A poisson hidden markov model for multiview video traffic
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Nexgen Technology provides final year IEEE projects for 2015-2016. Contact information is provided for Praveen Kumar. The document then summarizes a project titled "A Poisson Hidden Markov Model for Multiview Video Traffic". It proposes using a Poisson hidden Markov model to characterize the variable bit-rate traffic generated by Multiview Video Coding. The model represents the video activity evolution in one layer and encoded frame sizes across multiple views in another layer. Extensive simulations show the model can accurately produce realistic traffic characteristics for MVC sequences and predict sender/receiver buffers and network load for interactive multiview services.
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For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
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N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
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vCPE 2.0 – the business case for an open vCPE framework
More at http://cloudify.co/webinars/open-vCPE-framework-webinar.html
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To get IEEE 2015-2017 Project for above title in .Net or Java
mail to finalyearprojects2all@gmail.com or contact +91 8870791415
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Intelligent transportation systems (ITS) are among the most focused research in this century. Actually, autonomous driving provides very advanced tasks in terms of road safety monitoring which include identifying dangers on the road and protecting pedestrians. In the last few years, deep learning (DL) approaches and especially convolutional neural networks (CNNs) have been extensively used to solve ITS problems such as traffic scene semantic segmentation and traffic signs classification. Semantic segmentation is an important task that has been addressed in computer vision (CV). Indeed, traffic scene semantic segmentation using CNNs requires high precision with few computational resources to perceive and segment the scene in real-time. However, we often find related work focusing only on one aspect, the precision, or the number of computational parameters. In this regard, we propose RBANet, a robust and lightweight CNN which uses a new proposed balanced attention module, and a new proposed residual module. Afterward, we have simulated our proposed RBANet using three loss functions to get the best combination using only 0.74M parameters. The RBANet has been evaluated on CamVid, the most used dataset in semantic segmentation, and it has performed well in terms of parameters’ requirements and precision compared to related work.
IEEE 2015 C# Projects
List of IEEE C# Projects. It Contains the IEEE Projects in the Language C# with ieee publication year 2015
Cloud computing for java and dotnet
The document discusses several topics related to cloud computing including:
1. A hybrid cloud approach for secure authorized data deduplication that considers differential user privileges.
2. A framework called AMES-Cloud that provides adaptive mobile video streaming and efficient social video sharing using private cloud agents.
3. Research into using multi-cloud providers instead of single clouds to help maintain security.
IEEE 2015 C# Projects
List of IEEE C# Projects. It Contains the IEEE Projects in the Language C# with ieee publication year 2015
Architecting Microservices in .Net
This document provides an overview of architecting microservices using .NET. It discusses why microservices are used, common architecture patterns, and implementation considerations. Key points include:
- Independent, loosely coupled services that are fault tolerant and easy to scale are goals of a microservices architecture.
- Communication between services should be kept simple, using either synchronous HTTP or asynchronous messaging. Synchronous calls can lead to temporal coupling so circuit breakers and failure handling are important.
- Domain-driven design principles like bounded contexts and separating queries from commands (CQRS) can help define appropriate service boundaries and responsibilities.
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Ames cloud a framework of adaptive mobile video streaming and efficient socia...
Ames cloud a framework of adaptive mobile video streaming and efficient socia...Nagendra Nayak Bharothu
This document proposes a framework called AMES-Cloud for adaptive mobile video streaming and efficient social video sharing in cloud computing environments. The framework has two main parts: (1) AMoV provides adaptive mobile video streaming by adjusting the video bitrate based on fluctuating wireless link quality using scalable video coding, with each user assigned a private agent in the cloud to track feedback; (2) ESoV enables efficient social video sharing by analyzing social network activities to prefetch videos for users based on social links and activity history, reducing buffering times. The framework constructs private agents in clouds to offer scalable resources and processing for adaptive streaming and social video prefetching.Project-ReviewFinal.pptx
The document proposes using a cloud computing infrastructure with virtualization to optimize resources for delivering IPTV services. It discusses combining the workloads of live TV, video-on-demand, and other services. The system would minimize resource requirements by multiplexing across services and adjusting one service if another's workload changes. It would compute the resources needed to support multiple services without missing deadlines. A service orchestrator would understand each service's requirements, decide on adaptation methods, and reduce overall resource consumption.
