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Thematische Bibliographien / Hidden Markov models indexed by trees / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Hidden Markov models indexed by trees“

Autor: Grafiati

Veröffentlicht am 14. Dezember 2024

Zuletzt aktualisiert am 19. Juli 2025

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1

Herrera, F., U. A. Rozikov, and M. V. Velasco. "Ising models with hidden Markov structure: applications to probabilistic inference in machine learning." Journal of Statistical Mechanics: Theory and Experiment 2025, no. 7 (2025): 073201. https://doi.org/10.1088/1742-5468/ade5f8.

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Abstract In this paper, we investigate tree-indexed Markov chains (Gibbs measures) defined by a Hamiltonian that couples two Ising layers: hidden spins s ( x ) ∈ { ± 1 } and observed spins σ ( x ) ∈ { ± 1 } on a Cayley tree. The Hamiltonian incorporates Ising interactions within each layer and site-wise emission couplings between layers, extending hidden Markov models to a bilayer Markov random field. Specifically, we explore translation-invariant Gibbs measures (TIGMs) of this Hamiltonian on Cayley trees. Under certain explicit conditions on the model’s parameters, we demonstrate that there c

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Huang, Huilin. "Strong Law of Large Numbers for Hidden Markov Chains Indexed by Cayley Trees." ISRN Probability and Statistics 2012 (September 23, 2012): 1–11. http://dx.doi.org/10.5402/2012/768657.

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We extend the idea of hidden Markov chains on lines to the situation of hidden Markov chains indexed by Cayley trees. Then, we study the strong law of large numbers for hidden Markov chains indexed by Cayley trees. As a corollary, we get the strong limit law of the conditional sample entropy rate.

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Milone, Diego H., Leandro E. Di Persia, and María E. Torres. "Denoising and recognition using hidden Markov models with observation distributions modeled by hidden Markov trees." Pattern Recognition 43, no. 4 (2010): 1577–89. http://dx.doi.org/10.1016/j.patcog.2009.11.010.

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ANIGBOGU, J. C., and A. BELAÏD. "HIDDEN MARKOV MODELS IN TEXT RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 09, no. 06 (1995): 925–58. http://dx.doi.org/10.1142/s0218001495000389.

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A multi-level multifont character recognition is presented. The system proceeds by first delimiting the context of the characters. As a way of enhancing system performance, typographical information is extracted and used for font identification before actual character recognition is performed. This has the advantage of sure character identification as well as text reproduction in its original form. The font identification is based on decision trees where the characters are automatically arranged differently in confusion classes according to the physical characteristics of fonts. The character

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Fredes, Luis, and Jean-François Marckert. "Invariant measures of interacting particle systems: Algebraic aspects." ESAIM: Probability and Statistics 24 (2020): 526–80. http://dx.doi.org/10.1051/ps/2020008.

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Consider a continuous time particle system ηt = (ηt(k), k ∈ 𝕃), indexed by a lattice 𝕃 which will be either ℤ, ℤ∕nℤ, a segment {1, ⋯ , n}, or ℤd, and taking its values in the set Eκ𝕃 where Eκ = {0, ⋯ , κ − 1} for some fixed κ ∈{∞, 2, 3, ⋯ }. Assume that the Markovian evolution of the particle system (PS) is driven by some translation invariant local dynamics with bounded range, encoded by a jump rate matrix ⊤. These are standard settings, satisfied by the TASEP, the voter models, the contact processes. The aim of this paper is to provide some sufficient and/or necessary conditions on the matri

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Narayana, Pradyumna, J. Ross Beveridge, and Bruce A. Draper. "Interacting Hidden Markov Models for Video Understanding." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 11 (2018): 1855020. http://dx.doi.org/10.1142/s0218001418550200.

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People, cars and other moving objects in videos generate time series data that can be labeled in many ways. For example, classifiers can label motion tracks according to the object type, the action being performed, or the trajectory of the motion. These labels can be generated for every frame as long as the object stays in view, so object tracks can be modeled as Markov processes with multiple noisy observation streams. A challenge in video recognition is to recover the true state of the track (i.e. its class, action and trajectory) using Markov models without (a) counter-factually assuming th

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Durand, J. B., P. Goncalves, and Y. Guedon. "Computational Methods for Hidden Markov Tree Models—An Application to Wavelet Trees." IEEE Transactions on Signal Processing 52, no. 9 (2004): 2551–60. http://dx.doi.org/10.1109/tsp.2004.832006.

