Situation awareness approach to context-aware case-based decision support.

Context-aware case-based decision support systems (CACBDSS) use the context of users as one of the features for similarity assessment to provide solutions to problems. The combination of a context-aware case-based reasoning (CBR) with general domain knowledge has been shown to improve similarity assessment, solving domain specific problems and problems of uncertain knowledge. Whilst these CBR approaches in context awareness address problems of incomplete data and domain specific problems, future problems that are situation-dependent cannot be anticipated due to lack of data by the CACBDSS to make predictions. Future problems can be predicted through situation awareness (SA), a psychological concept of knowing what is happening around you in order to know the future. The work conducted in this thesis explores the incorporation of SA to CACBDSS. It develops a framework to decouple the interface and underlying data model using an iterative research and design methodology. Two new approaches of using situation awareness to enhance CACBDSS are presented: (1) situation awareness as a problem identification component of CACBDSS (2) situation awareness for both problem identification and solving in CACBDSS. The first approach comprises of two distinct parts; SA, and CBR parts. The SA part understands the problem by using rules to interpret cues from the environment and users. The CBR part uses the knowledge from the SA part to provide solutions. The second approach is a fusion of the two technologies into a single case-based situation awareness (CBSA) model for situation awareness based on experience rather than rule, and problem solving predictions. The CBSA system perceives the users context and the environment and uses them to understand the current situation by retrieving similar past situations. The futures of new situations are predicted through knowledge of the history of similar past situations. Implementation of the two approaches in flow assurance control domain to predict the formation of hydrate shows improvements in both similarity assessment and problem solving predictions compared to CACBDSS without SA. Specifically, the second approach provides an improved decision support in scenarios where there are experienced situations. In the absence of experienced situations, the second approach offers more reliable solutions because of its rule-based capability. The adaptation of the user interface of the approaches to the current situation and the presentation of a reusable sequence of tasks in the situation reduces memory loads on operators. The integrated research-design methodology used in realising these approaches links theory and practice, thinking and doing, achieving practical as well as research objectives. The action research with practitioners provided the understanding of the domain activities, the social settings, resources, and goals of users. The user-centered design process ensures an understanding of the users. The agile development model ensures an iterative work, enables faster development of a functional prototype, which are more easily communicated and tested, thus giving better input for the next iteration

Application of MRAC techniques to the PID Controller for nonlinear Magnetic Levitation system using Kalman filter

In this paper, an approach to model reference adaptive control based on pid Controller  is proposed and analyzed for a  magnetic levitation system class of  nonlinear dynamical systems. The controller structure can employ  a mit rule to compensate adaptively the nonlinearities in the plant. A stable controller- parameter adjustment mechanism, which is determined using the Kalman filter , is constructed using a pid controller-type updating law. The evaluation of control error in terms of the  error is performed.   the use of Kalmal Filter in conventional model reference adaptive control (MRAC) to control magnetic levitation system. In the conventional MRAC scheme, the controller is designed to realize plant output converges to reference model output based on the plant which is linear. This scheme is effectively for controlling linear plants with unknown parameters. However, using MRAC to control the magnetic levitation system at real time is a difficult problem for Control system design because it has highly sensitivity for atmospheric disturbance. The proposed method presents design methodology of PID controller using MRAC technique and kalman filter for solving the problems.  The adjustable PID parameters corresponding to changes in plant and disturbance will be determined by referring to the reference model specifying the properties of desired control system. Therefore, this technique is convenient to control the process for satisfying the requirement of the system performance Keywords: Marc, Pid Controller , Magnetic Levitation, Kalman filter , Matlab, Adaptive contro

Numerical product design: Springback prediction, compensation and optimization

Numerical simulations are being deployed widely for product design. However, the accuracy of the numerical tools is not yet always sufficiently accurate and reliable. This article focuses on the current state and recent developments in different stages of product design: springback prediction, springback compensation and optimization by finite element (FE) analysis. To improve the springback prediction by FE analysis, guidelines regarding the mesh discretization are provided and a new through-thickness integration scheme for shell elements is launched. In the next stage of virtual product design the product is compensated for springback. Currently, deformations due to springback are manually compensated in the industry. Here, a procedure to automatically compensate the tool geometry, including the CAD description, is presented and it is successfully applied to an industrial automotive part. The last stage in virtual product design comprises optimization. This article presents an optimization scheme which is capable of designing optimal and robust metal forming processes efficiently

Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach

In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach

Workshop on institutional changes for the NAFTA era: Belize, January 23 - 27 1995

Workshop materials, which include an agenda and report. Four tasks were presented at this workshop: a. Identification of new institutions and capacities that Belize will need to cope with the new international market economy; b. designing implementing appropriate transition; a legislative agenda for the institutional changes to accomplish the desired; c . formulating a research and drafting programme as a sound basis for producing the necessary legislation; and d. outlining training needs for senior management personnel to ensure implementation of the programme

Performance of a New Enhanced Topological Decision-Rule Map-Matching Algorithm for Transportation Applications

Indexación: Web of Science; ScieloMap-matching problems arise in numerous transportation-related applications when spatial data is collected using inaccurate GPS technology and integrated with a flawed digital roadway map in a GIS environment. This paper presents a new enhanced post-processing topological decision-rule map-matching algorithm in order to address relevant special cases that occur in the spatial mismatch resolution. The proposed map-matching algorithm includes simple algorithmic improvements: dynamic buffer that varies its size to snap GPS data points to at least one roadway centerline; a comparison between vehicle heading measurements and associated roadway centerline direction; and a new design of the sequence of steps in the algorithm architecture. The original and new versions of the algorithm were tested on different spatial data qualities collected in Canada and United States. Although both versions satisfactorily resolve complex spatial ambiguities, the comparative and statistical analysis indicates that the new algorithm with the simple algorithmic improvements outperformed the original version of the map-matching algorithm.El problema de la ambigüedad espacial ocurre en varias aplicaciones relacionadas con transporte, específicamente cuando existe inexactitud en los datos espaciales capturados con tecnología GPS o cuando son integrados con un mapa digital que posee errores en un ambiente SIG. Este artículo presenta un algoritmo nuevo y mejorado basado en reglas de decisión que es capaz de resolver casos especiales relevantes en modo post-proceso. El algoritmo propuesto incluye las siguientes mejoras algorítmicas: un área de búsqueda dinámica que varía su tamaño para asociar puntos GPS a al menos un eje de calzada, una comparación entre el rumbo del vehículo y la dirección del eje de calzada asignada, y un nuevo diseño de la secuencia de pasos del algoritmo. Tanto el algoritmo original como el propuesto fueron examinados con datos espaciales de diferentes calidades capturados en Canadá y Estados Unidos. Aunque ambas versiones resuelven satisfactoriamente el problema de ambigüedad espacial, el análisis comparativo y estadístico indica que la nueva versión del algoritmo con las mejoras algorítmicas entrega resultados superiores a la versión original del algoritmo.http://ref.scielo.org/9mt55

A3 thinking approach to support knowledge-driven design

Problem solving is a crucial skill in product development. Any lack of effective decision making at an early design stage will affect productivity and increase costs and the lead time for the other stages of the product development life cycle. This could be improved by the use of a simple and informative approach which allows the designers and engineers to make decisions in product design by providing useful knowledge. This paper presents a novel A3 thinking approach to problem solving in product design, and provides a new A3 template which is structured from a combination of customised elements (e.g. the 8 Disciplines approach) and reflection practice. This approach was validated using a case study in the Electromagnetic Compatibility (EMC) design issue for an automotive electrical sub-assembly product. The main advantage of the developed approach is to create and capture the useful knowledge in a simple manner. Moreover, the approach provides a reflection section allowing the designers to turn their experience of design problem solving into proper learning and to represent their understanding of the design solution. These will be systematically structured (e.g. as a design checklist) to be circulated and shared as a reference for future design projects. Thus, the recurrence of similar design problems will be prevented and will aid the designers in adopting the expected EMC test results

A Design Methodology for Space-Time Adapter

This paper presents a solution to efficiently explore the design space of communication adapters. In most digital signal processing (DSP) applications, the overall architecture of the system is significantly affected by communication architecture, so the designers need specifically optimized adapters. By explicitly modeling these communications within an effective graph-theoretic model and analysis framework, we automatically generate an optimized architecture, named Space-Time AdapteR (STAR). Our design flow inputs a C description of Input/Output data scheduling, and user requirements (throughput, latency, parallelism...), and formalizes communication constraints through a Resource Constraints Graph (RCG). The RCG properties enable an efficient architecture space exploration in order to synthesize a STAR component. The proposed approach has been tested to design an industrial data mixing block example: an Ultra-Wideband interleaver.Comment: ISBN : 978-1-59593-606-