A communication model to aid knowledge-based design systems

1990 ◽  
Vol 4 (2) ◽  
pp. 99-115 ◽  
Author(s):  
David V. Morse ◽  
Chris Hendrickson
Keyword(s):  
Conceptual Model ◽  
Domain Knowledge ◽  
Knowledge Engineering ◽  
Automated System ◽  
Engineering System ◽  
Communication Model ◽  
Industrial Facilities ◽  
Knowledge Based ◽  
Definition Of ◽  
Process Architecture

Recent research in the area of computer-aided engineering design has focused on the development of environments that provide effective integration of several domain specialties for complex multidisciplinary synthesis problems. The definition of communication requirements for co-operative interaction—and the subsequent establishment of a conceptual model for automating the process—are important considerations in the development of such environments. A communication model can also provide the basis for development of a knowledge engineering strategy by defining the organizational and representational requirements for domain knowledge in the automated system. This paper presents a conceptual model for communication in automated interactive design and demonstrates how the model can be employed as a knowledge engineering tool to facilitate the acquisition and organization of domain expertise. Both the process architecture and semantic modeling aspects of the communication problem are considered. An example is included which illustrates the use of the model in formulating an automated integrated engineering system in the domain of floor and equipment layout and design for industrial facilities.

Knowledge-Based Induction of Clinical Prediction Rules

2011 ◽  
pp. 350-375
Author(s):  
Mila Kwiatkowska ◽  
M. Stella Atkins ◽  
Les Matthews ◽  
Najib T. Ayas ◽  
C. Frank Ryan
Keyword(s):  
Domain Knowledge ◽  
Medical Knowledge ◽  
Data Sets ◽  
Clinical Prediction ◽  
Clinical Prediction Rules ◽  
Prediction Rules ◽  
Integrative Framework ◽  
Knowledge Based ◽  
The Creation ◽  
Definition Of

This chapter describes how to integrate medical knowledge with purely inductive (data-driven) methods for the creation of clinical prediction rules. It addresses three issues: representation of medical knowledge, secondary analysis of medical data, and evaluation of automatically induced predictive models in the context of existing knowledge. To address the complexity of the domain knowledge, the authors have introduced a semio-fuzzy framework, which has its theoretical foundations in semiotics and fuzzy logic. This integrative framework has been applied to the creation of clinical prediction rules for the diagnosis of obstructive sleep apnea, a serious and under-diagnosed respiratory disorder. The authors use a semio-fuzzy approach (1) to construct a knowledge base for the definition of diagnostic criteria, predictors, and existing prediction rules; (2) to describe and analyze data sets used in the data mining process; and (3) to interpret the induced models in terms of confirmation, contradiction, and contribution to existing knowledge.

scholarly journals A comparison of languages which operationalize and formalize KADS models of expertise

1994 ◽  
Vol 9 (2) ◽  
pp. 105-146 ◽  
Author(s):  
Dieter Fensel ◽  
Frank van Harmelen
Keyword(s):  
Problem Solving ◽  
Rapid Prototyping ◽  
Conceptual Model ◽  
Model Evaluation ◽  
Conceptual Models ◽  
Knowledge Engineering ◽  
Future Research ◽  
Knowledge Based Systems ◽  
Research Issues ◽  
Knowledge Based

AbstractIn the field of knowledge engineering, dissatisfaction with therapid-prototypingapproach has led to a number of more principled methodologies for the contruction of knowledge-based systems. Instead of immediately implementing the gathered and interpreted knowledge in a given implementation formalism according to the rapid-prototyping approach, many such methodologies centre around the notion of a conceptual model: an abstract, implementation independent description of the relevant problem solving expertise. A conceptual model should describe the task which is solved by the system and the knowledge which is required by it. Although such conceptual models more precisely, and operationally as a means for model evaluation. In this paper, we study a number of such formal and operational languages for specifying conceptual models. To enable a meaningful comparison of such languages, we focus on languages which are all aimed at the same underlying conceptual model, namely that from the KADS method for building KBS. We describe eight formal languages for KADS models of expertise, and compare these languages with respect to their modelling primitives, their semantics, their implementations and their applications, Future research issues in the area of formal and operational specification languages for KBS are identified as the result of studying these languages. The paper also contains an extensive bibliography of research in this area.

