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Journal articles on the topic 'Semi-random models'

Author: Grafiati

Published: 6 September 2023

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1

Dikta, Gerhard. "Asymptotically efficient estimation under semi-parametric random censorship models." Journal of Multivariate Analysis 124 (February 2014): 10–24. http://dx.doi.org/10.1016/j.jmva.2013.10.002.

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2

Xia, Lirong. "Semi-random Impossibilities of Condorcet Criterion." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 5 (2023): 5867–75. http://dx.doi.org/10.1609/aaai.v37i5.25727.

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The Condorcet criterion (CC) is a classical and well-accepted criterion for voting. Unfortunately, it is incompatible with many other desiderata including participation (PAR), half-way monotonicity (HM), Maskin monotonicity (MM), and strategy-proofness (SP). Such incompatibilities are often known as impossibility theorems, and are proved by worst-case analysis. Previous work has investigated the likelihood for these impossibilities to occur under certain models, which are often criticized of being unrealistic. We strengthen previous work by proving the first set of semi-random impossibilities

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3

Ohlssen, D. I., L. D. Sharples, and D. J. Spiegelhalter. "Flexible random-effects models using Bayesian semi-parametric models: applications to institutional comparisons." Statistics in Medicine 26, no. 9 (2007): 2088–112. http://dx.doi.org/10.1002/sim.2666.

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4

Caraballo, Tomás, Renato Colucci, and Xiaoying Han. "Semi-Kolmogorov models for predation with indirect effects in random environments." Discrete and Continuous Dynamical Systems - Series B 21, no. 7 (2016): 2129–43. http://dx.doi.org/10.3934/dcdsb.2016040.

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5

Abd El-Monsef, Mohamed, Elhoussainy Rady, and Ayat Sobhy. "WEIBULL SEMIPARAMETRIC REGRESSION MODELS UNDER RANDOM CENSORSHIP." JOURNAL OF ADVANCES IN MATHEMATICS 11, no. 8 (2015): 5577–82. http://dx.doi.org/10.24297/jam.v11i8.1209.

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Semiparametric regression is concerned with the flexible combination of non-linear functional relationships in regression analysis. The main advantage of the semiparametric regression models is that any application benefits from regression analysis can also benefit from the semiparametric regression. In this paper, we derived a consistent estimator of parametric portion and nonparametric portion in Weibull semi-parametric regression models under random censorship.

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6

Rushton, Philip A., Farid Taheri, and David C. Stredulinsky. "Fatigue Response and Characterization of 350WT Steel Under Semi-Random Loading." Journal of Pressure Vessel Technology 129, no. 3 (2006): 525–34. http://dx.doi.org/10.1115/1.2748835.

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Novel data obtained through experimental investigation into the fatigue response of 350WT steel, subjected to semi-random loading, comprised of various combinations of intermittent tensile overloads and compressive underloads are presented. An effective model for predicting the fatigue response is also introduced. For that, the capabilities of some of the currently available models are investigated and then an exponential delay model, being capable of accounting for the effects of not only overload ratio, but also stress ratio and overload/underload ratio is introduced. Since most variable amp

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7

Soullard, Yann, Martin Saveski, and Thierry Artières. "Joint semi-supervised learning of Hidden Conditional Random Fields and Hidden Markov Models." Pattern Recognition Letters 37 (February 2014): 161–71. http://dx.doi.org/10.1016/j.patrec.2013.03.028.

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Zhang, Yuanqing, and Dianmei Shen. "Estimation of semi-parametric varying-coefficient spatial panel data models with random-effects." Journal of Statistical Planning and Inference 159 (April 2015): 64–80. http://dx.doi.org/10.1016/j.jspi.2014.11.001.

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9

Loeys, Tom, Catherine Legrand, Antonio Schettino, and Gilles Pourtois. "Semi-parametric proportional hazards models with crossed random effects for psychometric response times." British Journal of Mathematical and Statistical Psychology 67, no. 2 (2013): 304–27. http://dx.doi.org/10.1111/bmsp.12020.

