Bibliografías temáticas / Bayesian therory

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Literatura académica sobre el tema "Bayesian therory"

Autor: Grafiati
Publicado: 10 de marzo de 2023

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Artículos de revistas sobre el tema "Bayesian therory"

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Thomson, A. H. "BAYESIAN FEEDBACK METHODS FOR OPTIMISING THERAPY." Clinical Neuropharmacology 15 (1992): 245A—246A. http://dx.doi.org/10.1097/00002826-199201001-00128.

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Abrams, Keith, Deborah Ashby, and Doug Errington. "Bayesian analysis of neutron therapy trial." Controlled Clinical Trials 12, no. 5 (1991): 666–67. http://dx.doi.org/10.1016/0197-2456(91)90200-6.

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Duan, Leo L., Alexander L. Young, Akihiko Nishimura, and David B. Dunson. "Bayesian constraint relaxation." Biometrika 107, no. 1 (2019): 191–204. http://dx.doi.org/10.1093/biomet/asz069.

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Summary Prior information often takes the form of parameter constraints. Bayesian methods include such information through prior distributions having constrained support. By using posterior sampling algorithms, one can quantify uncertainty without relying on asymptotic approximations. However, sharply constrained priors are not necessary in some settings and tend to limit modelling scope to a narrow set of distributions that are tractable computationally. We propose to replace the sharp indicator function of the constraint with an exponential kernel, thereby creating a close-to-constrained nei
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Neoptolemos, John P., and Trevor F. Cox. "Bayesian analysis unravels pancreas-cancer adjuvant therapy." Lancet Oncology 14, no. 11 (2013): 1034–35. http://dx.doi.org/10.1016/s1470-2045(13)70403-0.

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Tidwell, Rebecca S. Slack, S. Andrew Peng, Minxing Chen, Diane D. Liu, Ying Yuan, and J. Jack Lee. "Bayesian clinical trials at The University of Texas MD Anderson Cancer Center: An update." Clinical Trials 16, no. 6 (2019): 645–56. http://dx.doi.org/10.1177/1740774519871471.

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Background/aims In our 2009 article, we showed that Bayesian methods had established a foothold in developing therapies in our institutional oncology trials. In this article, we will document what has happened since that time. In addition, we will describe barriers to implementing Bayesian clinical trials, as well as our experience overcoming them. Methods We reviewed MD Anderson Cancer Center clinical trials submitted to the institutional protocol office for scientific and ethical review between January 2009 and December 2013, the same length time period as the previous article. We tabulated
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Büchter, Theresa, Nicole Steib, Katharina Böcherer-Linder, et al. "Designing Visualisations for Bayesian Problems According to Multimedia Principles." Education Sciences 12, no. 11 (2022): 739. http://dx.doi.org/10.3390/educsci12110739.

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Questions involving Bayesian Reasoning often arise in events of everyday life, such as assessing the results of a breathalyser test or a medical diagnostic test. Bayesian Reasoning is perceived to be difficult, but visualisations are known to support it. However, prior research on visualisations for Bayesian Reasoning has only rarely addressed the issue on how to design such visualisations in the most effective way according to research on multimedia learning. In this article, we present a concise overview on subject-didactical considerations, together with the most fundamental research of bot
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Mukha, V. S. "Comparative numerical analysis of Bayesian decision rule and probabilistic neural network for pattern recognition." Doklady BGUIR 19, no. 7 (2021): 13–21. http://dx.doi.org/10.35596/1729-7648-2021-19-7-13-21.

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At present, neural networks are increasingly used to solve many problems instead of traditional methods for solving them. This involves comparing the neural network and the traditional method for specific tasks. In this paper, computer modeling of the Bayesian decision rule and the probabilistic neural network is carried out in order to compare their operational characteristics for recognizing Gaussian patterns. Recognition of four and six images (classes) with the number of features from 1 to 6 was simulated in cases where the images are well and poorly separated. The sizes of the training an
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Quintela-del-Río, Alejandro, Beatriz Rodríguez-Romero, Verónica Robles-García, Pablo Arias-Rodríguez, Javier Cudeiro-Mazaira, and Alicia Martínez-Rodríguez. "Bayesian Methods in the Field of Rehabilitation." American Journal of Physical Medicine & Rehabilitation 98, no. 6 (2019): 516–20. http://dx.doi.org/10.1097/phm.0000000000001124.

