Artykuły w czasopismach: „Anomalous process”

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MEHTA, AK, i R. RAVIKUMAR. "ANOMALOUS ELONGATION OF STYLOID PROCESS". Medical Journal Armed Forces India 56, nr 3 (lipiec 2000): 248–49. http://dx.doi.org/10.1016/s0377-1237(17)30182-x.

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Wu, Renguang, i Zhuoqi He. "Two Distinctive Processes for Abnormal Spring to Summer Transition over the South China Sea". Journal of Climate 30, nr 23 (grudzień 2017): 9665–78. http://dx.doi.org/10.1175/jcli-d-17-0215.1.

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The period from April to June signifies the transition from spring to summer over the South China Sea (SCS). The present study documents two distinct processes for abnormal spring to summer transition over the SCS. One process is related to large-scale sea surface temperature (SST) anomalies in the tropical Indo-Pacific region. During spring of La Niña decaying years, negative SST anomalies in the equatorial central Pacific (ECP) and the southwestern tropical Indian Ocean (TIO) coexist with positive SST anomalies in the tropical western North Pacific. Negative ECP SST anomalies force an anomalous Walker circulation, negative southwestern TIO SST anomalies induce anomalous cross-equatorial flows from there, and positive tropical western North Pacific SST anomalies produce a Rossby wave–type response to the west. Together, they contribute to enhanced convection and an anomalous lower-level cyclone over the SCS, leading to an advanced transition to summer there. The other process is related to regional air–sea interactions around the Maritime Continent. Preceding positive ECP SST anomalies induce anomalous descent around the Maritime Continent, leading to SST increase in the SCS and southeast TIO. An enhanced convection region moves eastward over the south TIO during spring and reaches the area northwest of Australia in May. This enhances descent over the SCS via an anomalous cross-equatorial overturning circulation and contributes to further warming in the SCS. The SST warming in turn induces convection over the SCS, leading to an accelerated transition to summer. Analysis shows that the above two processes are equally important during 1979–2015.

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Hannah, Torben. "The anomalous process to two loops". Nuclear Physics B 593, nr 3 (styczeń 2001): 577–95. http://dx.doi.org/10.1016/s0550-3213(00)00641-6.

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Wada, H., T. Mori, M. Shiga, H. Aruga Katori, M. I. Bartashevich i T. Goto. "Anomalous magnetization process of Er1−xLuxCo2". Physica B: Condensed Matter 201 (lipiec 1994): 139–42. http://dx.doi.org/10.1016/0921-4526(94)91068-5.

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Dudley, J., i B. Chambers. "ANOMALOUS RESPONSE IN THE HALIFAX PROCESS". Water and Environment Journal 17, nr 3 (sierpień 2003): 168–70. http://dx.doi.org/10.1111/j.1747-6593.2003.tb00456.x.

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Sun, Yue, i Haishan Chen. "Atmospheric Circulation Anomalies and Key Physical Processes behind Two Categories of Anomalous Eurasian Spring Snowmelt". Journal of Hydrometeorology 24, nr 8 (sierpień 2023): 1349–63. http://dx.doi.org/10.1175/jhm-d-23-0010.1.

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Abstract Eurasian spring snowmelt plays an important role in the subsequent climate and hydrological cycle, however, the understanding of snowmelt itself and its causes remains insufficient. This study explored the basic characteristics of spring snowmelt in the eastern Europe–western Siberia (EEWS) region by classifying snowmelt anomalies into two categories based on the different factors that dominate spring snowmelt, and then investigated the associated atmospheric circulation anomalies and local physical processes. The first category of anomalous snowmelt (category 1) is controlled by both the initial snow mass and the later snowmelt process, while the second category of anomalous snowmelt (category 2) is mainly linked to the later snowmelt process. Specifically, category 1 is characterized by an anomalous trough in EEWS in winter, where water vapor transported and converged, accompanied by anomalous upward motion, which promotes snowfall and snow accumulation, providing initial conditions conducive to snowmelt. In April, this region is controlled by an anomalous ridge, with significant warm advection anomalies and subsidence promoting surface warming, thereby accelerating snow melting. In contrast, the winter circulation anomalies are insignificant in category 2, while the anomalous ridge in April is stronger than in category 1, accompanied by more intense snowmelt processes. In addition, from the surface energy balance perspective, atmospheric downward sensible heat transport is an important factor influencing the anomalous snowmelt in category 1, while shortwave radiation plays a secondary role. Conversely, the snowmelt in category 2 is dominated by shortwave radiation forcing, but the sensible heat effect is slightly weaker. Significance Statement Eurasian spring snowmelt significantly impacts the subsequent climate and hydrological cycle, but the understanding of snowmelt itself and its causes is still inadequate. The purpose of this study is to explore the monthly evolution of atmospheric circulation associated with anomalous snowmelt and its local physical processes associated by categorizing them based on snowmelt characteristics. Category 1 is jointly affected by winter snow accumulation and later warming, while category 2 is dominated by strong snowmelt process in late spring. These two categories are accompanied by different winter and spring circulation configurations. Our results provide a basis for further investigation of snowmelt precursor signals.

