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Добірка наукової літератури з теми "Anomaly patterns"

Автор: Grafiati

Опубліковано: 10 січня 2023

Оновлено: 28 січня 2023

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Статті в журналах з теми "Anomaly patterns"

Ilahude, Delyuzar. "MAGNETIC ANOMALY PATTERNS USING TREND SURFACE ANALYSIS APPLICATION (TSA) ON MARINE GEOLOGY MAPPING IN THE BALIKPAPAN WATERS." BULLETIN OF THE MARINE GEOLOGY 27, no. 1 (February 15, 2016): 19. http://dx.doi.org/10.32693/bomg.27.1.2012.42.

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The application of Trend Surface Analysis (TSA) method an geological and geophysical research in map sheets 1813-1814, Balikpapan Waters and its surrounding, shows the significant value of residual anomaly. The magnetic disseverance of regional and total anomaly value obtained the negative anomaly between -50 nT and -350 nT and positive anomaly between +50 nT and +400 nT. The contour of total and regional anomaly shows the magnetic properties of rocks which characterizes the geological arrangements of the research areas. Residual anomaly yielded from the 2nd order value of regional anomaly might be correlated with the formation of basin structures in the central and northern parts of research area, which is interpreted as a part of Kutai Basin. Keywords : TSA method, magnetic anomaly, geology and geophisics, Balikpapan Waters. Penerapan metode TSA dalam penelitian geologi dan geofisika di Lembar Peta 1813-1814, Perairan Balikpapan dan sekitarnya menunjukkan nilai anomali sisa yang cukup signifikan. Hasil pemisahan nilai anomali magnet regional dan anomaly total diperoleh nilai anomali yaitu antara -50 nT dan â€“350 nT dan anomali positif antara +50 nT dan +400 nT. Kontur anomali total dan anomali regional memperlihatkan sifat kemagnitan batuan yang mencirikan tatanan geologi daerah penelitian. Anomali sisa dihasilkan dari nilai anomali regional orde ke 2, kemungkinan berkaitan dengan pembentukan struktur cekungan di bagian tengah dan utara daerah penelitian yang ditafsirkan sebagai bagian dari Cekungan Kutai. Kata kunci : metode TSA, anomali magnet, geologi dan geofisika, Perairan Balikpapan.

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Subagio, Subagio, and Tatang Patmawidjaya. "POLA ANOMALI BOUGUER DAN ANOMALI MAGNET DAN KAITANNYA DENGAN PROSPEK SUMBER DAYA MINERAL DAN ENERGI DI PULAU LAUT, PULAU SEBUKU DAN SELAT SEBUKU, KALIMANTAN SELATAN." JURNAL GEOLOGI KELAUTAN 11, no. 3 (February 16, 2016): 115. http://dx.doi.org/10.32693/jgk.11.3.2013.236.

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Anomali Bouguer Pulau Laut, Pulau Sebuku, dan Selat Sebuku dapat dikelompokkan menjadi dua wilayah anomali meliputi anomali berpola melingkar dengan kisaran nilai dari 40 hingga 64 mGal, dan anomali berpola lurus dengan kisaran nilai 40 hingga 50 mGal. Anomali magnet di daerah ini bervariasi dari -700 hingga 1600 nT, membentuk pola tinggian dan rendahan. Anomali Bouguer berpola melingkar dengan kisaran nilai 45-64 mGal mencerminkan batuan ultrabasa yang relatif mendekati permukaan. Batuan ultrabasa yang tersingkap di permukaan dicirikan oleh anomali magnet tinggi. Anomali Bouguer berpola kontur lurus sejajar menunjukkan sesar naik maupun sesar turun yang terdapat di daerah tersebut. Sesar naik yang berkembang di daerah penelitian umumnya terdapat di Pegunungan Meratus yang mempunyai mendala geologi sama. Anomali Bouguer dan anomali magnet rendah mencerminkan cekungan sedimen. yang diakibatkan oleh adanya gaya tarikan yang pernah ada. Batuan terobosan yang dijumpai, diduga terbentuk bersamaan dengan periode gaya tarikan ini. Serangkaian proses tektonik yang hasilnya terekam pada anomali Bouguer, anomali magnet, dan singkapan batuan memberi implikasi kemungkinan terdapatnya sumber daya energi dan mineral di daerah penelitian. Mineralisasi logam diperkirakan dapat dijumpai di sekitar daerah terobosan. Bijih besi, nikel, dan kromit kemungkinan terdapat di daerah ultra-mafik, sedangkan batubara di daerah cekungan sedimen. Kata kunci : Anomali Bouguer, anomali magnet, sumber daya energi dan mineral, sesar naik dan sesar turun. Bouguer anomaly of the Laut Island, Sebuku Island, and The Sebuku Strait can be grouped into two anomaly groups covering the circular pattern anomaly with range from 40 to 64 mGals, and the straight pattern with range of values from 40 to 50 mGals. The range of magnetic anomalies in the study area area from -700 to 1600 nT, forming high and low anomay patterns. The circular pattern of the Bouguer anomalies with range from 45 to 64 mGals reflects that the ultramafic rocks relatively close to the surface, while exposed ultrabasic rocks are indicated by high magnetic anomalies. Paralled pattern contour of Bouguer anomaly show a thrust faults and normal faults in this area. Thrust faults of commonly develop in Meratus Mountaint that has the same geological setting. The low Bouguer and magnetic anomalies reflect a sedimentary basin caused by previous tensional force. The intrusion rocks found in the study area suggest to be formed together with this tensional force period. A series of tectonic events recorded in Bougue anomaly, magnetic anomaly, and out crops gave the implication the possibility the present of energy and mineral resources in the study area. Metal mineralization suggests to be found in the intrusion area. Irons, nickels and chromites supposed can be found in the ulta-mafic area, while coal can be found in the sedimentary basin. Keywords : Bouguer anomalies, magnetic anomalies, energy and mineral resources, thrust and normal faults.

