F5 steganography is much different from most of LSB replacement or matching steganographic schemes, because matrix encoding is employed to increase embedding efficiency while reducing the number of necessary changes. ...
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F5 steganography is much different from most of LSB replacement or matching steganographic schemes, because matrix encoding is employed to increase embedding efficiency while reducing the number of necessary changes. By using this scheme, the hidden message inserted into carrier media imperceptibly can be transferred via a more secure subliminal channel. The embedding domain is the quantized DCT coefficients of JPEG image, which makes the scheme be immune to visual attack and statistical attack from the steganalyst. Based on this effective scheme, an extended matrix encoding algorithm is proposed to improve the performance further in this paper. By changing the hash function in matrix encoding and converting the coding mode, the embedding efficiency and embedding rate get increased to a large extent. Eventually, the experimental results demonstrate the extended algorithm is superior to the classic F5 steganography. (C) 2011 Elsevier Ltd. All rights reserved.
AIAC algorithms (Asynchronous Iterations Asynchronous Communications) are a particular class of parallel iterative algorithms. Their asynchronous nature makes them more efficient than their synchronous counterparts in...
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AIAC algorithms (Asynchronous Iterations Asynchronous Communications) are a particular class of parallel iterative algorithms. Their asynchronous nature makes them more efficient than their synchronous counterparts in numerous cases as has already been shown in previous works. The first goal of this article is to compare several parallel programming environments in order to see if there is one of them which is best suited to efficiently implement AIAC algorithms. The main criterion for this comparison consists in the performances achieved in a global context of grid computing for two classical scientific problems. Nevertheless, we also take into account two secondary criteria which are the ease of programming and the ease of deployment. The second goal of this study is to extract from this comparison the important features that a parallel programming environment must have in order to be suited for the implementation of AIAC algorithms.
Employing computer algorithms for finding and outlining the boundaries between phases or grain boundaries (referred to as edge detection) is a widely used technique employed as an intermediate step in microstructure a...
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Employing computer algorithms for finding and outlining the boundaries between phases or grain boundaries (referred to as edge detection) is a widely used technique employed as an intermediate step in microstructure analysis. Having an outlined region of interest enables the user to extract data about the region or use it in the reconstruction of three-dimensional models. Because traditional edge detection relies on a user-selected threshold value, the results often are subjective. Furthermore, traditional edge detection frequently results in outlines that are incomplete, requiring additional processing steps, such as edge linking and spur removal. Active contouring is an edge-detection-based technique that typically yields results superior to that of a traditional edge detector. High noise tolerance and built-in flexibilities of active contours make the technique desirable to use across a broad range of applications. Although initially used for meteorological applications, several uses of active contours are presented for metallurgical microstructural data obtained using optical and electron microscopies to demonstrate robustness and the range of applications that can employ active contours.
This paper describes an adaptive fuzzy sliding-mode control algorithm for controlling unknown or uncertain, multi-input multi-output (MIMO), possibly chaotic, dynamical systems. The control approach encompasses a fuzz...
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This paper describes an adaptive fuzzy sliding-mode control algorithm for controlling unknown or uncertain, multi-input multi-output (MIMO), possibly chaotic, dynamical systems. The control approach encompasses a fuzzy system and a robust controller. The fuzzy system is designed to mimic an ideal sliding-mode controller, and the robust controller compensates the difference between the fuzzy controller and the ideal one. The parameters of the fuzzy system, as well as the uncertainty bound of the robust controller, are tuned adaptively. The adaptive laws are derived in the Lyapunov sense to guarantee the asymptotic stability and tracking of the controlled system. The effectiveness of the proposed method is shown by applying it to some well-known chaotic systems. (C) 2009 Elsevier Ltd. All rights reserved.
Embedding of confidential data in the least significant bit of an image is still an attractive method of steganography. Utilizing the full capacity of cover images by embedding one bit of data per pixel, using methods...
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Embedding of confidential data in the least significant bit of an image is still an attractive method of steganography. Utilizing the full capacity of cover images by embedding one bit of data per pixel, using methods such as LSB flipping or LSB matching, usually decreases the security, making the algorithm vulnerable to steganalytic attacks. And then, it is proposed by an efficient high payload +/- 1 data embedding scheme(EPES) based on a special two variable binary function. This function uses the information of the least two significant bit planes of the cover image for the embedding and extraction purposes. Rather than randomly selecting +1 or -1, EPES achieves higher embedding efficiencies by choosing the correct modification component. The steganalytic method based on sample pair analysis (SPA) cannot effectively detect EPES. Hence, we propose a steganalysis by constructing adjacency pixel bits structure (SAP). The resulting detection algorithm is simple and fast. Analytical and experimental results demonstrate that the proposed method provides;higher detecting efficiency than the other steganalysis. (C) 2012 Elsevier Ltd. All rights reserved.
