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ΠΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½Π°Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ° Π°Π½Π°Π»ΠΈΠ·Π° Π½Π°Π²ΡΠΊΠΎΠ² ΠΈ ΡΠΌΠ΅Π½ΠΈΠΉ ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π²ΡΡΡΠ΅Π³ΠΎ ΡΡΠ΅Π±Π½ΠΎΠ³ΠΎ Π·Π°Π²Π΅Π΄Π΅Π½ΠΈΡ
In the below article, the application of the fuzzy logical conclusion method is considered as decision-maker in the process of analyzing the students skills and abilities based on the requirements of potential employers, in order to reduce the time of the first interview for potential candidates on a vacant position. When analyzing the results of the assessment of the competence of university students, a certain degree of fuzziness arises. In modern practice, fuzzy logic is used in many different assessment methods, including questioning, interviewing, testing, descriptive method, classification method, pairwise comparison, rating method, business games competence models, and the like. Each of the methods has its advantages and disadvantages, but they are effective only as part of a unified personnel management system. As a method for implementing a systematic approach to the assessment of the contingent of students, it is proposed to use fuzzy logic, a mathematical apparatus that allows you to build a model of an object based on fuzzy judgments. The use of fuzzy logic, the mathematical apparatus of which allows you to build a model of the object, based on fuzzy reasoning and rules. The most important condition for creating such a model is to translate the fuzzy, qualitative assessments used by man into the language of mathematics, which will be understood by the computer. The most used are fuzzy inferences using the Mamdani and Sugeno methods. In a fuzzy inference of the Mamdani type, the value of the output variable is given by fuzzy terms, in the conclusion of the Sugeno type, as a linear combination of the input variables. Research in the field of application of fuzzy logic in socio-economic systems suggests that it can be used to assess the competencies of university students.Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Π° Π½Π΅ΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΡΠ²ΠΎΠ΄Π° Π΄Π»Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ ΠΏΡΠΈΠ½ΡΡΠΈΡ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π² Π·Π°Π΄Π°ΡΠ°Ρ
Π°Π½Π°Π»ΠΈΠ·Π° Π½Π°Π²ΡΠΊΠΎΠ² ΠΈ ΡΠΌΠ΅Π½ΠΈΠΉ ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΈΡΡ
ΠΎΠ΄Ρ ΠΈΠ· ΡΡΠ΅Π±ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Π΅ΠΉ, Ρ ΡΠ΅Π»ΡΡ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΡ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΊΠ°ΡΠ°ΡΠ΅Π»ΡΠ½ΠΎ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΠΎΠ² Π½Π° Π²Π°ΠΊΠ°Π½ΡΠ½ΡΡ Π΄ΠΎΠ»ΠΆΠ½ΠΎΡΡΡ. ΠΡΠΈ Π°Π½Π°Π»ΠΈΠ·Π΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΎΡΠ΅Π½ΠΊΠΈ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΠ½ΠΎΡΡΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π²ΡΠ·ΠΎΠ² Π²ΠΎΠ·Π½ΠΈΠΊΠ°Π΅Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½Π°Ρ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π½Π΅ΡΠ΅ΡΠΊΠΎΡΡΠΈ. Π ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅ Π½Π΅ΡΠ΅ΡΠΊΠ°Ρ Π»ΠΎΠ³ΠΈΠΊΠ° ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΡΡΡ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΈΡ
ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄Π°Ρ
ΠΎΡΠ΅Π½ΠΊΠΈ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π°Π½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅, ΠΈΠ½ΡΠ΅ΡΠ²ΡΡ, ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅, ΠΎΠΏΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΡΠΉ ΠΌΠ΅ΡΠΎΠ΄, ΠΌΠ΅ΡΠΎΠ΄ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ, ΠΏΠ°ΡΠ½ΠΎΠ΅ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠ΅, ΡΠ΅ΠΉΡΠΈΠ½Π³ΠΎΠ²ΡΠΉ ΠΌΠ΅ΡΠΎΠ΄, Π΄Π΅Π»ΠΎΠ²ΡΠ΅ ΠΈΠ³ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΠ½ΠΎΡΡΠΈ ΠΈ ΡΠΎΠΌΡ ΠΏΠΎΠ΄ΠΎΠ±Π½ΠΎΠ΅. ΠΠ°ΠΆΠ΄ΡΠΉ ΠΈΠ· ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΈΠΌΠ΅Π΅Ρ ΡΠ²ΠΎΠΈ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π° ΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΈ, Π½ΠΎ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½Ρ ΠΎΠ½ΠΈ ΡΠΎΠ»ΡΠΊΠΎ Π² ΡΠΎΡΡΠ°Π²Π΅ Π΅Π΄ΠΈΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΠΎΠΌ. ΠΠ°ΠΊ ΠΌΠ΅ΡΠΎΠ΄ Π΄Π»Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΊ ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ Π½Π΅ΡΠ΅ΡΠΊΡΡ Π»ΠΎΠ³ΠΈΠΊΡ, ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°ΠΏΠΏΠ°ΡΠ°Ρ, ΠΊΠΎΡΠΎΡΡΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΎΠ±ΡΠ΅ΠΊΡΠ°, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΡ Π½Π° Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΡΡΠΆΠ΄Π΅Π½ΠΈΡΡ
. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠΈ, ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°ΠΏΠΏΠ°ΡΠ°Ρ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΎΠ±ΡΠ΅ΠΊΡΠ°, ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡΡ Π½Π° Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΡΠ°ΡΡΡΠΆΠ΄Π΅Π½ΠΈΡΡ
ΠΈ ΠΏΡΠ°Π²ΠΈΠ»Π°Ρ
. ΠΠ°ΠΆΠ½Π΅ΠΉΡΠ΅Π΅ ΡΡΠ»ΠΎΠ²ΠΈΠ΅ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΠ°ΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΡΠΎΠΌ, ΡΡΠΎΠ±Ρ ΠΏΠ΅ΡΠ΅Π²Π΅ΡΡΠΈ Π½Π΅ΡΠ΅ΡΠΊΠΈΠ΅, ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅ ΠΎΡΠ΅Π½ΠΊΠΈ, ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΠ΅ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠΎΠΌ, Π½Π° ΡΠ·ΡΠΊ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ Π±ΡΠ΄Π΅Ρ ΠΏΠΎΠ½ΡΡΠ½Π° Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΌΠ°ΡΠΈΠ½Π΅. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΠΌΠΈ ΡΠ²Π»ΡΡΡΡΡ Π½Π΅ΡΠ΅ΡΠΊΠΈΠ΅ Π²ΡΠ²ΠΎΠ΄Ρ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠΏΠΎΡΠΎΠ±ΠΎΠ² ΠΠ°ΠΌΠ΄Π°Π½ΠΈ ΠΈ Π‘ΡΠ³Π΅Π½ΠΎ. Π Π½Π΅ΡΠ΅ΡΠΊΠΎΠΌ Π²ΡΠ²ΠΎΠ΄Π΅ ΡΠΈΠΏΠ° ΠΠ°ΠΌΠ΄Π°Π½ΠΈ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ Π²ΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π·Π°Π΄Π°ΡΡΡΡ Π½Π΅ΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠ΅ΡΠΌΠ°ΠΌΠΈ, Π² Π·Π°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠΈ ΡΠΈΠΏΠ° Π‘ΡΠ³Π΅Π½ΠΎ β ΠΊΠ°ΠΊ Π»ΠΈΠ½Π΅ΠΉΠ½Π°Ρ ΠΊΠΎΠΌΠ±ΠΈΠ½Π°ΡΠΈΡ Π²Ρ
ΠΎΠ΄Π½ΡΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠΈ Π² ΡΠΎΡΠΈΠΎΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ Π³ΠΎΠ²ΠΎΡΠΈΡΡ ΠΎ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ Π΅Π΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΠΈΠΉ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π²ΡΠ·ΠΎΠ²
Micropropagação e cultivo in vitro de gramΓneas forrageiras tropicais.