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10

Kazemi, Iraj, and Reyhaneh Rikhtehgaran. "Topics on Dynamic Panel Data Models with Random Effects Using Semi-Parametric Bayesian Approach." Communications in Statistics - Theory and Methods 43, no. 8 (2014): 1630–48. http://dx.doi.org/10.1080/03610926.2012.673672.

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Papageorgiou, Georgios, and John Hinde. "Multivariate generalized linear mixed models with semi-nonparametric and smooth nonparametric random effects densities." Statistics and Computing 22, no. 1 (2010): 79–92. http://dx.doi.org/10.1007/s11222-010-9207-y.

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12

Wisnalmawati, Wisnalmawati, Agus Sasmito Aribowo, and Yunie Herawati. "Semi-supervised Learning Models for Sentiment Analysis on Marketplace Dataset." International Journal of Artificial Intelligence & Robotics (IJAIR) 4, no. 2 (2022): 78–85. http://dx.doi.org/10.25139/ijair.v4i2.5267.

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Sentiment analysis aims to categorize opinions using an annotated corpus to train the model. However, building a high-quality, fully annotated corpus takes a lot of effort, time, and expense. The semi-supervised learning technique efficiently adds training data automatically from unlabeled data. The labeling process, which requires human expertise and requires time, can be helped by an SSL approach. This study aims to develop an SSL-Model for sentiment analysis and to compare the learning capabilities of Naive Bayes (NB) and Random Forest (RF) in the SSL. Our model attempts to annotate opinion

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13

Hsiao, Cheng, Qi Li, Zhongwen Liang, and Wei Xie. "Panel Data Estimation for Correlated Random Coefficients Models." Econometrics 7, no. 1 (2019): 7. http://dx.doi.org/10.3390/econometrics7010007.

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This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly focus on comparing two approaches of estimating unconditional mean of the coefficients for the correlated random coefficients models, the group mean estimator and the generalized least squares estimator. For the group mean estimator, we show that it achieves Chamberlain (1992) semi-parametric efficiency bound asymptotically. For the generalized least squares estimator, we show that when T is large, a generalized least squares estimator that ignores the correlation between the indi

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Millard, Salomon M., and Frans H. J. Kanfer. "Mixtures of Semi-Parametric Generalised Linear Models." Symmetry 14, no. 2 (2022): 409. http://dx.doi.org/10.3390/sym14020409.

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The mixture of generalised linear models (MGLM) requires knowledge about each mixture component’s specific exponential family (EF) distribution. This assumption is relaxed and a mixture of semi-parametric generalised linear models (MSPGLM) approach is proposed, which allows for unknown distributions of the EF for each mixture component while much of the parametric structure of the traditional MGLM is retained. Such an approach inherently allows for both symmetric and non-symmetric component distributions, frequently leading to non-symmetrical response variable distributions. It is assumed that

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15

Kariuki, C. M., E. D. Ilatsia, C. B. Wasike, I. S. Kosgey, and A. K. Kahi. "Genetic evaluation of growth of Dorper sheep in semi-arid Kenya using random regression models." Small Ruminant Research 93, no. 2-3 (2010): 126–34. http://dx.doi.org/10.1016/j.smallrumres.2010.05.011.

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16

Avola, Giovanni, Ezio Riggi, Fabio Gresta, Orazio Sortino, and Andrea Onofri. "Random effects models, BLUPs and redundancy analyses for grain legume crops in semi-arid environments." European Journal of Agronomy 93 (February 2018): 18–26. http://dx.doi.org/10.1016/j.eja.2017.11.004.

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17

Macdonald, A. S. "An Actuarial Survey of Statistical Models for Decrement and Transition Data - I: Multiple State, Poisson and Binomial Models." British Actuarial Journal 2, no. 1 (1996): 129–55. http://dx.doi.org/10.1017/s1357321700003366.

