PREVISE: A knowledge-based system to support the preparation and verification of space operations procedures

This paper presents the Previse system for preparing and verifying operations procedures, developed in the frame of a project conducted by Matra Marconi Space for the European Space Agency ESA/ESTEC. This knowledge-based system supports an evolutive procedures language (syntax and vocabulary). It improves the efficiency of procedures preparation by providing powerful editing facilities, by checking the validity of the syntax used by procedures writers, and by automating the formatting task. It also provides a set of verification mechanisms allowing to detect different types of semantic errors in procedures.     

A refinement framework to support validation and maintenance of knowledge-based systems

In this article, we argue that a refinement tool capable of assisting the maintainer of a Knowledge-Based System (KBS) with updating and upgrading of its knowledge base can substantially expand the scope of his activities and prolong the life of the system. We show that refinement tasks involved in KBS maintenance are similar to those taking place at the development stage, and thus a uniform refinement framework can be designed to support both activities. After defining refinement tasks expected to take place at different stages of a KBS's life cycle, we present a refinement framework capable of supporting them. It utilizes a small number of domain-independent heuristics to search for possible rule revisions which are expected to eliminate errors detected during KBS validation. An extended example is given to illustrate how different refinement tasks are carried out.     

A knowledge-based approach to the iris segmentation problem

This paper describes a knowledge-based approach to the problem of locating and segmenting the iris in images showing close-up human eyes. This approach is inspired in the expert system’s paradigm but, due the specific processing problems associated with image analysis, uses direct encoding of the “decision rules”, instead of a classic, formalized, knowledge base. The algorithm involves a succession of phases that deal with image pre-processing, pupil location, iris location, combination of pupil and iris, eyelids detection, and filtering of reflections. The development was iterative, based on successive improvements tested over a set of training images. The results that were achieved indicate that this global approach can be useful to solve image analysis problems over which human “experts” have better performance than the present computer-based solutions.     

任务链：知识库组织的一种新方法

提出了任务（Task)的概念，每个任务代表一种知识源，不同的任务可以采用不同知识表示形式及推理策略，一个知识库由一组前向或后向链构成的任务链组成，实现了知识库的结构化，可视化，支持知识部件的重用与共享，并提供了一种知识建模机制。     

A flexible semantic inference methodology to reason about user preferences in knowledge-based recommender systems

Recommender systems arose with the goal of helping users search in overloaded information domains (like e-commerce, e-learning or Digital TV). These tools automatically select items (commercial products, educational courses, TV programs, etc.) that may be appealing to each user taking into account his/her personal preferences. The personalization strategies used to compare these preferences with the available items suffer from well-known deficiencies that reduce the quality of the recommendations. Most of the limitations arise from using syntactic matching techniques because they miss a lot of useful knowledge during the recommendation process. In this paper, we propose a personalization strategy that overcomes these drawbacks by applying inference techniques borrowed from the Semantic Web. Our approach reasons about the semantics of items and user preferences to discover complex associations between them. These semantic associations provide additional knowledge about the user preferences, and permit the recommender system to compare them with the available items in a more effective way. The proposed strategy is flexible enough to be applied in many recommender systems, regardless of their application domain. Here, we illustrate its use in AVATAR, a tool that selects appealing audiovisual programs from among the myriad available in Digital TV.     

A process knowledge representation approach for decision support in design of complex engineered systems

Process knowledge is of considerable significance to the digitalization and intelligentization of the manufacturing industry. Current research on the process knowledge representation of decision-making in engineering design has predominantly focused on either mathematical models of individual decisions at the micro-level or organizational models of group decision consensus at the macro-level. However, the management of complexity and uncertainty in the model-based realization of engineered systems is critical to achieving rational, comprehensive, and robust decisions, especially in terms of knowledge-intensive design. The efficiency and effectiveness of decisions in system design are intrinsically linked to the process, knowledge, and system concepts involved, necessitating a more flexible and systematic decision process representation scheme that supports both the management of complexity and uncertainty. Hence, in this paper, we propose a decision-centric design process representation scheme named the Phase-Event-Information X (PEI-X) diagram and its corresponding systematic design guidance method for designing decision workflows. Using the proposed method, designers have the ability to (1) model hierarchical decision processes that cover vertical and horizontal interaction patterns, and (2) exploit the synthesis of the “Formulating-Identifying-Reusing-Exploring” iterative process to extend the understanding and prediction of decision process behaviors in design. We achieve the aforesaid abilities through the implementation of a knowledge-based design guidance system for collaborative decision support and we demonstrate the efficacy by adopting a specific multi-stage manufacturing process design problem, hot rod rolling system design, and carry out an integrated design of materials, products, and related manufacturing processes.     

