinatorial nature of data association itself by propagation of an object density measure that can be computed efficiently, without maintaining explicit trajectory hypotheses. In this work, the filter recursion is used to augment measurements with an additional hidden kinematic state to be used for construction of more informed flow network cost terms, e.g., based on linear motion models. The method is evaluated on public benchmarks where a considerate improvement is achieved compared to network flow formulations that are based on static features alone, such as distance between detections and appearance similarity. A second part of this thesis focuses on the related task of detecting and tracking a single robot operator in crowded environments. Different from the conventional multiple object tracking scenario, the tracked individual can leave the scene and later reappear after a longer period of absence. Therefore, a re-identification component is required that picks up the track on reentrance. Based on random finite sets, the Bernoulli filter is an optimal Bayes filter that provides a natural representation for this type of problem. In this work, it is shown how the Bernoulli filter can be combined with a Probability Hypothesis Density filter to track operator and non-operators simultaneously. The method is evaluated on a publicly available multiple object tracking dataset as well as on custom sequences that are specific to the targeted application. Experiments show reliable tracking in crowded scenes and robust re-identification after long term occlusion. Finally, a third part of this thesis focuses on appearance modeling as an essential aspect of any method that is applied to visual object tracking scenarios. Therefore, a feature representation that is robust to pose variations and changing lighting conditions is learned offline, before the actual tracking application. This thesis proposes a joint classification and metric learning objective where a deep convolutional neural network is trained to identify the individuals in the training set. At test time, the final classification layer can be stripped from the network and appearance similarity can be queried using cosine distance in representation space. This framework represents an alternative to direct metric learning objectives that have required sophisticated pair or triplet sampling strategies in the past. The method is evaluated on two large scale person re-identification datasets where competitive results are achieved overall. In particular, the proposed method better generalizes to the test set compared to a network trained with the well-established triplet loss.
In dieser Arbeit wird ein System zur Erzeugung und Darstellung stereoskopischen Video-Panoramen vorgestellt. Neben der theoretischen Grundlagen werden der Aufbau und die Funktionsweise dieses Systems erläutert.
Dazu werden spezielle Kameras verwendet, die Panoramen aufnehmen
können und zur Wiedergabe synchronisiert werden. Anschließend wird ein Renderer implementiert, welcher die Panoramen mithilfe einer VirtualReality Brille stereoskopisch darstellen kann. Dafür werden separate Aufnahmen für die beiden Augen gemacht und getrennt wiedergegeben. Zum Abschluss wird das entstandene Video-Panorama mit einem Panorama eines schon bestehenden Systems verglichen.
The Internet of Things (IoT) is a concept in which connected physical objects are integrated into the virtual world to become active partakers of businesses and everyday processes (Uckelmann, Harrison and Michahelles, 2011; Shrouf, Ordieres and Miragliotta, 2014). It is expected to have a major impact on businesses (Council, Nic and Intelligence, 2008), but small and medium enterprises’ business models are threatened if they do not adopt the new concept (Sommer, 2015). Thus, this thesis aims to showcase a sample implementation of connected devices in a small enterprise, demonstrating its added benefits for the business.
Design Science Research (DSR) is used to develop a prototype based on a use case provided by a carpentry. The prototype comprises a hardware sensor and a web application which can be used by the wood shop to improve their processes. The thesis documents the iterative process of developing a prototype from the grounds up to useable hard- and software.
This contribution provides an example of how IoT can be used and implemented at a small business.