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van der Aalst, W. M. P., i A. K. A. de Medeiros. "Process Mining and Security: Detecting Anomalous Process Executions and Checking Process Conformance". Electronic Notes in Theoretical Computer Science 121 (luty 2005): 3–21. http://dx.doi.org/10.1016/j.entcs.2004.10.013.

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Trirat, Patara, Youngeun Nam, Taeyoon Kim i Jae-Gil Lee. "AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 13 (26.06.2023): 16488–90. http://dx.doi.org/10.1609/aaai.v37i13.27088.

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This paper presents AnoViz, a novel visualization tool of anomalies in multivariate time series, to support domain experts and data scientists in understanding anomalous instances in their systems. AnoViz provides an overall summary of time series as well as detailed visualizations of relevant detected anomalies in both query and stream modes, rendering near real-time visual analysis available. Here, we show that AnoViz streamlines the process of finding a potential cause of an anomaly with a deeper analysis of anomalous instances, giving explainability to any anomaly detector.

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Pithwa, Yogesh Kishorkant. "Anomalous Cervical Spinous Process Leading to Myelopathy". Spine 40, nr 20 (październik 2015): E1117—E1119. http://dx.doi.org/10.1097/brs.0000000000001088.

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Arkashov, N. S., i V. A. Seleznev. "Energy Characteristics of the Anomalous Diffusion Process". Theoretical and Mathematical Physics 199, nr 3 (czerwiec 2019): 894–908. http://dx.doi.org/10.1134/s0040577919060096.

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Shigeoka, T., A. Garnier, D. Gignoux, D. Schmitt, F. Y. Zhang i J. Voiron. "Anomalous metamagnetic process of TbCo2Ge2 single crystal". Physica B: Condensed Matter 211, nr 1-4 (maj 1995): 118–20. http://dx.doi.org/10.1016/0921-4526(94)00960-4.

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Kilian, W., M. Krämer i P. M. Zerwas. "Anomalous couplings in the Higgs-strahlung process". Physics Letters B 381, nr 1-3 (lipiec 1996): 243–47. http://dx.doi.org/10.1016/0370-2693(96)00537-0.

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Sakai, Tôru, Kiyomi Okamoto, Kouichi Okunishi i Masahiro Sato. "Anomalous magnetization process in frustrated spin ladders". Journal of Physics: Condensed Matter 16, nr 11 (4.03.2004): S785—S789. http://dx.doi.org/10.1088/0953-8984/16/11/030.

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FUJII, Yasuhiko, Masao NOMURA, Hatsuki ONITSUKA i Kunihiklko TAKEDA. "Anomalous Isotope Fractionation in Uranium Enrichment Process". Journal of Nuclear Science and Technology 26, nr 11 (listopad 1989): 1061–64. http://dx.doi.org/10.1080/18811248.1989.9734427.

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Feng, Juan, Wen Chen i Xiaocong Wang. "Reintensification of the Anomalous Western North Pacific Anticyclone during the El Niño Modoki Decaying Summer: Relative Importance of Tropical Atlantic and Pacific SST Anomalies". Journal of Climate 33, nr 8 (15.04.2020): 3271–88. http://dx.doi.org/10.1175/jcli-d-19-0154.1.

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AbstractThe El Niño Modoki–induced anomalous western North Pacific anticyclone (WNPAC) undergoes an interesting reintensification process in the El Niño Modoki decaying summer, the period when El Niño Modoki decays but warm sea surface temperature (SST) anomalies over the tropical North Atlantic (TNA) and cold SST anomalies over the central-eastern Pacific (CEP) dominate. In this study, the region (TNA or CEP) in which the SST anomalies exert a relatively important influence on reintensification of the WNPAC is investigated. Observational analysis demonstrates that when only anomalous CEP SST cooling occurs, the WNPAC experiences a weak reintensification. In contrast, when only anomalous TNA SST warming emerges, the WNPAC experiences a remarkable reintensification. Numerical simulation analysis demonstrates that even though the same magnitude of CEP SST cooling and TNA warming is respectively set to force the atmospheric general circulation model, the response of the WNPAC is still much stronger in the TNA warming experiment than in the CEP cooling experiment. Further analysis demonstrates that this difference is caused by the distinct location of the effective tropical forcing between the CEP SST cooling and TNA SST warming for producing a WNPAC. The CEP cooling-induced effective anomalous diabatic cooling is located in the central Pacific, by which the forced anticyclone becomes gradually weak from the central Pacific to the western North Pacific. Thus, a weak WNPAC is produced. In contrast, as the TNA SST warming–induced effective anomalous diabatic cooling is just located in the western North Pacific via a Kelvin wave–induced Ekman divergence process, the forced anticyclone is significant and powerful in the western North Pacific.

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Krinkin, David. "Anomalously large kinetic isotope effect". Open Chemistry 5, nr 4 (1.12.2007): 1019–63. http://dx.doi.org/10.2478/s11532-007-0048-2.

