„Nothing is missing”. Heteroglozje wideo by Agnieszka Rejniak-Majewska, Tomasz Majewski

“…Cykl zapisów wideo został poświęcony matkom imigrantów z Afryki, Azji i Europy Wschodniej. …”
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Eenergy effiency access strategy:towards hybrid wireless sensor network by Ya-song WANG, Qin-yu ZHANG, Yun-he LI, Jing HAN

“…A dynamically access mechanism of non-real-time sensor nodes with adaptive listening and sleeping,against the background,co-existence of real-time traffic and non-real-time traffic in the networks,was studied.The energy consumption is very slow while the node is in a sleep state; however,the long sleep time may make the network nodes miss transmission opportunity.Thus,according to the usage of the channel,a reasonable set of wireless sensor network nodes sleep time in the network energy consumption and transmission efficiency could be adjusted to maximize the energy transmission efficiency of wireless sensor network.Firstly,the continuous-time Markov modeling the problem was used and analyzed.Then system model based on perturbation analysis theory was proposed to obtain the gradient algorithm for solving the optimal sleep time.Finally,the feasibility of the recommended program is verified by comparing the theoretical results and computer simulation.…”
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Projecting the Spread of COVID-19 for Germany by Jean Roch Donsimoni, René Glawion, Bodo Plachter, Klaus Wälde

“…Their theoretical framework builds on a continuous time Markov chain with four physical states: healthy, sick, recovered or asymptomatic infected, and dead. …”
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Vertical handover policy for cyber-physical systems aided by SAGIN based on deep reinforcement learning by WU Yan, PAN Guangchuan, YAO Mingwu, YANG Qinghai, LEUNG Victor C.M.

“…By jointly taking the system stability, handover cost and network-using cost into account, the vertical handover policy problem was modeled as a constraint Markov decision process (CMDP), and a sufficient condition to ensure the existence of a feasible solution was derived.Furthermore, a constraint-proximal policy optimization (CPPO) algorithm was proposed to solve the CMDP, and also the distributed learning scheme at base station sides was introduced to accelerate the speed of converging. …”
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Online hierarchical reinforcement learning based on interrupting Option by Fei ZHU, Zhi-peng XU, Quan LIU, Yu-chen FU, Hui WANG

“…Aiming at dealing with volume of big data,an on-line updating algorithm,named by Macro-Q with in-place updating (MQIU),which was based on Macro-Q algorithm and takes advantage of in-place updating approach,was proposed.The MQIU algorithm updates both the value function of abstract action and the value function of primitive action,and hence speeds up the convergence rate.By introducing the interruption mechanism,a model-free interrupting Macro-Q Option learning algorithm(IMQ),which was based on hierarchical reinforcement learning,was also introduced to order to handle the variability which was hard to process by the conventional Markov decision process model and abstract action so that IMQ was able to learn and improve control strategies in a dynamic environment.Simulations verify the MQIU algorithm speeds up the convergence rate so that it is able to do with the larger scale of data,and the IMQ algorithm solves the task faster with a stable learning performance.…”
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Joint optimization strategy of age of information and energy consumption for offloading and scheduling in WBAN by ZHANG Zheng, XIE Xin, BAI Tong, LIN Jinzhao, LI Zhangyong

“…To handle the strong coupling between offloading and scheduling decisions, a two-layer Markov decision process (MDP) was used to approximate the optimal solution. …”
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Presence Service in IMS by David Petras, Ivan Baronak, Erik Chromy

“…This is described by a mathematical model using discrete Markov chains.…”
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Novel Strategy to Improve the Performance of Localization in WSN by M. Vasim Babu, A. V. Ramprasad

“…In our model the discrete hidden Markov process plays a major role in analyzing the node location in heterogeneous media. …”
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Asymptotic behavior of a delayed stochastic logistic model with impulsive perturbations by Sanling Yuan, Xuehui Ji, Huaiping Zhu