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Tso, Brandt, and Joe L. Tseng. "Multi-resolution semantic-based imagery retrieval using hidden Markov models and decision trees." Expert Systems with Applications 37, no. 6 (2010): 4425–34. http://dx.doi.org/10.1016/j.eswa.2009.11.086.

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Do, M. N. "Fast approximation of Kullback-Leibler distance for dependence trees and hidden Markov models." IEEE Signal Processing Letters 10, no. 4 (2003): 115–18. http://dx.doi.org/10.1109/lsp.2003.809034.

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Maua, D. D., C. P. De Campos, A. Benavoli, and A. Antonucci. "Probabilistic Inference in Credal Networks: New Complexity Results." Journal of Artificial Intelligence Research 50 (July 28, 2014): 603–37. http://dx.doi.org/10.1613/jair.4355.

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Credal networks are graph-based statistical models whose parameters take values in a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The computational complexity of inferences on such models depends on the irrelevance/independence concept adopted. In this paper, we study inferential complexity under the concepts of epistemic irrelevance and strong independence. We show that inferences under strong independence are NP-hard even in trees with binary variables except for a single ternary one. We prove that under epistemic irrelevance the pol

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Azari, David P., Yu Hen Hu, Brady L. Miller, Brian V. Le, and Robert G. Radwin. "Using Surgeon Hand Motions to Predict Surgical Maneuvers." Human Factors: The Journal of the Human Factors and Ergonomics Society 61, no. 8 (2019): 1326–39. http://dx.doi.org/10.1177/0018720819838901.

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Objective: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of surgical benchtop simulations. Background: Automatic computer vision recognition of surgical maneuvers (suturing, tying, and transition) could expedite video review and objective assessment of surgeries. Method: We recorded hand movements of 37 clinicians performing simple and running subcuticular suturing benchtop simulations, and applied three machine learning techniques (decision trees, random forests, and hidden Markov models) to classify surgical maneuvers

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Segers, Johan. "One- versus multi-component regular variation and extremes of Markov trees." Advances in Applied Probability 52, no. 3 (2020): 855–78. http://dx.doi.org/10.1017/apr.2020.22.

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AbstractA Markov tree is a random vector indexed by the nodes of a tree whose distribution is determined by the distributions of pairs of neighbouring variables and a list of conditional independence relations. Upon an assumption on the tails of the Markov kernels associated to these pairs, the conditional distribution of the self-normalized random vector when the variable at the root of the tree tends to infinity converges weakly to a random vector of coupled random walks called a tail tree. If, in addition, the conditioning variable has a regularly varying tail, the Markov tree satisfies a f

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Bischof, Walter F. "Visual Learning: An Overview." Swiss Journal of Psychology 63, no. 3 (2004): 151–64. http://dx.doi.org/10.1024/1421-0185.63.3.151.

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A review is presented of modern approaches to the learning and recognition of complex patterns, including discriminant functions, neural networks, decision trees, and hidden Markov models. Next, several relational learning systems are introduced and discussed, in detail one specific technique, conditional rule generation. This technique is shown to be very flexible and useful for the learning of static patterns, such as objects, as well as dynamic patterns, such as movement patterns. The technique is illustrated with a number of very difficult visual learning problems.

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Tür, Gökhan, Dilek Hakkani-Tür, Andreas Stolcke, and Elizabeth Shriberg. "Integrating Prosodic and Lexical Cues for Automatic Topic Segmentation." Computational Linguistics 27, no. 1 (2001): 31–57. http://dx.doi.org/10.1162/089120101300346796.

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We present a probabilistic model that uses both prosodic and lexical cues for the automatic segmentation of speech into topically coherent units. We propose two methods for combining lexical and prosodic information using hidden Markov models and decision trees. Lexical information is obtained from a speech recognizer, and prosodic features are extracted automatically from speech waveforms. We evaluate our approach on the Broadcast News corpus, using the DARPA-TDT evaluation metrics. Results show that the prosodic model alone is competitive with word-based segmentation methods. Furthermore, we

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Loomis, Samuel P., and James P. Crutchfield. "Exploring predictive states via Cantor embeddings and Wasserstein distance." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 12 (2022): 123115. http://dx.doi.org/10.1063/5.0102603.