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McAleer, S. D., H. Chrystyn, and D. A. G. Newton. "BAYESIAN DERIVED PHARMACOKINETIC/PHARMACODYNAMIC VARIABLES FROM WARFARIN THERAPY." Journal of Pharmacy and Pharmacology 42, S1 (1990): 189P. http://dx.doi.org/10.1111/j.2042-7158.1990.tb14562.x.

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Cao, Ming, Yue Fan, and Qinke Peng. "Bayesian Gene Selection Based on Pathway Information and Network-Constrained Regularization." Computational and Mathematical Methods in Medicine 2021 (August 4, 2021): 1–9. http://dx.doi.org/10.1155/2021/7471516.

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High-throughput data make it possible to study expression levels of thousands of genes simultaneously under a particular condition. However, only few of the genes are discriminatively expressed. How to identify these biomarkers precisely is significant for disease diagnosis, prognosis, and therapy. Many studies utilized pathway information to identify the biomarkers. However, most of these studies only incorporate the group information while the pathway structural information is ignored. In this paper, we proposed a Bayesian gene selection with a network-constrained regularization method, whic
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Tesis sobre el tema "Bayesian therory"

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Vecchi, Claudio. "Scripting automation e modelli bayesiani: Applicazioni cliniche in radioterapia e sviluppo di tecniche innovative per adaptive radiation therapy." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6623/.

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La presente ricerca consiste nel validare ed automatizzare metodiche di Adaptive Radiation Therapy (ART), che hanno come obiettivo la personalizzazione continua del piano di trattamento radioterapico in base alle variazioni anatomiche e dosimetriche del paziente. Tali variazioni (casuali e/o sistematiche) sono identificabili mediante l’utilizzo dell’imaging diagnostico. Il lavoro svolto presso la struttura di Fisica Medica dell’Azienda Ospedaliera Universitaria del Policlinico di Modena, si inserisce in un progetto del Ministero della Salute del bando Giovani Ricercatori dal titolo: “Dose wa
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Maposa, Innocent. "Survival modelling and analysis of HIV/AIDS patients on HIV care and antiretroviral treatment to determine longevity prognostic factors." University of the Western Cape, 2016. http://hdl.handle.net/11394/5444.

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Philosophiae Doctor - PhD<br>The HIV/AIDS pandemic has been a torment to the African developmental agenda, especially the Southern African Development Countries (SADC), for the past two decades. The disease and condition tends to affect the productive age groups. Children have also not been spared from the severe effects associated with the disease. The advent of antiretroviral treatment (ART) has brought a great relief to governments and patients in these regions. More people living with HIV/AIDS have experienced a boost in their survival prospects and hence their contribution to national dev
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SEDDA, GIULIA. "The interplay between movement and perception: how interaction can influence sensorimotor performance and neuromotor recovery." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/1011732.

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Movement and perception interact continuously in daily activities. Motor output changes the outside world and affect perceptual representations. Similarly, perception has consequences on movement. Nevertheless, how movement and perception influence each other and share information is still an open question. Mappings from movement to perceptual outcome and vice versa change continuously throughout life. For example, a cerebrovascular accident (stroke) elicits in the nervous system a complex series of reorganization processes at various levels and with different temporal scales. Functiona
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Krizova, Katarina. "ADHD CHILDREN AND MENTAL HEALTH SERVICE USE: MATERNAL DETERMINANTS." UKnowledge, 2015. http://uknowledge.uky.edu/hes_etds/28.

