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Статті в журналах з теми "Anomalous process"
MEHTA, AK, and R. RAVIKUMAR. "ANOMALOUS ELONGATION OF STYLOID PROCESS." Medical Journal Armed Forces India 56, no. 3 (July 2000): 248–49. http://dx.doi.org/10.1016/s0377-1237(17)30182-x.
Повний текст джерелаWu, Renguang, and Zhuoqi He. "Two Distinctive Processes for Abnormal Spring to Summer Transition over the South China Sea." Journal of Climate 30, no. 23 (December 2017): 9665–78. http://dx.doi.org/10.1175/jcli-d-17-0215.1.
Повний текст джерелаHannah, Torben. "The anomalous process to two loops." Nuclear Physics B 593, no. 3 (January 2001): 577–95. http://dx.doi.org/10.1016/s0550-3213(00)00641-6.
Повний текст джерелаWada, H., T. Mori, M. Shiga, H. Aruga Katori, M. I. Bartashevich, and T. Goto. "Anomalous magnetization process of Er1−xLuxCo2." Physica B: Condensed Matter 201 (July 1994): 139–42. http://dx.doi.org/10.1016/0921-4526(94)91068-5.
Повний текст джерелаDudley, J., and B. Chambers. "ANOMALOUS RESPONSE IN THE HALIFAX PROCESS." Water and Environment Journal 17, no. 3 (August 2003): 168–70. http://dx.doi.org/10.1111/j.1747-6593.2003.tb00456.x.
Повний текст джерелаSun, Yue, and Haishan Chen. "Atmospheric Circulation Anomalies and Key Physical Processes behind Two Categories of Anomalous Eurasian Spring Snowmelt." Journal of Hydrometeorology 24, no. 8 (August 2023): 1349–63. http://dx.doi.org/10.1175/jhm-d-23-0010.1.
Повний текст джерелаvan der Aalst, W. M. P., and A. K. A. de Medeiros. "Process Mining and Security: Detecting Anomalous Process Executions and Checking Process Conformance." Electronic Notes in Theoretical Computer Science 121 (February 2005): 3–21. http://dx.doi.org/10.1016/j.entcs.2004.10.013.
Повний текст джерелаTrirat, Patara, Youngeun Nam, Taeyoon Kim, and Jae-Gil Lee. "AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 13 (June 26, 2023): 16488–90. http://dx.doi.org/10.1609/aaai.v37i13.27088.
Повний текст джерелаPithwa, Yogesh Kishorkant. "Anomalous Cervical Spinous Process Leading to Myelopathy." Spine 40, no. 20 (October 2015): E1117—E1119. http://dx.doi.org/10.1097/brs.0000000000001088.
Повний текст джерелаArkashov, N. S., and V. A. Seleznev. "Energy Characteristics of the Anomalous Diffusion Process." Theoretical and Mathematical Physics 199, no. 3 (June 2019): 894–908. http://dx.doi.org/10.1134/s0040577919060096.
Повний текст джерелаДисертації з теми "Anomalous process"
Slifko, Matthew D. "The Cauchy-Net Mixture Model for Clustering with Anomalous Data." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/93576.
Повний текст джерелаDoctor of Philosophy
We live in the data explosion era. The unprecedented amount of data offers a potential wealth of knowledge but also brings about concerns regarding ethical collection and usage. Mistakes stemming from anomalous data have the potential for severe, real-world consequences, such as when building prediction models for housing prices. To combat anomalies, we develop the Cauchy-Net Mixture Model (CNMM). The CNMM is a flexible tool for identifying and isolating the anomalies, while simultaneously discovering cluster structure and making predictions among the nonanomalous observations. The result is a framework that allows for simultaneously clustering and predicting in the face of the anomalous data. We demonstrate the usefulness of the CNMM in a variety of experimental situations and apply the model for predicting housing prices in Fairfax County, Virginia.
Barnardo, Twilight. "Time resolved anomalous small angle X-ray scattering of the sol-gel process." Thesis, Aberystwyth University, 2010. http://hdl.handle.net/2160/17191ae6-e038-4c50-b380-8f4d227791a8.
Повний текст джерелаRyklina, Tatiana. "The role of anomalous phenomena in the therapeutic process : an exploration of counselling psychologists' experience." Thesis, University of Roehampton, 2012. https://pure.roehampton.ac.uk/portal/en/studentthesis/the-role-of-anomalous-phenomena-in-the-therapeutic-process(7a025bd0-3818-4f60-a461-ba88e22e35d5).html.