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Predictive states for stochastic processes are a nonparametric and interpretable construct with relevance across a multitude of modeling paradigms. Recent progress on the self-supervised reconstruction of predictive states from time-series data focused on the use of reproducing kernel Hilbert spaces. Here, we examine how Wasserstein distances may be used to detect predictive equivalences in symbolic data. We compute Wasserstein distances between distributions over sequences (“predictions”) using a finite-dimensional embedding of sequences based on the Cantor set for the underlying geometry. We

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SNIR, SAGI, and TAMIR TULLER. "THE NET-HMM APPROACH: PHYLOGENETIC NETWORK INFERENCE BY COMBINING MAXIMUM LIKELIHOOD AND HIDDEN MARKOV MODELS." Journal of Bioinformatics and Computational Biology 07, no. 04 (2009): 625–44. http://dx.doi.org/10.1142/s021972000900428x.

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Horizontal gene transfer (HGT) is the event of transferring genetic material from one lineage in the evolutionary tree to a different lineage. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Although the prevailing assumption is of complete HGT, cases of partial HGT (which are also named chimeric HGT) where only part of a gene is horizontally transferred, have also been reported, albeit less frequently. In this work we suggest a new probabilistic model, the NET-HMM, for analyzing and modeling phyloge

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Prokofieva, A. V., and A. N. Shniperov. "A Markov Chain - Based Method for JPEG Image Steganalysis and Its Application in Combination with Various Machine Learning Algorithms." Vestnik NSU. Series: Information Technologies 20, no. 4 (2023): 61–75. http://dx.doi.org/10.25205/1818-7900-2022-20-4-61-75.

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The paper proposes a method of extracting the feature vector of images, which makes it possible to effectively detect the presence of hidden information in JPEG images embedded by various popular steganography tools. This method is based on the usage of the transition probability matrix. The essence of the method for extracting the feature vector of the image is to use the transition probability matrix and apply the image calibration method to improve the accuracy of steganalysis and reduce the number of false positives. For each image from the training and test sets a feature vector is found

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Costes, Evelyne, Colin Smith, Michael Renton, Yann Guédon, Przemyslaw Prusinkiewicz, and Christophe Godin. "MAppleT: simulation of apple tree development using mixed stochastic and biomechanical models." Functional Plant Biology 35, no. 10 (2008): 936. http://dx.doi.org/10.1071/fp08081.

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Construction of tree architectural databases over years is time consuming and cannot easily capture event dynamics, especially when both tree topology and geometry are considered. The present project aimed to bring together models of topology and geometry in a single simulation such that the architecture of an apple tree may emerge from process interactions. This integration was performed using L-systems. A mixed approach was developed based on stochastic models to simulate plant topology and mechanistic model for the geometry. The succession of growth units (GUs) along axes and their branchin

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Ogundile, Olayinka, Oluwaseyi Babalola, Afolakemi Ogunbanwo, Olabisi Ogundile, and Vipin Balyan. "Credit Card Fraud: Analysis of Feature Extraction Techniques for Ensemble Hidden Markov Model Prediction Approach." Applied Sciences 14, no. 16 (2024): 7389. http://dx.doi.org/10.3390/app14167389.

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In the face of escalating credit card fraud due to the surge in e-commerce activities, effectively distinguishing between legitimate and fraudulent transactions has become increasingly challenging. To address this, various machine learning (ML) techniques have been employed to safeguard cardholders and financial institutions. This article explores the use of the Ensemble Hidden Markov Model (EHMM) combined with two distinct feature extraction methods: principal component analysis (PCA) and a proposed statistical feature set termed MRE, comprising Mean, Relative Amplitude, and Entropy. Both the

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Holmes, Ian. "Using evolutionary Expectation Maximization to estimate indel rates." Bioinformatics 21, no. 10 (2005): 2294–300. http://dx.doi.org/10.1093/bioinformatics/bti177.