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Peck, Sheldon. "Dental Anomaly Patterns (DAP)." Angle Orthodontist 79, no. 5 (September 1, 2009): 1015–16. http://dx.doi.org/10.2319/0003-3219-079.005.1015.

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Czeizel, Andrew, John M. Optiz, and James F. Reynolds. "Additive congenital anomaly patterns." American Journal of Medical Genetics 29, no. 4 (April 1988): 727–38. http://dx.doi.org/10.1002/ajmg.1320290402.

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Fyfe, John C., and David J. Lorenz. "Characterizing Midlatitude Jet Variability: Lessons from a Simple GCM." Journal of Climate 18, no. 16 (August 15, 2005): 3400–3404. http://dx.doi.org/10.1175/jcli3486.1.

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Abstract Fluctuations in the tropospheric zonal jet are often characterized using anomaly patterns, or empirical orthogonal functions, representing deviations of the zonal-mean flow from climatology. In previous studies the leading anomaly pattern has been interpreted as representing north–south jet movements, while the second anomaly pattern has been interpreted as representing independent fluctuations in jet strength and width. Here it is shown that these leading anomaly patterns are in fact dependent and together represent north–south movements of the jet. Fluctuations in jet strength, which are approximately inversely proportional to jet width, superimpose upon these dominant north–south meanderings. The distinction between the usual anomaly pattern perspective and this new perspective may have important implications in the interpretation of tropospheric zonal jet variability.

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Marpaung, Sartono, and Wawan K. Harsanugraha. "ANALYSIS OF SEA SURFACE HEIGHT ANOMALY CHARACTERISTICS BASED ON SATELLITE ALTIMETRY DATA (CASE STUDY: SEAS SURROUNDING JAVA ISLAND)." International Journal of Remote Sensing and Earth Sciences (IJReSES) 11, no. 2 (April 12, 2017): 137. http://dx.doi.org/10.30536/j.ijreses.2014.v11.a2611.

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Sea surface height anomaly is a oceanographic parameter that has spatial and temporal variability. This paper aims to determine the characters of sea surface height anomaly in the south and north seas of Java Island. To find these characters, a descriptive analysis of monthly anomaly data is performed spatially, zonally and temporally. Based on satellite altimetry data from 1993 to 2010, the analysis shows that the average of sea surface height anomaly varies, ranging from -15 cm to 15 cm. Spatially and zonally, there are three patterns that can be concidered as sea surface height anomaly characteristics: anomaly is higher in coastal areas than in open seas, anomaly is lower in coastal areas than in open seas and anomaly in coastal area is almost the same as in open seas. The first and second patterns occur in the south and north seas of Java Island. The third pattern occurs simultaneously in south and north seas of Java Island. Characteristics of temporal anomaly have a sinusoidal pattern in south and north seas of Java Island.

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Sabeti, Elyas, Sehong Oh, Peter Song, and Alfred Hero. "A Pattern Dictionary Method for Anomaly Detection." Entropy 24, no. 8 (August 9, 2022): 1095. http://dx.doi.org/10.3390/e24081095.

