Gotowe bibliografie tematyczne / Multiple mean estimation

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Gotowa bibliografia na temat „Multiple mean estimation”

Autor: Grafiati

Data publikacji: 26 października 2024

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Multiple mean estimation"

Green, Edwin J., William E. Strawderman, Ralph L. Amateis, and Gregory A. Reams. "Improved Estimation for Multiple Means with Heterogeneous Variances." Forest Science 51, no. 1 (2005): 1–6. http://dx.doi.org/10.1093/forestscience/51.1.1.

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Abstract Two new estimators are presented for use in situations where simultaneous estimation of more than two sample means is required and alternative, possibly biased information is available. The new estimators are modifications to an older estimator by Green and Strawderman. The latter estimator assumed homogeneous variances, whereas the new ones are designed for the more usual case of heterogeneous variances among the sample means. In simulation experiments, the new estimators yielded superior performance to that of the ordinary sample mean vector (X). Surprisingly, the estimator designed

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Liu, Huan Bin. "Additive-Accelerated Mean Regression Model for Multiple Type Recurrent Events." Advanced Engineering Forum 6-7 (September 2012): 93–96. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.93.

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Recurrent events data is often observed in applied research fields like biostatistics, clinical experiment, and so on. In this paper, an additive-accelerated mean regression model is established for multiple type recurrent events data, and the estimation methods of unknown parameter and non-parameter function based on the idea of estimating equation are given.

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Sedeeq, Bekhal Samad, Hogr Mohammed Qader, Azhy Akram Aziz, and Dlshad Mahmood Saleh. "Implementing a New Scale Technique in the M-Estimation Method to Estimate Parameters of Multiple Linear Regression: Simulation Study." Tikrit Journal of Administrative and Economic Sciences 19, no. 64, 1 (2023): 712–25. http://dx.doi.org/10.25130/tjaes.19.64.1.38.

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The goal of this study is to develop a new technique for estimating the parameters of a multiple linear regression by using M-estimation based on scale estimator to handle the influence of outlier values. In order to get new estimators, the root mean square error (RMSE) criterion is used to check the efficiency between the new technique and the classical method. The research showed that the new technique (M-estimation based on scale estimator) yields more accurate parameter estimates than the traditional approach (OLS) in all simulated cases.

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Rao, Zhushi, Qinzhong Shi, and Ichiro Hagiwara. "Optimal Estimation of Dynamic Loads for Multiple-Input System." Journal of Vibration and Acoustics 121, no. 3 (1999): 397–401. http://dx.doi.org/10.1115/1.2893993.

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An optimal method is developed to estimate the dynamic loads for systems subjected to multiple inputs. The method focuses on minimizing the ensemble mean square error of the estimation. First, the inverse system analysis technique is employed to establish the error estimation equation. Then, by applying the noncausal Wiener filtering theory, the optimal estimator of dynamic loads is derived out. Numerical simulation work demonstrates that the method is of a good ability in suppressing the influence of measurement noises on estimation accuracy. Meanwhile, the simulating calculation of load esti

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Pinette, M. G., Y. Pan, S. G. Pinette, J. Blackstone, J. Garrett, and A. Cartin. "Estimation of fetal weight: mean value from multiple formulas." Journal of Ultrasound in Medicine 18, no. 12 (1999): 813–17. http://dx.doi.org/10.7863/jum.1999.18.12.813.

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Kim, Jae-Hee, and Sooy-Oung Cheon. "Multiple Change-Point Estimation of Air Pollution Mean Vectors." Korean Journal of Applied Statistics 22, no. 4 (2009): 687–95. http://dx.doi.org/10.5351/kjas.2009.22.4.687.

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Lee, Andrew Sanghyun, Yuandi Wu, Stephen Andrew Gadsden, and Mohammad AlShabi. "Interacting Multiple Model Estimators for Fault Detection in a Magnetorheological Damper." Sensors 24, no. 1 (2023): 251. http://dx.doi.org/10.3390/s24010251.

