A hybrid stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints, including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing most invalid matches. The accuracy of matching in the vicinity of edges is also improved.

A constraint to improve the reliability of stereo matching using the rank transform

The rank transform is a non-parametric technique which has been recently proposed for the stereo matching problem. The motivation behind its application to the matching problem is its invariance to certain types of image distortion and noise, as well as its amenability to real-time implementation. This paper derives an analytic expression for the process of matching using the rank transform, and then goes on to derive one constraint which must be satisfied for a correct match. This has been dubbed the rank order constraint or simply the rank constraint. Experimental work has shown that this constraint is capable of resolving ambiguous matches, thereby improving matching reliability. This constraint was incorporated into a new algorithm for matching using the rank transform. This modified algorithm resulted in an increased proportion of correct matches, for all test imagery used.

Estimating the probability of an invalid match for matching using the rank transform

A fundamental problem faced by stereo matching algorithms is the matching or correspondence problem. A wide range of algorithms have been proposed for the correspondence problem. For all matching algorithms, it would be useful to be able to compute a measure of the probability of correctness, or reliability of a match. This paper focuses in particular on one class for matching algorithms, which are based on the rank transform. The interest in these algorithms for stereo matching stems from their invariance to radiometric distortion, and their amenability to fast hardware implementation. This work differs from previous work in that it derives, from first principles, an expression for the probability of a correct match. This method was based on an enumeration of all possible symbols for matching. The theoretical results for disparity error prediction, obtained using this method, were found to agree well with experimental results. However, disadvantages of the technique developed in this chapter are that it is not easily applicable to real images, and also that it is too computationally expensive for practical window sizes. Nevertheless, the exercise provides an interesting and novel analysis of match reliability.

Rank and file : assessing research quality in Australia

In this paper, the author describes recent developments in the assessment of research activity and publication in Australia. Of particular interest to readers will be the move to rank academic journals. Educational Philosophy and Theory (EPAT) received the highest possible ranking, however, the process is far from complete. Some implications for the field, for this journal and particularly, for the educational foundations are discussed.

Rank minimization across appearance and shape for AAM ensemble fitting

Active Appearance Models (AAMs) employ a paradigm of inverting a synthesis model of how an object can vary in terms of shape and appearance. As a result, the ability of AAMs to register an unseen object image is intrinsically linked to two factors. First, how well the synthesis model can reconstruct the object image. Second, the degrees of freedom in the model. Fewer degrees of freedom yield a higher likelihood of good fitting performance. In this paper we look at how these seemingly contrasting factors can complement one another for the problem of AAM fitting of an ensemble of images stemming from a constrained set (e.g. an ensemble of face images of the same person).

Predicting fault-prone software modules with rank sum classification

The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.

Integrin-functionalized artificial membranes as test platforms for monitoring small integrin ligand binding by surface plasmon-enhanced fluorescence spectroscopy

The design and synthesis of molecularly or supramolecularly defined interfacial architectures have seen in recent years a remarkable growth of interest and scientific research activities for various reasons. On the one hand, it is generally believed that the construction of an interactive interface between the living world of cells, tissue, or whole organisms and the (inorganic or organic) materials world of technical devices such as implants or medical parts requires proper construction and structural (and functional) control of this organism–machine interface. It is still the very beginning of generating a better understanding of what is needed to make an organism tolerate implants, to guarantee bidirectional communication between microelectronic devices and living tissue, or to simply construct interactive biocompatibility of surfaces in general. This exhaustive book lucidly describes the design, synthesis, assembly and characterization, and bio-(medical) applications of interfacial layers on solid substrates with molecularly or supramolecularly controlled architectures. Experts in the field share their contributions that have been developed in recent years.

Using the quantum probability ranking principle to rank interdependent documents

A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements.

Is intent-aware expected reciprocal rank sufficient to evaluate diversity?

In this paper we define two models of users that require diversity in search results; these models are theoretically grounded in the notion of intrinsic and extrinsic diversity. We then examine Intent-Aware Expected Reciprocal Rank (ERR-IA), one of the official measures used to assess diversity in TREC 2011-12, with respect to the proposed user models. By analyzing ranking preferences as expressed by the user models and those estimated by ERR-IA, we investigate whether ERR-IA assesses document rankings according to the requirements of the diversity retrieval task expressed by the two models. Empirical results demonstrate that ERR-IA neglects query-intents coverage by attributing excessive importance to redundant relevant documents. ERR-IA behavior is contrary to the user models that require measures to first assess diversity through the coverage of intents, and then assess the redundancy of relevant intents. Furthermore, diversity should be considered separately from document relevance and the documents positions in the ranking.

