Relevant bibliographies by topics / Event and anomaly

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Event and anomaly'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Event and anomaly"

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Huang, Huiqun, Xi Yang, and Suining He. "Multi-Head Spatio-Temporal Attention Mechanism for Urban Anomaly Event Prediction." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3 (2021): 1–21. http://dx.doi.org/10.1145/3478099.

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Timely forecasting the urban anomaly events in advance is of great importance to the city management and planning. However, anomaly event prediction is highly challenging due to the sparseness of data, geographic heterogeneity (e.g., complex spatial correlation, skewed spatial distribution of anomaly events and crowd flows), and the dynamic temporal dependencies. In this study, we propose M-STAP, a novel Multi-head Spatio-Temporal Attention Prediction approach to address the problem of multi-region urban anomaly event prediction. Specifically, M-STAP considers the problem from three main aspec
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Sun, Che, Chenrui Shi, Yunde Jia, and Yuwei Wu. "Learning Event-Relevant Factors for Video Anomaly Detection." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 2 (2023): 2384–92. http://dx.doi.org/10.1609/aaai.v37i2.25334.

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Most video anomaly detection methods discriminate events that deviate from normal patterns as anomalies. However, these methods are prone to interferences from event-irrelevant factors, such as background textures and object scale variations, incurring an increased false detection rate. In this paper, we propose to explicitly learn event-relevant factors to eliminate the interferences from event-irrelevant factors on anomaly predictions. To this end, we introduce a causal generative model to separate the event-relevant factors and event-irrelevant ones in videos, and learn the prototypes of ev
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Melath Nalinakshan Nair, Binoj. "Optimizing Cloud Costs with Anomaly Detection and Event-Driven Automation." International Journal of Science and Research (IJSR) 14, no. 1 (2025): 533–36. https://doi.org/10.21275/sr25111050909.

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Nisa, A. R. Khairun, and Ivonne M. Radjawane. "Evolution of Subsurface Temperatures in West Sumatra - Southern Java Waters During 2010–2014 Indian Ocean Dipole Events." Jurnal Segara 17, no. 1 (2021): 57. http://dx.doi.org/10.15578/segara.v17i1.10202.

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The temperature anomaly formation in the West Sumatra and South Java Waters plays an important role in the formation of the Indian Ocean Dipole (IOD). There have not been many detailed studies on the evolution of temperature anomalies in the subsurface layers in the area during the IOD events. In this study, temperature data from the HYCOM were used to examine the evolution of temperature anomalies on the surface and subsurface in the event of negative IOD (nIOD) 2010 and positive IOD (pIOD) 2012). The analysis was done using a cross-section plot and a Hovmöller diagram. It has shown that in t
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Li, Zhong, and Matthijs van Leeuwen. "Feature Selection for Fault Detection and Prediction based on Event Log Analysis." ACM SIGKDD Explorations Newsletter 24, no. 2 (2022): 96–104. http://dx.doi.org/10.1145/3575637.3575652.

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Event logs are widely used for anomaly detection and prediction in complex systems. Existing log-based anomaly detection methods usually consist of four main steps: log collection, log parsing, feature extraction, and anomaly detection, wherein the feature extraction step extracts useful features for anomaly detection by counting log events. For a complex system, such as a lithography machine consisting of a large number of subsystems, its log may contain thousands of different events, resulting in abounding extracted features. However, when anomaly detection is performed at the subsystem leve
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Huang, Shaonian, Dongjun Huang, and Xinmin Zhou. "Learning Multimodal Deep Representations for Crowd Anomaly Event Detection." Mathematical Problems in Engineering 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/6323942.

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Anomaly event detection in crowd scenes is extremely important; however, the majority of existing studies merely use hand-crafted features to detect anomalies. In this study, a novel unsupervised deep learning framework is proposed to detect anomaly events in crowded scenes. Specifically, low-level visual features, energy features, and motion map features are simultaneously extracted based on spatiotemporal energy measurements. Three convolutional restricted Boltzmann machines are trained to model the mid-level feature representation of normal patterns. Then a multimodal fusion scheme is utili
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Attard, Hannah E., and Andrea L. Lang. "Troposphere–Stratosphere Coupling Following Tropospheric Blocking and Extratropical Cyclones." Monthly Weather Review 147, no. 5 (2019): 1781–804. http://dx.doi.org/10.1175/mwr-d-18-0335.1.

