% Year: 2019 % Encoding: utf-8 @Article{vanderHooft2019, author = {van der Hooft, Jeroen and Torres Vega, Maria and Wauters, Tim and Ravuri, Hemanth Kumar and Timmerer, C. and Hellwagner, Hermann and De Turck, Filip}, journal = {IEEE COMSOC MMTC COMMUNICATIONS - FRONTIERS}, title = {{Towards 6DoF virtual reality video streaming: status and challenges}}, year = {2019}, month = sep, number = {5}, pages = {30--37}, volume = {14}, abstract = {In the last few years, delivery of immersive video with six degrees of freedom (6DoF) has become an important topic for content providers. Recent technological advancements have resulted in affordable head-mounted displays, allowing a broad range of users to enjoy Virtual Reality (VR) content. Service providers such as Facebook1and YouTube2were among the first to provide 360°video, using the principle of HTTP Adaptive Streaming (HAS) to deliver the content to the enduser. In HAS, the content is encoded using several quality representations, temporally segmented into chunks of one to ten seconds and stored on one or multiple servers within a content delivery network. Based on the perceived network conditions, the device characteristics, and the user's preferences, the client can then decide on the quality of each of these segments[1]. Having the ability to adapt the video quality, this approach actively avoids buffer starvation, and therefore results in smoother playback of the requested content and a higher Quality of Experience (QoE) for the end user[2]. The introduction of 360° video provides the user with three degrees of freedom to move within an immersive world, allowing changes in the yaw, roll, and pitch.In the last few years, multiple solutions have been proposed to efficiently deliver VR content through HAS, focusing, for instance, on foveas-and tile-based encoding, improved viewport prediction (i.e., prediction of the user’s head movement in the near future in order to buffer useful high-quality content), and application layer optimizations [3]. In these works, however, the location of the user remains fixed to the position of the camera within the scene. Recently, significant research efforts have been made to realize 6DoF for streamed video content, i.e., the user may experience three additional degrees of freedom by being able to change the viewing position in a video scene. These efforts are promising, but significant research contributions will be required in order to realize its full potential. In this paper, an overview of existing 6DoF solutions is presented, and key challenges and opportunities are highlighted.}, language = {{eng}}, url = {https://biblio.ugent.be/publication/8666820/file/8716606} } @InProceedings{Zabrovskiy2019, author = {Midoglu, Cise and Zabrovskiy, Anatoliy and Alay, Ozgu and Hoelbling-Inzko, Daniel and Griwodz, Carsten and Timmerer, Christian}, booktitle = {Proceedings of the 27th ACM International Conference on Multimedia}, title = {{Docker-Based Evaluation Framework for Video Streaming QoE in Broadband Networks}}, year = {2019}, month = {Oktober}, pages = {2288--2291}, publisher = {ACM New York}, doi = {10.1145/3343031.3350538}, url = {https://dl.acm.org/citation.cfm?doid=3343031.3350538} } @Article{Timmerer_Zabrovskiy2019, author = {Timmerer, Christian and Zabrovskiy, Anatoliy}, journal = {ZTE COMMUNICATIONS}, title = {{Automating QoS and QoE Evaluation of HTTP Adaptive Streaming Systems}}, year = {2019}, month = {März}, number = {1}, pages = {18--24}, volume = {17}, abstract = {Streaming audio and video content currently accounts for the majority of the In⁃ternet traffic and is typically deployed over the top of the existing infrastructure. We arefacing the challenge of a plethora of media players and adaptation algorithms showing dif⁃ferent behavior but lacking a common framework for both objective and subjective evalua⁃tion of such systems. This paper aims to close this gap byproposing such a framework,de⁃scribing its architecture,providing an example evaluation, anddiscussing open issues.}, doi = {10.12142/ZTECOM.201901004}, url = {https://www.researchgate.net/profile/Anatoliy_Zabrovskiy/publication/335620882_Automating_QoS_and_QoE_Evaluation_of_HTTP_Adaptive_Streaming_Systems/links/5d70f9074585151ee49e7674/Automating-QoS-and-QoE-Evaluation-of-HTTP-Adaptive-Streaming-Systems.pdf} } @Article{TimmererGUESTEDITORIAL, author = {Ji, Wen and Li, Zhu and Poor, H. Vincent and Timmerer, Christian and Zhu, Wenwu}, journal = {IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS}, title = {{Guest Editorial Multimedia Economics for Future Networks: Theory, Methods, and Applications}}, year = {2019}, month = {Juni}, number = {7}, pages = {1473--1477}, volume = {37}, abstract = {With the growing integration of telecommunication networks, Internet of Things (IoT), and 5G networks, there is a tremendous demand for multimedia services over heterogeneous networks. According to recent survey reports, mobile video traffic accounted for 60 percent of total mobile data traffic in 2016, and it will reach up to 78 percent by the end of 2021. Users’ daily lives are inundated with multimedia services, such as online video streaming (e.g., YouTube and Netflix), social networks (e.g., Facebook, Instagram, and Twitter), IoT and machine generated video (e.g, surveillance cameras), and multimedia service providers (e.g., Over-the-Top (OTT) services). Multimedia data is thus becoming the dominant traffic in the near future for both wired and wireless networks.}, doi = {10.1109/JSAC.2019.2918962}, url = {https://ieeexplore.ieee.org/abstract/document/8737812} } @InProceedings{Timmerer2019d, author = {Bentaleb, Abdelhak and Timmerer, Christian and Begen, Ali C. and Zimmermann, Roger}, booktitle = {Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video}, title = {{Bandwidth prediction on low-latency chunked streaming}}, year = {2019}, month = {Juni}, pages = {7--13}, publisher = {ACM New York}, doi = {10.1145/3304112.3325611}, url = {https://dl.acm.org/citation.cfm?doid=3304112.3325611} } @InProceedings{Timmerer2019c, author = {Timmerer, Christian and Begen, Ali C.}, booktitle = {Proceedings of the 27th ACM International Conference on Multimedia}, title = {{A Journey Towards Fully Immersive Media Access}}, year = {2019}, month = {Oktober}, pages = {2703--2705}, publisher = {ACM New York}, doi = {10.1145/3343031.3350543}, url = {https://dl.acm.org/citation.cfm?id=3350543} } @InProceedings{Timmerer2019b, author = {van der Hooft, Jeroen and Wauters, Tim and De Turck, Filip and Timmerer, Christian and Hellwagner, Hermann}, booktitle = {Proceedings of the 27th ACM International Conference on Multimedia}, title = {{Towards 6dof http adaptive streaming through point cloud compression}}, year = {2019}, month = {Oktober}, pages = {2405--2413}, publisher = {ACM New York}, doi = {10.1145/3343031.3350917}, url = {https://dl.acm.org/citation.cfm?id=3350917} } @Article{Timmerer2019a, author = {Timmerer, Christian}, title = {MPEG column: 124th MPEG meeting in Macau, China}, journal = {SIGMultimedia Records}, publisher = {ACM}, year = {2019}, volume = {10}, number = {4}, month = jan, issn = {1947-4598}, doi = {10.1145/3310195.3310203}, url = {http://doi.acm.org/10.1145/3310195.3310203}, pages = {8:8--8:8}, address = {New York, NY, USA} } @InProceedings{Sokolova2019, author = {Sokolova, Natalia and Schöffmann, Klaus and Taschwer, Mario and Putzgruber-Adamitsch, Doris and El-Shabrawi, Yosuf}, booktitle = {Proceedings of the 26th International Conference in MultiMedia Modeling (MMM 2020) (Part II)}, title = {{Evaluating the Generalization Performance of Instrument Classification in Cataract Surgery Videos}}, year = {2019}, address = {Berlin}, editor = {Wen-Huang Cheng and Junmo Kim and Wei-Ta Chu and Peng Cui and Jung-Woo Choi and Min-Chun Hu and Wesley De Neve}, month = {Dezember}, pages = {626--636}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {11962}, doi = {10.1007/978-3-030-37734-2_51}, url = {https://www.researchgate.net/publication/338188982_Evaluating_the_Generalization_Performance_of_Instrument_Classification_in_Cataract_Surgery_Videos} } @Article{Schöffmann2019e, author = {Schöffmann, Klaus and Þór Jónsson, Björn and Gurrin, Cathal}, journal = {ACM SIGMM Records}, title = {{Dataset Column: Report from the MMM 2019 Special Session on Multimedia Datasets for Repeatable Experimentation (MDRE 2019)}}, year = {2019}, month = {September}, number = {3}, volume = {11}, abstract = {Information retrieval and multimedia content access have a long history of comparative evaluation, and many of the advances in the area over the past decade can be attributed to the availability of open datasets that support comparative and repeatable experimentation. Sharing data and code to allow other researchers to replicate research results is needed in the multimedia modeling field, as it helps to improve the performance of systems and the reproducibility of published papers.This report summarizes the special session on Multimedia Datasets for Repeatable Experimentation (MDRE 2019), which was organized at the 25th International Conference on MultiMedia Modeling (MMM 2019), which was held in January 2019 in Thessaloniki, Greece.The intent of these special sessions is to be a venue for releasing datasets to the multimedia community and discussing dataset related issues. The presentation mode in 2019 was to have short presentations (8 minutes) with some questions, and an additional panel discussion after all the presentations, which was moderated by Björn Þór Jónsson. In the following we summarize the special session, including its talks, questions, and discussions.}, url = {https://records.sigmm.org/2019/10/22/dataset-column-report-from-the-mmm-2019-special-session-on-multimedia-datasets-for-repeatable-experimentation-mdre-2019/} } @Article{Schoeffmann2019g, author = {Gurrin, Cathal and Joho, Hideo and Zhou, Liting and Dang-Nguyen, Duc-Tien and Piras, Luca and Lokoc, Jakub and Schöffmann, Klaus and Leibetseder, Andreas and Duane, Aaron and Riegler, Michael and Tran, Minh-Triet and Hürst, Wolfgang}, journal = {ITE Transactions on Media Technology and Applications}, title = {{Comparing Approaches to Interactive Lifelog Search at the Lifelog Search Challenge (LSC2018)}}, year = {2019}, month = {April}, number = {2}, pages = {46--59}, volume = {7}, abstract = {The Lifelog Search Challenge (LSC) is an international content retrieval competition that evaluates search for personal lifelog data. At the LSC, content-based search is performed over a multi-modal dataset, continuously recorded by a lifelogger over 27 days, consisting of multimedia content, biometric data, human activity data, and information activities data. In this work, we report on the first LSC that took place in Yokohama, Japan in 2018 as a special workshop at ACM International Conference on Multimedia Retrieval 2018 (ICMR 2018). We describe the general idea of this challenge, summarise the participating search systems as well as the evaluation procedure, and analyse the search performance of the teams in various aspects. We try to identify reasons why some systems performed better than others and provide an outlook as well as open issues for upcoming iterations of the challenge.}, doi = {10.3169/mta.7.46}, url = {https://www.researchgate.net/publication/332118743_Invited_papers_Comparing_Approaches_to_Interactive_Lifelog_Search_at_the_Lifelog_Search_Challenge_LSC2018} } @Article{Schoeffmann2019f, author = {Rossetto, Luca and Berns, Fabian and Schöffmann, Klaus and Awad, George M. and Beecks, Christian}, journal = {ACM SIGMM Records}, title = {{The V3C1 Dataset: Advancing the State of the Art in Video Retrieval}}, year = {2019}, month = {Juni}, number = {2}, volume = {11}, abstract = {Standardized datasets are of vital importance in multimedia research, as they form the basis for reproducible experiments and evaluations. In the area of video retrieval, widely used datasets such as the IACC [5], which has formed the basis for the TRECVID Ad-Hoc Video Search Task and other retrieval-related challenges, have started to show their age. For example, IACC is no longer representative of video content as it is found in the wild [7]. This is illustrated by the figures below, showing the distribution of video age and duration across various datasets in comparison with a sample drawn from Vimeo and Youtube.}, url = {https://records.sigmm.org/2019/07/06/the-v3c1-dataset-advancing-the-state-of-the-art-in-video-retrieval/} } @InProceedings{Schoeffmann2019d, author = {Lokoc, Jakub and Schöffmann, Klaus and Bailer, Werner and Rossetto, Luca and Gurrin, Cathal}, booktitle = {Proceedings of the ACM International Conference on Multimedia Retrieval}, title = {{Interactive Video Retrieval in the Age of Deep Learning}}, year = {2019}, address = {New York, NY}, month = {Juni}, pages = {2--4}, publisher = {ACM - New York}, doi = {10.1145/3323873.3326588}, url = {https://dl.acm.org/doi/10.1145/3323873.3326588} } @InProceedings{Schoeffmann2019c, author = {Berns, Fabian and Rossetto, Luca and Schöffmann, Klaus and Beecks, Christian and Awad, George M.}, booktitle = {Proceedings of the ACM International Conference on Multimedia Retrieval}, title = {{V3C1 Dataset: An Evaluation of Content Characteristics }}, year = {2019}, address = {New York, NY}, month = {Juni}, pages = {334--338}, publisher = {ACM - New York}, doi = {10.1145/3323873.3325051}, url = {https://dl.acm.org/doi/10.1145/3323873.3325051} } @InProceedings{Schoeffmann2019b, author = {Peng, Cheng and Xu, Qing and Guo, Yuejun and Schöffmann, Klaus}, booktitle = {Proceedings of the 28th International Conference on Artificial Neural Networks}, title = {{Eye Movement-Based Analysis on Methodologies and Efficiency in the Process of Image Noise Evaluation}}, year = {2019}, address = {Berlin}, month = {September}, pages = {29--40}, publisher = {Springer}, doi = {10.1007/978-3-030-30508-6_3}, url = {https://www.researchgate.net/publication/335699630_Eye_Movement-Based_Analysis_on_Methodologies_and_Efficiency_in_the_Process_of_Image_Noise_Evaluation} } @InProceedings{Schoeffmann2019a, author = {Halvorsen, Pal and Riegler, Michael and Schöffmann, Klaus}, booktitle = {Proceedings of the 27th ACM International Conference on Multimedia}, title = {{Medical Multimedia Systems and Applications}}, year = {2019}, month = {Oktober}, pages = {2711--2713}, publisher = {ACM New York}, doi = {10.1145/3343031.3351319}, url = {https://dl.acm.org/doi/10.1145/3343031.3351319} } @InProceedings{Schoeffmann2019, author = {Schöffmann, Klaus}, booktitle = {Proceedings of the International Conference on Content-Based Multimedia Indexing (CBMI'19)}, title = {{Video Browser Showdown 2012-2019: A Review}}, year = {2019}, address = {Piscataway (NJ)}, month = {Oktober}, publisher = {IEEE}, doi = {10.1109/CBMI.2019.8877397}, url = {https://ieeexplore.ieee.org/document/8877397} } @InProceedings{Schatz2019, author = {Schatz, Raimund and Zabrovskiy, Anatoliy and Timmerer, Christian}, title = {Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective QoE Evaluation}, booktitle = {2019 Eleventh International Conference on Qualit of Multimedia Experience (QoMEX)}, year = {2019}, address = {New York, USA}, month = jun, publisher = {IEEE}, abstract = {Omnidirectional video (ODV) streaming applica- tions are becoming increasingly popular. They enable a highly immersive experience as the user can freely choose her/his field of view within the 360-degree environment. Current deployments are fairly simple but viewport-agnostic which inevitably results in high storage/bandwidth requirements and low Quality of Experience (QoE). A promising solution is referred to as tile- based streaming which allows to have higher quality within the user’s viewport while quality outside the user’s viewport could be lower. However, empirical QoE assessment studies in this domain are still rare. Thus, this paper investigates the impact of different tile-based streaming approaches and configurations on the QoE of ODV. We present the results of a lab-based subjective evaluation in which participants evaluated 8K omnidirectional video QoE as influenced by different (i) tile-based streaming approaches (full vs. partial delivery), (ii) content types (static vs. moving camera), and (iii) tile encoding quality levels determined by different quantization parameters. Our experimental setup is character- ized by high reproducibility since relevant media delivery aspects (including the user’s head movements and dynamic tile quality adaptation) are already rendered into the respective processed video sequences. Additionally, we performed a complementary objective evaluation of the different test sequences focusing on bandwidth efficiency and objective quality metrics. The results are presented in this paper and discussed in detail which confirm that tile-based streaming of ODV improves visual quality while reducing bandwidth requirements.}, keywords = {Omnidirectional Video, Tile-based Streaming, Subjective Testing, Objective Metrics, Quality of Experience} } @InProceedings{Saurabh2019, author = {Saurabh, Nishant and Remmers, Julian and Kimovski, Dragi and Prodan, Radu Aurel and Barbosa, jorge G.}, booktitle = {Proceedings of the 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS) 2019}, title = {{Semantics-Aware Virtual Machine Image Management in IaaS Clouds}}, year = {2019}, address = {Piscataway (NJ)}, month = {September}, pages = {418--427}, publisher = {IEEE}, doi = {10.1109/IPDPS.2019.00052}, url = {https://ieeexplore.ieee.org/document/8820973} } @InProceedings{ProdanIET2019a, author = {Oleksiak, Ariel and Lefevre, Laurent and Alonso, Pedro and Da Costa, Georges and De Maio, Vincenzo and Frasheri, Neki and Garcia, Victor M. and Guerrero, Joel and Lafond, Sebastien and Lastovetsky, Alexey L. and Manumachu, Ravi Reddy and Muite, Benson and Orgerie, Anne-Cecile and Piatek, Wojciech and Pierson, Jean-Marc and Prodan, Radu Aurel and Stolf, Patricia and Sheme, Enida and Varrette, Sebastien}, booktitle = {Ultrascale Computing Systems}, title = {{Energy aware ultrascale systems}}, year = {2019}, address = {Stevenage}, editor = {Jesus Carretero and Emmanuel Jeannot and Albert Y. Zomaya}, month = {Januar}, pages = {127--188}, publisher = {The Institution of Engineering and Technology (IET)}, abstract = {Energy consumption is one of the main limiting factors for the design of ultrascale infrastructures. Multi-level hardware and software optimizations must be designed and explored in order to reduce energy consumption for these largescale equipment. This chapter addresses the issue of energy efficiency of ultrascale systems in front of other quality metrics. The goal of this chapter is to explore the design of metrics, analysis, frameworks and tools for putting energy awareness and energy efficiency at the next stage. Significant emphasis will be placed on the idea of “energy complexity,” reflecting the synergies between energy efficiency and quality of service, resilience and performance, by studying computation power, communication/data sharing power, data access power, algorithm energy consumption, etc.}, doi = {10.1049/PBPC024E}, url = {https://digital-library.theiet.org/content/books/pc/pbpc024e} } @InProceedings{ProdanGLOBECOMWS, author = {Mudgill, Vipul and Aujla, Gagangeet Singh and Kumar, Neeraj and Obaidat, Mohammad S. and Prodan, Radu Aurel}, booktitle = {Proceedings of the 2018 IEEE Globecom Workshops}, title = {{DLopC: Data Locality Independency-Aware VM Clustering in Cloud Computing}}, year = {2019}, address = {Piscataway (NJ)}, month = {Februar}, pages = {1--6}, publisher = {IEEE}, doi = {10.1109/GLOCOMW.2018.8644081}, url = {https://ieeexplore.ieee.org/document/8644081} } @InProceedings{ProdanGLOBECOM, author = {Jindal, Anish and Aujla, Gagangeet Singh and Kumar, Neeraj and Prodan, Radu Aurel and Obaidat, Mohammad S.}, booktitle = {Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM)}, title = {{DRUMS: Demand Response Management in a Smart City Using Deep Learning and SVR}}, year = {2019}, address = {Piscataway (NJ)}, month = {Februar}, pages = {1--6}, publisher = {IEEE}, doi = {10.1109/GLOCOM.2018.8647926}, url = {https://ieeexplore.ieee.org/document/8647926} } @Article{Prodan2019_JofGridComputing, author = {Ricci, Laura and Iosup, Alexander and Prodan, Radu Aurel}, journal = {Journal of Grid Computing}, title = {{EDITORIAL Special Issue on Large Scale Cooperative Virtual Environments}}, year = {2019}, month = {März}, pages = {1--2}, volume = {17}, doi = {10.1007/s10723-019-09480-4}, url = {https://link.springer.com/article/10.1007/s10723-019-09480-4} } @Article{Prodan2019JavaSymphony, author = {Aleem, Muhammad and Prodan, Radu Aurel and Arshad Islam, Muhammad and Azhar Iqbal, Muhammad}, journal = {International Journal of Ad Hoc and Ubiquitous Computing}, title = {{On the Parallel Programmability of JavaSymphony for Multi-cores and Clusters}}, year = {2019}, month = {März}, number = {4}, pages = {247--264}, volume = {30}, abstract = {This paper explains the programming aspects of a promising Java-based programming and execution framework called JavaSymphony. JavaSymphony provides unified high-level programming constructs for applications related to shared, distributed, hybrid memory parallel computers, and co-processors accelerators. JavaSymphony applications can be executed on a variety of multi-/many-core conventional and data-parallel architectures. JavaSymphony is based on the concept of dynamic virtual architectures, which allows programmers to define a hierarchical structure of the underlying computing resources and to control load-balancing and task-locality. In addition to GPU support, JavaSymphony provides a multi-core aware scheduling mechanism capable of mapping parallel applications on large multi-core machines and heterogeneous clusters. Several real applications and benchmarks (on modern multi-core computers, heterogeneous clusters, and machines consisting of a combination of different multi-core CPU and GPU devices) have been used to evaluate the performance. The results demonstrate that the JavaSymphony outperforms the Java implementations, as well as other modern alternative solutions.