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    ИспользованиС ΠΌΠ΅Ρ€Ρ‹ цСнности ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π‘Ρ‚Ρ€Π°Ρ‚ΠΎΠ½ΠΎΠ²ΠΈΡ‡Π° для ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ Π³ΠΈΠ±ΠΊΠΈΡ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ диагностирования тСхничСских ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ²

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    Π‘ΡƒΡ‰Π΅ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ вычислСния цСнности диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, Ρ†ΠΈΡ€ΠΊΡƒΠ»ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΉ Π² Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… систСмах ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³Π° тСхничСского состояния ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ², Π½Π΅ ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°ΡŽΡ‚ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ (Π²Ρ‹ΠΈΠ³Ρ€Ρ‹ΡˆΠΈ), связанныС с принятиСм Π½Π΅ΠΏΡ€Π°Π²ΠΈΠ»ΡŒΠ½Ρ‹Ρ… Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΉ ΠΏΡ€ΠΈ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ этого состояния. ЦСль Ρ€Π°Π±ΠΎΡ‚Ρ‹ β€” Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ° Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰Π΅Π³ΠΎ Ρ€Π΅ΡˆΠΈΡ‚ΡŒ Π·Π°Π΄Π°Ρ‡Ρƒ распознавания тСхничСского состояния, Π² ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΌ находится Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹ΠΉ ΠΎΠ±ΡŠΠ΅ΠΊΡ‚, ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ динамичСского программирования, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ Π² качСствС ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΠΎΠ³ΠΎ показатСля Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ. РСшСниС Π·Π°Π΄Π°Ρ‡ΠΈ ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ диагностичСской ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Ρ‹ основано Π½Π° использовании ΠΌΠ΅Ρ€Ρ‹ цСнности ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π . Π›.Β Π‘Ρ‚Ρ€Π°Ρ‚ΠΎΠ½ΠΎΠ²ΠΈΡ‡Π°, ΠΌΠΎΠ΄ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΏΡ€ΠΈΠΌΠ΅Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ ΠΊ ΠΏΡ€Π΅Π΄ΠΌΠ΅Ρ‚Π½ΠΎΠΉ области тСхничСского диагностирования ΠΈ ΠΏΡ€ΠΈ использовании диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ², прСдставлСнных Π² Π²ΠΈΠ΄Π΅ ΠΈΠ½Ρ‚Π΅Ρ€Π²Π°Π»ΠΎΠ² Π½Π° вСщСствСнной числовой оси. Максимальная Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ достигаСтся ΠΏΡ€ΠΈ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ срСдних ΠΏΠΎΡ‚Π΅Ρ€ΡŒΒ (максимизации срСдних Π²Ρ‹ΠΈΠ³Ρ€Ρ‹ΡˆΠ΅ΠΉ), ΠΏΠΎΠ»ΡƒΡ‡Π°Π΅ΠΌΡ‹Ρ… ΠΏΡ€ΠΈ Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ², Π² процСссС распознавания тСхничСского состояния ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Π°. Для Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π·Π°Π΄Π°Ρ‡ΠΈ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‰Π΅Π΅ Π½Π°ΡƒΡ‡Π½ΠΎΠΉ Π½ΠΎΠ²ΠΈΠ·Π½ΠΎΠΉ Ρ€Π΅ΠΊΡƒΡ€Ρ€Π΅Π½Ρ‚Π½ΠΎΠ΅ Π²Ρ‹Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰Π΅Π΅ Π²Ρ‹Ρ‡ΠΈΡΠ»ΡΡ‚ΡŒ Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, ΠΏΠΎΠ»ΡƒΡ‡Π°Π΅ΠΌΠΎΠΉ ΠΏΡ€ΠΈ Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ² Π² ΠΊΠ°ΠΆΠ΄ΠΎΠΌ ΠΈΠ· Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… состояний процСсса диагностирования. Π’ процСссС Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ диагностирования ΠΏΡ€ΠΈ распознавании тСхничСского состояния ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ‹ ΠΊΠ°ΠΊ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ, Ρ‚Π°ΠΊ ΠΈ Π²Ρ‹ΠΈΠ³Ρ€Ρ‹ΡˆΠΈ. Π Π°Π·Π½ΠΎΡΡ‚ΡŒ ΠΈΡ… Π°ΠΏΡ€ΠΈΠΎΡ€Π½Ρ‹Ρ… ΠΈ апостСриорных срСдних Π·Π½Π°Ρ‡Π΅Π½ΠΈΠΉ числСнно Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΠ΅Ρ‚ Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ. Π’Π΅Π»ΠΈΡ‡ΠΈΠ½Π° показатСля цСнности ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ зависит ΠΎΡ‚ вСроятностСй исходов ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ² ΠΈ ΠΏΡ€ΠΎΠΏΠΎΡ€Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Π° разности апостСриорных ΠΈ Π°ΠΏΡ€ΠΈΠΎΡ€Π½Ρ‹Ρ… вСроятностСй достиТСния Ρ†Π΅Π»ΠΈ диагностирования. ИспользованиС ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ позволяСт ΡΠΈΠ½Ρ‚Π΅Π·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½ΡƒΡŽ ΠΏΠΎ ΠΊΡ€ΠΈΡ‚Π΅Ρ€ΠΈΡŽ максимума цСнности диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π³ΠΈΠ±ΠΊΡƒΡŽ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡƒ диагностирования Π² Π²ΠΈΠ΄Π΅ ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ Π³Ρ€Π°Ρ„Π° ΠΈΠ»ΠΈ упорядочСнных ΠΏΠΎ очСрСдности ΠΈΡ… выполнСния Π½Π°Π±ΠΎΡ€ΠΎΠ² ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ, Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΡ‹Ρ… для распознавания ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½ΠΎΠ³ΠΎ тСхничСского состояния, Π² ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΌ находится ΠΎΠ±ΡŠΠ΅ΠΊΡ‚. РСализация Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Π° Π² ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½ΠΎ-алгоритмичСском обСспСчСнии Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… систСм ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³Π° состояния слоТных тСхничСских ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ²

