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This thesis presents novel approaches for integrating context information into probabilistic models. Data from social media is typically associated with metadata, which includes context information such as timestamps, geographical coordinates or links to user profiles. Previous studies showed the benefits of using such context information in probabilistic models, e.g.\ improved predictive performance. In practice, probabilistic models which account for context information still play a minor role in data analysis. There are multiple reasons for this. Existing probabilistic models often are complex, the implementation is difficult, implementations are not publicly available, or the parameter estimation is computationally too expensive for large datasets. Additionally, existing models are typically created for a specific type of content and context and lack the flexibility to be applied to other data.
This thesis addresses these problems by introducing a general approach for modelling multiple, arbitrary context variables in probabilistic models and by providing efficient inference schemes and implementations.
In the first half of this thesis, the importance of context and the potential of context information for probabilistic modelling is shown theoretically and in practical examples. In the second half, the example of topic models is employed for introducing a novel approach to context modelling based on document clusters and adjacency relations in the context space. They can cope with areas of sparse observations and These models allow for the first time the efficient, explicit modelling of arbitrary context variables including cyclic and spherical context (such as temporal cycles or geographical coordinates). Using the novel three-level hierarchical multi-Dirichlet process presented in this thesis, the adjacency of ontext clusters can be exploited and multiple contexts can be modelled and weighted at the same time. Efficient inference schemes are derived which yield interpretable model parameters that allow analyse the relation between observations and context.
The provision of electronic participation services (e-participation) is a complex socio-technical undertaking that needs comprehensive design and implementation strategies. E-participation service providers, in the most cases administrations and governments, struggle with changing requirements that demand more transparency, better connectivity and increased collaboration among different actors. At the same time, less staff are available. As a result, recent research assesses only a minority of e-participation services as successful. The challenge is that the e-participation domain lacks comprehensive approaches to design and implement (e-)participation services. Enterprise Architecture (EA) frameworks have evolved in information systems research as an approach to guide the development of complex socio-technical systems. This approach can guide the design and implementation services, if the collection of organisations with the commonly held goal to provide participation services is understood as an E Participation Enterprise (EE). However, research & practice in the e participation domain has not yet exploited EA frameworks. Consequently, the problem scope that motivates this dissertation is the existing gap in research to deploy EA frameworks in e participation design and implementation. The research question that drives this research is: What methodical and technical guides do architecture frameworks provide that can be used to design and implement better and successful e participation?
This dissertation presents a literature study showing that existing approaches have not covered yet the challenges of comprehensive e participation design and implementation. Accordingly, the research moves on to investigate established EA frameworks such as the Zachman Framework, TOGAF, the DoDAF, the FEA, the ARIS, and the ArchiMate for their use. While the application of these frameworks in e participation design and implementation is possible, an integrated approach is lacking so far. The synthesis of literature review and practical insights in design and implementation of e participation services from four projects show the challenges of adapting architecture frameworks for this domain. However, the research shows also the potential of a combination of the different approaches. Consequently, the research moves on to develop the E-Participation Architecture Framework (EPART-Framework). Therefore, the dissertation applies design science research including literature review and action research. Two independent settings test an initial EPART-Framework version. The results yield into the EPART-Framework presented in this dissertation.
The EPART-Framework comprises of the EPART-Metamodel with six EPART-Viewpoints, which frame the stakeholder concerns: the Participation Scope, the Participant Viewpoint, the Participation Viewpoint, the Data & Information Viewpoint, the E-participation Viewpoint, and Implementation & Governance Viewpoint. The EPART-Method supports the stakeholders to design the EE and implement e participation and stores its output in an architecture description and a solution repository. It consists of five consecutive phases accompanied by requirements management: Initiation, Design, Implementation and Preparation, Participation, and Evaluation. The EPART-Framework fills the gap between the e participation domain and the enterprise architecture framework domain. The evaluation gives reasonable evidence that the framework is a valuable addition in academia and in practice to improve e-participation design and implementation. The same time, it shows opportunities for future research to extend and advance the framework.
