A precision resistance measurement method based on synchronous sampling is proposed to enable accurate resistance measurement under low-current testing conditions. This method utilizes a single current source input, connecting the standard resistor a...
Realizing coherent sampling is one of the major bottlenecks in high-precision ADC spectrum testing. In spectrum analysis, if coherent sampling is not implemented, spectral leakage will result, which in turn leads to inaccurate test results. In this p...
Biologists commonly use standard sampling protocols to ensure that data are comparable spatiotemporally. Data also need to be precise to allow for statistically meaningful comparisons. However, the effort needed to precisely sample desert fishes is u...
The accurate quantification of microplastics (MPs) in aquatic environments remains challenging due to the heterogeneous distribution of MPs in different environments, making representative sampling difficult, as well as methodological variabilities i...
Ground control point (GCP) selection is a critical step in the automated high-precision geometric correction of remote sensing imagery. While the quantity, quality, and distribution of GCPs are three factors which may affect the accuracy of geometric...
Expected shortfall (ES) is a tail functional whose estimation precision is governed by the effective tail sample size
Surface roughness is one of the main bases for measuring the surface quality of machined parts. A large amount of training data can effectively improve model prediction accuracy. However, obtaining a large and complete surface roughness sample datase...
The sampling effect of the imaging acquisition device is an integration of the input signal within the pixel, resulting in an additional error in the pixel value. Additionally, a sampler with asymmetric intra-pixel quantum efficiency leads to positio...
Precision agriculture techniques contribute to optimizing the use of agricultural inputs, as they consider the spatial and temporal variability in the production factors. Prescription maps of limestone and fertilizers at variable rates (VRA) can be g...
Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash features. Some of these systems are constrained by their long setup time, positioning requirements and co...
In the USA, agriculture is the largest consumer of freshwater resources, and precision irrigation (PI) can conserve water significantly while maintaining crop yield. Current approaches to soil volumetric water content (VWC) mapping for PI rely on ins...
Finding new valuable sampling points and making these points better distributed in the design space is the key to determining the approximate effect of Kriging. To this end, a high-precision Kriging modeling method based on hybrid sampling criteria (...
Estimating the amplitude of a sinewave from a set of data points is a common procedure in various applications. This is typically achieved using a least squares method that provides closed-form estimators. The sampling process itself is often affecte...
In this work, we present a 3D single-particle tracking system that can apply tailored sampling patterns to selectively extract photons that yield the most information for particle localization. We demonstrate that off-center sampling at locations pre...
A high frequency periodic signal measurement system based on equivalent sampling method is developed. A high-speed sampling voltage tracking circuit, the core component of the system, is described in detail. The circuit can transform the amplitude co...
Scirtothrips dorsalis Hood is an invasive and foliar pest of Florida blueberry that reduces plant growth by feeding on new leaf growth. A sampling plan is needed to make informed control decisions for S. dorsalis in blueberry. Fourteen blueberry fiel...
Viticulture is facing growing economic and environmental pressures that demand a transition toward intelligent and autonomous crop management systems. Phytopathologies remain one of the most critical threats, causing substantial yield losses and redu...
In order to improve the accuracy of pipe burst detection in water distribution networks (WDNs), a novel small sample diagnosis method (SSDM) based on the head loss ratio (HLR) method and deep transfer learning (DTL) method has been proposed. In this...
Locational errors and sampling bias may produce unrepresentative species distribution models. To decompose the influence of errors, I modeled species distributions of 31 mammal species from georeferenced records and random samples from range maps, wi...
The “Little MonSta” benthic lander array consists of 8 ROV-deployable (remotely operated vehicle) instrumented lander platforms for monitoring physical and chemical oceanographic properties and particle sampling developed as part of the MMMonKey_Pro...
Adequately sampling benthic cover in marine ecosystems is a challenge with most methods encompassing only a small portion of the area for which cover is estimated. Recent advances in photogrammetric techniques are providing opportunity to map expansi...
The estimation of the number of samples required for reliably monitoring lakes’ benthic macroinvertebrates is difficult due to the natural variability and cost and time constraints. To determine a statistically robust and effective sampling design, w...
Synchrosqueezing transform (SST) can effectively improve time-frequency precision and resolution by squeezing time-frequency spectra via instantaneous frequencies, and it has been applied in many diverse disciplines; however, the precision of estimat...
Digital morphology (DM) analyzers are widely applied in clinical practice. It is necessary to evaluate performances of DM analyzers by focusing on leukopenic samples. We evaluated the analytical performance, including precision, of a Sysmex DI-60 sys...
The a priori procedure was designed as a pre-data procedure whereby researchers could find the sample sizes necessary to ensure that sample statistics to be obtained are within particular distances of corresponding population parameters with known pr...
