As networks develop into large-scale systems, survivability of network systems is imperative. The systematic metrics of network survivability are used to measure or evaluate network survivability. This Paper summarize...
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With the growing utilization of ontologies in almost all branches of science and industry, not only the number of available ontologies has increased considerably but also many widely used ontologies has reached a size...
With the growing utilization of ontologies in almost all branches of science and industry, not only the number of available ontologies has increased considerably but also many widely used ontologies has reached a size that cannot be handled by the available reasoners. Due to the size and the monolithic nature of large-scale ontologies, problems with large monolithic ontologies in terms of reusability, scalability and maintenance have led to the increasing modularization techniques for ontologies. In this paper a novel two-phase partitioning approach is proposed which partitions the large ontologies into smaller modules based on the weighted graph constructed from the ontologies. In the first phase it clusters the sparse weighted graph into several sub clusters, and in the second phase it iteratively selects two clusters for which both RI and RC between them are high and merges them into one module until it has reached the original requirements. And the experiments have demonstrated that this method performs quite well.
In the area of retrieving image databases, one of the promising approaches is to retrieve it by specifying image example. However, specifying a single image example is not always sufficient to get satisfactory result,...
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Salient point is an important point feature in the content-based image retrieval. A novel image retrieval based on salient point is proposed in this paper. Firstly, an improved algorithm is presented based on SPARSE(S...
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Salient point is an important point feature in the content-based image retrieval. A novel image retrieval based on salient point is proposed in this paper. Firstly, an improved algorithm is presented based on SPARSE(Salient Points Auto-Reduction using Segmentation), which using dynamic threshold segmentation algorithm in the between-class variance and within-class variance of the image segmentation. And then three color features and three texture features are adopted by image retrieval. Experimental results show that the improved method has better performance.
In this paper, we propose a 4K digital cinema transmission over 1.2Gbps wireless LAN system. The proposed system employs the next generation wireless LAN system based on IEEE802.11ac specification. It reaches more tha...
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In this paper, we propose a 4K digital cinema transmission over 1.2Gbps wireless LAN system. The proposed system employs the next generation wireless LAN system based on IEEE802.11ac specification. It reaches more than 33 meter propagation distance by using 80MHz of bandwidth on the 5GHz band. In this system, video data is compressed by JPEG 2000 with error resilience tools. These tools improve error performance against wireless channel, and enable very high throughput communication. computer simulations are used to evaluate the bit error performance's influences to the video quality. Finally, we present RTL design results of the proposed wireless LAN system.
In this paper we consider passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms. Due to its combined passive synthetic aperture and the fixed-freq...
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ISBN:
(纸本)9781424458110
In this paper we consider passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms. Due to its combined passive synthetic aperture and the fixed-frequency nature of the transmitted waveforms, we refer to the system under consideration as Doppler Synthetic Aperture Hitchhiker (DSAH). We present a novel image formation method for DSAH. Our method first correlates the windowed signal obtained from one receiver with the windowed, filtered, scaled and translated version of the received signal from another receiver. This processing removes the transmitter related variables from the phase of the Fourier integral operator that maps the radiance of the scene to the correlated signal. We next use the microlocal analysis to reconstruct the scene radiance by the weighted-backprojection of the correlated signal. This imaging algorithm can put the visible edges of the scene radiance at the correct location, and under appropriate conditions, with correct strength. Additionally, it is an analytic reconstruction technique which can be made computationally efficient. We show that the resolution of the image is directly related to the length of the support of the windowing function and the frequency of the transmitted waveform. The image reconstruction method is applicable with both cooperative and non-cooperative sources of opportunity using one or more airborne receivers. We present numerical simulations to demonstrate the performance of the image reconstruction method and to verify the theoretical results.
A behavioral strategy designed for a humanoid robot for the purpose of obstacle avoidance based on four ultrasonic sensors for the learning behavior and performance is proposed and implemented with an autonomous human...
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Fuzzy C-Means(FCM) algorithm is one of the most popular methods for image segmentation, but it is in essence a technology of searching local optimal solution. The algorithm's initial clustering centers are the sto...
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Fuzzy C-Means(FCM) algorithm is one of the most popular methods for image segmentation, but it is in essence a technology of searching local optimal solution. The algorithm's initial clustering centers are the stochastic selection which causes it to depend on the selection of the initial cluster centers excessively. It always converges at the local optimum and is sensitive to noise. In order to overcome those defects, the fuzzy C-means cluster segmentation algorithm based on hybridized particle swarm optimization is proposed in this paper. Firstly, the hybridized particle swarm algorithm is used to get the initial cluster centers. Then, the images are segmented using standard FCM algorithm. Experimental results show that the proposed algorithm used for image segmentation can segment images more effectively and can provide more robust segmentation results.
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