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Abstract Motivation The Expectation Maximization (EM) algorithm, in the form of the Baum–Welch algorithm (for hidden Markov models) or the Inside-Outside algorithm (for stochastic context-free grammars), is a powerful way to estimate the parameters of stochastic grammars for biological sequence analysis. To use this algorithm for multiple-sequence evolutionary modelling, it would be useful to apply the EM algorithm to estimate not only the probability parameters of the stochastic grammar, but also the instantaneous mutation rates of the underlying evolutionary model (to facilitate the developm

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Griffin, Kevin, Thomas Harris, Sarah Bruner, Patrick McKenzie, and Jeremy Hise. "Is the Radial Growth of Irrigated Urban Trees More Strongly Correlated to Light and Temperature than Water?" Arboriculture & Urban Forestry 47, no. 5 (2021): 214–31. http://dx.doi.org/10.48044/jauf.2021.019.

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Background: Real-time monitoring of tree growth can provide novel information about trees in urban/suburban areas and the myriad ecosystem services they provide. By monitoring irrigated specimen trees, we tested the hypothesis that in trees with sufficient water, growth is governed by environmental factors regulating energy gain rather than by factors related to water use. Methods: Internet-enabled, high-resolution dendrometers were installed on 3 trees in Southampton, NY, USA. The instruments, along with a weather station, streamed data to a project web page that was updated once an hour. Gro

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Mouaz, Bezoui, Cherif Walid, Beni-Hssane Abderrahim, and Elmoutaouakkil Abdelmajid. "A new framework based on KNN and DT for speech identification through emphatic letters in Moroccan dialect." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 3 (2021): 1417–23. https://doi.org/10.11591/ijeecs.v21.i3.pp1417-1423.

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Arabic dialects differ substantially from modern standard arabic and each other in terms of phonology, morphology, lexical choice and syntax. This makes the identification of dialects from speeches a very difficult task. In this paper, we introduce a speech recognition system that automatically identifies the gender of speaker, the emphatic letter pronounced and also the diacritic of these emphatic letters given a sample of author’s speeches. Firstly we examined the performance of the single case classifier hidden markov models (HMM) applied to the samples of our data corpus. Then we eva

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Ghahramani, Zoubin. "Bayesian non-parametrics and the probabilistic approach to modelling." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1984 (2013): 20110553. http://dx.doi.org/10.1098/rsta.2011.0553.

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Modelling is fundamental to many fields of science and engineering. A model can be thought of as a representation of possible data one could predict from a system. The probabilistic approach to modelling uses probability theory to express all aspects of uncertainty in the model. The probabilistic approach is synonymous with Bayesian modelling, which simply uses the rules of probability theory in order to make predictions, compare alternative models, and learn model parameters and structure from data. This simple and elegant framework is most powerful when coupled with flexible probabilistic mo

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Nzenwata, Uchenna Jeremiah, Goodness Oluwamayokun Opateye, Noze-Otote Aisosa, et al. "Autonomous Database Systems – A Systematic Review of Self-Healing and Self-Tuning Database Systems." Asian Journal of Research in Computer Science 18, no. 7 (2025): 77–87. https://doi.org/10.9734/ajrcos/2025/v18i7721.

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Problem Statement: Autonomous database systems represent a significant change in the management of databases, utilizing Machine Learning (ML) and Artificial Intelligence (AI) in order to carry out self-healing and self-tuning with minimal human intervention. Objectives: This systematic review investigates the defining characteristics, AI/ML techniques, challenges and the future trends of self-healing and self-tuning autonomous databases. Methodology: The research questions were answered integrating findings from 35 current literatures between 2020 and 2025. These literatures were obtained from

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Mouaz, Bezoui, Cherif Walid, Beni-Hssane Abderrahim, and Elmoutaouakkil Abdelmajid. "A new framework based on KNN and DT for speech identification through emphatic letters in Moroccan dialect." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 3 (2021): 1417. http://dx.doi.org/10.11591/ijeecs.v21.i3.pp1417-1423.

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<p class="keywords"><span id="docs-internal-guid-6347807a-7fff-e7da-a2d6-74cb8393677f"><span>Arabic dialects differ substantially from modern standard arabic and each other in terms of phonology, morphology, lexical choice and syntax. This makes the identification of dialects from speeches a very difficult task. In this paper, we introduce a speech recognition system that automatically identifies the gender of speaker, the emphatic letter pronounced and also the diacritic of these emphatic letters given a sample of author’s speeches. Firstly we examined the performance of the

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Negrón, Claudia, Loreto Contador, Bruce D. Lampinen, et al. "How different pruning severities alter shoot structure: a modelling approach in young ‘Nonpareil’ almond trees." Functional Plant Biology 42, no. 3 (2015): 325. http://dx.doi.org/10.1071/fp14025.

