13 research outputs found

    SVCEval-RA: an evaluation framework for adaptive scalable video streaming

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    [EN] Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks. Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.Castellanos HernĂĄndez, WE.; Guerri Cebollada, JC.; Arce Vila, P. (2017). SVCEval-RA: an evaluation framework for adaptive scalable video streaming. Multimedia Tools and Applications. 76(1):437-461. doi:10.1007/s11042-015-3046-yS437461761Akhshabi S, Begen AC, Dovrolis C (2011) An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In: Proceedings of the second annual ACM conference on Multimedia systems. ACM, pp 157–168Alabdulkarim MN, Rikli N-E (2012) QoS Provisioning for H.264/SVC Streams over Ad-Hoc ZigBee Networks Using Cross-Layer Design. In: 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). pp 1–8Birkos K, Tselios C, Dagiuklas T, Kotsopoulos S (2013) Peer selection and scheduling of H. 264 SVC video over wireless networks. In: Wireless Communications and Networking Conference (WCNC), 2013 IEEE. pp 1633–1638Castellanos W (2014) SVCEval-RA - An Evaluation Framework for Adaptive Scalable Video Streaming. In: SourceForge Project. http://sourceforge.net/projects/svceval-ra/ . Accessed 1 May 2015Castellanos W, Guerri JC, Arce P (2015) A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks. Comput Commun. http://dx.doi.org/10.1016/j.comcom.2015.08.012Castellanos W, Arce P, Acelas P, Guerri JC (2012) Route Recovery Algorithm for QoS-Aware Routing in MANETs. Springer Berlin Heidelberg, Bilbao, pp. 81–93Chikkerur S, Sundaram V, Reisslein M, Karam LJ (2011) Objective video quality assessment methods: A classification, review, and performance comparison. Broadcast, IEEE Trans on 57:165–182Choupani R, Wong S, Tolun M (2014) Multiple description coding for SNR scalable video transmission over unreliable networks. Multimed Tools Appl 69:843–858. doi: 10.1007/s11042-012-1150-9CISCO Corp. (2014) Cisco Visual Networking Index Forecast and Methodology. In: White Paper. http://www.cisco.com/c/en/us/solutions/collateral/service-provider/ip-ngn-ip-next-generation-network/white_paper_c11-481360.pdf.Dai M, Zhang Y, Loguinov D (2009) A unified traffic model for MPEG-4 and H. 264 video traces. IEEE Trans Multimedia 11:1010–1023Detti A, Bianchi G, Pisa C, et al. (2009) SVEF: an open-source experimental evaluation framework for H.264 scalable video streaming. In: IEEE Symposium on Computers and Communications. pp 36–41Espina F, Morato D, Izal M, Magaña E (2014) Analytical model for MPEG video frame loss rates and playback interruptions on packet networks. Multimed Tools Appl 72:361–383. doi: 10.1007/s11042-012-1344-1Fiems D, Steyaert B, Bruneel H (2012) A genetic approach to Markovian characterisation of H.264 scalable video. Multimedia Tools Appl 58:125–146Floyd S, Handley M, Kohler E Datagram Congestion Control Protocol (DCCP). http://tools.ietf.org/html/rfc4340 . Accessed 17 Feb 2014Floyd S, Padhye J, Widmer J TCP Friendly Rate Control (TFRC): Protocol Specification. http://tools.ietf.org/html/rfc5348 . Accessed 17 Feb 2014Fraz M, Malkani YA, Elahi MA (2009) Design and implementation of real time video streaming and ROI transmission system using RTP on an embedded digital signal processing (DSP) platform. In: 2nd International Conference on Computer, Control and Communication, 2009. IC4 2009. pp 1–6ISO/IEC (2014) Information technology - Dynamic adaptive streaming over HTTP (DASH) - Part 1: Media presentation description and segment formats.ITU-T (2013) Rec. H.264 & ISO/IEC 14496-10 AVC. Advanced Video Coding for Generic Audiovisual Services.Ivrlač MT, Choi LU, Steinbach E, Nossek JA (2009) Models and analysis of streaming video transmission over wireless fading channels. Signal Process Image Commun 24:651–665. doi: 10.1016/j.image.2009.04.005Karki R, Seenivasan T, Claypool M, Kinicki R (2010) Performance Analysis of