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Innovative architecture and networks for learner-centred, local education and life-long-learning are receiving growing attention. Yet, practitioners still require practical guidance, given the challenge of involving and interacting with new and diverse stake-holder groups, such as architects and politicians, or the community at large. With the goal of advancing scientific and practical frameworks, this thesis approaches how stakeholders in ‘education-centred urban development’ (ECUD) can be helped to accomplish mutual understanding and more effective communication and interaction during planning.
Assuming the organizational theory of ‘networked governance’ (NG), a literature re-view is conducted across ‘institutional learning space development’ (ILSD) and the ‘learning city / region’ discourse (LCR), in order to discuss stakeholder involvement in planning. Six key themes are summarized and tested against a case study of ‘Hume Global Learning Village’ (HGLV), Australia, using a document analysis and expert online interviews.
The review finds the following themes: First, the concepts of ILSD and ECUD can be very abstract to comprehend, and stakeholders’ varied understandings of ‘learning’ demands an open, continuous dialogue. Next, individual leadership needs to initiate a vision, and multiply buy-in and followers. Securing sustainable funding sources is a precondition to foster participation and commitment. Long-standing organizational ‘silo-thinking’ has to be opened up towards cultures of sharing, collaboration, and innovation. Facilitation capacities are crucial to provide an inclusive planning process where con-sent and commitment is fostered. Lastly, change and positive learning effects may take a long time to show – this expectation has to be internalized by all stakeholders.
Despite few optimal interview sources, the case study confirms the themes, and illustrates that excess leadership can ensure the other conditions. This suggests that the six themes can serve as a framework for practitioners to conduct successful stake-holder involvement in planning. However, they are not unique among good-case literature. Moreover, the review shows a literature gap in how a suitable degree of stakeholder involvement can be selected. It is recommended to consolidate the various, alterna-tive planning processes and models, and further triangulate local experiences, in order to close this gap and derive more comprehensive and universal tools for practitioners.
The capabilities of Artificial Intelligence (AI) are utilized increasingly
in today‘s world. The autonomous and adaptive characteristics
allow applications to be more effective and efficient. A certain
subfield of Artificial Intelligence, Machine Learning, is enabling
services to be tailored to a user‘s specific needs. This could prove to
be useful in an information-heavy field such as Statistics. As design
research from SPSS Statistics, a legacy statistical application, has
indicated, statistics beginners struggle to tackle the challenge of
preparing a statistical research study. They turn to several sources
of information in an attempt to find help and answers but are not
always successful. This leads to them being unconfident before
they have even started to execute the statistical study. The adaptive
features of Artificial Intelligence could help support students
in this case, if designed according to established principles. This
thesis investigated the question whether an AI-powered solution
could elevate the users‘ confidence in statistical research studies.
In order to find the answer, a prototype with exemplary User Experience
was designed and implemented. Preceding research determined
the domain and market offer. User research was conducted
to ensure a human-centered outcome. The prototype was evaluated
with real test users and the results answered the question in
the affirmative.
Privacy in Social Networks
(2016)
Online Social Networks (OSNs) are heavily used today and despite of all privacy concerns found a way into our daily life. After showing how heavy data collection is a violation of the user's privacy, this thesis establishes mandatory and optional requirements for a Privacy orientated Online Social Network (POSN). It evaluates twelve existing POSNs in general and in regard to those requirements. The paper will find that none of these POSNs are able to fulfill the requirements and therefore proposes features and patterns as a reference architecture.
This bachelor thesis wants to describe a prototypical implementation of a 3D user interface for intuitive real-time set editing in virtual production. Furthermore this approach is evaluated qualitatively through a user group, testing the device and fill in a questionnaire. The dimension of virtual elements created with computer graphics technology in all areas of entertainment industry is steadily growing since the past years. Nevertheless can the editing process of virtual elements still require a costly process in terms of time and money. With the appearance of new input devices and improved tracking technologies it is interesting to evaluate if a real-time editing process could improve this situation. Being currently bound to experts on special workstations, this could lead to a more intuitive and real-time workflow, enabling everybody on a film set to influence the digital editing process and work collaboratively on the scene consisting of virtual and real elements.
