Identifying pesticide mixtures at country-wide scale by Cairo, Milena, Monnet, Anne-Christine, Robin, Stéphane, Porcher, Emmanuelle, Fontaine, Colin

Subjects: “…Active substances, Cluster, mixture model, expectation-maximization algorithm, risk assessment…”
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Joint symbol detection and channel estimation for MIMO-OFDM systems via the variational Bayes EM algorithm by ZHANG Xiao-ying, WEI Ji-bo, WANG De-gang, XIONG Chun-lin

Subjects: “…variational Bayes expectation maximization algorithm…”
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Bounded multivariate contaminated normal mixture model with applications to skin cancer detection by Abbas Mahdavi

“…A feasible expectation-maximization algorithm is developed to compute the maximum likelihood estimates of the model parameters using a selection mechanism. …”
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Joint user activity and signal detection for massive multiple-input multiple-output by Xiaoqun SONG, Ming JIN, Zhongjie JIA

“…In uplink grant-free massive multiple-input multiple-output (mMIMO) systems, the performance of available methods for joint user activity and signal detection deteriorates when the correlation of receiving antennas or the number of active devices increases.Moreover, the available methods require the knowledge of noise power, which is often practically unknown.To address the above issues, combining approximate message passing with unitary transformation and expectation maximization algorithm to jointly implement user activity and signal detection was proposed.Different from the conventional approximate message passing algorithm, the proposed one assumes that the noise power was unknown.Firstly, by exploiting the approximate message passing algorithm with unitary transform, the distribution of transmitted symbols together with the distribution of noise power was obtained.Secondly, expectation maximization algorithm was applied to estimate the user activity.Finally, the signal detection was implemented by deriving the posterior distribution of the decoupled signal belongs.Simulation results show that the proposed method is better than the traditional method in joint user activity and signal detection.…”
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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data. by Lulu Pan, Qian Gao, Kecheng Wei, Yongfu Yu, Guoyou Qin, Tong Wang

“…Data integration, Variable selection, T distribution, Expectation maximization algorithm, Genotype-Tissue Expression, Cross validation.…”
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A prediction algorithm of telecom customer churn based on Bayesian network parameters learning under incomplete data by Yuxiang ZHAO, Guangyue LU, Hanglong WANG, Siwei LI

“…Aiming at prediction of telecom customer churn,a novel method was proposed to increase the prediction accuracy with the missing data based on the Bayesian network.This method used k-nearest neighbor algorithm to fill the missing data and adds two types of monotonic influence constraints into the process of learning Bayesian network parameter.Simulations and actual data analysis demonstrate that the proposed algorithm obtains higher prediction accuracy of churn customers with the loss of less cost prediction accuracy of loyal customers,outperforms the classic expectation maximization algorithm.…”
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A distributed expectation maximization-principal component analysis monitoring scheme for the large-scale industrial process with incomplete information by Xuanyue Wang, Xu Yang, Jian Huang, Xianzhong Chen

“…Then, the missing information of variables is estimated by expectation maximization algorithm in the principal component analysis framework, then the expectation maximization-principal component analysis method is applied for fault detection to each sub-block. …”
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PEM-PCA: A Parallel Expectation-Maximization PCA Face Recognition Architecture by Kanokmon Rujirakul, Chakchai So-In, Banchar Arnonkijpanich

“…Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages’ complexity. …”
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A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica by Xin Zou, Wen Long Yue

“…By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts’ knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. …”
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An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand by Bin Wang, Shaoquan Ni, Fucai Jin, Zixu Huang

“…First, for the “censored data” problem in the railway passenger demand forecast, we constructed an unconstrained model of railway passenger demand and solved the unconstrained demand through an expectation-maximization algorithm. Then, on this basis, we use gray neural networks (GNNs) to predict the passenger demand of different origins and destinations (ODs), and according to the prediction results, we propose two ticket allocation methods based on operation and capacity control: accurate predivided model and fuzzy predivided model. …”
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First in Vivo SPECT Imaging of Mouse Femorotibial Cartilage Using Tc-NTP 15-5 by Elisabeth Miot-Noirault, Aurélien Vidal, Philippe Auzeloux, Jean-Claude Madelmont, Jean Maublant, Nicole Moins

“…Tomographic reconstruction of SPECT data was performed with a three-dimensional ordered subset expectation maximization algorithm, and slices were reconstructed in three axes. 99m Tc-NTP 15-5 rapidly accumulated in the joint, with a peak of radioactivity being reached from 5 minutes postinjection and maintained for at least 90 minutes. …”
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An Extendable Gaussian Mixture Model for Lane-Based Queue Length Estimation Based on License Plate Recognition Data by Chaofeng Tan, Hao Wu, Keshuang Tang, Chaopeng Tan

“…Then, the two-dimensional Gaussian distributions of queued vehicles and nonqueued vehicles were fitted, and the expectation-maximization algorithm was adopted to solve the distribution parameters. …”
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Effective Lock Detectors Based on Costas Loop Output for SBPSK Mobile Communications by D. Ferramola, T. Casilli, S. Pradella, G. Giunta, D. Orlando

“…Such estimates are obtained through an iterative strategy relying on the Expectation Maximization algorithm. Moreover, when possible, we provide exact statistical characterizations of the considered decision schemes (including the competitors) or, in the other case, suitable approximations that allow for a straightforward performance evaluation. …”
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Semisupervised Association Learning Based on Partial Differential Equations for Sparse Representation of Image Class Attributes by Wei Song, Guang Hu, Liuqing OuYang, Zhenjie Zhu

“…Using the variational expectation-maximization algorithm, the whole generative process model can be inferred. …”
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Modeling and simulation for toxicity assessment by Cristina Anton, Jian Deng, Yau Shu Wong, Yile Zhang, Weiping Zhang, Stephan Gabos, Dorothy Yu Huang, Can Jin

“…To efficiently estimate the model's parameters, we design an Expectation Maximization algorithm. The model is validated by showing that it accurately represents the information provided by the TCRCs recorded after the experiments. …”
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Effects of Regional Trade Agreement to Local and Global Trade Purity Relationships by Siyu Huang, Wensha Gou, Hongbo Cai, Xiaomeng Li, Qinghua Chen

“…Here, we separate the influence of geographical distance, economic volume, and overall increase in transportation and labor costs and use the expectation maximization algorithm to optimize the parameters and quantify the trade purity indicator, which describes the true global trade environment and relationships among countries. …”
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Influence of MHC on genetic diversity and testicular expression of linked olfactory receptor genes by Mingue Kang, Byeongyong Ahn, Jae Yeol Shin, Hye-Sun Cho, Jongan Lee, Chankyu Park

“…We observed significantly higher allelic diversity (P < 0.01) in ORs with strong linkage disequilibrium (LD) to SLA compared to those with weak or no LD, and we identified 48 SLA class I-OR haplotypes using the expectation-maximization algorithm. The genetic diversity of SLA-linked ORs was positively correlated with their expression levels in the testis. …”
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