Relevant bibliographies by topics / Anomaly reasoning

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Anomaly reasoning'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Anomaly reasoning"

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Naguib, Mohamed, Sorin J. Brull, and Hal R. Arkes. "Reasoning of an Anomaly." Anesthesia & Analgesia 117, no. 2 (August 2013): 297–300. http://dx.doi.org/10.1213/ane.0b013e318292ee3c.

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Fauzi, Arwin Happy Nur, and Masduki Masduki. "Student’s Anomaly Reasoning in Solving Number Pattern in terms of Gender." Jurnal Didaktik Matematika 9, no. 2 (October 31, 2022): 328–42. http://dx.doi.org/10.24815/jdm.v9i2.27146.

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Relational reasoning plays an important role in helping students to understand mathematical concepts. The student's ability to distinguish patterns or objects is one of the understandings of mathematical concept indicators. The anomaly dimension is part of the relational reasoning that students need to be able to determine a pattern or object in mathematics. This study aims to reveal the student's relational reasoning ability of anomaly dimension in solving number pattern problems in terms of gender differences. The subjects of this study are 52 grade-8 students in one of Muhammadiyah Junior High Schools in Kartasura. We used two similar problems on number patterns to disclose the student's ability to identify the pattern deviation in solving problems. The two selected students had relatively similar in their mathematical abilities. The finding showed that female subject met the three anomaly dimension indicators: identification, interpretation, and adaptation. Conversely, male student cannot fulfill the anomaly indicators. He cannot recognize pattern deviation in the formed mathematical model. He also failed to identify a pattern different from the two problems. Although the subjects interviewed were limited, the finding provided the insightful into the differences in anomaly reasoning abilities in male and female students
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Samaan, Nancy, and Ahmed Karmouch. "Network anomaly diagnosis via statistical analysis and evidential reasoning." IEEE Transactions on Network and Service Management 5, no. 2 (June 2008): 65–77. http://dx.doi.org/10.1109/tnsm.2008.021103.

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Zaheer, Muhammad Zaigham, Arif Mahmood, Hochul Shin, and Seung-Ik Lee. "A Self-Reasoning Framework for Anomaly Detection Using Video-Level Labels." IEEE Signal Processing Letters 27 (2020): 1705–9. http://dx.doi.org/10.1109/lsp.2020.3025688.

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Jaunzemis, Andris D., Marcus J. Holzinger, and K. Kim Luu. "Sensor Tasking for Spacecraft Custody Maintenance and Anomaly Detection Using Evidential Reasoning." Journal of Aerospace Information Systems 15, no. 3 (March 2018): 131–56. http://dx.doi.org/10.2514/1.i010584.

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Jungck, John R. "Reasoning in biological discoveries: Essays of mechanisms, interfield relations, and anomaly resolution." Science Education 91, no. 5 (September 2007): 844–45. http://dx.doi.org/10.1002/sce.20229.

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Sun, De Gang, Kun Yang, Xiang Jing, Bin Lv, and Yan Wang. "Abnormal Network Traffic Detection Based on Conditional Event Algebra." Applied Mechanics and Materials 644-650 (September 2014): 1093–99. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1093.

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Network anomaly traffic detection can discover network abnormal behavior and unknown network attacks. But anomaly detection system in current has the disadvantage of the high rate of false positives. Because the condition is not sufficient and high-order conditional reasoning cannot be computed, it leads inaccurate detection of abnormal behavior. In this paper, an analysis method for abnormal network traffic detection is presented. The method firstly applied conditional event algebra for abnormal network traffic detection of Denial-of-Service (DoS) attacks on the 10% trainset of KDD Cup 99 data set. Neptune attack, as an instance of DoS attacks, is used to illustrate this method. Firstly of all, introducing analyzes the attack process of neptune attack. Then, Selecting the most related features of neptune attack on KDD Cup 99 data set and summarizes the basic flow chart of neptune attack. Finally, applying this method for detection of Neptune attack, it can be found that this method can handle with high-order conditional reasoning under insufficient situation, and detect network abnormal behavior.
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ABE, MITSUO, and NOBORU NAKANISHI. "EXACT SOLUTIONS TO THE TWO-DIMENSIONAL BF AND YANG–MILLS THEORIES IN THE LIGHT-CONE GAUGE." International Journal of Modern Physics A 17, no. 11 (April 30, 2002): 1491–502. http://dx.doi.org/10.1142/s0217751x02009825.