“…By using the theory of integral Markov semigroups, we further derive sufficient conditions for the existence of the stationary distribution of the system. …”
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Evaluation of the Methods for Response Analysis under Non-Stationary Excitation by R.S. Jangid, T.K. Datta

“…Response of structures to non-stationary ground motion can be obtained either by the evolutionary spectral analysis or by the Markov approach. In certain conditions, a quasi-stationary analysis can also be performed. …”
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Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications by Hanan Haj Ahmad

“…Since Bayes estimators cannot be expressed explicitly, Gibbs and the Markov Chain Monte Carlo techniques are utilized for Bayesian calculation. …”
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Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays by Ling Hou, Dongyan Chen, Chan He

“…This paper considers the stochastic finite-time dissipative (SFTD) control problem based on nonfragile controller for discrete-time neural networks (NNS) with Markovian jumps and mixed delays, in which the mode switching phenomenon, is described as Markov chain, and the mixed delays are composed of discrete time-varying delay and distributed delays. …”
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Nonlinear Fluctuation Behavior of Financial Time Series Model by Statistical Physics System by Wuyang Cheng, Jun Wang

“…Contact process is a continuous time Markov process; one interpretation of this model is as a model for the spread of an infection, where the epidemic spreading mimics the interplay of local infections and recovery of individuals. …”
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Self-corrected coefficient smoothing method based network security situation prediction by Hongyu YANG, Xugao ZHANG

“…In order to solve the problem of insufficient accuracy of current network security situation prediction methods,a new network security situation prediction model was proposed based on self-correcting coefficient smoothing.Firstly,a network security assessment quantification method was designed to transform the alarm information into situation real value time series based on the entropy correlation degree.Then,the adaptive solution of the static smoothing coefficient was calculated and the predicted initial value was obtained by using the variable domain space.Finally,based on the error category,the time-changing weighted Markov chain was built to modify the initial network situation prediction result and the prediction accuracy was further raised.The prediction model was tested with LL_DOS_1.0 dataset and the experimental results show that the proposed model has higher adaptability and prediction accuracy for network situation time series.…”
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Optimal tactics in community pension model for defined benefit pension plans. by Jun Wang, Chunli Cui, Tian Tian

“…Leveraging the Hamilton-Jacobi-Bellman equation, we derive the Markov Perfect Nash Equilibrium solution and optimal portfolio. …”
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A New Bayesian Network-Based Generalized Weighting Scheme for the Amalgamation of Multiple Drought Indices by Muhammad Ahmad Raza, Mohammed M. A. Almazah, Nadhir Al-ansari, Ijaz Hussain, Fuad S. Al-Duais, Mohammed A. Naser

“…These ADPPs are obtained from Bayesian networks (BNs)-based Markov Chain Monte Carlo (MCMC) simulations. Results have shown that the MWADI correlates more with the standardized precipitation index (SPI) and the standardized precipitation temperature index (SPTI). …”
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A Comparative Study of Some Automatic Arabic Text Diacritization Systems by Ali Mijlad, Yacine El Younoussi

“…One uses a variant of the hidden Markov model. The other one is a pipeline, which includes a Long Short-Term Memory deep learning model, a rule-based correction component, and a statistical-based component. …”
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Exponential Stability of Stochastic Delayed Neural Networks with Inverse Hölder Activation Functions and Markovian Jump Parameters by Yingwei Li, Huaiqin Wu

“…The jumping parameters are modeled as a continuous-time finite-state Markov chain. Firstly, based on Brouwer degree properties, the existence and uniqueness of the equilibrium point for SNNs without noise perturbations are proved. …”
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Bayesian Non-Parametric Mixtures of GARCH(1,1) Models by John W. Lau, Ed Cripps

“…Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. …”
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Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition by Ping-Heng Kuo, Pang-An Ting

“…By applying these analytical results, the fluctuations of MIMO-GMD schemes are examined by modeling both link gains and capacities using finite-state Markov chains (FSMCs).…”
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