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Axillary meristem fate patterns along shoots, also referred to as shoot structure, appear to be fairly consistent among trees within a genotype growing under similar conditions. Less is known about shoot structural plasticity following external manipulations, such as pruning. The aim of this study on almond (Prunus dulcis (Mill.)) shoots was to investigate how pruning severity affects the structure of 1-year-old shoots that grew after pruning (regrowth shoots), the 2-year-old portion of shoots that remained from the previous year’s growth after pruning (pruned shoots), and whether regrowth sho

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Schirmer, Michael, Michael Lehning, and Jürg Schweizer. "Statistical forecasting of regional avalanche danger using simulated snow-cover data." Journal of Glaciology 55, no. 193 (2009): 761–68. http://dx.doi.org/10.3189/002214309790152429.

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AbstractIn the past, numerical prediction of regional avalanche danger using statistical methods with meteorological input variables has shown insufficiently accurate results, possibly due to the lack of snowstratigraphy data. Detailed snow-cover data were rarely used because they were not readily available (manual observations). With the development and increasing use of snow-cover models this deficiency can now be rectified and model output can be used as input for forecasting models. We used the output of the physically based snow-cover model SNOWPACK combined with meteorological variables

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Aman, Pawar. "Crime Prevention and Addressing Violence Against Women." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 609–13. http://dx.doi.org/10.22214/ijraset.2024.65134.

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The safety of women remains a pressing societal concern, with many facing threats like harassment, rape, molestation, and domestic abuse due to various sociocultural factors. The Internet of Things (IoT) has emerged as a promising tool to address these issues. This study systematically reviews research papers on IoT-based devices for women's safety, analyzing key features, wearable components, sensor types, and machine learning algorithms used. The review covers articles published between 2016 and 2022. It finds that pulse-rate and pressure sensors are commonly used to monitor women in distres

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Moraru, Cristina. "VirClust—A Tool for Hierarchical Clustering, Core Protein Detection and Annotation of (Prokaryotic) Viruses." Viruses 15, no. 4 (2023): 1007. http://dx.doi.org/10.3390/v15041007.

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Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called “megataxonomy of viruses”, recognizes six different viral realms, defined based on the presence of viral hallmark genes (VHGs). Within the realms, viruses are classified into hierarchical taxons, ideally defined by the phylogeny of their shared genes. To enable the detection of shared genes, viruses have first to be clustered, and there is currently a need for tools to assist with virus clustering and classification. Here, VirClust is presented. It is a no

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Stolcke, Andreas, Klaus Ries, Noah Coccaro, et al. "Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech." Computational Linguistics 26, no. 3 (2000): 339–73. http://dx.doi.org/10.1162/089120100561737.

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We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as STATEMENT, Question, BACKCHANNEL, Agreement, Disagreement, and Apology. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence. The dialogue model is based on treating the discourse structure of a conversation as a hidden Markov model and the individual dialogue acts as observations emanating from the model states. Constraints on the likely sequence of dialogue act

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Patil, Prof Pradnya, Prof Minal Sonkar, Prof Pallavi Patil, Prof Priyanka Deshmukh, and Prof Trupti Patil. "A Comprehensive Strategy for Detecting Credit Card Fraud in E-Commerce Utilizing DNS Authentication." International Journal of Soft Computing and Engineering 14, no. 5 (2024): 30–35. http://dx.doi.org/10.35940/ijsce.f3656.14051124.

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E commerce has transformed global trade, enabling businesses to reach audiences worldwide since the World Wide Webs inception in 1990. Companies like Amazon demonstrate this growth, evolving from a small online bookstore to a retail giant. E commerces appeal lies in its global reach, cost efficiency, and 24 slash 7 availability. However, security challenges, especially credit card fraud, remain significant, causing substantial losses to businesses, particularly small and medium sized enterprises. Addressing fraud in e-commerce through machine learning techniques is crucial. Techniques such as

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Lee, Michael D. "GToTree: a user-friendly workflow for phylogenomics." Bioinformatics 35, no. 20 (2019): 4162–64. http://dx.doi.org/10.1093/bioinformatics/btz188.