Confidentiality, integrity, and availability are often listed as the three major requirements for achieving data security and are collectively referred to as the C-I-A triad. Confidentiality of data restricts the data access to authorized parties only, integrity means that the data can only be modified by authorized parties, and availability states that the data must always be accessible when requested. Although these requirements are relevant for any computer system, they are especially important in open and distributed networks. Such networks are able to store large amounts of data without having a single entity in control of ensuring the data's security. The Semantic Web applies to these characteristics as well as it aims at creating a global and decentralized network of machine-readable data. Ensuring the confidentiality, integrity, and availability of this data is therefore also important and must be achieved by corresponding security mechanisms. However, the current reference architecture of the Semantic Web does not define any particular security mechanism yet which implements these requirements. Instead, it only contains a rather abstract representation of security.
This thesis fills this gap by introducing three different security mechanisms for each of the identified security requirements confidentiality, integrity, and availability of Semantic Web data. The mechanisms are not restricted to the very basics of implementing each of the requirements and provide additional features as well. Confidentiality is usually achieved with data encryption. This thesis not only provides an approach for encrypting Semantic Web data, it also allows to search in the resulting ciphertext data without decrypting it first. Integrity of data is typically implemented with digital signatures. Instead of defining a single signature algorithm, this thesis defines a formal framework for signing arbitrary Semantic Web graphs which can be configured with various algorithms to achieve different features. Availability is generally supported by redundant data storage. This thesis expands the classical definition of availability to compliant availability which means that data must only be available as long as the access request complies with a set of predefined policies. This requirement is implemented with a modular and extensible policy language for regulating information flow control. This thesis presents each of these three security mechanisms in detail, evaluates them against a set of requirements, and compares them with the state of the art and related work.
In order to enhance the company’s appeal for potential employees and improve the satisfaction of already salaried workers, it is necessary to offer a variety of work-life balance measures. But as their implementation causes time and financial costs, a prioritization of measures is needed. To express a recommendation for companies, this study is led by the questions if there are work-life balance measures which have more impact on employee satisfaction than others, how big the relative impact of work-life balance measures on job satisfaction in comparison to other work and private life variables is, if there is a relation between the effectiveness of measures and their use and if there is a difference between the measures which are most important from the employees’ perspective and the companies’ offers.
These questions are formulated in eight research hypotheses which are examined in a quantitative research design with online survey data from 289 employees of fifteen different German companies. The formation of a hierarchy of the effectiveness of measures towards job satisfaction as well as the investigation of the relative impact in comparison to other variables is performed using a multiple regression analysis, whilst the differences between employees’ expectations and the availability of offers are examined with t-tests.
Support in childcare, support in voluntary activities and teambuilding events have a significantly higher impact on job satisfaction than other work-life balance measures, and their potential use is higher than the actual use which leads to the conclusion that there is yet potential for companies to improve their employees’ satisfaction by implementing these measures. In addition, flexible work hours, flexible work locations and free time and overtime accounts are the most important measures from the employees’ point of view and already widely offered by the surveyed companies. In general, the overall use of the available measures and the quantity of offered measures are more important with regard to job satisfaction than the specific kind of measure. In addition, work-life balance measures are more important towards job satisfaction for younger people.
This thesis analyzes the online attention towards scientists and their research topics. The studies compare the attention dynamics towards the winners of important scientific prizes with scientists who did not receive a prize. Web signals such as Wikipedia page views, Wikipedia edits, and Google Trends were used as a proxy for online attention. One study focused on the time between the creation of the article about a scientist and their research topics. It was discovered that articles about research topics were created closer to the articles of prize winners than to scientists who did not receive a prize. One possible explanation could be that the research topics are more closely related to the scientist who got an award. This supports that scientists who received the prize introduced the topics to the public. Another study considered the public attention trends towards the related research topics before and after a page of a scientist was created. It was observed that after a page about a scientist was created, research topics of prize winners received more attention than the topics of scientists who did not receive a prize. Furthermore, it was demonstrated that Nobel Prize winners get a lower amount of attention before receiving the prize than the potential nominees from the list of Citation Laureates of Thompson Reuters. Also, their popularity is going down faster after receiving it. It was also shown that it is difficult to predict the prize winners based on the attention dynamics towards them.
