Refine
Year of publication
- 2018 (98) (remove)
Document Type
- Doctoral Thesis (35)
- Bachelor Thesis (30)
- Master's Thesis (18)
- Part of Periodical (14)
- Conference Proceedings (1)
Keywords
- Vorlesungsverzeichnis (4)
- Bildverarbeitung (2)
- 1H-NMR Relaxometry (1)
- Aesthetics (1)
- Agoraphobie (1)
- Analysis of social platform (1)
- Astrophysik (1)
- Augmented Reality (1)
- Barrieren (1)
- Berufsausbildung (1)
Institute
- Institut für Computervisualistik (29)
- Institut für Wirtschafts- und Verwaltungsinformatik (9)
- Institute for Web Science and Technologies (9)
- Institut für Management (8)
- Zentrale Einrichtungen (8)
- Fachbereich 7 (7)
- Institut für Umweltwissenschaften (7)
- Fachbereich 4 (4)
- Fachbereich 6 (3)
- Fachbereich 8 (2)
Companies try to utilise Knowledge Management (KM) to gain more efficiency and effectiveness in business. The major problem is that most of these KM projects are not or rarely based on sustainable analyses or established theories about KM. Often there is a big gap between the expectations and the real outcome of such KM initiatives. So the research question to be answered is: What challenges arise in KM projects, which KM requirements can be derived from them and which recommendations support the goal of meeting the requirements for KM? As theoretical foundation a set of KM frameworks is examined. Subsequently KM challenges from literature are analysed and best practices from case studies are used to provide recommendations for action on this challenges. The main outcome of this thesis is a best practice guideline,which allows Chief Knowledge Officers (CKOs) and KM project managers to examine the challenges mentioned in this thesis closely, and to find a suitable method to master these challenge in an optimal way. This guideline shows that KM can be positively and negatively influenced in a variety of ways. Mastering Knowledge Management (KM) in a company is a big and far-reaching venture and that technology respectively Information Technology (IT) is only a part of the big picture.
Die vorliegende Masterarbeit thematisiert die Evaluation einer sprachgesteuerten Lösung in der Produktion mit multimodaler Eingabe. Dabei wurden die Usability und die Benut-zerfreundlichkeit eines gewählten Sprachdialogsystems bewertet. Die Bewertung wurde mit Hilfe von Benutzertests und eines modifizierten SASSI-Fragebogens durchgeführt. Weiterhin wurden auch technische Kriterien, wie die Wortfehlerrate und die Out-of-grammar Rate zur Hilfe gezogen. Für den Versuch wurden zwei verschiedene Szenarien aus einer realen Produktionsum-gebung definiert. Dabei sollten die Teilnehmer verschiedene Aufgaben mit Hilfe des Testsystems erledigen. Die Interaktion mit dem Sprachdialogsystem fand anhand von ge-sprochenen Befehlen statt, welche durch eine Grammatik definiert wurden. Die Sprach-kommandos wurden durch die Zuhilfenahme eines WLAN-Headsets an das Sprachsys-tem übertragen. Während des Versuchs wurden Aussagen der Teilnehmer protokolliert und die technischen Kriterien notiert.
Das Ergebnis der Evaluation verdeutlicht, dass das Sprachdialogsystem eine hohe Quali-tät bezüglich Usability und Benutzerfreundlichkeit aufweist. Dabei sind die Wortfehler-rate und die Out-of-grammar Rate sehr niedrig ausgefallen und das System wurde von den Benutzern deutlich positiv bewertet. Nichtsdestotrotz wurden einige Kritikpunkte ge-nannt, die zu einer Verbesserung des Systems beitragen können.
Topic models are a popular tool to extract concepts of large text corpora. These text corpora tend to contain hidden meta groups. The size relation of these groups is frequently imbalanced. Their presence is often ignored when applying a topic model. Therefore, this thesis explores the influence of such imbalanced corpora on topic models.
The influence is tested by training LDA on samples with varying size relations. The samples are generated from data sets containing a large group differences i.e language difference and small group differences i.e. political orientation. The predictive performance on those imbalanced corpora is judged using perplexity.
The experiments show that the presence of groups in training corpora can influence the prediction performance of LDA. The impact varies due to various factors, including language-specific perplexity scores. The group-related prediction performance changes for groups when varying the relative group sizes. The actual change varies between data sets.
LDA is able to distinguish between different latent groups in document corpora if differences between groups are large enough, e.g. for groups with different languages. The proportion of group-specific topics is under-proportional to the share of the group in the corpus and relatively smaller for minorities.