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Abstract Summary Genome-level evolutionary inference (i.e. phylogenomics) is becoming an increasingly essential step in many biologists’ work. Accordingly, there are several tools available for the major steps in a phylogenomics workflow. But for the biologist whose main focus is not bioinformatics, much of the computational work required—such as accessing genomic data on large scales, integrating genomes from different file formats, performing required filtering, stitching different tools together etc.—can be prohibitive. Here I introduce GToTree, a command-line tool that can take any combina

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Prado, Lenio, Marcelo Fonseca, José V. Bernardes, Mateus G. Santos, Edson C. Bortoni, and Guilherme S. Bastos. "Forecast of Operational Downtime of the Generating Units for Sediment Cleaning in the Water Intakes: A Case of the Jirau Hydropower Plant." Energies 16, no. 17 (2023): 6354. http://dx.doi.org/10.3390/en16176354.

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Hydropower plants (HPP) in the Amazon basin suffer from issues caused by trees and sediments carried by the river. The Jirau HPP, located in the occidental Amazon basin, is directly affected by high sediment transportation. These materials accumulate in the water intakes and obstruct the trash racks installed in the intake system to prevent the entry of materials. As a result, head losses negatively impact the efficiency of the generating units and the power production capacity. The HPP operation team must monitor these losses and take action timely to clear the intakes. One of the possible ac

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Prof., Pradnya Patil. "A Comprehensive Strategy for Detecting Credit Card Fraud in E-Commerce Utilizing DNS Authentication." International Journal of Soft Computing and Engineering (IJSCE) 14, no. 5 (2024): 30–35. https://doi.org/10.35940/ijsce.F3656.14051124.

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<strong>Abstract: </strong>E-commerce has transformed global trade, enabling businesses to reach audiences worldwide since the World Wide Web's inception in 1990. Companies like Amazon demonstrate this growth, evolving from a small online bookstore to a retail giant. E-commerce's appeal lies in its global reach, cost-efficiency, and 24/7 availability. However, security challenges, especially credit card fraud, remain significant, causing substantial losses to businesses, particularly small and medium-sized enterprises. Addressing fraud in e-commerce through machine learning techniques is cruci

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Tibbetts, Jake, Bethany L. Goldblum, Christopher Stewart, and Arman Hashemizadeh. "Classification of Nuclear Reactor Operations Using Spatial Importance and Multisensor Networks." Journal of Nuclear Engineering 3, no. 4 (2022): 243–62. http://dx.doi.org/10.3390/jne3040014.

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Distributed multisensor networks record multiple data streams that can be used as inputs to machine learning models designed to classify operations relevant to proliferation at nuclear reactors. The goal of this work is to demonstrate methods to assess the importance of each node (a single multisensor) and region (a group of proximate multisensors) to machine learning model performance in a reactor monitoring scenario. This, in turn, provides insight into model behavior, a critical requirement of data-driven applications in nuclear security. Using data collected at the High Flux Isotope Reacto

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Yordanova, Kristina, Stefan Lüdtke, Samuel Whitehouse, et al. "Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring." Sensors 19, no. 3 (2019): 646. http://dx.doi.org/10.3390/s19030646.

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Wellbeing is often affected by health-related conditions. Among them are nutrition-related health conditions, which can significantly decrease the quality of life. We envision a system that monitors the kitchen activities of patients and that based on the detected eating behaviour could provide clinicians with indicators for improving a patient’s health. To be successful, such system has to reason about the person’s actions and goals. To address this problem, we introduce a symbolic behaviour recognition approach, called Computational Causal Behaviour Models (CCBM). CCBM combines symbolic repr

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Shchetinin, E. Yu. "AUTOMATIC ARRHYTHMIA DETECTION BASED ON THE ANALYSIS OF ELECTROCARDIOGRAMS WITH DEEP LEARNING." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 203 (May 2021): 18–27. http://dx.doi.org/10.14489/vkit.2021.05.pp.018-027.