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The current study investigated maternal determinants of mental health service use, namely, individual child therapy, among preadolescent children diagnosed with ADHD. The Behavioral Model of Health Care Utilization (Andersen, 2008) was used as a theoretical framework for the study. Data from the last three rounds of ECLS-K dataset were employed to test a longitudinal model using Bayesian analysis. Socio-demographic variables and maternal mental health were tested as exogenous variables and mother-child relationship variables, discipline variables, and perceived maternal concern about child’s o
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NUNZIATI, MATTEO. "Tecnologie biometriche per il riconoscimento del parlante / Biometric technologies for speaker recognition." Doctoral thesis, 2008. http://hdl.handle.net/2158/590123.

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Cypko, Mario A. "Therapy Decision Support System using Bayesian Networks for Multidisciplinary Treatment Decisions." 2017. https://ul.qucosa.de/id/qucosa%3A16891.

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Treatment decision-making in head and neck oncology is gaining complexity by the increasing evidence pointing towards more individualized and selective treatment options. Therefore, decision making in multidisciplinary teams is becoming the key point in the clinical pathways. Clinical decision-support systems based on Bayesian networks can support complex decision-making processes by providing mathematically correct and transparent advises. In the last three decades, different clinical applications of Bayesian networks have been proposed. Because appropriate data for model learning and testing
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Powell, Ryan. "A novel approach to support evidence-based medicine: should sulfonylureas remain an acceptable therapy for diabetes?" Thesis, 2017. https://hdl.handle.net/2144/23373.

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A key element in evidence-based medicine approaches is the ability for clinicians to evaluate the scientific rigor and relevance of research evidence. In the treatment of diabetes, clinicians make increasingly difficult decisions about which drug regimens are best for their patients with limited evidence-based information. While the consensus is that metformin should be the initial drug treatment when diet and exercise are not sufficient, clinicians disagree on whether sulfonylureas should remain a suitable therapy after metformin. While this would be improved with further research inve
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"A Study on Optimization Measurement Policies for Quality Control Improvements in Gene Therapy Manufacturing." Master's thesis, 2020. http://hdl.handle.net/2286/R.I.62668.

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abstract: With the increased demand for genetically modified T-cells in treating hematological malignancies, the need for an optimized measurement policy within the current good manufacturing practices for better quality control has grown greatly. There are several steps involved in manufacturing gene therapy. These steps are for the autologous-type gene therapy, in chronological order, are harvesting T-cells from the patient, activation of the cells (thawing the cryogenically frozen cells after transport to manufacturing center), viral vector transduction, Chimeric Antigen Receptor (CAR) atta
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Wijeysundera, Harindra Channa. "Economic Evaluation of Percutaneous Coronary Intervention in Stable Coronary Artery Disease: Studies in Utilities and Decision Modeling." Thesis, 2011. http://hdl.handle.net/1807/32162.

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The initial treatment options for patients with stable coronary artery disease include optimal medical therapy alone, or coronary revascularization with optimal medical therapy. The most common revascularization modality is percutaneous coronary intervention (PCI) with either bare metal stents (BMS) or drug-eluting stents (DES). PCI is believed to reduce recurrent angina and thereby decrease the need for additional procedures compared to optimal medical therapy alone. It remains unclear if these benefits are sufficient to offset the increased costs and small increase in adverse events associat
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Libros sobre el tema "Bayesian therory"

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Pan, Haitao, and Ying Yuan. Bayesian Adaptive Design for Immunotherapy and Targeted Therapy. Springer, 2024.

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Pan, Haitao, and Ying Yuan. Bayesian Adaptive Design for Immunotherapy and Targeted Therapy. Springer, 2023.

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Capítulos de libros sobre el tema "Bayesian therory"

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Adak, Sudeshna, and Abhinanda Sarkar. "Longitudinal Modeling of the Side Effects of Radiation Therapy." In Case Studies in Bayesian Statistics. Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-1502-8_5.

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"Bayesian Predictive Inference for a Binary RandomVariable: Survey Estimation of the Quality of Care thatRadiation Therapy Patients Receive." In Bayesian Biostatistics. CRC Press, 2018. http://dx.doi.org/10.1201/9781315274300-38.

