Teleiletişim ve Enformatik Teknolojileri Uygulama ve Araştırma Merkezi

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Alper Denli, Cemil Gurbuz, James Mechie and Michael Weber, Preliminary Results of 2-D Modelling Studies From Cyprus Arc ProjectExplosion Seismic Data, EGU General Assembly 2013, held 7-12 April, 2013 in Vienna, Austria, id. EGU2013-188

  • Alper Denli, Cemil Gurbuz, James Mechie and Michael Weber, Crustal Structure of the Central Anatolia – Eastern Mediterrenean, Turkey and Cyprus from Wide-Angle Seismic Data, EGU General Assembly 2016, held 17-22 April, 2016 in Vienna, Austria, id. EGU2016-392

    Defense Jury Members

    1. Prof. Dr. Nurcan Meral Özel Boğaziçi University

    2. Prof. Dr. Hülya Kurt Istanbul Technical University

    3. Prof. Dr. Oğuz Özel Istanbul University

    4. Assist. Prof. Dr. A. Özgün Konca Boğaziçi University

    5. Assist. Prof. Dr. Çağrı Diner Boğaziçi University

    Defense Date: 28.03.2016

    Erinç Dikici
    Thesis Supervisor: Assoc. Prof. Murat Saraçlar

    Discriminative language modeling aims to reduce the error rates by rescoring the output of an automatic speech recognition (ASR) system. Discriminative language model (DLM) training conventionally follows a supervised approach, using acoustic recordings together with their manual transcriptions (reference) as training examples, and the recognition performance is improved with increasing amount of such matched data. In this thesis we investigate the case where matched data for DLM training is limited or not available at all, and explore methods to improve ASR accuracy by incorporating unmatched acoustic and text data that come from separate sources. For semi-supervised training, we utilize weighted finite-state transducer and machine translation based confusion models to generate artificial hypotheses in addition to the real ASR hypotheses. For unsupervised training, we explore target output selection methods to replace the missing reference. We handle discriminative language modeling both as a structured prediction and a reranking problem and employ variants of the perceptron, MIRA and SVM algorithms adapted for both problems. We propose several hypothesis sampling approaches to decrease the complexity of algorithms and to increase the diversity of artificial hypotheses. We obtain significant improvements over baseline ASR accuracy even when there is no transcribed acoustic data available to train the DLM.


    1. Dikici, E., Semerci, M., Saraçlar, M., Alpaydın, E., “Classification and Ranking Approaches to Discriminative Language Modeling for ASR”, IEEE Transactions on Audio, Speech, and Language Processing, Vol. 21, No. 2, pp. 291-300, 2013. (SCI-E)

    2. Dikici, E., Saraçlar, M., “Semi-supervised and unsupervised discriminative language model training for automatic speech recognition”, Elsevier Speech Communication, accepted for publication. (SCI)

    Conferences - International

    1. Dikici, E., Semerci, M., Saraçlar, M., Alpaydın, E., “Data Sampling and Dimensionality Reduction Approaches for Reranking ASR Outputs Using Discriminative Language Models”, 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), pp. 1461-1464, Florence, Italy, 28-31 August 2011.

    2. Çelebi, A., Sak, H., Dikici, E., Saraçlar, M., Lehr, M., Prud’hommeaux, E., Xu, P., Glenn, N., Karakos, D., Khudanpur, S., Roark, B., Sagae, K., Shafran, I., Bikel, D., Callison-Burch, C., Cao, Y., Hall, K., Hasler, E., Koehn, P., Lopez, A., Post, M., Riley, D., “Semi-Supervised Discriminative Language Modeling for Turkish ASR”, 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), pp. 5025-5028, Kyoto, Japan, 25-30 March 2012.

    3. Dikici, E., Çelebi, A., Saraçlar, M., “Performance Comparison of Training Algorithms for Semi-Supervised Discriminative Language Modeling”, 13th Annual Conference of the International Speech Communication Association (Interspeech 2012), pp. 206-209, Portland, OR, USA, 9-13 September 2012.