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In this paper, we propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. The proposed method is capable of learning complex patterns in a training data sequence, using these learned patterns to detect potentially anomalous patterns in a test data sequence. The proposed pattern dictionary method uses a measure of complexity of the test sequence as an anomaly score that can be used to perform stand-alone anomaly detection. We also show that when combined with a universal source coder, the proposed pattern dictionary yields a powerful atypicality detector that is equally applicable to anomaly detection. The pattern dictionary-based atypicality detector uses an anomaly score defined as the difference between the complexity of the test sequence data encoded by the trained pattern dictionary (typical) encoder and the universal (atypical) encoder, respectively. We consider two complexity measures: the number of parsed phrases in the sequence, and the length of the encoded sequence (codelength). Specializing to a particular type of universal encoder, the Tree-Structured Lempel–Ziv (LZ78), we obtain a novel non-asymptotic upper bound, in terms of the Lambert W function, on the number of distinct phrases resulting from the LZ78 parser. This non-asymptotic bound determines the range of anomaly score. As a concrete application, we illustrate the pattern dictionary framework for constructing a baseline of health against which anomalous deviations can be detected.

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Plastun, Alex, Inna Makarenko, Lyudmila Khomutenko, Svitlana Shcherbak, and Olha Tryfonova. "Exploring price gap anomaly in the Ukrainian stock market." Investment Management and Financial Innovations 16, no. 2 (June 5, 2019): 150–58. http://dx.doi.org/10.21511/imfi.16(2).2019.13.

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This paper analyzes price gaps in the Ukrainian stock market for the case of UX index over the period 2009–2018. Using different statistical tests (Student’s t-tests, ANOVA, Mann-Whitney test) and regression analysis with dummy variables, as well as modified cumulative approach and trading simulation, the authors test a number of hypotheses searching for price patterns and abnormal market behavior related to price gaps: there is seasonality in price gaps (H1); price gaps generate statistical anomalies in the Ukrainian stock market (H2); upward gaps generate price patterns in the Ukrainian stock market (H3) and downward gaps generate price patterns in the Ukrainian stock market (H4). Overall results are consistent with the Efficient Market Hypothesis: there is no seasonality in price gaps and in most cases there is no evidences of price patterns or abnormal price behavior after the gaps in the Ukrainian stock market. Nevertheless, the authors find very strong and convincing evidences in favor of momentum effect on the days of negative gaps. These observations are confirmed by trading simulations: trading strategy based on detected price pattern generates profits and demonstrates overall efficiency, which is against the market efficiency. These results can be interesting both for academicians (further evidences against market efficiency) and practitioners (real and effective trading strategy to generate profits in the Ukrainian market market).

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Kang, Na Ra, and Wonsun Paek. "Accruals Anomaly and Earnings Announcement Patterns." korean management review 45, no. 2 (April 30, 2016): 503. http://dx.doi.org/10.17287/kmr.2016.45.2.503.

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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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Більше джерел

Дисертації з теми "Anomaly patterns"

Chung, Chi-hang, and 鍾志恆. "Teleconnection of global precipitation anomaly with climate patterns." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/195968.

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Atmospheric oscillations, which mostly associate with climate patterns, have great influences on global climate variables, and they usually lead to extreme climate conditions and events, which cause lots of adverse impacts on our socioeconomic statuses. This study aims to identify the influence of climate patterns on the global precipitation anomaly. Four major climate patterns are investigated, and they are El Niño/La Niña–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Arctic Oscillation (AO) and Antarctic Oscillation (AAO). This study adopts the NINO3.4, DMI, AO index and AAO index to represent the climate patterns of ENSO, IOD, AO and AAO, respectively. The other research data used include precipitation data from the Global Precipitation Climatology Project (GPCP). The multiple linear regression method is used to study the relationships between the climate patterns and the global precipitation anomalies. Then, the precipitation anomalies all over the globe is modeled by those four climate pattern indexes. The signs and magnitudes of the regression coefficients for those indexes can reflect the relations of the climate patterns with the precipitations and their strength. Part of the results from the regression analysis matches well with the general understanding about the impact of those climate patterns. The influences of the climate patterns can be explained by their impact on the Walker circulation, monsoon system, jet stream, convection and atmospheric moisture transport. This suggests that the regression method is able to represent the teleconnection between the climate patterns and precipitation anomalies. Further, for each calendar month of the year, the variations of the relationships between precipitation anomalies and climate indexes show that the influences of the climate patterns on the precipitation anomalies vary throughout the year. The variations are mainly due to the different general circulation patterns in different seasons. The strengths of the relations also vary, and they mostly change with the strength of the climate patterns. Usually the stronger the climate pattern, the stronger the relationship. The variation of the heating from the sun also explain some of the seasonal variations of the relationships. Overall, this study indicates that the precipitation anomalies in Asia near the tropics and subtropics are significantly related to ENSO and IOD. Precipitation anomalies in Australia show significant relation with ENSO, IOD and AAO. AO has the greatest influence on the precipitation anomalies over Europe. For Africa, IOD and AAO have large influence on the precipitation anomalies on the east part and south part respectively. The south part of the North America is mainly affected by ENSO, while AO is dominant over the regions located at higher latitudes. ENSO is the dominant climate pattern affecting the precipitation anomalies in South America, and further, AAO and IOD also show some significant influences.
published_or_final_version
Civil Engineering
Master
Master of Philosophy

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Vural, Gurkan. "Anomaly Detection From Personal Usage Patterns In Web Applications." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607973/index.pdf.

