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Yubo Tan

Bio: Yubo Tan is an academic researcher from Henan University of Technology. The author has contributed to research in topics: Quality of service & Dynamic priority scheduling. The author has an hindex of 2, co-authored 5 publications receiving 16 citations.

Papers
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Proceedings ArticleDOI
01 Dec 2008
TL;DR: Simulation results indicate that this algorithm can guarantee satisfied performance for video transmission in the high-packet- lost networks and reduces the network load caused by the retransmission of lost packets.
Abstract: Real-time video communication is very important to the Internet applications of video conferencing, video telephony, video-on-demand, and etc. However, the heavy traffic of video data along with its timing constraints makes it a challenge to provide large-scale, high QoS media streaming service over the current best-effect network. This paper presents a self-adapted feedback algorithm for video transmission which is based on the FEC coding technology and the Kalman filter theory. By modifying the rate using the adapted Kalman filter, this algorithm efficiently solves the problem of rate fluctuation caused by the lost packets. It reduces the network load caused by the retransmission of lost packets. It also weakens the influence of the loss of elementary layer packets (or other important contents) in transmission and provides the continuity of the video transmission over Internet. Simulation results indicate that this algorithm can guarantee satisfied performance for video transmission in the high-packet- lost networks.

11 citations

Proceedings ArticleDOI
01 Dec 2008
TL;DR: Two hybrid prediction models based on BP neural network, ES (exponential smoothing) and FCM (Fuzzy C-Means) clustering are proposed to predict the possible rate and ages of smokers suffering the lung cancer.
Abstract: Recent researches show that lung cancer owns actual dose-response relationship with calendar-year smoking environment exposure matrix and individual medical record. In this paper, two hybrid prediction models based on BP neural network, ES (exponential smoothing) and FCM (Fuzzy C-Means) clustering are proposed to predict the possible rate and ages of smokers suffering the lung cancer. The BP-ES (Exponential Smoothing) model can exert the superiorities of the time series datum of smoking crowds and other pathogenic factors; and the BPFCM clustering model can reduce the parameter amount and complexity of BP netpsilas training greatly. The experiments show that the accuracy of the hybrid models are enhanced greatly contrasted with single BP neural network, and can work as effective methods for the statistic, analysis and prediction to lung cancer.

3 citations

Proceedings ArticleDOI
15 Sep 2009
TL;DR: A scheduling algorithm based on Real-time Stream Video, QFEC(QoS based on FEC) algorithm is proposed, associated the FEC and Kalman Filter theories, which indicate the scheduling algorithm can provide good video service.
Abstract: Because of the best-effort network, the QoS of video transmission can't be gotten well Guarantee. With the development of network, the video applications based on Internet are growing rapidly. The real-time video applications become popular. Because of the complexity of the network and real-time stream video on demand, the scheduling algorithm has great influence on the QoS. In this paper, a scheduling algorithm based on Real-time Stream Video, QFEC(QoS based on FEC) algorithm is proposed, associated the FEC and Kalman Filter theories. According to the status of the receiver, the sending rate is adapted automatically by Kalman filter. The state of the scheduling algorithm is analyzed. This algorithm can maintain the continuity of the real-time video transmission. The simulation results are given, which indicate the scheduling algorithm can provide good video service.

1 citations

Proceedings ArticleDOI
15 Sep 2009
TL;DR: A way to recognize medical image automatically by using the fuzzy morphological associative memories is provided, which will provide a way to recognizing the useful signals from badly polluted images.
Abstract: Medical image recognition is crucial step of medical image processing and has become a very hot research topic. But many problems, which are caused by a great deal of missing, polluting, and superimposing of the signals, still generally exist in practical application, such as the low recognizing rate. How to recognize the useful signals from badly polluted images has become a difficult point in medical image process. Thus, this paper will provide a way to recognize medical image automatically by using the fuzzy morphological associative memories.

1 citations

Proceedings ArticleDOI
01 Dec 2008
TL;DR: A robust architecture, cactus-architecture, is proposed, which can avoid the system fluctuation caused by the new joining nodes or the departing nodes and a new incentive mechanism is introduced, which could well motivate the clients to be providing service.
Abstract: The P2P technology makes it possible that the number of the clients can be infinite, while the P2P technology still has some problems Under the free riding model, someone always shut down the P2P services to others immediately after downloaded he wanted, which will influence the continue service and cause instability and fluctuation In this paper, a robust architecture, cactus-architecture, is proposed, which can avoid the system fluctuation caused by the new joining nodes or the departing nodes A new incentive mechanism is introduced, which can well motivate the clients to be providing service