    4. Dikici, E., Prud’hommeaux, E., Roark, B., Saraçlar, M., “Investigation of MT-based ASR Confusion Models for Semi-Supervised Discriminative Language Modeling”, 14th Annual Conference of the International Speech Communication Association (Interspeech 2013), pp. 1218-1222, Lyon, France, 25-29 August 2013.

    5. Dikici, E., Saraçlar, M., “Unsupervised Training Methods for Discriminative Language Modeling”, 15th Annual Conference of the International Speech Communication Association (Interspeech 2014), pp. 2857-2861, Singapore, 14-18 September 2014.

    6. Dikici, E., Saraçlar, M., “MT-based Artificial Hypothesis Generation for Unsupervised Discriminative Language Modeling”, the 23rd European Signal Processing Conference (EUSIPCO 2015), pp. 1416-1420, Nice, France, 31 August - 4 September 2015.

    7. Dikici, E., Saraçlar, M., E. Arısoy, “A Decade of Discriminative Language Modeling for Automatic Speech Recognition”, Lecture Notes in Artificial Intelligence, vol. 9319, pp. 11-22.

    Conferences - National

    1. Dikici, E., Saraçlar, M., “Curriculum Based Discriminative Language Model Training”, IEEE 21st Signal Processing and Communications Applications Conference (SIU 2013), Girne, North Cyprus, 2013.

    2. Dikici, E., Saraçlar, M., “Unsupervised Discriminative Language Model Training”, IEEE 22nd Signal Processing and Communications Applications Conference (SIU 2014), pp. 1158-1161, Trabzon, Turkey, 2014.

    Defense Jury Members

    1. Assoc. Prof Murat Saraçlar Boğaziçi University

    2. Prof. Ethem Alpaydın Boğaziçi University

    3. Prof. Levent Arslan Boğaziçi University

    4. Assoc. Prof. Hakan Erdoğan Sabancı University

    5. Assoc. Prof Engin Erzin Koç University

    Defense Date: 21.06.2016

    İskender Haydaroğlu

    Thesis Supervisor: Assoc. Prof. Şenol Mutlu


    This thesis covers a novel approach to photovoltaic energy harvesting and optical data transmission in the context of millimeter-scaled smart autonomous microsystems through the use of a single light emitting diode (LED) to both efficiently harvest optical energy and transmit data to enable wireless, batteryless operation. A proof of concept design for demonstrating the viability of the use of a LED in the proposed manner, harvesting optical energy and transmitting a fixed device ID optically through the same LED using a transmitter based on a continually running charge pump is presented. Next, a low voltage temperature sensor design is integrated into the existing design, to prove by example that the harvested voltage from the LED is high enough that it requires no voltage boosting to power essential analog blocks such as sub-bandgap references, oscillators, and comparators, as opposed to integrated CMOS photovoltaic harvesting. Finally, an alternative, energy efficient optical transmitter architecture and a new ultra low power, ultra low energy temperature sensor are designed and integrated into a single chip. The scalable, inverter based switched capacitor boosting transmitter uses the trickle current from the LED to charge its capacitors directly with minimized losses in efficiency, transmitting data with 1 nJ/bit to a receiver designed and built in-house for up to 10 cm distance. The temperature sensor consumes less than 3 µW, features digital offset correction and an adaptive full-partial conversion algorithm to minimize the conversion time, effectively reducing energy per conversion from 0.6 nJ-3 nJ to 0.15 nJ-0.75 nJ. Total power consumption is in the order of 6 µW, harvested by a 0.1 mm2 LED, making the system viable for millimeter-scaled outdoor solar harvesting applications. All three designs were fabricated in UMC 0.18 µm CMOS process and tested in-house.



    1. Haydaroglu, I., Mutlu, S., "Optical Power Delivery and Data Transmission in a Wireless and Batteryless Microsystem Using a Single Light Emitting Diode," in Journal of Microelectromechanical Systems, vol. 24, no. 1, pp. 155-165, Feb. 2015. (SCI-E)

    2. Haydaroglu, I., Ozgun, M.T., Mutlu, S., "Optically Powered Temperature Measuring Circuit with Optical Transmission Using a Single Light Emitting Diode," IEEE Journal of solid State Circuits, submitted. (SCI-E)


    1. Haydaroglu, I., Mutlu, S., "Energy harvesting and data transmitting microsystem using a light emitting diode," Optical MEMS and Nanophotonics (OMN), 2011 International Conference on, Istanbul, 2011, pp. 87-88.