Mit der Microsoft Kinect waren die ersten Aufnahmen von synchronisierten Farb- und Tiefendaten (RGB-D) möglich, ohne hohe finanzielle Mittel aufwenden zu müssen und neue Möglichkeiten der Forschung eröffneten sich. Mit fortschreitender Technik sind auch mobile Endgeräte in der Lage, immer mehr zu leisten. Lenovo und Asus bieten die ersten kommerziell erwerblichen Geräte mit RGB D-Wahrnehmung an. Mit integrierten Funktionen der Lokalisierung, Umgebungserkennung und Tiefenwahrnehmung durch die Plattform Tango von Google gibt es bereits die ersten Tests in verschiedenen Bereichen des Rechnersehens z.B. Mapping. In dieser Arbeit wird betrachtet, inwiefern sich ein Tango Gerät für die Objekterkennung eignet. Aus den Ausgangsdaten des Tango Geräts werden RGB D-Daten extrahiert und für die Objekterkennung verarbeitet. Es wird ein Überblick über den aktuellen Stand der Forschung und gewisse Grundlagen bezüglich der Tango Plattform gegeben. Dabei werden existierende Ansätze und Methoden für eine Objekterkennung auf mobilen Endgeräten untersucht. Die Implementation der Erkennung wird anhand einer selbst erstellten Datenbank von RGB-D Bildern gelernt und getestet. Neben der Vorstellung der Ergebnisse werden Verbesserungen und Erweiterungen für die Erkennung vorgeschlagen.
Digitalisation and further media development are core processes of the current digital age. In order for companies to benefit from technical progress, their employees must have or are expected to acquire the relevant skills. Companies therefore are faced with the task of not being overwhelmed with the mass of innovations and opportunities and, in the best-case scenario, of being able to use them to improve their own performance.
Small and medium-sized enterprises represent 99% of all enterprises in Germany. Though, it has not been further established, how the majority of small enterprises and their employees participate in this development. The research question therefore consists of two parts. On the one hand: "Is the promotion of employees' skills taken care of in micro-enterprises?" and on the other hand: "Where are the opportunities and challenges for companies of this size?”
In order to answer the research question, a qualitative research method was used, the guideline-based interview. The interviewed companies were all in the media and IT sector. Thus, the recorded and transcribed data provided a real insight into the current situation in micro-enterprises.
The responses to the interviews showed that companies with very small numbers of employees are more dependent on their employees than others. So, the commitment of the employees is decisive for the success of the company itself. It is the management's task to promote this and ensure employee satisfaction.
Companies that pay more attention to employee development are therefore more recommendable for career starters who need and/or want to develop themselves and their entire horizon of experience.
This Master Thesis is an exploratory research to determine whether it is feasible to construct a subjectivity lexicon using Wikipedia. The key hypothesis is that that all quotes in Wikipedia are subjective and all regular text are objective. The degree of subjectivity of a word, also known as ''Quote Score'' is determined based on the ratio of word frequency in quotations to its frequency outside quotations. The proportion of words in the English Wikipedia which are within quotations is found to be much smaller as compared to those which are not in quotes, resulting in a right-skewed distribution and low mean value of Quote Scores.
The methodology used to generate the subjectivity lexicon from text corpus in English Wikipedia is designed in such a way that it can be scaled and reused to produce similar subjectivity lexica of other languages. This is achieved by abstaining from domain and language-specific methods, apart from using only readily-available English dictionary packages to detect and exclude stopwords and non-English words in the Wikipedia text corpus.
The subjectivity lexicon generated from English Wikipedia is compared against other lexica; namely MPQA and SentiWordNet. It is found that words which are strongly subjective tend to have high Quote Scores in the subjectivity lexicon generated from English Wikipedia. There is a large observable difference between distribution of Quote Scores for words classified as strongly subjective versus distribution of Quote Scores for words classified as weakly subjective and objective. However, weakly subjective and objective words cannot be differentiated clearly based on Quote Score. In addition to that, a questionnaire is commissioned as an exploratory approach to investigate whether subjectivity lexicon generated from Wikipedia could be used to extend the coverage of words of existing lexica.
