Representation Of Process Knowledge Research Articles

Rough computational methods for information systems

Rough set theory is a relatively new mathematical tool for use in computer applications in circumstances which are characterized by vagueness and uncertainty. The technique called rough analysis can be applied very fruitfully in artificial intelligence and cognitive sciences. Although this methodology has been shown to be successful in dealing with the vagueness of many real-life applications, there are still several theoretical problems to be solved, and we also need to consider practical issues if we want to apply the theory. It is the latter set of issues we address here, in the context of handling and analysing large data sets during the knowledge representation process. Some of the associated problems (for example, the general problem of finding all “keys”) have been shown to be NP-hard. Thus, it is important to seek efficient computational methods for the theory. In rough set theory, a table called an information system or a database relation is used as a special kind of formal language to represent knowledge syntactically. Semantically, knowledge is defined as classifications of information systems. The use of rough analysis does not involve the details of rough set theory directly, but it uses the same basic classification techniques. We discuss computational methods for the rough analysis of databases.

Integrated process improvement in design and manufacture using a systems approach

The paper describes a soft-systems method for the capture, representation and analysis of process knowledge as a platform for process improvement in capital goods manufacture. It is based on the formative results of some collaborative work, funded by two EPSRC grants, between manufacturing companies, including an MNE and an SME. The paper reports on: the problem addressed by the collaborative programme; the approach taken; the results obtained thus far; and the response of the problem-owners to those results and to the prospects of future work. It proposes specific deliverables based on formative results which may enable strategists in certain manufacturing enterprises to begin to design and implement process improvement programmes based on a system approach. The paper describes a novel form of systemic diagram (systemigram) which is used as the means to capture process understanding. Process models, represented by systemigrams, have proved useful to multifunction teams charged with the responsibility of implementing concurrent engineering philosophies by their companies who are seeking significant reductions in product cycle time.

An intelligent assistant for requirements validation

The process of determining user requirements for software systems is often plagued with uncertainty, ambiguity, and inconsistency. Rapid prototyping offers an iterative approach to requirements engineering that can be used to alleviate some of the problems with communication and understanding. Since the systems development process is characterized by changing requirements and assumptions, involving multiple stakeholders with often differing viewpoints, it is beneficial to capture the justifications for the decisions in the development process in a structured manner. Thisdesign rationale captured during requirements engineering can be used in conjunction with the rapid prototyping process to support various stakeholders involved in systems development. CAPS (the Computer Aided Prototyping System) has been built to help software engineers rapidly construct prototypes of proposed software systems. REMAP (Representation and MAintenance of Process knowledge) provides a conceptual model and mechanisms to represent and reason with (design) rationale knowledge. In this paper, we describe how in the context of evolving requirements, the CAPS system augmented with REMAP helps firm up software requirements through iterative negotiations via examination of executable prototypes and reasoning with design rationale knowledge.

Representing and maintaining process knowledge for large-scale systems development

Discusses how the Remap system (representation and maintenance of process knowledge) uses a semiformal representation that supports the design and maintenance of large-scale software systems. The conceptual model relates design rationale knowledge to the resulting system, providing the primitives/ templates with which we can capture (often informal) design rationale information. The model's semantics are well defined, allowing automated reasoning with its components. By providing a complete design history, Remap enhances the understandability of designs and offers a mechanism for propagating changes in design decisions into changes in design solutions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

User modelling for graphical design in complex dynamic environments: concepts and prototype implementations

In this paper, it is proposed that using knowledge-based technology to generate different types of models of a target domain can better assist designers of support systems. The main argument is that designers' decisions should be based on knowledge about a domain rather than on their "common sense" judgments. This approach is illustrated by describing a canonical user model capturing operators' information and knowledge acquisition behaviour. In the present work, this model is used to help designers identify what process variables need to be associated with flow diagrams representing the structure of the technical system. Concepts underlying the user modelling approach as well as the knowledge elicitation and knowledge representation process are described. Finally, functionality provided by the user model is discussed as well as how the approach can be evaluated.

