3,343 research outputs found

    Evaluating platform architectures within ecosystems: modeling the relation to indirect value

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    This thesis establishes a framework for understanding the role of a supplier within the context of a business ecosystem. Suppliers typically define their business in terms of capturing value by meeting the demands of direct customers. However, the framework recognises the importance of understanding how a supplier captures indirect value by meeting the demands of indirect customers. These indirect customers increasingly use a supplier’s products and services over time in combination with those of other suppliers. This type of indirect demand is difficult for the supplier to anticipate because it is asymmetric to their own definition of demand. Customers pay the costs of aligning products and services to their particular needs by expending time and effort, for example, to link disparate social technologies or to coordinate healthcare services to address their particular condition. The accelerating tempo of variation in individual needs increases the costs of aligning products and services for customers. A supplier’s ability to reduce its indirect customers’ costs of alignment represents an opportunity to capture indirect value. The hypothesis is that modelling the supplier's relationship to indirect demands improves the supplier’s ability to identify opportunities for capturing indirect value. The framework supports the construction and analysis of such models. It enables the description of the distinct forms of competitive advantage that satisfy a given variety of indirect demands, and of the agility of business platforms supporting that variety of indirect demands. Models constructed using this framework are ‘triply-articulated’ in that they articulate the relationships among three sub-models: (i) the technical behaviours generating products and services, (ii) the social entities managing their supply, and (iii) the organisation of value defined by indirect customers’ demands. The framework enables the derivation from such a model of a layered analysis of the risks to which the capture of indirect value exposes the supplier, and provides the basis for an economic valuation of the agility of the supporting platform architectures. The interdisciplinary research underlying the thesis is based on the use of tools and methods developed by the author in support of his consulting practice within large and complex organisations. The hypothesis is tested by an implementation of the modeling approach applied to suppliers within their ecosystems in three cases: (a) UK Unmanned Airborne Systems, (b) NATO Airborne Warning and Control Systems, both within their respective theatres of operation, and (c) Orthotics Services within the UK's National Health Service. These cases use this implementation of the modeling approach to analyse the value of platforms, their architectural design choices, and the risks suppliers face in their use. The thesis has implications for the forms of leadership involved in managing such platform-based strategies, and for the economic impact such strategies can have on their larger ecosystem. It informs the design of suppliers’ platforms as system-of-system infrastructures supporting collaborations within larger ecosystems. And the ‘triple-articulation’ of the modelling approach makes new demands on the mathematics of systems modeling

    IST Austria Thesis

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    Fabrication of curved shells plays an important role in modern design, industry, and science. Among their remarkable properties are, for example, aesthetics of organic shapes, ability to evenly distribute loads, or efficient flow separation. They find applications across vast length scales ranging from sky-scraper architecture to microscopic devices. But, at the same time, the design of curved shells and their manufacturing process pose a variety of challenges. In this thesis, they are addressed from several perspectives. In particular, this thesis presents approaches based on the transformation of initially flat sheets into the target curved surfaces. This involves problems of interactive design of shells with nontrivial mechanical constraints, inverse design of complex structural materials, and data-driven modeling of delicate and time-dependent physical properties. At the same time, two newly-developed self-morphing mechanisms targeting flat-to-curved transformation are presented. In architecture, doubly curved surfaces can be realized as cold bent glass panelizations. Originally flat glass panels are bent into frames and remain stressed. This is a cost-efficient fabrication approach compared to hot bending, when glass panels are shaped plastically. However such constructions are prone to breaking during bending, and it is highly nontrivial to navigate the design space, keeping the panels fabricable and aesthetically pleasing at the same time. We introduce an interactive design system for cold bent glass façades, while previously even offline optimization for such scenarios has not been sufficiently developed. Our method is based on a deep learning approach providing quick and high precision estimation of glass panel shape and stress while handling the shape multimodality. Fabrication of smaller objects of scales below 1 m, can also greatly benefit from shaping originally flat sheets. In this respect, we designed new self-morphing shell mechanisms transforming from an initial flat state to a doubly curved state with high precision and detail. Our so-called CurveUps demonstrate the encodement of the geometric information into the shell. Furthermore, we explored the frontiers of programmable materials and showed how temporal information can additionally be encoded into a flat shell. This allows prescribing deformation sequences for doubly curved surfaces and, thus, facilitates self-collision avoidance enabling complex shapes and functionalities otherwise impossible. Both of these methods include inverse design tools keeping the user in the design loop

    Castell: a heterogeneous cmp architecture scalable to hundreds of processors

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    Technology improvements and power constrains have taken multicore architectures to dominate microprocessor designs over uniprocessors. At the same time, accelerator based architectures have shown that heterogeneous multicores are very efficient and can provide high throughput for parallel applications, but with a high-programming effort. We propose Castell a scalable chip multiprocessor architecture that can be programmed as uniprocessors, and provides the high throughput of accelerator-based architectures. Castell relies on task-based programming models that simplify software development. These models use a runtime system that dynamically finds, schedules, and adds hardware-specific features to parallel tasks. One of these features is DMA transfers to overlap computation and data movement, which is known as double buffering. This feature allows applications on Castell to tolerate large memory latencies and lets us design the memory system focusing on memory bandwidth. In addition to provide programmability and the design of the memory system, we have used a hierarchical NoC and added a synchronization module. The NoC design distributes memory traffic efficiently to allow the architecture to scale. The synchronization module is a consequence of the large performance degradation of application for large synchronization latencies. Castell is mainly an architecture framework that enables the definition of domain-specific implementations, fine-tuned to a particular problem or application. So far, Castell has been successfully used to propose heterogeneous multicore architectures for scientific kernels, video decoding (using H.264), and protein sequence alignment (using Smith-Waterman and clustalW). It has also been used to explore a number of architecture optimizations such as enhanced DMA controllers, and architecture support for task-based programming models. ii

    Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption

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    In this paper, we present a novel pose normalization method for indoor mapping point clouds and triangle meshes that is robust against large fractions of the indoor mapping geometries deviating from an ideal Manhattan World structure. In the case of building structures that contain multiple Manhattan World systems, the dominant Manhattan World structure supported by the largest fraction of geometries is determined and used for alignment. In a first step, a vertical alignment orienting a chosen axis to be orthogonal to horizontal floor and ceiling surfaces is conducted. Subsequently, a rotation around the resulting vertical axis is determined that aligns the dataset horizontally with the coordinate axes. The proposed method is evaluated quantitatively against several publicly available indoor mapping datasets. Our implementation of the proposed procedure along with code for reproducing the evaluation will be made available to the public upon acceptance for publication

    Psychological challenges for the analysis of style.

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    This article remains the copyright of Cambridge University Press. The definitive version of this article can be found at: http://dx.doi.org/10.1017/S089006040606015XAnalyses of styles in design have paid little attention to how people see style, and how designers use perceptions of style to guide designing. While formal and computational methods for analysing styles and generating designs provide impressively parsimonious accounts of what some styles are, they do not address many of the factors that influence how humans understand styles. The subtlety of human style judgements raises challenges for computational approaches to style. This paper differentiates between a range of distinct meanings of 'style', and explores how designers and ordinary people learn and apply perceptual similarity classes and style concepts in different situations to interpret and create designed artefacts. A range of psychological evidence indicates that style perception is dependent on knowledge, and involves the interaction of perceptual recognition of style features and explanatory inference processes that create a coherent understanding of an object as an exemplar of a style. This paper concludes by outlining how formal style analyses can be used in combination with psychological research to develop a fuller understanding of style perception and creative design
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