Space weather studies of IONOLAB group

IONOLAB is an interdisciplinary research group dedicated for handling the challenges of near earth environment on communication, positioning and remote sensing systems. IONOLAB group contributes to the space weather studies by developing state-of-the-art analysis and imaging techniques. On the website of IONOLAB group, www.ionolab.org, four unique space weather services, namely, IONOLAB-TEC, IRI-PLAS-2015, IRI-PLAS-MAP and IRI-PLAS-STEC, are provided in a user friendly graphical interface unit. Newly developed algorithm for ionospheric tomography, IONOLAB-CIT, provides not only 3-D electron density but also tracking of ionospheric state with high reliability and fidelity. The algorithm for ray tracing through ionosphere, IONOLAB-RAY, provides a simulation environment in all communication bands. The background ionosphere is generated in voxels where IRI-Plas electron density is used to obtain refractive index. One unique feature is the possible update of ionospheric state by insertion of Total Electron Content (TEC) values into IRI-Plas. Both ordinary and extraordinary paths can be traced with high ray and low ray scenarios for any desired date, time and transmitter location. 2-D regional interpolation and mapping algorithm, IONOLAB-MAP, is another tool of IONOLAB group where automatic TEC maps with Kriging algorithm are generated from GPS network with high spatio-temporal resolution. IONOLAB group continues its studies in all aspects of ionospheric and plasmaspheric signal propagation, imaging and mapping. © 2016 IEEE

A dataset for Turkish dialect recognition and classification with deep learning

Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780Dialect Recognition Systems (DRS) are systems that group dialects, according to similar acoustic features found in dialect regions. The speaker's age, gender, and dialect characteristics negatively affect the performance of speech recognition systems. To handle dialect differences, dialect recognition systems can be integrated into speech recognition systems. By determining the spoken dialect, the system can be switched to the corresponding speech recognition model. There is no dataset that can be used for Turkish automatic dialect recognition systems. In this study, it is thought that this deficiency should be eliminated in some way. In addition, an experimental study has been carried out to classify the generated data set by convolutional neural networks. The resulting 83.3% accuracy is satisfactory. © 2018 IEEE

Multisource geophysical investigation of the Acıgöl caldera structure (central Turkey): preliminary results

Neogene and Quaternary volcanic activity formed the large volume ignimbritic units (about 10 different units, namely Cappadocian ignimbritic field) around Nevşehir, Derinkuyu and Acıgöl districts. These large volume ignimbrites are mostly caldera-related products but the calderas are partially or totally buried by later pyroclastic and sedimentary cover. Source estimations for the caldera-related pyroclastics in Nevşehir plateau indicate that the calderas concentrate around Derinkuyu and Acıgöl plains. Geophysical methods (resistivity imaging, self-potential, TDEM and magnetic surveys) were applied around Acıgöl plain and Mt. Erdaş to reveal out the near-surface structural elements related to the Acıgöl caldera system. Additionally, remote sensing coupled with morphology was used. Preliminary results show that the Acıgöl caldera complex may have an elongated shape. Possible structural models for the caldera system/complex are explained. Future geophysical studies and a detailed study of the geological relationship between the caldera-related products are necessary to better understand the Acıgöl caldera system