4 research outputs found

    ΠŸΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ гСнСтичСского Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° для нахоТдСния Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ расстояния ΠΌΠ΅ΠΆΠ΄Ρƒ модСлями процСссов

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    Finding graph-edit distance (graph similarity) is an important task in many computer science areas, such as image analysis, machine learning, chemicalinformatics. Recently, with the development of process mining techniques, it became important to adapt and apply existing graph analysis methods to examine process models (annotated graphs) discovered from event data. In particular, finding graph-edit distance techniques can be used to reveal patterns (subprocesses), compare discovered process models. As it was shown experimentally and theoretically justified, exact methods for finding graph-edit distances between discovered process models (and graphs in general) are computationally expensive and can be applied to small models only. In this paper, we present and assess accuracy and performance characteristics of an inexact genetic algorithm applied to find distances between process models discovered from event logs. In particular, we find distances between BPMN (Business Process Model and Notation) models discovered from event logs by using different process discovery algorithms. We show that the genetic algorithm allows us to dramatically reduce the time of comparison and produces results which are close to the optimal solutions (minimal graph edit distances calculated by the exact search algorithm).Поиск Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ расстояния ΠΌΠ΅ΠΆΠ΄Ρƒ Π³Ρ€Π°Ρ„ΠΎΠ²Ρ‹ΠΌΠΈ модСлями (ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ схоТСсти Π³Ρ€Π°Ρ„ΠΎΠ²Ρ‹Ρ… ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ) являСтся Π²Π°ΠΆΠ½ΠΎΠΉ Π·Π°Π΄Π°Ρ‡Π΅ΠΉ Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… областях ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½Ρ‹Ρ… Π½Π°ΡƒΠΊ, Ρ‚Π°ΠΊΠΈΡ… ΠΊΠ°ΠΊ Π°Π½Π°Π»ΠΈΠ· ΠΈΠ·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠΉ, машинноС ΠΎΠ±ΡƒΡ‡Π΅Π½ΠΈΠ΅, химичСская ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠΊΠ°. Π’ послСднСС врСмя, Π² связи с Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ΠΌ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² извлСчСния ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° процСссов, появилась Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ Π² Π°Π΄Π°ΠΏΡ‚Π°Ρ†ΠΈΠΈ ΡΡƒΡ‰Π΅ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΡ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² сравнСния Π³Ρ€Π°Ρ„ΠΎΠ²Ρ‹Ρ… ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ для Π°Π½Π°Π»ΠΈΠ·Π° ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ процСссов (Π°Π½Π½ΠΎΡ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… Π³Ρ€Π°Ρ„ΠΎΠ²), ΠΈΠ·Π²Π»Π΅ΠΊΠ°Π΅ΠΌΡ‹Ρ… ΠΈΠ· Π»ΠΎΠ³ΠΎΠ² событий ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… систСм. ΠœΠ΅Ρ‚ΠΎΠ΄Ρ‹ нахоТдСния минимального Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ расстояния ΠΌΠ΅ΠΆΠ΄Ρƒ Π³Ρ€Π°Ρ„Π°ΠΌΠΈ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ для обнаруТСния шаблонов (подпроцСссов), Π° Ρ‚Π°ΠΊΠΆΠ΅ для сравнСния ΠΈΠ·Π²Π»Π΅ΠΊΠ°Π΅ΠΌΡ‹Ρ… ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ процСссов. Как Π±Ρ‹Π»ΠΎ ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΎ ΠΈ тСорСтичСски обосновано, Ρ‚ΠΎΡ‡Π½Ρ‹Π΅ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ нахоТдСния минимального Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ расстояния ΠΌΠ΅ΠΆΠ΄Ρƒ ΠΈΠ·Π²Π»Π΅ΠΊΠ°Π΅ΠΌΡ‹ΠΌΠΈ модСлями процСссов (ΠΈ Π³Ρ€Π°Ρ„Π°ΠΌΠΈ Π² ΠΎΠ±Ρ‰Π΅ΠΌ случаС) ΠΈΠΌΠ΅ΡŽΡ‚ Π±ΠΎΠ»ΡŒΡˆΡƒΡŽ Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΡƒΡŽ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ ΠΈ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½Ρ‹ лишь ΠΊ нСбольшим модСлям процСссов. Π’ этой ΡΡ‚Π°Ρ‚ΡŒΠ΅ ΠΌΡ‹ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π΅ΠΌ Ρ‚ΠΎΡ‡Π½ΠΎΡΡ‚ΡŒ ΠΈ Π²Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Π΅ характСристики гСнСтичСского Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°, примСняСмого для нахоТдСния расстояний ΠΌΠ΅ΠΆΠ΄Ρƒ модСлями процСссов, ΠΈΠ·Π²Π»Π΅ΠΊΠ°Π΅ΠΌΡ‹Ρ… ΠΈΠ· Π»ΠΎΠ³ΠΎΠ² событий. Π’ частности ΠΌΡ‹ Π½Π°Ρ…ΠΎΠ΄ΠΈΠΌ расстояния ΠΌΠ΅ΠΆΠ΄Ρƒ BPMN (Business Process Model and Notation) модСлями, ΠΈΠ·Π²Π»Π΅ΠΊΠ°Π΅ΠΌΡ‹ΠΌΠΈ ΠΈΠ· Π»ΠΎΠ³ΠΎΠ² событий с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠΎΠ² синтСза. Π’ этой Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ, Ρ‡Ρ‚ΠΎ прСдставлСнный гСнСтичСский Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ позволяСт Π² Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΉ стСпСни ΡƒΠΌΠ΅Π½ΡŒΡˆΠΈΡ‚ΡŒ врСмя вычислСний, ΠΏΡ€ΠΈ этом показывая Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹, Π±Π»ΠΈΠ·ΠΊΠΈΠ΅ ΠΊ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹ΠΌ (ΠΌΠΈΠ½ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹ΠΌ Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΎΠ½Π½Ρ‹ΠΌ расстояниям)

