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131.
Alireza Montazeri Behzad Akbari Mohammed Ghanbari 《Peer-to-Peer Networking and Applications》2012,5(3):257-278
P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video
streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation
between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance.
To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary.
In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming
networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore,
we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our
simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the
non-free rider nodes and consequently in the whole network. 相似文献
132.
Mohammed Hawa Jamal S. Rahhal Dia I. Abu-Al-Nadi 《Peer-to-Peer Networking and Applications》2012,5(3):279-291
Peer-to-Peer (P2P) traffic has increased rapidly over the past few years, with file sharing providing the main drive behind
such traffic. In this work we perform a measurement study of the content shared over the popular BitTorrent P2P file sharing
network. We mathematically model the file size distributions of shared files after categorizing them into Audio, Video, Archive
and CD image classes. For each of these categories we look into the most popular shared file formats and investigate their
file size statistics. This provides an important milestone to building a realistic simulation framework for P2P systems, and
for future analytical modeling of P2P networks. 相似文献
133.
134.
Fahd A. Alhaidari Saleh A. Al-Dossary Ilyas A. Salih Abdlrhman M. Salem Ahmed S. Bokir Mahmoud O. Fares Mohammed I. Ahmed Mohammed S. Ahmed 《计算机系统科学与工程》2021,36(1):57-67
Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%. 相似文献
135.
Abbass Mohammed Y. Kwon Ki-Chul Kim Nam Abdelwahab Safey A. El-Samie Fathi E. Abd Khalaf Ashraf A. M. 《Artificial Intelligence Review》2021,54(5):3349-3360
Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial... 相似文献
136.
Sharma Rashmi Nitin Nitin AlShehri Mohammed Abdul Rahman Dahiya Deepak 《The Journal of supercomputing》2021,77(1):890-908
The Journal of Supercomputing - Multiple tasks arrive in the distributed systems that can be executed in either parallel or sequential manner. Before the execution, tasks are scheduled prioritywise... 相似文献
137.
Iyer Srikrishna Velmurugan T. Gandomi A. H. Noor Mohammed V. Saravanan K. Nandakumar S. 《Neural computing & applications》2021,33(11):5897-5915
Neural Computing and Applications - A multi-robot-based fault detection system for railway tracks is proposed to eliminate manual human visual inspection. A hardware prototype is designed to... 相似文献
138.
Zaidi Brahim Fares Selouani Sid Ahmed Boudraa Malika Sidi Yakoub Mohammed 《Neural computing & applications》2021,33(15):9089-9108
Neural Computing and Applications - This paper investigates the ability of deep neural networks (DNNs) to improve the automatic recognition of dysarthric speech through the use of convolutional... 相似文献
139.
Tianqi ZhangAuthor Vitae Shaosheng DaiAuthor VitaeWei ZhangAuthor Vitae Guoning MaAuthor VitaeXiangyun GaoAuthor Vitae 《Digital Signal Processing》2012,22(1):106-113
This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR. 相似文献
140.