Construction of quasi-binary relations in the semantic networks

2003 ◽  
Author(s):  
L.Yu. Zhilyakova
Keyword(s):  
Semantic Networks ◽  
Binary Relations

Theoretical Basics of NTA

2018 ◽  
pp. 97-124
Keyword(s):  
General Theory ◽  
Cartesian Product ◽  
Semantic Networks ◽  
Basic Structure ◽  
Relational Algebra ◽  
Binary Relations ◽  
Mathematical Structures ◽  
Theoretical Generalization

The chapter introduces theoretical features of n-tuple algebra developed by the authors as a theoretical generalization of structures and methods applied in intelligence systems. NTA supports formalization of a wide set of logical problems (abductive and modified conclusions, modeling of graphs, semantic networks, expert rules, etc.). This chapter contains main definitions and theorems of NTA. Unlike relational algebra and theory of binary relations, NTA uses Cartesian product of sets rather than sequences of elements (elementary n-tuples) as a basic structure and implements a general theory of n-ary relations. Novelty of our approach is that we developed some new mathematical structures allowing to implement many techniques of semantic and logical analyses; these methods have no analogies in conventional theories.

Only connections: A critique of semantic networks.

1984 ◽  
Vol 96 (2) ◽  
pp. 292-315 ◽  
Author(s):  
P. N. Johnson-Laird ◽  
D. J. Herrmann ◽  
R. Chaffin
Keyword(s):  
Semantic Networks

An Examination of False Memories Using Artificial Semantic Networks

2014 ◽  
Author(s):  
John Powell Taylor ◽  
Shanna'le Ashworth ◽  
Matthew Fischer ◽  
Kadie Skou ◽  
Almyra Perry
Keyword(s):  
False Memories ◽  
Semantic Networks

USING THESAURI AND SEMANTIC NETWORKS IN THE SYSTEM OF NATIONAL DATABASES OF ETHNIC MINORITIES AND ETHNIC POLICIES

2017 ◽  
Author(s):  
Nguyen Manh Hung ◽  
Be Trung Anh
Keyword(s):  
Critical Point ◽  
Ethnic Minorities ◽  
Semantic Networks ◽  
Relevant Information ◽  
Design And Development ◽  
State Management ◽  
Main Requirement ◽  
Important Means ◽  
National Databases ◽  
Adequate Data

The System of National Databases of Ethnic Minorities and Ethnic Policies (System) is recognized as one of most important means for governance and management in ethnic minority’s field of Vietnam State. The task of building this System now was put down in a direction of government and is going on first stage of design and development of database framework. One among main requirement for the System is that ability to provide fullest and adequate data and information to requests from users from various organizations of state management. As mentioned in the first draft of this design in the national-wide conference that recently hold in Hanoi (Aug-2017), one of the critical point of the design and development of databases of this system is to build “smart” searching engine based on semantic technology. It can retrieve those information on ethnic minorities and ethnic minority’s area that relevant together in term of providing users any relevant information based on only one unique query. This paper is aiming to introduce some techniques with illustrative examples that suitable for the idea of building this smart engine.

FACTOR ANALYSIS OF GEOGRAPHIC COORDINATES AT POINTS OF THE CHANNEL OF A SMALL RIVER ON SPACE IMAGES

2020 ◽  
Author(s):  
Peter Matveevich Mazurkin ◽  
Yana Oltgovna Georgieva
Keyword(s):  
Correlation Coefficient ◽  
Geographical Location ◽  
Small River ◽  
Binary Relations ◽  
Catchment Basin ◽  
Space Images ◽  
The North ◽  
Inverse Effect ◽  
Characteristic Points ◽  
Fractal Representation