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The anomaly detection task is to recognize the presence of an unusual (and potentially hazardous) state within the behaviors or activities of a computer user, system, or network with respect to some model of normal behavior which may be either hard-coded or learned from observation. An anomaly detection agent faces many learning problems including learning from streams of temporal data, learning from instances of a single class, and adaptation to a dynamically changing concept. The domain is complicated by considerations of the trusted insider problem (recognizing the difference between innocuous and malicious behavior changes on the part of a trusted user). This study introduces the anomaly detection in web applications and formulates it as a machine learning task on temporal sequence data. In this study the goal is to develop a model or profile of normal working state of web application user and to detect anomalous conditions as deviations from the expected behavior patterns. We focus, here, on learning models of normality at the user behavioral level, as observed through a web application. In this study we introduce some sensors intended to function as a focus of attention unit at the lowest level of a classification hierarchy using Finite State Markov Chains and Hidden Markov Models and discuss the success of these sensors.

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Åkerström, Paul Linus Martin. "RETURN PATTERNS PROXIMAL TO CENTRAL BANK RATE DECISION ANNOUNCEMENTS : OMX 30 excess return and monetary policy announcements." Thesis, Stockholms universitet, Finansiering, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-105824.

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In this study, it is determined that excess returns on the OMX 30 are confirmed to rise in anticipation of monetary policy decisions made by the central banks of Sweden and The United States of America. Those findings were manifested at a greater magnitude on the first day prior to the announcements and on a statistically significant level one day prior to monetary policy decisions from the Federal Open Market Committee. Moreover, excess returns beyond the average rate were found to be substantially higher on the first and third day prior monetary policy decisions from the Swedish Central bank (Riksbanken) albeit not on a statistically significant level. The results drawn from the data in the study were reinforced by findings in similar tests conducted during times of global recession.

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Pal, Aritra. "Improving Service Level of Free-Floating Bike Sharing Systems." Scholar Commons, 2017. https://scholarcommons.usf.edu/etd/7433.

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Bike Sharing is a sustainable mode of urban mobility, not only for regular commuters but also for casual users and tourists. Free-floating bike sharing (FFBS) is an innovative bike sharing model, which saves on start-up cost, prevents bike theft, and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. Efficient management of a FFBS requires: 1) analyzing its mobility patterns and spatio-temporal imbalance of supply and demand of bikes, 2) developing strategies to mitigate such imbalances, and 3) understanding the causes of a bike getting damaged and developing strategies to minimize them. All of these operational management problems are successfully addressed in this dissertation, using tools from Operations Research, Statistical and Machine Learning and using Share-A-Bull Bike FFBS and Divvy station-based bike sharing system as case studies.

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Costa, Gabriel de Barros Paranhos da. "Detecção de anomalias utilizando métodos paramétricos e múltiplos classificadores." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-20112014-105415/.