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Berzuini, Carlo, Riccardo Bellazzi, and David Spiegelhalter. "BAYESIAN NETWORKS APPLIED TO THERAPY MONITORING." In Uncertainty Proceedings 1991. Elsevier, 1991. http://dx.doi.org/10.1016/b978-1-55860-203-8.50008-5.

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Little, Max A. "Nonparametric Bayesian machine learning and signal processing." In Machine Learning for Signal Processing. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198714934.003.0010.

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We have seen that stochastic processes play an important foundational role in a wide range of methods in DSP. For example, we treat a discrete-time signal as a Gaussian process, and thereby obtain many mathematically simplified algorithms, particularly based on the power spectral density. At the same time, in machine learning, it has generally been observed that nonparametric methods outperform parametric methods in terms of predictive accuracy since they can adapt to data with arbitrary complexity. However, these techniques are not Bayesian so we are unable to do important inferential procedures such as draw samples from the underlying probabilistic model or compute posterior confidence intervals. But, Bayesian models are often only mathematically tractable if parametric, with the corresponding loss of predictive accuracy. An alternative, discussed in this section, is to extend the mathematical tractability of stochastic processes to Bayesian methods. This leads to so-called Bayesian nonparametrics exemplified by techniques such as Gaussian process regression and Dirichlet process mixture modelling that have been shown to be extremely useful in practical DSP and machine learning applications.
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Sankararaman, Shankar, and Sankaran Mahadevan. "Statistical Approach to Structural Damage Diagnosis under Uncertainty." In Emerging Design Solutions in Structural Health Monitoring Systems. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8490-4.ch008.

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This chapter presents a statistical methodology for structural damage diagnosis (detection, localization and estimation), in the context of continuous online monitoring. There are several sources of uncertainty such as physical variability, measurement uncertainty and model errors that affect structural damage diagnosis, and therefore, it may not be possible to precisely detect, localize, and estimate damage. Hence, a statistical approach can help to identify these sources of uncertainty, quantify their combined effect on diagnosis, and thereby, provide an estimate of the confidence in the results of diagnosis. Damage detection is based on residuals between nominal and damaged system-level responses, using statistical hypothesis testing whose uncertainty can be captured easily. Localization is based on the comparison of damage signatures derived from the system model. Both classical statistics-based methods and Bayesian statistics-based methods are investigated to quantify the uncertainty in all the three steps of diagnosis, i.e. detection, localization, and quantification. While classical statistics-based methods use the concept of least squares-based optimization, Bayesian methods make use of likelihood function and Bayes theorem. The uncertainties in damage detection, isolation and quantification are combined to quantify the overall uncertainty in diagnosis. The proposed methods are illustrated using the example of a structural frame.
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Mishra, Mayank, and Chavon Grande. "Probabilistic NDT data fusion of Ferroscan test data using Bayesian inference." In Structural Analysis of Historical Constructions: Anamnesis, Diagnosis, Therapy, Controls. CRC Press, 2016. http://dx.doi.org/10.1201/9781315616995-99.

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Han, Seunghan, and Walter Stechele. "Default Reasoning for Forensic Visual Surveillance Based on Subjective Logic and its Comparison with L-Fuzzy Set Based Approaches." In Multimedia Data Engineering Applications and Processing. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2940-0.ch004.

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Default reasoning can provide a means of deriving plausible semantic conclusion under imprecise and contradictory information in forensic visual surveillance. In such reasoning under uncertainty, proper uncertainty handling formalism is required. A discrete species of Bilattice for multivalued default logic demonstrated default reasoning in visual surveillance. In this article, the authors present an approach to default reasoning using subjective logic that acts in a continuous space. As an uncertainty representation and handling formalism, subjective logic bridges Dempster Shafer belief theory and second order Bayesian, thereby making it attractive tool for artificial reasoning. For the verification of the proposed approach, the authors extend the inference scheme on the bilattice for multivalued default logic to L-fuzzy set based logics that can be modeled with continuous species of bilattice structures. The authors present some illustrative case studies in visual surveillance scenarios to contrast the proposed approach with L-fuzzy set based approaches.
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Taffarel, S., G. P. Campostrini, L. Rosato, C. Marson, F. da Porto, and C. Modena. "The application of a Bayesian approach to assess the seismic vulnerability of historical centers." In Structural Analysis of Historical Constructions: Anamnesis, Diagnosis, Therapy, Controls. CRC Press, 2016. http://dx.doi.org/10.1201/9781315616995-166.

