Sökning: "Information Systems and Applications"
Visar resultat 21 - 25 av 2071 avhandlingar innehållade orden Information Systems and Applications.
21. Transport Analytics Based on Cellular Network Signalling Data
Sammanfattning : Cellular networks of today generate a massive amount of signalling data. A large part of this signalling is generated to handle the mobility of subscribers and contains location information that can be used to fundamentally change our understanding of mobility patterns. LÄS MER
22. Samskapande datortillämpningar : en systemteoretisk ansats för lösning av vissa förändringsproblem vid administrativ datoranvändning
Sammanfattning : This thesis starts by observing a change problem in a medical computer application. The change problem occurs when data and rules that make up the core of a computer application, degenerate. Sometimes the process is slow, but it is not unusual for the application to be out of date even before it has been put into use. LÄS MER
23. Cognitively inspired design : Rethink the wheel for self-driving cars
Sammanfattning : This thesis examines Cognitively Inspired Design (CID), which is the process of transferring cognitive science frameworks and theories to intelligent systems in an application context. The thesis studies the relation between cognitive science and the traditional approach to developing systems. LÄS MER
24. Scheduling and Optimization of Fault-Tolerant Embedded Systems
Sammanfattning : Safety-critical applications have to function correctly even in presence of faults. This thesis deals with techniques for tolerating effects of transient and intermittent faults. Reexecution, software replication, and rollback recovery with checkpointing are used to provide the required level of fault tolerance. LÄS MER
25. Distributed and federated learning of support vector machines and applications
Sammanfattning : Machine Learning (ML) has achieved remarkable success in solving classification, regression, and related problems over the past decade. In particular the exponential growth of digital data, makes using ML inevitable and necessary to exploit the wealth of information hidden inside the data. LÄS MER