• Not all mistakes are equal 

  Şensoy, M.; Saleki, Maryam; Julier, S.; Aydoğan, Reyhan; Reid, J. (The ACM Digital Library, 2020)

  In many tasks, classifiers play a fundamental role in the way an agent behaves. Most rational agents collect sensor data from the environment, classify it, and act based on that classification. Recently, deep neural networks ...

• Extraction of novel features based on histograms of mfccs used in emotion classification from generated original speech dataset 

  Pakyurek, M.; Atmış, Mahir; Kulac, S.; Uludag, U. (Kauno Technologijos Universitetas, 2020-02-17)

  This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from ...

• SeCaS: Secure capability sharing framework for IoT devices in a structured P2P network 

  Aktypi, A.; Çakmakçı, Kübra Kalkan; Rasmussen, K. B. (The ACM Digital Library, 2020-03-16)

  The emergence of the internet of Things (IoT) has resulted in the possession of a continuously increasing number of highly heterogeneous connected devices by the same owner. To make full use of the potential of a personal ...

• Description-aware fashion image inpainting with convolutional neural networks in coarse-to-fine manner 

  Kınlı, Osman Furkan; Özcan, Barış; Kıraç, Mustafa Furkan (The ACM Digital Library, 2020-04-14)

  Inpainting a particular missing region in an image is a challenging vision task, and promising improvements on this task have been achieved with the help of the recent developments in vision-related deep learning studies. ...

• Objective and subjective QoE evaluation for adaptive point cloud streaming 

  Van Der Hooft, J.; Vega, M. T.; Timmerer, C.; Beğen, Ali Cengiz; De Turck, F.; Schatz, R. (IEEE, 2020-05)

  Volumetric media has the potential to provide the six degrees of freedom (6DoF) required by truly immersive media. However, achieving 6DoF requires ultra-high bandwidth transmissions, which real-world wide area networks ...

• Foreword 

  Toni, L.; Beğen, Ali Cengiz; Alay, O.; Timmerer, C. (The ACM Digital Library, 2020-05)

  N/A

• When they go high, we go low: low-latency live streaming in dash.js with LoL 

  Lim, M.; Akçay, Mehmet Necmettin; Bentaleb, A.; Beğen, Ali Cengiz; Zimmermann, R. (The ACM Digital Library, 2020-05)

  Live streaming remains a challenge in the adaptive streaming space due to the stringent requirements for not just quality and rebuffering, but also latency. Many solutions have been proposed to tackle streaming in general, ...

• Metadata-based user interface design for enhanced content access and viewing 

  Karmis, A. A.; Derya, A.; Beğen, Ali Cengiz (The ACM Digital Library, 2020-05)

  The nature of viewing is changing due to the huge volumes of content being produced including user content generated by amateurs and the proliferation of personalized services. The type of content being produced is not ...

• HTTP adaptive streaming over multiple network interfaces 

  Kara, Burak; Öztürk, Kemal Sarp; Beğen, Ali Cengiz (The ACM Digital Library, 2020-05)

  Enhancing user experience in streaming applications is an important problem. Delivering the best quality possible for the given network conditions is not an easy task. In the case of a streaming client running in a multi-homed ...

• Language inference with multi-head automata through reinforcement learning 

  Şekerci, Alper; Köken, Özlem Salehi (IEEE, 2020)

  The purpose of this paper is to use reinforcement learning to model learning agents which can recognize formal languages. Agents are modeled as simple multi-head automaton, a new model of finite automaton that uses multiple ...

• Evaluating the performance of apple’s low-latency HLS 

  Durak, Kerem; Akçay, Mehmet Necmettin; Erinç, Yiğit Kemal; Pekel, Boran; Beğen, Ali Cengiz (IEEE, 2020-09-21)

  In its annual developers conference in June 2019, Apple has announced a backwards-compatible extension to its popular HTTP Live Streaming (HLS) protocol to enable low-latency live streaming. This extension offers new ...

• Prioritization of test cases with varying test costs and fault severities for certification testing 

  Dirim, S.; Sözer, Hasan (IEEE, 2020-10)

  We present an industrial case study on the application of test case prioritization techniques in the context of certification testing in consumer electronics domain. Test execution times and fault severities are subject ...

• High-level representations through unconstrained sensorimotor learning 

  Öztürkçü, Özgür Baran; Uğur, E.; Öztop, E. (IEEE, 2020-10-26)

  How the sensorimotor experience of an agent can be organized into abstract symbol-like structures to enable effective planning and control is an open question. In the literature, there are many studies that start by assuming ...

• DPSec: A blockchain-based data plane authentication protocol for SDNs 

  Latah, Majd; Çakmakçı, Kübra Kalkan (IEEE, 2020-11-02)

  Software-Defined Networking (SDN) is a promising networking architecture that enables central management along with network programmability. However, SDN brings additional security threats due to untrusted control and data ...

• Machine learning based activity learning for behavioral contexts in Internet of things (IoT) 

  Safyan, M.; Sarwar, S.; Ul Qayyum, Z.; Iqbal, M.; Li, S. C.; Kashif, Muhammad (Springer Nature, 2020-12)

  Ontology based activity learning models play a vital role in diverse fields of Internet of Things (IoT) such as smart homes, smart hospitals or smart communities etc. The prevalent challenges with ontological models are ...

• Performance analysis of ACTE: A bandwidth prediction method for low-latency chunked streaming 

  Bentaleb, A.; Timmerer, C.; Beğen, Ali Cengiz; Zimmermann, R. (Association for Computing Machinery, Inc, 2020-07)

  HTTP adaptive streaming with chunked transfer encoding can offer low-latency streaming without sacrificing the coding efficiency. This allows media segments to be delivered while still being packaged. However, conventional ...

• Using convolutional neural networks to automate aircraft maintenance visual inspection 

  Doğru, Anıl; Bouarfa, S.; Arizar, R.; Aydoğan, Reyhan (MDPI, 2020-12)

  Convolutional Neural Networks combined with autonomous drones are increasingly seen as enablers of partially automating the aircraft maintenance visual inspection process. Such an innovative concept can have a significant ...

• Metric labeling and semimetric embedding for protein annotation prediction 

  Sefer, Emre; Kingsford, C. (Mary Ann Liebert, Inc., 2020)

  Computational techniques have been successful at predicting protein function from relational data (functional or physical interactions). These techniques have been used to generate hypotheses and to direct experimental ...

• Predicting shuttle arrival time in istanbul 

  Çoban, Selami; Sanchez-Anguix, V.; Aydoğan, Reyhan (Springer Nature, 2020)

  Nowadays, transportation companies look for smart solutions in order to improve quality of their services. Accordingly, an intercity bus company in Istanbul aims to improve their shuttle schedules. This paper proposes ...

• Load and stress testing for SDN’s northbound API 

  Latah, Majd; Toker, L. (Springer Nature, 2020-01)

  In this work, we apply load and stress testing for well-known Software defined networking (SDN) controllers from an SDN application perspective. More precisely, we focus on the communication between the controller and SDN ...

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