Fresh water resources like rivers and reservoirs are exposed to a drastically changing world. In order to safeguard these lentic ecosystems, they need stronger protection in times of global change and population growth. In the last years, the exploitation pressure on drinking water reservoirs has increased steadily worldwide. Besides securing the demands of safe drinking water supply, international laws especially in Europe (EU Water Framework Directive) stipulate to minimize the impact of dams on downstream rivers. In this study we investigate the potential of a smart withdrawal strategy at Grosse Dhuenn Reservoir to improve the temperature and discharge regime downstream without jeopardizing drinking water production. Our aim is to improve the existing withdrawal strategy for operating the reservoir in a sustainable way in terms of water quality and quantity. First, we set-up and calibrated a 1D numerical model for Grosse Dhuenn Reservoir with the open-source community model “General Lake Model” (GLM) together with its water quality module “Aquatic Ecodynamics” library (AED2). The reservoir model reproduced water temperatures and hypolimnetic dissolved oxygen concentrations accurately over a 5 year period. Second, we extended the model source code with a selective withdrawal functionality (adaptive offtake) and added operational rules for a realistic reservoir management. Now the model is able to autonomously determine the best withdrawal height according to the temperature and flow requirements of the downstream river and the raw water quality objectives. Criteria for the determination of the withdrawal regime are selective withdrawal, development of stratification and oxygen content in the deep hypolimnion. This functionality is not available in current reservoir models, where withdrawal heights are generally provided a priori to the model and kept fixed during the simulation. Third, we ran scenario simulations identifying an improved reservoir withdrawal strategy to balance the demands for downstream river and raw water supply. Therefore we aimed at finding an optimal parallel withdrawal ratio between cold hypolimnetic water and warm epilimnetic or metalimnetic water in order to provide a pre-defined temperature in the downstream river. The reservoir model and the proposed withdrawal strategy provide a simple and efficient tool to optimize reservoir management in a multi-objective view for mastering future reservoir management challenges.
Retrospektive Analyse der Ausbreitung und dynamische Erkennung von Web-Tracking durch Sandboxing
(2018)
Aktuelle quantitative Analysen von Web-Tracking bieten keinen umfassenden Überblick über dessen Entstehung, Ausbreitung und Entwicklung. Diese Arbeit ermöglicht durch Auswertung archivierter Webseiten eine rückblickende Erfassung der Entstehungsgeschichte des Web-Trackings zwischen den Jahren 2000 und 2015. Zu diesem Zweck wurde ein geeignetes Werkzeug entworfen, implementiert, evaluiert und zur Analyse von 10000 Webseiten eingesetzt. Während im Jahr 2005 durchschnittlich 1,17 Ressourcen von Drittparteien eingebettet wurden, zeigt sich ein Anstieg auf 6,61 in den darauffolgenden 10 Jahren. Netzwerkdiagramme visualisieren den Trend zu einer monopolisierten Netzstruktur, in der bereits ein einzelnes Unternehmen 80 % der Internetnutzung überwachen kann.
Trotz vielfältiger Versuche, dieser Entwicklung durch technische Maßnahmen entgegenzuwirken, erweisen sich nur wenige Selbst- und Systemschutzmaßnahmen als wirkungsvoll. Diese gehen häufig mit einem Verlust der Funktionsfähigkeit einer Webseite oder mit einer Einschränkung der Nutzbarkeit des Browsers einher. Mit der vorgestellten Studie wird belegt, dass rechtliche Vorschriften ebenfalls keinen hinreichenden Schutz bieten. An Webauftritten von Bildungseinrichtungen werden Mängel bei Erfüllung der datenschutzrechtlichen Pflichten festgestellt. Diese zeigen sich durch fehlende, fehlerhafte oder unvollständige Datenschutzerklärungen, deren Bereitstellung zu den Informationspflichten eines Diensteanbieters gehören.
Die alleinige Berücksichtigung klassischer Tracker ist nicht ausreichend, wie mit einer weiteren Studie nachgewiesen wird. Durch die offene Bereitstellung funktionaler Webseitenbestandteile kann ein Tracking-Unternehmen die Abdeckung von 38 % auf 61 % erhöhen. Diese Situation wird durch Messungen von Webseiten aus dem Gesundheitswesen belegt und aus technischer sowie rechtlicher Perspektive bewertet.