Supporting systems development by capturing deliberations during requirements engineering

Support for various stakeholders involved in software projects (designers, maintenance personnel, project managers and executives, end users) can be provided by capturing the history about design decisions in the early stages of the system's development life cycle in a structured manner. Much of this knowledge, which is called the process knowledge, involving the deliberation on alternative requirements and design decisions, is lost in the course of designing and changing such systems. Using an empirical study of problem-solving behavior of individual and groups of information systems professionals, a conceptual model called REMAP (representation and maintenance of process knowledge) that relates process knowledge to the objects that are created during the requirements engineering process has been developed. A prototype environment that provides assistance to the various stakeholders involved in the design and management of large systems has been implemented. >

Hybrid Modelling of Bioprocesses within a Network Transformation Framework: A Software Engineering Concept

Various modelling paradigms (deterministic, stochastic, statistical, classification, approximation, fuzzy, logical) have been applied to bioprocess control. Each approach is able to cover certain aspects of the complex bio/technical system. To achieve robust control strategies for practical application, different methods for simulation, analysis, validation and control have to be combined. The arising computer programs can be seen as implementations of “hybrid process models”. Usually they have a high complexity and are difficult to maintain with respect to program tranparency, reusability and knowledge retrieval.A software engineering approach is presented that allows the representation of hybrid process knowledge in a well structured way. It is based on the notion of abstract frames, networks and information transformations. First results from previous and current work on an object oriented computer implementation of the described concept (“BioProcess ToolKit”) are summarized. Some applications (i.e. on-line bioprocess optimization, NMR spectral deconvolution) are discussed.

Non-linear adaptive control of fermentation processes utilizing a priori modelling knowledge

This paper describes both SISO and MIMO adaptive versions of non-linear generic model control (GMC) applied to a baker's yeast fermentation. A mechanistic non-linear model is used whose structure can represent a wide range of different fermentation systems and operating conditions. This a priori representation of process knowledge is then combined with a simple and effective adaptation scheme to yield optimal flexibility of the model. Only a few parameters which appear linearly in the model need to be estimated on-line, resulting in very fast and potentially offset-free tracking of the process by the model-based controller. Simulations demonstrate that an adaptive MIMO version of GMC is superior to the corresponding non-adaptive version when faced with modelling errors. Experiments with a bench-scale yeast fermentation system demonstrate for the SISO case the applicability of adaptive non-linear control methods to an actual process and compare adaptive GMC performance with that of a conventional PI controller.

OPSYN: A CAD BASED EXPERT SYSTEM FOR OPTIMUM STRUCTURAL SYNTHESIS

This paper presents an overview of an expert system, OPSYN, for optimum structural synthesis, with particular emphasis on the significance of the development environment for such systems. The knowledge base for this system includes rules for facilitating finite element modeling, optimum design modeling, and selection of optimization strategies and parameters. The environment for this development is an inference engine with both forward and backward reasoning capabilities, a detailed explanation facility, and an automated knowledge acquisition system with a knowledge base editor facility. The use of a computer aided design (CAD) interface with its significant data structure and graphics capabilities in the knowledge acquisition and knowledge representation process is demonstrated with this expert system.

Dependence directed reasoning and learning in systems maintenance support

The maintenance of large information systems involves continuous modifications in response to evolving business conditions or changing user requirements. Based on evidence from a case study, it is shown that the system maintenance activity would benefit greatly if the process knowledge reflecting the teleology of a design could be captured and used in order to reason about he consequences of changing conditions or requirements, A formalism called REMAP (representation and maintenance of process knowledge) that accumulates design process knowledge to manage systems evolution is described. To accomplish this, REMAP acquires and maintains dependencies among the design decisions made during a prototyping process, and is able to learn general domain-specific design rules on which such dependencies are based. This knowledge cannot only be applied to prototype refinement and systems maintenance, but can also support the reuse of existing design or software fragments to construct similar ones using analogical reasoning techniques.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Tools for building advanced user interfaces

System developers are noticing that their design decisions strongly affect computer usability. The design of the user interface has an important bearing on the knowledge users must have to accomplish work through the user-computer interface. Recognition of this fact is leading to the development of User Interface Management Systems (UIMSs). A UIMS is a design concept for separating the details of user interaction from the details of advanced applications. This paper shows how UIMS research and research into the representation of user process knowledge (i.e., user how-to-do-it skills) can help developers understand issues involving ease of learning and ease of use. This parallel progress in UIMS development and in user modeling makes it easier to build high-quality advanced user interfaces.