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AbstractActivated diffusion of water between macromolecules in swollen cellulose is accompanied by anomalously high kinetic isotope effects of oxygen. The separation factor of heavy-oxygen water (H218O /H216O) is thousands of permilles instead of tens of permilles according to modern Absolute Rate Theory. This anomalous separation under usual conditions is disguised by the opposing process of very fast equalization to equilibrium through water-filled cellulose pores. This process is quicker by approximately 3 orders of magnitude than diffusion through the cellulose body. As a consequence, this opposition-directed equalization virtually eliminates the results of isotope separation. To reveal this anomaly it is necessary to suppress equalization, which was the primary problem for both discovery of this anomaly and its investigation. The method of investigating the anomalous separation in cellulose was developed with suppression of this negative influence. Discussion of the theoretical nature of the anomalous kinetic isotope effect is presented. This theoretical study would probably permit the discovery and use for isotope separation of the anomalously high isotope effect for other chemical elements, in particular, for those heavier than oxygen.

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Wang, Yaoguang, Yaohao Zheng, Yunxiang Zhang, Yongsheng Xie, Sen Xu, Ying Hu i Liang He. "Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Using Classification-Based Methods". Applied Sciences 11, nr 23 (24.11.2021): 11128. http://dx.doi.org/10.3390/app112311128.

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The task of unsupervised anomalous sound detection (ASD) is challenging for detecting anomalous sounds from a large audio database without any annotated anomalous training data. Many unsupervised methods were proposed, but previous works have confirmed that the classification-based models far exceeds the unsupervised models in ASD. In this paper, we adopt two classification-based anomaly detection models: (1) Outlier classifier is to distinguish anomalous sounds or outliers from the normal; (2) ID classifier identifies anomalies using both the confidence of classification and the similarity of hidden embeddings. We conduct experiments in task 2 of DCASE 2020 challenge, and our ensemble method achieves an averaged area under the curve (AUC) of 95.82% and averaged partial AUC (pAUC) of 92.32%, which outperforms the state-of-the-art models.

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Wei, Lei, Yongqing Cao, Xin Lin i Weidong Huang. "Cellular Automaton Simulation of the Growth of Anomalous Eutectic during Laser Remelting Process". Materials 11, nr 10 (27.09.2018): 1844. http://dx.doi.org/10.3390/ma11101844.

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Anomalous eutectic morphologies were observed during laser remelting of a Ni-Sn powder bed, where it was sandwiched between a lamellar eutectic at the bottom of melt pool. That is, the anomalous eutectic growth mechanism can be divided into two processes: one is the lamellar to anomalous transition (LAT); the other is the anomalous to lamellar transition (ALT). The thermal distribution at the bottom of melt pool is simulated by the finite difference method. It is found that the cooling rate at the bottom of melt pool is a linear function of time. A cellular automaton (CA) model is developed to simulate the anomalous growth. Simulation results show that the mechanism of the LAT is that one phase overgrows the other followed by subsequent nucleating of the other phase. The mechanism of the ALT is the competitive growth between the anomalous and lamellar eutectic; as the cooling rate increased, the lamellar eutectic is more competitive.

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Akabori, Kei-ichi, Keiji Tanaka, Tisato Kajiyama i Atsushi Takahara. "Anomalous Surface Relaxation Process in Polystyrene Ultrathin Films". Macromolecules 36, nr 13 (lipiec 2003): 4937–43. http://dx.doi.org/10.1021/ma034001y.

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Ryzhikov, Artem, Maxim Borisyak, Andrey Ustyuzhanin i Denis Derkach. "NFAD: fixing anomaly detection using normalizing flows". PeerJ Computer Science 7 (18.11.2021): e757. http://dx.doi.org/10.7717/peerj-cs.757.

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Anomaly detection is a challenging task that frequently arises in practically all areas of industry and science, from fraud detection and data quality monitoring to finding rare cases of diseases and searching for new physics. Most of the conventional approaches to anomaly detection, such as one-class SVM and Robust Auto-Encoder, are one-class classification methods, i.e., focus on separating normal data from the rest of the space. Such methods are based on the assumption of separability of normal and anomalous classes, and subsequently do not take into account any available samples of anomalies. Nonetheless, in practical settings, some anomalous samples are often available; however, usually in amounts far lower than required for a balanced classification task, and the separability assumption might not always hold. This leads to an important task—incorporating known anomalous samples into training procedures of anomaly detection models. In this work, we propose a novel model-agnostic training procedure to address this task. We reformulate one-class classification as a binary classification problem with normal data being distinguished from pseudo-anomalous samples. The pseudo-anomalous samples are drawn from low-density regions of a normalizing flow model by feeding tails of the latent distribution into the model. Such an approach allows to easily include known anomalies into the training process of an arbitrary classifier. We demonstrate that our approach shows comparable performance on one-class problems, and, most importantly, achieves comparable or superior results on tasks with variable amounts of known anomalies.

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Boos, Eduard, Viacheslav Bunichev, Georgi Vorotnikov, Lev Dudko, Igor Myagkov i Maxim Perfilov. "The recipe to search for anomalous Wtb couplings in tWb associated production process." EPJ Web of Conferences 191 (2018): 02008. http://dx.doi.org/10.1051/epjconf/201819102008.

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The impact of anomalous Wtb couplings on tWb process of the single top quark production has been probed in different schemes of tWb modeling. A special attention devotes to influence of the particular schemes to the anomalous couplings sensitivity. The distributions of representative variables demonstrate different behaviour in different simulation schemes, therefore the correct probe for anomalous Wtb couplings require specific approach to simulate BSM contribution. Special approach to search for BSM contribution in the off-shell tWb process is proposed in this paper. The approach is based on the kinematic separation of the double and single resonant contributions by means of neural network. The specific BSM properties are considered separately for the double and single resonant events. Such approach allows to add information on the anomalous Wtb coupling from simultaneous consideration of the tt¯ (double resonant) and tWb (off-shell, single resonant) contribution of tWb processes and therefore can improve the sensitivity to the anomalous Wtb couplings.