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O. Soogun, Adenike, Ayesha B.M. Kharsany, Temesgen Zewotir, and Delia North. "Spatial Variation and Factors Associated with Unsuppressed HIV Viral Load among Women in an HIV Hyperendemic Area of KwaZulu-Natal, South Africa." In Infectious Diseases. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.105547.

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New HIV infections among young women remains exceptionally high and to prevent onward transmission, UNAIDS set ambitious treatment targets. This study aimed to determine the prevalence, spatial variation and factors associated with unsuppressed HIV viral load at ≥400 copies per mL. This study analysed data from women aged 15–49 years from the HIV Incidence Provincial Surveillance System (HIPSS) enrolled in two sequential cross-sectional studies undertaken in 2014 and 2015 in rural and peri-urban KwaZulu-Natal, South Africa. Bayesian geoadditive model with spatial effect for a small enumeration area was adopted using Integrated Nested Laplace Approximation (INLA) function to analyze the findings. The overall prevalence of unsuppressed HIV viral load was 45.2% in 2014 and 38.1% in 2015. Factors associated with unsuppressed viral load were no prior knowledge of HIV status, had a moderate-to-low perception of acquiring HIV, not on antiretroviral therapy (ART), and having a low CD4 cell count. In 2014, women who ever consumed alcohol and in 2015, ever ran out of money, had two or more lifetime sexual partners, ever tested for tuberculosis, and ever diagnosed with sexually transmitted infection were at higher risk of being virally unsuppressed. The nonlinear effect showed that women aged 15 to 29 years, from smaller households and had fewer number of lifetime HIV tests, were more likely to be virally unsuppressed. High viral load risk areas were the north-east and south-west in 2014, with north and west in 2015. The findings provide guidance on identifying key populations and areas for targeted interventions.
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Actas de conferencias sobre el tema "Bayesian therory"

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Seo, Sangwon, and Vaibhav V. Unhelkar. "Semi-Supervised Imitation Learning of Team Policies from Suboptimal Demonstrations." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/346.

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We present Bayesian Team Imitation Learner (BTIL), an imitation learning algorithm to model the behavior of teams performing sequential tasks in Markovian domains. In contrast to existing multi-agent imitation learning techniques, BTIL explicitly models and infers the time-varying mental states of team members, thereby enabling learning of decentralized team policies from demonstrations of suboptimal teamwork. Further, to allow for sample- and label-efficient policy learning from small datasets, BTIL employs a Bayesian perspective and is capable of learning from semi-supervised demonstrations.
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Bijedic, N., I. Hamulic, Z. Vukobrat-Bijedic, and A. Husic-Selimovic. "Bayesian network model of HCV therapy response prediction in FBiH." In 2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2012. http://dx.doi.org/10.1109/sisy.2012.6339487.

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Agrawal, Krishna, Kushagra Jain, Dhawal Gupta, Raunak Srivastav, Abhijeet Agnihotri, and Atul Thakur. "Bayesian Optimization Based Terrestrial Gait Tuning for a 12-DOF Alligator-Inspired Robot With Active Body Undulation." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86033.

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In addition to aiding in swimming, body undulation of an alligator plays a critical role in terrestrial locomotion by imparting stability. This paper reports design, fabrication and terrestrial locomotion control incorporating active body undulation of a 12-DOF alligator-inspired robot. Each of the four legs of the developed robot has two rotational degrees of freedom while the body can perform undulation using additional four rotational degrees of freedom. This paper also presents a Bayesian optimization based approach to tune the gait parameters of both leg oscillation and body undulation in
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Liu, Xiaofeng, Bo Hu, Linghao Jin, et al. "Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/122.