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This paper proposes a novel estimator for the purpose of fault detection and diagnosis. The interacting multiple model (IMM) strategy is effective for estimating the behaviour of systems with multiple operating modes. Each mode corresponds to a distinct mathematical model and is subject to a filtering process. This paper applies various model-based filters in combination with the IMM strategy. One such estimator employs the recently introduced extended sliding innovation filter (ESIF) known as the IMM-ESIF. The ESIF is an extension of the sliding innovation filter for nonlinear systems based o

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Omar Gan, Sarimah, and Sabri Ahmad. "ESTIMATION OF TRADE BALANCE USING MULTIPLE LINEAR REGRESSION MODEL." Labuan Bulletin of International Business and Finance (LBIBF) 16 (November 30, 2018): 44–52. http://dx.doi.org/10.51200/lbibf.v16i.1642.

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This study aims to evaluate the performance of multiple linear regression in estimating trade balance, so that a regression model for estimating the trade balance can be developed based on the important variables that have been identified. The performance of four regression methods including enter, stepwise regression, backward deletion, and forward selection is measured by mean absolute error, standard deviation, and Pearson correlation at the validation stage. The study concludes that multiple linear regression model developed by stepwise method is the best model for the trade balance estima

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Najlaa Ali Dhumad and Abbas Lafta Kneehr. "Comparison Of Some Estimation Methods For The Estimators Of Marshall Olkin Distribution With Simulation." Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa 2, no. 4 (2024): 234–47. http://dx.doi.org/10.62383/bilangan.v2i4.204.

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The research comprised multiple simulated tests to determine the relationship between (sample size, distribution parameter value, estimation method, and pollution indivuduales). The experimental findings indicate that the estimator is influenced by sample size, the value of distribution parameter, estimation method, and pollution indivuduales. The results of the mean square error analysis indicate that (robust estimation method) produces the best results with the lowest mean square error, and the best estimation method was (191) of (243) simulation experiments. Additional statistical distribut

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Neubauer, Jirí, and Vítezslav Veselý. "Detection of multiple changes in mean by sparse parameter estimation." Nonlinear Analysis: Modelling and Control 18, no. 2 (2013): 177–90. http://dx.doi.org/10.15388/na.18.2.14021.

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The contribution is focused on detection of multiple changes in the mean in a onedimensional stochastic process by sparse parameter estimation from an overparametrized model. The authors’ approach to change point detection differs entirely from standard statistical techniques. A stochastic process residing in a bounded interval with changes in the mean is estimated using dictionary (a family of functions, the so-called atoms, which are overcomplete in the sense of being nearly linearly dependent) and consisting of Heaviside functions. Among all possible representations of the process we want t

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Rozprawy doktorskie na temat "Multiple mean estimation"

Potter, Chris. "Modeling Channel Estimation Error in Continuously Varying MIMO Channels." International Foundation for Telemetering, 2007. http://hdl.handle.net/10150/604490.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada<br>The accuracy of channel estimation plays a crucial role in the demodulation of data symbols sent across an unknown wireless medium. In this work a new analytical expression for the channel estimation error of a multiple input multiple output (MIMO) system is obtained when the wireless medium is continuously changing in the temporal domain. Numerical examples are provided to illustrate our find

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Feng, Limin. "JAMES-STEIN TYPE COMPOUND ESTIMATION OF MULTIPLE MEAN RESPONSE FUNCTIONS AND THEIR DERIVATIVES." UKnowledge, 2013. http://uknowledge.uky.edu/statistics_etds/6.

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Charnigo and Srinivasan originally developed compound estimators to nonparametrically estimate mean response functions and their derivatives simultaneously when there is one response variable and one covariate. The compound estimator maintains self consistency and almost optimal convergence rate. This dissertation studies, in part, compound estimation with multiple responses and/or covariates. An empirical comparison of compound estimation, local regression and spline smoothing is included, and near optimal convergence rates are established in the presence of multiple covariates. James and Ste

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Fermanian, Jean-Baptiste. "High dimensional multiple means estimation and testing with applications to machine learning." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASM035.

