scholarly journals Consistency Checking in Complex Object Database Schemata with Integrity Constraints

1995 ◽  
Author(s):  
D. Beneventano ◽  
S Bergamaschi ◽  
S Lodi ◽  
C. Sartori
Keyword(s):  
Integrity Constraints ◽  
Complex Object ◽  
Consistency Checking ◽  
Object Database ◽  
Database Schemata

Consistency checking in complex object database schemata with integrity constraints

1998 ◽  
Vol 10 (4) ◽  
pp. 576-598 ◽  
Author(s):  
D. Beneventano ◽  
S. Bergamaschi ◽  
S. Lodi ◽  
C. Sartori
Keyword(s):  
Integrity Constraints ◽  
Complex Object ◽  
Consistency Checking ◽  
Object Database ◽  
Database Schemata

scholarly journals Consistency checking and querying in probabilistic databases under integrity constraints

2014 ◽  
Vol 80 (7) ◽  
pp. 1448-1489 ◽  
Author(s):  
Sergio Flesca ◽  
Filippo Furfaro ◽  
Francesco Parisi
Keyword(s):  
Integrity Constraints ◽  
Probabilistic Databases ◽  
Consistency Checking

A persistent complex object database language

1989 ◽  
Vol 3 (4) ◽  
pp. 225-243 ◽  
Author(s):  
Setrag Khoshafian
Keyword(s):  
Complex Object ◽  
Object Database ◽  
Database Language

MARKOV MATHEMATICAL MODEL OF DYNAMIC ADAPTIVE TESTING OF AN ACTIVE AGENT

2018 ◽  
pp. 29-35
Author(s):  
N. V. Brovka ◽  
P. P. Dyachuk ◽  
M. V. Noskov ◽  
I. P. Peregudova
Keyword(s):  
Mathematical Model ◽  
Finite State Machine ◽  
Active Agent ◽  
Adaptive Testing ◽  
State Machine ◽  
Learning Activities ◽  
Independent Learning ◽  
Complex Object ◽  
Total Reward ◽  
Finite State

The problem and the goal.The urgency of the problem of mathematical description of dynamic adaptive testing is due to the need to diagnose the cognitive abilities of students for independent learning activities. The goal of the article is to develop a Markov mathematical model of the interaction of an active agent (AA) with the Liquidator state machine, canceling incorrect actions, which will allow mathematically describe dynamic adaptive testing with an estimated feedback.The research methodologyconsists of an analysis of the results of research by domestic and foreign scientists on dynamic adaptive testing in education, namely: an activity approach that implements AA developmental problem-solving training; organizational and technological approach to managing the actions of AA in terms of evaluative feedback; Markow’s theory of cement and reinforcement learning.Results.On the basis of the theory of Markov processes, a Markov mathematical model of the interaction of an active agent with a finite state machine, canceling incorrect actions, was developed. This allows you to develop a model for diagnosing the procedural characteristics of students ‘learning activities, including: building axiograms of total reward for students’ actions; probability distribution of states of the solution of the problem of identifying elements of the structure of a complex object calculate the number of AA actions required to achieve the target state depending on the number of elements that need to be identified; construct a scatter plot of active agents by target states in space (R, k), where R is the total reward AA, k is the number of actions performed.Conclusion.Markov’s mathematical model of the interaction of an active agent with a finite state machine, canceling wrong actions allows you to design dynamic adaptive tests and diagnostics of changes in the procedural characteristics of educational activities. The results and conclusions allow to formulate the principles of dynamic adaptive testing based on the estimated feedback.

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