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Background: Electrocardiograms (ECGs) are routinely recorded and stored in a variety of paper or scanned image format. Current ECG recording machines record ECG on graph paper, also it provides digitized ECG signal along with automated cardiovascular diagnosis (CVD). However, such recording machines cannot analyse preserved paper ECG records as it requires input in terms of digitized signal. Therefore, it is important to extract ECG signal from these preserved paper ECG records using digitization method. There are different paper degradations that adversely affect digitization process. The purpose of this work is to perform an image enhancement and digitization of the degraded ECG images to extract continuous ECG signal., Methods: In this paper, we propose entropy-based bit plane slicing (EBPS) algorithm in which pre-processing is done using dominant color detection and local bit plane slicing. Maximum entropy based adaptive bit plane selection is applied to the pre-processed image. Discontinuous ECG correction (DECGC) is then done to produce continuous ECG signal., Results: The algorithm is tested on 836 different degraded paper ECG records obtained from various diagnostic centers. After analysis with 101 known ground truth ECG signals the accuracy, sensitivity, specificity and overall F-measure of ECG is 99.42%, 99.69%, 99.81% and 99.26% respectively. The RMS error and correlation between the extracted digitized signal and ground truth for 101 cases is 0.040 and 99.89% respectively., Conclusions: The EBPS method is able to remove all types of degradation in paper ECG records to generate a uniform digitized signal. Instead of manual measurement and prediction from archived paper ECG records, automated prediction (using already existing cardiovascular diagnosis software) is possible with the help of extracted digitized signal obtained using proposed digitization method, which will also help retrospective cardiovascular analysis., (Copyright © 2018 Elsevier Inc. All rights reserved.)

We study the static and dynamic properties of networks of crumpled creases formed in hand crushed sheets of paper. The fractal dimensionalities of crumpling networks in the unfolded (flat) and folded configurations are determined. Some other noteworthy features of crumpling networks are established. The physical implications of these findings are discussed. Specifically, we state that self-avoiding interactions introduce a characteristic length scale of sheet crumpling. A framework to model the crumpling phenomena is suggested. Mechanics of sheet crushing under external confinement is developed. The effect of compaction geometry on the crushing mechanics is revealed.

We study the effects of ambient air humidity on the dynamics of imbibition in a paper. We observed that a quick increase of ambient air humidity leads to depinning and non-Washburn motion of wetting fronts. Specifically, we found that after depinning the wetting front moves with decreasing velocity v[proportionality](h(p)/h(D))(γ), where h(D) is the front elevation with respect to its pinned position at lower humidity h(p), while γ=/~1/3. The spatiotemporal maps of depinned front activity are established. The front motion is controlled by the dynamics of local avalanches directed at 30° to the balk flow direction. Although the roughness of the pinned wetting front is self-affine and the avalanche size distribution displays a power-law asymptotic, the roughness of the moving front becomes multiaffine a few minutes after depinning.

Good cross-directional control of sheet variables in a paper machine depends on a number of factors. One such factor is the correct alignment of actuators with their corresponding responses. The alignment changes with time either locally or across the whole paper sheet due to a variety of reasons. In this paper, we provide an online mapping technique based on estimating the cross-correlation between actuator movement and the measurements. This procedure involves two steps-in the first step (called alignment monitoring) we determine if the current mapping is wrong at any CD position, and in the second step (called re-mapping), the alignment of actuators is corrected. The main advantage of this method is in its ability to re-align under closed loop conditions with minimal operational disruption.

We explore the application of terahertz spectroscopic techniques for the remote determination of the water content of paper. The aim is the development of a rapid diagnostic imaging tool applicable in paper fabrication processes. THz radiation offers a high sensitivity for water, a good spatial resolution, and insensitivity to scattering at the paper surface. The advent of THz cameras makes fast large-area image detectors feasible. In this paper, we show for the case of a 0.6-THz fixed-frequency system, that the water content of paper can be determined with high accuracy. We demonstrate a quantitative (calibrated) method for determining the moisture content in paper based on extinction and phase measurements in the lower THz range with a spatial resolution in the mm-range and scanning times below two minutes.