Bestehende systemische Werkzeuge zum Erfassen von Web-Tracking verwenden für ihre Messung die Schnittstellen der Browser. In der vorliegenden Arbeit wird mit DisTrack ein Framework zur Web-Tracking-Analyse vorgestellt, welches eine Sandbox-basierte Messmethodik verfolgt. Dies ist eine Vorgehensweise, die in der dynamischen Schadsoftwareanalyse erfolgreich eingesetzt wird und sich auf das Erkennen von Seiteneffekten auf das umliegende System spezialisiert. Durch diese Verhaltensanalyse, die unabhängig von den Schnittstellen des Browsers operiert, wird eine ganzheitliche Untersuchung des Browsers ermöglicht. Auf diese Weise können systemische Schwachstellen im Browser aufgezeigt werden, die für speicherbasierte Web-Tracking-Verfahren nutzbar sind.
The content aggregator platform Reddit has established itself as one of the most popular websites in the world. However, scientific research on Reddit is hindered as Reddit allows (and even encourages) user anonymity, i.e., user profiles do not contain personal information such as the gender. Inferring the gender of users in large-scale could enable the analysis of gender-specific areas of interest, reactions to events, and behavioral patterns. In this direction, this thesis suggests a machine learning approach of estimating the gender of Reddit users. By exploiting specific conventions in parts of the website, we obtain a ground truth for more than 190 million comments of labeled users. This data is then used to train machine learning classifiers to use them to gain insights about the gender balance of particular subreddits and the platform in general. By comparing a variety of different approaches for classification algorithm, we find that character-level convolutional neural network achieves performance with an 82.3% F1 score on a task of predicting a gender of a user based on his/her comments. The score surpasses 85% mark for frequent users with more than 50 comments. Furthermore, we discover that female users are less active on Reddit platform, they write fewer comments and post in fewer subreddits on average, when compared to male users.
The term “Software Chrestomaty” is defined as a collection of software systems meant to be useful in learning about or gaining insight into software languages, software technologies, software concepts, programming, and software engineering. 101companies software chrestomathy is a community project with the attributes of a Research 2.0 infrastructure for various stakeholders in software languages and technology communities. The core of 101companies combines a semantic wiki and confederated open source repositories. We designed and developed an integrated ontology-based knowledge base about software languages and technologies. The knowledge is created by the community of contributors and supported with a running example and structured documentation. The complete ecosystem is exposed by using Linked Data principles and equipped with the additional metadata about individual artifacts. Within the context of software chrestomathy we explored a new type of software architecture – linguistic architecture that is targeted on the language and technology relationships within a software product and based on the megamodels. Our approach to documentation of the software systems is highly structured and makes use of the concepts of the newly developed megamodeling language MegaL. We “connect” an emerging ontology with the megamodeling artifacts to raise the cognitive value of the linguistic architecture.
Smart Building Solutions - Generischer Ansatz für die Identifikation von Raumsteuerungsfunktionen
(2018)
40 percent of current housing and real estate companies plan to integrate intelligent control systems into their properties during new construction and modernization. At the same time, Internet companies are pushing their devices into homes and apartments, promising intelligent services for their users. The term "Smart Home" is used for both types of new technologies. The first group of systems has its origins in the field of "Building Automation", the second group developed from the concept of the "Internet of Things".
In order to discover what the differences are and what common foundations exist, both the areas of Building Automation and Internet of Things are analyzed and compared.
The central contribution of this thesis is the realization that both domains are based on similar concepts and an integration is possible, without compromising the integrity of the systems themselves. In addition, the work provides an approach to designing Building Automation Systems with the integration of the Internet of Things.
The following work describes the prototypical conception and development of the stat-raising game "Adventurer's Guild" using the game engine Ren'Py. The game's narrative is influenced by player decisions and the planning of activities. The game is to be visually pleasing and enjoyable.