Home Streaming Video Using Orb. In: Proceedings of the 20th International Workshop on Network and Operating Systems Support for Digital Audio and Video. ACM, New York, NY, USA, pp 111–116Ke C-H (2012) myEvalSVC-an Integrated Simulation Framework for Evaluation of H. 264/SVC Transmission. KSII Trans Internet Inf Syst (TIIS) 6:377–392. doi: 10.3837/tiis.2012.01.021Ke C-H, Shieh C-K, Hwang W-S, Ziviani A (2008) An Evaluation Framework for More Realistic Simulations of MPEG Video Transmission. J Inf Sci Eng 24:425–440Klaue J, Rathke B, Wolisz A (2003) Evalvid–A framework for video transmission and quality evaluation. In: Computer Performance Evaluation. Modelling Techniques and Tools. Springer, pp 255–272Le TA, Nguyen H (2014) End-to-end transmission of scalable video contents: performance evaluation over EvalSVC—a new open-source evaluation platform. Multimed Tools Appl 72:1239–1256. doi: 10.1007/s11042-013-1444-6Lie A, Klaue J (2008) Evalvid-RA: trace driven simulation of rate adaptive MPEG-4 VBR video. Multimedia Systems 14:33–50. doi: 10.1007/s00530-007-0110-0Moving Pictures Experts Group and ITU-T Video Coding Experts Group (2011) H. 264/SVC reference software (JSVM 9.19.14) and Manual.Nightingale J, Wang Q, Grecos C (2014) Empirical evaluation of H.264/SVC streaming in resource-constrained multihomed mobile networks. Multimed Tools Appl 70:2011–2035. doi: 10.1007/s11042-012-1219-5Parmar H, Thornburgh M (2012) Real-Time Messaging Protocol (RTMP) Specification. AdobePolitis I, Dounis L, Dagiuklas T (2012) H. 264/SVC vs. H. 264/AVC video quality comparison under QoE-driven seamless handoff. Signal Process Image Commun 27:814–826Pozueco L, Pañeda XG, GarcĂ­a R, et al. (2013) Adaptable system based on Scalable Video Coding for high-quality video service. Comput Electr Eng 39:775–789. doi: 10.1016/j.compeleceng.2013.01.015Pozueco L, Pañeda XG, GarcĂ­a R, et al. (2014) Adaptation engine for a streaming service based on MPEG-DASH. Multimed Tools Appl 1–20. doi: 10.1007/s11042-014-2034-ySchwarz H, Marpe D, Wiegand T (2007) Overview of the Scalable Video Coding Extension of the H.264/AVC Standard. IEEE Trans Circ Syst Video Technol 17:1103–1120. doi: 10.1109/TCSVT.2007.905532Seo H-Y (2013) An Efficient Transmission Scheme of MPEG2-TS over RTP for a Hybrid DMB System. ETRI J 35:655–665. doi: 10.4218/etrij.13.0112.0124Sohn H, Yoo H, De Neve W, et al. (2010) Full-Reference Video Quality Metric for Fully Scalable and Mobile SVC Content. IEEE Trans Broadcast 56:269–280. doi: 10.1109/TBC.2010.2050628Sousa-Vieira M-E (2011) Suitability of the M/G/∞ process for modeling scalable H.264 video traffic. In: Analytical and Stochastic Modeling Techniques and Applications. Springer, pp 149–158Tanwir S, Perros H (2013) A Survey of VBR Video Traffic Models. IEEE Commun Surv Tutor 15:1778–1802. doi: 10.1109/SURV.2013.010413.00071Tanwir S, Perros HG (2014) VBR Video Traffic Models. Wiley, HobokenThe Network Simulator (NS-2). http://www.isi.edu/nsnam/ns . Accessed 6 Feb 2015Unanue I, Urteaga I, Husemann R, et al. (2011) A Tutorial on H. 264/SVC Scalable Video Coding and its Tradeoff between Quality, Coding Efficiency and Performance. Recent Advances on Video Coding 1–24.Van der Auwera G, David PT, Reisslein M, Karam LJ (2008) Traffic and quality characterization of the H. 264/AVC scalable video coding extension. Adv Multimedia 2008:1Wang Y, Claypool M (2005) RealTracer—Tools for Measuring the Performance of RealVideo on the Internet. Multimed Tools Appl 27:411–430. doi: 10.1007/s11042-005-3757-6Wang Z, Lu L, Bovik AC (2004) Video quality assessment based on structural distortion measurement. Signal Process Image Commun 19:121–132. doi: 10.1016/S0923-5965(03)00076–6Wien M, Schwarz H, Oelbaum T (2007) Performance Analysis of SVC. IEEE Trans Circ Syst for Video Technol 17:1194–1203. doi: 10.1109/TCSVT.2007.905530YUV video repository. ftp://ftp.tnt.uni-hannover.de/pub/svc/testsequences/ . Accessed 10 Jan 201

