Distribution and prediction of catalytic domains in 2-oxoglutarate dependent dioxygenases by Kundu Siddhartha

Subjects: “…Hidden Markov Model…”
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A Profile Hidden Markov Model to investigate the distribution and frequency of LanB-encoding lantibiotic modification genes in the human oral and gut microbiome by Calum J. Walsh, Caitriona M. Guinane, Paul W. O’ Toole, Paul D. Cotter

Subjects: “…Hidden Markov Model…”
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Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding by Ming-Chyuan Lu, Shean-Juinn Chiou, Bo-Si Kuo, Ming-Zong Chen

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Applying hybrid hidden Markov model / artificial neural network (HMM/ANN) for speaker independent continuous malay language speech recognition / by Ong, Huey Fang, Abdul Manan Ahmad, Fakulti Sains Komputer dan Sistem Maklumat

Performance of speech recognition system using dynamic time warping based on Itakura and Diamond global constrain - comparison with hidden markov models / by 296421 Khairul Anuar Ishak

Taxonomic distribution of opsin families inferred from UniProt Reference Proteomes and a suite of opsin-specific hidden Markov models by Neil D. Clarke, John S. Taylor

“…Numerous subfamilies have been defined based on sequence similarity, cell-type localization, signal transduction mechanism, or biological function, but there is no consensus classification system.MethodsWe used multiple hidden Markov models (HMMs) to identify opsins in the UniProt Reference Proteomes database. …”
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Effects of stance control via hidden Markov model-based gait phase detection on healthy users of an active hip-knee exoskeleton by Miguel Sánchez-Manchola, Luis Arciniegas-Mayag, Marcela Múnera, Marcela Múnera, Maxime Bourgain, Maxime Bourgain, Thomas Provot, Thomas Provot, Carlos A. Cifuentes, Carlos A. Cifuentes

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A map matching algorithm based on modified hidden Markov model considering time series dependency over larger time span by Ha Yoon Song, Jae Ho Lee

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A Hidden Markov Model Based Detecting Solution for Detecting the Situation of Balance During Unsupported Standing Using the Electromyography of Ankle Muscles by Rashin Abdolhossein Harisi, Hamid Reza Kobravi

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Research on aging-related degradation of control rod drive system based on dynamic object-oriented Bayesian network and hidden Markov model by Kang Zhu, Xinwen Zhao, Liming Zhang, Hang Yu

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Noise reduction of electron holography observations for a thin-foiled Nd-Fe-B specimen using the wavelet hidden Markov model by Sujin Lee, Yoshihiro Midoh, Yuto Tomita, Takehiro Tamaoka, Mitsunari Auchi, Taisuke Sasaki, Yasukazu Murakami

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Estimating divergence time and ancestral effective population size of Bornean and Sumatran orangutan subspecies using a coalescent hidden Markov model. by Mailund, T, Dutheil, J, Hobolth, A, Lunter, G, Schierup, M

“…Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. …”

QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data by Colella, S, Yau, C, Taylor, J, Mirza, G, Butler, H, Clouston, P, Bassett, A, Seller, A, Holmes, C, Ragoussis, J

“…We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray™ SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. …”

QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data. by Colella, S, Yau, C, Taylor, J, Mirza, G, Butler, H, Clouston, P, Bassett, A, Seller, A, Holmes, C, Ragoussis, J

“…We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. …”

Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting by Isah, Nuhu

“…The findings showed that Hybrid Hidden Markov Model was found to provide more accurate crude oil price forecast than the other three models in which. …”
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Comparing maximum likelihood and Bayesian methods for fitting hidden Markov models to multi-state capture-recapture data of invasive carp in the Illinois River by Charles J. Labuzzetta, Alison A. Coulter, Richard A. Erickson

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Development of hidden Markov modeling method for molecular orientations and structure estimation from high-speed atomic force microscopy time-series images. by Tomonori Ogane, Daisuke Noshiro, Toshio Ando, Atsuko Yamashita, Yuji Sugita, Yasuhiro Matsunaga

“…In the method, we treat HS-AFM data as time-series data, and they are analyzed with the hidden Markov modeling. Using simulated HS-AFM images of the taste receptor type 1 as a test case, the proposed method shows a more robust estimation of molecular orientations than the frame-by-frame analysis. …”
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Fall Detection System Based on Simple Threshold Method and Long Short-Term Memory: Comparison with Hidden Markov Model and Extraction of Optimal Parameters by Seung Su Jeong, Nam Ho Kim, Yun Seop Yu

“…In terms of training data accuracy, the proposed STM-LSTM-based fall detection system is compared with the previously reported STM-hidden Markov model (HMM)-based fall detection system. The training accuracy of the STM-LSTM fall detection system is 100%, while the highest training accuracy by the STM-HMM-based one is 99.5%, which is 0.5% less than the best of the STM-LSTM-based system. …”
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Author Correction: Understanding the role of eye movement consistency in face recognition and autism through integrating deep neural networks and hidden Markov models by Janet H. Hsiao, Jeehye An, Veronica Kit Sum Hui, Yueyuan Zheng, Antoni B. Chan

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Isolated Areas Consumption Short-Term Forecasting Method by Guillaume Guerard, Hugo Pousseur, Ihab Taleb

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