}, doi = {10.1504/IJAHUC.2019.098861}, url = {https://www.inderscience.com/info/inarticle.php?artid=98861} } @Article{Prodan2019IndersciencePublishers, author = {Aleem, Muhammad and Prodan, Radu Aurel and Arshad Islam, Muhammad and Azhar Iqbal, Muhammad}, journal = {International Journal of Ad Hoc and Ubiquitous Computing}, title = {{On the paralell programmability of JavaSymphony for multi-cores and clusters}}, year = {2019}, month = {März}, number = {4}, pages = {247--264}, volume = {30}, abstract = {This paper explains the programming aspects of a promising Java-based programming and execution framework called JavaSymphony. JavaSymphony provides unified high-level programming constructs for applications related to shared, distributed, hybrid memory parallel computers, and co-processors accelerators. JavaSymphony applications can be executed on multi-/many-core conventional and data-parallel architectures. JavaSymphony is based on the concept of dynamic virtual architectures, which allows programmers to define a hierarchical structure of the underlying computing resources and to control load-balancing and task-locality. In addition to GPU support, JavaSymphony provides a multi-core aware scheduling mechanism capable of mapping parallel applications on large multi-core machines and heterogeneous clusters. Several real applications and benchmarks (on modern multi-core computers, heterogeneous clusters, and machines consisting of a combination of different multi-core CPU and GPU devices) have been used to evaluate the performance. The results demonstrate that the JavaSymphony outperforms the Java implementations, as well as other modern alternative solutions.}, doi = {10.1504/IJAHUC.2019.098861}, url = {https://www.inderscience.com/info/inarticle.php?artid=98861} } @InProceedings{Prodan2019, author = {Radu Prodan and Ennio Torre and Juan J. Durillo and Gagangeet Singh Aujla and Neeraj Kummar and Hamid Mohammadi Fard and Shajulin Benedikt}, booktitle = {2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)}, title = {{Dynamic Multi-objective Virtual Machine Placement in Cloud Data Centers}}, year = {2019}, month = {aug}, pages = {92--99}, publisher = {IEEE}, abstract = {Minimizing the resource wastage reduces the energy cost of operating a data center, but may also lead to a considerably high resource overcommitment affecting the Quality of Service (QoS) of the running applications. Determining the effective tradeoff between resource wastage and overcommitment is a challenging task in virtualized Cloud data centers and depends on how Virtual Machines (VMs) are allocated to physical resources. In this paper, we propose a multi-objective framework for dynamic placement of VMs exploiting live-migration mechanisms which simultaneously optimize the resource wastage, overcommitment ratio and migration cost. The optimization algorithm is based on a novel evolutionary meta-heuristic using an island population model underneath. We implemented and validated our method based on an enhanced version of a well-known simulator. The results demonstrate that our approach outperforms other related approaches by reducing up to 57% migrations energy consumption while achieving different energy and QoS goals.}, doi = {10.1109/seaa.2019.00023}, keywords = {Cloud computing, Energy efficiency, Multi objective optimization, Virtual machine placement}, url = {https://ieeexplore.ieee.org/document/8906523} } @Article{Pohl_Hellwagner, author = {Pohl, Daniela and Bouchachia, Abdelhamid and Hellwagner, Hermann}, journal = {IEEE Transactions on Knowledge and Data Engineering}, title = {{Active Online Learning for Social Media Analysis to Support Crisis Management}}, year = {2019}, month = {März}, pages = {1--14}, abstract = {People use social media (SM) to describe and discuss different situations they are involved in, like crises. It is therefore worthwhile to exploit SM contents to support crisis management, in particular by revealing useful and unknown information about the crises in real-time. Hence, we propose a novel active online multiple-prototype classifier, called AOMPC. It identifies relevant data related to a crisis. AOMPC is an online learning algorithm that operates on data streams and which is equipped with active learning mechanisms to actively query the label of ambiguous unlabeled data. The number of queries is controlled by a fixed budget strategy. Typically, AOMPC accommodates partly labeled data streams. AOMPC was evaluated using two types of data: (1) synthetic data and (2) SM data from Twitter related to two crises, Colorado Floods and Australia Bushfires. To provide a thorough evaluation, a whole set of known metrics was used to study the quality of the results. Moreover, a sensitivity analysis was conducted to show the effect of AOMPC's parameters on the accuracy of the results. A comparative study of AOMPC against other available online learning algorithms was performed. The experiments showed very good behavior of AOMPC for dealing with evolving, partly-labeled data streams.}, doi = {10.1109/TKDE.2019.2906173}, url = {https://ieeexplore.ieee.org/document/8669861} } @Article{Muenzer_Schoeffmann_2019, author = {Lokoc, Jakub and Kovalcik, Gregor and Münzer, Bernd and Schöffmann, Klaus and Bailer, Werner and Gasser, Ralph and Vrochidis, Stefanos and Nguyen, Phuong Anh and Rujikietgumjorn, Sitapa and Barthel, Kai Uwe}, journal = {ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)}, title = {{Interactive Search or Sequential Browsing? A Detailed Analysis of the Video Browser Showdown 2018}}, year = {2019}, month = {Februar}, pages = {1--26}, volume = {15}, abstract = {This work summarizes the findings of the 7th iteration of the Video Browser Showdown (VBS) competition organized as a workshop at the 24th International Conference on Multimedia Modeling in Bangkok. The competition focuses on video retrieval scenarios in which the searched scenes were either previously observed or described by another person (i.e., an example shot is not available). During the event, nine teams competed with their video retrieval tools in providing access to a shared video collection with 600 hours of video content. Evaluation objectives, rules, scoring, tasks, and all participating tools are described in the article. In addition, we provide some insights into how the different teams interacted with their video browsers, which was made possible by a novel interaction logging mechanism introduced for this iteration of the VBS. The results collected at the VBS evaluation server confirm that searching for one particular scene in the collection when given a limited time is still a challenging task for many of the approaches that were showcased during the event. Given only a short textual description, finding the correct scene is even harder. In ad hoc search with multiple relevant scenes, the tools were mostly able to find at least one scene, whereas recall was the issue for many teams. The logs also reveal that even though recent exciting advances in machine learning narrow the classical semantic gap problem, user-centric interfaces are still required to mediate access to specific content. Finally, open challenges and lessons learned are presented for future VBS events.