bitstream/item/32907/1/Doc-142.pd
An approach to measure similarity of business process models
At higher levels of BPM (Business Process Management) maturity, organizations tend to accumulate considerable amounts of business process models [1]. Thus, business process model repositories may contain hundreds or even thousands models, represented using various modeling notations [2]. Since business process modeling technique is used by organizations to describe knowledge about their activities, the problem of store, share, and reuse of organizational knowledge, represented using business process models, becomes relevant. In this paper a similarity measure, used to retrieve business process models from a repository in order to their further reuse in a business process continuous improvement cycle according to BPM concept, is proposed. The problem of similar business process models retrieving has been earlier considered in studies [1, 3, 4], which propose several measures, based on label similarity, structural similarity, behavioral similarity etc
ΠΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ Π±Π°ΡΠ΅Π½Π½Ρ ΡΠ° Π½Π΅ΡΡΡΠΊΠΎΡ Π»ΠΎΠ³ΡΠΊΠΈ Π΄Π»Ρ ΠΎΡΡΠ½ΠΊΠΈ ΡΠΊΠΎΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ²
In this paper we propose a method for quality assessment of business process models using computer vision and fuzzy logic. OpenCV library usage as well as bypassing of its drawbacks of template matching is considered. Membership functions of metrics of the business process model quality are outlined. Obtained results and future research are discussed.Π Π΄Π°Π½ΡΠΉ ΡΠΎΠ±ΠΎΡΡ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΡΡΡΡ ΠΌΠ΅ΡΠΎΠ΄ ΠΎΡΡΠ½ΠΊΠΈ ΡΠΊΠΎΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΊΠΎΠΌΠΏ'ΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ Π±Π°ΡΠ΅Π½Π½Ρ ΡΠ° Π½Π΅ΡΡΡΠΊΠΎΡ Π»ΠΎΠ³ΡΠΊΠΈ. Π ΠΎΠ·Π³Π»ΡΠ½ΡΡΠΎ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠΈ OpenCV ΡΠ° ΠΎΠ±Ρ
ΡΠ΄ ΡΡ Π½Π΅Π΄ΠΎΠ»ΡΠΊΡΠ² ΡΠΎΠ΄ΠΎ ΠΏΠΎΡΡΠΊΡ Π·Π° ΡΠ°Π±Π»ΠΎΠ½ΠΎΠΌ. ΠΠ°Π²Π΅Π΄Π΅Π½ΠΎ ΡΡΠ½ΠΊΡΡΡ Π½Π°Π»Π΅ΠΆΠ½ΠΎΡΡΡ ΠΌΠ΅ΡΡΠΈΠΊ ΡΠΊΠΎΡΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ². ΠΠΏΠΈΡΠ°Π½ΠΎ ΠΎΡΡΠΈΠΌΠ°Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈ ΡΠ° Π½Π°ΠΏΡΡΠΌΠΊΠΈ ΠΏΠΎΠ΄Π°Π»ΡΡΠΈΡ
Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Ρ
De Montessus de Ballore theorem for Pade approximation.
A research report submitted to the Faculty of Science, University of the Witwatersrand,
Johannesburg, in partial fulfilment of the degree of Master of ScienceThe importance of Pade approximation has been increasingly recognized in '
recent years. The first convergence result of Pade approximants valid for general
meromorphic functions was obtained by de Montessus de Ballore in 1902. He
proved that when a function f has precisely n poles in I z 1< R, then the (n+ 1)th
column in thePade table of f converges to f in I z J< R. (Abbreviation abstract)Andrew Chakane 201
Business process model optimization using the conjugate gradient method
This paper describes a model and a procedure of business process model optimization using the nonlinear conjugate gradient method. The research is based on business process modeling rules for BPMN (Business Process Model and Notation) as the de-facto standard for business process diagrams. Essential errors of business process modeling are outlined, as well as the metric used to define these shortcomings is denoted. Obtained results of business process model optimization are demonstrated
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