After giving an overview of stat-raising as a genre, the existing games "Dandelion - Wishes Brought to You", "Pastry Lovers", "Long Live the Queen" and "Magical Diary" are analysed to pinpoint various strengths and weaknesses of their different takes on the genre.
The resultant findings are used for the conception of a new stat-raising game.
The game mechanics and the design decisions made are then shown in screenshots and thoroughly explained.
In a final assessment, the game will be examined with regard to the given task. Further possibilities for potential improvements and expansions will be detailed at the end.
Social entrepreneurship is a form of entrepreneurship that marries a social mission to a competitive value proposition. Notably, social entrepreneurship fosters a more equitable society by addressing social issues and trying to achieve an ongoing sustainable impact through a social mission rather than purely profit maximization. The topic of social entrepreneurship has appealed considerably to many different streams of research. The focus on understanding how and why entrepreneurs think and act is a significant justification for future research. Nevertheless, the theoretical examination of this phenomenon is in its infancy. Social entrepreneurship research is still largely phenomenon-driven. Specifically, Social Entrepreneurial Intention is in an early stage and lacks quantitative research. Therefore, this thesis proposes to address this need. The thesis’ objectives are twofold: (1) develop a formation model for Social Entrepreneurial Intentions in general and (2) test the model by conducting an empirical study. Based on these objectives, the two research questions guiding the thesis are (1) what factors influence the intention of a person to become a social entrepreneur and (2) what relationships exist among these factors.
In order to answer these two research questions, this thesis uses purposeful research design, which is a combination of literature review and empirical study. The literature review is based on a comprehensive range of books, articles, and research papers published in leading academic journals and conference proceedings in different disciplines such as entrepreneurship, social entrepreneurship, entrepreneurship education, management, social psychology, and social economics. The empirical study is conducted via a survey of 600 last-year students from four universities in three regions in Vietnam: Hanoi, Da Nang, and Ho Chi Minh. The data are analyzed with SPSS-AMOS version 24, using screening data, scale development, exploratory factor analysis, and confirmation factor analysis. The thesis ascertains that Entrepreneurship Experience/Extra-curricular Activity, Role Model, Social Entrepreneurial Self-Efficacy, and Social Entrepreneurial Outcome Expectation directly and positively affect the intention of the Vietnamese students to be social entrepreneurs. Entrepreneurship Education also influences the Social Entrepreneurial Intention, but not directly, otherwise indirectly via Social Entrepreneurial Self-Efficacy and Social Entrepreneurial Outcome Expectation. Similarly, Perceived Support has no direct relationship to Social Entrepreneurial Intention; however, it shows an indirect link via the mediator ‘Social Entrepreneurial Outcome Expectation’. Furthermore, the dissertation brings new insights to the social entrepreneurship literature and provides important implications for practice. Limitations and future directions are also provided in the thesis.
This bachelor thesis’s objective is to offer the reader insight into the discrete Fourier transform, the discrete cosine transform and the discrete Hadamard-Walsh transform in the context of image processing, and also to compare these transformations under various aspects. For this purpose the term of transformation, originated in linear algebra, will be explained and applied to image processing. Subsequently, the understanding of the Fourier transform will successively be built up and connected to the two remaining transforms. Finally, the transformations will be compared and their usefulness in relation to image processing will be explained.
This thesis connects the endeavors of the winemaker’s intention in perfect and profitable wine making with an innovative technological application to use Internet of Things. Thereby the winemaker’s work may be supported and enriched – and enables until recent years still unthinkable optimization of managing and planning of his business, including close state control of different areas of his vineyard, and more than that, not ending up with the single grapevine. It is exemplarily shown in this thesis how to measure, transmit, store and make data available, exemplarily demonstrated with “live” temperature, air and soil humidity values from the vineyard. A modular architecture was designed for the system presented, which allows the use of current sensors, and similar low-voltage sensors, which will be developed in the future.