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It is shown that the BRS (= Becchi–Rouet–Stora)-formulated two-dimensional BF theory in the light-cone gauge (coupled with chiral Dirac fields) is solved very easily in the Heisenberg picture. The structure of the exact solution is very similar to that of the BRS-formulated two-dimensional quantum gravity in the conformal gauge. In particular, the BRS Noether charge has anomaly. Based on this fact, a criticism is made on the reasoning of Kato and Ogawa, who derived the critical dimension D=26 of string theory on the basis of the anomaly of the BRS Noether charge. By adding the [Formula: see text] term to the BF-theory Lagrangian density, the exact solution to the two-dimensional Yang–Mills theory is also obtained.
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Efendi, Erfan, and Abd Rozzaq. "Nalar Atensi Pemilihan Perguruan Tinggi Islam di Program Studi FTIK UIN K.H Achmad Shiddiq Jember." Scaffolding: Jurnal Pendidikan Islam dan Multikulturalisme 4, no. 2 (August 30, 2022): 531–48. http://dx.doi.org/10.37680/scaffolding.v4i2.1721.

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The distinction between public and religious campuses often occurs in the community, the dividing barrier between the two has implications for the favorite attention of the nation's generation in choosing universities, and campuses based on religion are always superior. However, in the traces of developments at the State Islamic University KH. Achmad Siddiq has made significant progress every year, and the increasing interest of prospective students is forced to reject many applicants. It is the main attraction of this research for Then answer how the progress occurred. This research is a type of qualitative research, as a bridge so that the results are more in-depth the author will use integrative theory and approach the problem above with a psycho-sociological approach. The focuses that will be studied include; How is the pre-attention anomaly of new students in the Faculty of Tarbiyah and Teacher Training at UIN Jember? What is the process of reasoning? And the new paradigm of attention is developing? The results showed that the attention paradigm that emerged was the reasoning that was built after the anomaly and crisis in the selection of Islamic universities, there were three adjustment processes, namely economical commensurability, formal education commensurability, and moral commensurability. All three are carried out using a negotiation process of general expectations and the impact of anomalies which are believed to be a necessity of the era.
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Al Rashdan, Ahmad Y., Hany S. Abdel-Khalik, Kellen M. Giraud, Daniel G. Cole, Jacob A. Farber, William W. Clark, Abenezer Alemu, Marcus C. Allen, Ryan M. Spangler, and Athi Varuttamaseni. "A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection." Energies 15, no. 15 (August 3, 2022): 5640. http://dx.doi.org/10.3390/en15155640.

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To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.
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Dissertations / Theses on the topic "Anomaly reasoning"

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Riveiro, María José. "Visual analytics for maritime anomaly detection." Doctoral thesis, Örebro universitet, Akademin för naturvetenskap och teknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-12783.

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The surveillance of large sea areas typically involves  the analysis of huge quantities of heterogeneous data.  In order to support the operator while monitoring maritime traffic, the identification of anomalous behavior or situations that might need further investigation may reduce operators' cognitive load. While it is worth acknowledging that existing mining applications support the identification of anomalies, autonomous anomaly detection systems are rarely used for maritime surveillance. Anomaly detection is normally a complex task that can hardly be solved by using purely visual or purely computational methods. This thesis suggests and investigates the adoption of visual analytics principles to support the detection of anomalous vessel behavior in maritime traffic data. This adoption involves studying the analytical reasoning process that needs to be supported,  using combined automatic and visualization approaches to support such process, and evaluating such integration. The analysis of data gathered during interviews and participant observations at various maritime control centers and the inspection of video recordings of real anomalous incidents lead to a characterization of the analytical reasoning process that operators go through when monitoring traffic. These results are complemented with a literature review of anomaly detection techniques applied to sea traffic. A particular statistical-based technique is implemented, tested, and embedded in a proof-of-concept prototype that allows user involvement in the detection process. The quantitative evaluation carried out by employing the prototype reveals that participants who used the visualization of normal behavioral models outperformed the group without aid. The qualitative assessment shows that  domain experts are positive towards providing automatic support and the visualization of normal behavioral models, since these aids may reduce reaction time, as well as increase trust and comprehensibility in the system. Based on the lessons learned, this thesis provides recommendations for designers and developers of maritime control and anomaly detection systems, as well as guidelines for carrying out evaluations of visual analytics environments.
Maria Riveiro is also affiliated to Informatics Research Centre, Högskolan i Skövde
Information Fusion Research Program, Högskolan i Skövde
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Eckroth, Joshua Ryan. "Anomaly-Driven Belief Revision by Abductive Metareasoning." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397557509.

