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Yayın A priority based packet scheduler with deadline considerations(IEEE Computer Soc, 2006) Dağ, Tamer; Gökgöl, OralQoS issues have become a focal point of research on Next Generation Networks (NGNs). In order to supply the various QoS requirement for different kinds of applications, new scheduling policies need to be developed and evaluated. This paper introduces a new kind of packet scheduler which tries to integrate an important QoS parameter (the delay) with the classical schedulers. The two sets of algorithms introduced; Static Priority with Deadline Considerations (SPD) and Dynamic Priority with Deadline Considerations (DPD); not only simplify the complexity and overhead of a classical Earliest Deadline First (EDF) or Static Priority (SP) algorithm, but also provide a better QoS based on the results of the simulations conducted.Yayın Generative and discriminative methods using morphological information for sentence segmentation of Turkish(IEEE-INST Electrical Electronics Engineers Inc, 2009-07) Güz, Ümit; Favre, Benoit; Hakkani Tür, Dilek; Tür, GökhanThis paper presents novel methods for generative, discriminative, and hybrid sequence classification for segmentation of Turkish word sequences into sentences. In the literature, this task is generally solved using statistical models that take advantage of lexical information among others. However, Turkish has a productive morphology that generates a very large vocabulary, making the task much harder. In this paper, we introduce a new set of morphological features, extracted from words and their morphological analyses. We also extend the established method of hidden event language modeling (HELM) to factored hidden event language modeling (fHELM) to handle morphological information. In order to capture non-lexical information, we extract a set of prosodic features, which are mainly motivated from our previous work for other languages. We then employ discriminative classification techniques, boosting and conditional random fields (CRFs), combined with fHELM, for the task of Turkish sentence segmentation.Yayın Construction of a Turkish proposition bank(Tubitak Scientific & Technical Research Council Turkey, 2018) Ak, Koray; Toprak, Cansu; Esgel, Volkan; Yıldız, Olcay TanerThis paper describes our approach to developing the Turkish PropBank by adopting the semantic role-labeling guidelines of the original PropBank and using the translation of the English Penn-TreeBank as a resource. We discuss the semantic annotation process of the PropBank and language-specific cases for Turkish, the tools we have developed for annotation, and quality control for multiuser annotation. In the current phase of the project, more than 9500 sentences are semantically analyzed and predicate-argument information is extracted for 1330 verbs and 1914 verb senses. Our plan is to annotate 17,000 sentences by the end of 2017.Yayın Model adaptation for dialog act tagging(IEEE, 2006) Tür, Gökhan; Güz, Ümit; Hakkani Tür, DilekIn this paper, we analyze the effect of model adaptation for dialog act tagging. The goal of adaptation is to improve the performance of the tagger using out-of-domain data or models. Dialog act tagging aims to provide a basis for further discourse analysis and understanding in conversational speech. In this study we used the ICSI meeting corpus with high-level meeting recognition dialog act (MRDA) tags, that is, question, statement, backchannel, disruptions, and floor grabbers/holders. We performed controlled adaptation experiments using the Switchboard (SWBD) corpus with SWBD-DAMSL tags as the out-of-domain corpus. Our results indicate that we can achieve significantly better dialog act tagging by automatically selecting a subset of the Switchboard corpus and combining the confidences obtained by both in-domain and out-of-domain models via logistic regression, especially when the in-domain data is limited.Yayın Forecasting and analysis of domestic solid waste generation in districts of istanbul with support vector regression(Institute of Electrical and Electronics Engineers Inc., 2020-10-12) Özçelik, Şuayb Talha; Tek, Faik BorayWaste planning is essential for large and developing cities such as Istanbul. In this report, we perform data analysis on "Waste Amount Based on District, Year and Waste Type"dataset shared by Istanbul