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According to the World Health Organization, cardiovascular diseases (CVD) are one of the most common causes of death in the world. The most effective clinical method for visualizing the cardiac electrical activity is electrocardiography (ECG). Automated ECG analysis has been of great interest in the medical researches. The problem of automated detection of cardiac arrhythmias may be reduced to the ECG signals classification. To solve this task such methods were used as Hidden Markov Models (HMM), discrete wavelet transforms (DWT), support vector machine (SVM) etc. Now days, the deep learning m

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Liu, Lichuan, Wei Li, and Beth Moxley. "AI-Based Classification of Pediatric Breath Sounds: Toward a Tool for Early Respiratory Screening." Applied Sciences 15, no. 13 (2025): 7145. https://doi.org/10.3390/app15137145.

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Context: Respiratory morbidity is a leading cause of children’s consultations with general practitioners. Auscultation, the act of listening to breath sounds, is a crucial diagnostic method for respiratory system diseases. Problem: Parents and caregivers often lack the necessary knowledge and experience to identify subtle differences in children’s breath sounds. Furthermore, obtaining reliable feedback from young children about their physical condition is challenging. Methods: The use of a human–artificial intelligence (AI) tool is an essential component for screening and monitoring young chil

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Ding, Luyu, Yang Lv, Ruixiang Jiang, et al. "Predicting the Feed Intake of Cattle Based on Jaw Movement Using a Triaxial Accelerometer." Agriculture 12, no. 7 (2022): 899. http://dx.doi.org/10.3390/agriculture12070899.

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The use of an accelerometer is considered as a promising method for the automatic measurement of the feeding behavior or feed intake of cattle, with great significance in facilitating daily management. To address further need for commercial use, an efficient classification algorithm at a low sample frequency is needed to reduce the amount of recorded data to increase the battery life of the monitoring device, and a high-precision model needs to be developed to predict feed intake on the basis of feeding behavior. Accelerograms for the jaw movement and feed intake of 13 mid-lactating cows were

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Shapiro, Jason W., and Catherine Putonti. "Rephine.r: a pipeline for correcting gene calls and clusters to improve phage pangenomes and phylogenies." PeerJ 9 (August 6, 2021): e11950. http://dx.doi.org/10.7717/peerj.11950.

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Background A pangenome is the collection of all genes found in a set of related genomes. For microbes, these genomes are often different strains of the same species, and the pangenome offers a means to compare gene content variation with differences in phenotypes, ecology, and phylogenetic relatedness. Though most frequently applied to bacteria, there is growing interest in adapting pangenome analysis to bacteriophages. However, working with phage genomes presents new challenges. First, most phage families are under-sampled, and homologous genes in related viruses can be difficult to identify.

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Milone, D. H., and L. E. Di Persia. "Learning Hidden Markov Models with Hidden Markov Trees as Observation Distributions." INTELIGENCIA ARTIFICIAL 12, no. 37 (2008). http://dx.doi.org/10.4114/ia.v12i37.953.

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Adam, Timo, Marius Ötting, and Rouven Michels. "Markov-switching decision trees." AStA Advances in Statistical Analysis, May 29, 2024. http://dx.doi.org/10.1007/s10182-024-00501-6.

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AbstractDecision trees constitute a simple yet powerful and interpretable machine learning tool. While tree-based methods are designed only for cross-sectional data, we propose an approach that combines decision trees with time series modeling and thereby bridges the gap between machine learning and statistics. In particular, we combine decision trees with hidden Markov models where, for any time point, an underlying (hidden) Markov chain selects the tree that generates the corresponding observation. We propose an estimation approach that is based on the expectation-maximisation algorithm and

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Rautiainen, Heidi, Moudud Alam, Paul G. Blackwell, and Anna Skarin. "Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data." Movement Ecology 10, no. 1 (2022). http://dx.doi.org/10.1186/s40462-022-00339-0.

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AbstractAnimal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms Random forests, Support vector machines, and hidden Markov models to classify reindeer beha

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Abbondandolo, Alberto, Florian Henning, Christof Külske, and Pietro Majer. "Infinite-Volume States with Irreducible Localization Sets for Gradient Models on Trees." Journal of Statistical Physics 191, no. 6 (2024). http://dx.doi.org/10.1007/s10955-024-03278-9.