    2. Haydaroglu, I., Ozgun, M., Mutlu, S., “Optical Wireless Transmitter with Concurrent Energy Harvesting”, Presentation at the 2016 International Solid State Circuits Conference (ISSCC) Student Research Preview session (Student work in progress), Jan. 31-Feb. 4, San Francisco, CA.

    Defense Jury Members

    1. Assoc. Prof Şenol Mutlu Boğaziçi University

    2. Prof. Günhan Dündar Boğaziçi University

    3. Asst. Prof. Tamer Özgün Şehir University

    4. Asst. Prof. Ahmet Öncü Boğaziçi University

    5. Asst. Prof. Hakan Doğan Şehir University

    Defense Date: 13.05.2016

    Kübra Kalkan

    Thesis Supervisor: Prof. Fatih Alagöz



    In this thesis, we present filtering based defense mechanisms against Distributed Denial of Service (DDoS) attacks for core networks. Initially, several filtering techniques are analyzed and their advantages and disadvantages are presented. A comparative classification of these methods is provided for security analysts. Classification results suggest that there are a few filtering methods that are both proactive and collaborative. Proactivity provides prevention of attacks before it spreads whereas collaboration enables getting knowledge about different points of the network and deciding filters together. Thus, we proposed a proactive and collaborative model called ScoreForCore. It is a statistical packet based defense mechanism that selects the most appropriate attributes for current attack traffic. Our results suggest that the success of the system’s behavior on legal and attack packets increased considerably. This strategy is also convenient for current emerging technology for core networks, called Software Defined Networking (SDN). It has several problems related to security that are largely induced by the centralized control paradigm. In that regard, DDoS attacks are specifically valid for SDN environment. Several defense mechanisms in SDN environment are analyzed and comparative classification is provided for rendering the current state of the art in the literature. Then, our defense strategy is applied on SDN environment with capable switches. This mechanism’s(SDNScore) results suggest that it gives perfect results for several known attacks and 84% success for an unknown attack. Since there is a trade-off between SDN paradigm and capable switches in SDNScore, we improved it and proposed another model called Joint Entropy based Scoring for SDN (JESS) that carries all burden to the controller and does not need capable switches. The results suggest that it is an elegant defense method for SDN environment.



    1. Kalkan, K. and Alagöz, F. "A distributed filtering mechanism against DDoS attacks: ScoreForCore." Computer Networks 108 (2016): 199-209, 2016.

    2. Kalkan, K., Gür, G., Alagöz, F., "Filtering Based Defense mechanisms against DDoS Attacks: A Survey", accepted by IEEE Systems Journal, 2016.

    3. Kalkan, K., Gür, G., Alagöz, F., "Defense Mechanisms Against DDoS Attacks on SDN Environment", submitted to IEEE Communications Magazine, 2016.

    4. Kalkan, K., Altay, L., Gür, G.,Alagöz, F., "Joint Entropy based Scoring against DDoS attacks in SDN environment: JESS", in progress for submission to IEEE/ACM Transactions on Networking, 2016.


    1. Kalkan, K., Gür, G., Alagöz, F., "SDNScore: A Statistical Defense Mechanism Against DDoS Attacks in SDN Environment", submitted to IEEE ICC 2016, Paris, France, 21-25 Mayıs 2017.

