Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…The integration of intelligent monitoring systems and self-learning algorithms is reshaping machining processes, enabling higher efficiency, precision, and sustainability. …”
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Representation of the stochastic matrix sets with given properties based on autonomous automatic models by V.M. Zakharov, S.V. Shalagin, B.F. Eminov

“…This paper considers the methods of construction (presentation) of the sets of ergodic stochastic matrices using automaton models and determination of the power estimates of the generated sets. The research aimed at developing algorithms for constructing the sets of ergodic stochastic matrices with rational elements with given structures and limit vector based on the automaton probabilistic and deterministic models represented by autonomous automata, as well as at estimating the power of the obtained sets of stochastic matrices depending on the dimensions of the given automaton models. …”
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Joint modeling of multistate survival processes with informative examination scheme: application to progressions in diabetes by Yuxi Zhu, Joshua J. Joseph, Neena Thomas, Lang Li, Guy Brock

“…Parameters of the joint model are estimated under the framework of likelihood function by the expectation–maximization (EM) algorithm. …”
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Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance by Min Cheng, Jiawei Yu, Mingkang Wu, Yayao Zhang, Yihua Zhu, Yuanfu Zhu

“…As the global energy structure transitions towards cleaner sources, large-scale integration of wind power has become a trend for modern power systems. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…We used the multivariate imputation via chained equations algorithm with 100 imputations. We carried out three sensitivity analyses for the primary outcome to investigate the impact of the changes on our findings: (1) estimating causal effect of ECHOMANTRA receipt rather than of offer, (2) excluding three patients who did not meet eligibility criteria of BMI < 18.5, (3) excluding patients recruited after pandemic start (after 11 March 2020). …”
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An Innovative Differentiated Creative Search Based on Collaborative Development and Population Evaluation by Xinyu Cai, Chaoyong Zhang

“…First, this paper proposes a collaborative development mechanism that organically integrates the estimation distribution algorithm and DCS to compensate for the shortcomings of the DCS algorithm’s insufficient exploration ability and its tendency to fall into local optimums through the guiding effect of dominant populations, and to improve the quality of the DCS algorithm’s search efficiency and solution at the same time. …”
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Markov Observation Models and Deepfakes by Michael A. Kouritzin

“…An expectation-maximization (EM) analog to the Baum–Welch algorithm is developed to estimate the transition probabilities as well as the initial hidden-state-observation joint distribution for all the models considered. …”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The GVSAO algorithm is a sophisticated optimization technique that fine-tunes the hyperparameters of CNNs. …”
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Accurate depth of anesthesia monitoring based on EEG signal complexity and frequency features by Tianning Li, Yi Huang, Peng Wen, Yan Li

“…A random forest regression model was employed to estimate anesthetic states, and an unsupervised learning method using the Hurst exponent algorithm and hierarchical clustering was introduced to detect transitions between anesthesia states. …”
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OPTIMIZATION OF THE PROBLEM SOLVING WITH LIMITED RESOURCE by S. V. Chebakov, L. V. Serebryanaya

“…The complexity estimation of proposed algorithms is realized and the general approach to the knapsack problem solving is presented.…”
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Quantum resonant dimensionality reduction by Fan Yang, Furong Wang, Xusheng Xu, Pan Gao, Tao Xin, ShiJie Wei, Guilu Long

“…Here, we propose a quantum resonant dimensionality reduction (QRDR) algorithm based on the quantum resonant transition to reduce the dimension of input data and accelerate the quantum machine learning algorithms. …”
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Indoor Mobile Localization in Mixed Environment with RSS Measurements by Zhengguo Cai, Lin Shang, Dan Gao, Kang Zhao, Yingguan Wang

“…Third, for the Markov transition between LOS and NLOS conditions, an effective unscented Kalman filter (UKF) based interactive multiple model (IMM) is proposed to estimate not only the posterior model probabilities but also a weighted-sum position estimation with the aid of likelihood function. …”
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Classical Simulability of Quantum Circuits with Shallow Magic Depth by Yifan Zhang, Yuxuan Zhang

“…Surprisingly, with the addition of just one T-gate layer or merely replacing all T gates with T^{1/2}, the Pauli evaluation task reveals a sharp complexity transition from being in P to being GapP-complete. Nevertheless, when the precision requirement is relaxed to 1/poly(n) additive error, we are able to give a polynomial-time classical algorithm to compute amplitudes, Pauli observables, and sampling from log⁡(n)-sized marginal distributions for any magic-depth-1 circuit that is decomposable into a product of diagonal gates. …”
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Deep Learning-Based Multi-Floor Indoor Localization Using Smartphone IMU Sensors With 3D Location Initialization by Jin-Woo Kim, Yoan Shin