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AbstractWe consider general classes of gradient models on regular trees with spin values in a countable Abelian group S such as $${\mathbb {Z}}$$ Z or $${\mathbb {Z}}_q$$ Z q . This includes unbounded spin models like the p-SOS model and finite-alphabet clock models. Under a strong coupling (low temperature) condition on the interaction, we prove the existence of families of distinct homogeneous tree-indexed Markov chain Gibbs states $$\mu _A$$ μ A whose single-site marginals concentrate on a given finite subset $$A\subset S$$ A ⊂ S of spin values. The existence of such states is a new and rob

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"Comments on "Fast approximation of Kullback-Leibler distance for dependence trees and hidden Markov models"." IEEE Signal Processing Letters 10, no. 8 (2003): 250. http://dx.doi.org/10.1109/lsp.2003.816070.

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Iloga, Sylvain. "Accurate comparison of tree sets using HMM-based descriptor vectors." Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées Volume 36 - Special issue CRI... (August 23, 2022). http://dx.doi.org/10.46298/arima.9107.

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Trees are among the most studied data structures and several techniques have consequently been developed for comparing two trees belonging to the same category. Until the end of year 2020, there was a serious lack of suitable metrics for comparing two weighted trees or two trees from different categories. The problem of comparing two tree sets was not also specifically addressed. These limitations have been overcome in a paper published in 2021 where a customizable metric based on hidden Markov models has been proposed for comparing two tree sets, each containing a mixture of trees belonging t

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Hsiao, Janet H., Jeehye An, Veronica Kit Sum Hui, Yueyuan Zheng, and Antoni B. Chan. "Understanding the role of eye movement consistency in face recognition and autism through integrating deep neural networks and hidden Markov models." npj Science of Learning 7, no. 1 (2022). http://dx.doi.org/10.1038/s41539-022-00139-6.

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AbstractGreater eyes-focused eye movement pattern during face recognition is associated with better performance in adults but not in children. We test the hypothesis that higher eye movement consistency across trials, instead of a greater eyes-focused pattern, predicts better performance in children since it reflects capacity in developing visual routines. We first simulated visual routine development through combining deep neural network and hidden Markov model that jointly learn perceptual representations and eye movement strategies for face recognition. The model accounted for the advantage

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Bhathena, Aaresh, Salar Fattahi, Andrés Gómez, and Simge Küçükyavuz. "A parametric approach for solving convex quadratic optimization with indicators over trees." Mathematical Programming, May 2, 2025. https://doi.org/10.1007/s10107-025-02222-3.

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Abstract This paper investigates convex quadratic optimization problems involving n indicator variables, each associated with a continuous variable, particularly focusing on scenarios where the matrix Q defining the quadratic term is positive definite and its sparsity pattern corresponds to the adjacency matrix of a tree graph. We introduce a graph-based dynamic programming algorithm that solves this problem in time and memory complexity of $$\mathcal {O}(n^2)$$ O ( n 2 ) . Central to our algorithm is a precise parametric characterization of the cost function across various nodes of the graph

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Runthala, Ashish, K. Sowmya, Shamantha Nasika, et al. "Refined Evolutionary Trees Through an Exceptionally Compatible Alignment-Substitution Model." Journal of Applied Biology & Biotechnology, 2024. http://dx.doi.org/10.7324/jabb.2024.163103.

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A phylogenetic tree commonly represents evolutionary relationships within a set of protein sequences. Various methods and strategies have been used to improve the accuracy of phylogenetic trees, but their capacity to derive a biologically credible relationship appears to be overestimated. Although the quality of the protein sequence alignment and the choice of substitution matrix are preliminary constraints to define the biological accuracy of the overlapped residues, the alignment is not iteratively optimized through the statistical testing of residue-substitution models. The exact alignment

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Zhang, Dao-Feng, Wei He, Zongze Shao, et al. "EasyCGTree: a pipeline for prokaryotic phylogenomic analysis based on core gene sets." BMC Bioinformatics 24, no. 1 (2023). http://dx.doi.org/10.1186/s12859-023-05527-2.

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Abstract Background Genome-scale phylogenetic analysis based on core gene sets is routinely used in microbiological research. However, the techniques are still not approachable for individuals with little bioinformatics experience. Here, we present EasyCGTree, a user-friendly and cross-platform pipeline to reconstruct genome-scale maximum-likehood (ML) phylogenetic tree using supermatrix (SM) and supertree (ST) approaches. Results EasyCGTree was implemented in Perl programming languages and was built using a collection of published reputable programs. All the programs were precompiled as stand

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