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Cullen, M. J. P., i K. Ngan. "On the relationship between stratospheric structure and tropospheric blocking patterns". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, nr 1991 (28.05.2013): 20120180. http://dx.doi.org/10.1098/rsta.2012.0180.

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Prediction of long-lived anomalous behaviour in the atmosphere is fundamental to extended range and seasonal forecasting. Prediction of changes in the climatology of such anomalous behaviour is also fundamental to regional climate modelling. Anomalous atmospheric behaviour is often related to mid-latitude tropospheric ‘blocking’ patterns, where the normal westerly flow associated with the temperature difference between the Poles and the Equator is disrupted. Following recent work on stratosphere–troposphere coupling, we show that the vertical structure of the atmosphere can strongly influence the climatology of tropospheric blocking. We invoke dynamical theory to argue that the development and decay of anomalous circulations is most efficient for a preferred aspect ratio of the flow, implying that the development of large-scale anomalies requires a large vertical scale. Evidence for this link comes from the observed evolution of the geopotential height. In particular, we find that the development of the large-scale tropospheric anomalies associated with blocking requires a vertical scale extending well into the stratosphere. This process is inhibited during periods of high stratospheric activity, when the vertical scale of tropospheric developments is restricted, leading to the persistence of large horizontal scales.

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Shiogama, Hideo, Toru Terao, Hideji Kida i Tatsuya Iwashima. "Roles of Low- and High-Frequency Eddies in the Transitional Process of the Southern Hemisphere Annular Mode". Journal of Climate 18, nr 6 (15.03.2005): 782–94. http://dx.doi.org/10.1175/jcli-3303.1.

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Abstract The effects of low- and high-frequency eddies (time scales longer and shorter than 10 days, respectively) on the transitional processes of the Southern Hemisphere “Annular Mode” are investigated, based on NCEP–NCAR daily reanalysis data for the period 1979–2001. Special attention is focused on the zonal symmetry/asymmetry and the temporal evolution of the eddy forcing. For the poleward transitional process, the effects of low-frequency eddies precede those of high-frequency eddies in driving the jet transition. Quasi-stationary Rossby waves propagating along the polar jet with wavelengths of 7000 km play an important role. The waves, originally come from the Indian Ocean through the waveguide associated with the polar jet, dissipate equatorward over the eastern Pacific Ocean. This anomalous equatorward dissipation of wave activity induces an anomalous poleward momentum flux, which is responsible for changes in the polar jet over the Pacific Ocean during the beginning stage. Following the low-frequency eddy forcing, momentum forcing anomalies due to the high-frequency eddies rapidly appear. This forcing continues to drive the polar jet poleward over the whole of longitude, while the low-frequency eddies have completed their role of inducing the anomalous poleward momentum flux during the earlier stage. For the equatorward transitional events, the roles of the low-frequency eddy forcing differ from that in the poleward ones. Anomalous equatorward momentum fluxes due to low-frequency eddies appear simultaneously with that due to high-frequency eddies. Quasi-stationary Rossby waves with wavelengths of 7000 km propagate southeastward through the waveguide over the Pacific Ocean. The convergence of their wave activity results in the deceleration of the westerlies over the higher latitudes of the Pacific Ocean. On the other hand, the high-frequency eddy forcing contributes to the equatorward jet drift longitudinally over the whole of the hemisphere.

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da Silva, Lucas A., Eulanda M. dos Santos, Leo Araújo, Natalia S. Freire, Max Vasconcelos, Rafael Giusti, David Ferreira i in. "Spatio-Temporal Deep Learning-Based Methods for Defect Detection: An Industrial Application Study Case". Applied Sciences 11, nr 22 (17.11.2021): 10861. http://dx.doi.org/10.3390/app112210861.

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Data-driven methods—particularly machine learning techniques—are expected to play a key role in the headway of Industry 4.0. One increasingly popular application in this context is when anomaly detection is employed to test manufactured goods in assembly lines. In this work, we compare supervised, semi/weakly-supervised, and unsupervised strategies to detect anomalous sequences in video samples which may be indicative of defective televisions assembled in a factory. We compare 3D autoencoders, convolutional neural networks, and generative adversarial networks (GANs) with data collected in a laboratory. Our methodology to simulate anomalies commonly found in TV devices is discussed in this paper. We also propose an approach to generate anomalous sequences similar to those produced by a defective device as part of our GAN approach. Our results show that autoencoders perform poorly when trained with only non-anomalous data—which is important because class imbalance in industrial applications is typically skewed towards the non-anomalous class. However, we show that fine-tuning the GAN is a feasible approach to overcome this problem, achieving results comparable to those of supervised methods.

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Trajanovski, Pece, Petar Jolakoski, Ljupco Kocarev i Trifce Sandev. "Ornstein–Uhlenbeck Process on Three-Dimensional Comb under Stochastic Resetting". Mathematics 11, nr 16 (18.08.2023): 3576. http://dx.doi.org/10.3390/math11163576.