Web Modeling-based Approach to Automating Web Services Mediation, Choreograph...
This document summarizes a modeling approach for automating web service mediation, choreography, and discovery. The approach uses Web Modeling Language (WebML) to model business processes, ontologies, navigation, and service invocation patterns. WebML models are generated from business process models and refined by designers. The models can then be used to automatically generate mediators and hypertextual applications. The approach also leverages the GLUE discovery engine to manage dynamics like partner and ontology changes.
SimP2P: a Peer-to-Peer System for Texture Distribution in Social Virtual Worlds
Social virtual worlds (MMOW) allow users to dynamically create new content with high degree of personalization and immersion in shared real time environments. Popular MMOWs, such as Second Life (SL), are based on a Client/Server (C/S) approach for guaranteeing a shared consistent view of the virtual world, thus generating high network traffic volumes. This is due to the intrinsic features of MMOWs, where servers keep most information of the virtual environment, unlike some other types of virtual worlds, such as Massively Multiplayer Online Games (MMOG), such as World of Warcraft, where clients keep all objects and textures stored locally. Although the C/S approach is universally used because it is reliable and easily controlled, it poses a high burden on server hardware and bandwidth. In this paper, we propose SimP2P, a peer-to-peer approach for sharing textures among clients for MMOW environments, such as OpenSim. Our results show that SimP2P is able to decrease significantly the traffic sent by the OpenSim server, as well as to provide a much better Quality of Experience (QoE) for users, measured by texture response time.
Java image processing ieee projects 2012 @ Seabirds ( Chennai, Bangalore, Hyd...
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Ki-Tech Solutions IEEE PROJECTS DEVELOPMENTS WE OFFER IEEE PROJECTS MCA FINAL YEAR STUDENT PROJECTS, ENGINEERING PROJECTS AND TRAINING, PHP PROJECTS, JAVA AND J2EE PROJECTS, ASP.NET PROJECTS, NS2 PROJECTS, MATLAB PROJECTS AND IPT TRAINING IN RAJAPALAYAM, VIRUDHUNAGAR DISTRICTS, AND TAMILNADU. Mail to: kitechsolutions.in@gmail.com
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www.nexgenproject.com
Mobile: 9791938249,9025656779
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Mobile: 9791938249,9025656779
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A poisson hidden markov model for multiview video traffic
- 1. NEXGEN TECHNOLOGY FINAL YEAR IEEE PROJECTS TITLES 2015-2016 CONTACT: PRAVEEN KUMAR. L (+91 – 9751442511, +91 – 9791938249) MAIL ID: sunsid1989@gmail.com, praveen@nexgenproject.com web:www.nexgenproject.com 1. A Poisson Hidden Markov Model for Multiview Video Traffic Multiview video has recently emerged as a means to improve user experience in novel multimedia services. We propose a new stochastic model to characterize the traffic generated by a Multiview Video Coding (MVC) variable bit-rate source. To this aim, we resort to a Poisson hidden Markov model (P-HMM), in which the first (hidden) layer represents the evolution of the video activity and the second layer represents the frame sizes of the multiple encoded views. We propose a method for estimating the model parameters in long MVC sequences. We then present extensive numerical simulations assessing the model's ability to produce traffic with realistic characteristics for a general class of MVC sequences. We then extend our framework to network applications where we show that our model is able to accurately describe the sender and receiver buffers behavior in MVC transmission. Finally, we derive a model of user behavior for interactive view selection, which, in conjunction with our traffic model, is able to accurately predict actual network load in interactive multiview services. .