Research Outputs

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    A deterministic analysis of an online convex mixture of experts algorithm
    (Institute of Electrical and Electronics Engineers (IEEE), 2015) Özkan, Hüseyin; Dönmez, Mehmet A.; N/A; Tunç, Sait; Master Student; Graduate School of Sciences and Engineering; N/A
    We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to estimate an unknown desired signal. This online learning algorithm is shown to achieve and in some cases outperform the mean-square error (MSE) performance of the best constituent algorithm in the steady state. However, the MSE analysis of this algorithm in the literature uses approximations and relies on statistical models on the underlying signals. Hence, such an analysis may not be useful or valid for signals generated by various real-life systems that show high degrees of nonstationarity, limit cycles and that are even chaotic in many cases. In this brief, we produce results in an individual sequence manner. In particular, we relate the time-accumulated squared estimation error of this online algorithm at any time over any interval to the one of the optimal convex mixture of the constituent algorithms directly tuned to the underlying signal in a deterministic sense without any statistical assumptions. In this sense, our analysis provides the transient, steady-state, and tracking behavior of this algorithm in a strong sense without any approximations in the derivations or statistical assumptions on the underlying signals such that our results are guaranteed to hold. We illustrate the introduced results through examples.
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    A novel economic-based scheduling heuristic for computational grids
    (Sage Publications Ltd, 2007) N/A; Department of Computer Engineering; Sönmez, Ömer Ozan; Gürsoy, Attila; Master Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 8745
    In the economic-based computational grids we need effective schedulers not only to minimize the makespan but also to minimize the costs that are spent for the execution of the jobs. in this work, A novel economy driven job scheduling heuristic is proposed and a simulation application is developed by using GridSim toolkit to investigate the performance of the heuristic. the simulation-based experiments demonstrate the effectiveness of the proposed heuristic both in terms of parameter sweep and sequential workflow type of applications.
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    A virtual reality toolkit for path planning and manipulation at nano-scale
    (IEEE Computer Soc, 2006) N/A; N/A; Department of Mechanical Engineering; Varol, Aydın; Günev, İhsan; Başdoğan, Çağatay; Master Student; Master Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 125489
    A virtual reality (VR) toolkit that integrates the human operator into a virtual environment by means of visual and haptic feedback has been developed to design and test manipulation strategies at nano-scale. Currently, the toolkit is capable of modeling the mechanistic interactions between an AFM tip and spherical particles on a substrate surface and generating optimum manipulation paths using a potential field approach. In addition, haptic fixtures were designed to guide the user to follow the calculated paths.
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    An adaptive and diversified vehicle routing approach to reducing the security risk of cash-in-transit operations
    (Wiley, 2017) Bozkaya, Burçin; Department of Industrial Engineering; N/A; Salman, Fatma Sibel; Telciler, Kaan; Faculty Member; Master Student; Department of Industrial Engineering; College of Engineering; Graduate School of Sciences and Engineering; 178838; N/A
    We consider the route optimization problem of transporting valuables in cash-in-transit (CIT) operations. The problem arises as a rich variant of the capacitated vehicle routing problem (CVRP) with time windows and pickup and deliveries. Due to the high-risk nature of this operation (e.g., robberies) we consider a bi-objective function where we attempt to minimize the total transportation cost and the security risk of transporting valuables along the designed routes. For risk minimization, we propose a composite risk measure that is a weighted sum of two risk components: (i) following the same or very similar routes, and (ii) visiting neighborhoods with low socioeconomic status along the routes. We also consider vehicle capacities in terms of monetary value carried as per insurance regulations. We develop an adaptive randomized bi-objective path selection algorithm that uses the composite risk measure in choosing alternative paths between origin-destination pairs over a sequence of days. We solve the rich CVRP approximately for each day with updated costs. We test our solution approach on a data set from a CIT delivery service provider and provide insights on how the routes diversify daily. Our approach generates a spectrum of solutions with costrisk trade-off to support decision making.
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    Broadcasting brake lights with MIMO-OFDM based vehicular VLC
    (IEEE Computer Society, 2016) Narmanloğlu, Ömer; Uysal, Murat; N/A; Department of Electrical and Electronics Engineering; Turan, Buğra; Ergen, Sinem Çöleri; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 7211
    Inter-vehicular connectivity to enhance road safety and enable highly autonomous driving is increasingly becoming popular. Despite the prevalent works on radio-frequency (RF) based vehicular communication schemes, visible light communication (VLC) is considered to be a promising candidate for vehicular communications due to its low complexity and RF interference-free nature. This paper investigates applicability of VLC to enhance road safety based on real world measurements. Deployment of multiple light emitting diodes (LEDs) enables multiple-input multiple-output (MIMO) transmission in the context of vehicular VLC. We consider direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) based MIMO transmission scheme and evaluate the performances of different MIMO modes including repetition code (RC) and spatial multiplexing (SM), different modulation orders and different transmitter-receiver selection. The results reveal that selection of the closest transmitters to the receivers, provide better performance due to high signal-to-noise-ratio (SNR) requirements for RC mode. However, usage of all possible transmitters does not always yield better performance due to power division at the transmitter side. Moreover, SM suffers from channel correlation whereas the performance of RC shows more degradation on higher-order modulations that are required to yield the same throughput with SM.