The purpose of the article is the analysis of asymmetric wavelets in binary relations between three coordinates at 290 characteristic points from the source to the mouth of the small river Irovka. The hypsometric characteristic is the most important property of the relief. The Irovka River belongs to a low level, at the mouth it is 89 m high, and at the source it is 148 m above sea level. Modeling of binary relations with latitude, longitude, and height has shown that local latitude receives the greatest quantum certainty. In this case, all paired regularities received a correlation coefficient of more than 0.95. Such a high adequacy of wave patterns shows that geomorphology can go over to the wave multiple fractal representation of the relief. The Irovka River is characterized by a small anthropogenic impact, therefore, the relief over a length of 69 km has the natural character of the oscillatory adaptation of a small river to the surface of the Vyatka Uval from its eastern side. This allows us to proceed to the analysis of the four tributaries of the small river Irovka, as well as to model the relief of the entire catchment basin of 917 km2. The greatest adequacy with a correlation coefficient of 0.9976 was obtained by the influence of latitude on longitude, that is, the geographical location of the relief of the river channel with respect to the geomorphology of the Vyatka Uval. In second place with a correlation of 0.9967 was the influence of the height of the points of the channel of the small river on local longitude and it is also mainly determined by the relief of the Vyatka Uval. In third place was the effect of latitude on height with a correlation coefficient of 0.9859. And in last sixth place is the inverse effect of altitude on local latitude in the North-South direction.

scholarly journals Generative Adversarial Networks to Improve the Robustness of Visual Defect Segmentation by Semantic Networks in Manufacturing Components

2021 ◽  
Vol 11 (14) ◽  
pp. 6368
Author(s):  
Fátima A. Saiz ◽  
Garazi Alfaro ◽  
Iñigo Barandiaran ◽  
Manuel Graña
Keyword(s):  
Ad Hoc ◽  
Data Augmentation ◽  
Semantic Network ◽  
Semantic Networks ◽  
Stereo Image ◽  
Generative Adversarial Networks ◽  
Specific Class ◽  
Adversarial Networks ◽  
Augmentation Techniques ◽  
Image Acquisition System

This paper describes the application of Semantic Networks for the detection of defects in images of metallic manufactured components in a situation where the number of available samples of defects is small, which is rather common in real practical environments. In order to overcome this shortage of data, the common approach is to use conventional data augmentation techniques. We resort to Generative Adversarial Networks (GANs) that have shown the capability to generate highly convincing samples of a specific class as a result of a game between a discriminator and a generator module. Here, we apply the GANs to generate samples of images of metallic manufactured components with specific defects, in order to improve training of Semantic Networks (specifically DeepLabV3+ and Pyramid Attention Network (PAN) networks) carrying out the defect detection and segmentation. Our process carries out the generation of defect images using the StyleGAN2 with the DiffAugment method, followed by a conventional data augmentation over the entire enriched dataset, achieving a large balanced dataset that allows robust training of the Semantic Network. We demonstrate the approach on a private dataset generated for an industrial client, where images are captured by an ad-hoc photometric-stereo image acquisition system, and a public dataset, the Northeastern University surface defect database (NEU). The proposed approach achieves an improvement of 7% and 6% in an intersection over union (IoU) measure of detection performance on each dataset over the conventional data augmentation.

scholarly journals Finite representability of semigroups with demonic refinement

2021 ◽  
Vol 82 (2) ◽  
Author(s):  
Robin Hirsch ◽  
Jaš Šemrl
Keyword(s):  
Partial Order ◽  
Turing Machines ◽  
Binary Relations ◽  
Finite Representation ◽  
First Order ◽  
Finite Structures ◽  
Finite Base ◽  
Finite Set ◽  
Finite Representability ◽  
Representation Class

AbstractThe motivation for using demonic calculus for binary relations stems from the behaviour of demonic turing machines, when modelled relationally. Relational composition (; ) models sequential runs of two programs and demonic refinement ($$\sqsubseteq $$ ⊑ ) arises from the partial order given by modeling demonic choice ($$\sqcup $$ ⊔ ) of programs (see below for the formal relational definitions). We prove that the class $$R(\sqsubseteq , ;)$$ R ( ⊑ , ; ) of abstract $$(\le , \circ )$$ ( ≤ , ∘ ) structures isomorphic to a set of binary relations ordered by demonic refinement with composition cannot be axiomatised by any finite set of first-order $$(\le , \circ )$$ ( ≤ , ∘ ) formulas. We provide a fairly simple, infinite, recursive axiomatisation that defines $$R(\sqsubseteq , ;)$$ R ( ⊑ , ; ) . We prove that a finite representable $$(\le , \circ )$$ ( ≤ , ∘ ) structure has a representation over a finite base. This appears to be the first example of a signature for binary relations with composition where the representation class is non-finitely axiomatisable, but where the finite representation property holds for finite structures.

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