998 resultados para knowledge spiral
Resumo:
The massive water hyacinth mats that covered water bodies in the 1990s had serious social and economic impacts. They affected fishing, transportation, water quality and health of fishing communities as well as production of goods and services of lake-based institutions (commercial establishments). At peak infestations, the communities and institutions were aware of and participated readily in control effort. However, after the major collapse of hyacinth in 1998, some of them relaxed in their control efforts. The status of knowledge, perception, impacts, preparedness and role of the lakeside communities and institutions to control the weed has, therefore, been monitored since the major resurgence of the weed to find out if the lakeside communities and institutions still perceive water hyacinth as a problem and the extent to which they are prepared to sustain control.
Resumo:
This paper describes an experimental study of a new form of prestressed concrete beam. Aramid Fiber Reinforced Polymers (AFRPs) are used to provide compression confinement in the form of interlocking circular spirals, while external tendons are made from parallel-lay aramid ropes. The response shows that the confinement of the compression flange significantly increases the ductility of the beam, allowing much better utilization of the fiber strength. The failure of the beam is characterized by rupture of spiral confinement reinforcement.
Resumo:
Chapter 15 Design Advisor: How to Supply Designers with Knowledge about Inclusion? E. Zitkus, PM Langdon and PJ Clarkson 15.1 Introduction In an ideal scenario accessibility issues such as legibility, usability and associated cognitive ...
Resumo:
Design knowledge can be acquired from various sources and generally requires an integrated representation for its effective and efficient re-use. Though knowledge about products and processes can illustrate the solutions created (know-what) and the courses of actions (know-how) involved in their creation, the reasoning process (know-why) underlying the solutions and actions is still needed for an integrated representation of design knowledge. Design rationale is an effective way of capturing that missing part, since it records the issues addressed, the options considered, and the arguments used when specific design solutions are created and evaluated. Apart from the need for an integrated representation, effective retrieval methods are also of great importance for the re-use of design knowledge, as the knowledge involved in designing complex products can be huge. Developing methods for the retrieval of design rationale is very useful as part of the effective management of design knowledge, for the following reasons. Firstly, design engineers tend to want to consider issues and solutions before looking at solid models or process specifications in detail. Secondly, design rationale is mainly described using text, which often embodies much relevant design knowledge. Last but not least, design rationale is generally captured by identifying elements and their dependencies, i.e. in a structured way which opens the opportunity for going beyond simple keyword-based searching. In this paper, the management of design rationale for the re-use of design knowledge is presented. The retrieval of design rationale records in particular is discussed in detail. As evidenced in the development and evaluation, the methods proposed are useful for the re-use of design knowledge and can be generalised to be used for the retrieval of other kinds of structured design knowledge. © 2012 Elsevier Ltd. All rights reserved.
Resumo:
The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the efficient alignment of large-scale knowledge bases still poses a considerable challenge. Here, we present Simple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts. SiGMa is an iterative propagation algorithm which leverages both the structural information from the relationship graph as well as flexible similarity measures between entity properties in a greedy local search, thus making it scalable. Despite its greedy nature, our experiments indicate that SiGMa can efficiently match some of the world's largest knowledge bases with high precision. We provide additional experiments on benchmark datasets which demonstrate that SiGMa can outperform state-of-the-art approaches both in accuracy and efficiency.