Parameters and Structure of Neural Network Databases for Assessment of Learning Outcomes - Pages 1638-1648

Eugeny Smirnov, Svetlana Dvoryatkina and Sergey Shcherbatykh

DOI: https://doi.org/10.6000/1929-4409.2020.09.188

Published: 14 December 2020

Abstract: The purpose of this study is to determine the methodology, develop a theory of construction, put into practice algorithmization and implement the functionality of a hybrid intelligent system for assessment of educational outcomes of trainees on the basis of the identified keyword parameters and structure of the artificial neural network using expert systems and fuzzy simulation; to develop a methodology for the construction of structural-logic, hierarchical, functional and fractal schemes for structuring databases of the didactic field of learning elements; to determine the content, structure of parameters and database components, selection criteria and the content of complexes of educational standards. The methodology of introducing intelligent systems into mathematical education is on the basis of the Hegelian triad: thesis (implementation of the coherence principle) – antithesis (implementation of principles of the fractality and historiogenesis) – synthesis (implementation of the principles of self-organization and reflection of the complex system inversion integrity). Requirements for the organization and construction of the artificial neural network for assessment of personal achievements on the basis of fuzzy simulation have been developed. In the direction of using elements of fractal geometry, the technological structures of clusters that constitute the basis of generalized structures have been developed. In particular, it is revealed that the didactic field of learning elements is equipped with a system of multi-level hierarchical databases of exercises, motivational-applied, research, practice-oriented tasks using expert systems and integration of mathematical, information, natural-science and humanities knowledge and procedures.

Keywords: Classification of learning outcomes, neural network, evaluation.

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A Miscellaneous Hindrances to an Effective Response to Cable Theft in Durban Railway Stations, South Africa - Pages 1649-1659

Liso Nobanda, Vuyelwa Kemiso Maweni, Witness Maluleke and Ephraim Kevin Sibanyoni

DOI: https://doi.org/10.6000/1929-4409.2020.09.189

Published: 14 December 2020

Abstract: This study focuses on notable miscellaneous hindrances to an effective response to cable theft in Durban railway stations of South Africa. From a qualitative standpoint; data was collected from Eight (8) purposively selected individuals to solicit their respective perceptions and experiences on this subject. This involved the Passenger Rail Agency of South Africa (PRASA) ‘Security Personnels – Cable Theft Investigators and Cable Theft Railway Patrollers, all involved in combating cable theft in Durban railway stations. Inductive Thematic Analysis was used for data analysis. This study found that scrap metal dealers are the major key contributors to cable theft in the Durban railway stations; and also the value of copper cable on the market promotes the exponential rise of cable theft. It was also established that, there was no proper protection of the rail infrastructure, and cable thieves get lighter sentences. It was further stablished that cable theft is perpetuated by the shortage of indispensable resources and workforce or police visibility in the stations. For the recommendations: More attention must be paid to scrap metal dealers by offering strict rules on the issuing of trading licenses. Moreover, severe stiff sentences should be handed to pontetial offenders and better working relations should be established, with more resources geared to the PRASA security department.

Keywords: Cable Theft, Durban railway stations, Effective response(s), Miscellaneous hindrances, South Africa.

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