Higher-Order Gauss–Lobatto Integration for Non-Linear Hyperbolic Equations

Least-squares spectral elements are capable of solving non-linear hyperbolic equations, in which discontinuities develop in finite time. In recent publications [De Maerschalck, B., 2003, http://www.aero.lr.tudelft.nl/∼bart; De Maerschalck, B., and Gerritsma, M. I., 2003, AIAA; De Maerschalck, B., and Gerritsma, M. I., 2005, Num. Algorithms, 38(1–3); 173–196], it was noted that the ability to obtain the correct solution depends on the type of linearization, Picard’s method or Newton linearization. In addition, severe under-relaxation was necessary to reach a converged solution. In this paper the use of higher-order Gauss–Lobatto integration will be addressed. When a sufficiently fine GL-grid is used to approximate the integrals involved, the discrepancies between the various linearization methods are considerably reduced and under-relaxation is no longer necessary     

Contaminant transport with adsorption and their inverse problems

In Constales et al. (water Resources Res. 39(30), 1303, 2003) dual-well tests are used to reconstruct the flow and dispersion parameters in contaminant transport. A tracer is introduced by the injection well, which is considered to be in steady-state regime with the extraction well. Then, from measurements of the time evolution of the extracted tracer (breakthrough curve) the required model data has been recovered. In Constales et al. (water Resources Res. 39(30), 1303, 2003), a very precise numerical method has been developed for the solution of the direct problem. In Kačur et al. (Comput. Meth. Appl. Mech. Engo. 194(2–5), 479–489, 2005); Remešiková (J. Comp. Appl. Math. 169(1), 101–116, 2004) an extension has been discussed which adds adsorption terms to the model. The inverse problem of determination of sorption isotherms in nonequilibrium mode was solved by a Levenberg–Marquardt iteration method. In the present paper we develop the adjoint system to evaluate the sensitivity of the solution (via the breakthrough curve) on the sorption parameters in equilibrium and nonequilibrium modes. Possible use of the adjoint system in determining the several parameters occuring in the model is a crucial point for iteration methods. The obtained model parameters then can be used in a 3D flow and transport model with adsorption. The numerical experiments we present, justify the used method.     

Thinking About Evolution in Terms of Cellular Computing

The past five decades of molecular genetics have produced many discoveries about genome structure and function that can only be understood from an informatic perspective: – distinct sequence codes to mark the individual steps in packaging, expression, replication, transmission, repair and restructuring of DNA molecules; – modularity of data files for RNA and protein products; – combinatoric organization of signals to format the genome for differential functioning during cellular and organismal cycles; – direct participation of DNA in the execution of biological algorithms (formation of highly structured nucleoprotein complexes); – hierarchical organization of genomic subsystems to form higher level system architectures. This review will discuss aspects of genome organization and genome change that require a more formal computational analysis. We will see how modern results indicate that genome evolution has many similarities to computer system engineering. The ability of cells to control the function of natural genetic engineering systems is central to the genome’s potential as a Read–Write information storage system.     

A Benders Decomposition Method for Solving Stochastic Complementarity Problems with an Application in Energy

In this paper we present a new Benders decomposition method for solving stochastic complementarity problems based on the work by Fuller and Chung (Comput Econ 25:303–326, 2005; Eur J Oper Res 185(1):76–91, 2007). A master and subproblem are proposed both of which are in the form of a complementarity problem or an equivalent variational inequality. These problems are solved iteratively until a certain convergence gap is sufficiently close to zero. The details of the method are presented as well as an extension of the theory from Fuller and Chung (2005, 2007). In addition, extensive numerical results are provided based on an electric power market model of Hobbs (IEEE Trans Power Syst 16(2):194–202, 2001) but for which stochastic elements have been added. These results validate the approach and indicate dramatic improvements in solution times as compared to solving the extensive form of the problem directly.     

Finding Total Unimodularity in Optimization Problems Solved by Linear Programs

A popular approach in combinatorial optimization is to model problems as integer linear programs. Ideally, the relaxed linear program would have only integer solutions, which happens for instance when the constraint matrix is totally unimodular. Still, sometimes it is possible to build an integer solution with the same cost from the fractional solution. Examples are two scheduling problems (Baptiste and Schieber, J. Sched. 6(4):395–404, 2003; Brucker and Kravchenko, J. Sched. 11(4):229–237, 2008) and the single disk prefetching/caching problem (Albers et al., J. ACM 47:969–986, 2000). We show that problems such as the three previously mentioned can be separated into two subproblems: (1) finding an optimal feasible set of slots, and (2) assigning the jobs or pages to the slots. It is straigthforward to show that the latter can be solved greedily. We are able to solve the former with a totally unimodular linear program, from which we obtain simple combinatorial algorithms with improved worst case running time.     