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ABSTRACTThis paper surveys some statistical models of survival data. A basic model of a random lifetime is defined, and censoring is introduced. Methods based on observations of small segments of lifetimes are compared. Markov and semi-Markov (multiple state) models are recommended as well-understood and flexible models well suited to actuarial data. A Poisson model is discussed as an approximation to a two state model, while traditional Binomial-type models are shown to be more restricted and less tractable than multiple state models.

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18

Seigal, Anna, and Guido Montufar. "Mixtures and products in two graphical models." Journal of Algebraic Statistics 9, no. 1 (2018): 1–20. http://dx.doi.org/10.18409/jas.v9i1.90.

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We compare two statistical models of three binary random variables. One is a mixture model and the other is a product of mixtures model called a restricted Boltzmann machine. Although the two models we study look different from their parametrizations, we show that they represent the same set of distributions on the interior of the probability simplex, and are equal up to closure. We give a semi-algebraic description of the model in terms of six binomial inequalities and obtain closed form expressions for the maximum likelihood estimates. We briefly discuss extensions to larger models.

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Han, Dongxiao, Lei Liu, Xiaogang Su, Bankole Johnson, and Liuquan Sun. "Variable selection for random effects two-part models." Statistical Methods in Medical Research 28, no. 9 (2018): 2697–709. http://dx.doi.org/10.1177/0962280218784712.

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Random effects two-part models have been applied to longitudinal studies for zero-inflated (or semi-continuous) data, characterized by a large portion of zero values and continuous non-zero (positive) values. Examples include monthly medical costs, daily alcohol drinks, relative abundance of microbiome, etc. With the advance of information technology for data collection and storage, the number of variables available to researchers can be rather large in such studies. To avoid curse of dimensionality and facilitate decision making, it is critically important to select covariates that are truly

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20

Verros, G., S. Natsiavas, and C. Papadimitriou. "Design Optimization of Quarter-car Models with Passive and Semi-active Suspensions under Random Road Excitation." Journal of Vibration and Control 11, no. 5 (2005): 581–606. http://dx.doi.org/10.1177/1077546305052315.

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A methodology is presented for optimizing the suspension damping and stiffness parameters of nonlinear quarter-car models subjected to random road excitation. The investigation starts with car models involving passive damping with constant or dual-rate characteristics. Then, we also examine car models where the damping coefficient of the suspension is selected so that the resulting system approximates the performance of an active suspension system with sky-hook damping. For the models with semi-active or passive dual-rate dampers, the value of the equivalent suspension damping coefficient is a

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21

Grabski, Franciszek. "The Renewal Process Generated By Return Times of Semi-Markov Process in Reliability Models." Journal of KONBiN 43, no. 1 (2017): 365–80. http://dx.doi.org/10.1515/jok-2017-0056.

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Abstract The renewal process generated by the return times of semi-Markov process to a given state is considered in the paper. The return time to a state j and also a first passage time from a given state i to the state j of semi-Markov process are basic concepts that are used to determine this process. The systems of equations for distributions, expectations and secondond moments of these random variables are presented. Theorem concerning the asymptotic distribution of the considered renewal process is presented in this article. Moreover an illustrative example from the reliability theory is

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22

Yenilmez, İsmail, Ersin Yılmaz, Yeliz Mert Kantar, and Dursun Aydın. "Comparison of parametric and semi-parametric models with randomly right-censored data by weighted estimators: Two applications in colon cancer and hepatocellular carcinoma datasets." Statistical Methods in Medical Research 31, no. 2 (2021): 372–87. http://dx.doi.org/10.1177/09622802211061635.

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In this study, parametric and semi-parametric regression models are examined for random right censorship. The components of the aforementioned regression models are estimated with weights based on Cox and Kaplan–Meier estimates, which are semi-parametric and nonparametric methods used in survival analysis, respectively. The Tobit based on weights obtained from a Cox regression is handled as a parametric model instead of other parametric models requiring distribution assumptions such as exponential, Weibull, and gamma distributions. Also, the semi-parametric smoothing spline and the semi-parame

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23

Boulanger, Patrice, Keith Attenborough, Qin Qin, and Chris M. Linton. "Reflection of sound from random distributions of semi-cylinders on a hard plane: models and data." Journal of Physics D: Applied Physics 38, no. 18 (2005): 3480–90. http://dx.doi.org/10.1088/0022-3727/38/18/024.