}, doi = {10.1145/3295663}, url = {https://dl.acm.org/doi/10.1145/3295663} } @Article{Moll_Theuermann_Lux, author = {Elmenreich, Wilfried and Moll, Philipp and Theuermann, Sebastian and Lux, Mathias}, journal = {PeerJ Computer Science}, title = {{Making simulation results reproducible - Survey, guidelines, and examples based on Gradle and Docker}}, year = {2019}, month = {Dezember}, number = {e240}, pages = {1--27}, volume = {5}, abstract = {This article addresses two research questions related to reproducibility within the context of research related to computer science. First, a survey on reproducibility addressed to researchers in the academic and private sectors is described and evaluated. The survey indicates a strong need for open and easily accessible results, in particular, reproducing an experiment should not require too much effort. The results of the survey are then used to formulate guidelines for making research results reproducible. In addition, this article explores four approaches based on software tools that could bring forward reproducibility in research results. After a general analysis of tools, three examples are further investigated based on actual research projects which are used to evaluate previously introduced tools. Results indicate that the evaluated tools contribute well to making simulation results reproducible but due to conflicting requirements, none of the presented solutions fulfills all intended goals perfectly.}, doi = {10.7717/peerj-cs.240}, url = {https://peerj.com/articles/cs-240.pdf} } @InProceedings{Moll2019c, author = {Philipp Moll and Andreas Leibetseder and Sabrina Kletz and Mathias Lux and Bernd Muenzer}, booktitle = {Proceedings of the 10th {ACM} Multimedia Systems Conference}, title = {{Alternative inputs for games and AR/VR applications}}, year = {2019}, month = {jun}, pages = {320--323}, publisher = {ACM}, abstract = {In multimedia research, scientific progress is often slowed downby high demands on hard- and software. However, hardware con-tinuously improves and today’s hardware got powerful enoughto meet the performance demands of complex 3D and deep learn-ing applications. With this demo, we demonstrate that utilizingdeep learning and 3D modeling is not a major barrier anymorewhen building prototypes for showcasing research projects. Ourweb-based game, called “HeadbangZ”, showcases a novel gesture-based input methodology realized through deeply learned poseestimation and user interaction in a 3D environment. Since gesture-based inputs increase the immersion in virtual environments, weassume this input methodology to be especially useful for AR/VRapplications and games. Furthermore, we demonstrate that rapidprototyping of applications using novel technologies, such as deeplearning, is even possible within 48 hours by developing a workingdemo within this time frame. Finally, we provide insights into whatwe learned during the development of HeadbangZ to encourageother researchers to make use of novel technologies. In referenceto Stephen Harper’s quote “Having hit a wall, the next logical stepis not to bang our heads against it.”, we hope that the presentationof HeadbangZ encourages researchers to bang their heads rhythmi-cally to rock music instead of angrily against a virtual wall createdby hard- and software limitations.}, doi = {10.1145/3304109.3323832}, keywords = {Alternative Inputs, Deep Learning, Rhythm Games}, url = {https://dl.acm.org/citation.cfm?id=3323832} } @Misc{Moll2019b, author = {Moll, Philipp and Frick, Veit and Rauscher, Natascha Jasmin and Lux, Mathias}, howpublished = {Online Publikation}, month = {September}, title = {{How Players Play Games: Observing the Influences of Game Mechanics}}, year = {2019}, abstract = {The popularity of computer games is remarkably high and is still growingevery year. Despite this popularity and the economical importance of gaming,research in game design, or to be more precise, of game mechanics that can beused to improve the enjoyment of a game, is still scarce. In this paper, weanalyze Fortnite, one of the currently most successful games, and observe howplayers play the game. We investigate what makes playing the game enjoyable byanalyzing video streams of experienced players from game streaming platformsand by conducting a user study with players who are new to the game. Weformulate four hypotheses about how game mechanics influence the way playersinteract with the game and how it influences player enjoyment. We presentdifferences in player behavior between experienced players and beginners anddiscuss how game mechanics could be used to improve the enjoyment forbeginners. In addition, we describe our approach to analyze games withoutaccess to game-internal data by using a toolchain which automatically extractsgame information from video streams.}, url = {https://arxiv.org/abs/1909.09738} } @InProceedings{Moll2019a, author = {Moll, Philipp and Theuermann, Sebastian and Hellwagner, Hermann and Burke, Jeff}, booktitle = {2019 IEEE International Conference on Communications Workshops (ICC Workshops)}, title = {{Distributing the Game State of Online Games: Towards an NDN Version of Minecraft}}, year = {2019}, address = {Piscataway (NJ)}, editor = {Philipp Moll and Sebastian Theuermann and Hellwagner, Hermann and Jeff Burke}, month = {Juli}, publisher = {IEEE}, doi = {10.1109/ICCW.2019.8756979}, url = {https://ieeexplore.ieee.org/document/8756979} } @InProceedings{Moll2019, author = {Moll, Philipp and Theuermann, Sebastian and Rauscher, Natascha Jasmin and Hellwagner, Hermann and Burke, Jeff}, booktitle = {Proceedings of the 6th ACM Conference on Information-Centric Networking (ICN' 19)}, title = {{Inter-Server Game State Synchronization using Named Data Networking}}, year = {2019}, address = {New York, NY}, month = {September}, pages = {12--18}, publisher = {ACM Digital Library}, doi = {10.1145/3357150.3357399}, url = {https://dl.acm.org/citation.cfm?id=3357399} } @InProceedings{Mehran2019, author = {Mehran, Narges and Kimovski, Dragi and Prodan, Radu Aurel}, booktitle = {Proceedings of the 9th International Conference on the Internet of Things (IoT 2019)}, title = {{MAPO: A Multi-Objective Model for IoT Application Placement in a Fog Environment}}, year = {2019}, month = {Oktober}, pages = {1--8}, publisher = {Association for Computing Machinery (ACM)}, doi = {10.1145/3365871.3365892}, url = {https://dl.acm.org/doi/pdf/10.1145/3365871.3365892?download=true} } @InProceedings{Madaan2019, author = {Vishu Madaan and Rupinder Kaur and Prateek Agrawal}, booktitle = {2019 4th International Conference on Information Systems and Computer Networks (ISCON)}, title = {{Rheumatoid Arthritis anticipation using Adaptive Neuro Fuzzy Inference System}}, year = {2019}, month = nov, pages = {340--346}, publisher = {IEEE}, abstract = {A state of discomfort is known as a disease, also termed as illness or sickness. When the tiniest living things like virus enters our body, it reacts with the cells of the body and results an illness. The Arthritis is very problematic to early forecast. It nurtures with the age and related to the large and small joint pain. The Rheumatoid Arthritis (RA) is chronic disease, its long-term auto-immune and inflammatory disease which damages many joints tissues. It occurs when immune system can't distinguish the cells and tissues. The ANFIS model is used for the prediction of the RA in human mortals. A complete process is mentioned in this study, which helps to a technique for the diagnosis of the Rheumatoid Arthritis in human beings with accuracy 93.5%. This diagnosis is made on the bases of 12 symptoms of RA in human lives like age, stiffness, joint deformity, ESR, CRP, WBC, Uric Acid etc. This paper also compares the ANFIS with Naive Bayes, Bagging algorithm and KNN classifiers.