    ИспользованиС ΠΌΠ΅Ρ€Ρ‹ цСнности ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π‘Ρ‚Ρ€Π°Ρ‚ΠΎΠ½ΠΎΠ²ΠΈΡ‡Π° для ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ Π³ΠΈΠ±ΠΊΠΈΡ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ диагностирования тСхничСских ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ²

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    Existing methods of calculating of the value of diagnostic information circulating in the automated systems of monitoring of technical condition of objects do not take into account "losses" ("gains") resulting from making β€œwrong” decisions when identifying this state. The purpose of the work is to develop an algorithm that allows to solve the problem of recognizing the technical state of the object being analyzed by means of dynamic programming, the value of the diagnostic information as an optimized indicator being used. The solution to the optimization problem of a diagnostic procedure is based on the use of a measure of the information value proposed by R. L. Stratonovich. It is modified according to the subject area of the technical diagnostics and in the case when the diagnostic features presented in the form of intervals on the real numerical axis are used. The maximum value of the diagnostic information is achieved by minimizing the average "losses" (maximizing the average "gains") obtained when performing tests of diagnostic signs in the process of recognizing the technical condition of an object. To solve the problem, a recurrent expression possessing a scientific novelty has been proposed. It allows to calculate the value of the information obtained when performing tests of diagnostic signs in each of the analyzed information states of the diagnostic process. In the process of the diagnostics program implementation when recognizing the technical condition of the object both β€œlosses” and β€œwinnings” are possible. The difference between their a priori and a posteriori means values characterizes the value of the diagnostic information numerically. The magnitude of the information value indication depends on the probabilities of the results of the diagnostic signs checks and is proportional to the difference between the a posteriori and a priori probabilities of achieving the diagnostic goal. By using the proposed solution, it is possible to synthesize the flexible diagnostics program that is optimal according to the maximum value of diagnostic information in the form of a oriented graph or sets of tests in proper sequence of their execution. This is necessary in order to recognize the specific technical state in which the object is located. The implementation of the algorithm developed is possible in the software and algorithmic support of the automated systems for monitoring the state of complex technical objects.Π‘ΡƒΡ‰Π΅ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ вычислСния цСнности диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, Ρ†ΠΈΡ€ΠΊΡƒΠ»ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΉ Π² Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… систСмах ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³Π° тСхничСского состояния ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ², Π½Π΅ ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°ΡŽΡ‚ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ (Π²Ρ‹ΠΈΠ³Ρ€Ρ‹ΡˆΠΈ), связанныС с принятиСм Π½Π΅ΠΏΡ€Π°Π²ΠΈΠ»ΡŒΠ½Ρ‹Ρ… Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΉ ΠΏΡ€ΠΈ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ этого состояния. ЦСль Ρ€Π°Π±ΠΎΡ‚Ρ‹ β€” Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ° Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰Π΅Π³ΠΎ Ρ€Π΅ΡˆΠΈΡ‚ΡŒ Π·Π°Π΄Π°Ρ‡Ρƒ распознавания тСхничСского состояния, Π² ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΌ находится Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹ΠΉ ΠΎΠ±ΡŠΠ΅ΠΊΡ‚, ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ динамичСского программирования, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ Π² качСствС ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΠΎΠ³ΠΎ показатСля Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ. РСшСниС Π·Π°Π΄Π°Ρ‡ΠΈ ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ диагностичСской ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Ρ‹ основано Π½Π° использовании ΠΌΠ΅Ρ€Ρ‹ цСнности ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π . Π›. Π‘Ρ‚Ρ€Π°Ρ‚ΠΎΠ½ΠΎΠ²ΠΈΡ‡Π°, ΠΌΠΎΠ΄ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΏΡ€ΠΈΠΌΠ΅Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ ΠΊ ΠΏΡ€Π΅Π΄ΠΌΠ΅Ρ‚Π½ΠΎΠΉ области тСхничСского диагностирования ΠΈ ΠΏΡ€ΠΈ использовании диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ², прСдставлСнных Π² Π²ΠΈΠ΄Π΅ ΠΈΠ½Ρ‚Π΅Ρ€Π²Π°Π»ΠΎΠ² Π½Π° вСщСствСнной числовой оси. Максимальная Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ достигаСтся ΠΏΡ€ΠΈ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ срСдних ΠΏΠΎΡ‚Π΅Ρ€ΡŒ (максимизации срСдних Π²Ρ‹ΠΈΠ³Ρ€Ρ‹ΡˆΠ΅ΠΉ), ΠΏΠΎΠ»ΡƒΡ‡Π°Π΅ΠΌΡ‹Ρ… ΠΏΡ€ΠΈ Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ², Π² процСссС распознавания тСхничСского состояния ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Π°. Для Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π·Π°Π΄Π°Ρ‡ΠΈ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‰Π΅Π΅ Π½Π°ΡƒΡ‡Π½ΠΎΠΉ Π½ΠΎΠ²ΠΈΠ·Π½ΠΎΠΉ Ρ€Π΅ΠΊΡƒΡ€Ρ€Π΅Π½Ρ‚Π½ΠΎΠ΅ Π²Ρ‹Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰Π΅Π΅ Π²Ρ‹Ρ‡ΠΈΡΠ»ΡΡ‚ΡŒ Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, ΠΏΠΎΠ»ΡƒΡ‡Π°Π΅ΠΌΠΎΠΉ ΠΏΡ€ΠΈ Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ² Π² ΠΊΠ°ΠΆΠ΄ΠΎΠΌ ΠΈΠ· Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Ρ… ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… состояний процСсса диагностирования. Π’ процСссС Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ диагностирования ΠΏΡ€ΠΈ распознавании тСхничСского состояния ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ‹ ΠΊΠ°ΠΊ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ, Ρ‚Π°ΠΊ ΠΈ Π²Ρ‹ΠΈΠ³Ρ€Ρ‹ΡˆΠΈ. Π Π°Π·Π½ΠΎΡΡ‚ΡŒ ΠΈΡ… Π°ΠΏΡ€ΠΈΠΎΡ€Π½Ρ‹Ρ… ΠΈ апостСриорных срСдних Π·Π½Π°Ρ‡Π΅Π½ΠΈΠΉ числСнно Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΠ΅Ρ‚ Ρ†Π΅Π½Π½ΠΎΡΡ‚ΡŒ диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ. Π’Π΅Π»ΠΈΡ‡ΠΈΠ½Π° показатСля цСнности ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ зависит ΠΎΡ‚ вСроятностСй исходов ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ диагностичСских ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ² ΠΈ ΠΏΡ€ΠΎΠΏΠΎΡ€Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Π° разности апостСриорных ΠΈ Π°ΠΏΡ€ΠΈΠΎΡ€Π½Ρ‹Ρ… вСроятностСй достиТСния Ρ†Π΅Π»ΠΈ диагностирования. ИспользованиС ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ позволяСт ΡΠΈΠ½Ρ‚Π΅Π·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½ΡƒΡŽ ΠΏΠΎ ΠΊΡ€ΠΈΡ‚Π΅Ρ€ΠΈΡŽ максимума цСнности диагностичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π³ΠΈΠ±ΠΊΡƒΡŽ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡƒ диагностирования Π² Π²ΠΈΠ΄Π΅ ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ Π³Ρ€Π°Ρ„Π° ΠΈΠ»ΠΈ упорядочСнных ΠΏΠΎ очСрСдности ΠΈΡ… выполнСния Π½Π°Π±ΠΎΡ€ΠΎΠ² ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΎΠΊ, Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΡ‹Ρ… для распознавания ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½ΠΎΠ³ΠΎ тСхничСского состояния, Π² ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΌ находится ΠΎΠ±ΡŠΠ΅ΠΊΡ‚. РСализация Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Π° Π² ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½ΠΎ-алгоритмичСском обСспСчСнии Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… систСм ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³Π° состояния слоТных тСхничСских ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ²