Variants of evolutionary learning for interactive image retrieval

We systematically compare four variants of evolutionary algorithms (EAs) for relevance feedback (RF) in image retrieval. We focus on the small sample size (SSS) performance, i.e., the requirement to learn the user’s information need based on a small – between 2 and 25 – number of positive and negative training images. Despite this being a fundamental requirement, none of the existing works dealing with EAs for RF in image retrieval addresses it. Common for the four variants is the hierarchical, region-based image similarity model, with region and feature weights as parameters. The difference between the variants is in the objective function of the EA used to adjust the model parameters. The objective functions include: (O-1) precision; (O-2) average rank; (O-3) ratio of within-class (i.e., positive images) and between-class (i.e., positive and negative images) scatter; and (O-4) combination of O-2 and O-3. We note that – unlike O-1 and O-2 – O-3 and O-4 are not used in any of the existing works dealing with EAs for RF. The four variants are evaluated on five test databases, containing 61,895 general-purpose images, in 619 semantic categories. Results of the evaluation reveal that variants with objective functions O-3 and O-4 consistently outperform those with O-1 and O-2. Furthermore, comparison with the representative of the existing RF methods shows that EAs are both effective and efficient approaches for SSS learning in region-based image retrieval.     

A face emotion tree structure representation with probabilistic recursive neural network modeling

This paper describes a novel structural approach to recognize the human facial features for emotion recognition. Conventionally, features extracted from facial images are represented by relatively poor representations, such as arrays or sequences, with a static data structure. In this study, we propose to extract facial expression features vectors as Localized Gabor Features (LGF) and then transform these feature vectors into FacE Emotion Tree Structures (FEETS) representation. It is an extension of the Human Face Tree Structures (HFTS) representation presented in (Cho and Wong in Lecture notes in computer science, pp 1245–1254, 2005). This facial representation is able to simulate as human perceiving the real human face and both the entities and relationship could contribute to the facial expression features. Moreover, a new structural connectionist architecture based on a probabilistic approach to adaptive processing of data structures is presented. The so-called probabilistic based recursive neural network (PRNN) model extended from Frasconi et al. (IEEE Trans Neural Netw 9:768–785, 1998) is developed to train and recognize human emotions by generalizing the FEETS representation. For empirical studies, we benchmarked our emotion recognition approach against other well known classifiers. Using the public domain databases, such as Japanese Female Facial Expression (JAFFE) (Lyons et al. in IEEE Trans Pattern Anal Mach Intell 21(12):1357–1362, 1999; Lyons et al. in third IEEE international conference on automatic face and gesture recognition, 1998) database and Cohn–Kanade AU-Coded Facial Expression (CMU) Database (Cohn et al. in 7th European conference on facial expression measurement and meaning, 1997), our proposed system might obtain an accuracy of about 85–95% for subject-dependent and subject-independent conditions. Moreover, by testing images having artifacts, the proposed model significantly supports the robust capability to perform facial emotion recognition.     

Linear systems of first order ordinary differential equations: fuzzy initial conditions

 We present two types of fuzzy solutions to linear systems of first order differential equations having fuzzy initial conditions. The first solution, called the extension principle solution, fuzzifies the crisp solution and then checks to see if its α-cuts satisfy the differential equations. The second solution, called the classical solution, solves the fuzzified differential equations and then checks to see if the solution always defines a fuzzy number. Three applications are presented: (1) predator–prey models; (2) the spread of infectious diseases; and (3) modeling an arms race.     

Image segmentation using a multilayer level-set approach

We propose an efficient multilayer segmentation method based on implicit curve evolution and on variational approach. The proposed formulation uses the minimal partition problem as formulated by D. Mumford and J. Shah, and can be seen as a more efficient extension of the segmentation models previously proposed in Chan and Vese (Scale-Space Theories in Computer Vision, Lecture Notes in Computer Science, Vol. 1682, pp. 141–151, 1999, IEEE Trans Image Process 10(2):266–277, 2001), and Vese and Chan (Int J Comput Vis 50(3):271–293, 2002). The set of unknown discontinuities is represented implicitly by several nested level lines of the same function, as inspired from prior work on island dynamics for epitaxial growth (Caflisch et al. in Appl Math Lett 12(4):13, 1999; Chen et al. in J Comput Phys 167:475, 2001). We present the Euler–Lagrange equations of the proposed minimizations together with theoretical results of energy decrease, existence of minimizers and approximations. We also discuss the choice of the curve regularization and conclude with several experimental results and comparisons for piecewise-constant segmentation of gray-level and color images.     