Pulping production process produces a large amount of wastewater and pollutant emitted, which has become one of the main pollution sources in pulp and paper industry. To solve this problem, it is necessary to implement cleaner production by using modeling and optimization technology. This paper studies the modeling and multi-objective genetic algorithms for continuous digester process. First, model is established, in which environmental pollution and saving energy factors are considered. Then hybrid genetic algorithm based on Pareto stratum-nichecount is designed for finding near-Pareto or Pareto optimal solutions in the problem and a new genetic evaluation and selection mechanism is proposed. Finally using the real data from a pulp mill shows the results of computer simulation. Through comparing with the practical curve of digester, this method can reduce the pollutant effectively and increase the profit while keeping the pulp quality unchanged.

Digital automation in reconstruction of apictorial hand torn paper document increases efficacy and reduces human effort. Reconstruction of torn document has importance in various fields like archaeology, art conservation and forensic sciences. The devised novel technique for hand torn paper document, consists of pre-processing, feature extraction and reconstruction phase. Torn fragment's boundaries are simplified as polygons using douglas peucker polyline simplification algorithm. Features such as Euclidean distance and number of sudden changes in contour orientation are extracted. Our matching criteria identify the matching counterparts. Proposed features curtail ambiguity and enriches efficacy in reconstruction. Reconstructed results of hand torn paper document favour the proposed methodology. [ABSTRACT FROM AUTHOR]

A novel algorithm has been developed and validated to isolate individual papermaking fibres in micro-computed tomographic images of paper handsheets as a first step to characterize the structure of the paper. The three-step fibre segmentation algorithm segments the papermaking fibres by (i) tracking the hollow inside the fibres via a modified connected component methodology, (ii) extracting the fibre walls using a distance transform and (iii) labelling the fibres through collapsed sections by a final refinement step. Furthermore, postprocessing algorithms have been developed to calculate the length and coarseness of the segmented fibres. The fibre segmentation algorithm is the first ever reported method for the automated segmentation of the tortuous three-dimensional morphology of papermaking fibres within microstructural images of paper handsheets. The method is not limited to papermaking fibres, but can be applied to any material consisting of tortuous and hollow fibres. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents a sufficient condition for observability of continuous-time switched nonlinear systems that also involve state jumps. Without the assumption of observability of individual modes, the sufficient condition is based on gathering partial information from each mode so that the state is completely recovered after several switchings. Based on the sufficient condition, a hybrid-type observer is designed, which comprises a copy of the actual plant and an error correction scheme at discrete time instants. In order to execute the proposed design, the observable component of the state at each mode needs to be estimated without transients or 'peaking' (caused by high-gain observers), and this motivates us to introduce a back-and-forth estimation technique. Under the assumption of persistent switching, analysis shows that the estimate thus generated converges asymptotically to the actual state of the system. Simulation results validate the utility of the proposed algorithm. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The increasing penetration of distributed generation (DG) sources in low-voltage grid feeders causes problems concerning voltage regulation. The penetration of DG sources such as photovoltaics (PVs) in the distribution system can significantly impact the power flow and voltage conditions on the customer side. As the DG sources are more commonly connected to low-voltage distribution systems, voltage fluctuations in the distribution system are experienced because of the DG fluctuation and uncertainty. Therefore, the penetration of DGs in distribution systems is often limited by the required operating voltage ranges. By using an energy storage system (ESS), voltage fluctuation can be compensated for, thus satisfying the voltage regulation requirements. This paper presents an ESS scheduling algorithm based on the power injection data obtained from a smart metering system. The proposed ESS scheduling algorithm is designed for use within a direct current (DC) distribution grid, which comprises customers, each with a PV and an ESS system. The purpose of this ESS scheduling algorithm is to optimize the ESS scheduling by considering the complementary operation among all the ESSs. [ABSTRACT FROM AUTHOR]