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The Ornstein–Uhlenbeck (O-U) process with resetting is considered as the anomalous transport taking place on a three-dimensional comb. The three-dimensional comb is a comb inside a comb structure, consisting of backbones and fingers in the following geometrical correspondence x–backbone →y–fingers–backbone →z–fingers. Realisation of the O-U process on the three-dimensional comb leads to anomalous (non-Markovian) diffusion. This specific anomalous transport in the presence of resets results in non-equilibrium stationary states. Explicit analytical expressions for the mean values and the mean squared displacements along all three directions of the comb are obtained and verified numerically. The marginal probability density functions for each direction are obtained numerically by Monte Carlo simulation of a random transport described by a system of coupled Langevin equations for the comb geometry.

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Chan i Chin. "Unsupervised Bayesian Nonparametric Approach with Incremental Similarity Tracking of Unlabeled Water Demand Time Series for Anomaly Detection". Water 11, nr 10 (3.10.2019): 2066. http://dx.doi.org/10.3390/w11102066.

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In this paper, a fusion of unsupervised clustering and incremental similarity tracking of hourly water demand series is proposed. Current research using unsupervised methodologies to detect anomalous water is limited and may possess several limitations such as a large amount of dataset, the need to select an optimal cluster number, or low detection accuracy. Our proposed approach aims to address the need for a large amount of dataset by detecting anomaly through (1) clustering points that are relatively similar at each time step, (2) clustering points at each time step by the similarity in how they vary from each time step, and (3) to compare the incoming points with a reference shape for online anomalous trend detection. Secondly, through the use of Bayesian nonparametric approach such as the Dirichlet Process Mixture Model, the need to choose an optimal cluster number is eliminated and provides a subtle solution for ‘reserving’ an empty cluster for the future anomaly. Among the 165 randomly generated anomalies, the proposed approach detected a total of 159 anomalies and other anomalous trends present in the data. As the data is unlabeled, identified anomalous trends cannot be verified. However, results show great potential in using minimally unlabeled water demand data for a preliminary anomaly detection.

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Rijayanti, Rita, Mintae Hwang i Kyohong Jin. "Detection of Anomalous Behavior of Manufacturing Workers Using Deep Learning-Based Recognition of Human–Object Interaction". Applied Sciences 13, nr 15 (26.07.2023): 8584. http://dx.doi.org/10.3390/app13158584.

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The increasing demand for industrial products has expanded production quantities, leading to negative effects on product quality, worker productivity, and safety during working hours. Therefore, monitoring the conditions in manufacturing environments, particularly human workers, is crucial. Accordingly, this study presents a model that detects workers’ anomalous behavior in manufacturing environments. The objective is to determine worker movements, postures, and interactions with surrounding objects based on human–object interactions using a Mask R-CNN, MediaPipe Holistic, a long short-term memory (LSTM), and worker behavior description algorithm. The process begins by recognizing the objects within video frames using a Mask R-CNN. Afterward, worker poses are recognized and classified based on object positions using a deep learning-based approach. Next, we identified the patterns or characteristics that signified normal or anomalous behavior. In this case, anomalous behavior consists of anomalies correlated with human pose recognition (emergencies: worker falls, slips, or becomes ill) and human pose recognition with object positions (tool breakage and machine failure). The findings suggest that the model successfully distinguished anomalous behavior and attained the highest pose recognition accuracy (approximately 96%) for standing, touching, and holding, and the lowest accuracy (approximately 88%) for sitting. In addition, the model achieved an object detection accuracy of approximately 97%.

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Osvensky, V. B., I. V. Stepantsova i Yu N. Bolsheva. "Anomalous behaviour of dopants in GaAs during growth process". Acta Physica Hungarica 70, nr 3 (sierpień 1991): 191–96. http://dx.doi.org/10.1007/bf03156265.

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Kai, Shoichi, Tomohiko Mitani i Masahiro Fujikawa. "Anomalous Biophoton Emission during Germination Process of Red Bean". Japanese Journal of Applied Physics 32, Part 2, No. 3B (15.03.1993): L417—L419. http://dx.doi.org/10.1143/jjap.32.l417.

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Phuoc, N. N., N. A. Tuan, N. P. Thuy, D. Babonneau i J. Rabier. "Anomalous magnetization process in exchange-biased MnPd/Co bilayers". Physica B: Condensed Matter 327, nr 2-4 (kwiecień 2003): 385–88. http://dx.doi.org/10.1016/s0921-4526(02)01751-9.

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Srokowski, Tomasz. "Anomalous diffusion for a correlated process with long jumps". Physica A: Statistical Mechanics and its Applications 390, nr 18-19 (wrzesień 2011): 3077–85. http://dx.doi.org/10.1016/j.physa.2011.04.022.

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Nikan, O., J. A. Tenreiro Machado, A. Golbabai i T. Nikazad. "Numerical investigation of the nonlinear modified anomalous diffusion process". Nonlinear Dynamics 97, nr 4 (5.08.2019): 2757–75. http://dx.doi.org/10.1007/s11071-019-05160-w.

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da S Senra Filho, A. C., C. E. Garrido Salmon i L. O. Murta Junior. "Anomalous diffusion process applied to magnetic resonance image enhancement". Physics in Medicine and Biology 60, nr 6 (26.02.2015): 2355–73. http://dx.doi.org/10.1088/0031-9155/60/6/2355.