    RANCANG BANGUN APLIKASI SMARTWATCH β€œSCHEDULLING ACTIVITIES” MENGGUNAKAN MODEL MOBILE-D

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    Smartwatch merupakan salah satu teknologi yang berkembang didunia. Perkembangan smartwatch dunia juga mempengaruhi penggunaannya di Indonesia. Pengguna Smartwatch didunia hanya sebesar 0.1% dari pengguna smartphone didunia yang sebesar 1914.6 juta pengguna, padahal perkembangan teknologi smartwatch sendiri semakin hari semakin bertambah. Smartwatch merupakan jam tangan pintar yang menggunakan sistem operasi android wear. Dengan menggunakan smartwatch pengguna mendapatkan fungsi utama jam tangan beserta kelebihan lainnya seperti kalkulator, pedometer, informasi waktu minum air dan lain-lainnya. Penggunaan smartwatch juga dapat membantu penggunya dalam berbagai kegiatan, salah satunya adalah penjadualan aktifitas setiap hari. Aplikasi penjadualan aktifitas berbasikan smartwatch dapat membantu pengguna dalam mengingat dan menentukan kegiatan setiap harinya dengan memasukkan jadual kegiatan pada sebuah smartphone dan informasi kegiatan akan dimunculkan pada smartwatch yang digunakan pengguna. Dengan keadaan seperti ini, maka pengguna selalu dapat melihat informasi yang muncul setiap ada janji yang akan berlangsung setiap harinya. Mobile-D merupakan salah satu model pengembangan apikasi yang digunakan dalam pengembangan aplikasi ini. Dengan lima kegiatan utama: Explore, Initialize Productionize, Stabilize dan System Test & Fix menjadikan mobile-d sebagai model pengembangan yang cocok dalam pengembangan aplikasi berbasiskan android. Aplikasi Smartwatch yang dikembangkan telah berhasil dan diuji pada dua buah smartwatch Lemfo Lem5 dan Asus Zenwatch. Uji aplikasi menggunakan teknologi bluetooth yang ada pada smartwatch dan dihubungkan dengan bluetooth dari smartphone.Dari hasil uji, aplikasi dapat berjalan baik pada kedua smartwatch yang berbeda dan fungsi-fungsi aplikasi juga telah berjalan sesuai dengan rencan

    Urban planning, public participation and digital technology: App development as a method of generating citizen involvement in local planning processes

