Structuring research methods and data with the research object model: genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

CORD an object model supporting statistical summary information for management decision making

Information systems have developed to the stage that there is plenty of data available in most organisations but there are still major problems in turning that data into information for management decision making. This thesis argues that the link between decision support information and transaction processing data should be through a common object model which reflects the real world of the organisation and encompasses the artefacts of the information system. The CORD (Collections, Objects, Roles and Domains) model is developed which is richer in appropriate modelling abstractions than current Object Models. A flexible Object Prototyping tool based on a Semantic Data Storage Manager has been developed which enables a variety of models to be stored and experimented with. A statistical summary table model COST (Collections of Objects Statistical Table) has been developed within CORD and is shown to be adequate to meet the modelling needs of Decision Support and Executive Information Systems. The COST model is supported by a statistical table creator and editor COSTed which is also built on top of the Object Prototyper and uses the CORD model to manage its metadata.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Object Recognition with Pictorial Structures

This thesis presents a statistical framework for object recognition. The framework is motivated by the pictorial structure models introduced by Fischler and Elschlager nearly 30 years ago. The basic idea is to model an object by a collection of parts arranged in a deformable configuration. The appearance of each part is modeled separately, and the deformable configuration is represented by spring-like connections between pairs of parts. These models allow for qualitative descriptions of visual appearance, and are suitable for generic recognition problems. The problem of detecting an object in an image and the problem of learning an object model using training examples are naturally formulated under a statistical approach. We present efficient algorithms to solve these problems in our framework. We demonstrate our techniques by training models to represent faces and human bodies. The models are then used to locate the corresponding objects in novel images.

View-Based Strategies for 3D Object Recognition

A persistent issue of debate in the area of 3D object recognition concerns the nature of the experientially acquired object models in the primate visual system. One prominent proposal in this regard has expounded the use of object centered models, such as representations of the objects' 3D structures in a coordinate frame independent of the viewing parameters [Marr and Nishihara, 1978]. In contrast to this is another proposal which suggests that the viewing parameters encountered during the learning phase might be inextricably linked to subsequent performance on a recognition task [Tarr and Pinker, 1989; Poggio and Edelman, 1990]. The 'object model', according to this idea, is simply a collection of the sample views encountered during training. Given that object centered recognition strategies have the attractive feature of leading to viewpoint independence, they have garnered much of the research effort in the field of computational vision. Furthermore, since human recognition performance seems remarkably robust in the face of imaging variations [Ellis et al., 1989], it has often been implicitly assumed that the visual system employs an object centered strategy. In the present study we examine this assumption more closely. Our experimental results with a class of novel 3D structures strongly suggest the use of a view-based strategy by the human visual system even when it has the opportunity of constructing and using object-centered models. In fact, for our chosen class of objects, the results seem to support a stronger claim: 3D object recognition is 2D view-based.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Clustering strategies for object databases

When object databases arrived on the scene some ten years ago, they provided database capabilities for previously neglected, complex applications, such as CAD, but were burdened with one inherent teething problem, poor performance. Physical database design is one tool that can provide performance improvements and it is the general area of concern for this thesis. Clustering is one fruitful design technique which can provide improvements in performance. However, clustering in object databases has not been explored in depth and so has not been truly exploited. Further, clustering, although a physical concern, can be determined from the logical model. The object model is richer than previous models, notably the relational model, and so it is anticipated that the opportunities with respect to clustering are greater. This thesis provides a thorough analysis of object clustering strategies with a view to highlighting any links between the object logical and physical model and improving performance. This is achieved by considering all possible types of object logical model construct and the implementation of those constructs in terms of theoretical clusterings strategies to produce actual clustering arrangements. This analysis results in a greater understanding of object clustering strategies, aiding designers in the development process and providing some valuable rules of thumb to support the design process.

A co-ordinated business object approach for supporting tactical level management decisions

The proliferation of data throughout the strategic, tactical and operational areas within many organisations, has provided a need for the decision maker to be presented with structured information that is appropriate for achieving allocated tasks. However, despite this abundance of data, managers at all levels in the organisation commonly encounter a condition of ‘information overload’, that results in a paucity of the correct information. Specifically, this thesis will focus upon the tactical domain within the organisation and the information needs of management who reside at this level. In doing so, it will argue that the link between decision making at the tactical level in the organisation, and low-level transaction processing data, should be through a common object model that used a framework based upon knowledge leveraged from co-ordination theory. In order to achieve this, the Co-ordinated Business Object Model (CBOM) was created. Detailing a two-tier framework, the first tier models data based upon four interactive object models, namely, processes, activities, resources and actors. The second tier analyses the data captured by the four object models, and returns information that can be used to support tactical decision making. In addition, the Co-ordinated Business Object Support System (CBOSS), is a prototype tool that has been developed in order to both support the CBOM implementation, and to also demonstrate the functionality of the CBOM as a modelling approach for supporting tactical management decision making. Containing a graphical user interface, the system’s functionality allows the user to create and explore alternative implementations of an identified tactical level process. In order to validate the CBOM, three verification tests have been completed. The results provide evidence that the CBOM framework helps bridge the gap between low level transaction data, and the information that is used to support tactical level decision making.

