One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are ...
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One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider the router node placement problem in WMNs. We want to find the optimal distribution of router nodes in order to provide the best network connectivity and user coverage in a set of uniformly distributed clients. From the simulation results, we conclude that, when the number of mesh clients is small, a small number of mesh routers are needed in order to optimize the size of Giant Component (GC) and number of covered mesh clients (NCMC). However, some of mesh routers can not cover the clients. On the other hand, when the number of mesh clients is big, many mesh routers are needed to optimize the GC and the NCMC. In this case, a mesh router can cover more than one mesh clients.
Wordnets are lexico-semantic resources essential in many NLP tasks. Princeton WordNet is the most widely known, and the most influential, among them. Wordnets for languages other than English tend to adopt unquestioni...
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Wordnets are lexico-semantic resources essential in many NLP tasks. Princeton WordNet is the most widely known, and the most influential, among them. Wordnets for languages other than English tend to adopt unquestioninglyWordNet's structure and its net of lexicalised concepts. We discuss a large wordnet constructed independently of WordNet, upon a model with a small yet significant difference. A mapping ontoWordNet is under way;the large portions already linked open up a unique perspective on the comparison of similar but not fully compatible lexical resources. We also try to characterise numerically a wordnet's aptitude for NLP applications.
The article analyzes consecutive phases of time series modelling with Fuzzy Cognitive Maps. The subject of interest are features determining models of good quality. First, we present the procedure: design phase, learn...
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The article analyzes consecutive phases of time series modelling with Fuzzy Cognitive Maps. The subject of interest are features determining models of good quality. First, we present the procedure: design phase, learning phase, and in the end - application. The discussion is illustrated with experiments on two synthetic time series. We have shown that the design phase determines qualitative and quantitative effectiveness of modelling. We have addressed effects of misdesigns: too large, too small or unfit at all maps on modelling quality.
The rapid development in wireless technologies and multimedia services has given rise to new requirements for the Internet, such as supporting billions of mobile devices and transmitting huge amount of multimedia cont...
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ISBN:
(纸本)9781479930845
The rapid development in wireless technologies and multimedia services has given rise to new requirements for the Internet, such as supporting billions of mobile devices and transmitting huge amount of multimedia content in real time. Content-Centric Networking (CCN), a future Internet architecture for efficient content dissemination, has been attracting ever-increasing attention from both academia and industry. In this paper, a new analytical model is developed as a cost-effective tool to investigate the performance of caching in CCN under bursty content requests. The accuracy of the model is validated through comparing the analytical results with those obtained from the extensive simulation experiments. As an example of its applications, the analytical model is used to investigate the effects of the cache size, content size, and bursty content requests on the cache hit ratio in CCN.
Classification, especially in the case of a small space of features, is prone to errors. This is more important when it is costly to gain data from samples to calculate the values for futures. We study what effect lim...
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Classification, especially in the case of a small space of features, is prone to errors. This is more important when it is costly to gain data from samples to calculate the values for futures. We study what effect limiting the space of features has on the performance of built classifiers and how the quality of classification can be improved by rejecting misclassified elements.
The problem of adaptively equalizing doubly dispersive MIMO channels for FBMC/OQAM systems is studied in this paper. The challenges in this type of multicarrier systems include their intrinsic self-interference and th...
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ISBN:
(纸本)9781479958641
The problem of adaptively equalizing doubly dispersive MIMO channels for FBMC/OQAM systems is studied in this paper. The challenges in this type of multicarrier systems include their intrinsic self-interference and the need to cope with time- and frequency-selective subchannels in realistic propagation conditions. An efficient and numerically stable algorithm is adopted, relying on a decision feedback structure that implements BLAST ordering for the input signals recovery. The ability of this algorithm to address the above challenges has been demonstrated. The focus of this paper is on reducing the needs of this equalizer in training information. A channel estimate-based (re-)initialization scheme is developed and shown to be quite effective in lowering the training overhead, at an affordable additional cost in complexity. For the sake of comparison, the MIMO-OFDM problem is also studied. Simulation results for practical scenarios demonstrate the effectiveness of the proposed approach.
We present a simple and versatile formulation of grid-based graph representation problems as an integer linear program (ILP) and a corresponding SAT instance. In a grid-based representation vertices and edges correspo...
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In this paper,we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape *** construction is based on the definition of a diffusion process...
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In this paper,we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape *** construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric *** results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.
We demonstrate two 8×1 silicon ring-based multiplexers for dual stream multiplexing. All resonances were thermo-optically tuned and spaced by 100GHz having >40GHz bandwidth. Error-free performance without sign...
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We demonstrate two 8×1 silicon ring-based multiplexers for dual stream multiplexing. All resonances were thermo-optically tuned and spaced by 100GHz having >40GHz bandwidth. Error-free performance without significant signal degradation was obtained for two 4-channel streams at 10Gb/s.
This paper presents an approach to rebuild the benefits lost from moving from traditional Instructor-led Training to Web-based Training by using computer-Supported Collaborative Learning and Social Networks. The innov...
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This paper presents an approach to rebuild the benefits lost from moving from traditional Instructor-led Training to Web-based Training by using computer-Supported Collaborative Learning and Social Networks. The innovative approach of using Learning Analytics and Educational Data Mining techniques to track and analyse the interactive behavior of on-line collaborative learning and social networks is explored to enhance and improve corporate distance training. The results of this multidisciplinary proposal addressing pedagogical, technological and business issues to support Web-based Training becomes decisive for enhancing and improving the overall distance training experience and for finding new opportunities for cost-effective ways to deliver training programs. We believe the outcomes of this research will be crucial for greatly enhance and improve corporate distance training.
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