Considerations in development of expert systems for real-time space applications

Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications

The Impact of Expert Systems on AIS - Characteristics and Productivity Work Life Cycle: A Study Targeting Jordan Large Market Organizations

The computer science new emerged technology on AIS researches should explore the application of AIS on the commercial development in terms of availability and characteristics, in addition to productivity and life cycle. The AIS researches are concerning not only into computer science and accounting, but also in organizations and organizational effects. A general citation of expert systems on AIS will be stated and studied in this paper, which aims to investigate the impact of theuse of artificial intelligence and expert systems techniques strategies on accounting information systems. Itconcentrates on concerns that are of most interest for accounting information systems, this investigation looks at the use of Artificial Intelligence and expert systems to be a solution to those concerns, and to be efficient factors in improving general characteristics of accounting information systems in an organization simply by improving productivity and work quality and make a reasonable change in the process life cycle. This thesis targets the large scale market organization in Jordan, where those organizations also has many constrains and limitations. Keywords – AIS; Expert Systems; Work Life Cycle; Productivit

Considerations in development of expert systems for real-time space applications

Over the years demand on space systems have been increased tremendously and this trend will continue for the near future. The enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems, and artificial intelligence and expert system concepts have a significant role in space applications. Expert systems could facilitate decision making, improved fault diagnosis and repair, enhanced performance and less reliance on ground support. However, some requirements have to be fulfilled before practical use of flight-worthy expert systems for onboard (and ground) operations. This paper discusses some of the characteristics and important considerations in design, development, implementation and use of expert systems for real-life space applications. Further, it describes a typical life cycle of expert system development and its usage

A review of expert systems for chromatography

Expert systems for chromatography are reviewed. A taxonomy is proposed that allows present (and future) expert systems in this area to be classified and facilitates an understanding of their inter-relationship. All the systems are described focusing on the reasons for their development, what their purpose was and how they were to be used. The engineering methods, knowledge representations, tools and architectures used for the systems are compared and contrasted in a discussion covering all the stages of the development life cycle of expert systems. The review reveals that too often developers of expert systems for chromatography do not justify their decisions on engineering matters and that the literature suggests that many ideas advocated by knowledge engineers are not being used

Expert system development methodology and the transition from prototyping to operations: FIESTA, a case study

A major barrier in taking expert systems from prototype to operational status involves instilling end user confidence in the operational system. The software of different life cycle models is examined and the advantages and disadvantages of each when applied to expert system development are explored. The Fault Isolation Expert System for Tracking and data relay satellite system Applications (FIESTA) is presented as a case study of development of an expert system. The end user confidence necessary for operational use of this system is accentuated by the fact that it will handle real-time data in a secure environment, allowing little tolerance for errors. How FIESTA is dealing with transition problems as it moves from an off-line standalone prototype to an on-line real-time system is discussed

Expert Systems as Applied to Future Space Transportation Syst

Future space transportation system programs must utilize cost reduction tools and techniques in order to become viable entities in the prevailing political and economic environments. Expert system and knowledge based technology can provide this opportunity for significant cost savings. Current active programs may achieve some limited cost benefits via piecemeal applications to identifiable worthwhile targets. But, the real value of the technology lies in the inclusion of its principles in the initial requirements definition phase for the target program and application of these principles throughout the program life cycle. Therefore, it is clear that accommodation of this kind of usage which encompasses the application of technology using sound engineering principles requires the development of tools to accommodate implementation. This means that expert system life cycle standards similar to MIL-STD 2167 are required, various expert system architectures must be developed, e.g., distributed and hybrid distributed systems, large and complex expert systems must easily integrate and interface with procedural language systems such as Ada, and tools that automate the process of knowledge base rule generation from domain experts must be developed to simplify the knowledge acquisition process. Development of these tools and capabilities is realizable within the capabilities of existing technologies. In the current environment of intensive development effort in pursuit of these tools and capabilities, it is reasonable to assume expert system technology will be in a condition suitable to support development of the next generation of space transportation system elements

An overview of the program to place advanced automation and robotics on the Space Station