Abstract: In school, at least in the US, we were taught to multiply by hand according to a standard algorithm. Most people find that algorithm difficult to use, and many children fail to learn it. We propose a new way to make sense of this difficulty: to treat explicit computation as perceptually supported physical and mental action. Based on recent work in neuroscience, we trace the flow of arithmetic information to emphasize demands on visual working memory and attention. We predict that algorithms that make moderate demands on memory and attention will work better than others that make stronger demands. We suggest that the judicious use of spatial schemas can reduce such cognitive demands. Experimental evidence from children in an inner-city school supports this claim. Our work suggests new ways to think about instruction. The goal should be to minimize demands that present obstacles and maximize instead what human eyes, bodies, and brains do well. [Copyright &y& Elsevier]

Algorithm performance evaluation is so entrenched in the machine learning community that one could call it an addiction. Like most addictions, it is harmful and very difficult to give up. It is harmful because it has serious limitations. Yet, we have great faith in practicing it in a ritualistic manner: we follow a fixed set of rules telling us the measure, the data sets and the statistical test to use. When we read a paper, even as reviewers, we are not sufficiently critical of results that follow these rules. Here, we will debate what are the limitations and how to best address them. This article may not cure the addiction but hopefully it will be a good first step along that road. [ABSTRACT FROM AUTHOR]

After a quick review of the most used numerical indicators for evaluating research, we present an integrated model for ranking scientific publications together with authors and journals. Our model relies on certain adjacentcy matrices obtained from the relationship between papers, authors, and journals. These matrices are first normalized to obtain stochastic matrices and then are combined together using appropriate weights to form a suitable irreducible stochastic matrix whose dominant eigenvector provides the desired ranking. Our main contribution is a in-depth analysis of various strategies for choosing the weights, showing their probabilistic interpretation and showing how they affect the outcome of the ranking process. We also prove that, by solving an inverse eigenvector problem, we can determine a weighting strategy in which the relative importance of papers, authors, and journals is chosen by the final user of the ranking algorithm. The impact of the different weighting strategies is analyzed also by means of extensive experiments on large synthetic datasets. [ABSTRACT FROM AUTHOR]

In this paper, we extend the notion of similarity matrix, which has been used to define similarity between nodes of two graphs, to the case of colored graphs, where the coloring is either on the nodes or on the edges of both graphs. The proposed method tries to find the optimal matching between the nodes or edges of both graphs but only performs the comparison when their colors are the same. The proposed cost function nevertheless uses the connectivity between all nodes and edges of both graphs. We then also show how to extend this to the notion of low rank similarity matrix, by defining it as a constrained optimization problem. [ABSTRACT FROM AUTHOR]

The array redistribution problem occurs in many important applications in parallel computing. In this paper, we consider this problem in a torus network. Tori are preferred to other multidimensional networks (like hypercubes) due to their better scalability (IEE Trans. Parallel Distrib. Syst. 50(10), 1201–1218, []). We present a message combining approach that splits any array redistribution problem in a series of broadcasts where all sources send messages of the same size, thus a balanced traffic load is achieved. Unlike existing array redistribution algorithms, the scheme introduced in this work eliminates the need for data reorganization in the memory of the source and target processors. Moreover, the processing of the scheduled broadcasts is pipelined, thus the total cost of redistribution is reduced. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we kernelize conventional clustering algorithms from a novel point of view. Based on the fully mathematical proof, we first demonstrate that kernel KMeans (KKMeans) is equivalent to kernel principal component analysis (KPCA) prior to the conventional KMeans algorithm. By using KPCA as a preprocessing step, we also generalize Gaussian mixture model (GMM) to its kernel version, the kernel GMM (KGMM). Consequently, conventional clustering algorithms can be easily kernelized in the linear feature space instead of a nonlinear one. To evaluate the newly established KKMeans and KGMM algorithms, we utilized them to the problem of semantic object extraction (segmentation) of color images. Based on a series of experiments carried out on a set of color images, we indicate that both KKMeans and KGMM can offer more elaborate output than the conventional KMeans and GMM, respectively. [Copyright &y& Elsevier]