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Abstract A climatology of the 100- and 250-hPa 45°–75°N zonal-mean meridional eddy heat flux anomaly, hereafter heat flux anomaly, was created to examine its variability following cool-season (i.e., October–April) blocks and extratropical cyclones. The goal is to elucidate the dynamical and environmental differences between synoptic events followed by the most extreme heat flux anomalies. The analysis was conducted with the National Aeronautics and Space Administration’s Modern-Era Retrospective Analysis for Research and Applications, version 2 reanalysis. The results show that, on average, Eu
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Thore, Pierre D., and Corrine Juliard. "Fresnel zone effect on seismic velocity resolution." GEOPHYSICS 64, no. 2 (1999): 593–603. http://dx.doi.org/10.1190/1.1444566.

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For impedance, velocity resolution depends on Fresnel zone considerations. A change of velocity can be distinguished only if its size is greater than the Fresnel zone. This is demonstrated on synthesized examples where a single velocity anomaly is introduced in a homogeneous medium. (Although unrealistic, this model was designed to exhibit the physical phenomenon in its simplest configuration.) The presence of the velocity anomaly breaks the wavefront into two main parts. The first part, which travels through the anomaly, corresponds to the specular ray and gives rise to an event which we call
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Dai, Xuan, Jian Mao, Jiawei Li, Qixiao Lin, and Jianwei Liu. "HomeGuardian: Detecting Anomaly Events in Smart Home Systems." Wireless Communications and Mobile Computing 2022 (June 13, 2022): 1–11. http://dx.doi.org/10.1155/2022/8022033.

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As a typical application of Internet of Things (IoT), home automation systems, namely, smart homes, provide a more convenient and intelligent life experience through event recognition, automation control, and remote device access. However, smart home systems have also given rise to new complications for security issues. As an event-driven IoT system, smart home environments are vulnerable to security attacks, and vulnerable devices are far-spread due to the quick development cycles. Attack vectors to smart homes inevitably manifest in abnormal event contexts. In this paper, we propose HomeGuar
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Ye, Pengfei. "The Value of Active Investing: Can Active Institutional Investors Remove Excess Comovement of Stock Returns?" Journal of Financial and Quantitative Analysis 47, no. 3 (2012): 667–88. http://dx.doi.org/10.1017/s0022109012000099.

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AbstractThis study uses Cremers and Petajisto’s (2009) method to separate active institutional investors from passive ones and shows that active investors can alleviate the anomalous comovement of stock returns. Focusing on 2 events linked to the excess comovement anomaly, Standard & Poor’s 500 Index additions and stock splits, I find that if an event stock has more active institutional investors trading in the post-event period, the anomalous comovement effect disappears. In contrast, if an event stock experiences a massive exit of active investors, this anomaly persists. The exit of acti
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Dissertations / Theses on the topic "Event and anomaly"

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Amen, Bakhtiar. "Distributed contextual anomaly detection from big event streams." Thesis, University of Huddersfield, 2018. http://eprints.hud.ac.uk/id/eprint/34687/.

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The age of big digital data is emerged and the size of generating data is rapidly increasing in a millisecond through the Internet of Things (IoT) and Internet of Everything (IoE) objects. Specifically, most of today’s available data are generated in a form of streams through different applications including sensor networks, bioinformatics, smart airport, smart highway traffic, smart home applications, e-commerce online shopping, and social media streams. In this context, processing and mining such high volume of data stream becomes one of the research priority concern and challenging tasks. O
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Studiawan, Hudan. "Forensic investigation of event logs by automatic anomaly detection." Thesis, Studiawan, Hudan (2020) Forensic investigation of event logs by automatic anomaly detection. PhD thesis, Murdoch University, 2020. https://researchrepository.murdoch.edu.au/id/eprint/59418/.

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Attacks on an operating system have become a significant and increasingly common problem. This type of security incident is recorded in forensic artifacts, such as log files. Forensic investigators will generally examine the logs to analyze such incidents. An anomaly is highly correlated to an attacker's attempts to compromise the system. This thesis proposes a novel framework to automatically detect an anomaly in a forensic timeline constructed from log files. Before identifying anomalies, an automatic log parser is built so that the investigators do not need to define a rule-based parser. Pa
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Vendramin, Nicoló. "Unsupervised Anomaly Detection on Multi-Process Event Time Series." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254885.

