Conceptualization of the tabular representation of knowledge

2021 ◽  
Author(s):  
Viktor Shynkarenko ◽  
Larysa Zhuchyi ◽  
Oleksandr Ivanov
Keyword(s):  
Representation Of Knowledge

An Electronic Study Form to Support Collaborating Agents in the Management of Clinical Knowledge

1999 ◽  
Vol 38 (03) ◽  
pp. 154-157
Author(s):  
W. Fierz ◽  
R. Grütter
Keyword(s):  
Procedural Knowledge ◽  
Health Care Provision ◽  
Markup Language ◽  
Artificial Agents ◽  
Care Provision ◽  
Clinical Knowledge ◽  
Extensible Markup ◽  
Implementation Level ◽  
Biological Organisms ◽  
Representation Of Knowledge

AbstractWhen dealing with biological organisms, one has to take into account some peculiarities which significantly affect the representation of knowledge about them. These are complemented by the limitations in the representation of propositional knowledge, i. e. the majority of clinical knowledge, by artificial agents. Thus, the opportunities to automate the management of clinical knowledge are widely restricted to closed contexts and to procedural knowledge. Therefore, in dynamic and complex real-world settings such as health care provision to HIV-infected patients human and artificial agents must collaborate in order to optimize the time/quality antinomy of services provided. If applied to the implementation level, the overall requirement ensues that the language used to model clinical contexts should be both human- and machine-interpretable. The eXtensible Markup Language (XML), which is used to develop an electronic study form, is evaluated against this requirement, and its contribution to collaboration of human and artificial agents in the management of clinical knowledge is analyzed.

Representing wine concepts: A hybrid approach

2020 ◽  
Vol 15 (4) ◽  
pp. 475-491
Author(s):  
M. Cristina Amoretti ◽  
Marcello Frixione
Keyword(s):  
Hybrid Approach ◽  
Sufficient Conditions ◽  
Geometric Representation ◽  
Conceptual Spaces ◽  
Geographical Indication ◽  
Knowledge Based ◽  
Quality Dimensions ◽  
Grape Varieties ◽  
Degree Of Similarity ◽  
Representation Of Knowledge

Wines with geographical indication can be classified and represented by such features as designations of origin, producers, vintage years, alcoholic strength, and grape varieties; these features allow us to define wines in terms of a set of necessary and/or sufficient conditions. However, wines can also be identified by other characteristics, involving their look, smell, and taste; in this case, it is hard to define wines in terms of necessary and/or sufficient conditions, as wine concepts exhibit typicality effects. This is a setback for the design of computer science ontologies aiming to represent wine concepts, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. To solve this problem, we propose to adopt a hybrid approach in which ontology-oriented formalisms are combined with a geometric representation of knowledge based on conceptual spaces. As in conceptual spaces, concepts are identified in terms of a number of quality dimensions. In order to determine those relevant for wine representation, we use the terminology developed by the Italian Association of Sommeliers to describe wines. This will allow us to understand typicality effects about wines, determine prototypes and better exemplars, and measure the degree of similarity between different wines.

scholarly journals ABSTRACT STRUCTURE OF CONFIGURATION SYSTEM FOR PRODUCT DATA MANAGEMENT SYSTEM

Aviation ◽  
2008 ◽  
Vol 12 (4) ◽  
pp. 124-128 ◽  
Author(s):  
Linas Burneika
Keyword(s):  
Data Management ◽  
Product Data Management ◽  
Data Management System ◽  
Product Data ◽  
Technical Data ◽  
Different Types ◽  
Configuration System ◽  
Abstract Structure ◽  
Product Data Management System ◽  
Representation Of Knowledge

A product configurator is a system providing questions and sets of possible answers about products with sets of possible answers. This paper proposes a new idea for a configurator in which information about products are expressed as a structured net of interconnected classes of different types. Classes hold information about assemblies, product structural links, and logical constraints. Some classes have references to technical data on a product data management (PDM) system. Such a system allows flexible representation of knowledge about product configurations for production of aviation equipment. Santrauka Gaminio konfigūratorius yra programinė sistema, pateikianti klausimus apie produktą su galimais pasirinkimų variantais. Šiame darbe pasiūlyta nauja konfigūratoriaus idėja ir pateiktas konfigūracijų aprašo modelis. Šis modelis buvo kuriamas taip, kad juo būtų galima aprašyti realius, dažnai tobulinamus ir sudėtingos sandaros gaminius. Modelyje informacija apie gaminį pateikiama kaip tarpusavyje sujungtų įvairių klasių tinklas. Modelio klasėse saugoma informacija apie gaminio junginius, komponentų ryšius ir loginius apribojimus. Siūlomas konfigūracijų aprašo modelis leidžia lanksčiai perteikti inžinerines žinias apie įvairių gaminių, tarp jų ir aviacijos reikmėms skirtų gaminių, variantus.