Abstract: This paper presents a novel algorithm for computing graph edit distance (GED) in image categorization. This algorithm is purely structural, i.e., it needs only connectivity structure of the graph and does not draw on node or edge attributes. There are two major contributions: (1) Introducing edge direction histogram (EDH) to characterize shape features of images. It is shown that GED can be employed as distance of EDHs. This algorithm is completely independent on cost function which is difficult to be defined exactly. (2) Computing distance of EDHs with earth mover distance (EMD) which takes neighborhood bins into account so as to compute distance of EDHs correctly. A set of experiments demonstrate that the newly presented algorithm is available for classifying and clustering images and is immune to the planar rotation of images. Compared with GED from spectral seriation, our algorithm can capture the structure change of graphs better and consume 12.79% time used by the former one. The average classification rate is 5% and average clustering rate is 25% higher than the spectral seriation method. [Copyright &y& Elsevier]

Abstract: -Means algorithm and its variations are known to be fast clustering algorithms. However, they are sensitive to the choice of starting points and inefficient for solving clustering problems in large data sets. Recently, a new version of the -means algorithm, the global -means algorithm has been developed. It is an incremental algorithm that dynamically adds one cluster center at a time and uses each data point as a candidate for the -th cluster center. Results of numerical experiments show that the global -means algorithm considerably outperforms the -means algorithms. In this paper, a new version of the global -means algorithm is proposed. A starting point for the -th cluster center in this algorithm is computed by minimizing an auxiliary cluster function. Results of numerical experiments on 14 data sets demonstrate the superiority of the new algorithm, however, it requires more computational time than the global -means algorithm. [Copyright &y& Elsevier]

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Since H.264/A VC achieves a high compression atio by reducing spatio-temporal redundancy in video equences, the payload of a single packet can often contain a vhole frame encoded by H.264/AVC. Therefore, the loss of a ingle packet does not only cause the loss of a whole frame, `ut also produce error propagation into succeeding frames. ~o deal with this problem, in this paper, we propose a novel ~rame error concealment method for ff264/A VC. First, the iroposed method extrapolates motion vectors from available reighboring frames onto the lost frame. Then, inter-modes of rh macroblocks in the lost frame are adaptively estimated by rsing the extrapolated motion vectors and features of 1.264/A VC. Experimental results exhibit that the proposed ~iethod outperforms the conventional methods in terms of roth objective and subjective video quality. [ABSTRACT FROM AUTHOR]

This paper presents an integrated color imaging system for taking images in extremely high dynamic range scenes. The system first fuses several differently exposed raw images to acquire more intensity information. The effective dynamic range of the image raw data can be extended to 256 times ~five differently exposed images are fused. Then it runs edge detection iterations to extract the image details in different luminance levels. The proposed tone reproduction algorithm equalizes the histogram of the extracted fine edges which tends to assign larger dynamic range for highly populated regions. Finally, the local contrast enhancement is performed to further refine the image details. The experimental results show that the proposed high dynamic range imaging system has good performance on both tone and color reproduction'. [ABSTRACT FROM AUTHOR]

A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences. [ABSTRACT FROM AUTHOR]

Abstract: Phylogenetic trees are an important tool to help in the understanding of relationships between objects that evolve through time, in particular molecular sequences. In this paper, we efficiently solve two subtree-comparison problems on a set of phylogenetic trees which have practical applications to analyze the evolution and co-evolution genes clustering of genomic sequences. Let be a set of k phylogenetic trees such that the leaves of each tree are drawn from and the leaves for two arbitrary trees are not necessary the same, where n is the maximum number of the leaves among the k trees. We present a linear-time algorithm to find all the leaf-agreement descendant subtrees. By further extending this result, we present a linear-time algorithm to find all the leaf-agreement isomorphic descendant subtrees. Based on our algorithms, a web-based system using input tree files from TreeBASE is also implemented. [Copyright &y& Elsevier]