“…In this paper, we explain conventional IMU sensor-based PDR methods and describe the problems of PDR as well as the limitations of barometer-based floor transition detection techniques. The proposed initial 3D position estimation method detects the initial floor using a deep learning model trained on magnetic field sequences from the user&#x2019;s first 10 steps, and estimates the 2D position by comparing the current magnetometer data with a pre-built magnetic field map using the k-nearest neighbors algorithm. …”
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Lightweight opportunistic routing forwarding strategy based on Markov chain by Feng LI, Ya-li SI, Zhen CHEN, Li-min SHEN

“…A lightweight opportunistic routing forwarding strategy (MOR) was proposed based on Markov chain.In the scheme,the execute process of network was divided into a plurality of equal time period,and the random encounter state of node in each time period was represented by activity degree.The state sequence of a plurality of continuous time period constitutes a discrete Markov chain.The activity degree of encounter node was estimated by Markov model to predict its state of future time period,which can enhance the accuracy of activity degree estimation.Then,the method of comprehensive evaluating forwarding utility was designed based on the activity degree of node and the average encounter interval.MOR used the utility of node for making a routing forwarding decision.Each node only maintained a state of last time period and a state transition probability matrix,and a vector recording the average encounter interval of nodes.So,the routing forwarding decision algorithm was simple and efficient,low time and space complexity.Furthermore,the method was proposed to set optimal number of the message copy based on multiple factors,which can effectively balance the utilization of network resources.Results show that compared with existing algorithms,MOR algorithm can effectively increase the delivery ratio and reduce the delivery delay,and lower routing overhead ratio.…”
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Unscented Auxiliary Particle Filter Implementation of the Cardinalized Probability Hypothesis Density Filters by M. R. Danaee, F. Behnia

“…While there are a few new approaches to enhance the Sequential Monte Carlo (SMC) implementation of the PHD filter, current SMC implementation for the CPHD filter is limited to choose only state transition density as a proposal distribution. In this paper, we propose an auxiliary particle implementation of the CPHD filter by estimating the linear functionals in the elementary symmetric functions based on the unscented transform (UT). …”
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Lightweight opportunistic routing forwarding strategy based on Markov chain by Feng LI, Ya-li SI, Zhen CHEN, Li-min SHEN

“…A lightweight opportunistic routing forwarding strategy (MOR) was proposed based on Markov chain.In the scheme,the execute process of network was divided into a plurality of equal time period,and the random encounter state of node in each time period was represented by activity degree.The state sequence of a plurality of continuous time period constitutes a discrete Markov chain.The activity degree of encounter node was estimated by Markov model to predict its state of future time period,which can enhance the accuracy of activity degree estimation.Then,the method of comprehensive evaluating forwarding utility was designed based on the activity degree of node and the average encounter interval.MOR used the utility of node for making a routing forwarding decision.Each node only maintained a state of last time period and a state transition probability matrix,and a vector recording the average encounter interval of nodes.So,the routing forwarding decision algorithm was simple and efficient,low time and space complexity.Furthermore,the method was proposed to set optimal number of the message copy based on multiple factors,which can effectively balance the utilization of network resources.Results show that compared with existing algorithms,MOR algorithm can effectively increase the delivery ratio and reduce the delivery delay,and lower routing overhead ratio.…”
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Evaluating the Outcomes of Students’ Training in the Context of Information Technology Model of Education by B. Y. Staritchenko

“…The paper deals with the urgent problem of estimating the students training quality in higher educational institutions; the authors emphasize the need for transition to the European Credit Transfer System (ECTS) corresponding with the Bologna Declaration in order to provide both academic and labor mobility of students and university graduates. …”
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A novel method for assessing cycling movement status: an exploratory study integrating deep learning and signal processing technologies by Yingchun He, Yi-haw Jan, Fan Yang, Yunru Ma, Chun Pei

“…Spearman’s rank correlation analysis, intraclass correlation coefficient (ICC), error analysis, and t-test were conducted to compare the consistency of data obtained from the two movement capture systems, including the peak frequency of acceleration, transition time point between movement statuses, and the complexity index average (CIA) of the movement status based on multiscale entropy analysis.The KR algorithm showed excellent consistency (ICC1,3=0.988) between the two methods when estimating the peak acceleration frequency. …”
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A Novel Mobile Localization Method for Distributed Sensor Network with Non-Line-of-Sight Error Mitigation by Nan Hu, Hao Wu, Chengdong Wu, Yuan Gao

“…The interacting multiple model frame is employed to estimate the position of unknown node. The probability data association algorithm is used to filter the estimated location. …”
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