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In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training. Considering the inherent conditional and label shifts, we would expect the alignment of p(x|y) and p(y). However, the widely used domain invariant feature learning (IFL) methods relies on aligning the marginal concept shift w.r.t. p(x), which rests on an unrealistic assumption that p(y) is invariant across domains. We thereby propose a novel variational Bayesian inference framework to enforce the conditional distri
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Sengupta, Ushnish, Carl E. Rasmussen, and Matthew P. Juniper. "Bayesian Machine Learning for the Prognosis of Combustion Instabilities From Noise." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14904.

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Abstract Experiments are performed on a turbulent swirling flame placed inside a vertical tube whose fundamental acoustic mode becomes unstable at higher powers and equivalence ratios. The power, equivalence ratio, fuel composition and boundary condition of this tube are varied and, at each operating point, the combustion noise is recorded. In addition, short acoustic pulses at the fundamental frequency are supplied to the tube with a loudspeaker and the decay rates of subsequent acoustic oscillations are measured. This quantifies the linear stability of the system at every operating point. Us
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Shahan, David, and Carolyn C. Seepersad. "Bayesian Network Classifiers for Set-Based Collaborative Design." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28724.

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Complex design problems are typically decomposed into smaller design problems that are solved by domain-specific experts who must then coordinate their solutions into a satisfactory system-wide solution. In set-based collaborative design, collaborating engineers coordinate themselves by communicating multiple design alternatives at each step of the design process. The goal in set-based collaborative design is to spend additional resources exploring multiple options in the early stages of the design process, in exchange for less iteration in the latter stages, when iterative rework tends to be
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Bai, Guangxing, Amirmahyar Abdolsamadi, and Pingfeng Wang. "Failure Prognosis Based on Adaptive State Space Models." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-66167.

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This paper presents a generic data-driven failure prognosis method based on adaptive state space models for engineering systems, which integrates adaptive model recognition with a dynamic system model for remaining useful life prediction. The developed approach employs a statistical learning framework for adaptively learning of time-series degradation performance, and then a Bayesian technique for self-updating of data-driven models to adapt the operational or environmental changes. With the developed approach, the prognosis technique can eliminate the dependence to system specific models and
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Wendel, John C., Andrew W. Nelson, Arif S. Malik, and Mark E. Zipf. "Bayesian-Based Probabilistic Force Modeling in Cold Rolling." In ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/msec2013-1226.

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A primary factor in manufacturing high-quality cold-rolled sheet is the ability to accurately predict the required rolling force. The rolling force directly influences roll-stack deflections, which correlate to the resulting flatness quality of the rolled sheet. Increasingly high demand for thin and ultra-thin gauge for cold-rolled sheet metals, along with the correspondingly larger sensitivity of flatness defects when rolling thin gauges, makes it more important to accurately and rapidly predict the rolling force before the rolling operation begins. Accurate rolling force predictions enable a
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Stöhr, M., A. Hikal, A. Oeser, et al. "Development of a therapy decision-supporting system for laryngeal cancer based on Bayesian networks." In Abstract- und Posterband – 90. Jahresversammlung der Deutschen Gesellschaft für HNO-Heilkunde, Kopf- und Hals-Chirurgie e.V., Bonn – Digitalisierung in der HNO-Heilkunde. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1686080.

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Hamaide, Valentin, and François Glineur. "Transfer learning in Bayesian optimization for the calibration of a beam line in proton therapy." In ESANN 2021 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Ciaco - i6doc.com, 2021. http://dx.doi.org/10.14428/esann/2021.es2021-79.

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Informes sobre el tema "Bayesian therory"

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Li, wanlin, jie Yun, siying He, ziqi Zhou, and ling He. Effect of different exercise therapies on fatigue in maintenance hemodialysis patients:A Bayesian Network Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0144.