Повний текст джерелаRosten, Jonatan Hans Niclas. "The ZZ → 4l process and anomalous triple gauge couplings with ATLAS at the LHC." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/271838.
Повний текст джерелаHolt, Nicola J. "Creativity, altered states of consciousness and anomalous cognition : the role of epistemological flexibility in the creative process." Thesis, University of Northampton, 2007. http://nectar.northampton.ac.uk/2847/.
Повний текст джерелаŠkultéty, Viktor. "Critical behaviour of directed percolation process in the presence of compressible velocity field." Thesis, Stockholms universitet, Fysikum, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-144061.
Повний текст джерелаGao, Jun. "Measurement of the WW production cross-section in Proton-Proton Collisions at sqrt(s) = 8 TeV with the ATLAS detector." Thesis, Aix-Marseille, 2015. http://www.theses.fr/2015AIXM4066.
Повний текст джерелаThe Standard Model (SM), actual fundamental theory for particle physics, provides a description of the elementary particles and the fundamental interactions: the electromagnetic, weak and strong forces. At the European Organization for Nuclear Research (CERN), physicists and engineers from all over the world are searching to understand the fundamental laws of the universe. It is at CERN that the world's largest and most sophisticated experimental instruments have been built, to accelerate particles at the energy of 3.5-4 TeV with the Large Hadron Collider (LHC). A Toroidal LHC ApparatuS (ATLAS), one of the four main detectors at LHC. In ATLAS, di-boson production is one of the most important electro-weak processes.The electro-weak sector of the SM, as well as the strong interactions, can be tested through the precision measurements of the W⁺W⁻ production cross section. A measurement of the W⁺W⁻ production cross section in 8 TeV center of mass proton-proton collisions is presented here from data collected with the ATLAS detector at the LHC for a total integrated luminosity of 20.3 fb⁻¹. The W⁺W⁻ events are selected with 3 final states: ee, eµ, and µµ. In order to suppress the background contamination, mainly from the Drell-Yan and ttbar processes, a cut on missing transverse energy is applied and events with hadronic jets satisfying appropriate selection criteria are rejected. The major backgrounds, mainly including W +jets, top and Z+jets, are estimated by data driven technique. The measured cross section is 71.0⁺¹⋅¹₋₁⋅₁(stat)⁺⁵⋅⁷₋₅⋅₀(syst)⁺²⋅¹₋₂⋅₀(lumi) pb, which is consistent with SM Next-to-Next-Leading-Order prediction of 63.2⁺²⋅⁰₋₁⋅₈ pb
Roca, Chunga Guiuliana Krystal, and Echevarría Irving Godofredo Tristán. "Mejora del proceso de monitoreo de accesos y comportamiento de usuarios en entorno cloud." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/656443.
Повний текст джерелаThe objective of this research work is to improve the process of Monitoring Accesses and User Behavior in the Cloud Environment of the Technological Security management, this process is one of the main controls in the information security and cybersecurity program of Mibanco by contribute to the timely detection of security events, avoid incidents that could affect the organization and for the fulfillment of security standards that every financial entity must comply with. The research work was developed in six chapters where, first, the Theoretical Framework used is detailed; Then, in the Project Development chapter, the analysis of the business architecture and the identification of the objective problems that must be worked on to improve the process is carried out. Likewise, in the other chapters the solution software architecture and project management were developed.
Tesis
Paulin, Carl. "Detecting anomalies in data streams driven by ajump-diffusion process." Thesis, Umeå universitet, Institutionen för fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184230.
Повний текст джерелаHopp-diffusionsprocesser används regelbundet för att modellera finansiella tidsserier eftersom de kan simulera de slumpmässiga hopp som ofta uppstår. Dessa hopp kan ses som anomalier och är viktiga för finansiell analys och modellbyggnad, vilket gör dom väldigt viktiga att hitta. Den realiserade variationen, realiserade bipower variationen, och realiserade semi-variationen är faktorer av en tidsserie som kan användas för att hitta hopp i hopp-diffusionprocesser. De används här för att testa om anomali-detektionsalgoritmer kan använda funktionerna för att förbättra dess förmåga att detektera hopp. Algoritmerna som testades var Isolation Forest, Robust Random Cut Forest, och Isolation Forest Algoritmen för Strömmande data, där de två sistnämnda använder strömmande data. Detta gjordes genom att genera data från en Merton hopp-diffusionprocess med varierande hoppfrekvens där de olika algoritmerna testades med varje funktion samt med kombinationer av funktioner. Prestationen av varje algoritm beräknades med hjälp av F1-värde för att kunna jämföra algoritmerna och funktionerna med varandra. Det hittades att funktionerna kan användas för att extrahera hopp från hopp-diffusionprocesser och även använda de som en indikator för när hopp skulle ha hänt. Algoritmerna fick även ett högre F1-värde när de använde funktionerna. Isolation Forest fick ett förbättrat F1-värde genom att använda en eller fler utav funktionerna och hade ett högre F1-värde än att bara använda funktionerna för att detektera hopp. Robust Random Cut Forest hade högst F1-värde av de två algoritmer som använde strömmande data och båda fick högst F1-värde när man använde en kombination utav alla funktioner. Resultatet visar att dessa funktioner fungerar för att extrahera hopp från hopprocesser, använda dem för att detektera hopp, och att algoritmernas förmåga att detektera hoppen ökade med hjälp av funktionerna.
