A smart cloud platform service for socialized travel and transportation with mobile support

Thesis (M.A.)--Özyeğin University, Graduate School of Sciences and Engineering, Department of Computer Engineering, September 2013.It is now clear that social networking services are evolving towards mobile web applications and continuous location sharing is also becoming a trend. In this evolution, we believe that the next step will be complete and continuous route and experience sharing. A route-based social networking cloud platform is a service in which users share their travel routes as well as experiences and stories using their mobile devices, or search for and get matched with people with similar travel and transportation habits in real-time. This work mainly focuses on the development of an end-to-end route-based social networking cloud platform service and its client-side mobile application. First, we describe the design and implementation of our real-time taxi ride-sharing service for metropolitan areas, which is a specific application of the route-sharing service. This system is composed of 1) taxi location data collection system, 2) real-time passenger coupling service and 3) a dashboard for visualization and analysis of the results. Second, we describe our location tracking mobile application that captures rich location-based information and saves it to the cloud.Turkish Telecom R&D Program ; European Commission ; IBM SUR (Shared University Research) awar

Otonom helikopterler için öğrenebilir yapay sinir ağı tabanlı olmayan adaptif kontrol algoritmalarının uçuş testleri ile doğrulanması

TÜBİTAK MAG01.05.2010Bu projede bir model helikopter için dinamik matematiksel benzetimi geliştirilmiştir. Geliştirilen benzetim yapay sinir ağı tabanlı adaptif kontrol algoritmaları ile sanal ortamda kontrol edilmiştir. Kontrolcünün model helikopter üzerinde test edilmesi için helikoptere otonom uçuş yetisi kazandırılmaya çalışılmıştır. Kontrolcünün denenmesi ve testlerin güvenli bir ortamda gerçekleştirilmesi için test platformları tasarlanmış ve testler gerçekleştirilmiştir. Aviyonik sistemler birbirleri ile entegre edilmiş ve birlikte çalıştırılmıştır. Sensörlerden gelen veriler elde edilmiş ve bu veriler kontrolcüye beslenerek model helikopterin kararlı bir şekilde askı pozisyonunda kalması hedeflenmiştir.Tüm sistem platforma monte edilmiş ve sistemlerin birbiriyle uyumlu çalışması için çalışmalar gerçekleştirilmiştir. Tüm testlerden sonra simulasyon ortamındaki verilerle testlerden elde edilen veriler karşılaştırılarak kontrol algoritmalarının doğrulanması öngörülmektedir.In this Project, a simulation model for an RC helicopter is developed. The system is tested in the laboratory with neural network based adaptive control algorithms. The helicopter is equipped with autonomous flying capability. Test platforms were designed in order to test the controller and perform these tests in a secure environment. Avionic systems were integrated with each other and operated together. Flight data was obtained from sensors and data was fed back to the controller to keep the helicopter in hover in a stable manner. The whole system was installed on the platform and studies were carried out for the operation of the sub- systems. After the tests, it is expected to verify control algorithms comparing both data obtained in the simulation environment and actal tests

Performance analysis of classical MAP adaptation based methods in speaker and channel adaptation in GMM-based speaker verification systems

Due to copyright restrictions, the access to the full text of this article is only available via subscription.In this paper, performance of Gaussian mixture models (GMM) based algorithms implemented in Speech Processing Laboratory at Ozyegin University, within NIST SRE2004 and 2006 database was reported. Gaussian mixture models (GMM) is one of the most commonly used methods in text-independent speaker verification systems. In this paper, performance of the GMM approach has been measured with different parameters and settings. It has also been observed that eigenchannel-MAP and JFA methods both have increased the performance of the system against session variability which is one of the most challenging problem in text-independent speaker verification systems.Sante