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24

Kim, Jiwoong. "Applicability of special quasi-random structure models in thermodynamic calculations using semi-empirical Debye–Grüneisen theory." Journal of Alloys and Compounds 650 (November 2015): 564–71. http://dx.doi.org/10.1016/j.jallcom.2015.08.035.

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25

Zhang, Yizhun, and Qisheng Yan. "Landslide Susceptibility Prediction Based on High-Trust Non-Landslide Point Selection." ISPRS International Journal of Geo-Information 11, no. 7 (2022): 398. http://dx.doi.org/10.3390/ijgi11070398.

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Landslide susceptibility prediction has the disadvantages of being challenging to apply to expanding landslide samples and the low accuracy of a subjective random selection of non-landslide samples. Taking Fu’an City, Fujian Province, as an example, a model based on a semi-supervised framework using particle swarm optimization to optimize extreme learning machines (SS-PSO-ELM) is proposed. Based on the landslide samples, a semi-supervised learning framework is constructed through Density Peak Clustering (DPC), Frequency Ratio (FR), and Random Forest (RF) models to expand and divide the landsli

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26

Witte, M. J., and T. A. Newell. "Transmission of Solar Radiation Through a Random Medium of Water and Glass." Journal of Solar Energy Engineering 108, no. 3 (1986): 199–205. http://dx.doi.org/10.1115/1.3268093.

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Two models are presented for the prediction of solar radiation transmission through a random medium of glass and water. One model is based on two-dimensional radiation exchange through a rectangular lattice of glass and water. This model is also applicable for materials other than glass and water. The other model is a semi-empirical equation which expresses the transmission as an exponential function. Both models predict transmittances within 5–10 percent of experimental data.

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27

Et.al, Md Azman Shahadan. "Bayesian Hierarchical Growth Model for Experimental Data on the Effectiveness of an Incentive-Based Weight Reduction Method." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 1036–47. http://dx.doi.org/10.17762/turcomat.v12i3.840.

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The objective of this current research is to model the experimental data on the effectiveness of an incentive-based weight reduction method by using Bayesian hierarchical growth models. Three Bayesian hierarchical growth models are proposed, namely parametric Bayesian hierarchical growth model with correlated intercept and slope random effects model, parametric Bayesian hierarchical growth model with no correlated intercept and slope random effects model and semi-parametric Bayesian hierarchical growth model with Dirichlet process mixture prior model. The data is obtained from forty eight (48)

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28

Esquível, Manuel L., Nadezhda P. Krasii, and Gracinda R. Guerreiro. "Open Markov Type Population Models: From Discrete to Continuous Time." Mathematics 9, no. 13 (2021): 1496. http://dx.doi.org/10.3390/math9131496.

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We address the problem of finding a natural continuous time Markov type process—in open populations—that best captures the information provided by an open Markov chain in discrete time which is usually the sole possible observation from data. Given the open discrete time Markov chain, we single out two main approaches: In the first one, we consider a calibration procedure of a continuous time Markov process using a transition matrix of a discrete time Markov chain and we show that, when the discrete time transition matrix is embeddable in a continuous time one, the calibration problem has opti

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29

Gu, Anhui, and Yangrong Li. "A Combined Criterion for Existence and Continuity of Random Attractors for Stochastic Lattice Dynamical Systems." International Journal of Bifurcation and Chaos 27, no. 02 (2017): 1750019. http://dx.doi.org/10.1142/s0218127417500195.