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Establishing whether the observed data are anomalous or not is an important task that has been widely investigated in literature, and it becomes an even more complex problem if combined with high dimensional representations and multiple sources independently generating the patterns to be analyzed. The work presented in this master thesis employs a data-driven pipeline for the definition of a recurrent auto-encoder architecture to analyze, in an unsupervised fashion, high-dimensional event time-series generated by multiple and variable processes interacting with a system. Facing the above menti
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Klerx, Timo [Verfasser]. "Anomaly detection as a one-class problem in discrete event systems / Timo Klerx." Paderborn : Universitätsbibliothek, 2017. http://d-nb.info/1135258287/34.

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Li, Zongze. "Event Sequence Identification and Deep Learning Classification for Anomaly Detection and Predication on High-Performance Computing Systems." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1609172/.

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High-performance computing (HPC) systems continue growing in both scale and complexity. These large-scale, heterogeneous systems generate tens of millions of log messages every day. Effective log analysis for understanding system behaviors and identifying system anomalies and failures is highly challenging. Existing log analysis approaches use line-by-line message processing. They are not effective for discovering subtle behavior patterns and their transitions, and thus may overlook some critical anomalies. In this dissertation research, I propose a system log event block detection (SLEBD) met
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Chin, Philip Allen. "Sensor Networks: Studies on the Variance of Estimation, Improving Event/Anomaly Detection, and Sensor Reduction Techniques Using Probabilistic Models." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/33645.

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Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman opti
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Larroche, Corentin. "Network-wide intrusion detection through statistical analysis of event logs : an interaction-centric approach." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAT041.

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Les journaux d’événements sont des données structurées décrivant toutes sortes d’activités au sein d’un réseau informatique. En particulier, les comportements malveillants adoptés par d’éventuels attaquants sont susceptibles de laisser une trace dans ces journaux, rendant ces derniers utiles pour la supervision et la détection d’intrusion. Cependant, le volume considérable des journaux d’événements générés en production en rend l’analyse difficile. Cette problématique a suscité de nombreux travaux de recherche sur l’analyse statistique de journaux d’événements pour la détection d’intrusion.Cet
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Spedicato, Eugenia. "Fast simulation of the MUonE 2021 test run setup." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23207/.

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This thesis contributes to the study of the electromagnetic calorimeter performances and to the clarification of its role in the selection of mu-e elastic scattering events for the MUonE experiment.Together with the tracking system, the calorimeter constitutes the prototype detector for 2021 the Test Run(TR).One of the main proposals of this thesis is the development of the fast simulation for the calorimeter response, in the working condition expected in the TR.Given a generated set of NLO events, consisting in high energy muons scattering on electrons at rest with prefixed kinematical condit
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Conzemius, Robert John. "Stratospheric behavior during tropospheric persistent anomaly events." Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/51477.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1990.<br>Includes bibliographic references (p. 131-133).<br>by Robert John Conzemius.<br>M.S.
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Paxton, Leilani D. "Development of a Forecast Process for Meteotsunami Events in the Gulf of Mexico." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6564.

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The purpose of this research was to provide a better understanding of meteotsunamis over the eastern Gulf of Mexico along the west coast of Florida and to develop a process for forecasting those events. Meteotsunami waves develop from resonant effects of strong pressure perturbations greater than 1 hPa, moving in excess of 10 m s-1, over water areas up to around 100 m in depth. Meteotsunami events over 0.3 m in height, as measured by three primary NOAA coastal tide gauges at Cedar Key, Clearwater Beach, and Naples, from 2007-2015, impact the Florida Gulf coastline several times per year and ar
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Books on the topic "Event and anomaly"

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Anomaly Detection and Complex Event Processing over IoT Data Streams. Elsevier, 2022. http://dx.doi.org/10.1016/c2020-0-00589-x.

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Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to Electrocardiogram Patient Data Monitoring. Elsevier Science & Technology, 2022.

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Xhafa, Fatos, and Patrick Schneider. Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to EHealth and Patient Data Monitoring. Elsevier Science & Technology Books, 2022.