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Anomalias ou outliers são exemplos ou grupo de exemplos que apresentam comportamento diferente do esperado. Na prática,esses exemplos podem representar doenças em um indivíduo ou em uma população, além de outros eventos como fraudes em operações bancárias e falhas em sistemas. Diversas técnicas existentes buscam identificar essas anomalias, incluindo adaptações de métodos de classificação e métodos estatísticos. Os principais desafios são o desbalanceamento do número de exemplos em cada uma das classes e a definição do comportamento normal associada à formalização de um modelo para esse comportamento. Nesta dissertação propõe-se a utilização de um novo espaço para realizar a detecção,esse espaço é chamado espaço de parâmetros. Um espaço de parâmetros é criado utilizando parâmetros estimados a partir da concatenação(encadeamento) de dois exemplos. Apresenta-se,então,um novo framework para realizar a detecção de anomalias através da fusão de detectores que utilizam fechos convexos em múltiplos espaços de parâmetros para realizar a detecção. O método é considerado um framework pois é possível escolher quais os espaços de parâmetros que serão utilizados pelo método de acordo como comportamento da base de dados alvo. Nesse trabalho utilizou-se,para experimentos,dois conjuntos de parâmetros(média e desvio padrão; média, variância, obliquidade e curtose) e os resultados obtidos foram comparados com alguns métodos comumente utilizados para detecção de anomalias. Os resultados atingidos foram comparáveis ou melhores aos obtidos pelos demais métodos. Além disso, acredita-se que a utilização de espaços de parâmetros cria uma grande flexibilidade do método proposto, já que o usuário pode escolher um espaço de parâmetros que se adeque a sua aplicação. Tanto a flexibilidade quanto a extensibilidade disponibilizada pelo espaço de parâmetros, em conjunto como bom desempenho do método proposto nos experimentos realizados, tornam atrativa a utilização de espaços de parâmetros e, mais especificamente, dos métodos apresentados na solução de problemas de detecção de anomalias.
Anomalies or outliers are examples or group of examples that have a behaviour different from the expected. These examples may represent diseases in individuals or populations,as well as other events such as fraud and failures in banking systems.Several existing techniques seek to identify these anomalies, including adaptations of classification methods, statistical methods and methods based on information theory. The main challenges are that the number of samples of each class is unbalanced, the cases when anomalies are disguised among normal samples and the definition of normal behaviour associated with the formalization of a model for this behaviour. In this dissertation,we propose the use of a new space to helpwith the detection task, this space is called parameter space. We also present a new framework to perform anomaly detection by using the fusion of convex hulls in multiple parameter spaces to perform the detection.The method is considered a framework because it is possible to choose which parameter spaces will be used by the method according to the behaviour of the target data set.For the experiments, two parameter spaces were used (mean and standard deviation; mean, variance, skewness and kurtosis) and the results were compared to some commonly used anomaly detection methods. The results achieved were comparable or better than those obtained by the other methods. Furthermore, we believe that a parameter space created great fexibility for the proposed method, since it allowed the user to choose a parameter space that best models the application. Both the flexibility and extensibility provided by the use of parameter spaces, together with the good performance achieved by the proposed method in the experiments, make parameter spaces and, more specifically, the proposed methods appealing when solving anomaly detection problems.

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Losik, Len, Sheila Wahl, and Lewis Owen. "Predicting Failures and Estimating Duration of Remaining Service Life from Satellite Telemetry." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/611451.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California
This paper addresses research completed for predicting hardware failures and estimating remaining service life for satellite components using a Failure Prediction Process (FPP). It is a joint paper, presenting initial research completed at the University of California, Berkeley, Center for Extreme Ultraviolet (EUV) Astrophysics using telemetry from the EUV EXPLORER (EUVE) satellite and statistical computation analysis completed by Lockheed Martin. This work was used in identifying suspect "failure precursors." Lockheed Martin completed an exploration into the application of statistical pattern recognition methods to identify FPP events observed visually by the human expert. Both visual and statistical methods were successful in detecting suspect failure precursors. An estimate for remaining service life for each unit was made from the time the suspect failure precursor was identified. It was compared with the actual time the equipment remained operable. The long-term objective of this research is to develop a resident software module which can provide information on FPP events automatically, economically, and with high reliability for long-term management of spacecraft, aircraft, and ground equipment. Based on the detection of a Failure Prediction Process event, an estimate of remaining service life for the unit can be calculated and used as a basis to manage the failure.

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Rahman, Anisur. "Rare sequential pattern mining of critical infrastructure control logs for anomaly detection." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/132077/1/__qut.edu.au_Documents_StaffHome_staffgroupW%24_wu75_Documents_ePrints_Anisur_Rahman_Thesis_Redacted.pdf.

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Supervisory Control and Data Acquisition (SCADA) systems are used to drive much of a nation's critical infrastructure, which by definition is essential for the nation's citizens' way of life. They are connected to the computer networks and internet systems to operate, control and monitor their operations. This connectivity enables these SCADA systems to be exposed to cyber-attacks. This thesis detects anomalies or cyber-attacks on SCADA systems. It analyses SCADA control logs to find abnormal process activities which are treated as anomalies. A novel rare sequential pattern mining approach is proposed and developed to find rare or abnormal behaviour in SCADA systems.

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Jakkula, Vikramaditya Reddy. "Enhancing smart home resident activity prediction and anomaly detection using temporal relations." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Fall2007/v_jakkula_102207.pdf.

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McAbee, Ashley S. M. "Traffic pattern detection using the Hough transformation for anomaly detection to improve maritime domain awareness." Thesis, Monterey, California: Naval Postgraduate School, 2013. http://hdl.handle.net/10945/38977.

