000 Allgemeines, Informatik, Informationswissenschaft
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This thesis deals with the creation of a cross-platform application using Xamarin.Forms. The cross-platform application will cover three different platforms android, iOS, and UWP.
The application is the first concept of a possible feature for a companion application for LS telcom. There, the user can identify cell antennas using a map-view and a camera-view making the application an augmented reality application. Thus, the user can search for a specific cell and access various information that he would not be able to see with his eyes like for example the frequency of the transmitting cells.
The cell data is generated from three different sources, Cartoradio, OpenCelliD, and the LS telcom databrowser. Eventually, the decision was taken, that the main source should be the LS telcom databrowser which has multiple advantages over the other cell sources.
The cells on the map-view are placed using the extracted coordinates from the source data. However, the cells on the camera-view are placed with complex calculations using different formulas like the Haversine formula to calculate the distance between the cell and the user and the bearing to calculate the angle between the cell and the user. Various settings will allow the user to personalize the application according to his wishes.
The improvements in the hardware and software of communication devices have allowed running Virtual Reality (VR) and Augmented Reality (AR) applications on those. Nowadays, it is possible to overlay synthetic information on real images, or even to play 3D on-line games on smart phones or some other mobile devices. Hence the use of 3D data for business and specially for education purposes is ubiquitous. Due to always available at hand and always ready to use properties of mobile phones, those are considered as most potential communication devices. The total numbers of mobile phone users are increasing all over the world every day and that makes mobile phones the most suitable device to reach a huge number of end clients either for education or for business purposes. There are different standards, protocols and specifications to establish the communication among different communication devices but there is no initiative taken so far to make it sure that the send data through this communication process will be understood and used by the destination device. Since all the devices are not able to deal with all kind of 3D data formats and it is also not realistic to have different version of the same data to make it compatible with the destination device, it is necessary to have a prevalent solution. The proposed architecture in this paper describes a device and purpose independent 3D data visibility any time anywhere to the right person in suitable format. There is no solution without limitation. The architecture is implemented in a prototype to make an experimental validation of the architecture which also shows the difference between theory and practice.
Cloud computing is the emerging technology providing IT as a utility through internet. The benefits of cloud computing are but not limited to service based, scalable, elastic, shared pool of resources, metered by use. Due to mentioned benefits the concept of cloud computing fits very well with the concept of m-learning which differs from other forms of e-learning, covers a wide range of possibilities opened up by the convergence of new mobile technologies, wireless communication structure and distance learning development. The concept of cloud computing like any other concept has not only benefits but also introduces myriad of security issues, such as transparency between cloud user and provider, lack of standards, security concerns related to identity, Service Level Agreements (SLA) inadequacy etc. Providing secure, transparent, and reliable services in cloud computing environment is an important issue. This paper introduces a secured three layered architecture with an advance Intrusion Detection System (advIDS), which overcomes different vulnerabilities on cloud deployed applications. This proposed architecture can reduce the impact of different attacks by providing timely alerts, rejecting the unauthorized access over services, and recording the new threat profiles for future verification. The goal of this research is to provide more control over data and applications to the cloud user, which are now mainly controlled by Cloud Service Provider (CSP).
This paper shows the results of the evaluation of two sets of mobile web design guidelines concerning mobile learning. The first set of guidelines is concerned with the usage of text on mobile device screens. The second set is concerned with the usage of images on mobile devices. The evaluation is performed by eye tracking (objective) as well as questionnaires and interviews (subjective) respectively.
Flashcards are a well known and proven method to learn and memorise. Such a way of learning is perfectly suited for “learning on the way,” but carrying all the flashcards could be awkward. In this scenario, a mobile device (mobile phone) is an adequate solution. The new mobile device operating system Android from Google allows for writing multimedia-enriched applications.
This thesis deals with the implementation of the SUBSCALE algorithm in the Python programming language. First, the current state of research and the needs of the target group are considered. Then, the choice of language is decided based on the findings. On the basis of self-generated requirements, the implementation is carried out.
Finally, the code is evaluated for accuracy, consistency, and execution time, as well as its applicability in practice.
Since the implementation of the current work proved to be unconvincing, an approach is tested in which Python is used only as a front-end.
Diese Arbeit befasst sich mit der Konzeption und Implementierung eines Dateiimportfilters für Mess- und Kalibrierwerkzeuge. Dieser ermöglicht das Importieren von INCA-Experimenten nach CANape, indem aus Experiment-Exportdateien Konfigurationsdateien generiert werden. Im Zuge der Umsetzung wurde dazu das aus binären Daten bestehende Exportdateiformat von INCA analysiert. Das Ziel dieser Analyse bestand darin, herauszufinden, wo und wie die Informationen in den Exportdateien gespeichert sind. Die so erlangten Erkenntnisse wurden verwendet, um den Dateiimportfilter zu entwickeln. Dieser liest aus Exportdateien die notwendigen Informationen aus, überführt sie in eine CANape interne Repräsentation und generiert daraus eine entsprechende Konfigurationsdatei. Die korrekte Funktionsweise wurde anhand von selbst erstellten Experimenten sowie mithilfe von Kundenexperimenten validiert.
Intelligente Assistenten - Untersuchung der Spracheingabe in Verbindung mit dem ERP-System SIVAS.ERP
(2018)
Die vorliegende Bachelorarbeit wurde für die schrempp edv GmbH erstellt. Die Untersuchung von Technologien intelligenter Assistenz und eine fundierte Einsatzempfehlung für zukünftige Entwicklungen in Verbindung mit dem ERP-System SIVAS sind die primären Ziele der Abschlussarbeit. Das Hauptaugenmerk der Analyse liegt auf der Spracherkennung und der Sprachverarbeitung. Diese Technologien sollen den Umgang mit den komplexen Anwendungen im SIVAS-Umfeld erleichtern.
Der erste Teil der Abschlussarbeit befasst sich mit den theoretischen Grundlagen intelligenter (Sprach-) Assistenz. Im zweiten Teil wird die SIVAS.Montage-App und ein Szenario zur prototypischen Umsetzung intelligenter Assistenz vorgestellt.
Die folgenden Teile beschäftigen sich mit der Spracherkennung und Sprachverarbeitung von Google und Microsoft. Die beiden Unternehmen betreiben seit Jahren intensive Forschungen zu den Sprachtechnologien und bieten erfolgreiche Lösungskonzepte an. Analysierte Frameworks der Spracherkennung sind die Google Speech API und die Bing Speech API. Kandidaten der Sprachverarbeitung sind Dialogflow von Google und LUIS von Microsoft.
Das Ergebnis der Analyse ist die Einsatzempfehlung der Frameworks von Google. Insbesondere bei der ermittelten Fehlerrate als Schlüsselkriterium der Spracherkennung, kann Google mit 11,11 % gegenüber Microsoft mit 23,09 % überzeugen. Der Vergleich der Frameworks zur Sprachverarbeitung liefert ähnliche Resultate. Google ist Microsoft bei der Klassifizierung bisher unbekannter Aussagen der Anwender mit einer Genauigkeit von 86,67 % um fünf Prozentpunkte überlegen. Informationen werden mit Hilfe von Dialogflow erfolgreicher und strukturell besser aufbereitet extrahiert.
Abschließend wird SIVAS mit den analysierten Google-Technologien mittels einer prototypischen Umsetzung des ausgewählten Szenarios zur Erfassung von Montagezeiten zusammengebracht.