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Cosenza, Philippe, i Dean Korošak. "Secondary consolidation of clay as an anomalous diffusion process". International Journal for Numerical and Analytical Methods in Geomechanics 38, nr 12 (12.02.2014): 1231–46. http://dx.doi.org/10.1002/nag.2256.

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Rahul Chand Reddy, P., i P. S. Salvekar. "Phytoplankton blooms induced/sustained by cyclonic eddies during the Indian Ocean Dipole event of 1997 along the southern coasts of Java and Sumatra". Biogeosciences Discussions 5, nr 5 (26.09.2008): 3905–18. http://dx.doi.org/10.5194/bgd-5-3905-2008.

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Abstract. The Indonesian archipelago is the gateway in the tropics connecting two oceans (Pacific and the Indian Ocean) and two continents (Asia and Australia). During the Indian Ocean Dipole 1997, record anomalous and unanticipated upwelling had occurred along the southern coasts of Java and Sumatra causing massive phytoplankton blooms. But the method/mode/process for such anomalous upwelling was not known. Using monthly SeaWifs chlorophyll-a anomalies, TOPEX Sea Surface Height (SSH) anomalies, Sea Surface Temperatures (SST) and currents from a state-of-the-art OGCM, we report the presence of a series of cyclonic eddies along southern coasts of Sumatra and Java during November, December 1997 and January 1998. Upwelling caused by these cyclonic eddies, as also supported by the SSH and SST anomalies, has been responsible for the phytoplankton blooms to persist and dissipate during the 3 months (November, December 1997 and January 1998).

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Lu, Ke, Xianwen Fang i Na Fang. "PN-BBN: A Petri Net-Based Bayesian Network for Anomalous Behavior Detection". Mathematics 10, nr 20 (14.10.2022): 3790. http://dx.doi.org/10.3390/math10203790.

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Business process anomalous behavior detection reveals unexpected cases from event logs to ensure the trusted operation of information systems. Anomaly behavior is mainly identified through a log-to-model alignment analysis or numerical outlier detection. However, both approaches ignore the influence of probability distributions or activity relationships in process activities. Based on this concern, this paper incorporates the behavioral relationships characterized by the process model and the joint probability distribution of nodes related to suspected anomalous behaviors. Moreover, a Petri Net-Based Bayesian Network (PN-BBN) is proposed to detect anomalous behaviors based on the probabilistic inference of behavioral contexts. First, the process model is filtered based on the process structure of the process activities to identify the key regions where the suspected anomalous behaviors are located. Then, the behavioral profile of the activity is used to prune it to position the ineluctable paths that trigger these activities. Further, the model is used as the architecture for parameter learning to construct the PN-BBN. Based on this, anomaly scores are inferred based on the joint probabilities of activities related to suspected anomalous behaviors for anomaly detection under the constraints of control flow and probability distributions. Finally, PN-BBN is implemented based on the open-source frameworks PM4PY and PMGPY and evaluated from multiple metrics with synthetic and real process data. The experimental results demonstrate that PN-BBN effectively identifies anomalous process behaviors and improves the reliability of information systems.

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Marchuk, Vladimir I., i Dmitriy Y. Chernyshov. "Methods of substitution detected anomalous values in the realization of a random process". MATEC Web of Conferences 226 (2018): 05005. http://dx.doi.org/10.1051/matecconf/201822605005.

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The paper considers a proposed method of detecting anomalous values in the realization of a random process in case of a limited amount of a priori information about the statistical characteristics of the noise component. A new approach is proposed to replace the detected anomalous values, which does not introduce a correlation relation into the results of the output pro-cessed random process.

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Jasra, Sameer Kumar, Gianluca Valentino, Alan Muscat i Robert Camilleri. "Hybrid Machine Learning–Statistical Method for Anomaly Detection in Flight Data". Applied Sciences 12, nr 20 (12.10.2022): 10261. http://dx.doi.org/10.3390/app122010261.

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This paper investigates the use of an unsupervised hybrid statistical–local outlier factor algorithm to detect anomalies in time-series flight data. Flight data analysis is an activity carried out by airlines primarily as a means of improving the safety and operation of their fleet. Traditionally, this is performed by checking exceedances in pre-set limits to the flight data parameters. However, this method highlights single events during a flight, making this analysis laborious. The process also fails to establish trends or reflect potential unknown hazards. This research took advantage of machine learning techniques to recognize patterns in large datasets by implementing the local outlier factor (LOF). In order to minimize human input, a statistical approach was adopted to establish the threshold value above which the flights are considered to be anomalous and interpret the scores. This paper shows that LOF quantifies the degree of outlier-ness of an outlier rather than binary categorizing a point into inlier or outlier, as in the case of clustering algorithms. Thus, with LOF, for the first time, we demonstrated that in the aviation industry, anomalous flights could not only be identified but also be given an anomaly score to compare two anomalous flights in an unsupervised manner. Furthermore, LOF helps to track anomalous behavior in time during the flight. This is insightful when a flight is abnormal, only for some seconds or short duration. For the first time, we attempted to detect flight parameters responsible for anomalous behavior or at least give direction to human experts looking for the cause of abnormal behavior. This was all analyzed with real-life flight data in an unsupervised manner in contrast to simulated data.