This paper describes the robot Lisa used by team homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2017 in Nagoya, Japan. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on
http://wiki.ros.org/agas-ros-pkg.
This paper describes the robot Lisa used by team
homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2016 in Leipzig, Germany. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on http://wiki.ros.org/agas-ros-pkg.
In dieser Forschungsarbeit wird eine Methode zur anwendungsbasierten Verknüpfung von Anforde-rungen und Enterprise Collaboration Softwarekompenten vorgestellt. Basierend auf dem etablierten IRESS Modell wird dabei ein praxistaugliches Mappingschema entwickelt, welches Use Cases über Kol-laborationsszenarien, Collaborative Features und Softwarekomponenten mit ECS verbindet. Somit las-sen sich Anforderungen von Unterhemen in Form von Use Cases und Kollaborationsszenarien model-lieren und anschließend über das Mappingschema mit konkreten ECS verbinden. Zusätzlich wird eine Methodik zur Identifikation von in Softwarekomponenten enthaltenen Collaborative Features vorge-stellt und exemplarisch angewandt.
Anschließend wird ein Konzept für eine Webapplikation entworfen, welches das vorgestellte Mapping automatisiert durchführt, und somit nach Eingabe der Anforderungen in Form vom Use Cases oder Kol-laborationsszenarien, die ECS ausgibt, die eben diese Anforderungen unterstützen.
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.
Homonegative discrimination such as the denial of leadership qualities and higher salaries concern not only lesbians and gay men but also individuals who were perceived as lesbian or gay (Fasoli et al., 2017). Hence, it is assumed that especially straight people become victims of homonegative discrimination (Plöderl, 2014). The perception of sexual orientation is indeed stereotype-driven (e.g., Cox et al., 2015) but there is a lack of knowledge on how accurate stereotypes are – particularly those referring to speech. Despite a variety of sociophonetic and social psychological research related to sexual orientation and gender, an encompassing understanding is missing on how sexual orientation is expressed and perceived.
The present thesis aims to fill these gaps. The two major aims of the present work are a) the examination of the accuracy of speech stereotypes in the context of sexual orientation and b) the development of a model on how sexual orientation is interpersonally construed. Overall, the present thesis comprises five manuscripts with the following aspects in common: They integratively deal with social psychological and sociophonetic perspectives, share a social identity approach, and primarily center speech instead of facial appearance. Moreover, mostly German and German native speaking participants, respectively, have been investigated.
Manuscript 1 establishes the Traditional Masculinity/Femininity-Scale as a reliable and valid instrument for assessing gender-role self-concept. The invention was necessary because existing scales insufficiently represented the self-ascribed masculinity/femininity yet (e.g., Abele, 2003; Evers & Sieverding, 2014). Manuscripts 2, 3, and 4 address the (in)accuracy of speech stereotypes regarding stereotypic content and suggested within-group homogeneity. This is carried out by the application of different methodological approaches. On the one hand, relevant acoustic parameters of lesbian/gay and straight women and men were averaged for each group. On the other hand, voice morphing was applied in order to create prototypical and naturally sounding voice averages (Kawahara et al., 2008). Lesbians and straight women differed in none, gay and straight men in one of the analyzed acoustic parameters only. In contrast, a fine-grained psychological analysis yielded various evidence for acoustic within-group heterogeneity. In particular, the exclusivity of sexual orientation and gender-role self-concept have been acoustically indexicalized which suggests that speech stereotypes are inaccurate. However, voice averages do carry perceivable sexual orientation information. Hence, speech stereotypes can be considered as exaggerations of tiny kernels of truth. In Manuscript 5, previous literature on the interpersonal construction of sexual orientation is integrated in a model: The Expression and Perception of Sexual Orientation Model (EPSOM). This model postulates an indirect route and describes how sexual orientation information is transmitted from producer to perceiver by proposing three mediating components. Thereby, the model is able to offer an explanation why sexual orientation can be perceived with above-chance but far-away-from-perfect accuracy.
Overall, the present thesis provides meaningful impulses for enhancements of research on social markers of sexual orientation and gender. This thesis offers a model on how sexual orientation is expressed and perceived, shows the benefits of combining sociophonetic and social psychological approaches, and points out the value of applying novel methods and technologies. Beyond that, the present thesis offers useful implications for practice. Speech stereotypes in the context of sexual orientation can be rejected as inaccurate – for example, native German straight men do not nasalize more or less than gay men. Thereby, the present thesis contributes to an erosion of stereotypes and a potential reduction of homonegative discrimination.