The simulation of rubber-like materials is usually based on hyperelasticity. If strain-rate dependency has to be considered viscous dampers also have to be taken into account in the rheological model. A disadvantage of such a description is time-consuming parameter identification associated with the damping constants. In this paper, a tabulated formulation is presented which allows the fast generation of input data based on uniaxial static and dynamic tensile tests at different strain rates. Unloading, i.e. forming a hysteresis loop, can also be modeled easily based on a damage formulation. We show the theoretical background and algorithmic setup of our model that has been implemented in the explicit finite element program LS-DYNA [1-3]. Apart from purely numerical examples, the validation of a soft and a hard rubber under loading and subsequent unloading at different strain rates is shown. [ABSTRACT FROM AUTHOR]

This paper investigates algorithms of motion planning for a six-legged walking machine over complex terrain. Application of the Rodrigues-Hamilton parameters for describing the orientation of the body enables one to develop algorithms of motion planning for the body and legs in an absolute coordinate frame with automatic adaptation to the surface. Experiments with a laboratory scale walking machine have demonstrated the efficiency of proposed algorithms. [ABSTRACT FROM AUTHOR]

Modern information retrieval systems use keywords within documents as indexing terms for search of relevant documents. As Chinese is an ideographic character-based language, the words in the texts are not delimited by white spaces. Indexing of Chinese documents is impossible without a proper segmentation algorithm. Many Chinese segmentation algorithms have been proposed in the past. Traditional segmentation algorithms cannot operate without a large dictionary or a large corpus of training data. Nowadays, the Web has become the largest corpus that is ideal for Chinese segmentation. Although most search engines have problems in segmenting texts into proper words, they maintain huge databases of documents and frequencies of character sequences in the documents. Their databases are important potential resources for segmentation. In this paper, we propose a segmentation algorithm by mining Web data with the help of search engines. On the other hand, the Romanized pinyin of Chinese language indicates boundaries of words in the text. Our algorithm is the first to utilize the Romanized pinyin to segmentation. It is the first unified segmentation algorithm for the Chinese language from different geographical areas, and it is also domain independent because of the nature of the Web. Experiments have been conducted on the datasets of a recent Chinese segmentation competition. The results show that our algorithm outperforms the traditional algorithms in terms of precision and recall. Moreover, our algorithm can effectively deal with the problems of segmentation ambiguity, new word (unknown word) detection, and stop words. [ABSTRACT FROM AUTHOR]

With more and more information available on the Internet, the task of making personalized recommendations to assist the user's navigation has become increasingly important. Considering there might be millions of users with different backgrounds accessing a Web site everyday, it is infeasible to build a separate recommendation system for each user. To address this problem, clustering techniques can first be employed to discover user groups. Then, user navigation patterns for each group can be discovered, to allow the adaptation of a Web site to the interest of each individual group. In this paper, we propose to model user access sequences as stochastic processes, and a mixture of Markov models based approach is taken to cluster users and to capture the sequential relationships inherent in user access histories. Several important issues that arise in constructing the Markov models are also addressed. The first issue lies in the complexity of the mixture of Markov models. To improve the efficiency of building/maintaining the mixture of Markov models, we develop a lightweight adapt-ive algorithm to update the model parameters without recomputing model parameters from scratch. The second issue concerns the proper selection of training data for building the mixture of Markov models. We investigate two different training data selection strategies and perform extensive experiments to compare their effectiveness on a real dataset that is generated by a Web-based knowledge management system, Livelink. [ABSTRACT FROM AUTHOR]

