004 Datenverarbeitung; Informatik
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Web-programming is a huge field of different technologies and concepts. Each technology implements a web-application requirement like content generation or client-server communication. Different technologies within one application are organized by concepts, for example architectural patterns. The thesis describes an approach for creating a taxonomy about these web-programming components using the free encyclopaedia Wikipedia. Our 101companies project uses implementations to identify and classify the different technology sets and concepts behind a web-application framework. These classifications can be used to create taxonomies and ontologies within the project. The thesis also describes, how we priorize useful web-application frameworks with the help of Wikipedia. Finally, the created implementations concerning web-programming are documented.
The estimation of various social objects is necessary in different fields of social life, science, education, etc. This estimation is usually used for forecasting, for evaluating of different properties and for other goals in complex man-machine systems. At present this estimation is possible by means of computer and mathematical simulation methods which is connected with significant difficulties, such as: - time-distributed process of receiving information about the object; - determination of a corresponding mathematical device and structure identification of the mathematical model; - approximation of the mathematical model to real data, generalization and parametric identification of the mathematical model; - identification of the structure of the links of the real social object. The solution of these problems is impossible without a special intellectual information system which combines different processes and allows predicting the behaviour of such an object. However, most existing information systems lead to the solution of only one special problem. From this point of view the development of a more general technology of designing such systems is very important. The technology of intellectual information system development for estimation and forecasting the professional ability of respondents in the sphere of education can be a concrete example of such a technology. Job orientation is necessary and topical in present economic conditions. It helps tornsolve the problem of expediency of investments to a certain sphere of education. Scientifically validated combined diagnostic methods of job orientation are necessary to carry out professional selection in higher education establishments. The requirements of a modern society are growing, with the earlier developed techniques being unable to correspond to them sufficiently. All these techniques lack an opportunity to account all necessary professional and personal characteristics. Therefore, it is necessary to use a system of various tests. Thus, the development of new methods of job orientation for entrants is necessary. The information model of the process of job orientation is necessary for this purpose. Therefore, it would be desirable to have an information system capable of giving recommendations concerning the choice of a trade on the basis of complex personal characteristics of entrants.
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.
The automatic detection of position and orientation of subsea cables and pipelines in camera images enables underwater vehicles to make autonomous inspections. Plants like algae growing on top and nearby cables and pipelines however complicate their visual detection: the determination of the position via border detection followed by line extraction often fails. Probabilistic approaches are here superior to deterministic approaches. Through modeling probabilities it is possible to make assumptions on the state of the system even if the number of extracted features is small. This work introduces a new tracking system for cable/pipeline following in image sequences which is based on particle filters. Extensive experiments on realistic underwater videos show robustness and performance of this approach and demonstrate advantages over previous works.
Social media platforms such as Twitter or Reddit allow users almost unrestricted access to publish their opinions on recent events or discuss trending topics. While the majority of users approach these platforms innocently, some groups have set their mind on spreading misinformation and influencing or manipulating public opinion. These groups disguise as native users from various countries to spread frequently manufactured articles, strong polarizing opinions in the political spectrum and possibly become providers of hate-speech or extremely political positions. This thesis aims to implement an AutoML pipeline for identifying second language speakers from English social media texts. We investigate style differences of text in different topics and across the platforms Reddit and Twitter, and analyse linguistic features. We employ feature-based models with datasets from Reddit, which include mostly English conversation from European users, and Twitter, which was newly created by collecting English tweets from selected trending topics in different countries. The pipeline classifies language family, native language and origin (Native or non-Native English speakers) of a given textual input. We evaluate the resulting classifications by comparing prediction accuracy, precision and F1 scores of our classification pipeline to traditional machine learning processes. Lastly, we compare the results from each dataset and find differences in language use for topics and platforms. We obtained high prediction accuracy for all categories on the Twitter dataset and observed high variance in features such as average text length especially for Balto-Slavic countries.
As Enterprise 2.0 (E2.0) initiatives are gradually moving out of the early experimentation phase it is time to focus greater attention on examining the structures, processes and operations surrounding E2.0 projects. In this paper we present the findings of an empirical study to investigate and understand the reasons for initiating E2.0 projects and the benefits being derived from them. Our study comprises seven in-depth case studies of E2.0 implementations. We develop a classification and means of visualising the scope of E2.0 initiatives and use these methods to analyse and compare projects.
Our findings indicate a wide range of motivations and combinations of technology in use and show a strong emphasis towards the content management functionality of E2.0 technologies.
Generalized methods for automated theorem proving can be used to compute formula transformations such as projection elimination and knowledge compilation. We present a framework based on clausal tableaux suited for such tasks. These tableaux are characterized independently of particular construction methods, but important features of empirically successful methods are taken into account, especially dependency directed backjumping and branch local operation. As an instance of that framework an adaption of DPLL is described. We show that knowledge compilation methods can be essentially improved by weaving projection elimination partially into the compilation phase.
The thesis develops and evaluates a hypothetical model of the factors that influence user acceptance of weblog technology. Previous acceptance studies are reviewed, and the various models employed are discussed. The eventual model is based on the technology acceptance model (TAM) by Davis et al. It conceptualizes and operationalizes a quantitative survey conducted by means of an online questionnaire, strictly from a user perspective. Finally, it is tested and validated by applying methods of data analysis.
Model-Driven Engineering (MDE) aims to raise the level of abstraction in software system specifications and increase automation in software development. Modelware technological spaces contain the languages and tools for MDE that software developers take into consideration to model systems and domains. Ontoware technological spaces contain ontology languages and technologies to design, query, and reason on knowledge. With the advent of the Semantic Web, ontologies are now being used within the field of software development, as well. In this thesis, bridging technologies are developed to combine two technological spaces in general. Transformation bridges translate models between spaces, mapping bridges relate different models between two spaces, and, integration bridges merge spaces to new all-embracing technological spaces. API bridges establish interoperability between the tools used in the space. In particular, this thesis focuses on the combination of modelware and ontoware technological spaces. Subsequent to a sound comparison of languages and tools in both spaces, the integration bridge is used to build a common technological space, which allows for the hybrid use of languages and the interoperable use of tools. The new space allows for language and domain engineering. Ontology-based software languages may be designed in the new space where syntax and formal semantics are defined with the support of ontology languages, and the correctness of language models is ensured by the use of ontology reasoning technologies. These languages represent a core means for exploiting expressive ontology reasoning in the software modeling domain, while remaining flexible enough to accommodate varying needs of software modelers. Application domains are conceptually described by languages that allow for defining domain instances and types within one domain model. Integrated ontology languages may provide formal semantics for domain-specific languages and ontology technologies allow for reasoning over types and instances in domain models. A scenario in which configurations for network device families are modeled illustrates the approaches discussed in this thesis. Furthermore, the implementation of all bridging technologies for the combination of technological spaces and all tools for ontology-based language engineering and use is illustrated.