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Kronberg, F., A. Weiner, T. Morgan, B. Stroozas, E. Girouard, A. Hopkins, L. Wong, M. James, J. Kneubuhl, and R. F. Malina. "Document Retrieval Triggered by Spacecraft Anomaly: Using the Kolodner Case-Based Reasoning (CBR) Paradigm to Design a Fault-Induced Response System." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/611459.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California
We report on the initial design and development of a prototype computer-mediated response system, the Fault Induced Document Officer (FIDO), at the UC Berkeley Center for EUV Astrophysics (CEA) Extreme Ultraviolet Explorer project (EUVE). Typical 24x7 staffed spacecraft operations use highly skilled expert teams to monitor current ground systems and spacecraft state for responding to anomalous ground system and spacecraft conditions. Response to ground system error messages and spacecraft anomalies is based on knowledge of nominal component behavior and the evaluation of relevant telemetry by the team. This type of human-mediated operation is being replaced by an intelligent software system to reduce costs and to increase performance and reliability. FIDO is a prototype software application that will provide automated retrieval and display of documentation for operations staff. Initially, FIDO will be applied for ground systems. Later implementations of FIDO will target spacecraft systems. FIDO is intended to provide system state summary, links to relevant documentation, and suggestions for operator responses to error messages. FIDO will provide the operator with near realtime expert assistance and access to necessary information. This configuration should allow the resolution of many anomalies without the need for on-site intervention by a skilled controller or expert.
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Books on the topic "Anomaly reasoning"

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. Cambridge University Press, 2006.

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. Cambridge University Press, 2006.

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. Cambridge University Press, 2009.

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. Cambridge University Press, 2006.

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. Cambridge University Press, 2006.

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. Cambridge University Press, 2009.

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Darden, Lindley. Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution (Cambridge Studies in Philosophy and Biology). Cambridge University Press, 2006.

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Book chapters on the topic "Anomaly reasoning"

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Zhang, Kehan, Xiaoqiang Di, Xu Liu, Bo Li, Luyue Fang, Yiping Qin, and Jinhui Cao. "LogLR: A Log Anomaly Detection Method Based on Logical Reasoning." In Wireless Algorithms, Systems, and Applications, 489–500. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19214-2_41.

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Eyorokon, Vahid B., Pratyusha Yalamanchili, and Michael T. Cox. "Tangent Recognition and Anomaly Pruning to TRAP Off-Topic Questions in Conversational Case-Based Dialogues." In Case-Based Reasoning Research and Development, 95–109. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01081-2_7.

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Hammer, Patrick, Tony Lofthouse, Enzo Fenoglio, Hugo Latapie, and Pei Wang. "A Reasoning Based Model for Anomaly Detection in the Smart City Domain." In Advances in Intelligent Systems and Computing, 144–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55187-2_13.

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Xu, Jie, and Jiantao Zhou. "A Fine-Grained Anomaly Detection Method Fusing Isolation Forest and Knowledge Graph Reasoning." In Web Information Systems and Applications, 135–42. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20309-1_12.

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Sharma, Pulkit, Shezan Rohinton Mirzan, Apurva Bhandari, Anish Pimpley, Abhiram Eswaran, Soundar Srinivasan, and Liqun Shao. "Evaluating Tree Explanation Methods for Anomaly Reasoning: A Case Study of SHAP TreeExplainer and TreeInterpreter." In Lecture Notes in Computer Science, 35–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65847-2_4.

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Corneli, Alessandra, Leonardo Binni, Berardo Naticchia, and Massimo Vaccarini. "Digital Twin Models Supporting Cognitive Buildings for Ambient Assisted Living." In The Urban Book Series, 167–78. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29515-7_16.

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AbstractThe rapid and global aging of population is outlining the need for environments that can provide support for these individuals during their daily activities. The challenge of an aging society is being addressed through the incorporation of new technologies into the home environment, which is nothing less than Ambient Assisted Living (AAL). To date, some of the AAL solutions exploit AI models to recognize the elderly’s behaviors through data collected by sensors. In recent times, Digital Twins (DTs) at building level have begun to appear on the construction domain. These are still under development but through the integration of users into assessments, they improve efficiency, prevention, and prediction of likely events through real-time AI computing. The integration of DT and AAL defines cognitive buildings which aim to learn at scale, reason with a purpose, and co-operate with users in a natural way. This research aims to develop DT models to achieve scenario awareness to provide support to elderly people living alone and suffering from cognitive disorders. The proposed multi-agent architecture is based on a five-layer system that autonomously develops high-level knowledge to detect anomalies in the home environment scenarios and therefore support the user. Bayesian networks (BNs) are exploited to perform high-level deductive reasoning on low-level multi-modal information, thus recognizing senseless or dangerous behaviors, environmental disruptions, changes in behavioral patterns, and serious medical events. Bi-directional user-system interaction provides user support by leveraging Speech-To-Text and Text-To-Speech AI agents. Three main functions were tested: real-time data integration, anomaly detection, and two-way interaction.
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Makhlouf, Amel Meddeb, and Noureddine Boudriga. "Intrusion and Anomaly Detection in Wireless Networks." In Handbook of Research on Wireless Security, 78–94. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-899-4.ch006.