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The paper is devoted to establishing a combination of sufficient criterion for the existence and upper semi-continuity of random attractors for stochastic lattice dynamical systems. By relying on a family of random systems itself, we first set up the abstract result when it is convergent, uniformly absorbing and uniformly random when asymptotically null in the phase space. Then we apply the results to the second-order lattice dynamical system driven by multiplicative white noise. It is indicated that the criterion depending on the dynamical system itself seems more applicable than the existing

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30

Dshalalow, Jewgeni H. "On intensities of modulated Cox measures." Journal of Applied Mathematics and Stochastic Analysis 11, no. 3 (1998): 411–23. http://dx.doi.org/10.1155/s1048953398000343.

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In this paper we introduce and study functionals of the intensities of random measures modulated by a stochastic process ξ, which occur in applications to stochastic models and telecommunications. Modulation of a random measure by ξ is specified for marked Cox measures. Particular cases of modulation by ξ as semi-Markov and semiregenerative processes enabled us to obtain explicit formulas for the named intensities. Examples in queueing (systems with state dependent parameters, Little's and Campbell's formulas) demonstrate the use of the results.

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31

Seyhan, Emel, Jonathan P. Stewart, and Robert W. Graves. "Calibration of a Semi-Stochastic Procedure for Simulating High-Frequency Ground Motions." Earthquake Spectra 29, no. 4 (2013): 1495–519. http://dx.doi.org/10.1193/122211eqs312m.

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Broadband ground motion simulation procedures typically utilize physics-based modeling at low frequencies, coupled with semi-stochastic procedures at high frequencies. The high-frequency procedure considered here combines deterministic Fourier amplitude spectra (dependent on source, path, and site models) with random phase. Previous work showed that high-frequency intensity measures from this simulation methodology attenuate faster with distance and have lower intra-event dispersion than in empirical equations. We address these issues by increasing crustal damping (Q) to reduce distance attenu

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32

Nhu, Viet-Ha, Ataollah Shirzadi, Himan Shahabi, et al. "Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran." Forests 11, no. 4 (2020): 421. http://dx.doi.org/10.3390/f11040421.

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We generated high-quality shallow landslide susceptibility maps for Bijar County, Kurdistan Province, Iran, using Random Forest (RAF), an ensemble computational intelligence method and three meta classifiers—Bagging (BA, BA-RAF), Random Subspace (RS, RS-RAF), and Rotation Forest (RF, RF-RAF). Modeling and validation were done on 111 shallow landslide locations using 20 conditioning factors tested by the Information Gain Ratio (IGR) technique. We assessed model performance with statistically based indexes, including sensitivity, specificity, accuracy, kappa, root mean square error (RMSE), and a

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33

Allahbakhshi, Hoda, Lindsey Conrow, Babak Naimi, and Robert Weibel. "Using Accelerometer and GPS Data for Real-Life Physical Activity Type Detection." Sensors 20, no. 3 (2020): 588. http://dx.doi.org/10.3390/s20030588.

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This paper aims to examine the role of global positioning system (GPS) sensor data in real-life physical activity (PA) type detection. Thirty-three young participants wore devices including GPS and accelerometer sensors on five body positions and performed daily PAs in two protocols, namely semi-structured and real-life. One general random forest (RF) model integrating data from all sensors and five individual RF models using data from each sensor position were trained using semi-structured (Scenario 1) and combined (semi-structured + real-life) data (Scenario 2). The results showed that in ge

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34

SEOANE, NICOLAS. "MODELLING FREE-RANGE CATTLE MOVEMENTS IN FORESTS USING MULTISTATE RANDOM WALKS." Journal of Biological Systems 23, supp01 (2015): S43—S54. http://dx.doi.org/10.1142/s0218339015400045.

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In this study multi-state random walk models were tested as general approach to analyse movement states in animal relocation data. For this purpose, GPS collars were fit to free-range cattle inhabiting Andean forests in Patagonia, Argentina. The results indicate that animal trajectories have re-visitation patterns in restricted areas of few kilometres and that a large part of behaviors occur at a time scale lower than six hours. Simple multi-state random walk models proved to be practical in modelling characteristics such as step and turning angles distribution in addition to emergent properti

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35

Stefanov, Valeri T. "On some waiting time problems." Journal of Applied Probability 37, no. 3 (2000): 756–64. http://dx.doi.org/10.1239/jap/1014842834.