By using IoT devices in the vineyard, the winemaker advances to a new quality of precision of forecasted data, starting from live data of his vineyard. Of more and more importance, the winemaker can start immediate action, when unforeseen heavy weather conditions occur. Immediate use of current data enabled by a Cloud Infrastructure. For this system, an open service infrastructure is employed. In contrast to other published commercial approaches, the described solution is based on open source.
As an alone-standing part of this work, a physical prototype for measuring relevant parameters in the vineyard was de-novo designed and developed until fulfilling the set of specifications. The outlined features and requirements for a functioning data collection and autonomously transmitting device was developed, described, and the fulfilment by the prototype device were demonstrated. Through literature research and supportive orientationally live interviews of winemakers, the theory and the practical application were synchronized and qualified.
For the development of the prototype the general principles of development of an electronic device were followed, in particular the Design Science Research development rules, and principles of Quality Function Deployment. As a characteristic of the prototype, some principles like re-use of approved construction and material price of the building blocks of the device were taken into consideration as well (e.g. housing; Arduino; PCB). Parts reduction principles, decomplexation and simplified assembly, testing and field service were integrated to the development process by the modular design of the functional vineyard device components, e.g. with partial reference to innovative electrical cabinet construction system Modular-3.
The software architectural concept is based on a three-layer architecture inclusive the TTN infrastructure. The front end is realized as a rich web client, using a WordPress plugin. WordPress was chosen due to the wide adoption through the whole internet, enabling fast and easy user familiarization. Relevant quality issues have been tested and discussed in the view of exemplary functionality, extensibility, requirements fulfilment, as usability and durability of the device and the software.
The prototype was characterized and tested with success in the laboratory and in field exposition under different conditions, in order to allow a measurement and analysis of the fulfilment of all requirements by the selected and realized electronic construction and layout.
The solution presented may serve as a basis for future development and application in this special showcase and within similar technologies. A prognosis of future work and applications concludes this work.
Maßnahmen der Führungskräfteentwicklung verfolgen das Ziel den Führungsnachwuchs des Unternehmens zu bilden und für einen reibungslosen Einstieg in die Füh-rungsaufgabe zu sorgen. In der Literatur gibt es zahlreiche Theorien und Modelle zu Führung und deren Entwicklung, doch offen bleibt meist, wie es um den praktischen Einsatz und die Effektivität steht. Das Ziel dieser Arbeit ist die Identifikation wesentlicher Bestandteile der Führungskräfteentwicklung, die effektiv Einfluss auf (Nachwuchs-)Führungskräfte nehmen. Drei Studien beschäftigen sich jeweils mit unter-schiedlichen Schwerpunkten mit der Gestaltung und Wirksamkeit von modularen Programmen der Führungskräfteentwicklung. Zur Beschreibung der Gestaltung wurde eine Expertenbefragung unter Verantwortlichen für Führungskräfteentwicklung in 4 Großunternehmen durchgeführt. Zur Prüfung der Wirksamkeit wurden zwei Prädiktoren erfolgreichen Führens, die praktische Führungsintelligenz und die Führungswirksamkeitserwartung (FWE), in zwei repräsentativen modularen Programmen gemessen. Dafür wurden zwei quasiexperimentelle Designs mit Prätest-Posttest durchgeführt: ein Design mit zusätzlicher Kontrollgruppe (Nexp = 14, Nkontr = 12), ein Design mit zusätzlicher Fremdeinschätzung (N = 11 bis N =57 je nach Messzeitpunkt und beteiligten Variablen). Die praktische Führungsintelligenz wurde anhand eines für die Untersuchung entwickelten Situational Judgment Tests (SJTs) gemessen. Neben der FWE (in Anlehnung an die Skala zur Erfassung der beruflichen Selbstwirksamkeitserwartung, BSW-Skala) wurden weitere Konstrukte wie Selbstregulation (Locomotion-Assessment-Fragebogen, L-A-F), Optimismus (Skala Optimismus-Pessimismus-2, SOP2) Selbstmanagement (Fragebogens zur Erfassung von Ressourcen und Selbstmanagementfähigkeiten, FERUS) erfasst, sowie explorativ entwicklungsförderliche Merkmale erhoben. Entsprechend der Annahme verdichten sich die Ergebnisse auf drei Merkmale wirksamer Trainingsgestaltung: Erfahrungssammlung, Feedback, Selbstreflexion. Es konnte nachgewiesen werden, dass Programme mit hohem erfahrungsorientiertem Trainingsanteil, die Erfolgserlebnisse und Modelllernen fördern sowie persönliche Gespräche und Feedback beinhalten, die FWE (ŋ2 = .24, ŋ2 = .50) und die praktische Führungsintelligenz (ŋ2 = .54). signifikant (p<.05) steigern. Deutlich wurde auch der enge Zusammenhang zwischen Merkmalen der Person (wie Ausprägung der FWE oder Selbstregulationsfähigkeiten) und der Wirksamkeit der Programme. Aus den Ergebnissen werden Empfehlungen zur praktischen Umsetzung in der Führungskräfteentwicklung abgeleitet und Anregungen für zukünftige Forschung diskutiert.
Estuaries are characterized by a longitudinal salinity gradient. This gradient is one of the main environmental factors responsible for the distribution of organisms. Distinguishing salinity zones is of crucial importance, e.g., for the development of tools for the assessment of ecological quality. The methods most often applied for classifying water according to salinity are the Venice System and the method of Bulger et al. (1993), both of which determine zone boundaries using species occurrences relative to mean salinity. However, although these methods were developed for homoiohaline waters, they have also been routinely applied to poikilohaline systems. I tested the applicability of both methods using salinity and macroinvertebrate data for the poikilohaline Elbe Estuary (Germany). My results showed that the mid-estuary distribution of macro-invertebrates is determined by variation in salinity rather than by mean salinity. Consequently, neither of the two methods is applicable for defining salinity zones in the Elbe Estuary. Cluster analysis combined with a significance test, by contrast, was a better tool for identifying the boundaries of salinity zones in poikilohaline systems.
In many estuaries, such as the Elbe Estuary, a maximum turbidity zone (MTZ) develops, where suspended matter accumulates owing to circulation processes. It is assumed that the MTZ is a stressful environment with an excess of organic matter, high deposition rates, large variations in salinity, and dredging activities. Under such harsh conditions, populations might remain below the carrying capacity, and it is assumed that competition is of little importance, as predicted by the stress gradient hypothesis. I tested whether competition for food is important in the MTZ of the Elbe Estuary using stable isotope analysis of the macroinvertebrate community. The isotopic niches of no two taxa within a feeding group overlapped, which indicated different resource use and the absence of competition. The main reasons for the lack of overlap of isotopic niches were differences in habitat, feeding behavior, and migration behavior.
The Elbe Estuary is nowadays highly industrialized and has long been subjected to a plethora of human-caused alterations. However, it is largely unknown what changes occurred in benthic communities in the last century. Hence, I considered taxonomic and functional aspects of macrobenthic invertebrates of the Elbe Estuary given in data from 1889 (most natural state), 1985 and 1986 (highly polluted state), and 2006 (recent state) to assess benthic community shifts. Beta-diversity analysis showed that taxonomic differences between the sampling dates were mainly due to species turnover, whereas functional differences were predominantly a result of functional nestedness. Species number (S), functional richness (FRic), and functional redundancy reached minimum values in 1985 and 1986 and were highest and rather similar in 1889 and 2006. The decline in FRic from 1889 to 1985/1986 was non-random, consistent with habitat filtering. FRic, functional beta diversity, and S data suggested that the state of the estuary from 1889 was almost re-established in 2006. However, the community in 1889 significantly differed from that in 2006 owing to species replacement. My results indicate that FRic and FR in 1889 could have promoted ecosystem resilience and stability.