Nouvelle méthodologie d’analyse bayésienne du report des voix et de l’abstention lors du deuxième tour des élections by Girondot, Marc

“…The information from the counts of the first and second rounds is used to model voter behavior as an inverse problem solved using a Bayesian approach. It is then possible to estimate the flow of votes between the first and the second round with very good precision and to provide the objective bases which will serve for an objective political or sociological analysis.…”
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Drug-induced autoimmune-like hepatitis: A disproportionality analysis based on the FAERS database. by Wangyu Ye, Yuan Ding, Meng Li, Zhihua Tian, Shaoli Wang, Zhen Liu

“…Positive signal drugs were identified using Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). …”
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Multi-omics integration and immune profiling identify possible causal networks leading to uterine microbiome dysbiosis in dairy cows that develop metritis by S. Casaro, J. G. Prim, T. D. Gonzalez, F. Cunha, A. C. M. Silva, H. Yu, R. S. Bisinotto, R. C. Chebel, J. E. P. Santos, C. D. Nelson, S. J. Jeon, R. C. Bicalho, J. P. Driver, Klibs N. Galvão

“…Results The Bayesian network analysis showed a positive directional correlation between prepartum BW, prepartum BW loss, and plasma fatty acids at parturition, suggesting that heavier cows were in lower energy balance than lighter cows. …”
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Genome-wide association study and genomic prediction of root system architecture traits in Sorghum (Sorghum bicolor (L.) Moench) at the seedling stage by Muluken Enyew, Mulatu Geleta, Kassahun Tesfaye, Amare Seyoum, Tileye Feyissa, Admas Alemu, Cecilia Hammenhag, Anders S. Carlsson

“…The genomic prediction accuracy estimated for the studied traits using five Bayesian models ranged from 0.30 to 0.63 while it ranged from 0.35 to 0.60 when the RR-BLUP model was used. …”
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Spatial co-distribution of tuberculosis prevalence and low BCG vaccination coverage in Ethiopia by Haileab Fekadu Wolde, Archie C. A. Clements, Beth Gilmour, Kefyalew Addis Alene

“…Posterior means and a 95% Bayesian credible interval (CrI) were used to summarize the parameters of the model. …”
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Assessing national exposure to and impact of glacial lake outburst floods considering uncertainty under data sparsity by H. Chen, Q. Liang, J. Zhao, S. B. Maharjan

“…This study aims to exploit remote sensing techniques, well-established Bayesian regression models for estimating glacial lake conditions, cutting-edge flood modelling technology, and open data from various sources to innovate a framework for assessing the national exposure and impact of GLOFs. …”
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Assessment of different genotyping markers and algorithms for distinguishing Plasmodium falciparum recrudescence from reinfection in Uganda. by Mwesigwa, Alex, Golumbeanu, Monica, Jones, Sam, Cantoreggi, L. Sara, Musinguzi, Benson, Nankabirwa, I. Joaniter, Bikaitwoha, Everd Maniple, Kalyango, N. Joan, Karamagi, Charles, Plucinski, Mateusz, Nsobya, L. Samuel, Nsanzabana, Christian, Byakika-Kibwika, Pauline

“…Discrepancies in recrudescence classification between match-counting and Bayesian algorithms highlight the need for standardized PCR correction practices…”
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Active deception defense method based on dynamic camouflage network by Shuo WANG, Jianhua WANG, Qingqi PEI, Guangming TANG, Yang WANG, Xiaohu LIU

“…In view of the problem that the existing honeypots often fail to resist the penetration attack due to the lack of confidentiality,an active deception defense method based on dynamic camouflage network (DCN) was presented.The definition of DCN was given firstly,and then the attacker-defender scenario of active deception based on DCN was described.Next,the interaction process of the attacker-defender scenario was modeled by using a signaling game,whose equilibrium can guide the selection of optimal deception strategy.Furthermore,to quantify the payoffs accurately,the two-layer threat penetration graph (TLTPG) was introduced.Finally,the solution for game equilibrium was designed,through which pure strategy and mixed strategy could be calculated simultaneously.The experimental results show that,based on the dynamic camouflage network,the perfect Bayesian equilibrium can provide effective guidance for the defender to implement the optimal defense strategy and maximize the benefits of the defender.In addition,the characteristics and rules of active deception defense DCN-based are summarized.…”
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Estimation of Parameters of Generalized Inverted Exponential Distribution for Progressive Type-II Censored Sample with Binomial Removals by Sanjay Kumar Singh, Umesh Singh, Manoj Kumar

“…We obtained the maximum likelihood and Bayes estimators of the parameters of the generalized inverted exponential distribution in case of the progressive type-II censoring scheme with binomial removals. Bayesian estimation procedure has been discussed under the consideration of the square error and general entropy loss functions while the model parameters follow the gamma prior distributions. …”
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Forecasting Volatility with Time-Varying Coefficient Regressions by Qifeng Zhu, Miman You, Shan Wu

“…We extend the heterogeneous autoregressive- (HAR-) type models by explicitly considering the time variation of coefficients in a Bayesian framework and comprehensively comparing the performances of these time-varying coefficient models and constant coefficient models in forecasting the volatility of the Shanghai Stock Exchange Composite Index (SSEC). …”
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STRUCTURE RELIABILITY CALCULATION METHOD BASED ON IMPROVED NEURAL NETWORK by LI YongHua, CHEN Peng, TIAN ZongRui, CHEN ZhiHao

