Mammographic Mass Detection with Statistical Region Merging

An automatic method for detection of mammographic masses is presented which utilizes statistical region merging for segmentation (SRM) and linear discriminant analysis (LDA) for classification. The performance of the scheme was evaluated on 36 images selected from the local database of mammograms and on 48 images taken from the Digital Database for Screening Mammography (DDSM). The Az value (area under the ROC curve) for classifying each region was 0.90 for the local dataset and 0.96 for the images from DDSM. Results indicate that SRM segmentation can form part of an robust and efficient basis for analysis of mammograms

Large-scale 3D environmental modelling and visualisation for flood hazard warning.

3D environment reconstruction has received great interest in recent years in areas such as city planning, virtual tourism and flood hazard warning. With the rapid development of computer technologies, it has become possible and necessary to develop new methodologies and techniques for real time simulation for virtual environments applications. This thesis proposes a novel dynamic simulation scheme for flood hazard warning. The work consists of three main parts: digital terrain modelling; 3D environmental reconstruction and system development; flood simulation models. The digital terrain model is constructed using real world measurement data of GIS, in terms of digital elevation data and satellite image data. An NTSP algorithm is proposed for very large data assessing, terrain modelling and visualisation. A pyramidal data arrangement structure is used for dealing with the requirements of terrain details with different resolutions. The 3D environmental reconstruction system is made up of environmental image segmentation for object identification, a new shape match method and an intelligent reconstruction system. The active contours-based multi-resolution vector-valued framework and the multi-seed region growing method are both used for extracting necessary objects from images. The shape match method is used with a template in the spatial domain for a 3D detailed small scale urban environment reconstruction. The intelligent reconstruction system is designed to recreate the whole model based on specific features of objects for large scale environment reconstruction. This study then proposes a new flood simulation scheme which is an important application of the 3D environmental reconstruction system. Two new flooding models have been developed. The first one is flood spreading model which is useful for large scale flood simulation. It consists of flooding image spatial segmentation, a water level calculation process, a standard gradient descent method for energy minimization, a flood region search and a merge process. The finite volume hydrodynamic model is built from shallow water equations which is useful for urban area flood simulation. The proposed 3D urban environment reconstruction system was tested on our simulation platform. The experiment results indicate that this method is capable of dealing with complicated and high resolution region reconstruction which is useful for many applications. When testing the 3D flood simulation system, the simulation results are very close to the real flood situation, and this method has faster speed and greater accuracy of simulating the inundation area in comparison to the conventional flood simulation model

Sensor-based formation control using a generalised rigidity framework and passivity techniques

The research in this thesis addresses the subject of sensor-based formation control for a network of autonomous agents. The task of formation control involves the stabilisation of the agents to a desired set of relative states, with the possible additional objective of manoeuvring the agents while maintaining this formation. Although the formation control challenge has been widely studied in the literature, many existing control strategies are based on full state information, and give little consideration to the sensor modalities available for the task. The focus of this thesis lies in the use of a generic arrangement of partial state measurements as can commonly be acquired by onboard sensors; for example, time-of-flight sensors can be used to measure the distances between vehicles, and onboard cameras can provide the bearing from one vehicle to each of the others. Particular aspects of the problem that are addressed in this thesis include (i) ways of modelling the formation control task, (ii) methods of analysing the system's behaviour, and (iii) the design of a formation control scheme based on generic arrangements of sensors that provide only partial position information. A key contribution in this thesis is a generalisation of the classical notion of rigidity, which considers the use of distance constraints between agents in R^2 or R^3 to specify a rigid body (or formation). This enables the concept of rigidity to be applied to agent networks involving a variety of (possibly non-Euclidean) state-spaces, with a generic set of state constraints that may, for example, include bearings between agents as well as distances. I demonstrate that this framework is very well-suited for modelling a wide variety of formation control problems (addressing goal (i) above), and I extend several fundamental results from classical rigidity theory in order to provide significant insight for system analysis (addressing goal (ii) above). To design a formation control scheme that uses generic partial position measurements (addressing goal (iii) above), I employ a modular passivity-based approach that is developed using the bondgraph modelling formalism. I illustrate how adaptive compensation can be incorporated into this design approach in order to account for the unknown position information that is not available from the onboard sensors. Although formation control is the subject of this thesis, it should be noted that the rigidity-based and passivity-based frameworks developed here are quite general and may be applied to a wide range of other problems