Deep learning methods have proven highly effective for object recognition tasks, especially
in the form of artificial neural networks. In this bachelor’s thesis, a way is shown to imple-
ment a ready-to-use object recognition implementation on the NAO robotic platform using
Convolutional Neural Networks based on pretrained models. Recognition of multiple objects
at once is realized with the help of the Multibox algorithm. The implementation’s object
recognition rates are evaluated and analyzed in several tests.
Furthermore, the implementation offers a graphical user interface with several options to
adjust the recognition process and for controlling movements of the robot’s head in order
to easier acquire objects in the field of view. Additionally, a dialogue system for querying
further results is presented.
Virtual-reality (VR) is an immersive technology with a growing market and many applications for gesture recognition. This thesis presents a VR gesture recognition method using signal processing techniques. The core concept is based on the comparison of motion features in the form of signals between a runtime recording of users and a possible gesture set. This comparison yields a similarity score through which the most similar gesture can be recognized by a continuous recognition system. Some selected comparison methods are presented, evaluated and discussed. An example implementation is demonstrated. However, due to an introduced layer model parts of the method and its implementation are interchangeable.
Similar or even better performance is achieved compared to other related work. The comparison method Dynamic Time Warping (DTW) reaches an average positive recognitions rate of 98.18% with acceptable real-time application performance. Additionally, the method comes with some benefits: position and direction of users is irrelevant, body proportions have no significant negative impact on recognition rates, faster and slower gesture executions are possible, no user inputs are needed to communicate gesture start and end (continuous recognition), also continuous gestures can be recognized, and the recognition is fast enough to trigger gesture specific events already during the execution.
This study investigates the possibility of using Bartle’s player types for gamification
in the context of language learning apps. By taking user preferences into
account, this might assist in selecting the most suitable game elements. Learning
apps are gaining popularity as an innovative method for obtaining an independent
and flexible learning experience. Gamification keeps users motivated and involved
with the content.
After the research on the usage of gamification and its effects on the user, a language
learning app prototype was created. The evaluation consisted of a user test with
interview questions and the short User Experience Questionnaire (UEQ). The Bartle
test of gamer psychology was used to determine the player types of the participants.
The results show that, while player type and gamification preference can partially
coincide, there are too many deviations to confidently say it can be transferred into
gamification contexts. We conclude that game elements should not be chosen based
on a user’s Bartle player type and are more effectively used by incorporating a variety
of different gamification components.
The number of people with cognitive impairments increases together with the aging population. Thus, social robots are being researched to aid relieve the nursing
sector as well as to combat cognitive impairments. However, it raises concerns regarding how a social robot should relate to members of this group and what might
be appropriate. In this thesis, research about the current state of social robots has been conducted and focus groups with people from the nursing and medical field were held. To verify the credibility of the results and the scenario developed, final
user tests were conducted with representatives of the target group. When using a
social robot in an interaction with persons who have cognitive disabilities, the robot
should speak and behave more human-like and make use of its facial expressions,
stressing empathy and responding to the person accordingly. Though the situation
of interacting with a social robot may be more significant in future generations.
When searching for bugs in Java enterprise applications, an essential part of the
eort consists in redeploying the source code and relaunching the server over and
over. In order to improve this situation, this thesis suggests the implementation
of a runtime debugging tool. The tool's purpose is to facilitate the enrichment of
operating application code with logging statements, which are inteded to generate
additional output concerning the webapp's current state. On behalf of this
so-called instrumentation, the actual process of debugging could be supported
and accelerated without having to interrupt the server's execution.
Due to the signicance of Java EE as well as Spring for today's enterprise development,
the implementation of a dedicated debugging tool for each platform
shall be covered. Both solutions pursue the same goal, but dier in the approach
and the programming paradigm forming their basis. This document introduces
their implementation details and evaluates them against a specication that de-
nes the general conditions and expectations in terms of the capabilities of a
satisfying result.
With the increasing use of visual effects in feature films, TV series and commercials, flexibility becomes essential to create astonishing pictures while meeting tight production schedules. Deep image compositing introduces new possibilities that increase flexibility and solve old problems of depth based compositing. The following thesis gives an introduction to deep image compositing, illustrating its power and analyzing its use in a modern visual effects pipeline.