The preliminary design phase of the Space Station has uncovered a large number of potential uses of automation and robotics, most of which deal with the assembly and operation of the Station. If NASA were to vigorously push automation and robotics concepts in the design, the Station crew would probably be free to spend a substantial portion of time on payload activities. However, at this point NASA has taken a conservative attitude toward automation and robotics. For example, the belief is that robotics should evolve through telerobotics and that uses of artificial intelligence should be initially used in an advisory capacity. This conservativeness is in part due to the new and untested nature of automation and robotics; but, it is also due to emphases plased on designing the Station to the so-called upfront cost without thoroughly understanding the life cycle cost. Presumably automation and robotics has a tendency to increase the initial cost of the Space Station but could substantially reduce the life cycle cost. To insure that NASA will include some form of robotic capability, Congress directed to set aside funding. While this stimulates the development of robotics, it does not necessarily stimulate uses of artificial intelligence. However, since the initial development costs of some forms of artificial intelligence, such as expert systems, are in general lower than they are for robotics one is likely to see several expert systems being used on the Station

Application Of Fuzzy Mathematics Methods To Processing Geometric Parameters Of Degradation Of Building Structures

The aim of research is formalization of the expert experience, which is used in processing geometric parameters of building structure degradation, using fuzzy mathematics. Materials that are used to specify fuzzy models are contained in expert assessments and scientific and technical reports on the technical condition of buildings. The information contained in the reports and assessments is presented in text form and is accompanied by a large number of photographs and diagrams. Model specification methods, based on the analysis of such information on the technical state of structures with damages and defects of various types, primarily lead to difficulties associated with the presentation of knowledge and require the formalization of expert knowledge and experience in the form of fuzzy rules. Approbation and adaptation of the rules is carried out in the process of further research taking into account the influence of random loads and fields. The scientific novelty of the work is expanding of the knowledge base due to the geometric parameters of structural degradation, on the basis of which a fuzzy conclusion about their technical state in the systems of fuzzy product rules at different stages of the object's life cycle is realized. The results of the work are presented in the form of a formalized description of the geometric parameters of degradation. The knowledge presented in the work is intended for the development of technical documentation that is used at the pre-project stage of building reconstruction, but the gained experience is the source of information on the basis of which a constructive solution is selected in the design process of analogical objects. In addition, the knowledge gained from the analysis of expert assessments of the state of various designs is necessary for development of automated expert evaluation processing systems. The use of such evaluation systems will significantly reduce the risks of the human factor associated with the errors in the specification of models for predicting the processes of structural failure at various stages of ensuring the reliability and safety of buildings

RobAFIS student competition actuality: Safety & Security interactions between Operators and with the System

International audienceThis paper presents the RobAFIS competition which is yearly organized since 2006, by AFIS, the French chapter of INCOSE. This competition, as well as its pedagogical objectives, have been presented in previous editions on Insight [1] [2] [3] [4]. RobAFIS enhances AFIS action, offering educational and research institutions an operation to better understand and develop the use of systems engineering best practices, as recommended and formalized by AFIS. Two reference documents are recommended for RobAFIS :-the book "To discover and understand Systems Engineering" [5].-the book "Thinking System" [6]. Since 2007, Students and their supervising teachers have the opportunity to exchange with the jury AFIS expert members, working in industry or teaching Systems Engineering. During development, these experts answer, via a FAQ page on a RobAFIS dedicated collaborative space [7], questions about technical or methodological issues related to stakeholder requirements or to the development document. The main objective of RobAFIS is to highlight the benefits of basing systems engineering education on a project life cycle realization: a full life cycle including the implementation of an operational system, deployed by a client, in a real environment

Constructing an Office Domain Ontology using Knowledge Engineering Process

Knowledge based identification of human activities in systems depends primarily on rich contextual domain knowledge casing all of the information about the human, objects around human and also relations amongst them. Knowledge engineering plays an important role in building knowledge based expert systems, to solve complex problems such as human activity recognition. This requires formal representation of the knowledge which is based on the conceptualization of the domain. Ontology is awidely chosen representational model that depicts knowledge as a set of concepts. In this work, we have applied knowledge engineering process for constructingthe domain ontology of the officeenvironment in agreement with the ontology development life cycle