The currently available variable selection procedures in model-based clustering assume that the irrelevant clustering variables are all independent or are all linked with the relevant clustering variables. A more vers...
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The currently available variable selection procedures in model-based clustering assume that the irrelevant clustering variables are all independent or are all linked with the relevant clustering variables. A more versatile variable selection model is proposed, taking into account three possible roles for each variable: The relevant clustering variables, the irrelevant clustering variables dependent on a part of the relevant clustering variables and the irrelevant clustering variables totally independent of all the relevant variables. A model selection criterion and a variable selection algorithm are derived for this new variable role modeling. The model identifiability and the consistency of the variable selection criterion are also established. Numerical experiments highlight the interest of this new modeling. (C) 2009 Elsevier B.V. All rights reserved.
For the probe descending and landing safely, a neural network control method based on proportional integral observer (PIO) is proposed. First, the dynamics equation of the probe under the landing site coordinate syste...
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For the probe descending and landing safely, a neural network control method based on proportional integral observer (PIO) is proposed. First, the dynamics equation of the probe under the landing site coordinate systemis deduced and the nominal trajectory meeting the constraints in advance on three axes is preplanned. Then the PIO designed by using LMI technique is employed in the control law to compensate the effect of the disturbance. At last, the neural network control algorithm is used to guarantee the double zero control of the probe and ensure the probe can land safely. An illustrative design example is employed to demonstrate the effectiveness of the proposed control approach.
Generic programming is a programming paradigm for creation of highly resuable software components through decoupling algorithms from specific data structures which are being processed. The rise of research on ways of ...
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Generic programming is a programming paradigm for creation of highly resuable software components through decoupling algorithms from specific data structures which are being processed. The rise of research on ways of handling generic programming in various programming languages took place last years. We analyze and develop a number of generic programming features, in particular associated types and constraint propagation, for the Scala programming language designed by Martin Odersky in A parts per thousand cole Polytechnique F,d,rale de Lausanne.
Relation extraction is one of the important research topics in the field of information extraction research. To solve the problem of semantic variation in traditional semisupervised relation extraction algorithm, this...
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Relation extraction is one of the important research topics in the field of information extraction research. To solve the problem of semantic variation in traditional semisupervised relation extraction algorithm, this paper proposes a novel semisupervised relation extraction algorithm based on ensemble learning (LXRE). The new algorithm mainly uses two kinds of support vector machine classifiers based on tree kernel for integration and integrates the strategy of constrained extension seed set. The new algorithm can weaken the inaccuracy of relation extraction, which is caused by the phenomenon of semantic variation. The numerical experimental research based on two benchmark data sets (PropBank and AIMed) shows that the LXRE algorithm proposed in the paper is superior to other two common relation extraction methods in four evaluation indexes (Precision, Recall, F-measure, and Accuracy). It indicates that the new algorithm has good relation extraction ability compared with others.
For detection of damage in structures, the damage locating vector (DLV) method is adapted to account for the different types and variations of internal forces and capacities along the length of each element by using t...
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For detection of damage in structures, the damage locating vector (DLV) method is adapted to account for the different types and variations of internal forces and capacities along the length of each element by using the normalized cumulative energy instead of the normalized cumulative stress. To filter out the actual damaged elements from the identified set of potential damaged elements, an intersection scheme is proposed. A 2-D warehouse structure comprising beam and column elements with constant and varied cross-sectional areas, and truss elements is used to verify the enhancements to the DLV method. With wireless sensors being integrated into damage detection systems, practical issues need to be addressed in conjunction with the detection algorithm employed. For cases where raw signals are transmitted, the intermittent loss of data packets during transmission from the sensor nodes to the base station needs to be addressed. An algorithm to patch the lost data is proposed and when integrated with the DLV damage detection methodology, is experimentally shown to be feasible using a 3-D modular truss structure. (C) 2009 Elsevier Ltd. All rights reserved.
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