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Approved for public release; distribution is unlimited.
Techniques for anomaly detection in the maritime domain by extracting traffic patterns from ship position data to generate atlases of expected ocean travel are developed in this thesis. An archive of historical data is used to develop a traffic density grid. The Hough transformation is used to extract linear patterns of elevated density from the traffic density grid, which can be considered the highways of the oceans. These highways collectively create an atlas that is used to define geographical regions of expected ship locations. Ship position reports are compared to the atlas of highways to flag as anomalous any ship that is not operating on an expected highway. The atlas generation techniques are demonstrated using automated information system (AIS) ship position data to detect highways in both open-ocean and coastal areas. Additionally, the atlas generation techniques are used to explore variability in ship traffic as a result of extreme weather and seasonal variation. Finally, anomaly detection is demonstrated by comparing AIS data from 2013 to the highways detected in the archive of data from 2012. The development of an automatic atlas generation technique that can be used to develop a definition of normal maritime behavior is the significant result of this thesis.

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Spasic, Nemanja. "Anomaly Detection and Prediction of Human Actions in a Video Surveillance Environment." Thesis, University of Cape Town, 2007. http://pubs.cs.uct.ac.za/archive/00000449/.

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World wide focus has over the years been shifting towards security issues, not in least due to recent world wide terrorist activities. Several researchers have proposed state of the art surveillance systems to help with some of the security issues with varying success. Recent studies have suggested that the ability of these surveillance systems to learn common environmental behaviour patterns as wells as to detect and predict unusual, or anomalous, activities based on those learnt patterns are possible improvements to those systems. In addition, some of these surveillance systems are still run by human operators, who are prone to mistakes and may need some help from the surveillance systems themselves in detection of anomalous activities. This dissertation attempts to address these suggestions by combining the fields of Image Understanding and Artificial Intelligence, specifically Bayesian Networks, to develop a prototype video surveillance system that can learn common environmental behaviour patterns, thus being able to detect and predict anomalous activity in the environment based on those learnt patterns. In addition, this dissertation aims to show how the prototype system can adapt to these anomalous behaviours and integrate them into its common patterns over a prolonged occurrence period. The prototype video surveillance system showed good performance and ability to detect, predict and integrate anomalous activity in the evaluation tests that were performed using a volunteer in an experimental indoor environment. In addition, the prototype system performed quite well on the PETS 2002 dataset 1, which it was not designed for. The evaluation procedure used some of the evaluation metrics commonly used on the PETS datasets. Hence, the prototype system provides a good approach to anomaly detection and prediction using Bayesian Networks trained on common environmental activities.

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Книги з теми "Anomaly patterns"

G, Hutchins D., and Petzel V, eds. The regional radiometric data set of Namibia: Comments on compilation of the data from west central and southern Namibia and on anomaly patterns thereof. Windhoek, Namibia: Ministry of Mines and Energy, Geological Survey of Namibia, 1997.

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Millikan, Ruth Garrett. Perception, Especially Perception through Language. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198717195.003.0014.

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Perceptual processing is translation of patterns in the data of sense into cognitive understanding without uniceptual inference. Understanding language differs from ordinary perceptual processing in that the signs it translates are detached rather than attached. This similarity is obscured because ordinary uses of the verbs of perception do not track a kind of psychological processing. Their use is mostly factive, which encourages overlooking the fallibility of perception. One result is the mistaken view that perceptual illusions are an anomaly and that perception is cognitively impenetrable. The assumption that each of the senses has its own proprietary level of perception and the assumption that differences in the result of perceptual processing are always accompanied by differences in perceptual experience are questioned. Finally, a number of intuitive objections to the idea that understanding language is a form of perceptual processing are discussed.

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Vostokov, Dmitry, and Software Diagnostics Institute. Trace, Log, Text, Narrative: An Analysis Pattern Reference for Data Mining, Diagnostics, Anomaly Detection, Fourth Edition. Opentask, 2021.