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Nous étudions dans cette thèse l'influence de la grande dimension dans des problèmes de test et d'estimation. Notre analyse porte sur la dépendance en la dimension de la vitesse de séparation d'un test de proximité et du risque quadratique de l'estimation multiples de vecteurs. Nous complétons les résultats existants en étudiant ces dépendances dans le cas de distributions non isotropes. Pour de telles distributions, le rôle de la dimension est alors joué par des notions de dimension effective définies à partir de la covariance des distributions. Ce cadre permet d'englober des données de dimen

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Tran, Nguyen Duy. "Performance bounds in terms of estimation and resolution and applications in array processing." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2012. http://tel.archives-ouvertes.fr/tel-00777503.

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This manuscript concerns the performance analysis in signal processing and consists into two parts : First, we study the lower bounds in characterizing and predicting the estimation performance in terms of mean square error (MSE). The lower bounds on the MSE give the minimum variance that an estimator can expect to achieve and it can be divided into two categories depending on the parameter assumption: the so-called deterministic bounds dealing with the deterministic unknown parameters, and the so-called Bayesian bounds dealing with the random unknown parameter. Particularly, we derive the clo

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Thomas, Robin Rajan. "Optimisation of adaptive localisation techniques for cognitive radio." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/27076.

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Spectrum, environment and location awareness are key characteristics of cognitive radio (CR). Knowledge of a user’s location as well as the surrounding environment type may enhance various CR tasks, such as spectrum sensing, dynamic channel allocation and interference management. This dissertation deals with the optimisation of adaptive localisation techniques for CR. The first part entails the development and evaluation of an efficient bandwidth determination (BD) model, which is a key component of the cognitive positioning system. This bandwidth efficiency is achieved using the Cramer-Rao lo

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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, i

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Hunter, Brandon. "Channel Probing for an Indoor Wireless Communications Channel." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/64.

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The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of th

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"Distributed estimation in wireless sensor networks under a semi-orthogonal multiple access technique." Thesis, 2014. http://hdl.handle.net/10388/ETD-2014-09-1753.

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This thesis is concerned with distributed estimation in a wireless sensor network (WSN) with analog transmission. For a scenario in which a large number of sensors are deployed under a limited bandwidth constraint, a semi-orthogonal multiple-access channelization (MAC) approach is proposed to provide transmission of observations from K sensors to a fusion center (FC) via N orthogonal channels, where K≥N. The proposed semi-orthogonal MAC can be implemented with either fixed sensor grouping or adaptive sensor grouping. The mean squared error (MSE) is adopted as the performance criterion and it i

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Tenenbaum, Adam. "MSE-based Linear Transceiver Designs for Multiuser MIMO Wireless Communications." Thesis, 2011. http://hdl.handle.net/1807/31954.

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This dissertation designs linear transceivers for the multiuser downlink in multiple-input multiple-output (MIMO) systems. The designs rely on an uplink/downlink duality for the mean squared error (MSE) of each individual data stream. We first consider the design of transceivers assuming channel state information (CSI) at the transmitter. We consider minimization of the sum-MSE over all users subject to a sum power constraint on each transmission. Using MSE duality, we solve a computationally simpler convex problem in a virtual uplink. The transformation back to the downlink is simplifi

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Dutta, Amit Kumar. "Transceiver Design Based on the Minimum-Error-Probability Framework for Wireless Communication Systems." Thesis, 2015. http://etd.iisc.ac.in/handle/2005/3732.

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Parameter estimation and signal detection are the two key components of a wireless communication system. They directly impact the bit-error-ratio (BER) performance of the system. Several criteria have been successfully applied for parameter estimation and signal detection. They include maximum likelihood (ML), maximum a-posteriori probability (MAP), least square (LS) and minimum mean square error (MMSE) etc. In the linear detection framework, linear MMSE (LMMSE) and LS are the most popular ones. Nevertheless, these criteria do not necessarily minimize the BER, which is one of the key aspect of

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Książki na temat "Multiple mean estimation"

Yang, Ming-Chung. Estimation of multiple poisson means under entropy loss. 1986.

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Butz, Martin V., and Esther F. Kutter. Top-Down Predictions Determine Perceptions. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0009.

