Ontology-based image annotation

With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

4-Carbamoylpiperidinium 5-nitrosalicylate

In the structure of the title compound, C6H13N2O+ C7H4NO5-, the isonipecotamide cations and the 5-nitrosalicylate anions form hydrogen-bonded chain substructures through head-to-tail piperidinium N---H...O(carboxyl) hydrogen bonds and through centrosymmetric cyclic head-to-head amide-amide hydrogen-bonding associations [graph set R2/2(8)]. These chains are cross linked by amide N---H...O~carboxyl~ and piperidinium N-H...O(nitro) associations to give a two-dimensional sheet structure.

Order and disorder in the structures of two crystal polymorphs of the adduct bis(quinolinium-2-carboxylate) DL-malic acid

The structures of two polymorphs of the anhydrous cocrystal adduct of bis(quinolinium-2-carboxylate) DL-malic acid, one triclinic the other monoclinic and disordered, have been determined at 200 K. Crystals of the triclinic polymorph 1 have space group P-1, with Z = 1 in a cell with dimensions a = 4.4854(4), b = 9.8914(7), c = 12.4670(8)Å, α = 79.671(5), β = 83.094(6), γ = 88.745(6)deg. Crystals of the monoclinic polymorph 2 have space group P21/c, with Z = 2 in a cell with dimensions a = 13.3640(4), b = 4.4237(12), c = 18.4182(5)Å, β = 100.782(3)deg. Both structures comprise centrosymmetric cyclic hydrogen-bonded quinolinic acid zwitterion dimers [graph set R2/2(10)] and 50% disordered malic acid molecules which lie across crystallographic inversion centres. However, the oxygen atoms of the malic acid carboxylic groups in 2 are 50% rotationally disordered whereas in 1 these are ordered. There are similar primary malic acid carboxyl O-H...quinaldic acid hydrogen-bonding chain interactions in each polymorph, extended into two-dimensional structures but in l this involves centrosymmetric cyclic head-to-head malic acid hydroxyl-carboxyl O-H...O interactions [graph set R2/2(10)] whereas in 2 the links are through single hydroxy-carboxyl hydrogen bonds.

Multi-version documents : A digitisation solution for textual cultural artefacts

Textual cultural heritage artefacts present two serious problems for the encoder: how to record different or revised versions of the same work, and how to encode conflicting perspectives of the text using markup. Both are forms of textual variation, and can be accurately recorded using a multi-version document, based on a minimally redundant directed graph that cleanly separates variation from content.

4-Carbamoylpiperidinium 2-carboxybenzoate-benzene-1,2-dicarboxylic acid (1/1)

In the structure of the title salt adduct, C6H13N2O+ C8H5O4- . C8H6O4, the asymmetric unit comprises one isonipecotamide cation, a hydrogen phthalate anion and a phthalic acid adduct molecule and form a two-dimensional hydrogen-bonded network through head-to-tail cation-anion-adduct molecule interactions which include a cyclic heteromolecular amide--carboxylate motif [graph set R2/2(8)], conjoint cyclic R2/2(6) and R3/3(10) piperidinium N-H...O(carboxyl) associations, as well as strong carboxylic acid O-H...O(carboxyl) hydrogen bonds.

Towards defining semantic foundations for purpose-based privacy policies

We define a semantic model for purpose, based on which purpose-based privacy policies can be meaningfully expressed and enforced in a business system. The model is based on the intuition that the purpose of an action is determined by its situation among other inter-related actions. Actions and their relationships can be modeled in the form of an action graph which is based on the business processes in a system. Accordingly, a modal logic and the corresponding model checking algorithm are developed for formal expression of purpose-based policies and verifying whether a particular system complies with them. It is also shown through various examples, how various typical purpose-based policies as well as some new policy types can be expressed and checked using our model.

Graphcut-based interactive segmentation using colour and depth cues

Segmentation of novel or dynamic objects in a scene, often referred to as background sub- traction or foreground segmentation, is critical for robust high level computer vision applica- tions such as object tracking, object classifca- tion and recognition. However, automatic real- time segmentation for robotics still poses chal- lenges including global illumination changes, shadows, inter-re ections, colour similarity of foreground to background, and cluttered back- grounds. This paper introduces depth cues provided by structure from motion (SFM) for interactive segmentation to alleviate some of these challenges. In this paper, two prevailing interactive segmentation algorithms are com- pared; Lazysnapping [Li et al., 2004] and Grab- cut [Rother et al., 2004], both based on graph- cut optimisation [Boykov and Jolly, 2001]. The algorithms are extended to include depth cues rather than colour only as in the original pa- pers. Results show interactive segmentation based on colour and depth cues enhances the performance of segmentation with a lower er- ror with respect to ground truth.

Clone detection in repositories of business process models

As organizations reach to higher levels of business process management maturity, they often find themselves maintaining repositories of hundreds or even thousands of process models, representing valuable knowledge about their operations. Over time, process model repositories tend to accumulate duplicate fragments (also called clones) as new process models are created or extended by copying and merging fragments from other models. This calls for methods to detect clones in process models, so that these clones can be refactored as separate subprocesses in order to improve maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. The proposed index is based on a novel combination of a method for process model decomposition (specifically the Refined Process Structure Tree), with established graph canonization and string matching techniques. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.

2-(4-Aminophenyl)-1-phenyldiazenium 2,4,6-trinitrophenolate

In the structure of the title salt, C12H12N3+ C6H2N3O7-, the diazenyl group of the 4-(phenyldiazenyl)aniline molecule is protonated and forms a hydrogen bond with the phenolate O acceptor of the picrate anion. Structure extension occurs through two symmetrical inter-ion three-centre amine N---H...O,O'(nitro) hydrogen-bonding associations [graph set R2/1(4)] giving a convoluted two-dimensional network structure.