Optimizing PTZ camera calibration from two images

In this paper, we address the problem of calibrating an active pan–tilt–zoom (PTZ) camera. In this regard, we make three main contributions: first, for the general camera rotation, we provide a novel solution that yields four independent constraints from only two images, by directly decomposing the infinite homography using a series of Givens rotations. Second, for a camera varying its focal length, we present a solution for the degenerate cases of pure pan and pure tilt that occur very frequently in practical applications of PTZ cameras. Third, we derive a new optimized error function for pure rotation or pan–tilt rotation, which plays a similar role as the epipolar constraint in a freely moving camera, in terms of characterizing the reprojection error of point correspondences. Our solutions and analysis are thoroughly validated and tested on both synthetic and real data, whereby the new geometric error function is shown to outperform existing methods in terms of accuracy and noise resilience.     

On the Behavior of True and False

Uzquiano (Analysis 70:39–44, 2010) showed that the Hardest Logic Puzzle Ever (HLPE) [in its amended form due to Rabern and Rabern (Analysis 68:105–112, 2008)] has a solution in only two questions. Uzquiano concludes his paper by noting that his solution strategy naturally suggests a harder variation of the puzzle which, as he remarks, he does not know how to solve in two questions. Wheeler and Barahona (J Philos Logic, to appear, 2011) formulated a three question solution to Uzquiano’s puzzle and gave an information theoretic argument to establish that a two question solution for Uzquiano’s puzzle does not exist. However, their argument crucially relies on a certain conception of what it means to answer self-referential yes–no questions truly and falsely. We propose an alternative such conception which, as we show, allows one to solve Uzquiano’s puzzle in two questions. The solution strategy adopted suggests an even harder variation of Uzquiano’s puzzle which, as we will show, can also be solved in two questions. Just as all previous solutions to versions of HLPE, our solution is presented informally. The second part of the paper investigates the prospects of formally representing solutions to HLPE by exploiting theories of truth.     

Stereo-disparity perception for a monochromatic flat slope based on a neural network dynamic model

Stereo-matching is one of the most active research topics in computer vision. In this article, the stereo-correspondence problem for a stereo-image pair on a monochromatic surface is considered. Even if some hints exist, it is not easy to reconstruct the correct 3-D scene from two images because it is an ill-posed problem. We have modified our previous competitive and cooperative neural network model so that we can efficiently perceive a monochromatic surface which is enclosed by two vertical stripes. The modification consists of two factors: (1) combining the parameterized multiple inputs (similarities); (2) extending the cooperative terms of the neural network equation. The effect of the proposed model is examined by experiments with both synthetic and real stereo-image pairs. For the real images, a segmentation method is proposed to deal with the similarity maps. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Parallelism of iterative CT reconstruction based on local reconstruction algorithm

An iterative algorithm is suited to reconstruct CT images from noisy or truncated projection data. However, as a disadvantage, the algorithm requires significant computational time. Although a parallel technique can be used to reduce the computational time, a large amount of communication overhead becomes an obstacle to its performance (Li et al. in J. X-Ray Sci. Technol. 13:1–10, 2005). To overcome this problem, we proposed an innovative parallel method based on the local iterative CT reconstruction algorithm (Wang et al. in Scanning 18:582–588, 1996 and IEEE Trans. Med. Imaging 15(5):657–664, 1996). The object to be reconstructed is partitioned into a number of subregions and assigned to different processing elements (PEs). Within each PE, local iterative reconstruction is performed to recover the subregion. Several numerical experiments were conducted on a high performance computing cluster. And the FORBILD head phantom (Lauritsch and Bruder ) was used as benchmark to measure the parallel performance. The experimental results showed that the proposed parallel algorithm significantly reduces the reconstruction time, hence achieving a high speedup and efficiency.

Multimedia mail

Electronic mail for traditional text exchange as asynchronous communication means between computer users is widely built upon in many application areas. Whereas Multimedia-Mail systems – including text, graphics, still images, audio, video and documents – were limited to isolated communities – at least two very promising approaches are being under development: the MIME (Multipurpose Internet Mail Extension), an extension of Internet Mail as well as the Multimedia Teleservice based on CCITT Recommendation X.400(88) being under development within the BERKOM project funded by the German TELEKOM. The store-and-forward mechanism inherent to electronic mail is complemented in the later one by an additional exchange mechanism allowing the resolution of references to message content, e.g. video. Such references may be put into a message in place of the content itself. Internet/MIME and OSI/X.400, their interworking, asynchronous information server access via Multimedia-Mail, as well as possible future developments especially in the area of asynchronous Computer Supported Cooperative Work (CSCW) are discussed.     

Modeling convection–diffusion processes based on a multidimensional integro-differential equation with degenerate parabolicity

An initial–boundary-value problem for a multidimensional integro-differential equation with degenerate parabolicity is considered. Based on the maximum-principle theorem and splitting method, a nonlinear monotonic high-order (higher than the first) numerical scheme is constructed for an implicit two-layer scheme. For the error of a numerical solution, a priori estimates are obtained and the sufficient convergence conditions are proved. A posteriori estimates for the numerical error of the solution are analyzed. Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 83–96, March–April 2009.     