    Study of the Kinetics of Cadmium Cementation in the Presence of a Flocculant

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    ВосстановлСниС ΠΈΠΎΠ½ΠΎΠ² кадмия ΠΈΠ· Π²ΠΎΠ΄Π½Ρ‹Ρ… растворов ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ ΠΏΠΎΡ€ΠΎΡˆΠΊΠΎΠΌ Ρ†ΠΈΠ½ΠΊΠ°, ΠΊΡ€ΡƒΠΏΠ½ΠΎΡΡ‚ΡŒΡŽ ΠΎΡ‚ 63 Π΄ΠΎ 200 ΠΌΠΊΠΌ. Π’ рядС ΠΎΠΏΡ‹Ρ‚ΠΎΠ² провСряли влияниС Π½Π° процСсс Ρ†Π΅ΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΠΈ кадмия ΠΊΠ°Ρ‚ΠΈΠΎΠ½ΠΎΠ°ΠΊΡ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ флокулянта Besfloc K6645. ΠŸΡ€ΠΎΡ†Π΅ΡΡ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π² области Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ ΠΎΡ‚ 30 Π΄ΠΎ 50 ΠΎΠ‘ ΠΏΡ€ΠΈ Π½Π΅ΠΏΡ€Π΅Ρ€Ρ‹Π²Π½ΠΎΠΌ ΠΏΠ΅Ρ€Π΅ΠΌΠ΅ΡˆΠΈΠ²Π°Π½ΠΈΠΈ со ΡΠΊΠΎΡ€ΠΎΡΡ‚ΡŒΡŽ 200 ΠΎΠ±/ΠΌΠΈΠ½ Π²Π΅Ρ€Ρ…Π½Π΅ΠΏΡ€ΠΈΠ²ΠΎΠ΄Π½ΠΎΠΉ мСшалкой. ΠšΠΈΠ½Π΅Ρ‚ΠΈΡ‡Π΅ΡΠΊΠΈΠ΅ ΠΊΡ€ΠΈΠ²Ρ‹Π΅ построили с использованиСм ΠΊΠ°Π΄ΠΌΠΈΠΉ-сСлСктивного элСктрода. Показано, Ρ‡Ρ‚ΠΎ ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΠ΅ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Ρ‹ протСкания Ρ€Π΅Π°ΠΊΡ†ΠΈΠΈ ΠΏΠΎΠ»ΠΎΠΆΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ влияСт Π½Π° Ρ†Π΅ΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΡŽ. Π’Π²Π΅Π΄Π΅Π½ΠΈΠ΅ Π² элСктролит флокулянта Π² количСствС 70 ΠΌΠ³/Π» сниТало ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒ Ρ†Π΅ΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΠΈ кадмия. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ Ρ€Π°ΡΡΡ‡ΠΈΡ‚Π°Ρ‚ΡŒ каТущиСся энСргии Π°ΠΊΡ‚ΠΈΠ²Π°Ρ†ΠΈΠΈ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ составили ΠΏΡ€ΠΈ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ процСсса Π±Π΅Π· Π΄ΠΎΠ±Π°Π²ΠΊΠΈ флокулянта ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²ΠΎΡ‡Π½ΠΎ 46, 33 ΠΈ 11 ΠΊΠ”ΠΆ/моль Π½Π° ΠΏΠ΅Ρ€Π²ΠΎΠΌ, Π²Ρ‚ΠΎΡ€ΠΎΠΌ ΠΈ Ρ‚Ρ€Π΅Ρ‚ΡŒΠ΅ΠΌ участках кинСтичСских ΠΊΡ€ΠΈΠ²Ρ‹Ρ…, соотвСтствСнно, ΠΏΡ€ΠΈ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ восстановлСния Π±Π΅Π· Π΄ΠΎΠ±Π°Π²ΠΊΠΈ флокулянта ΠΈ 117–130 ΠΈ 82–85 ΠΊΠ”ΠΆ/моль Π² присутствии флокулянта Besfloc K6645. ΠŸΡ€ΠΈ восстановлСнии кадмия Π² присутствии флокулянта каТущаяся энСргия Π°ΠΊΡ‚ΠΈΠ²Π°Ρ†ΠΈΠΈ возрастала Π±ΠΎΠ»Π΅Π΅ Ρ‡Π΅ΠΌ Π² Π΄Π²Π° Ρ€Π°Π·Π°The reduction of cadmium ions from aqueous solutions was carried out with zinc powder, particle size from 63 to 200 ΞΌm. In a number of experiments, the