Enhancing automatic level generation for platform videogames

This dissertation addresses the challenge of improving automatic level generation processes for plat-form videogames. As Procedural Content Generation (PCG) techniques evolved from the creation of simple elements to the construction of complete levels and scenarios, the principles behind the generation algorithms became more ambitious and complex, representing features that beforehand were only possible with human design. PCG goes beyond the search for valid geometries that can be used as levels, where multiple challenges are represented in an adequate way. It is also a search for user-centred design content and the creativity sparks of humanly created content. In order to improve the creativity capabilities of such generation algorithms, we conducted part of our research directed to the creation of new techniques using more ambitious design patterns. For this purpose, we have implemented two overall structure generation algorithms and created an addi-tional adaptation algorithm. The later can transform simple branched paths into more compelling game challenges by adding items and other elements in specific places, such as gates and levers for their activation. Such approach is suitable to avoid excessive level linearity and to represent certain design patterns with additional content richness. Moreover, content adaptation was transposed from general design domain to user-centred principles. In this particular case, we analysed success and failure patterns in action videogames and proposed a set of metrics to estimate difficulty, taking into account that each user has a different perception of that concept. This type of information serves the generation algorithms to make them more directed to the creation of personalised experiences. Furthermore, the conducted research also aimed to the integration of different techniques into a common ground. For this purpose, we have developed a general framework to represent content of platform videogames, compatible with several titles within the genre. Our algorithms run over this framework, whereby they are generic and game independent. We defined a modular architecture for the generation process, using this framework to normalise the content that is shared by multiple modules. A level editor tool was also created, which allows human level design and the testing of automatic generation algorithms. An adapted version of the editor was implemented for the semi-automatic creation of levels, in which the designer may simply define the type of content that he/she desires, in the form of quests and missions, and the system creates a corresponding level structure. This materialises our idea of bridging human high-level design patterns with lower level automated generation algorithms. Finally, we integrated the different contributions into a game prototype. This implementation allowed testing the different proposed approaches altogether, reinforcing the validity of the proposed archi-tecture and framework. It also allowed performing a more complete gameplay data retrieval in order to strengthen and validate the proposed metrics regarding difficulty perceptions

Sustainability of marketing systems: systeming interpretation of hybrid car manufacturer and consumer communications

The purpose of this qualitative macromarketing investigation is to explore the issue of the sustainability of marketing systems. Drawing on complex systems thinking, an alternative logic of marketing systems and a methodological basis for interpreting communicated meanings are developed. The alternative logic of marketing systems recognises the unity of a difference between a marketing system and its environment. This insight has become a cornerstone for synthesising the systeming methodology. Systeming comprises the philosophy, the model, and the method of interpreting communication-as-self-observation of marketing system agents. Data, communication by hybrid car manufacturers and consumers, were collected from netnographic sources such as corporate websites, reports posted online, weblogs, and consumer forums. The interpretation of these data was accomplished using systeming procedures, e.g. communication analysis, distinction identification, re-entry description, and logical level tracking. The systeming analysis of the hybrid car marketer and consumer communications illustrates that meaning-creation in the system is underpinned by purposeful human behaviour in reducing complexity of marketplace experience into a meaningful pattern, sustainability. Both manufacturers and consumers claim to become sustainable in reference to being unsustainable by creating self-referential differences, operating in different interaction contexts, and expanding meaning paradoxes. The interpretation shows that interactive meaning-creation in the system is inherently contradictory. Manufacturers expand (give a logical form to) contradictions through introducing hierarchical meaning structures, temporality, new functions, and communicative transvection. Consumers deal with the contradictions through enriching co-creation experiences and learning the proper continuation of specific hybrid car driving practices. The significant insight gained from this investigation is that the hybrid car marketing system is not a passive entity; it is the locus of purposefully expanding meanings. Two modes of sustainability with regard to the hybrid car marketing system can be distinguished: the content of communication that denotes enacted meanings of sustainability and the form of communication that indicates how sustainable these sustainability enactments are. The content/form distinction implies that the sustainability of the hybrid car marketing system is a matter of interactive meaning-creation between system agents. The sustainable development process, in at least a mobility domain, is driven by purposeful social interaction rather than static product attributes. This investigation is innovative because it a) offers a conceptualisation of a marketing system as a meaning flow; b) synthesises and compiles a methodology and method for interpreting communication in a marketing system; c) reveals systemic insights into the hybrid car marketing system; d) characterises the sustainability dimension of the hybrid car marketing system; e) explains a conceptual ground for reconciling the marketing system and society; f) provides a general macromarketing perspective to scrutinise recent conceptual developments in the marketing discipline; g) unifies marketing systems thinking with recent advancements in the marketing discipline, such as the service-dominant logic, and consumer culture theory; and, also, h) provides recommendations for a number of micro-managerial situations from a holistic perspective

The drivers of Corporate Social Responsibility in the supply chain. A case study.

Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and how its CSR strategies reflect on its suppliers and customers relations. Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the generalizing capacity of these findings. Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy. Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of sustainable innovation. Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”