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While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key t

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Części książek na temat "Multiple mean estimation"

Cetintav, Bekir, Gozde Ulutagay, Selma Gurler, and Neslihan Demirel. "Mean Estimation Based on FWA Using Ranked Set Sampling with Single and Multiple Rankers." In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40581-0_64.

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Abdelhady, Aya Salama, Aboul Ella Hassanien, Yasser Mahmoud Awad, Moataz El-Gayar, and Aly Fahmy. "Automatic Sheep Weight Estimation Based on K-Means Clustering and Multiple Linear Regression." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99010-1_50.

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Carraro, Marco, Matteo Munaro, Alina Roitberg, and Emanuele Menegatti. "Improved Skeleton Estimation by Means of Depth Data Fusion from Multiple Depth Cameras." In Intelligent Autonomous Systems 14. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48036-7_85.

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Brüningk, Sarah C., and Gibin G. Powathil. "Modelling Direct and Indirect Effects of Radiation: Experimental, Clinical and Environmental Implications." In NATO Science for Peace and Security Series A: Chemistry and Biology. Springer Netherlands, 2022. http://dx.doi.org/10.1007/978-94-024-2101-9_5.

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AbstractRadiotherapy is a commonly used treatment for cancer and is usually given in varying doses. Mathematical modelling of radiation effects traditionally means the modelling or estimation of cell-kill due to its direct exposure to irradiation and sometimes ignoring other multiple direct/indirect effects. However, advances in molecular biology have expanded this classical view and it is now realized that in addition to cell-death, signals produced by irradiated cells can further influence the behavior of non-irradiated cells or organisms in several ways. Consequently, it has now wider impli

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Legaz-Aparicio, Álvar-Ginés, Rafael Verdú-Monedero, Juan Morales-Sánchez, Jorge Larrey-Ruiz, and Jesús Angulo. "Detection of Retinal Vessel Bifurcations by Means of Multiple Orientation Estimation Based on Regularized Morphological Openings." In IFMBE Proceedings. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00846-2_79.

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Rastogi, Krati, and Divya Lohani. "Edge Computing-Based Internet of Things Framework for Indoor Occupancy Estimation." In Research Anthology on Edge Computing Protocols, Applications, and Integration. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5700-9.ch031.

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Indoor occupancy estimation has become an important area of research in the recent past. Information about the number of people entering or leaving a building is useful in estimation of hourly sales, dynamic seat allocation, building climate control, etc. This work proposes a decentralized edge computing-based IoT framework in which the majority of the data analytics is performed on the edge, thus saving a lot of time and network bandwidth. For occupancy estimation, relative humidity and carbon dioxide concentration are used as inputs, and estimation models are developed using multiple linear

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Brown, Philip J. "Regularized multiple regression." In Measurement, Regression, and Calibration. Oxford University PressOxford, 1994. http://dx.doi.org/10.1093/oso/9780198522454.003.0004.

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Abstract The Gauss-Markov theorem lends considerable weight to the use of least-squares as a method of fitting a linear parametric model. It provides ‘best’ estimators. It does, however, have a very restricted notion of what is best. Firstly it confines attention to estimators linear in the response Y. Secondly it looks only at unbiased estimators. Thirdly it minimizes mean-squared error, that is, it is concerned with expected squared error or quadratic loss: in the scalar case it uses is as an estimator of θ. Even retaining quadratic loss, there may be estimators which are either biased or no

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Kovačević, Branko, Zoran Banjac, and Tomislav Unkašević. "Perspective Chapter: Approximate Kalman Filter Using M-Robust Estimate Dynamic Stochastic Approximation with Parallel Adaptation of Unknown Noise Statistics by Huber’s M-Robust Parameter Estimator." In Kalman Filters -Theory, Applications, and Optimization [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1004294.