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The broadcast nature of wireless networks and the mobility features created new kinds of intrusions and anomalies taking profit of wireless vulnerabilities. Because of the radio links and the mobile equipment features of wireless networks, wireless intrusions are more complex because they add to the intrusions developed for wired networks, a large spectrum of complex attacks targeting wireless environment. These intrusions include rogue or unauthorized access point (AP), AP MAC spoofing, and wireless denial of service and require adding new techniques and mechanisms to those approaches detecting intrusions targeting wired networks. To face this challenge, some researchers focused on extending the deployed approaches for wired networks while others worked to develop techniques suitable for detecting wireless intrusions. The efforts have mainly addressed: (1) the development of theories to allow reasoning about detection, wireless cooperation, and response to incidents; and (2) the development of wireless intrusion and anomaly detection systems that incorporate wireless detection, preventive mechanisms and tolerance functions. This chapter aims at discussing the major theories, models, and mechanisms developed for the protection of wireless networks/systems against threats, intrusions, and anomalous behaviors. The objectives of this chapter are to: (1) discuss security problems in a wireless environment; (2) present the current research activities; (3) study the important results already developed by researchers; and (4) discuss the validation methods proposed for the protection of wireless networks against attacks.
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Conference papers on the topic "Anomaly reasoning"

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Carter, Kevin M., and William W. Streilein. "Probabilistic reasoning for streaming anomaly detection." In 2012 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2012. http://dx.doi.org/10.1109/ssp.2012.6319708.

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Sun, Che, Yunde Jia, and Yuwei Wu. "Evidential Reasoning for Video Anomaly Detection." In MM '22: The 30th ACM International Conference on Multimedia. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3503161.3548091.

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Saleh, Babak, Ali Farhadi, and Ahmed Elgammal. "Object-Centric Anomaly Detection by Attribute-Based Reasoning." In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.107.

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Ramachandran, Sowmya, and Christian Belardi. "Case-Based Reasoning for System Anomaly Detection and Management." In 2021 IEEE Aerospace Conference. IEEE, 2021. http://dx.doi.org/10.1109/aero50100.2021.9438252.

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Vandecasteele, Arnaud, and Aldo Napoli. "An enhanced spatial reasoning ontology for maritime anomaly detection." In 2012 7th International Conference on System of Systems Engineering (SoSE). IEEE, 2012. http://dx.doi.org/10.1109/sysose.2012.6384120.

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Ren, Wenyu, Tuo Yu, Timothy Yardley, and Klara Nahrstedt. "CAPTAR: Causal-Polytree-based Anomaly Reasoning for SCADA Networks." In 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, 2019. http://dx.doi.org/10.1109/smartgridcomm.2019.8909766.

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Trifunov, Violeta Teodora, Maha Shadaydeh, Bjorn Barz, and Joachim Denzler. "Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning." In 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2021. http://dx.doi.org/10.1109/icmla52953.2021.00033.

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Chen, Qiuwen, Qing Wu, Morgan Bishop, Richard Linderman, and Qinru Qiu. "Self-structured confabulation network for fast anomaly detection and reasoning." In 2015 International Joint Conference on Neural Networks (IJCNN). IEEE, 2015. http://dx.doi.org/10.1109/ijcnn.2015.7280371.

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Li, Fei, Guowen Zhou, Xingshuo Li, Linhai Zhu, and Hongzhi Wang. "A symbolic reasoning based anomaly detection for gas turbine subsystems." In 2017 Prognostics and System Health Management Conference (PHM-Harbin). IEEE, 2017. http://dx.doi.org/10.1109/phm.2017.8079230.

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Riveiro, Maria, and Göran Falkman. "Supporting the Analytical Reasoning Process in Maritime Anomaly Detection: Evaluation and Experimental Design." In 2010 14th International Conference Information Visualisation (IV). IEEE, 2010. http://dx.doi.org/10.1109/iv.2010.34.

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Reports on the topic "Anomaly reasoning"

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Muchnik, Ilya B., William M. Pottenger, and Nikita I. Lytkin. Anomaly Detection by Reasoning from Evidence in Mobile Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, August 2008. http://dx.doi.org/10.21236/ada501011.

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