“…Firstly, the Mind Evolutionary Algorithm was used to optimize the weights and thresholds of BP neural network to obtain the optimal initial value. Secondly, the Bayesian Regularization algorithm was used to train the optimized neural network to establish MEA-BR-BP neural network surrogate model and verify the effectiveness of the improved surrogate model used test function. …”
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Novel Strategy to Improve the Performance of Localization in WSN by M. Vasim Babu, A. V. Ramprasad

“…In this energy consumption model we use both static and dynamic sensor nodes to monitor the optimized energy of all sensor nodes in which every sensor state can be considered as the dynamic Bayesian network. By using this method the power is assigned in terms of dynamic manner to each sensor over discrete time steps to control the graphical structure of our network. …”
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Inferential analysis of the stress-strength reliability for a new extended family of distributions by Mohammed S. Kotb, Mohammed Z. Raqab

“…We propose estimators, including the maximum likelihood and Bayes estimators, as well as various confidence and credible intervals for both the unknown parameters and R, utilizing conjugate priors. In a Bayesian context, we use importance sampling within the Metropolis-Hastings sampler for parameter and reliability function estimation. …”
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GAN-based unsupervised domain adaptive person re-identification by Shengsheng ZHENG, Haibing YIN, Xiaofeng HUANG, Tianjie ZHANG

“…Aiming at the problem that the inaccurate clustering in the unsupervised domain adaptive pedestrian re-recognition results in low network recognition accuracy, an unsupervised domain adaptive pedestrian re-recognition method based on generative confrontation network was proposed.Firstly, the CNN model was optimized by using the batch normalization layer after the pooling layer, deleting a fully connected layer and adopting the Adam optimizer.Secondly, the cluster error was analyzed and the important parameter in the cluster was decided based on minimum error rate Bayesian decision theory.Finally, the generative adversarial network was utilized to adjust the cluster.These steps effectively improved the recognition accuracy of unsupervised domain adaptive person re-identification.In the case of the source domain Market-1501 and the target domain DukeMTMC-reID, experimental results show that mAP and Rank-1 can reach 53.7% and 71.6%, respectively.…”
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Shrinkage Methods for Estimating the Shape Parameter of the Generalized Pareto Distribution by Wilhemina Adoma Pels, Atinuke O. Adebanji, Sampson Twumasi-Ankrah, Richard Minkah

“…The proposed methods use the shrinkage principle to adapt the existing empirical Bayesian with data-based prior and the likelihood moment method to obtain two estimators. …”
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Sliding Recurrence Analysis and its Application of Gear Vibration Signal by Xiao Han, Lv Yong

“…According to the recurrence plot analysis to the gear vibration signal,it is found that there are obvious difference between the gear condition and the driver system characteristics represented by recurrence plots.If the recurrence plots are regarded as a binary image,the parameters calculation by recurrence qualification analysis,such as recurrence rate,determinism,laminarity and recurrence time etc can be used to describe the feature of the image.The characteristics of recurrence plots that correspond to dynamical system and image respectively are analyzed.In order to depict the local feature of recurrence plot,the sliding recurrence analysis is proposed.The proposed approach combined with Gaussian mixture model and Bayesian maximum likelihood classifier are used to classify the gear vibration signals which are acquired from gear fault experiment facility.The classification results show that the higher discrimination rate can be achieved by the proposed method.…”
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Efficient 3D imaging method of MIMO radar for moving target by Wei WANG, Ziying HU, Jia’nan YUE

“…When compressive sensing (CS) was used to achieve sparse imaging of moving targets,the Doppler frequency caused by motion will increase the processing dimension,change the center frequency of echo and worsen the mutual coherence property of measurement matrix.In order to improve the three-dimensional (3D) imaging performance of MIMO radar for moving targets,an efficient method was proposed.In each dimension,the distribution information of targets was searched respectively and a new low-dimensional measurement matrix was reconstructed accordingly,so the targets’ area was narrowed down.At the same time,in order to optimize the mutual coherence property of measurement matrix,Bayesian method was used to optimize the velocity-dimensional projection matrix to reduce the strong mutual coherence brought by sampling of Doppler frequency,then the efficient sparse imaging could be achieved.The simulation results show that proposed method can improve the efficiency,accurate imaging performance with efficient.…”
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Optimization design and application of library face recognition access control system based on improved PCA. by Na Lin, Yan Ding, Yulei Tan

“…The PCA algorithm is optimized by introducing beta prior and full probability Bayesian model. In addition, the research also integrates K-means Clustering Algorithm (KA) to further improve the accuracy and efficiency of face recognition. …”
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Probability of Dying in Each of the Competing Risks under Bimorbid Condition by Kalpana Singh, Suddhendu Biswas

“…This is obtained by choice of a model which is bivariate negative binomial distribution for obtaining the number of deaths (assuming the deaths occur in the last trial). A Bayesian method has also been used for estimating probability of dying in heart disease and chronic kidney disease in the presence of diabetes, hypertension, and stroke or heart disease with chronic kidney disease. …”
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Assessment of Ethical Ideals and Ethical Manners in Care of Older People by Marianne Frilund, Lisbeth Fagerström, Katie Eriksson, Patrik Eklund

“…In this study, we use Bayesian Belief Networks (BBNs) to analyse ethical values (ethos) and ethical manners in daily work with older people. …”
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