Metropolitan Municipality. After analyzing the waste of the districts, we used support vector regression (SVR) to forecast the waste amounts for the coming years. The analysis has shown an overall increasing trend in the waste generation, although it dropped in 2019. The SVR predicts that the most waste generating district will be Küçükçekmece in the coming years.Yayın A tree-based approach for English-to-Turkish translation(Tubitak Scientific & Technical Research Council Turkey, 2019) Bakay, Özge; Avar, Begüm; Yıldız, Olcay TanerIn this paper, we present our English-to-Turkish translation methodology, which adopts a tree-based approach. Our approach relies on tree analysis and the application of structural modification rules to get the target side (Turkish) trees from source side (English) ones. We also use morphological analysis to get candidate root words and apply tree-based rules to obtain the agglutinated target words. Compared to earlier work on English-to-Turkish translation using phrase-based models, we have been able to obtain higher BLEU scores in our current study. Our syntactic subtree permutation strategy, combined with a word replacement algorithm, provides a 67% relative improvement from a baseline 12.8 to 21.4 BLEU, all averaged over 10-fold cross-validation. As future work, improvements in choosing the correct senses and structural rules are needed.Yayın EEG signal compression based on classified signature and envelope vector sets(IEEE Computer Society, 2007) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaIn this paper, a novel method to compress ElectroEncephaloGram (EEG) Signal is proposed. The proposed method is based on the generation Classified Signature and Envelope Vector Sets (CSEVS) by using an effective k-means clustering algorithm. In this work on a frame basis, any EEG signal is modeled by multiplying three parameters as called the Classified Signature Vector, Classified Envelope Vector, and Frame-Scaling Coefficient. In this case, EEG signal for each frame is described in terms of the two indices R and K of CSEVS and the frame-scaling coefficient. The proposed method is assessed through the use of root-mean-square error (RMSE) and visual inspection measures. The proposed method achieves good compression ratios with low level reconstruction error while preserving diagnostic information in the reconstructed EEG signal.Yayın QoS-constrained core selection for group communication(IEEE, 2005) Karaman, Ayşe; Hassanein, HossamThe core-based approach in multipoint communication enhances the solution space in terms of QoS-efficiency of solutions in inter and intra-domain routing. In an earlier work [KH04], we showed that the constrained cost minimization solutions in core-based approach proposed to date are restrictive in their search to a subrange of solutions, and we proposed SPAN, a generic framework to process in our identified extended solution space. In this paper, we study the core selection component of SPAN and propose two novel algorithms, SPAN/COST and SPAN/ADJUST, which define the core-selection component of SPAN. SPAN/COST mainly optimizes the cost distances to be traveled between the source-core and core-receiver pairs on the multicast trees, while SPAN/ADJUST selects the cores based on the numbers of nodes they dominate and adjusting the set based on cost. Our algorithms consistently outperform their counterparts proposed to date and can be considered pioneering in their optimization range of multiple metrics and processing in the extended solution space.Yayın Doğrudan pazarlama amaçlı hedef kitle analizi(Institute of Electrical and Electronics Engineers Inc., 2018-07-05) Kegeci, Sinan; Özbek, Eyüp Erkan; Türkel, Mustafa Sertaç; Düzağaç, Remzi; Yıldız, Olcay TanerDoğrudan pazarlama, uygun ürünleri uygun kişilerle en kısa yoldan buluşturma sürecidir. Son yılların en popüler pazarlama yaklaşımlarından birisidir. Bu çalışmada turizm sektörüne ait isimsizleştirilmiş bir veri tabanını kullandık. Bir otel zinciri için yapılan kampanya kapsamında veri madenciliği tekniklerini uygulayarak hedef kitle seçimi yaptık. Çalışmada birçok makine öğrenmesi yöntemini denedik. Sonuç olarak; geçmişte yapılan ve herhangi bir makine öğrenmesi yöntemi kullanılmadan hazırlanan kampanya sonuçlarına göre daha iyi sonuçlar elde ederken benzer analizlerde kullanılabilecek bir altyapı oluşturmuş olduk.