A knowledge-based decision support system to analyze the debris-flow problems at Chen-Yu-Lan River, Taiwan

Decision-making for the debris-flow management involves multiple decision-makers often with concerning geomorphological and hydraulic conditions. Spatial decision support systems (SDSS) can be developed to improve our understanding of the relations among the natural and socio-economic variables to the occurrence/non-occurrence samples of debris-flow. Accordingly, the goal of this study is to development a debris-flow decision support system to manage and monitor the debris-flows in Nan-Tou County, Taiwan. The present study, more specifically, combines a spatial information system with an advanced Data Mining technique to investigate the debris-flow problem. In the first stage, our spatial information system integrates remote sensing, DEM, and aerial photos as three different resources to generate our spatial database. Each of the geomorphological and hydraulic attributes are obtained automatically through our spatial database. Then, a Data Mining classifier (hybrid model of decision tree (D.T.) + support vector machine (S.V.M.)) will be used to analyze and resolve the classification of occurrence of debris-flow. The contribution of this study has found that watershed area and NDVI (Normalized Difference Vegetation Index) are the crucial factors governing debris-flow by means of decision tree analysis. Further, the performance of prediction accuracy on testing samples through support vector machine is 73% which could be helpful for us to have better understanding of debris-flow problem.     

A note on the coprime fractional representation of nonlinear feedback systems

A very large infinite-dimensional Banach space of bounded nonlinear operators is suggested as an underlying framework for studies of nonlinear systems control. Meanwhile, it is pointed out that all results obtained in Verma [6] can be extended to this much larger family of nonlinear control systems.     

Expert systems as extensions of the human mind: A user oriented,holistic approach to the design of multiple reasoning system environments and interfaces

Expert systems have had little impact as computing artifacts. In this paper we argue that the reason for this stems from the underlying assumption of most builders of expert systems that an expert system needs to acquire information and to control the interaction between the human user and itself. We show that this assumption has serious linguistic and usability flaws which diminish the likelihood of producing socially acceptable expert systems. We propose a reversal of this paradigm, for the design of expert systems, by assuming that it is the human user who needs to acquire information and to control the interaction between themselves and the system.     

A quiver approach to studying orbit spaces of linear systems

Orbit spaces associated to linear actions are of particular interest in control theory. Their geometrical properties can be naturally investigated by using the representations of quivers as an abstract framework. The aim of the paper is to bring into attention an application of this approach and to show how the use of quivers makes it easy handling concepts arising in control theory. Specifically, the natural duality between controllable and observable systems, as well as the construction of compactifications for the associated orbit spaces is interpreted in terms of opposite quivers.     

A modelling framework to support farmers in designing agricultural production systems

Given the new challenges confronting world agriculture, innovative production systems need to be designed at the farm level. As experiments are not easy to conduct at this level, modelling is required to evaluate ex-ante the multiple impacts of proposed innovations. A conceptual framework based on three sub-systems (biophysical, technical, and decisional) interacting within the farm is proposed to guide this process. The advantages and limitations of the framework are illustrated with three examples. The first describes a conceptual, rule-based model representing management decisions for the cultivation of salad in southern France. The second uses a computerized model of the three sub-systems to study irrigation management strategies on farms producing hay in southern France. The third presents a spreadsheet model designed to assist dairy farms in Morocco to define new livestock and forage system strategies. The lessons learned concern the modelling process, the fit between the type of model and its use, and the advantage of involving stakeholders in the design process of tools and innovations.     

A different paradigm for expert systems: an introduction to logic programming and related knowledge representation issues

Abstract: Current expert system technology is 30 years old. Expert system shells find their origins in the work of early expert systems, most notably MYCIN which was developed at Stanford in the mid-1970s. Even Prolog programmers are settling for less robust reasoning power. The logic programming community (from which both expert systems and Prolog arose) has made notable advances since those times. These advances are lacking from current expert system technology. The advances include a well-developed theory of multiple forms of negation, an understanding of open domains and the closed world assumption, default reasoning with exceptions, reasoning with respect to time (i.e. a solution to the frame problem, and introspection with regard to previous beliefs), reasoning about actions, introspection, and maintaining multiple views of the world simultaneously.
The contribution of this paper is to discuss these developments in a singular, integrated, practical, digestible manner. Some of these ideas exist in a variety of papers spread across decades. They also exist in the minds of a very small community of researchers. Some of these ideas are unpublished. The presentation in this paper is from a different point of view, and intended to be more comprehensive and pedagogical. The presentation is also intended to be accessible to a much wider audience. Both the synthesis and the simplicity of this presentation are absent from the literature.     

A web search-centric approach to recommender systems with URLs as minimal user contexts

In service-oriented computing, a recommender system can be wrapped as a web service with machine-readable interface. However, owing to the cross-organizational privacy issue, the internal dataset of an organization is seldom exposed to external services. In this paper, we propose a higher level recommender strategy INSERT that guides the underlying external universal recommender to suggest a set of indexes. INSERT then matches the title of each top-ranked index entry with the domain-specific keywords in the organization's internal dataset, and further directs the universal recommender to verify the popularity of such matching. INSERT finally makes recommendation based on the verification results. INSERT also employs URLs taken from a client as user contexts, which is challenging because URLs contain little content. Our experiment shows that this strategy is feasible and effective.     