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The problem of designing a feasible adaptive M-robustified Kalman filter in a case of a thick-tailed Gaussian environment, characterized by impulsive noise-inducing observation and innovation outliers, and/or errors in mathematical model-inducing structural outliers, has been considered. Firstly, the time-varying criterion is used to generate a family of dynamic stochastic approximation algorithms. The M-robust estimate stochastic approximation is derived by minimizing the minimum variance criterion, the estimates of the latter being combined with the one-step minimum mean square error predict

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Eid, Abdulrahman M., Ali Bou Nassif, Chaouki Ghenai, Heba Y. Youssef, Latifa A. Alkhaja, and Hajar H. Almazrouei. "Machine Learning-Based SOC Prediction for Lithium-ion Batteries in Electric Vehicles." In Chronicle of Computing. Oklahoma International Publishing, 2024. http://dx.doi.org/10.55432/978-1-6692-0007-9_12.

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Developing an effective and accurate battery management system that can predict the state of charge of electric vehicles is essential to enhance the safety and efficiency of electric vehicles. The assessment of the state of charge of the battery is important not only for determining the amount of energy that is available from the battery but also for determining how long the battery will last. This paper provides a brief understanding of how the state of charge estimation was predicted before and after the era of Machine Learning (ML). In addition, it proposes an accurate and fast state of cha

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Khani, Salar, and Neda Khademi Shiraz. "Electrical Conductivity Estimation in the Medina River, Texas, USA: An Integrated Approach Using Wavelet Analysis and Machine Learning Techniques." In River Basin Management - Challenges and Coping Strategies [Working Title]. IntechOpen, 2024. https://doi.org/10.5772/intechopen.1008267.

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Electrical conductivity (EC) is an important indicator for monitoring water quality in riverine systems. EC is inherently associated with the concentration of dissolved ionic compounds present in aqueous environments, including various salts and minerals. EC estimations are crucial for environmental monitoring and the overall health assessment of aquatic ecosystems. The present study investigated the application of discrete wavelet transform (DWT) in conjunction with artificial neural networks (ANNs) and multiple linear regression (MLR) models to predict daily river water EC. For this purpose,

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Streszczenia konferencji na temat "Multiple mean estimation"

Guibert, Alexandre, Álvaro Díaz-Flores, Anirban Chaudhuri, and H. Alicia Kim. "Multifidelity Uncertainty Quantification in Battery Performance for eVTOL Flights Under Material and Loading Uncertainties." In Vertical Flight Society 80th Annual Forum & Technology Display. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0080-2024-1167.

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This study addresses safety concerns within the rapidly evolving Electric Vertical Takeoff and Landing (eVTOL) aircraft domain, focusing on efficient tools to quantify uncertainties in lithium-ion battery behavior - a critical aspect of eVTOL. One major issue with quantifying uncertainty is the prohibitive computational cost associated with many queries of an expensive-to-evaluate computational model. This work employs three physics-based battery models models of varying fidelity and cost to estimate the mean and the variance of the selected quantities of interest through a multifidelity metho

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Bregonzio, Valerio, and Fabrizio Martini. "Digital Monitoring System of Saipem Pipelay Vessels Productivity Parameters." In MPWT 2019. NACE International, 2019. https://doi.org/10.5006/mpwt19-15321.

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Abstract Saipem recently took a more integrated approach at production data collection and elaboration recently launched an advanced pilot project: the deployment of a vast data collection and analysis system in the production lines of its Flagship CastorONE. Data is collected from multiple sources by means of communication infrastructures and articulated network systems that allow to connect to different machines and equipment. The most meaningful data are identified and pre-filtered. The data are then processed, aggregated and subject to advanced analytics in order to extract useful informat

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Sekokotoana, Lehlohonolo Edwin, Fambirai Takawira, and Olutayo Oyeyemi Oyerinde. "Least Mean Squares Channel Estimation for Downlink Non-Orthogonal Multiple Access." In 2019 IEEE AFRICON. IEEE, 2019. http://dx.doi.org/10.1109/africon46755.2019.9133868.

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Wilson, D. Keith, Chris L. Pettit, and Vladimir Ostashev. "Bayesian estimation of mean transmission loss along multiple paths with randomly scattered signals." In 176th Meeting of Acoustical Society of America 2018 Acoustics Week in Canada. Acoustical Society of America, 2018. http://dx.doi.org/10.1121/2.0000968.