Fica, Tapia María Fernanda. "Detección de anomalías en un proceso de carguío autónomo." Tesis, Universidad de Chile, 2018. http://repositorio.uchile.cl/handle/2250/169246.
Повний текст джерелаLa automatización de la maquinaria dentro de la minería es una tendencia que ha cobrado mayor importancia con el transcurso del tiempo, principalmente por el ambiente peligroso e impredecible en el que deben ser manejadas, lo que genera una serie de riesgos para los operadores manuales de los equipos. Lo anterior sumado a los potenciales beneficios económicos por aumento del factor de utilización, reducción del desgaste de los componentes y operación eficiente de la máquina, hacen del concepto de la minería autónoma una promesa interesante. El objetivo de este trabajo es crear un detector de anomalías para el proceso de carguío autónomo de maquinaria minera, en donde la anomalía se define como la necesidad de impactar más de una vez contra la pila de recolección para llenar el balde del cargador. Para esto se utilizaron los datos de operación obtenidos de un cargador LHD utilizado en la minera 'San Gerónimo'. Debido a la complejidad física de estos sistemas, se utilizará un modelo no paramétrico para la modelación del proceso, el cual corresponde a un modelo basado en similitud (SBM de sus siglas en inglés). Se creará una metodología para obtener un modelo que contengan las variables explicativas del proceso y con el que se pueda generar una rutina de detección que avise al operario en caso de que las señales medidas mientras carga sean similares a las caracterizadas en el modelo SBM como anomalía. La metodología propuesta en este trabajo fue probada con los datos obtenidos en la minera, con los cuales se obtuvo un error de un 7,5% en la detección de carguíos anómalos. También se probó la metodología con datos de carguío manual, en donde un operador manejaba en la mina el cargador de forma remota. En este caso los resultados no fueron tan positivos como en el caso autónomo, en donde se consiguió que el detector errara en promedio un 23,3% de las veces que fue probado. Como principales conclusiones, se verifica el uso de modelos no paramétricos para la caracterización de procesos multivariables, sin embargo la metodología desarrollada sólo es aplicable a la maquinaria estudiada. También se destaca la importancia de datos variados para la creación de los modelos, es decir, que contengan diferentes puntos de operación del proceso. En particular en el caso de los carguíos autónomos, existe una mayor complejidad para caracterizar el carguío, dado que se necesita recolectar los datos de muchos operarios para tener una matriz de entrada rica en información, no así en el caso autónomo donde el hecho de utilizar una secuencia programada reduce la cantidad de datos necesarios para la modelación.
Книги з теми "Anomalous process"
Mullins, John W. The process of timely strategic marketing change: Punctuations, influences and anomalies. Cambridge, Mass: Marketing Science Institute, 1995.
Знайти повний текст джерелаMullins, John W. The process of timely strategic marketing change: Punctuations, influences and anomalies. Cambridge, Mass: Marketing Science Institute, 1995.
Знайти повний текст джерелаRing, L. R. Process development and fabrication of space station type aluminum-clad graphite epoxy struts. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.
Знайти повний текст джерелаRegularised integrals, sums, and traces: An analytic point of view. Providence, R.I: American Mathematical Society, 2012.
Знайти повний текст джерелаDaniel. [from old catalog] Campos, Vicenç Méndez, and Frederic Bartumeus. Stochastic Foundations in Movement Ecology: Anomalous Diffusion, Front Propagation and Random Searches. Springer London, Limited, 2013.
Знайти повний текст джерелаDaniel. [from old catalog] Campos, Vicenç Méndez, and Frederic Bartumeus. Stochastic Foundations in Movement Ecology: Anomalous Diffusion, Front Propagation and Random Searches. Springer, 2013.