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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 widespread fish mortality during the event. Quite opposite of this characteristic change in the ocean condition, cold SST anomalies prevail in the eastern equatorial Pacific during the El Niño Modoki events, but with the warm anomalies intensified in the central Pacific. The boreal winter condition of 2004 is a typical example of such an event, when a tripole pattern is noticed in the SST anomalies; warm central Pacific flanked by cold eastern and western regions. The SST anomalies are coupled to a double cell in anomalous Walker circulation with rising motion in the central parts and sinking motion on both sides of the basin. This is again a different feature compared to the well-known single-cell anomalous Walker circulation during El Niños. La Niña Modoki is the opposite phase of the El Niño Modoki, when a cold central Pacific is flanked by warm anomalies on both sides.The Modoki events are seen to peak in both boreal summer and winter and hence are not seasonally phase-locked to a single seasonal cycle like El Niño/La Niña events. Because of this distinction in the seasonality, the teleconnection arising from these events will vary between the seasons as teleconnection path will vary depending on the prevailing seasonal mean conditions in the atmosphere. Moreover, the Modoki El Niño/La Niña impacts over regions such as the western coast of the United States, the Far East including Japan, Australia, and southern Africa, etc., are opposite to those of the canonical El Niño/La Niña. For example, the western coasts of the United States suffer from severe droughts during El Niño Modoki, whereas those regions are quite wet during El Niño. The influences of Modoki events are also seen in tropical cyclogenesis, stratosphere warming of the Southern Hemisphere, ocean primary productivity, river discharges, sea level variations, etc. A remarkable feature associated with Modoki events is the decadal flattening of the equatorial thermocline and weakening of zonal thermal gradient. The associated ocean-atmosphere conditions have caused frequent and persistent developments of Modoki events in recent decades.

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Частини книг з теми "Anomaly patterns"

Dueholm, Jacob Velling, Kamal Nasrollahi, and Thomas Baltzer Moeslund. "Object-Centric Anomaly Detection Using Memory Augmentation." In Computer Analysis of Images and Patterns, 362–71. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89128-2_35.

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Byrne, Charles J. "Bouguer Gravity Anomaly Patterns of Impact Features." In The Moon's Largest Craters and Basins, 29–34. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-22032-1_5.

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Boekhoudt, Kayleigh, Alina Matei, Maya Aghaei, and Estefanía Talavera. "HR-Crime: Human-Related Anomaly Detection in Surveillance Videos." In Computer Analysis of Images and Patterns, 164–74. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89131-2_15.

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Campbell, Scott, Mariam Kiran, and Fatema Bannat Wala. "Unsupervised Anomaly Detection in Daily WAN Traffic Patterns." In Communications in Computer and Information Science, 240–56. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63393-6_16.

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Wacker, Esther-Sabrina, and Joachim Denzler. "Combining Structure and Appearance for Anomaly Detection in Wire Ropes." In Computer Analysis of Images and Patterns, 163–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23678-5_18.

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Vy, Ngo Duy Khanh, and Duong Tuan Anh. "Detecting Variable Length Anomaly Patterns in Time Series Data." In Data Mining and Big Data, 279–87. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40973-3_28.

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Noh, Sang-Kyun, Yong-Min Kim, DongKook Kim, and Bong-Nam Noh. "Network Anomaly Detection Based on Clustering of Sequence Patterns." In Computational Science and Its Applications - ICCSA 2006, 349–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11751588_37.

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Kozik, Rafał, Michał Choraś, Rafał Renk, and Witold Hołubowicz. "Patterns Extraction Method for Anomaly Detection in HTTP Traffic." In Advances in Intelligent Systems and Computing, 227–36. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19713-5_20.

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Kim, Young Geun, Jeong-Han Yun, Siho Han, Hyoung Chun Kim, and Simon S. Woo. "Revitalizing Self-Organizing Map: Anomaly Detection Using Forecasting Error Patterns." In ICT Systems Security and Privacy Protection, 382–97. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78120-0_25.

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Cavallaro, Claudia, and Elisabetta Ronchieri. "Identifying Anomaly Detection Patterns from Log Files: A Dynamic Approach." In Computational Science and Its Applications – ICCSA 2021, 517–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86960-1_36.

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Тези доповідей конференцій з теми "Anomaly patterns"

Sukhobok, Dina, Nikolay Nikolov, and Dumitru Roman. "Tabular Data Anomaly Patterns." In 2017 International Conference on Big Data Innovations and Applications (Innovate-Data). IEEE, 2017. http://dx.doi.org/10.1109/innovate-data.2017.10.

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Roh, Jong-hyuk, Sung-Hun Lee, and Soohyung Kim. "Anomaly detection of access patterns in database." In 2015 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2015. http://dx.doi.org/10.1109/ictc.2015.7354751.

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Seleznyov, Alexandr, and Oleksiy Mazhelis. "Learning temporal patterns for anomaly intrusion detection." In the 2002 ACM symposium. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/508791.508836.

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Gutchess, Daniel, Neal Checka, and Magnús S. Snorrason. "Learning patterns of human activity for anomaly detection." In Defense and Security Symposium, edited by Kevin L. Priddy and Emre Ertin. SPIE, 2007. http://dx.doi.org/10.1117/12.741379.

