41643555
A Fuzzy Dead Reckoning Algorithm for Distributed Interactive Applications
A fuzzy Dead Reckoning (DR) algorithm for distributed interactive applications is proposed in this paper. Since fixed threshold cannot adequately handle the dynamic relationships between moving entities, some multi-level threshold DR algorithms were proposed in the past few years. In these algorithms the level of threshold is adaptively adjusted based on the distance between entities. The proposed fuzzy DR algorithm is based on multi-level threshold DR algorithm and takes all properties of entity (e.g. position, size and view angle etc.) into consideration when adjusting the level of threshold. This algorithm employs fuzzy correlation degree to measure the relationships between entities and determine the level of threshold for DR algorithm. Fuzzy consistent relation is used to distribute weight for each property. Simulation results indicate that fuzzy DR algorithm can achieve a considerable reduction in the number of state update messages while maintaining adequate accuracy in extrapolation.
1426843
Priority based Overlay Multicast with Filtering Mechanism for Distributed Interactive Applications
The "priority-based directed minimum spanning tree" (PST) is designed for distributed interactive applications (DIAs) in which the data are delivered to the receiver node according to their priority; however PST cannot balance the bandwidth usage among the nodes and the system will be unstable when its scale increases. This paper proposes a novel overlay multicast protocol named priority based overlay multicast (POM), which uses the priority, delay and available bandwidth to construct the multicast tree, besides a filtering mechanism is proposed to rebuild the tree when the available bandwidth shortage appears. The effectiveness of our protocol is demonstrated in the simulation results, showing that POM uses the available bandwidth efficiently, besides it keeps the system stable when its scale increases
11658624
Statistical Feature Selection for Mandarin Speech Emotion Recognition
Performance of speech emotion recognition largely depends on the acoustic features used in a classifier. This paper studies the statistical feature selection problem in Mandarin speech emotion recognition. This study was based on a speaker dependent emotional mandarin database. Pitch, energy, duration, formant related features and some velocity information were selected as base features. Some statistics of them consisted of original feature set and full stepwise discriminant analysis (SDA) was employed to select extracted features. The results of feature selection were evaluated through a LDA based classifier. Experiment results indicate that pitch, log energy, speed and 1st formant are the most important factors and the accuracy rate increases from 63.1 % to 76.5 % after feature selection. Meanwhile, the features selected by SDA are better than the results of other feature selection methods in a LDA based classifier and SVM. The best performance is achieved when the feature number is in the range of 9 to 12.
8895078
An Adaptive-Filtering Policy for Distributed Virtual Environments
In this paper, an adaptive-filtering policy for distributed virtual environments (DVEs) was brought forward. It took advantages of two traditional filtering policies (static-filtering policy and equidistance-transmission policy) and could adaptively select the fittest filtering policy corresponding to current motion characteristic of the virtual object in DVEs. An experiment was designed to compare this filtering policy with the two traditional filtering policies on task performance. Objective (task completion time, state updates transmitted and state updates per second) and subjective (filtering quality) evaluations were recorded in the experiment. The experiment results show that if mean state updates per second is equal or greater than 20 in the task, SUT and SUPS can be decreased by adaptive-filtering policy without task performance affected obviously. However, if mean state updates per second is around 10 in the task, accompanied with SUT and SUPS decreased by adaptive-filtering policy, task performance also deteriorated badly
206977606
Priority Based Overlay Multicast for Distributed Interactive Applications
Distributed Interactive Applications (DIAs) is different with other network-based applications, since the data should be delivered to the receiver node according to its priority. Among the existing overlay multicast protocols the "priority-based directed minimum spanning tree" (PST) is designed for DIAs. But in PST the available bandwidth (avail-bw) is used inefficiently and the system becomes unstable when its scale increases. This paper proposed a novel overlay multicast protocol named Priority Based Overlay Multicast (POM), which uses the entities’ priority, links’ delay and node’s avail-bw to build multicast tree. By using POM the nodes with high priority receive the data in short delay, while the nodes with low priority tolerate a long delay in order to balance the available bandwidth usage among the nodes. The simulation results show that POM uses the avail-bw efficiently and keeps the system stable when its scale increases. Keywords: DIAs; Priority; Available bandwidth.