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    There has been a recent shift in England towards empowering citizens to shape their neighbourhoods. However, current methods of participation are unsuitable or unwieldy for many people. In this paper, we report on ChangeExplorer, a smart watch application to support citizen feedback, to investigate the extent to which digital wearables can address barriers to participation in planning. The research contributes to both technology-mediated citizen involvement and urban planning participation methods. The app leverages in-situ, quick interactions encouraging citizens to reflect and comment on their environment. Taking a case study approach, the paper discusses the design and deployment of the app in a local planning authority through interviews with 19 citizens and three professional planners. The paper discusses the potential of the ChangeExplorer app to address more conceptual issues, and concludes by assessing the degree to which the technology raises awareness of urban change and whether it could serve as a gateway to more meaningful participatory methods

    Geospatial Semantics

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    Geospatial semantics is a broad field that involves a variety of research areas. The term semantics refers to the meaning of things, and is in contrast with the term syntactics. Accordingly, studies on geospatial semantics usually focus on understanding the meaning of geographic entities as well as their counterparts in the cognitive and digital world, such as cognitive geographic concepts and digital gazetteers. Geospatial semantics can also facilitate the design of geographic information systems (GIS) by enhancing the interoperability of distributed systems and developing more intelligent interfaces for user interactions. During the past years, a lot of research has been conducted, approaching geospatial semantics from different perspectives, using a variety of methods, and targeting different problems. Meanwhile, the arrival of big geo data, especially the large amount of unstructured text data on the Web, and the fast development of natural language processing methods enable new research directions in geospatial semantics. This chapter, therefore, provides a systematic review on the existing geospatial semantic research. Six major research areas are identified and discussed, including semantic interoperability, digital gazetteers, geographic information retrieval, geospatial Semantic Web, place semantics, and cognitive geographic concepts.Comment: Yingjie Hu (2017). Geospatial Semantics. In Bo Huang, Thomas J. Cova, and Ming-Hsiang Tsou et al. (Eds): Comprehensive Geographic Information Systems, Elsevier. Oxford, U

    Technology-enabled planning participation: Designing & deploying digital technology to encourage citizen participation in urban planning

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    Ph. D. Thesis.Citizens increasingly want to formally engage with the governmental and policy processes that manage how places change. Whilst enhancing the role of citizens in urban planning has been a longstanding objective for academics and communities, translating these aspirations into practice has proved to be more challenging. Although a range of conceptual ideas and practical techniques have been developed in planning to provide opportunities to enhance citizen involvement, these ideas and methods have faced several challenges. These include the strict legalistic and policy parameters that determine what sort of comments that are permissible, the governmental initiators of public engagement, and the need to understand and utilise the often complex language of planning. And yet citizens and communities are increasingly resorting to social media and digital communication to express their views about urban change. This research assesses the degree to which new digital technology can be designed and deployed to enhance citizen engagement within urban planning and identify whether it offers one potential method to address and overcome some of the challenges being experienced in citizen engagement. Through designing, deploying and evaluating speculative digital technologies, the research aims to understand the potential role of technology in facilitating enhanced citizen participation in planning. Working with citizens, community organisations and planners, the research explores the factors at play when innovative and bespoke engagement methods are used to amplify citizens’ voices in urban change. An action research approach was taken, which uses a continual cycle of designing and planning, deploying different types of technologies and reflections to inform design. Three technologies were piloted in different settings and contexts: a social media example addressing a complex planning issues; a smart watch application to support in-place engagement; and an interactive digital device that encourages people to communicate their feelings and aspirations through visual and oral means. Across the three examples, over 1400 citizens participated in the research. Findings demonstrate how the three digital initiatives encouraged people to be expressive when communicating complicated feelings towards urban change, and the influence different methods have on what people communicate. They illustrate how different participation methods can support differing levels of engagement, and how digital technologies might better align with how citizens would like to participate. The research critiques the suitability of current participation methods, and the extent to which they can support a genuine discussion about where people live and what they care about. It concludes by questioning whether current planning engagement methods can adequately equip non-experts with the tools to participate. The overall conclusion is that by employing digital technologies, a much more productive and fruitful conversation can be designed to facilitate citizen participation in planning compared to traditional methods
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