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Fan, Lingli, Jianjun Xu i Huade Guan. "Impacts of Different Onset Time El Niño Events on Winter Precipitation over South China". Atmosphere 9, nr 10 (20.09.2018): 366. http://dx.doi.org/10.3390/atmos9100366.

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Winter precipitation over South China tended to be much higher than normal for the spring El Niño events during 1979–2016. For the spring El Niño events, the meridional and zonal circulations served as a bridge, linking the warmer sea surface temperature (SST) in the eastern equatorial Pacific (EEP) and South China winter precipitation. This possible physical process can be described as follows: During boreal winter, a positive SST anomaly in the EEP was concurrent with strong anomalous convection activity over South China via anomalous Walker circulation, an anomalous Hadley Cell along 110°–130° E, and a zonal westward teleconnection wave train pattern at 700 hPa in the Northern Hemisphere. In addition, an anomalous pumping effect at 200 hPa contributed to the convective activity. Meanwhile, the western Pacific subtropical high moved southwards and strengthened at 500 hPa, and abnormal southwesterly winds brought plentiful water vapor to South China at 850 hPa. All these factors favored an increase in precipitation over South China. For the summer El Niño events, the aforementioned anomalies were weaker, which resulted in a precipitation close to normal over South China.

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40

Tavares, Gabriel Marques, Victor Guilherme Turrisi da Costa, Vinicius Eiji Martins, Paolo Ceravolo i Sylvio Barbon Jr. "Leveraging Anomaly Detection in Business Process with Data Stream Mining". iSys - Brazilian Journal of Information Systems 12, nr 1 (17.04.2019): 54–75. http://dx.doi.org/10.5753/isys.2019.383.

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Identifying fraudulent or anomalous business procedures is today a key challenge for organisations of any dimension. Nonetheless, the continuous nature of business activities conveys to the continuous acquisition of data in support of business process monitoring. In light of this, we propose a method for online anomaly detection in business processes. From a stream of events, our approach extract cases descriptors and applies a density-based clustering technique to detect outliers. We applied our method to a real-life dataset, and we used streaming clustering measures for evaluating performances. Exploring different combinations of parameters, we obtained promising performance metrics, showing that our method is capable of finding anomalous process instances in a vast complexity of scenarios.

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41

Manev, Angel. "Tropopause dynamics and temperature anomalies on the Black Sea surface". Journal scientific and applied research 1, nr 1 (3.03.2012): 114–21. http://dx.doi.org/10.46687/jsar.v1i1.27.

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The suggested research analyzes the tropopause dynamics during the short-term temperature anomalies on the Black Sea surface for a period of 11 years. Satellite data for the condition of the tropopause and the temperature fields on the sea surface are used as a basis from several satellite systems. Tropopause uplifting is registered almost always before the onset of anomalous surface heating process. Issues are dis-cussed for the generation of the temperature anomalies and their connection with the atmospheric processes.

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42

Teuerle, Marek, Agnieszka Wyłomańska i Grzegorz Sikora. "Modeling anomalous diffusion by a subordinated fractional Lévy-stable process". Journal of Statistical Mechanics: Theory and Experiment 2013, nr 05 (31.05.2013): P05016. http://dx.doi.org/10.1088/1742-5468/2013/05/p05016.

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Lenzi, E. K., L. R. Evangelista, G. Barbero i F. Mantegazza. "Anomalous diffusion and the adsorption-desorption process in anisotropic media". EPL (Europhysics Letters) 85, nr 2 (styczeń 2009): 28004. http://dx.doi.org/10.1209/0295-5075/85/28004.

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Tavares, F. W., P. M. Ndiaye, E. K. Lenzi, L. R. Evangelista, H. V. Ribeiro i R. S. Zola. "Anomalous diffusion and sorption-desorption process in complex fluid systems". Communications in Nonlinear Science and Numerical Simulation 90 (listopad 2020): 105411. http://dx.doi.org/10.1016/j.cnsns.2020.105411.

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Godinho, M., P. Estrela, A. P. Gonçalves, M. Almeida, J. C. Spirlet i G. Bonfait. "Anomalous magnetisation process in UFe4Al8 probed by magnetisation and magnetoresistance". Journal of Magnetism and Magnetic Materials 157-158 (maj 1996): 690–91. http://dx.doi.org/10.1016/0304-8853(95)01025-4.

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Yoshida, N., M. Nakanishi, K. Ikegami, S. Shimura i S. Kishimoto. "Anomalous Behavior of Glassy GeO2in the Reduction Process by Hydrogen". Berichte der Bunsengesellschaft für physikalische Chemie 91, nr 6 (czerwiec 1987): 666–70. http://dx.doi.org/10.1002/bbpc.19870910616.

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Rasulova, A., i A. Izmailova. "Application of the Isolation Forest Algorithm to Substantiate the Uniqueness of Water Bodies in the Group of Karst Lakes". Bulletin of Science and Practice 7, nr 11 (15.11.2021): 63–79. http://dx.doi.org/10.33619/2414-2948/72/08.

