A knowledge based application for industrialization design

After being designed, a product has to be manufactured, which means converting concepts and information into a real, physical object. This requires a big amount of resources and a careful planning. The product manufacturing must be designed too, and that is called Industrialization Design. An accepted methodology for this activity is starting defining simple structures and then progressively increasing the detail degree of the manufacturing solution. The impact of decisions taken at first stages of Industrialization Design is remarkable, and software tools to assist designers are required. In this paper a Knowledge Based Application prototype for the Industrialization Design is presented. The application is implemented within the environment CATIA V5/DELMIA. A case study with a simple Product from aerospace sector illustrates the prototype development.

Application of knowledge engineering acquisition techniques to requirements capture: a case study

In this paper we want to point out, by means of a case study, the importance of incorporating some knowledge engineering techniques to the processes of software engineering. Precisely, we are referring to the knowledge eduction techniques. We know the difficulty of requirements acquisition and its importance to minimise the risks of a software project, both in the development phase and in the maintenance phase. To capture the functional requirements use cases are generally used. However, as we will show in this paper, this technique is insufficient when the problem domain knowledge is only in the "experts? mind". In this situation, the combination of the use case with eduction techniques, in every development phase, will let us to discover the correct requirements.

A knowledge based application for industrialization design

After being designed, a product has to be manufactured, which means converting concepts and information into a real, physical object. This requires a big amount of resources and a careful planning. The product manufacturing must be designed too, and that is called Industrialization Design. An accepted methodology for this activity is starting defining simple structures and then progressively increasing the detail degree of the manufacturing solution. The impact of decisions taken at first stages of Industrialization Design is remarkable, and software tools to assist designers are required. In this paper a Knowledge Based Application prototype for the Industrialization Design is presented. The application is implemented within the environment CATIA V5/DELMIA. A case study with a simple Product from aerospace sector illustrates the prototype development.

Extracting knowledge through friendsourcing: application to new financial services

Personalization has become a key factor for the success of new ICT services. However, the personal information required is not always available in a single site, but scattered in heterogeneous sources, and extracting knowledge from raw information is not an easy job. As a result, many organizations struggle to obtain knowledge on their users useful enough for their business purposes. This paper introduces a comprehensive personal data framework that opens the knowledge extraction process up to collaboration by the involvement of new actors, while enabling users to monitor and control it. The contributions have been validated in a financial services scenario where socioeconomic knowledge on some users is generated by tapping into their social network and used to assists them in raising money from their friends.

Photo interpretation of the terrain along the southern part of the Alaska Highway : An application of the combined knowledge and techniques of botany and geology to the phot interpretation of terrain in northern regions /

Folded plates, maps, and table in pocket.

A general system of chemical knowledge, and its application to the phenomena of nature and art.

Mode of access: Internet.

Understanding conceptual schemas: exploring the role of application and IS domain knowledge

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.

The application of knowledge based expert systems to mechanical engineering design

Investigation of the different approaches used by Expert Systems researchers to solve problems in the domain of Mechanical Design and Expert Systems was carried out. The techniques used for conventional formal logic programming were compared with those used when applying Expert Systems concepts. A literature survey of design processes was also conducted with a view to adopting a suitable model of the design process. A model, comprising a variation on two established ones, was developed and applied to a problem within what are described as class 3 design tasks. The research explored the application of these concepts to Mechanical Engineering Design problems and their implementation on a microcomputer using an Expert System building tool. It was necessary to explore the use of Expert Systems in this manner so as to bridge the gap between their use as a control structure and for detailed analytical design. The former application is well researched into and this thesis discusses the latter. Some Expert System building tools available to the author at the beginning of his work were evaluated specifically for their suitability for Mechanical Engineering design problems. Microsynics was found to be the most suitable on which to implement a design problem because of its simple but powerful Semantic Net Knowledge Representation structure and the ability to use other types of representation schemes. Two major implementations were carried out. The first involved a design program for a Helical compression spring and the second a gearpair system design. Two concepts were proposed in the thesis for the modelling and implementation of design systems involving many equations. The method proposed enables equation manipulation and analysis using a combination of frames, semantic nets and production rules. The use of semantic nets for purposes other than for psychology and natural language interpretation, is quite new and represents one of the major contributions to knowledge by the author. The development of a purpose built shell program for this type of design problems was recommended as an extension of the research. Microsynics may usefully be used as a platform for this development.

Seed phytate and protein content in beans depending on the application of basalt powder

Seed phytate and protein content in beans depending on the application of basalt powder. The content of phytate in the grains is correlated with the supply of phosphorus to the plant, but there is a lack of knowledge as to possible effect of slower availability of nutrients in the soil. The objectives of this study were to assess the effect of rock powder, alone or combined with cattle manure, on the productivity, levels of phosphorus, protein and phytate content in beans. The experiment was carried out in a randomized blocks design, with four replications. The treatments were control (limestone, granite and natural phosphate); conventional fertilization; powder basalt (2.5, 5.0, 10.0 and 20.0 ton. ha(-1)); cattle manure, and doses of powder basalt with cattle manure. In the treatment with conventional fertilizer, the total phosphorus content in grain was higher than the control, but the application of powder of basalt did not show a difference significant. Increase in the doses of basalt powder increased the phosphorus content, but phytate content remained constant. Basalt powder proved to be an alternative to maintain low levels of phosphorus in the form of phytate in the grains.

Application of biotechnology in breeding lentil for resistance to biotic and abiotic stress

Lentil is a self-pollinating diploid (2n = 14 chromosomes) annual cool season legume crop that is produced throughout the world and is highly valued as a high protein food. Several abiotic stresses are important to lentil yields world wide and include drought, heat, salt susceptibility and iron deficiency. The biotic stresses are numerous and include: susceptibility to Ascochyta blight, caused by Ascochyta lentis; Anthracnose, caused by Colletotrichum truncatum; Fusarium wilt, caused by Fusarium oxysporum; Sclerotinia white mold, caused by Sclerotinia sclerotiorum; rust, caused by Uromyces fabae; and numerous aphid transmitted viruses. Lentil is also highly susceptible to several species of Orabanche prevalent in the Mediterranean region, for which there does not appear to be much resistance in the germplasm. Plant breeders and geneticists have addressed these stresses by identifying resistant/tolerant germplasm, determining the genetics involved and the genetic map positions of the resistant genes. To this end progress has been made in mapping the lentil genome and several genetic maps are available that eventually will lead to the development of a consensus map for lentil. Marker density has been limited in the published genetic maps and there is a distinct lack of co-dominant markers that would facilitate comparisons of the available genetic maps and efficient identification of markers closely linked to genes of interest. Molecular breeding of lentil for disease resistance genes using marker assisted selection, particularly for resistance to Ascochyta blight and Anthracnose, is underway in Australia and Canada and promising results have been obtained. Comparative genomics and synteny analyses with closely related legumes promises to further advance the knowledge of the lentil genome and provide lentil breeders with additional genes and selectable markers for use in marker assisted selection. Genomic tools such as macro and micro arrays, reverse genetics and genetic transformation are emerging technologies that may eventually be available for use in lentil crop improvement.