A- AND V-UNCERTAINTY: AN EXPLORATION ABOUT UNCERTAINTY MODELING FROM A KNOWLEDGE ENGINEERING PERSPECTIVE

2007 ◽  
Vol 16 (02) ◽  
pp. 161-194 ◽  
Author(s):  
PIETRO BARONI ◽  
GIOVANNI GUIDA ◽  
MASSIMILIANO GIACOMIN
Keyword(s):  
Domain Knowledge ◽  
Knowledge Engineering ◽  
Uncertainty Modeling ◽  
Uncertain Reasoning ◽  
Correct Treatment ◽  
Knowledge Based ◽  
Uncertainty Sources ◽  
Concrete Experience ◽  
The One ◽  
Uncertainty Models

This paper presents a concrete experience of Knowledge Engineering, which, starting from a specific problem which occurred during the development of ASTRA, a knowledge-based system for preventive diagnosis of power transformers, turned out to provide significant insights concerning modeling of uncertain knowledge. In particular, it was observed that there are (at least) two conceptually distinct types of uncertainty affecting knowledge, namely uncertainty about applicability (A-uncertainty, for short) and uncertainty about validity (V-uncertainty, for short), which are different in nature and play different roles in uncertain reasoning. The concepts of A- and V-uncertainty are applicable in any context where uncertainty affecting domain knowledge can be ascribed to two kinds of sources: on the one hand, the existence of exceptions, on the other hand, deep-rooted doubts about the foundations themselves of the relevant domain knowledge. The introduction of these concepts allows one to define articulated uncertainty models, supporting the representation of the reasoning mechanisms used by experts in domains where both such uncertainty sources are present. This general claim was confirmed by the experience developed with ASTRA, where the explicit representation and management of A- and V-uncertainty enabled the correct treatment of some critical diagnostic cases.

Application of Expert Systems Technology in Water Quality Modeling

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1045-1056 ◽  
Author(s):  
Thomas O. Barnwell ◽  
Linfield C. Brown ◽  
Wiktor Marek
Keyword(s):  
Water Quality ◽  
Expert Systems ◽  
Knowledge Engineering ◽  
Stream Water ◽  
Environmental Modeling ◽  
Water Quality Modeling ◽  
Stream Water Quality ◽  
Quality Model ◽  
Knowledge Based ◽  
Available Technology

Computerized modeling is becoming an integral part of decision making in water pollution control. Expert systems is an innovative methodology that can assist in building, using, and interpreting the output of these models. This paper reviews the use and evaluates the potential of expert systems technology in environmental modeling and describes elements of an expert advisor for the stream water quality model QUAL2E. Some general conclusions are presented about the tools available to develop this system, the level of available technology in knowledge-based engineering, and the value of approaching problems from a knowledge engineering perspective.

scholarly journals Resource and dependency based test case generation for RESTful Web services

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Man Zhang ◽  
Bogdan Marculescu ◽  
Andrea Arcuri
Keyword(s):  
Web Services ◽  
Domain Knowledge ◽  
Automated System ◽  
Test Case ◽  
Test Cases ◽  
Evolutionary Search ◽  
Sampling Strategies ◽  
Mutation Operators ◽  
On Line ◽  
Restful Web Services

AbstractNowadays, RESTful web services are widely used for building enterprise applications. REST is not a protocol, but rather it defines a set of guidelines on how to design APIs to access and manipulate resources using HTTP over a network. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services, by exploiting domain knowledge on the handling of HTTP resources. The proposed techniques use domain knowledge specific to RESTful web services and a set of effective templates to structure test actions (i.e., ordered sequences of HTTP calls) within an individual in the evolutionary search. The action templates are developed based on the semantics of HTTP methods and are used to manipulate the web services’ resources. In addition, we propose five novel sampling strategies with four sampling methods (i.e., resource-based sampling) for the test cases that can use one or more of these templates. The strategies are further supported with a set of new, specialized mutation operators (i.e., resource-based mutation) in the evolutionary search that take into account the use of these resources in the generated test cases. Moreover, we propose a novel dependency handling to detect possible dependencies among the resources in the tested applications. The resource-based sampling and mutations are then enhanced by exploiting the information of these detected dependencies. To evaluate our approach, we implemented it as an extension to the EvoMaster tool, and conducted an empirical study with two selected baselines on 7 open-source and 12 synthetic RESTful web services. Results show that our novel resource-based approach with dependency handling obtains a significant improvement in performance over the baselines, e.g., up to + 130.7% relative improvement (growing from + 27.9% to + 64.3%) on line coverage.