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Ben Hassen, Sonia, Faouzi Bellili, Abdelaziz Samet, and Sofiene Affes. "Estimation of Angular Spreads and Mean Angles of Arrival for Multiple Incoherently-Distributed Noncircular Sources." In 2015 IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB). IEEE, 2015. http://dx.doi.org/10.1109/icuwb.2015.7324449.

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Alecsa, Cristian Daniel. "G-KMM: A Flexible Kernel Mean Matching Optimization Method for Density Ratio Estimation Involving Multiple Train & Test Datasets." In 12th International Conference on Soft Computing, Artificial Intelligence and Applications. Academy & Industry Research Collaboration Center, 2023. http://dx.doi.org/10.5121/csit.2023.132422.

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In the present paper we introduce new optimization algorithms for the task of density ratio estimation. More precisely, we consider extending the well-known KMM (kernel mean matching) method using the construction of a suitable loss function, in order to encompass more general situations involving the estimation of density ratio with respect to subsets of the training data and test data, respectively. The codes associated to our Python implementation can be found at https://github.com/CDAlecsa/ Generalized-KMM.

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Young, Monica J., Mark N. Glauser, Hiroshi Higuchi, and Jeffrey Taylor. "Towards Sensing and Control of Separation in Subsonic Flows." In ASME/JSME 2003 4th Joint Fluids Summer Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/fedsm2003-45586.

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The purpose of this study is to validate the use of Proper Orthogonal Decomposition POD and Modified Linear Stochastic Estimation mLSE based low-dimensional methods to model an external flow over a NACA 4412 airfoil. By using a combination of Particle Image Velocimetry PIV and multiple airfoil surface pressure measurements, the full velocity field (mean plus fluctuating) is estimated through implementation of a modified complementary technique. We will identify a low-dimensional mean flow just from the wall pressure, specifically observing when the profiles are at the incipient condition. This

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Hamadate, Naoya, Keiichi Watanuki, and Kazunori Kaede. "Confidence Estimation in Multiple Choice Questions Using Eye Movements." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001801.

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In recent years, with the spread of electronic devices, e-learning has become a common form of learning, especially among students and other young people. One of the most common forms of e-learning is multiple-choice questions. While multiple-choice questions allow the learner to grasp the answer instantaneously and reliably, they also allow the learner to answer correctly by guesswork or chance, which may cause the learner to ignore content that should be reviewed. Therefore, it is important to estimate the confidence level from the learner's mental information. Eye movements are often used a

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Hardesty, R. M., and Barry J. Rye. "Simulations of discrete spectral peak estimators for single and multiple lidar pulse returns." In Coherent Laser Radar. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/clr.1991.tha2.

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Given an estimate of the spectrum of a time series sample drawn from a single pulse lidar return, there are several ways in which the signal frequency can be estimated. Texts on weather radar stress use of the first moment expression for estimation of the mean Doppler frequency shift, with or without threshold techniques to remove contributions from the spectrum of the noise.1,2 For lidar, there is increasing interest in discrete spectral peak estimation (DSPE) techniques,3 where the frequency at which the spectral maximum occurs is accepted as the estimate. Indeed, the weighting algorithm pro

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Oba, Ryoya, Keiichi Watanuki, Kazunori Kaede, and Yusuke Osawa. "Feature Selection for Machine Learning-Based Core Body Temperature Estimation Using Hand-Measurable Biological Information." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004362.

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Core body temperature (CBT) is an important health indicator that denotes the temperature of the body core, and maintains brain and organ function. Invasive methods of CBT measurement pose challenges in assessing and monitoring human health. To address this, estimation of tympanic membrane temperature using multiple biological parameters often referenced for CBT has been attempted in previous studies. Our research focused on machine learning-based CBT estimation using hand-measurable biological data. Furthermore, while various studies have investigated machine learning models and the impact of

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Raporty organizacyjne na temat "Multiple mean estimation"

DiGrande, Laura, Sue Pedrazzani, Elizabeth Kinyara, et al. Field Interviewer– Administered Dietary Recalls in Participants’ Homes: A Feasibility Study Using the US Department of Agriculture’s Automated Multiple-Pass Method. RTI Press, 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0045.2105.

