IMPLEMENTATION OF THE ADVANCED LEARNING IN THE PROCESS OF FUNDAMENTAL MATHEMATICAL TRAINING OF BACHELORS IN THE FIELD OF ELECTRONICS AND TELECOMMUNICATION

The article substantiates the expediency of the implementation of the advanced learning in the process of fundamental mathematical training of bachelors in the field of electronics and telecommunications. At the moment, the field requires mandatory (deep) knowledge of the main classical sections of mathematics, it is also important to acquaint students in higher mathematics with elements of modern mathematical theories, concepts that allow learners to better understand special courses in mathematics and relevant special disciplines. materials of mathematics, which are used in the modern mathematical models of technical developments. The aim of the article is to reveal the approaches to the concept of the advanced learning in the process of fundamental mathematical training of future bachelors in the field of electronics and telecommunications.The main methods that were implemented in the study of the problem of advanced learning were the analysis and synthesis of the scientific sources on the selected problem, observation, implementation of projects and evaluation of their results. It is offered (from the first semester) to introduce generalized concepts (norm, operator, etc.) in time, to acquaint with ideas of variational calculus, functional analysis, mathematical methods of research of linear equations with variable coefficients, theory of stochastic approximation, mathematical modelling. Then the future specialist will be able to comprehend the objects, which have been already developed by mathematicians but have not been used yet. Thus, a difficult topic or concept can be considered in advance in some connection with the currently studied material. For example, during the study of a function and the construction of its graph, along with the asymptote, students can be introduced to the approximation of the function, the concepts of interpolation and approximation. It is expedient to acquaint students with these problems more deeply during performance of independent tasks (consultations, the abstract, the report at conference, etc.).

An Efficient Approach for Incremental Mining Fuzzy Frequent Itemsets with FP-Tree

Keeping the generated fuzzy frequent itemsets up-to-date and discovering the new fuzzy frequent itemsets are challenging problems in dynamic databases. In this paper, the classical H-struct structure is extended to mining fuzzy frequent itemsets. The extended H-mine algorithm can use any t-norm operator to calculate the support of fuzzy itemset. The FP-tree-based structure called the Initial-FP-tree and the New-FP-tree are built to maintain the fuzzy frequent itemsets in the original database and the new inserted transactions respectively. The strategy of incremental mining of fuzzy frequent itemsets is achieved by breath-first-traversing the Initial-FP-tree and the New-FP-tree. All of the fuzzy frequent itemsets in the updated database can be obtained by traversing the Initial-FP-tree. The experiments on real datasets show that the proposed approach runs faster than the batch extended H-mine algorithm. Comparing with the existing algorithm for incremental mining fuzzy frequent itemsets, the proposed approach is superior in terms of the execution time. The memory cost of the proposed approach is lower than that of the existing algorithm when the minimum support threshold is low.

SOFT AGGREGATION IN FLEXIBLE DATABASES QUERYING BASED ON THE VECTOR p-NORM

In this paper a model of soft aggregation of preferences in flexible database querying is proposed, based on the vector p-norm operator. The model allows aggregating conditions with distinct importance by modeling both veto and favour semantics of the conditions. We outline how the semantics of the compound query varies for increasing values of the parameter p, when the selection conditions are ANDed and ORed.