In addressing the optimal motion planning issue for multi-arm rock drilling robots, this paper introduces a high-precision motion planning method based on Multi-Strategy Sampling RRT* (MSS-RRT*). A dual Jacobi iterative inverse solution method, coupl...
Appropriate sampling, sample preparation, choosing the right analytical instrument, analytical methodology, and adopting proper data generation protocols are essential for generating data of the required quality for both basic and applied geochemical...
The development of precision grass measurement technologies is of vital importance to securing the future sustainability of pasture-based livestock production systems. There is potential to increase grassland production in a sustainable manner by ach...
Soil sampling constitutes a fundamental process in agriculture, enabling precise soil analysis and optimal fertilization. The automated selection of accurate soil sampling locations representative of a given field is critical for informed soil treatm...
Coffee production has become increasingly technified in order to optimize the use of inputs and the sustainable use of natural resources. In this context, one way that farmers are investing in their coffee plantations is in the use of precision agric...
Precision agriculture hinges on accurate soil condition data obtained through soil testing across the field, which is a foundational step for subsequent processes. Soil testing is expensive, and reducing the number of samples is an important task. On...
Soil mapping plays a crucial role in optimizing agricultural production by providing spatially explicit information on soil types and properties, which supports decision-making in precision fertilization, irrigation, and crop selection. Traditional s...
Laser ablation combined with inductively coupled plasma mass spectrometry for the analysis of trace elements in specially prepared glass beads is adapted to silicate rocks of unusual compositions. The modified technique is applied to standard samples...
Near-seafloor acoustic field characteristics are essential prior knowledge for near-seafloor underwater acoustic engineering. Scholte waves are a crucial component of the near-seafloor acoustic fields. These fields, when considering Scholte waves, ar...
The Net Promoter Score (NPS) is a widely used metric for customer loyalty in business. However, the current theoretical gaps in the literature suggest practical refinements for real-world applications. In this simulation study, we use an unbiased est...
Underground coal mines belong to the GNSS-denied environment, and the Strapdown Inertial Navigation System (SINS) has a significant advantage in the precise positioning of equipment in this environment because of its operation without requiring inter...
This paper presents an autonomous robotic system, an unmanned ground vehicle (UGV), for in-field soil sampling and analysis of nitrates. Compared to standard methods of soil analysis it has several advantages: each sample is individually analyzed com...
The handling of biomaterials is crucial for precision medicine in advanced-stage lung patients with only cytology or small biopsies available. The main purpose of the study was to evaluate the quantity and quality of nucleic acids extracted from mixe...
Soil-sample collection and strategy are costly and time-consuming endeavors, mainly when the goal is in-field variation mapping that usually requires dense sampling. This study developed and tested a streamlined soil mapping methodology, applicable a...
Pancreatic cancer is the most lethal solid malignancy, and the number of patients with pancreatic cancer is increasing. Systemic chemotherapies are often ineffective for such patients, and there is an urgent need for personalized medicine. Unlike oth...
Gaussian graphical models have been widely used to measure the association networks for high-dimensional data; however, most existing methods assume fully observed data. In practice, missing values are inevitable in high-dimensional data and should b...
Geosynchronous (GEO) spaceborne–airborne very high-frequency ultra-wideband bistatic synthetic aperture radar (VHF UWB BiSAR) can conduct high-resolution and wide-swath imaging for ocean scenes. However, GEO spaceborne–airborne VHF UWB Bi...
Background/Objectives: The quality of clinical studies is largely determined by the bioanalytical methods used for testing study samples. Rigorous assay validation following defined criteria, for example, the European Medicines Agency guideline for b...
This study assessed whether stratifying agricultural areas into macro- and micro-variability regions allows targeted sampling to better capture soil attribute variability, thus improving digital soil maps compared to regular grid sampling. Allocating...
In this study, an advanced method for apricot tree disease detection is proposed that integrates deep learning technologies with various data augmentation strategies to significantly enhance the accuracy and efficiency of disease detection. A compreh...
The characterization of soil attribute variability often requires dense sampling grids, which can be economically unfeasible. A possible solution is to perform targeted sampling based on previously collected data. The objective of this research was t...
The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ea...
Size exclusion chromatography with total organic carbon detection (HPSEC-TOC) is a widely employed technique for characterizing aquatic natural organic matter (NOM) into high, medium, and low molecular weight fractions. This study validates the suita...
Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost. In this study, the potential of UAV imagery was evaluated to quantify lodging percentage and lodging severity o...
Few-Shot Object Detection (FSOD) aims to identify new object categories with a limited amount of labeled data, which holds broad application prospects in real-life scenarios. Previous approaches usually ignore attention to critical information, which...
of 251