We study the problem of structured motif search in DNA sequences. This is a fundamental task in bioinformatics which contributes to better understanding of genome characteristics and properties. We propose an efficien...
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This paper presents the activities carried out within SatNex on land mobile satellite and satellite-to-indoor channel modeling. SatNex is an EU Network of Excellence.
ISBN:
(纸本)9783800731527
This paper presents the activities carried out within SatNex on land mobile satellite and satellite-to-indoor channel modeling. SatNex is an EU Network of Excellence.
Information retrieval is one of the major research areas due to accumulation of huge information in digital form. Various techniques of Information retrieval are based on the fact that terms contained in a document al...
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Information retrieval is one of the major research areas due to accumulation of huge information in digital form. Various techniques of Information retrieval are based on the fact that terms contained in a document along with their frequency of occurrence signify the semantics of the document. Recent attempts to find the relevant document for a context represents documents in a vector space model as document-term vector containing term weights for every index term in that document. As there will be enormous number of index terms this leads to high dimensionality problem. We can reduce the dimensionality based on the observation that groups of terms associated with related concepts occur together or do not occur in a document based on whether the document is relevant or not to that concept. Such a group of terms Is identified as an equivalence class and can be viewed as a single dimension in a Rough set based information retrieval system. In this paper we present a hybrid clustering approach for the formation of equivalence classes of terms associated with related concepts. It uses the outcome of hierarchical clustering to provide seed points for implementing Incremental K-means algorithm. Due to the sparsity of the term vector the cosine similarity estimate was found to be ineffective for term clustering. Another promising measure of proximity estimate used in information retrieval namely Euclidian distance has a drawback that It is biased towards changes in the term frequencies in larger documents when the term weights are represented by tf-ldf estimates. Hence we propose normalization for tf-idf estimates while representing a term as a vector in a document space before clustering the terms.
MP3 allows a high compression ratio while providing high fidelity. As it has become one of the most popular digital audio formats, MP3 is also conceivably a most utilized carrier for audio steganography, therefore, MP...
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MP3 allows a high compression ratio while providing high fidelity. As it has become one of the most popular digital audio formats, MP3 is also conceivably a most utilized carrier for audio steganography, therefore, MP3 steganalysis is a topic deserving attention. In this paper, we propose a scheme for steganalysis of MP3Stego based on feature mining and pattern recognition techniques. We first extract the moment statistical features of GGD shape parameters of the MDCT sub-band coefficients, as well as the moment statistical features, neighboring joint densities, and Markov transition features of the second order derivatives of the MDCT coefficients on MPEG-1 Audio Layer 3. Support vector machines (SVM) are applied to these features for detection. Experimental results show that our method can successfully discriminate the steganograms created by using MP3stego from their MP3 covers, even with fairly low embedding ratio.
Electronic Support Measures consist of passive receivers which can identify emitters coming from a small bearing angle, which, in turn, can be related to platforms that belong to 3 classes: either Friend, Neutral, or ...
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ISBN:
(纸本)9780982443804
Electronic Support Measures consist of passive receivers which can identify emitters coming from a small bearing angle, which, in turn, can be related to platforms that belong to 3 classes: either Friend, Neutral, or Hostile. Decision makers prefer results presented in STANAG 1241 allegiance form, which adds 2 new classes: Assumed Friend, and Suspect. Dezert-Smarandache (DSm) theory is particularly suited to this problem, since it allows for intersections between the original 3 classes. Results are presented showing that the theory can be successfully applied to the problem of associating ESM reports to established tracks, and its results identify when miss-associations have occurred and to what extent. Results are also compared to Dempster-Shafer theory which can only reason on the original 3 classes. Thus decision makers are offered STANAG 1241 allegiance results in a timely manner, with quick allegiance change when appropriate and stability in allegiance declaration otherwise.
The dynamics of networks have become more and more important in all research fields that depend on network analysis. Standard network visualization and analysis tools usual do not offer a suitable interface to network...
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ISBN:
(纸本)9781605581415
The dynamics of networks have become more and more important in all research fields that depend on network analysis. Standard network visualization and analysis tools usual do not offer a suitable interface to network dynamics. These tools do not incorporate specialized visualization algorithms for dynamic networks but only algorithms for static networks. This results in layouts that bother the user with too many layout changes which makes it very hard to work with them. To handle dynamic networks the DGD-tool was implemented. It does not only provide several layout algorithms that were designed for dynamic networks but also different instruments for statistical network analysis. Network visualization and statistics are combined in a multiple view interface that allows visual comparison of several network layouts and several network metrics at the same time. Furthermore the time-dependent behaviour of structural changes becomes visible and facilitates the analysis of network dynamics. Copyright 2008 ACM.
This paper proposes an unsupervised approach to automatically interpret noun compounds using semantic similarity. Our proposed unsupervised method is based on obtaining a large amount of robust evidence for NC interpr...
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ISBN:
(纸本)9781424427802
This paper proposes an unsupervised approach to automatically interpret noun compounds using semantic similarity. Our proposed unsupervised method is based on obtaining a large amount of robust evidence for NC interpretation. In order to obtain evidence sentences for semantic relations (SRs), we first acquired sentences containing both a head noun and its modifier in the form of SR definitions. Then we determined the semantic relations represented in the sentences by looking at the nouns in the test instances (noun mapping) and verbs in the SR definitions (verb mapping). In the noun mapping, we measured the similarity between nouns in test instances and nouns in the collected sentences. In the verb mapping, we mapped the verbs ofsentences onto those in the SR definitions. Finally, we built a statistical classifier to interpret noun compounds and evaluated it over 17 SRs defined in [1].
Image inpainting or completion is a technique to restore a damaged image. Recently various approaches have been proposed. Wavelet transform has been used for various image analysis problems due to its nice multiresolu...
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The difficulty of writing, reading, and understanding formal specifications is one of the main obstacles in adopting formal verification techniques such as model checking and runtime verification. Introducing concepts...
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ISBN:
(纸本)9780769531441
The difficulty of writing, reading, and understanding formal specifications is one of the main obstacles in adopting formal verification techniques such as model checking and runtime verification. Introducing concepts in formal methods in an undergraduate program is essential for training a workforce that can develop and test high-assurance systems. This paper presents educational outcomes and outlines an instructive component that can be used in an undergraduate course to teach formal approaches and languages. The component uses a model checker and a specification tool to teach Linear Temporal Logic (LTL), a specification language that is widely used in a variety of verification tools. The paper also introduces a novel technique that analyzes LTL specifications by using the SPIN model checker to elucidate the behaviors accepted by the specifications.
software Requirements engineering addresses specific challenges which exist in the effort to gain an understanding of the nature of the engineering problem arising from user's real-world needs and desires. This re...
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ISBN:
(纸本)9788476531440
software Requirements engineering addresses specific challenges which exist in the effort to gain an understanding of the nature of the engineering problem arising from user's real-world needs and desires. This research is aimed at helping software analysts meet these challenges. The proposed methodology forms the basis of the automated process designed to capture the high-level system services and actors from the textual user requirements. This model is intended to serve as a basis for software Use-Case Model development, and can be used by analysts in their in-dept. study of requirements text. The approach is rooted in the syntactical analysis and formalization of text written in natural language, and it is enriched with domain-related information provided by the Expert Comparable Contextual (ECC) models that are extracted from reusable domain-specific data models. We illustrate the applicability of our methodology an order invoicing case study and demonstrate it with a prototype tool. The results of the validation of our methodology prove that such a tool for assisting the elicitation of use-case models from textual requirements is feasible.
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