}, doi = {10.1109/iscon47742.2019.9036297}, keywords = {Disease Diagnosis, Arthritis Symptoms, Arthritis Prediction, KNN Classifier, ANFIS, Naive Bayes Classification}, url = {https://ieeexplore.ieee.org/document/9036297} } @Article{Lux2019f, author = {Chryssanthi, Iakovidou and Anagnostopoulos, Nektarios and Lux, Mathias and Christodoulou, Klitos and Boutalis, Yiannis and Chatzichristofis, Savvas}, journal = {IEEE Transactions on Image Processing}, title = {{Composite Description Based on Salient Contours and Color Information for CBIR Tasks}}, year = {2019}, month = {Juni}, number = {6}, pages = {3115--3129}, volume = {28}, abstract = {This paper introduces a novel image descriptor for content-based image retrieval tasks that integrates contour and color information into a compact vector. Loosely inspired by the human visual system and its mechanisms in efficiently identifying visual saliency, operations are performed on a fixed lattice of discrete positions by a set of edge detecting kernels that calculate region derivatives at different scales and orientation. The description method utilizes a weighted edge histogram where bins are populated on the premise of whether the regions contain edges belonging to the salient contours, while the discriminative power is further enhanced by integrating regional quantized color information. The proposed technique is both efficient and adaptive to the specifics of each depiction, while it does not need any training data to adjust parameters. An experimental evaluation conducted on seven benchmarking datasets against 13 well known global descriptors along with SIFT, SURF implementations (both in VLAD and BOVW), highlight the effectiveness and efficiency of the proposed descriptor.}, doi = {10.1109/TIP.2019.2894281}, url = {https://ieeexplore.ieee.org/document/8626513} } @InProceedings{Lux2019e, author = {Dang-Nguyen, Duc-Tien and Piras, Luca and Riegler, Michael and Zhou, Liting and Lux, Mathias and Tran, Minh-Triet and Le, Tu-Khiem and Ninh, Van-Tu and Gurrin, Cathal}, booktitle = {Proceedings of the Conference and Labs of the Evaluation Forum (CLEF 2019)}, title = {{Overview of ImageCLEFlifelog 2019: Solve My Life Puzzle and Lifelog Moment Retrieval}}, year = {2019}, pages = {09--12}, publisher = {CEUR-Workshop Proceedings}, volume = {2380}, url = {https://www.semanticscholar.org/paper/Overview-of-ImageCLEFlifelog-2019%3A-Solve-My-Life-Dang-Nguyen-Piras/736f4783f29dd1ac0ec5fb0c020567e049cae5b1} } @InProceedings{Lux2019d, author = {Ionescu, Bogdan and Müller, Henning and Péteri, Renaud and Dang-Nguyen, Duc-Tien and Piras, Luca and Riegler, Michael and Tran, Minh-Triet and Lux, Mathias and Gurrin, Cathal and Dicente Cid, Yashin and Liauchuk, Vitali and Kovalev, Vassili and Abacha, Asma Ben and Hasan, Sadid A. and Datla, Vivek and Liu, Joey and Demner-Fushman, Dina and Pelka, Obioma and Friedrich, Christoph M. and Chamberlain, Jon and Clark, Adrian and Seco de Herrera, Alba Garcia and Garcia, Narciso and Kavallieratou, Ergina and del Blanco, Carlos Roberto and Cuevas Rodríguez, Carlos and Vasillopoulos, Nikos and Karampidis, Konstantinos}, booktitle = {Proceedings of the 41st European Conference on Information Retrieval (ECIR 2019)}, title = {{ImageCLEF 2019: Multimedia Retrieval in Lifelogging, Medical, Nature, and Security Applications}}, year = {2019}, address = {Berlin}, editor = {Leif Azzopardi and Benno Stein and Norbert Fuhr and Philipp Mayr and Claudia Hauff and Djoerd Hiemstra}, month = {April}, pages = {301--308}, publisher = {Springer}, doi = {10.1007/978-3-030-15719-7_40}, url = {https://link.springer.com/chapter/10.1007/978-3-030-15719-7_40} } @InProceedings{Lux2019c, author = {Lux, Mathias and Halvorsen, Pal and Dang-Nguyen, Duc-Tien and Stensland, Hakon and Kesavulu, Manoj and Potthast, Martin and Riegler, Michael}, booktitle = {Proceedings of the 11th ACM Workshop on Immersive Mixed and Virtual Environment Systems (MMVE 2019)}, title = {{Summarizing E-sports matches and tournaments: the example of counter-strike: global offensive}}, year = {2019}, address = {New York, NY}, month = {Juni}, pages = {13--18}, publisher = {ACM Digital Library}, doi = {10.1145/3304113.3326116}, url = {https://dl.acm.org/doi/10.1145/3304113.3326116} } @InProceedings{Lux2019b, author = {Ninh, Van-Tu and Le, Tu-Khiem and Zhou, Liting and Piras, Luca and Riegler, Michael and Lux, Mathias and Tran, Minh-Triet and Gurrin, Cathal and Dang-Nguyen, Duc-Tien}, booktitle = {Proceedings of the Conference and Labs of the Evaluation Forum (CLEF 2019)}, title = {{LIFER 2.0: Discovering Personal Lifelog Insights using an Interactive Lifelog Retrieval System}}, year = {2019}, month = {September}, publisher = {CEUR-Workshop Proceedings}, volume = {2380}, url = {https://pdfs.semanticscholar.org/c1d9/d2cbfebc7d275f9a4ca48d6c7953544d1e6b.pdf?_ga=2.244744845.962216161.1578471476-1581210800.1576149693} } @InProceedings{Lux2019a, author = {Hicks, Steven Alexander and Riegler, Michael and Smedsrud, Pia and Haugen, Trine B. and Ranheim Randel, Kristin and Pogorelov, Konstantin and Stensland, Hakon and Dang-Nguyen, Duc-Tien and Lux, Mathias and Petlund, Andreas and de Lange, Thomas and Schmidt, Peter T. and Halvorsen, Pal}, booktitle = {Proceedings of the 27th ACM International Conference on Multimedia}, title = {{ACM Multimedia BioMedia 2019 Grand Challenge Overview}}, year = {2019}, month = {Oktober}, pages = {2563--2567}, publisher = {ACM New York}, doi = {10.1145/3343031.3356058}, url = {https://dl.acm.org/doi/10.1145/3343031.3356058} } @InProceedings{Lux2019, author = {Lux, Mathias and Riegler, Michael and Halvorsen, Pal and Dang-Nguyen, Duc-Tien and Potthast, Martin}, booktitle = {Savegame}, title = {{Challenges for Multimedia Research in E-Sports Using Counter-Strike}}, year = {2019}, address = {Wiesbaden}, editor = {Wilfried Elmenreich and René Reinhold Schallegger and Felix Schniz and Sonja Gabriel and Gerhard Pölsterl and Wolfgang B. Ruge}, month = {November}, pages = {197--206}, publisher = {Springer VS}, abstract = {That video and computer games have reached the masses is a well-known fact. However, game streaming and, therefore, watching other people play videogames has also outgrown its humble beginnings by far. Game streams, be it live or recorded, are viewed by millions. Many of the streams are broadcasting competitive multiplayer games. This is called e-sports and it is very similar to sports broadcasting. E-sports is organized in leagues and tournaments in which players can compete in controlled environments and viewers can experience the matches, discuss and criticize just like in physical sports. In this paper, we look into the challenges for computer science in general and multimedia research in particular. The multimedia research community has done a lot of work on video streaming, broadcasting and analyzing the audience, but has missed the opportunity to investigate e-sports in detail. We focus on one particular game we deem representative for e-sports, Counter-Strike: Global Offensive, and investigate how the audience consumes game streams from competitive tournaments.