Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253
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Publication About nanometer sized analogues of basic electronic and optical components(IEEE, 2008) Quandt, Alexander; Özdoğan, Cem; Ferrari, Maurizio; Speranza, GiorgioWe discuss a downsizing of optical components into the nanometer range. It presupposes the substitution of photons by ballistic electrons, but it also requires a simple and robust concept to assemble the analogues of basic electronic and optical components on such a tiny length scale. Here, one of the most promising candidate schemes employs graphene as a basic nanosubstrate. We elucidate the suggested behaviour of graphene as an electronic metamaterial [1], and show that other desired electronic or optical functionalities may be obtained through a patterning with sub-nanometer sized boron clusters [2].Conference Object SpEnD portal: linked data discovery using SPARQL endpoints(IEEE, 2017) Yumuşak, Semih; Aras, Rıza Emre; Uysal, Elif; Doğdu, Erdoğan; Kodaz, Halife; Öztoprak, KasımWe present the project SpEnD, a complete SPARQL endpoint discovery and analysis portal. In a previous study, the SPARQL endpoint discovery and analysis steps of the SpEnD system were explained in detail. In the SpEnD portal, the SPARQL endpoints are extracted from the web by using web crawling techniques, monitored and analyzed by live querying the endpoints systematically. After many sustainability improvements in the SpEnD project, the SpEnD system is now online as a portal. SpEnD portal currently serves 1487 SPARQL endpoints, out of which 911 endpoints are uniquely found by SpEnD only when compared to the other existing SPARQL endpoint repositories. In this portal, the analytic results and the content information are shared for every SPARQL endpoint. The endpoints stored in the repository are monitored and updated continuously.Book Part Parallelization of sparsity-driven change detection method(IEEE, 2017) Özgür, Atilla; Saran, Ayşe Nurdan; Nar, FatihIn this study, Sparsity-driven Change Detection (SDCD) method, which has been proposed for detecting changes in multitemporal synthetic aperture radar (SAR) images, is parallelized to reduce the execution time. Parallelization of the SDCD is realized using OpenMP on CPU and CUDA on GPU. Execution speed of the parallelized SDCD is shown on real-world SAR images. Our experimental results show that the computation time of the parallel implementation brings significant speed-ups.Book Part Predicting flight delays with artificial neural networks: case study of an airport(IEEE, 2017) Demir, Engin; Demir, Vahap BurhanAir transportation has an important place among transportation systems and it is indispensable for the flights to perform their voyages in scheduled time in order to ensure the comfort of passengers and controllability of operational costs. There are several reasons for flight delays like weather conditions, excessive intensity in air traffic, accidents or closed airfields, conditions that will lead to an increase in distances between planes and operational delays in ground services. In this study, using the data collected from the sensors located in the airport and the information about the flight, the goal is develop a machine learning model to estimate departure delays of flights using artificial neural networks.