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Martin, Colin. Wreck-Site Formation Processes. Edited by Ben Ford, Donny L. Hamilton, and Alexis Catsambis. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199336005.013.0002.

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The environmental settings within which shipwrecks occur are matters of chance rather than of choice. It is primarily the wreck and not its physical context that is of consequence to nautical archaeologists. No two wreck-site formations are the same, since the complex and interacting variables that constitute the environmental setting, the nature of the ship, and the circumstances of its loss combine to create a set of attributes unique to each site. The dynamic phase, which begins with the event of shipwreck, is characterized by the wreck's status as an environmental anomaly. It is unstable,
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Behera, Swadhin, and Toshio Yamagata. Climate Dynamics of ENSO Modoki Phenomena. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.612.

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The El Niño Modoki/La Niña Modoki (ENSO Modoki) is a newly acknowledged face of ocean-atmosphere coupled variability in the tropical Pacific Ocean. The oceanic and atmospheric conditions associated with the El Niño Modoki are different from that of canonical El Niño, which is extensively studied for its dynamics and worldwide impacts. A typical El Niño event is marked by a warm anomaly of sea surface temperature (SST) in the equatorial eastern Pacific. Because of the associated changes in the surface winds and the weakening of coastal upwelling, the coasts of South America suffer from widespre
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Duquette, Jerold J. Regulating the National Pastime. Greenwood Publishing Group, Inc., 1999. http://dx.doi.org/10.5040/9798216188322.

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Major League Baseball, alone among industries of its size in the United States, operates as an unregulated monopoly. This 20th-century regulatory anomaly has become known as the baseball anomaly. Major League Baseball developed into a major commercial enterprise without being subject to antitrust liability. Long after the interstate commercial character of baseball had been established and even recognized by the Supreme Court, baseball's monopoly remained free from federal regulation. Duquette explains the baseball anomaly by connecting baseball's regulatory status to the larger political envi
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Rasula, Jed. Genre and Extravagance in the Novel. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192897763.001.0001.

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This book addresses an anomaly in the novel as genre: the generic promise to readers—that “reading a novel” is a familiar and repeatable experience—is challenged by the extravagant exceptions to this rule. Furthermore, these exceptions (like Moby-Dick, Ulysses, or To the Lighthouse) are sui generis, hybrid concoctions that cannot be said to be typical novels. The novel, then, as literary form, succeeds by extravagantly disregarding or even disavowing the protocols of its own genre. Examining a number of famous examples from Don Quixote to Nostromo, this book offers an anatomy of exceptions tha
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Wisman, Jon D. The Origins and Dynamics of Inequality. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197575949.001.0001.

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Whereas President Barack Obama identified inequality as “the defining challenge of our time,” this book claims more: it is the defining issue of all human history. The struggle over inequality has been the underlying force driving human history’s unfolding. Drawing on the dynamics of inequality, this book reinterprets history and society. Beyond according inequality the central role in human history, this book is novel in two other respects. First, transcending the general failure of social scientists and historians to anchor their work in explicit theories of human behavior, this book grounds
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and, Bruno. Synaesthesia. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198725022.003.0006.

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Synaesthesia is a curious anomaly of multisensory perception. When presented with stimulation in one sensory channel, in addition to the percept usually associated with that channel (inducer) a true synaesthetic experiences a second percept in another perceptual modality (concurrent). Although synaesthesia is not pathological, true synaesthetes are relatively rare and their synaesthetic associations tend to be quite idiosyncratic. For this reason, studying synaesthesia is difficult, but exciting new experimental results are beginning to clarify what makes the brain of synaesthetes special and
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Plummer, Marjorie Elizabeth. Stripping the Veil. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192857286.001.0001.

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Protestant nuns and mixed-confessional convents are an unexpected anomaly in early modern Germany. According to sixteenth-century evangelical reformers’ theological positions outlined in their publications and reform-minded rulers’ institutional efforts, monastic life in Protestant regions should have ended by the mid-sixteenth century. Instead, many convent congregations exhibiting elements of traditional and evangelical practices in Protestant regions survived into the seventeenth century and beyond. How did these convents survive? What is a Protestant nun? How many convent congregations cam
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Book chapters on the topic "Event and anomaly"

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Bai, Xue, Yun Xiong, Yangyong Zhu, Qi Liu, and Zhiyuan Chen. "Co-anomaly Event Detection in Multiple Temperature Series." In Knowledge Science, Engineering and Management. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39787-5_1.