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Improving the scientific foundations for the development and expansion of the network of specially protected natural areas requires the search for algorithms that could be used to identify unique ecosystems. Algorithmization of the anomaly identification process provides an opportunity not only to process large amounts of data but also leads to obtaining objective and comparable estimates. The purpose of this research is to identify the most optimal mechanisms for identifying anomalous values for the morphometric characteristics of karst lakes, which may indicate the uniqueness of the entire lake ecosystem. Within the framework of this article, the study was carried out based on a mathematical analysis of samples built for various characteristics based on the WORLDLAKE database. Statistical methods and the Isolation Forest (iForest) machine learning algorithm were used as methods of analysis. As a result of applying the iForest algorithm to a sample of morphometric parameters of karst lakes, consisting of 738 objects, 43 anomalous water bodies were identified. An expert assessment of the final set of lakes for the uniqueness of their ecosystems showed that the chosen method for identifying anomalous values is well suited for the task at hand. Many lakes with an anomaly index above 60% can be recognized as unique due to the unusualness of their abiotic characteristics; a number of them also have a peculiar biota. The anomalous objects included such well-known lakes as Tserik-Kol’, Crveno, Salda Lake, Trihonida, Vegoritida, Petron, etc. Moreover, for most of them, anomalies were detected for several parameters at once. Thus, the applied algorithm for identifying anomalous morphometric characteristics of lakes made it possible to obtain interesting samples for further expert analysis of the entire lake ecosystem for its uniqueness.

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Dias, B., I. Araya, J. P. Nogueira-Cavalcante, L. Saker i A. Shokry. "Galactic or extragalactic chemical tagging for NGC 3201?" Astronomy & Astrophysics 614 (czerwiec 2018): A146. http://dx.doi.org/10.1051/0004-6361/201731957.

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Context. The origin of the globular cluster (GC) NGC 3201 is under debate. Its retrograde orbit points to an extragalactic origin, but no further chemical evidence supports this idea. Light-element chemical abundances are useful to tag GCs and can be used to shed light on this discussion. Aims. Recently it was shown that the CN and CH indices are useful to identify GCs that are anomalous to those typically found in the Milky Way. A possible origin of anomalous clusters is the merger of two GCs and/or the nucleus of a dwarf galaxy. We aim to derive CN and CH band strengths for red giant stars in NGC3201 and compare these with photometric indices and high-resolution spectroscopy and discuss in the context of GC chemical tagging. Methods. We measure molecular band indices of S(3839) and G4300 for CN and CH, respectively from low-resolution spectra of red giant stars. Gravity and temperature effects are removed. Photometric indices are used to indicate further chemical information on C+N+O or s-process element abundances that are not derived from low-resolution spectra. Results. We found three groups in the CN–CH distribution. A main sequence (S1), a secondary less-populated sequence (S2), and a group of peculiar (pec) CN-weak and CH-weak stars, one of which was previously known. The three groups seem to have different C+N+O and/or s-process element abundances, to be confirmed by high-resolution spectroscopy. These are typical characteristics of anomalous GCs. The CN distribution of NGC 3201 is quadrimodal, which is more common in anomalous clusters. However, NGC 3201 does not belong to the trend of anomalous GCs in the mass-size relation. Conclusions. The globular cluster NGC 3201 shows signs that it can be chemically tagged as anomalous: it has an unusual CN–CH relation, indications that pec-S1-S2 is an increasing sequence of C+N+O or s-process element abundances, and a multi-modal CN distribution that seems to correlate with s-process element abundances. The non-anomalous characteristics are that it has a debatable Fe-spread and it does not follow the trend of mass size of all anomalous clusters. Three scenarios are postulated here: (i) if the sequence pec-S1-S2 has increasing C+N+O and s-process element abundances, NGC 3201 would be the first anomalous GC outside of the mass-size relation; (ii) if the abundances are almost constant, NGC 3201 would be the first non-anomalous GC with multiple CN–CH anti-correlation groups; or (iii) it would be the first anomalous GC without variations in C+N+O and s-process element abundances. In all cases, the definition of anomalous clusters and the scenario in which they have an extragalactic origin must be revised.

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Jiang, Xiaoying, Xiangzeng Kong i Gongde Guo. "A method of identifying and analyzing Outgoing Long-wave Radiation anomalies before earthquake". MATEC Web of Conferences 189 (2018): 11001. http://dx.doi.org/10.1051/matecconf/201818911001.

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A large amount of anomalous information will appear before the earthquake, but it is difficult to identify and analyze valuable anomalous information from large-scale data. To solve this problem, this paper presents a method of pre-earthquake Outgoing Long-wave Radiation (OLR) anomaly identification and analysis based on quantum walking algorithm. The National Oceanic and Atmospheric Administration (NOAA) data are used to process and analyze the OLR data before and after the 6 major earthquakes in 2017 in western China.The results show that different degrees of thermal infrared anomalies have appeared before and after these large earthquakes. In this paper, we also analyze and discuss the similarities and differences of these changes by combining geological conditions and other factors.

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Kosztołowicz, T., i K. D. Lewandowska. "Anomalous Diffusion in a Membrane System". Ukrainian Journal of Physics 56, nr 8 (9.02.2022): 824. http://dx.doi.org/10.15407/ujpe56.8.824.

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We briefly discuss the physical basis of anomalous diffusion and equations with fractional derivatives, which describe this process. We also present the method of extracting subdiffusion parameters from experimental data.

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