This paper investigates the use of Particle Swarm Optimization (PSO) for cluster analysis. In clustering, primitive exploration with minimum prior knowledge consists of research across a wide variety of communities. The diversity in the field of PSO-based clustering equips us with many tools. This paper provides an integrated framework of the diversified PSO-based clustering. In addition, a novel Particle Swarm Optimization (PSO) algorithm using the concept of aging of particles like bird within a flock is provided. The effectiveness of this concept is demonstrated by cluster analysis. Results show that the model provides enhanced performance and maintains more diversity in the swarm and thereby allows the particles to be robust to trace the changing environment. [ABSTRACT FROM AUTHOR]

Abstract: For positive integers , an -labeling of a digraph D is a function f from into the set of nonnegative integers such that if x is adjacent to y in D and if x is of distance two to y in D. Elements of the image of f are called labels. The -labeling problem is to determine the -number of a digraph D, which is the minimum of the maximum label used in an -labeling of D. This paper studies -numbers of digraphs. In particular, we determine -numbers of digraphs whose longest dipath is of length at most 2, and -numbers of ditrees having dipaths of length 4. We also give bounds for -numbers of bipartite digraphs whose longest dipath is of length 3. Finally, we present a linear-time algorithm for determining -numbers of ditrees whose longest dipath is of length 3. [Copyright &y& Elsevier]

Abstract: In this paper, we will derive a solver for a symmetric strongly nonsingular higher order generator representable semiseparable plus band matrix. The solver we will derive is based on the Levinson algorithm, which is used for solving strongly nonsingular Toeplitz systems. In the first part an solver for a semiseparable matrix of semiseparability rank p is derived, and in a second part we derive an solver for a band matrix with bandwidth . Both solvers are constructed in a similar way: firstly a Yule–Walker-like equation needs to be solved, and secondly this solution is used for solving a linear equation with an arbitrary right-hand side. Finally, a combination of the above methods is presented to solve linear systems with semiseparable plus band coefficient matrices. The overall complexity of this solver is plus lower order terms. In the final section numerical experiments are performed. Attention is paid to the timing and the accuracy of the described methods. [Copyright &y& Elsevier]

Abstract: Any set of C 2 planar boundary data (two points with associated velocities and acceleration vectors) can be interpolated by a PH curve of degree 9. In the generic case there are four such curves [R.T. Farouki, J. Manjunathaiah, S. Jee, Design of rational cam profiles with Pythagorean Hodograph curves, Mech. Mach. Theory 33 (1998) 669–682]. In this paper we give a detailed description and a qualitative analysis of these solutions. In particular we label the four solutions and compare their fairness from the point of view of possible application. For this purpose we consider the Hermite data taken from an analytical curve and study the behavior of the solutions for decreasing step-size h. This allows us to identify explicitly the solution which—for sufficiently small step-size—matches the shape of the curve with a high precision (the approximation order is 6). Consequently we are able to develop a highly robust, fast and precise algorithm converting analytical curves or curves described in G-code into a C 2 continuous PH spline curve of degree 9. [Copyright &y& Elsevier]

Abstract: In this paper, the problem of providing a fully predictable execution environment for critical and hard real-time applications on embedded and DSP-based platforms is studied from the viewpoint of system architecture and operation. We introduce a set of homogenous models for time, signals and tasks, which will further serve as a basis for describing the architecture and operation of a particular hard real-time kernel – “HARETICK”. The kernel provides support for concurrent operation of hard real-time tasks (the HRT execution environment), using non-preemptive scheduling algorithms, along with soft real-time tasks (the SRT environment), using classical, preemptive, priority-based scheduling algorithms. A set of applications has been developed to test the correct operation of the HARETICK kernel according to the theoretical models and to evaluate its abilities to provide high predictability of execution for critical applications. Some of the main testing results are also discussed in the paper. [Copyright &y& Elsevier]