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Journal ArticleDOI
TL;DR: A survey of recent work on computational intelligence approaches that have been applied to prostate cancer predictive modeling, and considers the challenges which need to be addressed.
Abstract: Focus is on computational intelligence methods in prostate cancer predictive modeling.We survey metaheuristic optimisation methods.We review machine learning methods.We consider cancer data of different modalities.We discuss recent advances, challenges and provide future directions. Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex for conventional statistical techniques to process quickly and efficiently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty and imprecision which is typically found in clinical and biological datasets. This paper provides a survey of recent work on computational intelligence approaches that have been applied to prostate cancer predictive modeling, and considers the challenges which need to be addressed. In particular, the paper considers a broad definition of computational intelligence which includes metaheuristic optimisation algorithms (also known as nature inspired algorithms), Artificial Neural Networks, Deep Learning, Fuzzy based approaches, and hybrids of these, as well as Bayesian based approaches, and Markov models. Metaheuristic optimisation approaches, such as the Ant Colony Optimisation, Particle Swarm Optimisation, and Artificial Immune Network have been utilised for optimising the performance of prostate cancer predictive models, and the suitability of these approaches are discussed.

73 citations

Book ChapterDOI
02 Jan 2011
TL;DR: This article surveys and appraises available literature on various video encoding and wireless transmission techniques and discusses various parameters of wireless medium like reliability, QoS, transmission rate, transmission delay for video transmission as a key element of wireless multimedia communication.
Abstract: The video transmission using wireless technology is an important functionality in multimedia communication. Video coding/compression and real time transmission are the key indicators to select the appropriate techniques and needs very careful designing of the parameters. The extra efforts taken at the encoder side allows the decoding of the video on a less powerful hardware platform, where the issues like client buffer capacity and computational time are very critical. This article surveys and appraises available literature on various video encoding and wireless transmission techniques. It also discusses various parameters of wireless medium like reliability, QoS, transmission rate, transmission delay for video transmission as a key element of wireless multimedia communication.

7 citations

Journal Article
TL;DR: Compared with the FCNN algorithm, RFCNN is much more robust to outliers in the datasets, and its update rules are derived by using Lagrange optimization theory.
Abstract: In this paper a new robust fuzzy clustering neural networks (RFCNN) is presented to resolve the sensitivity of the fuzzy clustering neural network (FCNN) to outliers in real datasets. The new objective function of RFCNN is obtained by introducing Vapnik’s e-insensitive loss function, and RFCNN’s update rules are derived by using Lagrange optimization theory. Compared with the FCNN algorithm, RFCNN is much more robust to outliers in the datasets. Experimental results demonstrate the effectiveness of RFCNN.

5 citations

Journal ArticleDOI
TL;DR: Results indicate that the proposed method can guarantee satisfied end-to-end performance by increased packet delivery ratio, reduced end- to-end delay and hence increased network throughput for video transmission in wireless network.
Abstract: Real time video transmission in wireless environment considers various parameters of wireless channel like information rate, error resiliency, security, end-to-end latency, quality of service etc. The available internet protocols are transmission control protocol and user datagram protocol (UDP). But most of the real-time applications uses UDP as their transport protocol. UDP is a fast protocol suitable for delay sensitive applications like video and audio transmission as it does not provide flow control or error recovery and does not require connection management. Due to the tremendous growth in wired and wireless real-time applications, some improvements should be made in the existing systems or protocols. Various techniques to improve end-to-end performance of system for real time video transmission over wireless channel are available in literature. Authors claim that the solution suggested in the paper provide more reliability in wireless video transmission. In the proposed solution, adaptive redundant packets are added in every block (or datagram) transmitted in order to achieve a desired recovery rate at the receiver. The suggested method dose not use any retransmission mechanism. The network simulator NS-2 is used to evaluate the method and the simulation results indicate that the proposed method can guarantee satisfied end-to-end performance by increased packet delivery ratio, reduced end-to-end delay and hence increased network throughput for video transmission in wireless network.

5 citations

Proceedings ArticleDOI
17 Dec 2010
TL;DR: It is shown that the optimization algorithm can significantly increase the video quality, without increasing the gross data rate at the cost of an acceptable delay.
Abstract: Received video quality is dependent on the available link rate and the packet loss rate, which are inter-related in a busy network link. Even low packet loss ratios (PLRs) can significantly reduce the video quality. In this paper, a packet level parity FEC is applied to the video stream in order to reduce the video PLR. A constant gross data rate is assumed, such that adding a FEC leads to a decrease in effective video data rate and the introduction of an additional delay at the decoder-side, but this delay can be limited by limiting the length of a FEC block. An algorithm is proposed to optimize the FEC length, based on the Quality of Experience as modelled by the ITU-T R G.1070 standard. It is shown that the optimization algorithm can significantly increase the video quality, without increasing the gross data rate at the cost of an acceptable delay.

5 citations