scholarly journals Getting to Hope: Perspectives from Patients and Caregivers Living with Chronic Childhood Illness

Children ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 525
Author(s):  
Emily von Scheven ◽  
Bhupinder K. Nahal ◽  
Rosa Kelekian ◽  
Christina Frenzel ◽  
Victoria Vanderpoel ◽  
...  
Keyword(s):  
Conceptual Model ◽  
Research Question ◽  
Young Patients ◽  
Future Research ◽  
Childhood Onset ◽  
Virtual Focus Groups ◽  
Definition Of ◽  
Selection Of ◽  
Chronic Childhood ◽  
Research Studies

Promoting hope was identified in our prior work as the top priority research question among patients and caregivers with diverse childhood-onset chronic conditions. Here, we aimed to construct a conceptual model to guide future research studies of interventions to improve hope. We conducted eight monthly virtual focus groups and one virtual workshop with patients, caregivers, and researchers to explore key constructs to inform the model. Discussions were facilitated by Patient Co-Investigators. Participants developed a definition of hope and identified promotors and inhibitors that influence the experience of hope. We utilized qualitative methods to analyze findings and organize the promotors and inhibitors of hope within three strata of the socio-ecologic framework: structural, interpersonal, and intrapersonal. Participants identified three types of interventions to promote hope: resources, navigation, and activities to promote social connection. The hope conceptual model can be used to inform the selection of interventions to assess in future research studies aimed at improving hope and the specification of outcome measures to include in hope research studies. Inclusion of the health care system in the model provides direction for identifying strategies for improving the system and places responsibility on the system to do better to promote hope among young patients with chronic illness and their caregivers.

scholarly journals A physical resilience conceptual model – contributions to gerontological nursing

2018 ◽  
Vol 71 (5) ◽  
pp. 2589-2593 ◽  
Author(s):  
Rafael Bernardes ◽  
Cristina Lavareda Baixinho
Keyword(s):  
Older Adults ◽  
Conceptual Model ◽  
Nursing Care ◽  
Functional Capacity ◽  
Geriatric Nursing ◽  
Frailty Syndrome ◽  
Gerontological Nursing ◽  
Innate Capacity ◽  
Potential Applicability ◽  
Definition Of

ABSTRACT Objectives: To analyze and reflect on the potential applicability of the contribution of the physical resilience conceptual model of Whitson et al. in the care for older adults. Method: The present article of reflection was structured based on the consultation of articles and definition of inherent concepts, with analysis and reason of the potentialities of its application in geriatric nursing care. Results: Physical resilience is influenced by diverse stimuli. The identification of stressors and early intervention enable the delay of the functional capacity decline. In practice, the planning of interventions that depend on the innate capacity of older adults is of utmost importance. Conclusion: The trajectory outlined over a debilitating event is relevant to understand the factors that contribute to the development of frailty or pre-frailty conditions. This knowledge allows nurses to adjust their practice and contribute to the effectiveness of interventions and a better prevention of the frailty syndrome.

Configuration Tree Solver: A Technology for Automated Design and Configuration

1990 ◽  
Author(s):  
Alexander Kott ◽  
Gerald Agin ◽  
Dave Fawcett
Keyword(s):  
Problem Solving ◽  
General Model ◽  
General Class ◽  
Domain Knowledge ◽  
Automated Design ◽  
Automotive Component ◽  
Business Operation ◽  
Knowledge Based ◽  
Specific Configuration

Abstract Configuration is a process of generating a definitive description of a product or an order that satisfies a set of specified requirements and known constraints. Knowledge-based technology is an enabling factor in automation of configuration tasks found in the business operation. In this paper, we describe a configuration technique that is well suited for configuring “decomposable” artifacts with reasonably well defined structure and constraints. This technique may be classified as a member of a general class of decompositional approaches to configuration. The domain knowledge is structured as a general model of the artifact, an and-or hierarchy of the artifact’s elements, features, and characteristics. The model includes constraints and local specialists which are attached to the elements of the and-or-tree. Given the specific configuration requirements, the problem solving engine searches for a solution, a subtree, that satisfies the requirements and the applicable constraints. We describe an application of this approach that performs configuration and design of an automotive component.

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