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Publication Metadata only Automatic melodic segmentation of Turkish makam music scores(IEEE, 2014) Bozkurt, Baris; Karaali, Bilge; Karaosmanoglu, M. Kemal; Unal, Erdem; Bahcesehir University; Izmir Institute of Technology; Yildiz Technical University; Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)Automatic melodic segmentation is one of the important steps in computational analysis of melodic content from symbolic data This widely studied research problem has been very rarely considered for Turkish makam music. In this paper we first present test results for state-of-the-art techniques from literature on Turkish makam music data Then, we present a statistical classification-based segmentation system that exploits the link between makant melodies and usul and makam scale hierarchies together with the well-known features in literature. We show through tests on a large dataset that the proposed system has a higher accuracy.Publication Metadata only Dendritic Spine Shape Classification from Two-Photon Microscopy Images(IEEE, 2015) Ghani, Muhammad Usman; Kanik, Sumeyra Demir; Argunsah, Ali Ozgur; Tasdizen, Tolga; Unay, Devrim; Cetin, Mujdat; Sabanci University; Fundacao Champalimaud; Utah System of Higher Education; University of Utah; Bahcesehir UniversityFunctional properties of a neuron are coupled with its morphology, particularly the morphology of dendritic spines. Spine volume has been used as the primary morphological parameter in order the characterize the structure and function coupling. However, this reductionist approach neglects the rich shape repertoire of dendritic spines. First step to incorporate spine shape information into functional coupling is classifying main spine shapes that were proposed in the literature. Due to the lack of reliable and fully automatic tools to analyze the morphology of the spines, such analysis is often performed manually, which is a laborious and time intensive task and prone to subjectivity. In this paper we present an automated approach to extract features using basic image processing techniques, and classify spines into mushroom or stubby by applying machine learning algorithms. Out of 50 manually segmented mushroom and stubby spines, Support Vector Machine was able to classify 98% of the spines correctly.Publication Metadata only Coupled Shape Priors for Dynamic Segmentation of Dendritic Spines(IEEE, 2017) Atabakilachini, Naeimeh; Erdil, Ertunc; Argunsah, A. Ozgur; Rada, Lavdie; Unay, Devrim; Cetin, Mujdat; Sabanci University; University of Zurich; Bahcesehir University; Izmir Ekonomi UniversitesiSegmentation of biomedical images is a challenging task, especially when there is low quality or missing data. The use of prior information can provide significant assistance for obtaining more accurate results. In this paper we propose a new approach for dendritic spine segmentation from microscopic images over time, which is motivated by incorporating shape information from previous time points to segment a spine in the current time point. In particular, using a training set consisting of spines in two consecutive time points to construct coupled shape priors, and given the segmentation in the previous time point, we can improve the segmentation process of the spine in the current time point. Our approach has been evaluated on 2-photon microscopy images of dendritic spines and its effectiveness has been demonstrated by both visual and quantitative results.Publication Metadata only From Asia to Europe: Short-Term Traffic Flow Prediction Between Continents(IEEE, 2014) Kaya, Sevgi; Kilic, Necati; Kocak, Taskin; Gungor, Cagri; Swiss Federal Institutes of Technology Domain; ETH Zurich; Bahcesehir UniversityModelling the traffic flow and predicting the near-future traffic status are two challenging problems of the smart transportation on roads. The difficulty is particularly pronounced in forecasting the complex non-linear dynamics of flow. Most of the state-of-the-art work on traffic flow prediction determine the parameters based on the fundamental relationship between flow, density and speed without considering its influence to the consecutive one. However, these approaches tend to fail in real life scenarios due to the negligence of the spatio-temporal dependence of parameters within road segments. In this paper, we propose a new traffic flow model to predict the arterial travel time using probe data. We then evaluate our model under various traffic conditions to determine its feasibility for near-future traffic flow prediction. The proposed method presents promising results by outperforming the state-of-the-art in predicting near-future traffic flow on roads in case of sparse data and high flow density.Publication Metadata only Age of Information Scaling in Large Networks with Hierarchical Cooperation(IEEE, 2019) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityGiven n randomly located source-destination (S-D) pairs on a fixed area network that want to communicate with each other, we study the age of information with a particular focus on its scaling as the network size n grows. We propose a three-phase transmission scheme that utilizes hierarchical cooperation between users along with mega update packets and show that an average age scaling of O(n(alpha(h)) log n) per-user is achievable where h denotes the number of hierarchy levels and alpha(h) = 1/3.2(h)+1 which tends to 0 as h increases such that asymptotically average age scaling of the proposed scheme is O(log n). To the best of our knowledge, this is the best average age scaling result in a status update system with multiple S-D pairs.Publication Metadata only Age of Information Scaling in Large Networks(IEEE, 