17905519
A Measurement and Modeling Study of P2P IPTV Applications
P2P IPTV applications start to be very popular on the Internet. Previous work on measuring and analyzing P2P IPTV traffic mostly focuses on a specific type of P2P applications or the behavior characteristics of P2P IPTV nodes acting as a client. In this paper, we have undertaken an in-depth measurement and modeling study of the most common P2P IPTV applications, specially focusing on the behavior characteristics of peers acting as a server. We measure and model the distributions of flow inter-arrival time, arrival rate, duration and size. Our results show the following. The statistics can fit equally well into distributions. Due to the different strategies, there exhibit some differences in the traffic characteristics. But, because of P2P IPTV users behaving similarly, they mainly have similar distributions and the traffic of them all have heavy-tailed phenomenon. Insights obtained in this study will be valuable for the identification of P2P IPTV traffic.
22450367
Networking Business Model In Regional Medical Service- Case of Chikamori Medical Group in Kochi, Japan
Japan's Health Care System has experienced a number of changes over the last half a century. And the most heated aspect of current health policy debate focuses on the potential radical reform of the medical care system. In addition, the regional medical service organizations are in front of a more severe challenge because of the rapidly aging population and decreasing young population. Consequently, hospitals and other NHS organizations in local areas have been required to introduce reforms in their management structure for their survival This paper reports in depth on a case study of a private Japanese hospital, the Chikamori medical group, to introduce a key competence-based management model and differentiation marketing strategy. As one of the regional medical care support hospitals, Chikamori plays an active and important role in the regional medical care network. The case implies the effective business model based on positioning in the network architecture, which is significant not only for medical service field but also for other regional industries. The mutual correlations among financial strategy, human resource design, managing policy and collaboration manner with regional doctors are discussed in the paper.
41632859
A Novel Frequency Offset Estimator over Frequency Selective Fading Channels by Using Correlative Coding
A new data-aided carrier frequency offset (CFO) estimation technique is presented for correlative coded OFDM systems in the presence of strong multipath. Different from traditional data-aided estimation techniques, the technique estimates CFO by detecting amplitude of pilots rather than their phase shift and removes effects on CFO estimation due to intercarrier interference by an iterative compensation method. A theoretical analysis of its performance has been derived and simulation results comparing the new technique with a traditional data-aided estimation technique are presented.
27479532
Subspace-Based Blind Detection of Space-Time Coding
Space-time coding (STC) schemes for communication systems employing multiple transmit and receive antennas have received considerable interest recently. On space-time coding, some algorithms with perfect channel state information (CSI) have been proposed. In certain fast varying situation, however, it may be difficult to estimate the channel accurately and it is natural to study the blind detection algorithm without CSI. In this paper, based on subspace, a new blind detection algorithm without CSI is proposed. Using singular value decomposition (SVD) on output signal, noise subspace and signal subspace, which keep orthogonal to each other, are obtained. By searching the intersection of the signal subspace and the limited symbol vector set, symbol detection is achieved. The simulations illustrate that the proposed algorithm significantly improves system performance by receiving more output signals relative to transmit symbols. Furthermore, the presented algorithm is robust to the fading channel that changes between two successive blocks.
36390607
Wavelet-based diffusion approaches for signal denoising
The efficiency of nonlinear diffusion filters is related to diffusivity. In the previous models, diffusivity depended on the derivatives of a signal, and hence it is easily affected by noise. This paper considers the nonlinear wavelet-based diffusion (NWD) methods for signal denoising in which the diffusivity is expressed by the wavelet transforms of received signal at several scales. Due to the multiresolution of wavelet transform, the proposed diffusivity with wavelet transforms efficiently reduces the influence of noise on the estimate of diffusion amount and improves nonlinear diffusion filters. Some numerical experimental results compared with the previous models are shown.
27148951
Diffusion filtering in image processing based on wavelet transform
The nonlinear diffusion filtering in image processing bases on the heat diffusion equations. Its key is the control of diffusion amount. In the previous models, the diffusivity depends on the gradients of images. So it is easily affected by noises. This paper first gives a new multiscale computational technique for diffusivity. Then we proposed a class of nonlinear wavelet diffusion (NWD) models that are used to restore images. The NWD model has strong ability to resist noise. But it, like the previous models, requires higher computational effort. Thus, by simplifying the NWD, we establish linear wavelet diffusion (LWD) models that consist of advection and diffusion. Since there exists the advection, the LWD filter is anisotropic, and hence can well preserve edges although the diffusion at edges is isotropic. The advantage is that the LWD model is easy to be analyzed and has lesser computational load. Finally, a variety of numerical experiments compared with the previous model are shown.
15250571
Frequent Itemset Mining Based on Heuristic Two Level Counting
Recently, many enchanced Apriori algorithms have been proposed to efficiently generate all frequent itemsets from datasets in data mining field. Although efficient techniques were presented, those algorithms are either time-consuming or memory-consuming. To address the issue further, a new algorithm, which introduced a novel support counting method, heuristic two level counting, is proposed. HTLC method adopts an improved itemset generating technology in the generation process of low level itemsets, which promotes the production of low level frequent itemsets or candidate itemsets. It also applies a heuristic traversal technology which speeds up one pass over datasets and support counting technology which largely reduces the number of passes over datasets to the generation of high level frequent itemsets. Finally, the experimental results show that it outperforms existing Apriori-like algorithms in mostly datasets
6983597
A Comparative Study of Parallel Prefix Adders in FPGA Implementation of EAC
Several regular parallel trees have been proposed over the years to optimize logic depth, area, fan-out and in- terconnect count for logic circuits. In this paper, we propose a comparative study of different parallel prefix trees used in the design of a new end-around carry (EAC) adder targeting FPGA technology. This new adder is based on the fast 128-bit binary floating-point EAC adder which has been implemented in the IBM POWER6 microprocessor's fused multiply-add unit. The parallel prefix tree implemented on the IBM's EAC adder is a Kogge-Stone tree which has been chosen for its high performance and its low power consumption. Our comparative study highlights the main performance differences among fourteen different architecture configurations when targeting an FPGA EAC adder design. We focus on the area requirements and the critical path delay of these designs. Our experimental results show that there is one architecture configuration with the lower area requirement and the higher performance.
42839671
A Novel Integrated Supporting System for Mesh-Pull Based P2P IPTV
This paper presents a novel integrated supporting system for the mesh-pull based P2P IPTV. The proposed system can monitor the service quality of each overlays within the system by initiating random walks to sample key metrics of the system periodically and analyze the service quality statistically, and improve them to some extend. When the service quality is below the threshold, the system will increase its upload bandwidth adaptive to the workload of the system. The supporting system will allocate its bandwidth among multiple overlays to get the as much revenue as possible. This paper presents the design of this architecture and describes its functions and shows its adaptability to the high dynamic nature of p2p IPTV system and fitness for commercial deployment. At last we verify the feasibility of the architecture by simulation, and the results show its performance and adaptability.
1165057
An Extensible Three-tier XML Dialogue System Architecture for Multimodal Interaction and Automated Agent Services
45720537
Bayesian Network Structure Ensemble Learning
Bayesian networks (BNs) have been widely used for learning model structures of a domain in the area of data mining and knowledge discovery. This paper incorporates ensemble learning into BN structure learning algorithms and presents a novel ensemble BN structure learning approach. Based on the Markov condition and the faithfulness condition of BN structure learning, our ensemble approach proposes a novel sample decomposition technique and a components integration technique. The experimental results reveal that our ensemble BN structure learning approach can achieve an improved result compared with individual BN structure learning approach in terms of accuracy.