influence of the cationic flocculant Besfloc K6645 on the cadmium cementation process was tested. The process was carried out in the temperature range from 30 to 50 Β°C with continuous stirring at a speed of 200 rpm with an overhead stirrer. Kinetic curves were built using a cadmium selective electrode. It is shown that an increase in the reaction temperature has a positive effect on cementation. The introduction of a flocculant in the amount of 70 mg/l into the electrolyte reduced the degree of cadmium cementation. respectively, when carrying out the reduction without the addition of a flocculant, and 117–130 and 82–85 kJ/mol in the presence of the Besfloc K6645 flocculant. When cadmium was reduced in the presence of a flocculant, the apparent activation energy more than double

    Application of Genetic Algorithms for Finding Edit Distance between Process Models

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    Finding graph-edit distance (graph similarity) is an important task in many computer science areas, such as image analysis, machine learning, chemicalinformatics. Recently, with the development of process mining techniques, it became important to adapt and apply existing graph analysis methods to examine process models (annotated graphs) discovered from event data. In particular, finding graph-edit distance techniques can be used to reveal patterns (subprocesses), compare discovered process models. As it was shown experimentally and theoretically justified, exact methods for finding graph-edit distances between discovered process models (and graphs in general) are computationally expensive and can be applied to small models only. In this paper, we present and assess accuracy and performance characteristics of an inexact genetic algorithm applied to find distances between process models discovered from event logs. In particular, we find distances between BPMN (Business Process Model and Notation) models discovered from event logs by using different process discovery algorithms. We show that the genetic algorithm allows us to dramatically reduce the time of comparison and produces results which are close to the optimal solutions (minimal graph edit distances calculated by the exact search algorithm)

    Applications of Supramolecular Anion Recognition

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