2019) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityWe study age of information in a multiple source-multiple destination setting with a focus on its scaling in large wireless networks. There are n nodes that are randomly paired with each other on a fixed area to form n source-destination (SD) pairs. We propose a three-phase transmission scheme which utilizes local cooperation between the nodes by forming what we call mega update packets to serve multiple S-D pairs at once. We show that under the proposed scheme average age of an S-D pair scales as O(n(1/4) log n) as the number of users, n, in the network grows. To the best of our knowledge, this is the best age scaling result for a multiple source-multiple destination setting.Publication Metadata only Age of Information in Multicast Networks with Multiple Update Streams(IEEE, 2019) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; Matthews, MB; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityWe consider the age of information in a multicast network where there is a single source node that sends time-sensitive updates to n receiver nodes. Each status update is one of two kinds: type I or type II. To study the age of information experienced by the receiver nodes for both types of updates, we consider two cases: update streams are generated by the source node at-will and update streams arrive exogenously to the source node. We show that using an earliest k(1) and k(2) transmission scheme for type I and type II updates, respectively, the age of information of both update streams at the receiver nodes can be made a constant independent of n. In particular, the source node transmits each type I update packet to the earliest k(1) and each type II update packet to the earliest k(2) of n receiver nodes. We determine the optimum k(1) and k(2) stopping thresholds for arbitrary shifted exponential link delays to individually and jointly minimize the average age of both update streams and characterize the pareto optimal curve for the two ages.Publication Metadata only Performance Evaluation of Background Subtraction Algorithms for Android Devices Deployed in Wireless Multimedia Sensor Networks(IEEE, 2014) Sarisaray-Boluk, Pinar; Akkaya, Kemal; Bahcesehir University; Southern Illinois University System; Southern Illinois UniversityWith the increased use of smart phones, Wireless Multimedia Sensor Networks (WMSNs) will have opportunities to deploy such devices in several contexts for data collection and processing. While smart phones come with richer resources and can do complex processing, their battery is still limited. Therefore, data reduction techniques can be used on these devices to reduce energy consumption. One of the common techniques for energy reduction is background subtraction, which has been used for camera sensors in WMSNs. In this paper, we investigate the performance of various BS algorithms on Android devices in terms of computation and communication energy, time and quality. To this end, we picked five different BS algorithms and implemented them in an Android platform. Considering the fact that these BS algorithms will be run within the context of WMSNs where the data is subject to packet losses and errors, we also investigated the performance in terms of packet loss ratio in the network under various packet sizes. The experiment results indicated that the most energy-efficient BS algorithm could also provide the best quality in terms of the foreground detected. The results also indicate that BS algorithms can provide significant energy savings in terms of transmission energy costs.Publication Metadata only Age of Information in Two-Hop Multicast Networks(IEEE, 2018) Buyukates, Baturalp; Soysal, Alkan; Ulukus, Sennur; Matthews, MB; University System of Maryland; University of Maryland College Park; Bahcesehir UniversityWe consider the age of information in a two-hop multicast network where there is a single source node sending lime-sensitive updates to n(2) end nodes through 11, middle nodes. In the first hop, the source node sends updates to n middle nodes, and in the second hop each middle node relays the update packets that it receives to n end users that are connected to it. We study the age of information experienced by the end nodes, and in particular, its scaling as a function of n. We show that, using an earliest Is transmission scheme, the age of information at the end nodes can be made a constant independent of n. In particular, the source node transmits each update packet to the earliest k(1) of the n middle nodes, and each middle node that receives the update relays it to the earliest k(2) out of 'n end nodes that are connected to it. We determine the optimum k(1) and k(2) stopping values for arbitrary shifted exponential link delays.Publication Metadata only Age of Information in G/G/1/1 Systems(IEEE, 2019) Soysal, Alkan; Ulukus, Sennur; Matthews, MB; Bahcesehir University; University System of Maryland; University of Maryland College ParkWe consider a single server communication setting where the interarrival times of data updates at the source node and the service times to the destination node are arbitrarily distributed. We consider two service discipline models. In the first model, if a new update arrives when the service is busy, it is blocked, in the second model, a new update preempts the current update in service. For both models, we derive exact expressions for the age of information metric with no restriction on the distributions of interarrival and service times. In addition, we derive upper bounds that are easier to calculate than the exact expressions. In the case with blocking, we also derive a second upper bound by utilizing stochastic ordering if the interarrival and service times have log-concave distribution.