Single step purification of plasmid DNA using peptide ligand affinity chromatography

Single step affinity chromatography was employed for the purification of plasmid DNA (pDNA), thus eliminating several steps compared with current commercial purification methods for pDNA. Significant reduction in pDNA production time and cost was obtained. This chromatographic operation employed a peptide-monolith construct to isolate pDNA from Escherichia coli (E. coli) impurities present in a clarified lysate feedstock. Mild conditions were applied to avoid any degradation of pDNA. The effect of some important parameters on pDNA yield was also evaluated with the aim of optimising the affinity purification of pDNA. The results demonstrate that 81% of pDNA was recovered and contaminating gDNA, RNA and protein were removed below detectable levels. © 2008 Elsevier B.V. All rights reserved.

Do-Rank: DCG optimization for learning-to-rank in tag-based item recommendation systems

Discounted Cumulative Gain (DCG) is a well-known ranking evaluation measure for models built with multiple relevance graded data. By handling tagging data used in recommendation systems as an ordinal relevance set of {negative,null,positive}, we propose to build a DCG based recommendation model. We present an efficient and novel learning-to-rank method by optimizing DCG for a recommendation model using the tagging data interpretation scheme. Evaluating the proposed method on real-world datasets, we demonstrate that the method is scalable and outperforms the benchmarking methods by generating a quality top-N item recommendation list.

Different correlation of Sphingosine-1-Phosphate receptor 1 with receptor activator of nuclear factor kappa B ligand and regulatory T cells in rat periapical lesions

Introduction Sphingosine-1-phosphate receptor 1 (S1P1) is crucial for regulation of immunity and bone metabolism. This study aimed to investigate the expression of S1P1 in rat periapical lesions and its relationship with receptor activator of nuclear factor kappa B ligand (RANKL) and regulatory T (Treg) cells. Methods Periapical lesions were induced by pulp exposure in the first lower molars of 55 Wistar rats. Thirty rats were killed on days 0, 7, 14, 21, 28, and 35, and their mandibles were harvested for x-ray imaging, micro–computed tomography scanning, histologic observation, immunohistochemistry, enzyme histochemistry, and double immunofluorescence analysis. The remaining 25 rats were killed on days 0, 14, 21, 28, and 35, and mandibles were harvested for flow cytometry. Results The volume and area of the periapical lesions increased from day 0 to day 21 and then remained comparably stable after day 28. S1P1-positive cells were observed in the inflammatory periapical regions; the number of S1P1-positive cells peaked at day 14 and then decreased from day 21 to day 35. The distribution of S1P1-positive cells was positively correlated with the dynamics of RANKL-positive cells but was negatively correlated with that of Treg cells. Conclusions S1P1 expression was differentially correlated with RANKL and Treg cell infiltration in the periapical lesions and is therefore a contributing factor to the pathogenesis of such lesions.

The structures of the isomorphous potassium and rubidium salts of 4-nitrobenzoic acid and an overview of the metal complex stereochemistries of the alkali metal salt series with this ligand

The structures of the isomorphous potassium and rubidium polymeric coordination complexes with 4-nitrobenzoic acid, poly[mu2-aqua-aqua-mu3-(4-nitrobenzoato)-potassium], [K(C7H4N2O2)(H2O)2]n, (I) and poly[mu3-aqua-aqua-mu5-(4-nitrobenzoato)-rubidium], [Rb(C7H4N2O2)(H2O)2]n, (II) have been determined. In (I) the very distorted KO6 coordination sphere about the K+ centres in the repeat unit comprise two bridging nitro O-atom donors, a single bridging carboxyl O-atom donor and two water molecules, one of which is bridging. In the the Rb complex (II), the same basic MO6 coordination is found in the repeat unit but is expanded to RbO9 through a slight increase in the accepted Rb-O bond length range and includes an additional Rb-O(carboxyl) bond, completing a bidentate O,O'-chelate interaction, and additional bridging Rb-Onitro) and Rb-O(water) bonds. The comparative K-O and Rb-O bond length ranges are 2.738(3)-3.002(3)Ang. (I) and 2.884(2)-3.182(2)Ang. (II). The structure of (II) is also isomorphous as well as isostructural with the known structure of the nine-coordinate caesium 4-nitrobenzoate analogue, [Cs(C7H4N2O~2~)(H~2~O)2]n, (III) in which the Cs---O range is 3.047(4)-3.338(4)Ang. In all three complexes, common basic polymeric extensions are found, including two different centrosymmetric bridging interactions through both water and nitro groups as well as extensions along c through the p-related carboxyl group, giving a two-dimensional structure in (I). In (II) and (III), three-dimensional structures are generated through additional bridges through the nitro and water O-atoms. In all structures, both water molecules are involved in similar intra-polymer O-H...O hydrogen-bonding interactions to both carboxyl as well as water O-atom acceptors. A comparison of the varied coordination behaviour of the full set of Li-Cs salts with 4-nitrobenzoic acid is also made.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.