Знайти повний текст джерелаDaniel. [from old catalog] Campos, Vicenç Méndez, and Frederic Bartumeus. Stochastic Foundations in Movement Ecology: Anomalous Diffusion, Front Propagation and Random Searches. Springer, 2016.
Знайти повний текст джерелаDaniel. [from old catalog] Campos, Vicenç Méndez, and Frederic Bartumeus. Stochastic Foundations in Movement Ecology: Anomalous Diffusion, Front Propagation and Random Searches. Springer, 2013.
Знайти повний текст джерелаColeman, John J. Monitoring Prescriptions, Third-Party Healthcare Payers, Prescription Benefit Managers, and Private-Sector Policy Options. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199981830.003.0003.
Повний текст джерелаCohen, Maurie J. Workers—and Consumers—of the World Unite! Opportunities for Hybrid Co-operativism. Edited by Jonathan Michie, Joseph R. Blasi, and Carlo Borzaga. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199684977.013.26.
Повний текст джерелаЧастини книг з теми "Anomalous process"
Cooper, Callum E., Chris A. Roe, and Graham Mitchell. "Anomalous Experiences and the Bereavement Process." In Death, Dying, and Mysticism, 117–31. New York: Palgrave Macmillan US, 2015. http://dx.doi.org/10.1057/9781137472083_8.
Повний текст джерелаChen, Wen, HongGuang Sun, and Xicheng Li. "Fractional Diffusion Model, Anomalous Statistics and Random Process." In Fractional Derivative Modeling in Mechanics and Engineering, 115–57. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8802-7_4.
Повний текст джерелаYau, Ken, Kam-Pui Chow, and Siu-Ming Yiu. "Detecting Anomalous Programmable Logic Controller Events Using Process Mining." In Critical Infrastructure Protection XV, 119–33. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93511-5_6.
Повний текст джерелаArmentano, Marcelo G., and Analía A. Amandi. "Detection of Sequences with Anomalous Behavior in a Workflow Process." In Lecture Notes in Computer Science, 111–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22849-5_8.
Повний текст джерелаMozafari Mehr, Azadeh Sadat, Renata M. de Carvalho, and Boudewijn van Dongen. "Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach." In Lecture Notes in Business Information Processing, 44–56. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_4.
Повний текст джерелаGupta, Nisha, Kritika Anand, and Ashish Sureka. "Pariket: Mining Business Process Logs for Root Cause Analysis of Anomalous Incidents." In Databases in Networked Information Systems, 244–63. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16313-0_19.
Повний текст джерелаLebrun, Stéphanie, Stéphane Kaloustian, Raphaël Rollier, and Colin Barschel. "GNSS Positioning Security: Automatic Anomaly Detection on Reference Stations." In Critical Information Infrastructures Security, 60–76. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-93200-8_4.
Повний текст джерелаHopersky, Alexey N., and Victor A. Yavna. "Research Results of the Process of the Anomalous Elastic X-Ray Photon Scattering by a Many-Electron System." In Scattering of Photons by Many-Electron Systems, 1–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04256-0_1.
Повний текст джерелаZumofen, G., J. Klafter, and A. Blumen. "Models for Anomalous Diffusion." In Disorder Effects on Relaxational Processes, 251–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78576-4_8.
Повний текст джерелаAwad, Ahmed, Gero Decker, and Niels Lohmann. "Diagnosing and Repairing Data Anomalies in Process Models." In Business Process Management Workshops, 5–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12186-9_2.
Повний текст джерелаТези доповідей конференцій з теми "Anomalous process"
Matsumoto, Osamu, Kan Kimura, Yuko Saito, Haruo Uyama, and Tsuyoshi Yaita. "Tritium production process - comparison between neutron emission rate and tritium production rate." In Anomalous nuclear effects in deuterium/solid systems. AIP, 1991. http://dx.doi.org/10.1063/1.40670.
Повний текст джерелаMu, Shaomin, Shengfeng Tian, and Chuanhuan Yin. "Using Length-weighted Once Kernel to Detect Anomalous Process." In Third International Conference on Natural Computation (ICNC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icnc.2007.802.
Повний текст джерелаMourad, Abdel-Hamid I., and Aladdin Abu-Assi. "Effect of Machining Process on Stable Crack Growth." In ASME 2009 Pressure Vessels and Piping Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/pvp2009-78085.
Повний текст джерелаMcMaster, Kirby, Samuel Sambasivam, and Nicole Anderson. "How Anomalous Is Beladv's Anomaly?" In InSITE 2009: Informing Science + IT Education Conference. Informing Science Institute, 2009. http://dx.doi.org/10.28945/3390.