Science education has been facing important challenges in the recent years: the decline in student’s interest in scientific topics, and moreover, the decrease of students pursuing science beyond their compulsory studies (Bennett, Hogarth, Lubben, 2003). As a result, research has focus on examining different approaches that could attempt to improve the situation. One of these approaches has been the use of context-based problem-solving tasks (Kölbach & Sumfleth, 2011; Bennett, Hogarth, Lubben, 2003). While research into context-based problem-solving tasks suggest that they are very motivating for students, it is still unclear how they influence motivation. Following an experimental pretest-postest design, two studies examined the effects of context-based task characteristics of contextualization, complexity, and transparency, on students’ motivational variables, performance, and metacognitive experiences.
Results from both studies suggest that the task characteristic of contextualization directly influences how students’ interest is triggered and maintained throughout the task. On the other hand, the task characteristics of complexity and transparency had different effects for the other dependent variables of effort, difficulty, and solution correctness.
Moreover, data shows that other motivational variables such as anxiety and success expectancies are strongly influenced by the interaction of the parameters under study. The dissertation concludes that appropriate design and use of context-based task characteristics can benefit students’ learning processes and outcomes.
The purpose of this research is to examine various existing cloud-based Internet of Things (IoT) development platforms and evaluate one platform (IBM Watson IoT) in detail using a use case scenario. Internet of Things IoT is an emerging technology that has a vision of interconnecting the virtual world (e.g. clouds, social networks) and the physical world (e.g. device, cars, fridge, people, animals) through the Internet technology. For example, the IoT concept of smart cities which has the objectives to improve the efficiency and development of business, social and cultural services in the city, can be achieved by using sensors, actuators, clouds and mobile devices (IEEE, 2015). A sensor (e.g. temperature sensor) in the building (global world) can send the real-time data to the IoT cloud platform (virtual world), where it can be monitored, stored, analysed, or used to trigger some action (e.g. turn on the cooling system in the building if temperature exceeds a threshold limit). Although, the IoT creates vast opportunities in different areas (e.g. transportation, healthcare, manufacturing industry), it also brings challenges such as standardisation, interoperability, scalability, security and privacy. In this research report, IoT concepts and related key issues are discussed.
The focus of this research is to compare various cloud-based IoT platforms in order to understand the business and technical features they offer. The cloud-based IoT platforms from IBM, Google, Microsoft, PTC and Amazon have been studied.
To design the research, the Design Science Research (DSR) methodology has been followed, and to model the real-time IoT system the IOT-A modelling approach has been used.
The comparison of different cloud based IoT development platforms shows that all of the studied platforms provide basic IoT functionalities such as connecting the IoT devices to the cloud based IoT platform, collecting data from the IoT devices, data storage and data analytics. However, the IBM’s IoT platform appears to have an edge over the other platforms studied in this research because of the integrated run-time environment which also makes it more developer friendly. Therefore, IBM Watson IoT for Bluemix is selected for further examination of its capabilities. The IBM Watson IoT for Bluemix offerings include analytics, risk management, connect and information management. A use case was implemented to assess the capabilities that IBM Watson IoT platform offers. The digital artifacts (i.e. applications) are produced to evaluate the IBM’s IoT solution. The results show that IBM offers a very scalable, developer and deployment friendly IoT platform. Its cognitive, contextual and predictive analytics provide a promising functionality that can be used to gain insights from the IoT data transmitted by the sensors and other IoT devices.
