Article
Engineering, Mechanical
Marko Nagode, Jan Papuga, Simon Oman
Summary: This paper discusses the practical task of estimating missing material fatigue strengths for the evaluation of multiaxial fatigue strength criteria, using machine learning models implemented in R. The dataset used for training and testing the models is based on the FatLim dataset with different material parameters. The results show that more data points are needed to achieve the desired goal, and the random forest model rf performs the best while the pcr model performs the worst.
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
(2023)
Article
Ecology
Valerie A. Steen, Adam Duarte, James T. Peterson
Summary: Detecting spatiotemporal changes in organism abundances is crucial for species conservation. Traditional occupancy models and N-mixture models have limitations, but multistate occupancy models have the potential to overcome these limitations by differentiating between high and low abundance sites and detecting population declines.
ECOLOGICAL MODELLING
(2023)
Article
Ecology
Kevin E. See, Michael W. Ackerman, Richard A. Carmichael, Sarah L. Hoffmann, Chris Beasley
Summary: Establishing robust methods and metrics to evaluate habitat quality is critical for the recovery of endangered Pacific salmonids. Modeling approaches like the quantile random forest model developed in this study allow for estimation of habitat carrying capacity at different scales, considering noisy data, correlated variables, and non-linear relationships. These models provide managers with a framework to guide habitat rehabilitation actions and recover salmon populations.
Article
Mathematics, Interdisciplinary Applications
Sebastian Olschewski, Pavel Sirotkin, Jorg Rieskamp
Summary: This study examines the issue of empirical underidentification in estimating parameters in random utility models and explores factors that could potentially mitigate this problem. The results suggest that using specific choice sets and standardizing utility scales can improve estimation accuracy, but may have detrimental effects on the estimation accuracy of risk preference.
BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY
(2022)
Article
Statistics & Probability
Giuseppe Di Benedetto, Francois Caron, Yee Whye Teh
Summary: This paper introduces a flexible class of nonexchangeable random partition models that can generate partitions with cluster sizes growing sublinearly with the sample size, controlled by one parameter. Experiments on real data sets highlight the usefulness of the approach compared to a two-parameter Chinese restaurant process.
ANNALS OF STATISTICS
(2021)
Article
Endocrinology & Metabolism
Gjertrud Louise Laurell, Pontus Plaven-Sigray, Annette Johansen, Nakul Ravi Raval, Arafat Nasser, Clara Aabye Madsen, Jacob Madsen, Hanne Demant Hansen, Lene Lundgaard Donovan, Gitte Moos Knudsen, Adriaan A. Lammertsma, R. Todd Ogden, Claus Svarer, Martin Schain
Summary: The traditional design of PET target engagement studies involves baseline scan and subsequent scans after drug administration. Researchers propose an alternative design, the displacement study, where the drug is administered during an ongoing scan, resulting in reduced radiation exposure and costs. They develop kinetic models to analyze PET displacement data, modifying existing compartment models to accommodate time-variant increase in occupancy. Through simulations and application to PET data from pigs, the proposed models show promise in estimating target occupancy from a single displacement scan.
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM
(2023)
Article
Chemistry, Multidisciplinary
Nurul Amalin Fatihah Kamarul Zaman, Kasturi Devi Kanniah, Dimitris G. Kaskaoutis, Mohd Talib Latif
Summary: The study utilizes machine-learning models to estimate PM2.5 concentrations across Malaysia, showing higher levels at urban/industrial sites and lower levels at suburban/rural sites. Seasonal variations in PM2.5 concentrations, with the highest levels during the dry season, were also recorded. The Random Forest model displayed slightly better performance than Support Vector Regression for most models.
APPLIED SCIENCES-BASEL
(2021)
Article
Psychology, Mathematical
Joshua Correll, Chris Mellinger, Eric J. Pedersen
Summary: Mixed-effects models are commonly used in various disciplines, but it is challenging to specify a standardized effect size like eta(2) due to the distinction between multiple sources of variation. This paper introduces new, flexible approaches to estimating eta(2) in mixed-effect models with crossed random factors and conducts simulations to compare old and new methods. Recommendations for a simple approach based on previous work are provided after examining the strengths and weaknesses of the different methods.
BEHAVIOR RESEARCH METHODS
(2022)
Article
Polymer Science
Kaffayatullah Khan, Mudassir Iqbal, Babatunde Abiodun Salami, Muhammad Nasir Amin, Izaz Ahamd, Anas Abdulalim Alabdullah, Abdullah Mohammad Abu Arab, Fazal E. Jalal
Summary: This study investigated the estimation of the flexural capacity of beams using non-linear capabilities of two Artificial Intelligence (AI) models and conducted parametric and sensitivity analysis. The results showed that the Artificial Neural Network (ANN) model outperformed the Random Forest (RF) regression model in terms of accuracy and flexural strength performance. Increasing bottom reinforcement, width and depth of the beam, and compressive strength all improved the bending moment capacity. The change in bottom flexural reinforcement was found to be the most influential parameter.
Article
Environmental Sciences
Suthira Thongkao, Pakorn Ditthakit, Sirimon Pinthong, Nureehan Salaeh, Ismail Elkhrachy, Nguyen Thi Thuy Linh, Quoc Bao Pham
Summary: This study adopted five soft computing methods to estimate the b-factor in FAO Blaney-Criddle and compared their performances. SVR-rbf method had the highest performance among the five methods.