    Defense Jury Members

    1. Prof. Fatih Alagöz Boğaziçi University

    2. Prof. M. Ufuk Çağlayan Boğaziçi University

    3. Prof. Albert Levi Sabancı University

    4. Prof. Sema Oktuğ İstanbul Technical University

    5. Prof. Tuna Tuğcu Boğaziçi University

    Defense Date: 07.10.2016

    Özlem Özmen Okur
    Thesis Supervisor: Prof. Dr. Cengizhan Öztürk



    Voxel Based Morphometry, VBM, is one of the most widely used brain morphometry methods which aims to reveal the structural differences between the brain MR images of different populations. It is a whole brain and fully automatic approach in which all the images are registered onto a common template and then segmented into grey matter, white matter and cerebrospinal fluid. After an optional modulation step (regaining the original volume which is shrinked or enlarged during the registration), smoothing takes place in order to make the data more normally distributed and to diminish the inexact nature of the nonlinear registration. Finally, voxel-wise statistical operations are performed between the groups of the images. As revealed in several studies, changes in these steps and changes in their parameters might influence the resulting statistics. Although some short guidelines exist for conducting the processing stages, this thesis tries to explain each main step and gathers the discussions in the literature to make the VBM users aware of some pitfalls and limitations of VBM; and also gives brief descriptions about the other brain morphometry methods to give a view for where VBM stands at. In this thesis, the effect of modulation and masking strategy at the statistical stage were studied and concluded that not using the modulation and using average-based masking for the statistical part increased the detection power of VBM. Additionally, within the scope of this thesis, three clinical applications of VBM are performed and presented: Comparisons of the brain images of mathematicians, SSPE patients, and solvent abusers vs healthy controls.



    1. Effects of Unmodulation and Thresholding by Average-Based Masking on Voxel-based Mor- phometry: O. Ozmen Okur, C. Ozturk, Journal of Medical Imaging and Health Informatics, 2016. (submitted) (SCI-E)

    2. Reduced Gray Matter Volume in the Frontotemporal Cortex of Patients with Early Subacute Sclerosing Panencephalitis: K. Aydin, O. Ozmen Okur, B. Tatli, SG. Sarwar, C. Ozturk, C. Dilber, American Journal of Neuroradiology, vol.30(2), pp.271-75, 2009. (SCI)

    3. SmallerGrayMatterVolumesinFrontalandParietalCorticesofSolventAbusersCorrelatewith Cognitive Deficits: K. Aydin, S. Kircan, S. Sarwarb, O. Ozmen Okur, E. Balaban, American Journal of Neuroradiology, vol.30(10), pp.1922-1928, 2009. (SCI)

    4. Increased Gray Matter Density Density in the Parietal Cortex of Mathematicians: K. Aydin, A. Ucar, K.K. Oguz, O. Ozmen Okur, A. Agayev, Z. Unal, S. Yilmaz, C. Ozturk, American Journal of Neuroradiology, vol.28, pp. 1859-1900, 2007. (SCI)


    1. Effects of the Modulation in the White Matter Voxel Based Morphometry: O. Ozmen Okur, C. Ozturk, K. Aydin, Proceedings, International Society for Magnetic Resonance in Medicine, 17, 4685, Honolulu, USA, 2009.

    2. Evaluation of non-rigid registration of SPM5 in normal children: O. Ozmen Okur, K. Aydin, C. Ozturk, Proceedings of 25th Annual Meeting of ESMRMB, Valencia, Spain, 2008.

    3. Morphological Differences in the Grey Matters of Mathematicians: A Voxel-Based Morphome- try Study: O. Ozmen Okur, A. Agayev, C. Ozturk, K. Aydin Proceedings, International Society for Magnetic Resonance in Medicine, Berlin, Germany, May 2007.

    4. Comparison of SPM and Freesurfer Brain Morphometry Analyses Results: Ozmen Okur, O., Ozturk, C., Aydin, K., Proceedings of 14th National Biomedical Engineering Conference: BIYOMUT 2009, Izmir, 2009.

    Defense Jury Members

    1. Prof. Dr. Cengizhan Öztürk Boğaziçi University

    2. Prof. Dr. Tamer Demiralp İstanbul University

    3. Prof. Dr. Alp Dinçer Acıbadem University

    4. Assoc. Dr. Albert Güveniş Boğaziçi University

    5. Asst. Prof. Dr. Özgür Kocatürk Boğaziçi University

    Defense Date: 31.08.2016

    Seda Yelkenci
    Thesis Supervisor: Prof. Dr. Mustafa Aktar

    Modelling 3D Seismic Wave Propagation in Marmara Region


    This study focuses on the modeling of 3D seismic wave propagation in the east of the Marmara Sea in particular for the city of Istanbul, which is identified as one of the megacities with the highest seismic risk in the world. For the first time, an attempt is made for creating a 3D seismic model and for testing the new model with real data. In the frame of constructing 3D velocity model, previous crustal studies of Marmara region and all other available field data, including surface and borehole measurements, are compiled to form a collection of 1D models. Each 1D model relates to a specific location point inside the study area. We have used interpolation methods, in particular Delaunay triangles approach, in order to fill in the no-data zones, which separate the 1D observation points.