Using Gelfond-Przymusinska’s epistemic specifications to justify (some) heuristic methods used in expert systems and intelligent control

 We show that epistemic specifications, proposed by M. Gelfond and H. Przymusinska in [4], lead to a natural justification of several heuristic methods used in expert systems and in intelligent control. This paper is an overview of several results, some of which have already been published before. In contrast to the original publications, that were targeted specifically towards researchers that design and analyze traditional (degree of certainty, MYCIN-type) expert systems and intelligent control systems, we present the corresponding results in such a way that they become understandable (and hopefully, natural) to the logic programming community as well. The relationship between epistemic specifications and heuristic methods not only makes heuristic methods more reliable, it also adds confidence that the formalism of epistemic specifications, as proposed by M. Gelfond and H. Przymusinska, is an appropriate formalization of knowledge: Indeed, the fact that the language of epistemic specifications, that was originally proposed without any numerical degree of certainty in mind, turns out to be quite consistent with (practically successful) number-valued heuristics, is a strong argument in favor of this language. Received: 18 March 1997/Accepted: 13 May 1997     

A Delphi-based approach to developing expert systems with the cooperation of multiple experts

Knowledge acquisition has been a critical bottleneck in building knowledge-based systems. In past decades, several methods and systems have been proposed to cope with this problem. Most of these methods and systems were proposed to deal with the acquisition of domain knowledge from single expert. However, as multiple experts may have different experiences and knowledge on the same application domain, it is necessary to elicit and integrate knowledge from multiple experts in building an effective expert system. Moreover, the recent literature has depicted that “time” is an important parameter that might significantly affect the accuracy of inference results of an expert system; therefore, while discussing the elicitation of domain expertise from multiple experts, it becomes an challenging and important issue to take the “time” factor into consideration. To cope with these problems, in this study, we propose a Delphi-based approach to eliciting knowledge from multiple experts. An application on the diagnosis of Severe Acute Respiratory Syndrome has depicted the superiority of the novel approach.     

A frame-based knowledge representation model and its mapping to nested relations

The first part of this paper introduces the basic constructs of a frame representation model and gives a formal definition for them. Subsequently the nested relational model (NF²) is described as an extension of the classical relational model to support relation-valued attributes. In the second part of this paper both models are compared with each other and a mapping of frame representation structures to NF² structures is specified. The structural similarities between frames and NF² relations are made clear and it is shown that their main difference is due to the type polymorphism introduced by the concept hierarchy of the frame model. This causes type collisions to occur in the strictly typed NF² model when frames are directly mapped to NF² structures. Two solutions to this problem are suggested and compared. The paper concludes with a reformulation of query operations of the frame model in terms of NF² algebra operations.     

Graph based knowledge models for capitalizing,predicting and learning: A proof of concept applied to the dam systems

The capitalization and the analysis of historical information is nowadays a prerequisite for any effective risk management and assessment in a wide range of domains. Despite the development of mathematical models, procedures, support decision systems and databases, some engineering disciplines, such as civil engineering, remain resistant to the use of new digital technology due to the gap between the expectations of the engineers and the support that the tools may really provide. It is essential to propose a tool able to process both cross disciplinary and interdisciplinary knowledge flux and feedback from experience in a common and convenient unifying framework. The aim is to assist and to support engineering work and to make the task of knowledge modelling easier. The domain of dam systems is no exception to the rule. Dam failures are still commonplace. These failures stem from a lack of understanding about the complex relationships between three different factors: random hazards, the limit states of dam structures along with human activities and decisions. No generic and holistic approach is currently available that permits the processing of both knowledge and data, performs inferences and is easily usable for all types of users. This paper proposes the basic principles of a convenient design methodology for capitalizing, learning and predicting based on the formalism of conceptual graphs. The aim is to provide an easily usable tool able to (1) capitalise heterogeneous knowledge and store a database about dams, (2) issue alerts on current projects, (3) draw lessons from past dam failures and (4) tackle key issues in forensic civil engineering.     

A model, a heuristic and a decision support system to solve the scheduling problem of an earth observing satellite constellation

China plans to launch four small optical satellites and four small SAR satellites to form a natural disaster monitoring constellation. Data can be obtained by the constellation in all weather conditions for disaster alert and environmental damage analysis. The scheduling problem for the constellation consists of selecting and timetabling the observation activities to acquire the requested images of the earth surface and scheduling the download activities to transmit the image files to a set of ground stations. The scheduling problem is required to be solved every day in a typical 1-day horizon and it must respect complex satellite operational constraints as well as request preferences, such as visibility time windows, transition time between consecutive observations or downloads, memory capacity, energy capacity, polygon target requests and priorities. The objective is to maximize the rewards of the images taken and transmitted. We present a nonlinear model of the scheduling problem, develop a priority-based heuristic with conflict-avoided, limited backtracking and download-as-needed features, which produces satisfactory feasible plans in a very short time. A decision support system based on the model and the heuristic is also provided. The system performance shows a significant improvement with respect to faster and better scheduling of an earth observing satellite constellation.     

A counterexample to “Generalized eigenvalue-based stability tests for 2-D linear systems: Necessary and sufficient conditions” by Fu, P., Chen, J., and S.I. Niculescu

We present a counterexample contradicting the equivalence of statements (i)-(ii) and (iii)-(v) of Theorem 1 of Fu, Chen, and Niculescu (2006).