Interval Parameters Research Articles

Forces Between Pair of Rings Made of a Magnetically Soft Ferromagnet in an Axial External Field

Purpose. Demonstration of the way to enhance the attraction force between coaxial rings made of a magnetically soft ferromagnet by way of profiling their edges facing each other.Methods. In the framework of magnetostatics numerical calculation is carried out for a system of two coaxial rings made of a magnetically soft ferromagnet under conditions when the system is subjected to a uniform magnetic field directed along the rings’ axis. Such a design prototypes a soft gripper for robotics. On the basis of the found out field distribution, the force of mutual attraction is evaluated. Using a particular example, the advantages of a system where the ring edges facing each other are profiled (tapered) are considered in comparison with the its analog where the rings have rectangular edges.Results. In is shown that tapering of the edges enables one to acquire a notable gain with respect to the attraction strength. The dependences of the force of the force are calculated on the inter-ring distance and on extent of tapering of the edges: replacement of the rectangular shape by a trapezoid one. It is found that the advantages of the tapered system take place only in certain intervals of the respective parameters. For example, tapering entails an order of magnitude enhancement provided that inter-ring gap is sufficiently narrow (much smaller than the thickness of the ring wall) but it loses to a standard system all its advantage when the rings are separated by a distance of the order of their radius or greater. The dependence of the attraction force on the extent of tapering (the ratio of the upper and lower bases of the trapezium) is non-monotonic. Under a weak tapering, this function grows rapidly, then it passes a maximum (its position depends on the magnetic susceptibility of the ring material) and afterwards goes down when the profile of the edge approaches triangular shape.Conclusions. The obtained results enable one to optimize the force interaction in the system under consideration. It is worth noting that the profiling not only augments the mutual attraction force but as well reduces that amount of magnetic material required for the construction.

Dynamics of chaotic and hyperchaotic modified nonlinear Schrödinger equations and their compound synchronization

We present in this paper four versions of chaotic and hyperchaotic modified nonlinear Schrödinger equations (MNSEs). These versions are hyperchaotic integer order, hyperchaotic commensurate fractional order, chaotic non-commensurate fractional order, and chaotic distributed order MNSEs. These models are regarded as extensions of previous models found in literature. We also studied their dynamics which include symmetry, stability, chaotic and hyperchaotic solutions. The sufficient condition is stated as a theorem to study the existence and uniqueness of the solutions of hyperchaotic integer order MNSE. We state and prove another theorem to test the dependence of the solution of hyperchaotic integer order MNSE on initial conditions. By similar way, we can introduce the previous two theorems for the other versions of MNSEs. The Runge-Kutta of the order 4, the Predictor-Corrector and the modified spectral numerical methods are used to evaluate the numerical solutions for integer, fractional and distributed orders MNSEs, respectively. We calculate numerically using the Lyapunov exponents the intervals of parameters of the purposed models at which hyperchaotic, chaotic and stable solutions are exist. The MNSEs have an important role in many fields of science and technology, such as nonlinear optics, electromagnetic theory, superconductivity, chemical and biological dynamics, lasers and plasmas. The compound synchronization for these chaotic and hyperchaotic models is investigated. We state its scheme using the tracking control technique among three integer commensurate and non-commensurate orders as the derive models and one distributed order as a slave model. We presented and proved a theorem that provides us with the analytical formula for the control functions which are required to achieve compound synchronization. The analytical results are supported by numerical calculations and agreement is found.

ASCD: Automatic sensing and control device for crop irrigation scheduling

Traditional agricultural irrigation systems suffer from wasting a lot of water allocated for irrigation through evaporation and drainage. To address water waste and increase crop productivity, irrigation scheduling is used, as irrigation scheduling depends on four elements: soil moisture, soil characteristics, weather conditions, and plant type. This paper proposes a new design for monitoring agricultural conditions and controlling the amount of soil moisture by determining the required irrigation water ratios and the ideal time period for irrigating crops. An intelligent control and monitoring algorithm was created using experimental data for a wide range of plants (for soil moisture from 21 to 80 kPa), where plants were classified into three groups according to their common irrigation starting point. Based on the proposed plant classification, three models were provided, where irrigation ratios as the required parameter, soil moisture, plant type, and time interval as input parameters. This algorithm was used to program a custom-made automatic sensor and control device (ASCD). The ASCD is equipped with two input ports to communicate with two types of soil moisture sensors (a resistive sensor and a capacitive sensor) and with three output ports to drive three types of electronic irrigation valves. The ASCD can read from one sensor and drive one electronic valve at a time, the choice of which is made by the farmer. ASCD based the new algorithm showed high accuracy compared to a number of experimental results. The average absolute relative deviation (AAPD) of the new models and experimental data is 5.46 %. The application of the new algorithm shows a reduction in the amount of water used for crop irrigation during the day versus irrigation at night. On the other hand, ASCD has proven its success in sensing and controlling, and it works automatically and independently.