}, doi = {10.1007/978-3-658-27395-8_13}, url = {https://link.springer.com/chapter/10.1007/978-3-658-27395-8_13} } @InProceedings{Leibetseder2019b, author = {Leibetseder, Andreas and Münzer, Bernd and Primus, Manfred Jürgen and Kletz, Sabrina and Schöffmann, Klaus and Berns, Fabian and Beecks, Christian}, booktitle = {Proceedings of the ACM Workshop on Lifelog Search Challenge (LSC 19)}, title = {{lifeXplore at the Lifelog Search Challenge 2019 }}, year = {2019}, address = {New York, NY}, month = {Juni}, pages = {13--17}, publisher = {ACM - New York}, doi = {10.1145/3326460.3329157}, url = {https://www.researchgate.net/publication/333690590_lifeXplore_at_the_Lifelog_Search_Challenge_2019} } @InProceedings{Leibetseder2019a, author = {Leibetseder, Andreas and Kletz, Sabrina and Schöffmann, Klaus and Keckstein, Simon and Keckstein, Jörg}, booktitle = {Proceedings of the 26th International Conference in MultiMedia Modeling (MMM 2020) (Part II)}, title = {{GLENDA: Gynecologic Laparoscopy Endometriosis Dataset}}, year = {2019}, address = {Berlin}, editor = {Wen-Huang Cheng and Junmo Kim and Wei-Ta Chu and Peng Cui and Jung-Woo Choi and Min-Chun Hu and Wesley De Neve}, month = {Dezember}, pages = {439--450}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {11962}, doi = {10.1007/978-3-030-37734-2_36}, url = {https://www.researchgate.net/publication/338189084_GLENDA_Gynecologic_Laparoscopy_Endometriosis_Dataset/link/5e1c30554585159aa4cb7378/download} } @InProceedings{Leibetseder2019, author = {Leibetseder, Andreas and Münzer, Bernd and Primus, Manfred Jürgen and Kletz, Sabrina and Schöffmann, Klaus}, booktitle = {Proceedings of the 26th International Conference in MultiMedia Modeling (MMM 2020) (Part II)}, title = {{diveXplore 4.0: The ITEC Deep Interactive Video Exploration System at Video Browser Showdown 2020}}, year = {2019}, address = {Berlin}, editor = {Wen-Huang Cheng and Junmo Kim and Wei-Ta Chu and Peng Cui and Jung-Woo Choi and Min-Chun Hu and Wesley De Neve}, month = {Dezember}, pages = {753--759}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {11962}, doi = {10.1007/978-3-030-37734-2_65}, url = {https://link.springer.com/chapter/10.1007%2F978-3-030-37734-2_65} } @InProceedings{Kletz_Leibetseder_Moll, author = {Errath, Daniela and Kletz, Sabrina and Leibetseder, Andreas and Moll, Philipp and Zraunig, Julia and Elmenreich, Wilfried}, booktitle = {Das Anthropozän.}, title = {{Digitalisierung und Anthropozän}}, year = {2019}, address = {München, Wien}, editor = {Heike Egner and Horst Peter Groß}, pages = {133--176}, publisher = {Profil Verlag}, abstract = {Das Anthropozän bezeichnet ein neues Erdzeitalter, in dem die Menschheit deutliche Spuren hinterlässt. Diese reichen von Gesteinsschichten mit radioaktiven Ablagerungen aus Atomtests über ausgerottete Tier- und Pflanzenarten bis hin zum allgegenwärtigen Klimawandel. Für manche dieser Spuren ist technologischer Fortschritt ein erheblicher Einflussfaktor. Während Mensch und Technik zusammen Spuren hinterlassen, beeinflusst auch die Technik den Menschen. Insbesondere die Digitalisierung könnte einen besonderen Einfluss auf das neue Erdzeitalter nehmen, in dem digitales Grundverständnis und Computational Thinking notwendige Kompetenzen auf dem Weg in die Zukunft darstellen. Wie diese aussieht, ist aufgrund der hohen Dynamik der gegenwärtigen Systeme ungewiss, insbesondere da durch die digitale Vernetzung eine hohe Produktivität einer großen Volatilität bei der Langzeitarchivierung gegenübersteht. In diesem Buchkapitel spannen wir einen Bogen vom Anthropozän über derzeitige Auswirkungen der menschlichen Intervention hin zur Entwicklung und Wirkung von Kommunikations- und Computertechnik in der heutigen Welt, zusammengefasst als digitale (R)evolution. In einem weiteren Schritt beschäftigen wir uns mit der gegenwärtig vorherrschenden und uns täglich umgebenden “digitalen Welt” und der Notwendigkeit zu digitalem Grundverständnis und Computational Thinking. Den Abschluss des Kapitels bildet ein Ausblick in die Zukunft und erläutert mögliche Zukunftsszenarien im digitalen Bereich.} } @InProceedings{Kletz2019b, author = {Sabrina Kletz and Andreas Leibetseder and Klaus Schoeffmann}, booktitle = {Proceedings of the 10th ACM Multimedia Systems Conference}, title = {{A comparative study of video annotation tools for scene understanding}}, year = {2019}, month = {jun}, pages = {133--144}, publisher = {ACM}, abstract = {Computers are powerful tools capable of solving a great variety of ever so complex problems, yet training them to interpret even the simplest video scenes can prove more challenging than one might imagine. Still being one of the major problems in computer vision, this issue recently is addressed by utilizing promising deep learning approaches in order to recognize objects and their semantics. For achieving this goal, huge artificial networks are fed with many human-created annotations using more or less sophisticated tools for speeding up the otherwise time-consuming task of manual annotation. Purposefully refraining from designing yet another of these annotation tools, in this work we strive for evaluating what makes existing ones great or not, i.e. we aim at determining effectiveness and efficiency of state-of-the-art object annotation tools when employed for annotating different kinds of video content. Our findings in a user study evaluating three comparable tools on three videos of distinct domains indicate a significant difference in annotation effort from a video perspective, yet no significance regarding utilized tools. Further, we determine a significant correlation between annotation time and accuracy.}, doi = {10.1145/3304109.3306223}, keywords = {Video Annotation Tools, User Study, Object Detection, Interpolation, Bounding Boxes, Machine Learning}, url = {https://dl.acm.org/citation.cfm?id=3306223} } @Article{Kletz2019a, author = {Kletz, Sabrina and Schöffmann, Klaus and Husslein, Heinrich}, journal = {IET Healthcare Technology Letters}, title = {{Learning the representation of instrument images in laparoscopy videos }}, year = {2019}, month = {November}, number = {6}, pages = {197--203}, volume = {6}, abstract = {Automatic recognition of instruments in laparoscopy videos poses many challenges that need to be addressed, like identifying multiple instruments appearing in various representations and in different lighting conditions, which in turn may be occluded by other instruments, tissue, blood, or smoke. Considering these challenges, it may be beneficial for recognition approaches that instrument frames are first detected in a sequence of video frames for further investigating only these frames. This pre-recognition step is also relevant for many other classification tasks in laparoscopy videos, such as action recognition or adverse event analysis. In this work, the authors address the task of binary classification to recognise video frames as either instrument or non-instrument images. They examine convolutional neural network models to learn the representation of instrument frames in videos and take a closer look at learned activation patterns. For this task, GoogLeNet together with batch normalisation is trained and validated using a publicly available dataset for instrument count classifications. They compared transfer learning with learning from scratch and evaluate on datasets from cholecystectomy and gynaecology. The evaluation shows that fine-tuning a pre-trained model on the instrument and non-instrument images is much faster and more stable in learning than training a model from scratch.