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Yu, Tsung-Chiao, Jyun-Yao Huang, I.-En Liao, and Kuo-Fong Kao. "Mining Anomaly Communication Patterns for Industrial Control Systems." In 2018 Australasian Universities Power Engineering Conference (AUPEC). IEEE, 2018. http://dx.doi.org/10.1109/aupec.2018.8757940.

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Vespe, M., I. Visentini, K. Bryan, and P. Braca. "Unsupervised learning of maritime traffic patterns for anomaly detection." In 9th IET Data Fusion & Target Tracking Conference (DF&TT 2012): Algorithms & Applications. IET, 2012. http://dx.doi.org/10.1049/cp.2012.0414.

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Parvathy, R., Soumya Thilakan, Meenu Joy, and K. M. Sameera. "Anomaly Detection Using Motion Patterns Computed from Optical Flow." In 2013 Third International Conference on Advances in Computing and Communications (ICACC). IEEE, 2013. http://dx.doi.org/10.1109/icacc.2013.18.

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Paredes-Oliva, Ignasi, Ismael Castell-Uroz, Pere Barlet-Ros, Xenofontas Dimitropoulos, and Josep Sole-Pareta. "Practical anomaly detection based on classifying frequent traffic patterns." In IEEE INFOCOM 2012 - IEEE Conference on Computer Communications Workshops. IEEE, 2012. http://dx.doi.org/10.1109/infcomw.2012.6193518.

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Kayode, J. S., M. N. M. Nawawi, Y. Yusup, A. E. Khalil, and M. H. Arifin. "Distributions of Subsurface Anomaly Patterns Using Machine Learning Tools." In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9883869.

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Pulfer, Brian, Yury Belousov, Joakim Tutt, Roman Chaban, Olga Taran, Taras Holotyak, and Slava Voloshynovskiy. "Anomaly localization for copy detection patterns through print estimations." In 2022 IEEE International Workshop on Information Forensics and Security (WIFS). IEEE, 2022. http://dx.doi.org/10.1109/wifs55849.2022.9975416.

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Звіти організацій з теми "Anomaly patterns"

Mueller, C., S. J. Piercey, M. G. Babechuk, and D. Copeland. Stratigraphy and lithogeochemistry of the Goldenville horizon and associated rocks, Baie Verte Peninsula, Newfoundland. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328990.

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The Goldenville horizon in the Baie Verte Peninsula is an important stratigraphic horizon that hosts primary (Cambrian to Ordovician) exhalative magnetite and pyrite and was a chemical trap for younger (Silurian to Devonian) orogenic gold mineralization. The horizon is overlain by basaltic flows and volcaniclastic rocks, is intercalated with variably coloured argillites and cherts, and underlain by mafic volcaniclastic rocks; the entire stratigraphy is cut by younger fine-grained mafic dykes and coarser gabbro. Lithogeochemical signatures of the Goldenville horizon allow it to be divided into high-Fe iron formation (HIF; &gt;50% Fe2O3), low-Fe iron formation (LIF; 15-50% Fe2O3), and argillite with iron minerals (AIF; &lt;15% Fe2O3). These variably Fe-rich rocks have Fe-Ti-Mn-Al systematics consistent with element derivation from varying mineral contributions from hydrothermal venting and ambient detrital sedimentation. Post-Archean Australian Shale (PAAS)-normalized rare earth element (REE) signatures for the HIF samples have negative Ce anomalies and patterns similar to modern hydrothermal sediment deposited under oxygenated ocean conditions. The PAAS-normalized REE signatures of LIF samples have positive Ce anomalies, similar to hydrothermal sediment deposited under anoxic to sub-oxic conditions. The paradoxical Ce behaviour is potentially explained by the Mn geochemistry of the LIF samples. The LIF have elevated MnO contents (2.0-7.5 weight %), suggesting that Mn from hydrothermal fluids was oxidized in an oxygenated water column during hydrothermal venting, Mn-oxides then scavenged Ce from seawater, and these Mn-oxides were subsequently deposited in the hydrothermal sediment. The Mn-rich LIF samples with positive Ce anomalies are intercalated with HIF with negative Ce anomalies, both regionally and on a metre scale within drill holes. Thus, the LIF positive Ce anomaly signature may record extended and particle-specific scavenging rather than sub-oxic/redox-stratified marine conditions. Collectively, results suggest that the Cambro-Ordovician Taconic seaway along the Laurentian margin may have been completely or near-completely oxygenated at the time of Goldenville horizon deposition.

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Maps showing anomaly patterns for silver, molybdenum, lead, and zinc in altered rocks and soils, Williams Fork and St. Louis Peak Roadless Areas, Clear Creek, Grand, and Summit counties, Colorado. US Geological Survey, 1985. http://dx.doi.org/10.3133/mf1588e.

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