Article
Multidisciplinary Sciences
Eric P. M. Grist, Trevelyan J. McKinley, Saptarshi Das, Tom Tregenza, Aileen Jeffries, Nicholas Tregenza
Summary: This article presents a simple and transparent non-parametric trend evaluation method called "Paired Year Ratio Assessment (PYRA)" for evaluating population trends in acoustic monitoring data for cetacean conservation. The study compares the performance of PYRA with traditional generalized additive models (GAMS) and nonparametric randomization tests, concluding that PYRA is a powerful tool for identifying population trends.
Article
Physics, Multidisciplinary
Fei Ma, Ping Wang, Bing Yao
Summary: This paper introduces a growth model called Fibonacci trees F(t) with power-law degree distribution, and analytical expressions for two topological indices on random walks in the model. The study shows a linear correlation between MFPT and the number of vertices in F(t), indicating a more optimal topological structure in Fibonacci trees F(t).
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Biodiversity Conservation
Emily L. Weiser, Jay E. Diffendorfer, Laura Lopez-Hoffman, Darius Semmens, Wayne E. Thogmartin
Summary: The TrendPowerTool is a web-based lookup app that quickly provides users with an estimate of the statistical power to detect a population trend of a particular magnitude in a planned monitoring program. With a user-friendly interface, users can retrieve results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.
CONSERVATION SCIENCE AND PRACTICE
(2021)
Article
Ecology
Hanna Meyer, Edzer Pebesma
Summary: Machine learning algorithms are popular for spatial mapping due to their ability to fit complex relationships, but their use is limited to data similar to the training set. The study proposes a method to assess the area where a prediction model can be reliably applied, using a Dissimilarity Index (DI) to define the Area of Applicability (AOA) and map estimated performance. Simulation studies show comparable prediction errors within the AOA to cross-validation errors, emphasizing the importance of considering the relationship between DI and cross-validation performance.
METHODS IN ECOLOGY AND EVOLUTION
(2021)
Article
Forestry
Liang Liu, Shaoda Li, Wunian Yang, Xiao Wang, Xinrui Luo, Peilian Ran, Helin Zhang
Summary: Forests face threats like drought in the context of global climate change. Canopy water content (CWC) serves as an important indicator for forest water stress, mortality, and fire monitoring. This study used radiative transfer models and the random forest algorithm to retrieve forest CWC in the contiguous U.S. The results demonstrated that accurate simulation of leaf traits and canopy structure leads to improved CWC inversion. The study highlights the suitability of 3D radiative transfer models for canopy parameter inversion.
Article
Biodiversity Conservation
Andrew Sier, Don Monteith
ECOLOGICAL INDICATORS
(2016)
Article
Behavioral Sciences
Francoise Wemelsfelder, Ian Nevison, Alistair B. Lawrence
Article
Food Science & Technology
N. R. Lambe, R. I. Richardson, J. M. Macfarlane, I. Nevison, W. Haresign, O. Matika, L. Buenger
Article
Reproductive Biology
E. M. Baxter, S. Jarvis, R. B. D'Eath, D. W. Ross, S. K. Robson, M. Farish, I. M. Nevison, A. B. Lawrence, S. A. Edwards
Review
Environmental Sciences
Martin Musche, Mihai Adamescu, Per Angelstam, Sven Bacher, Jaana Baeck, Heather L. Buss, Christopher Duffy, Giovanna Flaim, Jerome Gaillardet, George V. Giannakis, Peter Haase, Lubos Halada, Daniel Kissling, Lars Lundin, Giorgio Matteucci, Henning Meesenburg, Don Monteith, Nikolaos P. Nikolaidis, Tanja Pipan, Petr Pysek, Ed C. Rowe, David B. Roy, Andrew Sier, Ulrike Tappeiner, Montserrat Vila, Tim White, Martin Zobel, Stefan Klotz
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2019)
Article
Agriculture, Dairy & Animal Science
C. J. Savory, L. Kostal, I. M. Nevison
BRITISH POULTRY SCIENCE
(2006)
Article
Agriculture, Dairy & Animal Science
CH Knight, MA Alamer, A Sorensen, IM Nevison, DJ Flint, RG Vernon
JOURNAL OF DAIRY RESEARCH
(2004)
Article
Agriculture, Dairy & Animal Science
JM Yeo, CH Knight, IM Nevison, DG Chamberlain
JOURNAL OF DAIRY SCIENCE
(2003)
Article
Environmental Sciences
TW Parr, ARJ Sier, RW Battarbee, A Mackay, J Burgess
SCIENCE OF THE TOTAL ENVIRONMENT
(2003)
Article
Environmental Sciences
LG Firbank, CJ Barr, RGH Bunce, MT Furse, R Haines-Young, M Hornung, DC Howard, J Sheail, A Sier, SM Smart
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2003)
Article
Food Science & Technology
IM Nevison, DD Muir
JOURNAL OF SENSORY STUDIES
(2002)
Article
Plant Sciences
J Chard, S Irvine, AMI Roberts, IM Nevison, WJ McGavin, AT Jones