The object binary interface: C++ objects for evolvable shared class libraries

Object-oriented design and object-oriented languages support the development of independent software components such as class libraries. When using such components, versioning becomes a key issue. While various ad-hoc techniques and coding idioms have been used to provide versioning, all of these techniques have deficiencies - ambiguity, the necessity of recompilation or re-coding, or the loss of binary compatibility of programs. Components from different software vendors are versioned at different times. Maintaining compatibility between versions must be consciously engineered. New technologies such as distributed objects further complicate libraries by requiring multiple implementations of a type simultaneously in a program. This paper describes a new C++ object model called the Shared Object Model for C++ users and a new implementation model called the Object Binary Interface for C++ implementors. These techniques provide a mechanism for allowing multiple implementations of an object in a program. Early analysis of this approach has shown it to have performance broadly comparable to conventional implementations.

Estimação da permeabilidade em reservatórios fraturados - Comparação entre o método do tensor e o método de upscaling

A simulação dinâmica de reservatórios de petróleo requer a alocação de permeabilidades equivalentes para todos os blocos. A determinação da permeabilidade equivalente em reservatórios fraturados é uma questão complexa e crítica no fluxograma de modelação, porque é totalmente dependente da geometria 3D sistema de fraturas, e respetivas aberturas, que muitas vezes são mal conhecidos. Para avaliar a permeabilidade equivalente de blocos fraturados, o método do tensor ou de Oda é um dos mais utilizados. É expedito e eficiente mesmo para a sistemas com vários milhões de fraturas. Todavia, na literatura são apontadas algumas críticas, por exemplo, sobrestima a permeabilidade em blocos pouco fraturados e subestima-a em blocos muito fraturados. Este trabalho tem como objetivos, revisitar a problemática da caracterização da permeabilidade equivalente em blocos de reservatórios fraturados. Recorreu-se a um pacote de programas informáticos FROM3D-K (fractures object model – permeability evaluation) desenvolvidos e/ ou adaptados no contexto deste trabalho e que permitem as funcionalidades: (1) simulação estocástica 3D de fraturas; (2) determinação da permeabilidade equivalente pelo método do tensor; (3) determinação da permeabilidade equivalente pelo método de upscaling de microblocos. Estas funções permitem que a mesma rede de fraturas seja avaliada pelos dois métodos. Para a demonstração de resultados mostram-se dois exemplos, o primeiro onde são simuladas fraturas condicionadas a estatísticas sintéticas de orientação, intensidade e abertura e o segundo onde se utilizam dados FMI de poço de um reservatório fraturado.

Oliotietokannan muuttaminen relaatiotietokannaksi

Diplomityön tavoitteena oli parantaa oliotietokantaan perustuvan mökkivarausjärjestelmän pitkiä vasteaikoja ja epävakaata toimintaa sekä luoda tietokantaperusta uusille toiminnoille. Ratkaisua etsittiin korvaamalla oliotietokanta relaatiotietokannalla. Diplomityö on osa koko varausjärjestelmän uusintaa. Työn teoreettinen osuus käsittelee sekä olio- että relaatiotietokannan rakennetta ja oliomallin muuttamista relaatiomalliksi. Käytännön osassa esitellään relaatiotietokannan luominen vaiheittain ja kerrotaan tietojen siirron periaatteesta. Relaatiotietokannan havaittiin olevan vakaampi ja tehokkaampi vasteajoiltaan. Samoin sen vaatima levytilan ja muistin määrä oli pienempi kuin oliotietokannalla. Lisäksi siihen todettiin uusien järjestelmien liittämisen olevan yksinkertaisempaa.

Toimitusketjun mallinnuksen tarpeet ja rakenne LOCOMOTIVE projekstissa

Työn tavoitteena oli kuvata ja priorisoida toimitusketjun dynaamisen mallinnustyökalun vaatimukset, sekä muodostaa tämän pohjalta ohjelmistokehitystä tukeva oliomalli. Vaatimuksia selvitettiin teoreettisen tarkastelun, aiemmin toteutettujen kyselytutkimusten sekä viiden pilottitapauksen avulla. Toimitusketjun hallinta ei ole pelkästään materiaalivirtojen vaan myös näihin liittyvän informaation hallintaa. Holististen toimitusketjuongelmien mallintaminen edellyttää siis informaatiovirtojen ja niitä saatelevien ohjausmekanisemien mallintamista. Markkinoilla on selkeästi tilaa tukijärjestelmille, jotka mahdollistaisivat multidimensionaalisten - tuotto, aika, palvelu - toimitusketjuongelmien tarkastelun. Systeemidynamiikan teorian mukaisesti oliomallin lähtökohdaksi valittiin tärkeimpien takaisinkytkentäsilmukkojen mallinnus. Takaisinkytkentäsilmukoiden avulla kyetään mallintamaan kompleksisia systeemejä ajan suhteen. Mallinnetut toimitusketjujen takaisinkytkentäsilmukkat ovat operaatio-, ohjaus-, kysyntä- ja strategiasilmukka. Toimitusketjun ohjausmekanismien, sekä systeemidynamiikan perusteiden pohjalta mallinnustyökalun vaatimuksista muodostettiin oliomalli. Muodostettu oliomalli on Locomotiven - toimitusketjun mallinnustyökalun - perusta.