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    Data-driven abnormal behavior detection for autonomous platoon
    (IEEE Computer Society, 2018) N/A; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Uçar, Seyhan; Ergen, Sinem Çöleri; Özkasap, Öznur; PhD Student; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 7211; 113507
    Autonomous platoon is a technique where co-operative adaptive cruise control (CACC) enabled vehicles are organized into groups of close following vehicles through communication. It is envisioned that with the increased demand for autonomous vehicles, platoons would be a part of our life in near future. Although many efforts have been devoted to implement the vehicle platooning, ensuring the security remains challenging. Due to lack of security, platoons would be subject to modified packets which can mislead the platoon and result in platoon instability. Therefore, identifying malicious vehicles has become an important requirement. In this paper, we investigate a data-driven abnormal behavior detection approach for an autonomous platoon. We propose a novel statistical learning based technique to detect data anomalies. We demonstrate that shared speed value among platoon members would be sufficient to detect the misbehaving vehicles.
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    Detection of food intake events from throat microphone recordings using convolutional neural networks
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) N/A; Department of Computer Engineering; Turan, Mehmet Ali Tuğtekin; Erzin, Engin; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 34503
    Food intake analysis is a crucial step to develop an automated dietary monitoring system. Processing of eating sounds deliver important cues for the food intake monitoring. Recent studies on detection of eating activity generally utilize multimodal data from multiple sensors with conventional feature engineering techniques. In this study, we target to develop a methodology for detection of ingestion sounds, namely swallowing and chewing, from the recorded food intake sounds during a meal. Our methodology relies on feature learning in the frequency domain using a convolutional neural network (CNN). Spectrograms extracted from the recorded food intake sounds through a laryngeal throat microphone are fed in to the CNN architecture. Experimental evaluations are performed on our in-house food intake dataset, which includes 8 subject, 10 different food types covering 276 minutes of recordings. The proposed system attains high detection rates of the swallow and chew events with high sensitivity and specificity, and delivers a potential for food intake monitoring under daily life conditions in future studies.
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    Dimming support for visible light communication in intelligent transportation and traffic system
    (Ieee, 2016) N/A; N/A; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Uçar, Seyhan; Turan, Buğra; Ergen, Sinem Çöleri; Özkasap, Öznur; Ergen, Mustafa; PhD Student; PhD Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; N/A; 7211; 113507; N/A
    The automotive industry is under a major change and new vehicles are being enriched by the recent advances in communication. Not only business plans are changing due to connected and urbanized lifestyle, but also transportation is becoming more intelligent with smart roads that connect smart cars. Technology coined as the vehicular ad-hoc network (VANET) is harmonizing with Intelligent Transportation System (ITS) and Intelligent Traffic System (ITF). However, ITS and ITF systems suffer from the scarcity of radio frequency spectrum. Visible light communication (VLC) that uses modulated optical radiation in the visible light spectrum is an alternative medium being researched. To date, the majority of research on vehicular VLC was aimed at achieving high data rates provided that high lighting quality is achieved without any concern on dimmable LED lights. Auto-dimmable headlights gain attention due to danger caused by sudden glare on drivers at night conditions which makes dimming in VLC necessary. In this paper, we first present the latest concept of vehicular VLC on ITS and ITF systems and address dimming utility. We then demonstrate experimentally that dimming is a key parameter in VLC which affects data dissemination and received power signal strength.
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    Dimming support for visible light communication in intelligent transportation and traffic system
    (Institute of Electrical and Electronics Engineers (IEEE), 2016) N/A; N/A; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Uçar, Seyhan; Turan, Buğra; Ergen, Sinem Çöleri; Özkasap, Öznur; Ergen, Mustafa; PhD Student; PhD Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; N/A; 7211; 113507; N/A
    The automotive industry is under a major change and new vehicles are being enriched by the recent advances in communication. Not only business plans are changing due to connected and urbanized lifestyle, but also transportation is becoming more intelligent with smart roads that connect smart cars. Technology coined as the vehicular ad-hoc network (VANET) is harmonizing with Intelligent Transportation System (ITS) and Intelligent Traffic System (ITF). However, ITS and ITF systems suffer from the scarcity of radio frequency spectrum. Visible light communication (VLC) that uses modulated optical radiation in the visible light spectrum is an alternative medium being researched. To date, the majority of research on vehicular VLC was aimed at achieving high data rates provided that high lighting quality is achieved without any concern on dimmable LED lights. Auto-dimmable headlights gain attention due to danger caused by sudden glare on drivers at night conditions which makes dimming in VLC necessary. In this paper, we first present the latest concept of vehicular VLC on ITS and ITF systems and address dimming utility. We then demonstrate experimentally that dimming is a key parameter in VLC which affects data dissemination and received power signal strength.
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    Distributed management of service-enabled flow-paths across multiple SDN domains
    (IEEE, 2015) Civanlar, Seyhan; Lokman, Erhan; Kaytaz, Bülent; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207
    Future Internet may be comprised of interconnected multiple software-defined networks (SDN), where each domain is administered by a different controller or control plane. Provisioning of an end-to-end flow-path across such a network with specific service levels requires collaboration between domain controllers across control planes. A service-enabled flow-path shall be quality of service (QoS) enabled, reliable and/or secure, which requires a transport path with certain quantitative service level requirements such as high throughput, low packet loss, or high availability. Each SDN controller can autonomously determine such end-to-end flow-paths when all other SDN controllers periodically advertise to other controllers its available service-enabled paths. Doing so, each SDN controller is presented with several service-enabled path alternatives, crossing other domains, to choose from. We propose a multi-domain SDN controller design, wherein each SDN controller shares its network's "summarized" topology of service-enabled paths with other SDN controllers, such that all domains (controllers) have real-time autonomous decision making capability for end-to-end flow-path selection. We also describe how an SDN controller can reserve and release a flow traversing other SDN domains.