14850996
Effects of network characteristics on task performance in a desktop CVE system
The influences of network characteristics on the task performance in a desktop collaborative virtual environment (CVE) system were studied. In the experiment, two participants worked together to accomplish a collaborative task and a network emulator was utilized to simulate real network characteristics. The task used in the experiment was designed to be highly interactive and had rigid requirements on network characteristics (e.g. latency and packet loss). The objective performance and subjective assessment were recorded and analyzed quantitatively as a function of network latency and packet loss rate. The experiment results show that network latency has no distinct effect on task performance when network latency is less than 200 ms and lightly affect task performance when network latency is between 200 and 600 ms; packet loss has no effect on task performance when there are 40 state update messages received per second and lightly affect task performance when there are between 15 and 40 state update messages received per second.
32150042
Exploring Protein's Optimal Hp Configurations by Self-organizing Mapping
Self-organizing map (SOM) has been used in protein folding prediction when the HP model is employed. The existing work uses a square-like shape lattice with l = m x n points to represent the optimal compact structure of a sequence of l amino acids. In this paper, a general l'-size sequence of amino acids is self-organized in a two dimensional lattice with l (> l') points. The obtained minimum configuration then has a flexible shape, in contrast to the compact structure limited in the lattice. To fulfil this extension, a new self-organizing map (SOM) technique is proposed to deal with the difficulty of the unsymmetric input and output spaces. New competition rules in the training phase are introduced and a local search method is applied to overcome the multi-mapping phenomena. Several HP benchmark examples with up to 36 amino acids are tested to verify the effectiveness of the proposed approach in this paper.
14175949
GATES: a grid-based middleware for processing distributed data streams
Increasingly, a number of applications rely on, or can potentially benefit from, analysis and monitoring of data streams. Moreover, many of these applications involve high volume data streams and require distributed processing of data arising from a distributed set of sources. Thus, we believe that a grid environment is well suited for flexible and adaptive analysis of these streams. This paper reports the design and initial evaluation of a middleware for processing distributed data streams. Our system is referred to as GATES (grid-based adaptive execution on streams). This system is designed to use the existing grid standards and tools to the extent possible. It flexibly achieves the best accuracy that is possible while maintaining the real-time constraint on the analysis. We have developed a self-adaptation algorithm for this purpose. Results from a detailed evaluation of this system demonstrate the benefits of distributed processing, and the effectiveness of our self-adaptation algorithm.
3172403
On overlay schemes to support point-in-range queries for scalable grid resource discovery
A resource directory is a critical component of a grid architecture. P2P computing paradigm could address some of the scalability issues that make distributed resource discovery services challenging. Unfortunately, most existing distributed hash table (DHT) based P2P overlays have difficulty in treating attribute range queries that are common in resource discovery lookups. This paper proposes a general framework for range-based resource discovery. In particular, the proposed framework maps tree-structured logical data (i.e., range indexing) onto a DHT-based physical node space (i.e., resource brokers). In this paper, we consider three mapping schemes from the logical space onto the physical space. Each mapping scheme uses a different replication mechanism to reduce range search time and to achieve load balance. We analytically and experimentally compare the performance characteristics (query/update costs and workload distributions) of these schemes and discuss their applicability under different resource discovery service scenarios.
3257950
Robustness of Regional Matching Scheme over Global Matching Scheme
Analyzing the effect of concentrated noise on a typical decision-making process of a simplified two-candidate voting model, we have demonstrated that a local approach using a regional matching process is more robust and stable than a direct approach using a global matching process, by establishing that the former is capable of accommodating a higher level of noise than the latter before the result of the decision overturns. To extend the theory to imagery analysis, we pose a conjecture that our conclusion on the robustness of the regional matching processes remains valid not only for the simpler vote counting schemes but also for practically more important decision-making schemes in image analysis which involve dimension-reducing transforms or other features extraction processes such as principal component analysis or Gablor transforms. Two convincing experimental verifications are provided, supporting not only the theory by a white-black flag recognition problem on a pixel-by-pixel basis, but also the validity of the conjecture by a facial recognition problem in the presence of localized noise typically represented by clutter or occlusion in imagery.
12814139
A partitioning based algorithm to fuzzy co-cluster documents and words
In this paper, a new algorithm fuzzy co-clustering with Ruspini's condition (FCR) is proposed for co-clustering documents and words. Compared to most existing fuzzy co-clustering algorithms, FCR is able to generate fuzzy word clusters that capture the natural distribution of words, which may be beneficial for information retrieval. We discuss the principle behind the algorithm through some theoretical discussions and illustrations. These, together with experiments on two standard datasets show that FCR can discover the naturally existing document-word co-clusters.