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A unifying technology is introduced for finding explicit closed form expressions for joint moment generating functions of various random quantities associated with some waiting time problems. Sooner and later waiting times are covered for general discrete- and continuous-time models. The models are either Markov chains or semi-Markov processes with a finite number of states. Waiting times associated with generalized phase-type distributions, that are of interest in survival analysis and other areas, are also covered.

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Stefanov, Valeri T. "On some waiting time problems." Journal of Applied Probability 37, no. 03 (2000): 756–64. http://dx.doi.org/10.1017/s0021900200015977.

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A unifying technology is introduced for finding explicit closed form expressions for joint moment generating functions of various random quantities associated with some waiting time problems. Sooner and later waiting times are covered for general discrete- and continuous-time models. The models are either Markov chains or semi-Markov processes with a finite number of states. Waiting times associated with generalized phase-type distributions, that are of interest in survival analysis and other areas, are also covered.

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37

Bogomolny, Eugene. "Barrier billiard and random matrices." Journal of Physics A: Mathematical and Theoretical 55, no. 2 (2021): 024001. http://dx.doi.org/10.1088/1751-8121/ac3da6.

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Abstract The barrier billiard is the simplest example of pseudo-integrable models with interesting and intricate classical and quantum properties. Using the Wiener–Hopf method it is demonstrated that quantum mechanics of a rectangular billiard with a barrier in the centre can be reduced to the investigation of a certain unitary matrix. Under heuristic assumptions this matrix is substituted by a special low-complexity random unitary matrix of independent interest. The main results of the paper are (i) spectral statistics of such billiards is insensitive to the barrier height and (ii) it is well

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38

Ruiz-Aĺvarez, Marcos, Francisco Gomariz-Castillo, and Francisco Alonso-Sarría. "Evapotranspiration Response to Climate Change in Semi-Arid Areas: Using Random Forest as Multi-Model Ensemble Method." Water 13, no. 2 (2021): 222. http://dx.doi.org/10.3390/w13020222.

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Large ensembles of climate models are increasingly available either as ensembles of opportunity or perturbed physics ensembles, providing a wealth of additional data that is potentially useful for improving adaptation strategies to climate change. In this work, we propose a framework to evaluate the predictive capacity of 11 multi-model ensemble methods (MMEs), including random forest (RF), to estimate reference evapotranspiration (ET0) using 10 AR5 models for the scenarios RCP4.5 and RCP8.5. The study was carried out in the Segura Hydrographic Demarcation (SE of Spain), a typical Mediterranea

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Nsenge Mpia, Héritier, Moïse Katembo Kasolen, Vingi Mutegheki Baraka, and Nephtali Inipaivudu Baelani. "Stacking Regression-Based Model for Predicting Patient's Length of Stay in a Semi Urban Hospital." International Journal of Research Publication and Reviews 04, no. 02 (2023): 273–85. http://dx.doi.org/10.55248/gengpi.2023.4212.

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In this research, the authors found that statistical analysis is very important preliminary phase in Machine Learning, especially for regression problems. Indeed, when the authors developed the first single models using the same algorithms and the same dataset, they obtained poor performances. After verifying the assumptions of the multiple linear regression, they adjusted the used data and produced efficient models. Moreover, as the objective was to apply the stacking model to predict Patient's Length of Stay in a semi urban hospital, the results showed that the stacking regressor performed b

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40

Shankara Krishna, A., Vishwanath Mane, Subba Rao, and Manu. "Effect of data normalisation in estimating wave overtopping discharge parameter of semicircular breakwater using ANN and Random Forest." IOP Conference Series: Earth and Environmental Science 1149, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1755-1315/1149/1/012001.

