In wireless multimedia networks, there exists traffic asymmetry between uplink and downlink channels. The CDMA/TDD system can alleviate this problem, however, previous work in this area can not manage efficiently the ...
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In wireless multimedia networks, there exists traffic asymmetry between uplink and downlink channels. The CDMA/TDD system can alleviate this problem, however, previous work in this area can not manage efficiently the traffic, asymmetry among cells. In this paper, we propose a new time slot allocation scheme that considers the traffic pattern of each cell. To solve the inter-cell interference problem, we divide a cell's area into two regions and we allocate the resource of crossed slots to mobile stations which are existing in the inner-region. This proposed scheme increases the resource utilization and decreases the blocking probability of the system as a whole. And our DARD (Different time slot Allocation based on a Region Division) scheme outperforms conventional SA (Same time slot Allocation) scheme in the heterogeneous traffic environment.
This paper describes computational methods that have been developed to automatically detect and quantify corrosion on images of aircraft panels obtained using nondestructive inspection (NDI) techniques. Images obtaine...
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This paper describes computational methods that have been developed to automatically detect and quantify corrosion on images of aircraft panels obtained using nondestructive inspection (NDI) techniques. Images obtained from NDI techniques are not directly suitable for corrosion analysis. We propose a multi-resolution wavelet analysis to segment the NDI images to isolate the corroded regions from the undamaged regions. Wavelet coefficients were extracted from each segment and subjected to a multivariate data analysis to obtain the most relevant features. These features are then used to identify the corroded region on the images and also to estimate the extent of damage, in terms of material loss, using backpropagation neural networks. Experiments were conducted to test the developed modules on images obtained from the Air Force Research Lab in Dayton, Ohio. The results obtained prove the feasibility and robustness of our approach in detecting the damaged regions and for estimating the material loss due to corrosion.
A modified constant modulus algorithm (MCMA) for adaptive equalization of the wireless indoor channel for QAM signals is presented. The algorithm minimizes an error cost function that includes both the amplitude and p...
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A modified constant modulus algorithm (MCMA) for adaptive equalization of the wireless indoor channel for QAM signals is presented. The algorithm minimizes an error cost function that includes both the amplitude and phase of the equalizer output. In addition to the amplitude-dependent term that is provided by the conventional constant modulus algorithm (CMA), the cost function includes a signal constellation matched error (CME) term. This term speeds up convergence and allows the equalizer to switch to decision directed (DD), or any soft-decision mode, faster than the CMA applied alone. The constellation-matched error term is constructed using polynomials with desirable properties. The MCMA is applied to a decision feedback equalizer and shown to provide improved performance over dual mode techniques.
A decision tree is a good classifier with a transparent decision mechanism. Decision-tree building methods usually have problems in splitting the learning samples into more subsets, because of the nature of the tree. ...
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A decision tree is a good classifier with a transparent decision mechanism. Decision-tree building methods usually have problems in splitting the learning samples into more subsets, because of the nature of the tree. If the classification into such subsets is not possible, it is better to put the classification decision on to some other classifier. This leads to the introduction of a null classification, which simply means that no classification is possible in this step. This approach is sensible with evolutionary methods, as they can handle a number of trees simultaneously. In the process of construction, we have to address the problem of whether a classification is sensible. The performance of the proposed model has been tested on several data sets and the results presented on one such data set show its potential.
In this paper, an affinity-based approach that provides good similarity measures for Web document clustering to discover user access behavior on the World Wide Web (WWW) is proposed. The proposed approach generates th...
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In this paper, an affinity-based approach that provides good similarity measures for Web document clustering to discover user access behavior on the World Wide Web (WWW) is proposed. The proposed approach generates the similarity measures for groups of Web documents by considering the user access patterns. Any clustering algorithm using better similarity measures should yield better clusters for discovering user access behavior. By utilizing the discovered user access behavior, for example, the companies can precisely target their potential customers and convince them to purchase their products or services in electronic commerce. An experiment on a real data set is conducted and the experimental result shows that the proposed approach yields a better performance than the cosine coefficient and the Euclidean distance method under the partitioning around medoid (PAM) method.
In this paper a novel unsupervised segmentation framework for texture image queries is presented. The proposed framework consists of an unsupervised segmentation method for texture images, and a multi-filter query str...
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In this paper a novel unsupervised segmentation framework for texture image queries is presented. The proposed framework consists of an unsupervised segmentation method for texture images, and a multi-filter query strategy. By applying the unsupervised segmentation method on each texture image, a set of texture feature parameters for that texture image can be extracted automatically. Based upon these parameters, an effective multi-filter query strategy which allows the users to issue texture-based image queries is developed The test results of the proposed framework on 318 texture images obtained from the MIT VisTex and Brodatz database are presented to show its effectiveness.
We implemented POPeye (Probe of Performance+eye), a system analysis simulator to evaluate DRAM performance in a personal computer environment. When running any real-life application programs such as Microsoft Office a...
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Summary form only given. Polarization mode dispersion (PMD) is a limiting factor for higher bit rate in optical transmission lines. Due to the complexity of calculating the complete set of PMD parameters a simple repr...
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Summary form only given. Polarization mode dispersion (PMD) is a limiting factor for higher bit rate in optical transmission lines. Due to the complexity of calculating the complete set of PMD parameters a simple representation is needed before real time PMD compensation can be realized. We used several broadband sources such as a multimode Fabry-Perot laser, ASE from an EDFA and 10 Gb/s NRZ data carried on a modulated CW source. A scanning polarization controller varies the input state of polarization of the source uniformly on the Poincare sphere at the input of the fiber transmission line under test. At the output, we use a HP8509B polarization analyzer to record the output state of polarization and the degree of polarization (DOP) as a function of time.
Recently, the Intelligent Transportation systems (ITS) have been identified as the new paradigm to address the growing mobility problems, and to alleviate congestion and augment the quality of vehicular flow. This pap...
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Recently, the Intelligent Transportation systems (ITS) have been identified as the new paradigm to address the growing mobility problems, and to alleviate congestion and augment the quality of vehicular flow. This paper presents an intelligent and automatic framework for spatio-temporal vehicle tracking in video sequences in order to provide useful information to the traffic control center. The spatio-temporal relationships of the objects are captured automatically via a proposed unsupervised image/video segmentation method and multimedia input strings. A traffic video sequence is used to demonstrate the effectiveness of the proposed framework to identify and track the vehicle objects in the video sequence.
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