Automatic Correction of Programming Faults using Semantic Networks

2012 ◽  
Author(s):  
Hager A. Hussein ◽  
Khaled M. Mahar ◽  
Mahmoud F. Hussein ◽  
Osama M. Badawy
Keyword(s):  
Semantic Networks ◽  
Automatic Correction

Automatic Correction of Programming Faults using Semantic Networks

2011 ◽  
Author(s):  
Hager A. Hussein ◽  
Khaled M. Mahar ◽  
Mahmoud F. Hussein ◽  
Osama M. Badawy
Keyword(s):  
Semantic Networks ◽  
Automatic Correction

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

Automatic Correction of Spelling Errors

Vestnik MEI ◽  
2019 ◽  
Vol 5 ◽  
pp. 117-128
Author(s):  
Oleg V. Barten′ev ◽  
◽  
Dmitriy A. Titov ◽  
Keyword(s):  
Automatic Correction ◽  
Spelling Errors

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.

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 Professional identity and experience of undergraduate students: an analysis of semantic networks

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Luara Carvalho ◽  
Elisa Maria Barbosa de Amorim-Ribeiro ◽  
Marcelo do Vale Cunha ◽  
Luciana Mourão
Keyword(s):  
Professional Identity ◽  
Identity Construction ◽  
Undergraduate Students ◽  
Semantic Networks ◽  
Work Experiences ◽  
Undergraduate Studies ◽  
Course Work

AbstractWork experiences during undergraduate studies can be remarkable in the journey of undergraduate students. The objective of this study was to assess, by analyzing semantic networks, the role of work experiences in the meanings those individuals attribute to professional identity. The sample consisted of 2291 students (60% women) divided into three groups: do not work, work in a field related to their course, work in a field not related to their course. The semantic networks of these groups were composed of words uttered from the professional identity prime. We chose to work with the critical network, obtained from the analysis of the incidence-fidelity indexes of the word pairs. The results evidence that work experiences are related to how undergraduate students attribute meaning to professional identity, in such a way that three different networks were formed for these groups. The network of those who work outside their field was the only one that integrated words with negative content, while the semantic networks of those who do not work and those who work in their field, despite containing words that do not always coincide, present a similar macrostructure. We conclude that work experiences play an important role in the meanings that undergraduate students attribute to professional identity. The study innovates by revealing elements of professional-identity construction, besides allowing for reflections on the effects of work experiences during the college period.

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