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Abstract Breakwaters are the structures constructed in the coastal areas to maintain calm inside the port or prevent beach erosion. Semi-circular Breakwater (SCB) is an innovative type of Breakwater made of hollow caisson on a base slab with or without perforations. In this study, the wave overtopping discharge parameter of an SCB is estimated using Artificial Neural Network and Random Forest. The data is collected and used in the current research from an experimental investigation conducted in the Wave Mechanics Laboratory of the Department of Water Resources and Ocean Engineering (WROE), NIT

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De Abreu, Jadson Coelho, Carlos Pedro Boechat Soares, and Helio Garcia Leite. "ASSESSING ALTERNATIVES TO ESTIMATE THE STEM VOLUME OF A SEASONAL SEMI-DECIDUOUS FOREST." FLORESTA 47, no. 4 (2017): 375. http://dx.doi.org/10.5380/rf.v47i4.54259.

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AbstractThe objective of this study was to evaluate the use of linear and hybrid linear models, artificial neural networks (ANN) and support vector machine (SVM) in the estimation of the stem volume in a Seasonal Semi-deciduous Forest. Cubing data of 99 sample-trees of 15 species were used for this purpose. After analysis, we verified that the inclusion of the species as random effect did not contribute to increase the accuracy of the estimates in the structure of a hybrid model. Artificial neural networks and support vector machines, including species as input categorical variables, were the

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42

Sánchez-Vidal, Francisco Javier. "A Cautionary Note on the Use of Accounting Semi-Identity-Based Models †." Journal of Risk and Financial Management 16, no. 9 (2023): 389. http://dx.doi.org/10.3390/jrfm16090389.

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This study employs a Monte Carlo simulation to see whether accounting identity problems are present in the Fazzari, Hubbard, and Petersen model (1988). The Monte Carlo simulation generates 50,000 random cash flows, Tobin’s Q, and error term variables, which shape an investment variable that is dependent on them. Cash flows and investments are linked by a partial accounting identity, also known as an accounting semi-identity (ASI). An accounting identity is, for example, an equality between the left and right sides of a balance sheet. An ASI is not a complete one since one or more components of

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43

Bohlouli, M., H. Mohammadi, and S. Alijani. "Genetic evaluation and genetic trend of growth traits of Zandi sheep in semi-arid Iran using random regression models." Small Ruminant Research 114, no. 2-3 (2013): 195–201. http://dx.doi.org/10.1016/j.smallrumres.2013.07.005.

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Cheng, Wen, Gurdiljot Singh Gill, Tom Vo, Jiao Zhou, and Taha Sakrani. "Use of Bivariate Dirichlet Process Mixture Spatial Model to Estimate Active Transportation-Related Crash Counts." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 38 (2018): 105–15. http://dx.doi.org/10.1177/0361198118782797.

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The current paper presents the comprehensive analysis of a bivariate Dirichlet process mixture spatial model for estimation of pedestrian and bicycle crash counts. This study focuses on active transportation at traffic analysis zone (TAZ) level by developing a semi-parametric model that accounts for the unobserved heterogeneity by combining the strengths of bivariate specification for correlation among crash modes; spatial random effects for the impact of neighboring TAZs; and Dirichlet process mixture for random intercept. Three alternate models, one Dirichlet and two parametric, are also dev

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Nakhost, Hootan, and Martin Mueller. "A Theoretical Framework for Studying Random Walk Planning." Proceedings of the International Symposium on Combinatorial Search 3, no. 1 (2021): 57–64. http://dx.doi.org/10.1609/socs.v3i1.18247.

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Random walks are a relatively new component used in several state of the art satisficing planners. Empirical results have been mixed: while the approach clearly outperforms more systematic search methods such as weighted A* on many planning domains, it fails in many others. So far, the explanations for these empirical results have been somewhat ad hoc. This paper proposes a formal framework for comparing the performance of random walk and systematic search methods. Fair homogenous graphs are proposed as a graph class that represents characteristics of the state space of prototypical planning d

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Zhou, Chenyan, Yahong Zhang, Ling Chen, and Zhongxin Wu. "Fatigue strength analysis of semi-submersible platforms based on wide-band stress." Journal of Physics: Conference Series 2553, no. 1 (2023): 012005. http://dx.doi.org/10.1088/1742-6596/2553/1/012005.

