Bearing Remaining Useful Life Prediction Based on a Scaled Health Indicator and a LSTM Model with Attention Mechanism by Songhao Gao, Xin Xiong, Yanfei Zhou, Jiashuo Zhang

“…In this study, a scale-normalized bearing health indicator based on the improved phase space warping (PSW) and hidden Markov model regression was established. This indicator was then used as the input for the encoder–decoder LSTM neural network with an attention mechanism to predict the rolling bearing RUL. …”
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DIPS-Plus: The enhanced database of interacting protein structures for interface prediction by Alex Morehead, Chen Chen, Ada Sedova, Jianlin Cheng

“…While the original DIPS dataset contains only the Cartesian coordinates for atoms contained in the protein complex along with their types, DIPS-Plus contains multiple residue-level features including surface proximities, half-sphere amino acid compositions, and new profile hidden Markov model (HMM)-based sequence features for each amino acid, providing researchers a curated feature bank for training protein interface prediction methods. …”
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Nonintrusive Load Monitoring Using Recurrent Neural Networks with Occupants Location Information in Residential Buildings by Myeung-Hun Lee, Hyeun-Jun Moon

“…The performance of the suggested models was evaluated with a conventional method that uses the factorial hidden Markov model. As a result, when developing the GRU disaggregation model based on an RNN, the energy disaggregation performance improved in accuracy, F1-score, mean absolute error (MAE), and root mean square error (RMSE). …”
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Device-to-Device Communications in Cloud, MANET and Internet of Things Integrated Architecture by Tanweer Alam

“…Methods: The methods are applied to discover the smart devices using probability-based model, hidden Markov model and gradient-based model. Results: A cloud-MANET architecture of the smart device is constructed with cloud and MANET computation. …”
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A Location Prediction Algorithm with Daily Routines in Location-Based Participatory Sensing Systems by Ruiyun Yu, Xingyou Xia, Shiyang Liao, Xingwei Wang

“…After considering the dynamism of users' behavior resulting from their daily routines, the SMLPR algorithm preliminarily predicts node's mobility based on the hidden Markov model in different daily periods of time and then amends the prediction results using location information of other nodes which have strong relationship with the node. …”
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Estimating Forest Fire Losses Using Stochastic Approach: Case Study of the Kroumiria Mountains (Northwestern Tunisia) by Ahmed Toujani, Hammadi Achour, Sami Faïz

“…Subsequently, the SOM clusters were incorporated into a Hidden Markov Model (HMM) framework to model their corresponding burned areas. …”
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Using natural head movements to continually calibrate EOG signals by Jason Nezvadovitz, Hrishikesh Rao

“…The fusion is executed as recursive inference on a hidden Markov model that accounts for all rotational degrees-of-freedom and uncertainties simultaneously. …”
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Detection and Prevention WEB-Service for Fraudulent E-Transaction using APRIORI and SVM by Shatha Jassim Muhamed

“…We observed that the accuracy of fraud transaction detection is higher in the proposed algorithm more than 94.56, and the false fraud transaction detection is less than the fraud detection based on the Hidden Markov Model. …”
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Vision based robot navigation by Roth, Daniel R. (Daniel Risner), 1979-

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Predictive modelling of quantum stochastic processes by Huang, Ruocheng

“…In this paper, predictive modelling involving non-orthogonal emissions upon state transitions of Hidden Markov Model is studied. Mixed-State Presentation (MSP) is used to unifilarise the process in order to keep track of the state of knowledge over underlying machine states after each measurement. …”
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STATINA – multi-channel acoustic room impulse response for speech processing by Krisnadi Wicaksono.

“…With the integrated speech recognizer, different applications or tasks can be invoked using voice commands. An HMM (Hidden Markov Model)-based ASR is being developed. A set of commands has been defined for STATINA with the flexibility to increase the size of the command set at any point of time. …”
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PENGGUNAAN PENGENALAN SUARASEBAGAI PERINTAH SUARA DARI PASIEN KE ROBOT PARAMEDIS by , DIPTA SATWIKO, , Nazrul Effendy, ST., M.Eng., Ph.D.

“…In this research, we used hidden markov model. There are two main steps for making a speech recognition system: training and recognition. …”

Fast MCMC sampling for Markov jump processes and extensions by Rao, V, Teh, Y

“…The first step involves simulating a piecewise-constant inhomogeneous Poisson process, while for the second, we use a standard hidden Markov model forward filtering-backward sampling algorithm. …”

Positional entropy during pigeon homing I: application of Bayesian latent state modelling. by Roberts, S, Guilford, T, Rezek, I, Biro, D

“…We analyse a fundamental measure of bird flight track complexity, spatio-temporal entropy, and explore its state-like structure using a probabilistic hidden Markov model. The emergence of a robust three-state structure proves that the technique has analytical power, since this structure was not obvious in the tracks alone. …”

Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep by Stevner, A, Vidaurre, D, Cabral, J, Rapuano, K, Nielsen, S, Tagliazucchi, E, Laufs, H, Vuust, P, Deco, G, Woolrich, M, Van Someren, E, Kringelbach, M

“…In order to obtain the most unbiased estimate of how whole-brain network states evolve through the human sleep cycle, we used a Markovian data-driven analysis of continuous neuroimaging data from 57 healthy participants falling asleep during simultaneous functional magnetic resonance imaging (fMRI) and EEG. This Hidden Markov Model (HMM) facilitated discovery of the dynamic choreography between different whole-brain networks across the wake-non-REM sleep cycle. …”

Combining statistical alignment and phylogenetic footprinting to detect regulatory elements. by Satija, R, Pachter, L, Hein, J

“…SAPF simultaneously performs both alignment and annotation by combining phylogenetic footprinting techniques with an hidden Markov model (HMM) transducer-based multiple alignment model, and can analyze sequence data from multiple sequences. …”

Stem cell differentiation as a non-Markov stochastic process by Stumpf, P, Smith, R, Lenz, M, Schuppert, A, Mueller, F, Babtie, A, Chan, T, Stumpf, M, Please, C, Howison, S, Arai, F, MacArthur, B

“…However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence. …”

Fuzzy qualitative human motion analysis by Chan, C.S., Liu, H.H.

“…An empirical comparison with conventional hidden Markov model (HMM) and fuzzy HMM (FHMM) shows that the proposed approach consistently outperforms both HMMs in human motion recognition.…”

Impact of acoustical voice activity detection on spontaneous filled pause classification by Hamzah, Raseeda, Jamil, Nursuriati, Seman, Noraini, Ardi, Norizah, C. Doraisamy, Shyamala

“…Few attempts of classifying filled pause and elongation employed Hidden Markov model. Our proposed method of utilizing Neural Network as a classifier achieved 96% precision rate. …”
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Malay continuous speech recognition using fast HMM match algorithm by Ting, Chee-Ming, Salleh, Sh-Hussain, Ariff, A. K.

“…This paper describes the implementation of fast hidden Markov model (HMM) match algorithm in a phoneme-based Malay continuous speech recognition system. …”