Abstract: In this paper we present a novel approximate algorithm to calculate the top-k closest pairs join query of two large and high dimensional data sets. The algorithm has worst case time complexity and space complexity and guarantees a solution within a factor of the exact one, where t ∈{1,2,…,∞} denotes the Minkowski metrics L t of interest and d the dimensionality. It makes use of the concept of space filling curve to establish an order between the points of the space and performs at most d +1 sorts and scans of the two data sets. During a scan, each point from one data set is compared with its closest points, according to the space filling curve order, in the other data set and points whose contribution to the solution has already been analyzed are detected and eliminated. Experimental results on real and synthetic data sets show that our algorithm behaves as an exact algorithm in low dimensional spaces; it is able to prune the entire (or a considerable fraction of the) data set even for high dimensions if certain separation conditions are satisfied; in any case it returns a solution within a small error to the exact one. [Copyright &y& Elsevier]

A watermark hidden in an image is retrieved differently from the original watermark due to the frequently used rounding approach. The simple rounding will cause numerous errors in the embedded watermark especially when it is large. A novel technique based on genetic algorithms (GAs) is presented in this paper to correct the rounding errors. The fundamental is to adopt a fitness function for choosing the best chromosome which determines the conversion rule of real numbers into integers during the cosine transformation. Experimental results show that the dramatic improvement in reducing the errors is successful when GAs are used in decision making. Furthermore, we develop an initial chromosome by comparing the difference between the original image and the rounded watermarked image to speed up the process. In additional to correct fragile-watermarking rounding errors, our algorithm can also be applied in robust watermarking to achieve higher watermarked image quality. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a detailed description of a real-time correlation-based stereo algorithm running completely on the graphics processing unit (GPU). This is important since it allows to free up the main processor for other tasks including high-level interpretation of the stereo results. We first introduce a two-view stereo algorithm that includes some advanced features such as adaptive windows and cross-checking. Then we extend it using a plane-sweep approach to allow multiple frames without rectification. By taking advantage of advanced features of recent GPUs the proposed algorithm runs in real-time. Our implementation running on an ATI Radeon 9800 graphics card achieves up to 289 million disparity evaluations per second including all the overhead to download images and read-back the disparity map, which is several times faster than commercially available CPU-based implementations. [Copyright &y& Elsevier]

Abstract Current implicit blending techniques are mostly designed for use in surface modelling, where only boundaries of the object defined by the implicit primitives are important. In contrast, in volumetric implicit modelling the interior of the object is also significant, which requires different and more suitable techniques for combining implicit primitives. In this paper, we first discuss irregularities that occur using the current techniques. Then, a new technique for blending implicit primitives, especially appropriate in volumetric modelling (e.g., cloud modelling), is introduced. It overcomes these abnormalities and gives us better results than current techniques. [ABSTRACT FROM AUTHOR]

Though a large body of research has focused on tracking and identifying objects from the domain of colour or grey-scale images, there is a relative dearth in the literature on complex articulated/non-rigid motion reconstruction from a collection of low density feature points. In this paper, we propose a segment-based articulated matching algorithm to establish a crucial self-initialising identification in model-based point-feature tracking of articulated motion with near-rigid segments. We avoid common assumptions such as pose similarity or small motion with respect to the model, and assume no prior knowledge of a specific movement from which to restrict pose identification. Experimental results based on synthetic pose and real-world human motion capture data demonstrate the ability of the algorithm to perform the identification task. [Copyright &y& Elsevier]

Presents a study which showed how curve and surface representations of fiber network, fiber wall and fiber lumen can be computed using distance transform based algorithms. Motive for analyzing volume images of paper; Uses of the representations; Levels of detail in which the analysis of paper and paper fibers can be divided.

This paper presents the new upper bounds of channel width required in multi- layer channel routing under a wiring rule in which horizontal wires must be wired in the odd-numbered layers and vertical wires in the even-numbered layers. In (M ≧ 4)-layer channel routing, it is proved the upper bound is equal to [(dc +k)/[M/2]], where dc is the channel density, and k is 9 when M = 5, 7 when M is even, and 13 when M is odd and greater than 5. These upper bounds are obtained by presenting the multiple-layer channel routing algorithms, which wire the channels in a column-by-column manner. [ABSTRACT FROM AUTHOR]