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Abstract As the focus of ocean resource exploitation shifts from shallow sea to ultra-deep sea, semi-submersible platforms are far away from the coastline for a long time. The semi-submersible platform structure is more prone to fatigue damage under complex sea conditions. The stress range and peaks are considered in the conventional frequency domain spectral method to obey the narrow-band distribution, which makes the results of fatigue assessment tend to be conservative. To solve the problems above, a wide-band fatigue assessment method based on Rice distribution is proposed from the perspec

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Gupta, Ashish, Nilanjan Bharadwaj, and Vikas Rastogi. "Computational Framework of Various Semi-Active Control Strategies for Road Vehicles Thorough Bondgraphs." International Journal of System Dynamics Applications 10, no. 4 (2021): 1–29. http://dx.doi.org/10.4018/ijsda.20211001.oa9.

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Vehicle suspension system plays a vital role in diminishing the vibration caused by the road roughness and prevent it from transmitting to the driver and the passenger. The semi-active suspensions contain spring and damping elements with variable properties, which can be changed by an external control. The work presented here is concerned with semi-active damper control for vibration isolation of base disturbances. Numerous control algorithms for semi active system had been suggested in the past, performed experimentally and validated with various computational models.In this work, the 2-DOF q

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Zhang, Min, Guohua Geng, and Jing Chen. "Semi-Supervised Bidirectional Long Short-Term Memory and Conditional Random Fields Model for Named-Entity Recognition Using Embeddings from Language Models Representations." Entropy 22, no. 2 (2020): 252. http://dx.doi.org/10.3390/e22020252.

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Increasingly, popular online museums have significantly changed the way people acquire cultural knowledge. These online museums have been generating abundant amounts of cultural relics data. In recent years, researchers have used deep learning models that can automatically extract complex features and have rich representation capabilities to implement named-entity recognition (NER). However, the lack of labeled data in the field of cultural relics makes it difficult for deep learning models that rely on labeled data to achieve excellent performance. To address this problem, this paper proposes

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Oh, Seungmin, Akm Ashiquzzaman, Dongsu Lee, Yeonggwang Kim, and Jinsul Kim. "Study on Human Activity Recognition Using Semi-Supervised Active Transfer Learning." Sensors 21, no. 8 (2021): 2760. http://dx.doi.org/10.3390/s21082760.

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In recent years, various studies have begun to use deep learning models to conduct research in the field of human activity recognition (HAR). However, there has been a severe lag in the absolute development of such models since training deep learning models require a lot of labeled data. In fields such as HAR, it is difficult to collect data and there are high costs and efforts involved in manual labeling. The existing methods rely heavily on manual data collection and proper labeling of the data, which is done by human administrators. This often results in the data gathering process often bei

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Goydaragh, Maryam Ghebleh, Ali Asghar Jafarzadeh, Farzin Shahbazi, Shahin Oustan, Ruhollah Taghizadeh-Mehrjardi, and Marcos Lado. "Estimation of elemental composition of agricultural soils from West Azerbaijan, Iran, using mid-infrared spectral models." Revista Brasileira de Engenharia Agrícola e Ambiental 23, no. 6 (2019): 460–66. http://dx.doi.org/10.1590/1807-1929/agriambi.v23n6p460-466.

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ABSTRACT Characterizing the elemental composition provides useful information about the weathering degree of soils. In Miandoab County, Northern Iran, this characterization was missing, and thus the objectives of this work were to evaluate the weathering degrees for the most typical soils in the area from their elemental compositions, and to estimate this elemental composition using Fourier transform infrared spectroscopy and Random Forest models. Five soil profiles, including Aridisols and Inceptisols, were selected as the most representative of the area. Major elemental oxides were determine

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