    Elastic wave propagation is simulated inside the newly created 3D model using finite difference approach. An open source code called Wave Propagation Program (WPP), which operates on parallel processing environment, is used for that purpose. We have tested the performance of the 3D model with real data using the earthquake of September 29, 2004 (Ml=4.1) occurred in Çınarcık Basin, which was recorded by 18 permanent broadband stations and 100 strong motion stations. A detailed analysis of the source properties of the event is done, both for the location and the fault plane solution. Real and synthetic waveforms are compared both in time and frequency domains. Matching of the waveform shapes are studied in detail. In each case improvement of 3D model over 1D counterpart is discussed. A more quantitative evaluation of 1D and 3D performances is carried out using waveform correlation. The final result shows that a considerable improvement is achieved with 3D model both in terms of amplitudes and P and S arrival times. The finite difference method is also applied to specified basin structures filled with soft sediments of low shear velocities. Sabiha Gökçen Airport area in Pendik, is studied in detail because its basement geometry and sedimentary cover are well-known. The analysis, performed both in the time and frequency domain, helps to understand the characteristics of the 3D wave propagation inside the basin and the site effects related to it.


    1. Seda Yelkenci and Mustafa Aktar, “Simulating Seismic Wave Propagation in 3-D Structure: A Case Study for Istanbul City”, European Geosciense Union, EGU, April 2013, Vienna, Austria.

    2. Seda Yelkenci and Mustafa Aktar, “Wave Propagation Properties and Site Amplification In Major Sedimentary Basins In Istanbul City”, European Seismological Commission, ESC, August 2012, Moscow, Russia.

    3. Seda Yelkenci and Mustafa Aktar, “Three-Dimensional Modeling of Wave Propagation In Sedimentary Basins Around Marmara Region”, American Geophysical Union, AGU, December 2011, San Fransisco, USA.

    4. Seda Yelkenci and Mustafa Aktar, “Marmara Bölgesi için Üç Boyutlu Dalga Yayılımı Modellemesi”, Birinci Türkiye Deprem Mühendisliği ve Sismoloji Konferansı, 1. TDMSK, Ekim 2011, Ankara,Türkiye.

    Defense Jury Members

    1. Prof. Mustafa Aktar Boğaziçi University

    2. Prof. Semih Ergintav Boğaziçi University

    3. Assoc. Prof. A. Özgün Konca Boğaziçi University

    4. Prof. Argun Kocaoğlu Istanbul Technical University

    5. Assoc. Prof. Tuna Eken Istanbul Technical University

    Defense Date: 25.05.2016

    Aykut Yiğitel
    Thesis Supervisors: Prof. Dr. Cem Ersoy ve Y. Doç. Dr. Özlem Durmaz İncel




    Increasing energy costs drive the telecommunication service providers to become highly interested in energy efficient operations. The exponential growth in mobile dataexchange which is further augmented by the rapid proliferation of smart phones increases the operational expenses of the cellular network operators significantly. Also, ecologists state that the primary triggering factor of the global warming is adding excessive amounts of greenhouse gases to the atmosphere and 72% of the totally emitted greenhouse gases is carbon dioxide (CO2). Increasing environmental awareness combined with the high energy prices has driven the network operators to reduce their CO2 footprint by adopting energy efficient green methods. In this thesis, our main focus is to save energy in three types of wireless cellular networks (i) Conventional Cellular Networks (ii) Packet-switched Cellular Networks and (iii) Next Generation Multi-tier Cellular Networks. We formulate novel mathematical optimization problems for each of the listed cellular networks to find the best possible topology which minimizes the overall power consumption of the network while satisfying a certain quality of service level. Our decision variables in the optimization models are switching base stations on/off and adaptively adjusting their transmission power levels as well as deploying additional pico base stations as a remedy according to the present traffic conditions. Although the optimization tools provide the optimum solutions for smaller instances of the problem, we propose novel heuristics to solve large-scale realistic instances due to their prohibitive complexity. Results of extensive simulations, which are designed as close to real life conditions as possible, show that the proposed green methods help to maintain an energy-aware network and save significant amount of energy by adjusting the network topology to the current traffic conditions adaptively.