The global problematic issue of the olive oil industry is in its generation of large amounts of olive mill wastewater (OMW). The direct discharge of OMW to the soil is very common which presents environmental problems for olive oil producing countries. Both, positive as well as negative effects on soil have been found in earlier studies. Therefore, the current study hypothesized that whether beneficial effects or negative effects dominate depends on the prevailing conditions before and after OMW discharge to soil. As such, a better understanding of the OMW-soil interaction mechanisms becomes essential for sustainable safe disposal of OMW on soil and sustainable soil quality.
A field experiment was carried out in an olive orchard in Palestine, over a period of 24 months, in which the OMW was applied to the soil as a single application of 14 L m-2 under four different environmental conditions: in winter (WI), spring (SP), and summer with and without irrigation (SUmoist and SUdry). The current study investigated the effects of seasonal conditions on the olive mill wastewater (OMW) soil interaction in the short-term and the long-term. The degree and persistence of soil salinization, acidification, accumulation of phenolic compounds and soil water repellency were investigated as a function of soil depth and time elapsed after the OMW application. Moreover, the OMW impacts on soil organic matter SOM quality and quantity, total organic carbon (SOC), water-extractable soil organic carbon (DOC), as well as specific ultraviolet absorbance analysis (SUVA254) were also investigated for each seasonal application in order to assess the degree of OMW-OM decomposition or accumulation in soil, and therefore, the persisting effects of OMW disposal to soil.
The results of the current study demonstrate that the degree and persistence of relevant effects due to OMW application on soil varied significantly between the different seasonal OMW applications both in the short-term and the long-term. The negative effects of the potentially hazardous OMW residuals in the soil were highly dependent on the dominant transport mechanisms and transformation mechanisms, triggered by the ambient soil moisture and temperature which either intensified or diminished negative effects of OMW in the soil during and after the application season. The negative effects of OMW disposal to the soil decreased by increasing the retention time of OMW in soil under conditions favoring biological activity. The moderate conditions of soil moisture and temperature allowed for a considerable amount of applied OMW to be biologically degraded, while the prolonged application time under dry conditions and high temperature resulted in a less degradable organic fraction of the OMW, causing the OMW constituents to accumulate and polymerize without being degraded. Further, the rainfall during winter season diminished negative effects of OMW in the soil; therefore, the risk of groundwater contamination by non-degraded constituents of OMW can be highly probable during the winter season.
Five personality traits commonly known as the “Big Five” have been widely acknowledged as universal. But most available psychological instruments are not necessarily transferable to other cultures. They are referred to as “W.E.I.R.D.” (western, educated, industrial, rich, democratic) and lack the combined emic-etic approach that is necessary for a transcultural perspective. This intercontinental congress brings experts from Kenya and Germany together – thinking out of the box and collecting ideas for a scientific based partnership of East Africa and Europe. Main topics are psychological constructs that prove relevant for Human Resources Management. The Five-Factor Model, core self-evaluations, coping processes and acculturation as well as globalization effects and gender issues are discussed.
While Virtual Reality has been around for decades it gained new life in recent years. The release of the first consumer hardware devices allows fully immersive and affordable VR for the user at home. This availability lead to a new focus of research on technical problems as well as psychological effects. The concepts of presence, describing the feeling of being in the virtual place, body ownership and their impact are central topics in research for a long time and still not fully understood.
To enable further research in the area of Mixed Reality, we want to introduce a framework that integrates the users body and surroundings inside a visual coherent virtual environment. As one of two main aspects we want to merge real and virtual objects to a shared environment in a way such that they are no longer visually distinguishable. To achieve this the main focus is not supposed to be on a high graphical fidelity but on a simplified representation of reality. The essential question is, what level of visual realism is necessary to create a believable mixed reality environment that induces a sense of presence in the user? The second aspect considers the integration of virtual persons. Can characters be recorded and replayed in a way such that they are perceived as believable entities of the world and therefore act as a part of the users environment?
The purpose of this thesis was the development of a framework called Mixed Reality Embodiment Platform. This inital system implements fundamental functionalities to be used as a basis for future extensions to the framework. We also provide a first application that enables user studies to evaluate the framework and contribute to aforementioned research questions.