Results 11 to 20 of about 13,264,037 (303)

Research Methods: Sampling

Evidence Based Library and Information Practice, 2014
.
Virginia Wilson
doaj   +6 more sources

Protein Fitness Prediction Is Impacted by the Interplay of Language Models, Ensemble Learning, and Sampling Methods

Pharmaceutics, 2023
Advances in machine learning (ML) and the availability of protein sequences via high-throughput sequencing techniques have transformed the ability to design novel diagnostic and therapeutic proteins.
Mehrsa Mardikoraem, Daniel Woldring
doaj   +1 more source

Comparisons of Sampling Procedures and Time of Sampling for the Detection of Salmonella in Danish Infected Chicken Flocks Raised in Floor Systems

Acta Veterinaria Scandinavica, 2002
Bacteriological follow-up samples were taken from 41 chicken (Gallus gallus) flocks in floor systems, where Salmonella enterica (Salmonella) had been detected either directly in bacteriological samples or indirectly by serological samples.
Madsen M, Andersen J, Gradel KO
doaj   +1 more source

Study on the Complexity Reduction of Observed Sequences Based on Different Sampling Methods: A Case of Wind Speed Data

Atmosphere, 2022
Many studies have confirmed that the complexity of a time sequence is closely related to its predictability, but few studies have proposed methods to reduce the time sequence complexity, which is the key to improving its predictability.
Xiaowei Huai, Pengcheng Yan, Li Li, Zelin Cai, Xunjian Xu, Xiaohui Hu   +5 more
doaj   +1 more source

Bayesian methods for hierarchical distance sampling models [PDF]

, 2014
Cornelia S. Oedekoven was supported by a studentship jointly funded by the University of St Andrews and EPSRC (EPSRC grant EP/C522702/1), through the National Centre for Statistical Ecology.The few distance sampling studies that use Bayesian methods ...
Oedekoven, Cornelia Sabrina, MacKenzie, Monique Lea, M. L. Mackenzie, Buckland, Stephen Terrence, C. S. Oedekoven, S. T. Buckland, L. W. Burger, Evans, Kristine O., King, Ruth, K. O. Evans, Burger, L. W., R. King   +11 more
core   +1 more source

Quantitative estimation of sampling uncertainties for mycotoxins in cereal shipments [PDF]

, 2012
Many countries receive shipments of bulk cereals from primary producers. There is a volume of work that is ongoing that seeks to arrive at appropriate standards for the quality of the shipments and the means to assess the shipments as they are out-loaded.
Bourgeois, Florent, Lyman, Geoffrey, Lyman, Geoffrey J.   +2 more
core   +1 more source

Analysis of the Impact of the Type of Sampling of Representative Properties on the Results of Mass Appraisal

Folia Oeconomica Stetinensia, 2020
Research background: Mass valuation is a process in which many properties are valued simultaneously with a uniform approach. An example of a procedure used for mass real estate valuation is the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA ...
Gnat Sebastian
doaj   +1 more source

Model-based distance sampling [PDF]

, 2015
CSO was part-funded by EPSRC/NERC Grant EP/1000917/1.Conventional distance sampling adopts a mixed approach, using model-based methods for the detection process, and design-based methods to estimate animal abundance in the study region, given estimated ...
Oedekoven, Cornelia Sabrina, Buckland, Stephen Terrence, S. T. Buckland, C. S. Oedekoven, D. L. Borchers, Borchers, David Louis   +5 more
core   +1 more source

Evaluation of respondent-driven sampling [PDF]

, 2012
Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred.
Joseph Katongole, Hayes, Richard J., Janet Seeley, Natasha L. Lunel, Tarsh, Matilda N., Richard J. Hayes, Maher, Dermot, Sonnenberg, Pam, Tarsh, Matilda N, Johnston, Lisa G., Hayes, Richard J, White, Richard G, White, Richard G., Lunel, Natasha L, Richard Ndunguse, Copas, Andrew J, Matilda N. Tarsh, Frost, Simon DW, Richard G. White, Andrew J. Copas, Seeley, Janet, Fatima Jichi, McCreesh, Nicky, Nicky McCreesh, Simon D. W. Frost, Lunel, Natasha L., Copas, Andrew J., Jichi, Fatima, Pam Sonnenberg, Frost, Simon D. W., Ndunguse, Richard, Lisa G. Johnston, Johnston, Lisa G, Katongole, Joseph, Dermot Maher   +34 more
core   +1 more source

Network intrusion detection using machine learning approaches: Addressing data imbalance

IET Cyber-Physical Systems, 2022
Cybersecurity has become a significant issue. Machine learning algorithms are known to help identify cyberattacks such as network intrusion. However, common network intrusion datasets are negatively affected by class imbalance: the normal traffic ...
Rahbar Ahsan, Wei Shi, Jean‐Pierre Corriveau   +2 more
doaj   +1 more source