Practical application of pseudospectral optimization to robot path planning

To obtain minimum time or minimum energy trajectories for robots it is necessary to employ planning methods which adequately consider the platform’s dynamic properties. A variety of sampling, graph-based or local receding-horizon optimisation methods have previously been proposed. These typically use simplified kino-dynamic models to avoid the significant computational burden of solving this problem in a high dimensional state-space. In this paper we investigate solutions from the class of pseudospectral optimisation methods which have grown in favour amongst the optimal control community in recent years. These methods have high computational efficiency and rapid convergence properties. We present a practical application of such an approach to the robot path planning problem to provide a trajectory considering the robot’s dynamic properties. We extend the existing literature by augmenting the path constraints with sensed obstacles rather than predefined analytical functions to enable real world application.

Overview of the INEX 2010 XML mining track : clustering and classification of XML documents

The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.

Proton-transfer compounds of isnipecotamide with the aromatic dicarboxylic acids 4-nitrophthalic, 4,5-dichlorophthalic, 5-nitroisophthalic and terephthalic acid

The structures of the 1:1 proton-transfer compounds of isonipecotamide (4-piperidinecarboxamide) with 4-nitrophthalic acid, 4-carbamoylpiperidinium 2-carboxy-4-nitrobenzoate, C6H13N2O8+ C8H4O6- (I), 4,5-dichlorophthalic acid, 4-carbamoylpiperidinium 2-carboxy-4,5-dichlorobenzoate, C6H13N2O8+ C8H3Cl2O4- (II) and 5-nitroisophthalic acid, 4-carbamoylpiperidinium 3-carboxy-5-nitrobenzoate, C6H13N2O8+ C8H4O6- (III) as well as the 2:1 compound with terephthalic acid, bis(4-carbamoylpiperidinium)benzene-1,2-dicarboxylate dihydrate, 2(C6H13N2O8+) C8H4O42- . 2H2O (IV)have been determined at 200 K. All salts form hydrogen-bonded structures, one-dimensional in (II) and three-dimensional in (I), (III) and (IV). In (I) and (III) the centrosymmetric R2/2(8) cyclic amide-amide association is found while in (IV) several different types of water-bridged cyclic associations are present [graph sets R2/4(8), R3/4(10), R4/4(12), R3/3(18) and R4/6(22)]. The one-dimensional structure of (I), features the common 'planar' hydrogen 4,5-dichlorophthalate anion together with enlarged cyclic R3/3(13) and R3/4(17) associations. With the structures of (I) and (III) the presence of head-to-tail hydrogen phthalate chain substructures is found. In (IV) head-to-tail primary cation-anion associations are extended longitudinally into chains through the water-bridged cation associations and laterally by piperidinium N-H...O(carboxyl) and water O-H...O(carboxyl) hydrogen bonds. The structures reported here further demonstrate the utility of the isonipecotamide cation as a synthon for the generation of stable hydrogen-bonded structures. An additional example of cation--anion association with this cation is also shown in the asymmetric three-centre piperidinium N-H...O,O'(carboxyl) interaction in the first-reported structure of a 2:1 isonipecotamide-carboxylate salt.

rac-2-Aminopyridinium cis-2-carboxycyclohexane-1-carboxylate

In the structure of the title compound, C5H7N2+ C8H11O4-, the cis-anions associate through head-to-tail carboxylic acid carboxyl O-H...O hydrogen-bonds [graph set C(7)], forming chains which extend along c and are inter-linked through the carboxyl groups forming cyclic R2/2(8) associations with the pyridinium and an amine H donor of the cation. Further amine...carboxyl N-H...O interactions form enlarged centrosymmetric rings [graph set R4/4(18)] and extensions down b to give a three-dimensional structure.

2,3-Dimethoxy-10-oxostrychnidinium 2-(2,4,6-trinitroanilino)benzoate monohydrate : a 1:1 proton-transfer salt of brucine with o-picraminobenzoic acid

In the structure of the 1:1 proton-transfer compound of brucine with 2-(2,4,6-trinitroanilino)benzoic acid C23H27N2O4+ . C13H7N4O8- . H~2~O, the brucinium cations form the classic undulating ribbon substructures through overlapping head-to-tail interactions while the anions and the three related partial water molecules of solvation (having occupancies of 0.73, 0.17 and 0.10) occupy the interstitial regions of the structure. The cations are linked to the anions directly through N-H...O(carboxyl) hydrogen bonds and indirectly by the three water molecules which form similar conjoint cyclic bridging units [graph set R2/4(8)] through O-H...O(carbonyl) and O(carboxyl) hydrogen bonds, giving a two-dimensional layered structure. Within the anion, intramolecular N-H...O(carboxyl) and N H...O(nitro) hydrogen bonds result in the benzoate and picrate rings being rotated slightly out of coplanarity inter-ring dihedral angle 32.50(14)\%]. This work provides another example of the molecular selectivity of brucine in forming stable crystal structures and also represents the first reported structure of any form of the guest compound 2-(2,4,6-trinitroanilino)benzoic acid.

rac-cis-Cyclohexaane-1,2-dicarboxylic acid-isoquinoline (1/1)

In the structure of the title molecular adduct C8H12O4 . C9H7N, the two species are interlinked through a carboxylic acid-isoquinoline O-H...N hydrogen bond, these molecular pairs then inter-associate through the second acid group of the cis-cyclohexane-1,2-dicarboxylic acids, forming a classic centrosymmetric cyclic head-to-head carboxylic acid--carboxyl O---H...O hydrogen-bonding association [graph set R^2^~2~(8)], giving a zero-dimensional structure.