    Influence of adding multiwalled carbon nanotubes on the adhesive strength of composite epoxy/sol–gel materials

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    The tensile shear strength of a composite epoxy/sol–gel system modified with different ratios of multiwall carbon nanotubes (MWCNTs) was evaluated using a mechanical testing machine. The experimental results showed that the shear strength increased when lower than ~0.07 wt% of MWCNTs were added in the composite solution. The increase of the shear strength was attributed to both the mechanical load transfer from the matrix to the MWCNTs and the high specific surface area of this material that increased the degree of crosslinking with other inorganic fillers in the formulation. However, a decrease in the adhesive shear strength was observed after more than ~0.07 wt% MWCNTs were added to the composite. The reason for this may be related to the high concentration of MWCNTs within the matrix leading to excessively high viscosity, dewetting of the substrate surfaces, and reduced bonding of MWCNTs with the matrix, thereby limiting the strength. SEM observation of the fracture surfaces for composite epoxy/sol–gel adhesive materials with 0.01 wt% MWCNTs showed a mixed interfacial/cohesive fracture mode. This fracture mode indicated strong links at the adhesive/substrate interface, and interaction between CNTs and the matrix was achieved; therefore, adhesion performance of the composite epoxy/sol–gel material to the substrate was improved. An increase of a strong peak related to the C–O bond at ~1733 cm-1 in the FTIR spectra was observed. This peak represented crosslinking between the CNT surface and the organosilica nanoparticles in the MWCNTs-doped composite adhesive. Raman spectroscopy was also used to identify MWCNTs within the adhesive material. The Raman spectra exhibit peaks at ~1275 cm-1 and in the range of ~1549–1590 cm-1. The former is the graphite G-band, while the latter is the diamond D-band. The D-band and G-band represent the C–C single bond and C=C double bond in carbon nanotubes, respectively

    Bismuth-Based Nanomaterials: Recent Advances in Tumor Targeting and Synergistic Cancer Therapy Techniques

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    Despite all of the efforts in the field of cancer therapy, the heterogeneous properties of tumor cells induce an insufficient therapeutic outcome when treated with conventional monotherapies, necessitating a shift in cancer treatment from monotherapy to combination therapy for complete cancer treatment. Multifunctional bismuth (Bi)-based nanomaterials (NMs) with therapeutic functions hold great promise for the fields of cancer diagnosis and therapy based on their low toxicity, X-ray sensitive capabilities, high atomic number, near-infrared driven semiconductor properties, and low cost. Herein, a comprehensive review of recent advances in various medicinal aspects of Bi-based NMs is presented including: evaluation of in-tumor site accumulation, tumor targeting, and therapeutic performance, as well as the characteristics, benefits, and shortcomings of Bi-based NM-mediated major monotherapies. In addition, the cooperative enhancement mechanisms between two or more of these monotherapies are described in detail to address common challenges in cancer therapy, such as multidrug resistance, hypoxia, and metastasis. Finally, this review opens new insights into the design of multimodal synergistic therapies for potential future clinical applications of Bi-based NMs

    A Review on the Biodistribution, Pharmacokinetics and Toxicity of Bismuth-Based Nanomaterials

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    Here, bismuth-based nanomaterials (Bi-based NMs) are introduced as promising theranostic agents to enhance image contrast as well as for the therapeutic gain for numerous diseases. However, understanding the interaction of such novel developed nanoparticles (NPs) within a biological environment is a requisite for the translation of any promising agent from the lab bench to the clinic. This interaction delineates the fate of NPs after circulation in the body. In an ideal setting, a nano-based therapeutic agent should be eliminated via the renal clearance pathway, meanwhile it should have specific targeting to a diseased organ to reach an effective dose and also to overcome off-targeting. Due to their clearance pathway, biodistribution patterns and pharmacokinetics (PK), Bi-based NMs have been found to play a determinative role to pass clinical approval and they have been investigated extensively in vivo to date. In this review, we expansively discuss the possible toxicity induced by Bi-based NMs on cells or organs, as well as biodistribution profiles, PK and the clearance pathways in animal models. A low cytotoxicity of Bi-based NMs has been found in vitro and in vivo, and along with their long-term biodistribution and proper renal clearance in animal models, the translation of Bi-based NMs to the clinic as a useful novel theranostic agent is promising to improve numerous medical applications
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