Повний текст джерелаMoriwaki, Kosuke, Gaku Nakano, and Tetsuo Inoshita. "The BRIO-TA Dataset: Understanding Anomalous Assembly Process in Manufacturing." In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897369.
Повний текст джерелаSatterthwaite, Peter F., Ananth Saran Yalamarthy, Sam Vaziri, Miguel Munoz Rojo, Eric Pop, and Debbie G. Senesky. "Process-induced anomalous current transport in graphene/InAlN/GaN heterostructured diodes." In 2019 IEEE International Reliability Physics Symposium (IRPS). IEEE, 2019. http://dx.doi.org/10.1109/irps.2019.8720465.
Повний текст джерелаV. V., Sagaradze, Shabashov V. A., Kataeva N. V., Kozlov K. A. Kozlov,, and Kuznetsov A. R. Kuznetsov1. "Anomalous Diffusion Transformations in Steels during Nanostructuring Process under Cold Deformation." In NANOMATERIALS AND TECHNOLOGIES-VI. Buryat State University Publishing Department, 2016. http://dx.doi.org/10.18101/978-5-9793-0883-8-185-189.
Повний текст джерелаZhu, Min, Feiyu Lai, Xinyu Chen, and Zhuyang Jing. "Time-Dependent Fractional Dynamics of Anomalous Diffusion Process on Complex Networks." In 2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC). IEEE, 2022. http://dx.doi.org/10.1109/yac57282.2022.10023695.
Повний текст джерелаRodriguez, Dryonis, Paul Clare, Rohit Srikonda, and Monika Suvarna. "Stampede Digital Twin: An Advanced Solution for Process Equipment Condition Monitoring." In SPE Annual Technical Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/210106-ms.
Повний текст джерелаRiveiro, Maria, Göran Falkman, Tom Ziemke, and Thomas Kronhamn. "Reasoning about anomalies: a study of the analytical process of detecting and identifying anomalous behavior in maritime traffic data." In SPIE Defense, Security, and Sensing, edited by William J. Tolone and William Ribarsky. SPIE, 2009. http://dx.doi.org/10.1117/12.818117.
Повний текст джерелаЗвіти організацій з теми "Anomalous process"
Roberts, C. D., and R. Alkofer. Study of the anomalous process {gamma}{pi}{yields}{pi}{pi}. Office of Scientific and Technical Information (OSTI), August 1995. http://dx.doi.org/10.2172/166446.
Повний текст джерелаRiccardella, Scott. PR-335-143705-R01 Study on Reliability of In-ditch NDE for SCC Anomalies. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), October 2018. http://dx.doi.org/10.55274/r0011529.
Повний текст джерелаTandon, Samarth, and Ravi Krishnamurthy. PR328-163605-R01 Methodology for Assessing Seam Weld Anomalies Using In-Line Inspection Data. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2019. http://dx.doi.org/10.55274/r0011638.
Повний текст джерелаLutz, Carsten. Reasoning about Entity Relationship Diagrams with Complex Attribute Dependencies. Aachen University of Technology, 2002. http://dx.doi.org/10.25368/2022.119.
Повний текст джерелаBerndt, Christian. RV SONNE Fahrtbericht / Cruise Report SO277 OMAX: Offshore Malta Aquifer Exploration, Emden (Germany) – Emden (Germany), 14.08. – 03.10.2020. GEOMAR Helmholtz Centre for Ocean Research Kiel, January 2021. http://dx.doi.org/10.3289/geomar_rep_ns_57_20.
Повний текст джерелаMacrory, Cara. PR727-213904-R01 Considerations for Crack ILI Response in Hazardous Liquids Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), February 2022. http://dx.doi.org/10.55274/r0012209.
Повний текст джерелаSemiga and Tiku. PR-214-104505-R02 Improved Methods for Estimating Remaining Fatigue Life of ERW Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 2015. http://dx.doi.org/10.55274/r0010204.
Повний текст джерелаKrause, Thomas, Mehrdad Keshefi, Ross Underhill, and Lynann Clapham. PR652-203801-R02 Magnetic Object Model for Large Standoff Magnetometry Measurement. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2021. http://dx.doi.org/10.55274/r0012151.
Повний текст джерелаTayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, January 2022. http://dx.doi.org/10.31979/mti.2022.2014.
Повний текст джерелаLaroche, Hervé, and Véronique Steyer. L’apport des théories du sensemaking à la compréhension des risques et des crises. Fondation pour une culture de sécurité industrielle, October 2012. http://dx.doi.org/10.57071/208snv.
Повний текст джерела