Measures of text similarity have been used for a long time in applications in natural language processing and related areas such as text mining, Web page retrieval, and dialogue systems. Existing methods for computing...
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Today software development projects fail to be delivered on time, within budget and with desired quality. Many software risk methodologies have been proposed for mitigation of risks but they do not fulfill the aim of ...
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ISBN:
(纸本)1601320884
Today software development projects fail to be delivered on time, within budget and with desired quality. Many software risk methodologies have been proposed for mitigation of risks but they do not fulfill the aim of software society because problems still exist. Herein, an attempt is made to propose a software risk model and implement in Waterfall process. It may have advantages over other models and provide opportunities to developers to use this model in Waterfall process.
A Disruption-Tolerant Network (DTN) attempts to route packets between nodes that are temporarily connected. Difficulty in such networks is that nodes have no information about the network status and contact opportunit...
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NTRU (Number Theorists aRe Us)[2] is a public key cryptosystem proposed by J. Hoffstein, J. Pipher and ***. NTRU were first presented in 1996 at the Crypto '96 Conference. It is an ultimate fast new public key cry...
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ISBN:
(纸本)160132085X
NTRU (Number Theorists aRe Us)[2] is a public key cryptosystem proposed by J. Hoffstein, J. Pipher and ***. NTRU were first presented in 1996 at the Crypto '96 Conference. It is an ultimate fast new public key cryptosystem. NTRU dominates its main rivals RSA, ECC and some other public key cryptosystems. The working mechanism is very simple, which best fits for devices with limited resources, such as smart cards. Most chips on smart cards can't process keys extending 1024 bits. This shows that there is a need for alternative public key crypto system like NTRU, which takes less resources and works fast than other public crypto systems and gives expected security. In this paper we presented some issues for an element to be invertible in the Rings (Z/pZ) [X]/ (XN-1) and (Z/qZ) [X]/ (XN- 1).
In recent years, Steganography and Steganalysis are two important areas of research that involve a number of applications. These two areas of research are important especially when reliable and secure information exch...
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ISBN:
(纸本)1424424089
In recent years, Steganography and Steganalysis are two important areas of research that involve a number of applications. These two areas of research are important especially when reliable and secure information exchange is required. Steganography is an art of embedding information in a cover image without causing statistically significant variations to the cover image. Steganalysis is the technology that attempts to defeat Steganography by detecting the hidden information and extracting. In this paper we propose an image Steganography that can verify the reliability of the information being transmitted to the receiver. The method can verify whether the attacker has tried to edit, delete or forge the secret information in the stego-image. The technique embeds the hidden information in the spatial domain of the cover image and uses two special AC coefficients of the Discrete Wavelet Transform domain to verify the veracity (integrity) of the secret information from the stego image. The analysis shows that the BER and PSNR is improved in the case of DWT than DCT.
This work deals with hyperspectral image analysis in the absence of ground-truth. The method adopts a projection pursuit (PP) procedure with entropy index to reduce the dimensionality followed by Markov Random Field (...
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ISBN:
(纸本)9781615677184
This work deals with hyperspectral image analysis in the absence of ground-truth. The method adopts a projection pursuit (PP) procedure with entropy index to reduce the dimensionality followed by Markov Random Field (MRF) model based segmentation. Ordinal optimization approach to PP determines a set of "good enough projections" with high probability the best among which is chosen with the help of MRF model based segmentation. The segmented output so obtained is labeled with desired number of landcover classes in the absence of ground-truth. While comparing with original hyperspectral image the methodology outperforms principal component analysis with respect to class separation as exhibited in the illustration of an archive EO-1 hyperspectral image. The technique is not a computational intensive as is usually the case in hyperspectral image analysis. When training samples are available, the segmented regions yields a classified image with any cluster validation technique viz.[12].
It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval (IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will incre...
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The objective of the study is to establish the technologies of automatic similarity analysis and comparison of two method patents in order to reduce the cost and human efforts. We propose a method to compare the simil...
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The objective of the study is to establish the technologies of automatic similarity analysis and comparison of two method patents in order to reduce the cost and human efforts. We propose a method to compare the similarity between the components and prepositions. The proposed methods automatically extract components, relations between components, steps, and relations between steps, and establish a machine readable tree structures for similarity comparison. Our experiments use the USPTO database [1] as data resource. The study conducts two experiments to evaluate the performance: 1) applying genetic algorithms to learn the weightings in calculation of step similarity and 2) comparing the performance with a statistical similarity calculation method, BLEU. The experimental results show that the system performs better in terms of recall and precision than BLEU methods that are usually adopted in machine translation.
Due to the complexity of the biological networks, it is difficult to extract the conserved modules across species with graphical representation. One of the arising challenges is to compare different networks in order ...
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ISBN:
(纸本)1601320558
Due to the complexity of the biological networks, it is difficult to extract the conserved modules across species with graphical representation. One of the arising challenges is to compare different networks in order to analyze and discover common sub-networks, especially cliqued structure of protein complexes that may share similar biological functions. We combine sequence alignment and ontology-based semantic similarity score to cluster potential orthologous proteins and use depth-first search for network comparison to discover the conserved networks and protein complexes across species. This method allows the biological evolutions such as duplication and divergence to be tolerated in the network alignment process under a user specified value Ε. We apply network alignment for two large protein-protein interactions (Saccharomyces cerevisiae and Caenorhabditis elegans) as our test data. We detect a large number of conserved networks and true complexes that match in the yeast MIPS database.
Owning to the great growth of e-learning objects, authorities (e.g. ADL and IEEE) have developed some metadata standards to facilitate the keyword search for various e-learning applications. However, too much fields, ...
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ISBN:
(纸本)9789868473522
Owning to the great growth of e-learning objects, authorities (e.g. ADL and IEEE) have developed some metadata standards to facilitate the keyword search for various e-learning applications. However, too much fields, such as 58 blank fields in IEEE LOM, waiting for authors or annotators to fill up become an endless nightmare. In order to reach our vision of sharing and reusing valuable assets, the needs for an intelligent and automatic annotation system become more and more urgent. Among these 58 elements, it is the most difficult to extract the fittest solutions for Description, which calls for the advanced Chinese language processing technologies to generate the suitable value. We also adopted the Self-Organizing Map clustering method from Neural Networks, feature selection from Information Retrieval, and Latent Semantic Analysis from Linguistics to cope with the automatic annotation problem. In this paper, we proposed a novel approach called Clustering Descriptor, CD, to automatically generate the description metadata in TW LOM - a Learning Object Metadata application profile in Taiwan. Then, we conducted two experiments to evaluate the annotation quality for Description data element in terms of three parameters: clustering, feature weight, and semantics. Because of the benefits from clustering and feature weight, Clustering Descriptor achieved improvement in precision rate: 6.30% (clustering) and 8.60% (clustering plus feature weight) compared with the baseline.
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