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Objective: The purpose of this study was to assess the feasibility of administering the Automated Multiple-Pass Method (AMPM), a widely used tool for collecting 24-hour dietary recalls, in participants’ homes by field interviewers. Design: The design included computer-assisted personal interviews led by either a nutritionist (standard) or field interviewer. Portion estimators tested were a set of three-dimensional food models (standard), a two-dimensional food model booklet, or a tablet with digital images rendered via augmented reality. Setting: Residences in central North Carolina. Participa

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Tarko, Andrew P., Mario Romero, Cristhian Lizarazo, and Paul Pineda. Statistical Analysis of Safety Improvements and Integration into Project Design Process. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317121.

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RoadHAT is a tool developed by the Center for Road Safety and implemented for the INDOT safety management practice to help identify both safety needs and relevant road improvements. This study has modified the tool to facilitate a quick and convenient comparison of various design alternatives in the preliminary design stage for scoping small and medium safety-improvement projects. The modified RoadHAT 4D incorporates a statistical estimation of the Crash Reduction Factors based on a before-and-after analysis of multiple treated and control sites with EB correction for the regression-to-mean ef

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Clarke, Paul S., Tom M. Palmer, and Frank Windmeijer. Estimating structural mean models with multiple instrumental variables using the generalised method of moments. Institute for Fiscal Studies, 2011. http://dx.doi.org/10.1920/wp.cem.2011.2811.

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Powers, Claire, Erin Borgman, Daniel Doak, Erin Borgman, Daniel Doak, and Claire Powers. Climate and species traits shape responses of alpine flora in the US Rocky Mountains to a changing world: Analysis of five GLORIA sites across the southern Rockies. National Park Service, 2024. https://doi.org/10.36967/2306920.

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The Global Observation Research Initiative in Alpine Environments (GLORIA) is a world-wide network of sites dedicated to monitoring changes in alpine flora near mountain tops. In this project we analyzed data collected at 5 sets of GLORIA monitoring sites in the Rocky Mountains of the western USA. Each site was visited between 2 and 4 times in the years spanning 2003 to 2021. These sites include four National Parks (Great Sand Dunes National Park and Preserve, Rocky Mountain National Park, Yellowstone National Park, and Glacier National Park) and one wilderness area in the Pecos Wilderness wit

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Hibbert, Angela, and Begona Pérez Gómez. Operational monitoring systems available at the three sites. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d5.9.

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Tide gauges can capture sea level variability on multiple timescales, from high frequency events like waves, tides and tsunamis, to seasonal and interannual changes and the longer-term trends associated with Climate Change. However, financial constraints dictate that they are often maintained to lower standards than the stringent accuracy requirements demanded by the IOC-UNESCO’s Global Sea Level Observing System (GLOSS) for monitoring sea level rise. In addition, a sparsity of Global Navigation Satellite System (GNSS) receivers at the coast means that there are large uncertainties in rates of

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Mizrach, Amos, Michal Mazor, Amots Hetzroni, et al. Male Song as a Tool for Trapping Female Medflies. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7586535.bard.

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This interdisciplinaray work combines expertise in engineering and entomology in Israel and the US, to develop an acoustic trap for mate-seeking female medflies. Medflies are among the world's most economically harmful pests, and monitoring and control efforts cost about $800 million each year in Israel and the US. Efficient traps are vitally important tools for medfly quarantine and pest management activities; they are needed for early detection, for predicting dispersal patterns and for estimating medfly abundance within infested regions. Early detection facilitates rapid response to invasio

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Grundy, Helen H., Lucy C. Brown, Mark Sykes, M. Rosario Romero, and Dominic Anderson. Review of allergen analytical testing methodologies. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.noe660.

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The Food Information Regulation (FIR) states that accurate and understandable allergen information needs to be supplied to consumers for the 14 priority allergens. Food allergies affects between 1-2% of the UK population, with some allergens responsible for hospital admissions with anaphylaxis. Food businesses have a legal responsibility to provide food that is safe, which means declaring allergens present as ingredients and warning consumers about their potential unintended presence due to cross-contact. A system needs to be implemented for testing allergens in foods, responding to incidents,

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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water

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