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Review question / Objective: Population: maintenance hemodialysis patients. Intervention: exercise therapy (resistance exercise； aerobic exercise； resistance combined aerobic exercise； muscle relaxation training； Baduanjin ). Comparison: simple routine nursing. Outcome: fatigue； sleep quality. Study design: randomized controlled trial. Eligibility criteria: Inclusion and exclusion criteria： RCT of study type exercise intervention in MHD patients' fatigue； Study subjects： MHD patients ≥18 years old, regardless of gender, nationality or race； The intervention measures were exercise therapy, incl
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Xu, Piao. Sound therapy for the treatment of chronic subjective tinnitus:A Bayesian network meta analysis of RCTs. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.4.0033.

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Zhou, Hang, Li Yan, Shuguang Zhang, et al. Acupuncture related therapy for ovulatory disorders: a systematic review and Bayesian network meta-analysis protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.6.0078.

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Chen, WanQiang, FangFang Wu, HongBo Lv, et al. Whether cognitive behavioral therapy is effective for Alzheimer's disease: a protocol for Bayesian network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.10.0076.

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Wu, Tong, Chengwei Fu, Yiran Deng, Wanping Huang, Yang Jiao, and Xiaoxiao Li. Acupuncture therapy for Radiotherapy-induced adverse effects: A protocol for systematic review and Bayesian network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.7.0054.

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Hossain, Niamat Ullah Ibne, Farjana Nur, Raed Jaradat, et al. Metrics for assessing overall performance of inland waterway ports : a Bayesian Network based approach. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40545.

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Because ports are considered to be the heart of the maritime transportation system, thereby assessing port performance is necessary for a nation’s development and economic success. This study proposes a novel metric, namely, “port performance index (PPI)”, to determine the overall performance and utilization of inland waterway ports based on six criteria, port facility, port availability, port economics, port service, port connectivity, and port environment. Unlike existing literature, which mainly ranks ports based on quantitative factors, this study utilizes a Bayesian Network (BN) model tha
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He, zhe, liwei Xing, ming He, yuhuan Sun, jinlong Xu, and rong Zhao. Effect of Acupuncture on Mammary Gland Hyperplasia (MGH): a Bayesian network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.9.0058.

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Review question / Objective: This review aims at conducting a network meta-analysis to assess the potential therapeutic effectiveness and safety of acupuncture therapy for the treatment of MGH. Condition being studied: MGH is a benign breast disease caused by excessive growth of mammary duct epithelial cells and interstitial fibers. Its prevalence rate among women of childbearing age is about 13.5-42%, accounting for 99.3% of the total number of patients with breast related diseases, and its possibility of developing breast cancer can reach 5-10%. Breast hyperplasia can cause clinical symptoms
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Zhang, Wei-ping, Dong-qing Zhao, Guang-yu Qian, Jing Jin, Yin-ping Yao, and Xing-mao Bian. Acupuncture therapy strategy options in postoperative management after laparoscopic cholecystectomy：A protocol for systematic review and Bayesian meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.12.0056.

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Han, Yiqun, Jiayu Wang, and Binghe Xu. Assessment of optimal choice as first-line therapy for patients with triple-negative breast cancer: a Bayesian analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.8.0030.

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Bian, Zhiyuan, Jie Yu, Mingqi Tu, et al. Acupuncture and related therapies for carpal tunnel syndrome: A protocol for systematic review and Bayesian network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.11.0094.

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Review question / Objective: We aim to compare the efficacy and safety of different acupuncture and related therapies for carpal tunnel syndrome (CTS) using systematic review and network meta-analysis (NMA). Condition being studied: CTS is a symptomatic condition caused by compression of the median nerve within the carpal tunnel. Patients with CTS typically report paresthesia or pain in distribution of median nerve distal to the wrist. Diverse non-surgical treatments and surgical decompression have been used in the management of CTS. Acupuncture, a prominent component of traditional Chinese me
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