The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.
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http://dx.doi.org/10.3390/s120303605 | DOI Listing |
Nat Sci Sleep
December 2024
Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China.
Purpose: Sleep apnea (SA), associated with absent neural output, is characterised by recurrent episodes of hypoxemia and repeated arousals during sleep, resulting in decreased sleep quality and various health complications. Mitochondrial DNA copy number (mtDNA-CN), an easily accessible biomarker in blood, reflects mitochondrial function. However, the causal relationship between mtDNA-CN and SA remains unclear.
View Article and Find Full Text PDFData Brief
December 2024
Department of Physiology and Membrane Biology, Tupper Hall, Rm 4327, 1275 Med Sciences Drive, University of California, Davis, CA 95616, United States.
Generalized Additive Models for Location, Scale, and Shape (GAMLSS) are widely used for developing spirometric reference equations but are often complex, requiring additional spline tables. This study explores the potential of Segmented (piecewise) Linear Regression as an alternative, comparing its predictive accuracy to GAMLSS and examining the agreement between the two methods. Spirometry data from nearly 16,600 patients, deemed Grade "A" and "B" acceptable from the NHANES 2007-2012 dataset, was analyzed.
View Article and Find Full Text PDFFluids Barriers CNS
December 2024
Department of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Miyagi, Japan.
Background: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is one of the neuroradiological characteristics of idiopathic normal pressure hydrocephalus (iNPH), which makes statistical analyses of brain images difficult. This study aimed to develop and validate methods of accurate brain segmentation and spatial normalisation in patients with DESH by using the Computational Anatomy Toolbox (CAT12).
Methods: Two hundred ninety-eight iNPH patients with DESH and 25 healthy controls (HCs) who underwent cranial MRI were enrolled in this study.
BMC Med Res Methodol
December 2024
Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Background: Graft loss is a major health concern for kidney transplant (KTx) recipients. It is of clinical interest to develop a prognostic model for both graft function, quantified by estimated glomerular filtration rate (eGFR), and the risk of graft failure. Additionally, the model should be dynamic in the sense that it adapts to accumulating longitudinal information, including time-varying at-risk population, predictor-outcome association, and clinical history.
View Article and Find Full Text PDFBMC Med Res Methodol
December 2024
Institute for Health Services Research and Clinical Epidemiology, Philipps-Universität Marburg, Karl-von-Frisch-Strasse 4, Marburg, 35043, Germany.
Background: Health services research often relies on secondary data, necessitating quality checks for completeness, validity, and potential errors before use. Various methods address implausible data, including data elimination, statistical estimation, or value substitution from the same or another dataset. This study presents an internal validation process of a secondary dataset used to investigate hospital compliance with minimum caseload requirements (MCR) in Germany.
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