The most popular method used to gain an understanding of population trends or of differences in bird abundance among land condition categories is to use information derived from point counts. Unfortunately, various factors can affect one's ability to detect birds, and those factors need to be controlled or accounted for so that any difference in one's index among time periods or locations is an accurate reflection of differences in bird abundance and not differences in detectability. Avian ecologists could use appropriately sized fixed-area surveys to minimize the chance that they might be deceived by distance-based detectability bias, but the current method of choice is to use a modeling approach that allows one to account for distance-based bias by modeling the effects of distance on detectability or occupancy. I challenge the idea that modeling is the best approach to account for distance-based effects on the detectability of birds because the most important distance-based modeling assumptions can never be met. The use of a fixed-area survey method to generate an index of abundance is the simplest way to control for distance-based detectability bias and should not be universally condemned or be the basis for outright rejection in the publication process.
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http://dx.doi.org/10.1002/eap.1385 | DOI Listing |
Diagnostics (Basel)
January 2025
Department of Digital Forensics Engineering, Technology Faculty, Firat University, Elazig 23119, Turkey.
Electroencephalography (EEG) signal-based machine learning models are among the most cost-effective methods for information retrieval. In this context, we aimed to investigate the cortical activities of psychotic criminal subjects by deploying an explainable feature engineering (XFE) model using an EEG psychotic criminal dataset. In this study, a new EEG psychotic criminal dataset was curated, containing EEG signals from psychotic criminal and control groups.
View Article and Find Full Text PDFComput Biol Med
January 2025
Delta Higher Institute for Engineering and Technology, Mansoura, Egypt. Electronic address:
Although it is not a new illness and has been around since the previous century, monkeypox later resurgence is fraught with difficulties. This study presents a novel approach of diagnosing monkeypox using artificial intelligence, which is called Effective Monkeypox Diagnosis Strategy (EMDS). The proposed EMDS is established through two sequential stages, namely; (i) Pre-Processing Phase (PP) and (ii) Monkeypox Diagnosing phase (MDP).
View Article and Find Full Text PDFBioData Min
January 2025
Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, No. 17, Xu-Zhou Road, Taipei, 100025, Taiwan.
Background: Analyzing free-living physical activity (PA) data presents challenges due to variability in daily routines and the lack of activity labels. Traditional approaches often rely on summary statistics, which may not capture the nuances of individual activity patterns. To address these limitations and advance our understanding of the relationship between PA patterns and health outcomes, we propose a novel motif clustering algorithm that identifies and characterizes specific PA patterns.
View Article and Find Full Text PDFNonlinear Dyn
September 2024
Department of Mathematics, University College London, London, UK.
Time series is a data structure prevalent in a wide range of fields such as healthcare, finance and meteorology. It goes without saying that analyzing time series data holds the key to gaining insight into our day-to-day observations. Among the vast spectrum of time series analysis, time series classification offers the unique opportunity to classify the sequences into their respective categories for the sake of automated detection.
View Article and Find Full Text PDFAnal Chem
January 2025
Department of Applied Chemistry, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.
The integration of barcode technology with smartphones on paper-based analytical devices (PADs) presents a promising approach to bridging manual detection with digital interpretation and data storage. However, previous studies of 1D barcode approaches have been limited to providing only a "yes/no" response for analyte detection. Herein, a method of using barcode readout for semiquantitative signal detection on PADs has been achieved through the integration of barcode technology with a distance-based measurement concept on PADs.
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