SIMAP: Intelligent System for Predictive Maintenance

2006 ◽  
Vol 57 (6) ◽  
pp. 552-568 ◽  
Author(s):  
Mari Cruz Garcia ◽  
Miguel A. Sanz-Bobi ◽  
Javier del Pico
Keyword(s):  
Intelligent System ◽  
Predictive Maintenance

Intelligent system of English composition scoring model based on improved machine learning algorithm

2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang
Keyword(s):  
Machine Learning ◽  
Evaluation System ◽  
Intelligent System ◽  
Learning Algorithm ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Assessment System ◽  
English Composition ◽  
Region Extraction ◽  
Constraint Model

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

2019 ◽  
pp. 21-30
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Interaction Analysis ◽  
Educational Data Mining ◽  
Main Task ◽  
Intellectual System ◽  
Will Force ◽  
To Come ◽  
Artificial Intelligence Systems

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

Improving Production System Performance Using Overall Equipment Effectiveness

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Lance Clarence ◽  
Wan Muhammad Noor Sarbani Mat Daud
Keyword(s):  
Production System ◽  
System Performance ◽  
Intelligent System ◽  
Global Market ◽  
Equipment Failure ◽  
Intuitive Knowledge ◽  
Analysis Tools ◽  
New Process ◽  
Knowledge Delivery

In the competition among organization on the global market, no organization will tolerate losses. Overall Equipment Effectiveness (OEE) overall is a new process in which the efficiency of a system is calculated and complicated manufacturing issues are truly simplified to simple and intuitive knowledge delivery. It thinks about the exceptionally important measures of productivity. An endeavour has been done to measure and analyse existing Overall Equipment Effectiveness (OEE) at company Kirino in hope to reduce unplanned downtime losses on equipment failure and tooling damage to maximize the productivity. The methods used to analyse these various causes were analysis tools and Intelligence Systems. After knowing the causes of various activities that leads to high rates of defects, then recommendations for improvements that could be used by company Kirino were ready to be made using intelligent system as a medium of solution

The Convergence between Predictive Maintenance and Augmented Reality to Aid Renewable Energy Equipment Availability

2014 ◽  
Vol 2 (5) ◽  
pp. 152
Author(s):  
José Manuel Torres Farinha ◽  
Inácio Adelino Fonseca ◽  
Rúben Silva Oliveira ◽  
Fernando Maciel Barbosa
Keyword(s):  
Renewable Energy ◽  
Augmented Reality ◽  
Predictive Maintenance ◽  
Equipment Availability ◽  
Energy Equipment
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