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Abb, Luka, and Jana-Rebecca Rehse. "Multivariate Anomaly Detection in Object-Centric Event Data." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70418-5_2.

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Sowmia, B., and G. Suseendran. "Anomaly Detection in Business Process Event Using KNN Algorithm." In Intelligent Computing and Innovation on Data Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3153-5_22.

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Qu, Yi, Yixuan Zhou, and Guofeng Yi. "ECD: Event-Centric Disentangler for Weakly Supervised Video Anomaly Detection." In Communications in Computer and Information Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2911-4_19.

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Lahann, Johannes, Peter Pfeiffer, and Peter Fettke. "LSTM-Based Anomaly Detection of Process Instances: Benchmark and Tweaks." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_17.

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AbstractAnomaly detection can identify deviations in event logs and allows businesses to infer inconsistencies, bottlenecks, and optimization opportunities in their business processes. In recent years, various anomaly detection algorithms for business processes have been proposed based on either process discovery or machine learning algorithms. While there are apparent differences between machine learning and process discovery approaches, it is often unclear how they perform in comparison. Furthermore, deep learning research in other domains has shown that advancements did not solely come from
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Landthaler, Jörg, Martin Kleehaus, and Florian Matthes. "Multi-Level Event and Anomaly Correlation Based on Enterprise Architecture Information." In Lecture Notes in Business Information Processing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49454-8_4.

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Guo, Hongcheng, Yuhui Guo, Jian Yang, et al. "LogLG: Weakly Supervised Log Anomaly Detection via Log-Event Graph Construction." In Database Systems for Advanced Applications. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30678-5_36.

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Ishikawa, Yosuke, Tomomi Sato, Kenji Iwata, and Yutaka Satoh. "Anomaly Detection Through Remote Vibration Measurement Using Neuromorphic Event-Based Camera." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-93965-5_16.

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Musaj, Zyrako, and Marwan Hassani. "Unsupervised Anomaly Detection of Prefixes in Event Streams Using Online Autoencoders." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81375-7_6.

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Kohlschmidt, Christian, Mahnaz Sadat Qafari, and Wil M. P. van der Aalst. "Detecting Surprising Situations in Event Data." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_16.

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AbstractProcess mining is a set of techniques that are used by organizations to understand and improve their operational processes. The first essential step in designing any process reengineering procedure is to find process improvement opportunities. In existing work, it is usually assumed that the set of problematic process instances in which an undesirable outcome occurs is known prior or is easily detectable. So the process enhancement procedure involves finding the root causes and the treatments for the problem in those process instances. For example, the set of problematic instances is c
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Conference papers on the topic "Event and anomaly"

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Amin, Omnia Osama, Walid M. Abdelmoez, and Mohamed Shaheen. "Anomaly Detection of Object-Centric Event Logs Using Event Knowledge Graph." In 2024 34th International Conference on Computer Theory and Applications (ICCTA). IEEE, 2024. https://doi.org/10.1109/iccta64612.2024.10974779.

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Sharma, Manisha, and Ravindra Purwar. "Anomaly Event Detection Using Isolation Forest on Surveillance Videos." In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). IEEE, 2024. https://doi.org/10.1109/globalaisummit62156.2024.10947967.

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Nguyen, Huy-Trung, Hai-Viet Le, Bui Khac Minh, Pham Van Huan, and Nguyen Hong Anh Tan. "Towards an Approach for Representing Log Event in Anomaly Detection." In 2024 International Conference on Expert Clouds and Applications (ICOECA). IEEE, 2024. http://dx.doi.org/10.1109/icoeca62351.2024.00030.

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Talasari, Resky Ayu Dewi, Hudan Studiawan, and Baskoro Adi Pratomo. "Normality Shift Identification for Anomaly Detection of Windows Event Logs." In 2024 7th International Conference on Information and Communications Technology (ICOIACT). IEEE, 2024. https://doi.org/10.1109/icoiact64819.2024.10913014.