    1. M. Aykut Yigitel, Ozlem Durmaz Incel and Cem Ersoy, Green BS Deployment and Management for Next Generation Heterogeneous Networks: A Case Study, IEEE Journal on Selected Areas In Communications, Special Issue: Green Communications and Networking, (In Preparation).

    2. M. Aykut Yigitel, Ozlem Durmaz Incel and Cem Ersoy, QoS vs. Energy: A Traffic-aware Topology Management Scheme for Green Heterogeneous Networks, Computer Networks (Elsevier), Special Issue: Green Communications, vol. 78, pp. 130-139, February 2015. DOI: 10.1016/j.comnet.2014.10.030.

    3. M. Aykut Yigitel, Ozlem Durmaz Incel and Cem Ersoy, Dynamic Base Station Planning with Power Adaptation for Green Wireless Cellular Access Networks, EURASIP Journal on Wireless Communications and Networking, vol. 2014, no. 77 , May 2014. DOI: 10.1186/1687-1499-2014-77.

    4. M. Aykut Yigitel, Ozlem Durmaz Incel and Cem Ersoy, Design and Implementation of a QoS-aware MAC Protocol for Wireless Multimedia Sensor Networks, Computer Communications (Elsevier), vol.34, no. 16, pp. 1991-2001, October 2011. DOI: 10.1016/j.comcom.2011.06.006.

    5. M. Aykut Yigitel, Ozlem Durmaz Incel and Cem Ersoy, QoS-Aware MAC Protocols for Wireless Sensor Networks: A Survey, Computer Networks (Elsevier), vol. 55, no. 8, pp. 1982-2004, June 2011. DOI: 10.1016/j.comnet.2011.02.007.

    International Conferences

    1. M. Aykut Yigitel, H. Birkan Yilmaz, and Tuna Tugcu, A Routing Protocol with Service Differentiation for Heterogeneous Wireless Sensor Networks, Proceedings of the International Workshop on Multi-Sensor Systems and Networks for Fire Detection and Management, Antalya, Turkey, 8-9 November 2012.

    2. M. Aykut Yigitel, Ozlem Durmaz Incel, Cem Ersoy, Diff-MAC: A QoS-Aware MAC Protocol with Differentiated Services and Hybrid Prioritization for Wireless Multimedia Sensor Networks, Proceedings of the 6th ACM Symposium on Quality of Service and Security for Wireless and Mobile Networks (Q2SWinet’10), pp. 62-69, Bodrum, Turkey, 17-21 October 2010. (Best Paper Award) DOI:10.1145/1868630.1868642.

    3. M. Aykut Yigitel, Tolga Tolgay, Cem Ersoy, On-Demand Coverage Problem in Wireless Video Sensor Networks, Proceedings of the 8th International Symposium On Computer Networks (ISCN’08), pp. 170-176, Istanbul, Turkey, 18-20 June 2008.

    Local Conferences

    1. M. Aykut Yigitel, Ozlem Durmaz Incel ve Cem Ersoy, Yeşil Hücresel Ağlara Hızlı Bir Bakış: Baz İstasyonlarının Enerji Tasarrufundaki Önemi, Akademik Bilişim’13, Antalya, 23-25 Ocak 2013.

    2. M. Aykut Yigitel, Tolga Tolgay, Cem Ersoy, Kablosuz Algılayıcı Ağlarda Devingen Kapsama Sorunu İçin Evrimsel Algoritma, Akademik Bilişim’08, Çanakkale, Ocak 2008.

    Defense Jury Members

    Prof. Cem Ersoy Boğaziçi University

    Assist Prof. Özlem Durmaz İncel Galatasaray University

    Prof. Necati Aras Boğaziçi University

    Prof. Can Özturan Boğaziçi University

    Prof. Tuna Tuğcu Boğaziçi University

    Assoc. Prof. Ayşegül Gençata Yayımlı İstanbul Teknik University

    Defense Date: 19.01.2016
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