Collaborative Engineering Based on Knowledge Sharing Agreements

1994 ◽  
Author(s):  
Gregory R. Olsen ◽  
Mark Cutkosky ◽  
Jay M. Tenenbaum ◽  
Thomas R. Gruber
Keyword(s):  
Knowledge Sharing ◽  
Information Sharing ◽  
Data Exchange ◽  
Formal Approach ◽  
Computational Framework ◽  
Engineering Knowledge ◽  
Exchange Information ◽  
Knowledge Intensive ◽  
Common Understanding ◽  
Representation Of Knowledge

Abstract The design of products by multi-disciplinary groups is a knowledge intensive activity. Collaborators must be able to exchange information and share some common understanding of the information’s content. The hope, however, that a centralized standards effort will lead to integrated tools spanning the needs of engineering collaborators is misplaced. Standards cannot satisfy the information sharing needs of collaborators, because these needs cannot be standardized. This paper discusses the design and use of a shared representation of knowledge (language and vocabulary) to facilitate communication among specialists and their tools. The paper advances the opinion that collaborators need the ability to establish and customize knowledge sharing agreements (i.e. mutually agreed upon terminology and definitions) that are usable by people and their machines. The paper describes a formal approach to representing engineering knowledge, describes its role in a computational framework that integrates a heterogeneous mix of software tools, and discusses its relationship to current and emerging data exchange standards. This work is supported by ARPA contract DAAA 15-91-C0104 as part of the SHADE project. (CDR TR# 19940912)

scholarly journals An Adversarial Attacks Resistance-based Approach to Emotion Recognition from Images using Facial Landmarks

2021 ◽  
Author(s):  
Harisu Abdullahi Shehu ◽  
William Browne ◽  
Hedwig Eisenbarth
Keyword(s):  
Emotion Recognition ◽  
High Performance ◽  
Input Image ◽  
Large Decrease ◽  
Facial Landmarks ◽  
The Past ◽  
Homogeneous Representation ◽  
Small Change ◽  
Deep Learning Model ◽  
Representation Of Knowledge

Emotion recognition has become an increasingly important area of research due to the increasing number of CCTV cameras in the past few years. Deep network-based methods have made impressive progress in performing emotion recognition-based tasks, achieving high performance on many datasets and their related competitions such as the ImageNet challenge. However, deep networks are vulnerable to adversarial attacks. Due to their homogeneous representation of knowledge across all images, a small change to the input image made by an adversary might result in a large decrease in the accuracy of the algorithm. By detecting heterogeneous facial landmarks using the machine learning library Dlib we hypothesize we can build robustness to adversarial attacks. The residual neural network (ResNet) model has been used as an example of a deep learning model. While the accuracy achieved by ResNet showed a decrease of up to 22%, our proposed approach has shown strong resistance to an attack and showed only a little (< 0.3%) or no decrease when the attack is launched on the data. Furthermore, the proposed approach has shown considerably less execution time compared to the ResNet model.

scholarly journals A survey on the process of knowledge representation of the small banana farmers (Musa spp.) in mangaratiba, rj

2021 ◽  
Vol 25 ◽  
pp. e7
Author(s):  
Emanuele Nunes de Lima Figueiredo Jorge ◽  
Sérgio Thode Filho ◽  
Cláudio Miceli de Farias
Keyword(s):  
Rio De Janeiro ◽  
Human Knowledge ◽  
Tropical Regions ◽  
Musa Spp ◽  
Soil Variables ◽  
The World ◽  
Long Time ◽  
Production Area ◽  
Domain Information ◽  
Representation Of Knowledge

The banana, the world's most widely produced and commercialized fruit, is grown in all tropical regions of the world, being strongly present in local businesses and subsistence crops serving as an important source of nutrients for the poorest populations. In the state of Rio de Janeiro it is commonly found in hillside and difficult access areas, where most other crops would not be able to settle and, because of this, is grown with inadequate management or insufficient, resulting in low productivity in the areas of Rio de Janeiro. The objective of the present work is to carry out a survey of smallholder information from the Vale do Rio Sahy Association in Mangaratiba, RJ, to enable the representation of knowledge in this domain. From the data collected in this research, it was realized that producers have been engaged in this activity for a long time. However, it was found that the knowledge used to production is extremely tacit, without systematization. The variety of banana species (Musa spp.) grown in the production area of the association's small farmers. The knowledge transfer process knowledge to the knowledge base of an expert system is called knowledge acquisition, where it involves extract all the knowledge from the source of the specialists to systematically represent in a coded form the domain information in an appropriate medium. It was observed, even if preliminarily, that this knowledge are not represented in a database for consultation. Thus, there is a need to define human expertise or producers capable of representing in a technological way data that can be conveniently accessed for Problem solving. In view of the evidence presented in the research, the use of representation of human knowledge (small local producers) to feed and train the system according to the domain presented. Thus, enabling the prototype to help understand climate and soil variables and collaborate in decision making.

Relational mentalizing after any representation

2021 ◽  
Vol 44 ◽  
Author(s):  
Eliane Deschrijver
Keyword(s):  
Knowledge Representation ◽  
Mental State ◽  
Nonhuman Primate ◽  
Social Conflict ◽  
Conflict Monitoring ◽  
Knowledge Representations ◽  
Representation Of Knowledge

Abstract Autistic, developmental, and nonhuman primate populations fail tasks that are thought to involve attributing beliefs, but not those thought to reflect the representation of knowledge. Instead of knowledge representations being more basic than belief representations, relational mentalizing may explain these observations: The tasks referred to as reflecting “belief” representation, but not the “knowledge” representation tasks, are social conflict designs. They involve mental conflict monitoring after another's mental state is represented – with effects that need to be accounted for.

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