Optimization of thermal assisted direct bonding of soda-lime glasses for lab-on chip application

Surface treatment on glass before thermal assisted direct bonding (TADB) is an issue for lab-on chip fabrication. Surface cleaning for obtaining good quality TADB on soda-lime glass are studied and tested in this paper. The optimized cleaning solution for soda lime glass samples is NH₄OH–H₂O₂–H₂O (0.5:1:5 volume ratio) and it can be considered as the optimised solution for cleaning soda-lime glasses by this solution, as a result of a trade-off between cleaning efficiency and surface etching. The surface quality before and after cleaning is evaluated by optical microscopy, profilometry and atomic force microscopy. TADB between the cleaned samples is carried out and the bonding strength measured. The tensile strength of optimized samples after TADB was found to be higher than 15 MPa.     

Maximal solution to algebraic Riccati equations linked to infinite Markov jump linear systems

In this paper, we deal with a perturbed algebraic Riccati equation in an infinite dimensional Banach space. Besides the interest in its own right, this class of equations appears, for instance, in the optimal control problem for infinite Markov jump linear systems (from now on iMJLS). Here, infinite or finite has to do with the state space of the Markov chain being infinite countable or finite (see Fragoso and Baczynski in SIAM J Control Optim 40(1):270–297, 2001). By using a certain concept of stochastic stability (a sort of L ₂-stability), we prove the existence (and uniqueness) of maximal solution for this class of equation and provide a tool to compute this solution recursively, based on an initial stabilizing controller. When we recast the problem in the finite setting (finite state space of the Markov chain), we recover the result of de Souza and Fragoso (Syst Control Lett 14:233–239, 1999) set to the Markovian jump scenario, now free from an inconvenient technical hypothesis used there, originally introduced in Wonham in (SIAM J Control 6(4):681–697). Research supported by grants CNPq 520367-97-9, 300662/2003-3 and 474653/2003-0, FAPERJ 171384/2002, PRONEX and IM-AGIMB.     

Multiparameter method for analysis and selection of motion estimation algorithms for video compression

This paper proposes a new multiparameter method for analysis and selection of motion estimation algorithms for video compression. We present motion estimation algorithms, results of computer simulations and illustrate the analysis with tables, PSNR and performance plots. Numerous algorithms and tests for analysis of algorithm performance for video compression have recently been suggested, which has resulted in a need for effective evaluation methods. A highly qualified expert is also needed to evaluate the test results. The more input parameters used the more complex and subjective the evaluation will be. Our multiparameter method for algorithm analysis and selection eliminates subjectivity and provides a qualitative and quantitative evaluation of the tested algorithms for any number of algorithms and parameters. We propose two new methods of evaluation: (1) a quality method—a graphic method using the Pareto approach, and (2) a quantity method which obtains an integrated parameter composed of numerous evaluation parameters. In addition, we evaluate various motion estimation algorithms accordingly to two different implementation strategies: (a) using a software video encoder that depends on available processing resources using a computational complexity–rate–distortion (C–R–D) evaluation framework and (b) using a power-limited video encoder implemented on mobile or handheld computing platform by using energy–rate–distortion (E–R–D) behavior.

Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE's

We are interested in PDE's (Partial Differential Equations) in order to smooth multi-valued images in an anisotropic manner. Starting from a review of existing anisotropic regularization schemes based on diffusion PDE's, we point out the pros and cons of the different equations proposed in the literature. Then, we introduce a new tensor-driven PDE, regularizing images while taking the curvatures of specific integral curves into account. We show that this constraint is particularly well suited for the preservation of thin structures in an image restoration process. A direct link is made between our proposed equation and a continuous formulation of the LIC's (Line Integral Convolutions by Cabral and Leedom (1993). It leads to the design of a very fast and stable algorithm that implements our regularization method, by successive integrations of pixel values along curved integral lines. Besides, the scheme numerically performs with a sub-pixel accuracy and preserves then thin image structures better than classical finite-differences discretizations. Finally, we illustrate the efficiency of our generic curvature-preserving approach – in terms of speed and visual quality – with different comparisons and various applications requiring image smoothing : color images denoising, inpainting and image resizing by nonlinear interpolation.     

Stability of solutions of stochastic functional-differential equations with poisson switchings and entire prehistory

The Markov properties of the solutions of Ito-Skorokhod stochastic functional-differential equations (SFDEs) with entire prehistory are considered, the concept of a weak infinitesimal operator is introduced for a Markov process that is a solution of an SFDE, and the strong solution of the SFDE is analyzed for stability. Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 123–134, January–February 2009.