}, doi = {10.1049/htl.2019.0077}, url = {https://digital-library.theiet.org/content/journals/10.1049/htl.2019.0077} } @InProceedings{Kletz2019, author = {Kletz, Sabrina and Schöffmann, Klaus and Leibetseder, Andreas and Benois-Pineau, Jenny and Husslein, Heinrich}, booktitle = {Proceedings of the 26th International Conference in MultiMedia Modeling (MMM 2020) (Part II)}, title = {{Instrument Recognition in Laparoscopy for Technical Skill Assessment}}, year = {2019}, address = {Berlin}, editor = {Wen-Huang Cheng and Junmo Kim and Wei-Ta Chu and Peng Cui and Jung-Woo Choi and Min-Chun Hu and Wesley De Neve}, month = {Dezember}, pages = {589--600}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {11962}, doi = {10.1007/978-3-030-37734-2_48}, url = {https://link.springer.com/chapter/10.1007%2F978-3-030-37734-2_48} } @Article{Kimovski_Prodan_2019, author = {Gec, Sandi and Kimovski, Dragi and Pascinski, Uros and Prodan, Radu Aurel and Stankovski, Vlado}, journal = {Concurrency and Computation: Practice and Experience}, title = {{Semantic approach for multi-objective optimisation of the ENTICE distributed Virtual Machine and container images repository}}, year = {2019}, month = {Februar}, number = {3}, volume = {31}, abstract = {New software engineering technologies facilitate development of applications from reusable software components, such as Virtual Machine and container images (VMI/CIs). Key requirements for the storage of VMI/CIs in public or private repositories are their fast delivery and cloud deployment times. ENTICE is a federated storage facility for VMI/CIs that provides optimisation mechanisms through the use of fragmentation and replication of images and a Pareto Multi‐Objective Optimisation (MO) solver. The operation of the MO solver is, however, time‐consuming due to the size and complexity of the metadata, specifying various non‐functional requirements for the management of VMI/CIs, such as geolocation, operational cost, and delivery time. In this work, we address this problem with a new semantic approach, which uses an ontology of the federated ENTICE repository, knowledge base, and constraint‐based reasoning mechanism. Open Source technologies such as Protégé, Jena Fuseki, and Pellet were used to develop a solution. Two specific use cases, (1) repository optimisation with offline and (2) online redistribution of VMI/CIs, are presented in detail. In both use cases, data from the knowledge base are provided to the MO solver. It is shown that Pellet‐based reasoning can be used to reduce the input metadata size used in the optimisation process by taking into consideration the geographic location of the VMI/CIs and the provenance of the VMI fragments. It is shown that this process leads to reduction of the input metadata size for the MO solver by up to 60% and reduction of the total optimisation time of the MO solver by up to 68%, while fully preserving the quality of the solution, which is significant.}, doi = {10.1002/cpe.4264}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4264} } @InProceedings{Hammer2019, author = {Hammer, Josef and Moll, Philipp and Hellwagner, Hermann}, booktitle = {2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)}, title = {{Transparent Access to 5G Edge Computing Services}}, year = {2019}, address = {Piscataway (NJ)}, month = {Juli}, pages = {895--898}, publisher = {IEEE}, doi = {10.1109/IPDPSW.2019.00147}, url = {https://ieeexplore.ieee.org/document/8778343} } @InProceedings{BarcisM2019, author = {Barcis, Agata and Barcis, Michal and Bettstetter, Christian}, booktitle = {International Symposium on Multi-Robot and Multi-Agent Systems (MRS)}, title = {{Robots that Sync and Swarm: A Proof of Concept in ROS 2}}, year = {2019}, address = {Piscataway (NJ)}, month = {November}, publisher = {IEEE}, doi = {10.1109/MRS.2019.8901095}, url = {https://ieeexplore.ieee.org/document/8901095} } @InProceedings{Barcis2019, author = {Barcis, Michal and Hellwagner, Hermann}, booktitle = {IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, title = {{An Evaluation Model for Information Distribution in Multi-Robot Systems}}, year = {2019}, month = {September}, pages = {824--829}, doi = {10.1109/INFCOMW.2019.8845299}, url = {https://ieeexplore.ieee.org/document/8845299} } @InProceedings{Agrawal2019b, author = {Kaur, Rupinder and Madaan, Vishu and Agrawal, Prateek}, booktitle = {Proceedings of the 3rd International Conference On Advanced Informatics For Computing Research}, title = {{Diagnosis of Arthritis Using K-Nearest Neighbor Approach}}, year = {2019}, editor = {Ashish Kumar Luhach and Dharm Singh Jat and Kamarul Bin Ghazali Hawari and Xiao-Zhi Gao and Pawan Lingras}, month = {September}, pages = {160--171}, publisher = {Springer Singapore}, series = {Communications in Computer and Information Science}, doi = {10.1007/978-981-15-0108-1_16}, url = {https://link.springer.com/chapter/10.1007/978-981-15-0108-1_16} } @InProceedings{Agrawal2019a, author = {Chaudhary, Deepak and Agrawal, Prateek and Madaan, Vishu}, booktitle = {Proceedings of the 3rd International Conference On Advanced Informatics For Computing Research}, title = {{Bank Cheque Validation Using Image Processing}}, year = {2019}, editor = {Ashish Kumar Luhach and Dharm Singh Jat and Kamarul Bin Ghazali Hawari and Xiao-Zhi Gao and Pawan Lingras}, month = {September}, pages = {148--159}, publisher = {Springer Singapore}, series = {Communications in Computer and Information Science}, doi = {10.1007/978-981-15-0108-1_15}, url = {https://link.springer.com/chapter/10.1007/978-981-15-0108-1_15} } @InProceedings{Agrawal2019, author = {Bhadwal, Neha and Agrawal, Prateek and Madaan, Vishu}, booktitle = {Proceedings of the 3rd International Conference On Advanced Informatics For Computing Research}, title = {{Bilingual Machine Translation System Between Hindi and Sanskrit Languages}}, year = {2019}, editor = {Ashish Kumar Luhach and Dharm Singh Jat and Kamarul Bin Ghazali Hawari and Xiao-Zhi Gao and Pawan Lingras}, month = {September}, pages = {312--321}, publisher = {Springer Singapore}, series = {Communications in Computer and Information Science}, doi = {10.1007/978-981-15-0108-1_29}, url = {https://link.springer.com/chapter/10.1007%2F978-981-15-0108-1_29} } @Book{2019, editor = {Jesus Carretero and Emmanuel Jeannot and Albert Y. Zomaya}, publisher = {Institution of Engineering and Technology}, title = {{Ultrascale Computing Systems}}, year = {2019}, month = {jan}, abstract = {With the spread of the Internet, applications and web-based services, distributed computing infrastructures, local parallel systems, and the availability of huge amounts of dispersed data, software-dependent systems will be more and more connected, more and more networked, leading to the creation of supersystems. The phrase ultrascale computing systems (UCSs) refers to this type of IT supersystems. UCSs are complex large-scale ecosystems aggregating high-performance parallel and distributed computing infrastructures. These systems provide to the end user intrinsically heterogeneous solutions, located at multiple sites and capable of delivering tremendous performance boosts. They are indispensable to applications offering several orders of magnitude increase in the size of data and in the computing power relative to today's existing conventional technologies. However, to really speak of UCS, we must consider several orders of magnitude increase in the size of data, in the computing power and in the network complexity relative to what is existing now.}, doi = {10.1049/pbpc024e}, url = {https://digital-library.theiet.org/content/books/pc/pbpc024e} }