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Kabir, Shaharier, Hridoy Paul, Md Samin Anjum, and Md Saniat Rahman Zishan. "Event and Anomaly Detection and Classification in Cyber-Physical Power System." In 2025 4th International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST). IEEE, 2025. https://doi.org/10.1109/icrest63960.2025.10914408.

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Li, Cheng, Guang Chen, Xiaoxi Mi, Yucheng Zhang, and Hongwei Zhou. "SeLog: A Log Anomaly Detection Method on Log Event and Variable Semantic." In 2024 IEEE 7th International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2024. https://doi.org/10.1109/iciscae62304.2024.10761356.

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Band, Saurabh, and Anna Foerster. "(POSTER) Navigating the Unknown: Anomaly Detection in Sensor Nodes Based on Event Traces." In 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE, 2024. http://dx.doi.org/10.1109/dcoss-iot61029.2024.00115.

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Nyyssölä, Jesse, and Mika Mäntylä. "Event-level Anomaly Detection on Software logs: Role of Algorithm, Threshold, and Window Size." In 2024 IEEE 24th International Conference on Software Quality, Reliability and Security (QRS). IEEE, 2024. http://dx.doi.org/10.1109/qrs62785.2024.00070.

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Marah, Hussein, Lucas Lima, Hans Vangheluwe, and Moharram Challenger. "An Agent-Oriented Twinning Architecture for Complex Event-Driven Anomaly Detection in Distributed CPS." In 2025 IEEE 22nd International Conference on Software Architecture Companion (ICSA-C). IEEE, 2025. https://doi.org/10.1109/icsa-c65153.2025.00040.

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Vidhya, B., V. Malathy, Piyush Kumar Pareek, Haider Alabdeli, and Javvadi Lakshmi Prasanna. "Anomaly Event Detection and Classification Using Deep Learning Model and Deep Double Q-learning Network." In 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON). IEEE, 2024. http://dx.doi.org/10.1109/nmitcon62075.2024.10698864.

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Reports on the topic "Event and anomaly"

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Farber, Jacob, Ahmad Al Rashdan, Hany Abdel-Khalik, et al. Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/2332982.

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O’Malley, Eoin. Ireland After the 2024 EP Elections: The Centre Holds … Just About. European Center for Populism Studies (ECPS), 2024. http://dx.doi.org/10.55271/rp0074.

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The 2024 European Parliament elections in Ireland came on the back of a rise in the prominence of immigration as an issue. Although Ireland had seen significant migration in the early to mid-2000s, the large number of migrants at this time had no significant impact on politics or voting. Nor was Ireland a country that saw any significant anti-EU sentiment. Thus, Ireland could be seen as an anomaly in Europe. In the aftermath of the COVID-19 pandemic, there was a sudden rise in the numbers in Ireland seeking international protection (asylum seekers). Most of these came as a direct result of the
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Shrestha, Sarthak, and Manish Shrestha. Hindu Kush Himalaya (HKH) monsoon outlook 2025. International Centre for Integrated Mountain Development (ICIMOD), 2025. https://doi.org/10.53055/icimod.1091.

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The Hindu Kush Himalaya (HKH) region is highly susceptible to the influence of monsoon, a periodic wind system, especially in the Indian Ocean and southern Asia. The summer monsoon, between June and September, is the major source of precipitation in the region with significant impacts on the hydrology of its rivers, which form the lifeline of nearly two billion people in the region. While a good monsoon is essential for replenishing these river systems, malevolence of water-related disasters such as floods, landslides, storms, heat waves, wildfires, droughts, glacial lake outburst floods (GLOF
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Sheets, Colton. PR-201-154500-R01 Composite Repair Load Transfer Study. Pipeline Research Council International, Inc. (PRCI), 2018. http://dx.doi.org/10.55274/r0011468.

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The objective of the PRCI MATR-3-11 Composite Repair Load Transfer Study was to evaluate the effect of internal pipe pressure during installation of composite reinforcement systems. Historically, there has been little work evaluating the effect of internal pressure during installation, even though almost all composite installations on transmission pipelines are performed with internal pressure present in the pipe. The focus of this work was specifically limited to reinforcement of pipelines containing simulated corrosion anomalies. Five composite repair technologies from four composite manufac
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