Finite-time interval stabilization for time-varying stochastic delayed systems via interval matrix method by piecewise controllers

This paper presents a comprehensive study addressing the problem of finite-time interval stabilization (FTIS) for two distinct types of systems: linear time-invariant stochastic delayed systems (LTISDSs) and linear time-varying stochastic delayed systems (LTVSDSs). To begin, the definition of FTIS is established, which is based on employing piecewise state feedback controllers. Subsequently, a time-varying Lyapunov-Krasovskii functional (LKF) is proposed and a novel optimization algorithm is designed to address the challenge of FTIS for LTISDSs. Additionally, this paper investigates the equivalence of LTVSDSs to uncertain stochastic delayed systems with interval parameters, represented as a series of convex combinations. Notably, both the optimization algorithm and the linear matrix inequalities (LMIs) technique are employed to establish sufficient conditions for achieving FTIS in LTVSDSs. Furthermore, when compared to traditional state feedback controllers, the piecewise controllers not only enhance the precision of system control but also lead to reduced control gains and fewer control effort requirements. Finally, the findings are substantiated through the presentation of two numerical examples, providing practical validation for the proposed methodologies and their effectiveness.

Reference intervals of complete blood count parameters in the adult western Sudanese population

BackgroundA complete blood count (CBC) analysis is one of the most common conventional blood tests that physicians frequently prescribe.The objectiveof this study was to determine the reference intervals (RIs) of CBC parameters in the population of healthy adults living in the western Sudan region.MethodsA cross-sectional study of healthy people residing in the western area of Sudan was carried out. We assessed the CBC RIs in samples taken from 153 individuals using an automated haematology analyser (Sysmex KX-21) and a modified Box–Cox transformation procedure to transform the data into a Gaussian distribution after eliminating outliers using the Dixon method. IBM SPSS Statistics version 25 was used to analyse the data, and t tests were employed to examine variations in the mean CBC parameters according to sex and age. P was considered significant at ≤ 0.05.ResultsBeyond all the other measured values, the only CBC parameters that significantly differed between the sexes were haemoglobin (HGB) and white blood cell (WBC) counts. Women were found to experience more WBC counts than men did. However, they have less HGB RIs.The male participants in our study exhibited lower WBC count RIs, a significantly lower limit, and a greater upper limit of platelet RIs than did the individuals from other nations.ConclusionsCompared with males, females had higher platelet and WBC counts and lower HGB.

Verification of bile acid determination method and establishing reference intervals for biochemical and haematological parameters in third-trimester pregnant women.

The aims of this study were to verify the bile acids (BA) method and to establish reference intervals (RIs) for bile acids (BA) and biochemical and haematological parameters in Croatian pregnant women. BA spectrophotometric method verification was performed on Siemens Atellica Solution CH 930 automated analyser using Sentinel reagent. Stability, precision, trueness, linearity, and RIs, as well as lipemia interference were tested according to CLSI guidelines. BA, biochemical, and haematological parameters were measured in serum (BA, biochemical) and whole blood (haematological) samples of fasting healthy third-trimester pregnant women from Croatia (n=121). The establishment of the RIs was done a priori according to the CLSI EP28-A3C:2010 guideline. Selected reference individuals' data were analysed using parametric, non-parametric, and robust methods. Stability study showed that BA are stable in serum samples for 2days at 20 °C, 14days at 4-8 °C, and 22days at-20 °C. The precision study and adult RIs verification met the criteria. Linearity was verified for the concentration range of 3.5-172.1 μmol/L whereas the lipemia interference test showed a positive bias (%) in BA concentration. The determined reference limits generally exhibited better precision for haematological parameters, being lower than the upper recommended value 0.2, unlike biochemical parameters. Haematological parameters showed notable differences between pregnant and non-pregnant women, while many biochemical parameters' RIs remained similar. Only ALT and GGT showed lower non-comparable RI upper limits in the population pregnant women. Spectrophotometric BA method showed satisfactory performance and all examined parameters were within the set criteria. Moreover, RIs for key biochemical and haematological parameters, including BAs, have been established for the first time in the population of Croatian pregnant women.

Freund – Nambu cosmology with the massless scalar field

Within the framework of the generalization of Freund – Nambu scalar-tensor theory of gravity, a massless scalar field is considered, the source of which is the trace of its own energy-momentum tensor. For the cosmological problem, numerical solutions of field equations were obtained, with the help of which the dependencies of the Hubble parameter and the photometric distance to the observed sources on red-shift were constructed. To the consistency of the models with observational data, contours of confidence intervals for model parameters were constructed.

Reference Intervals for Research Parameters of Reticulocyte Hemoglobin and Platelet Clumps in Healthy Korean Adults

Reference Intervals for Research Parameters of Reticulocyte Hemoglobin and Platelet Clumps in Healthy Korean Adults

On Sample Size Needed for Block Bootstrap Confidence Intervals to Have Desired Coverage Rates

Block bootstrap is widely used in constructing confidence intervals for parameters estimated from stationary time series. Theoretically, the method should provide valid confidence intervals as the length of the time series goes to infinity. In practice, however, it is necessary to know how large of a finite sample is required for block bootstrap confidence intervals to work well. This study aims to answer this question in a simple simulation setting where the data are generated from a first-order autoregressive process. The empirical coverage rates of several commonly used bootstrap confidence intervals for the mean, standard deviation, and the lag-1 autocorrelation coefficient are compared. A quite large sample is found necessary for the intervals to have the right coverage rates even when estimating a simple parameter like the mean. Some block bootstrap methods could fail when estimating the lag-1 autocorrelation. It is surprising that the coverage property even deteriorates as the sample size increases with some commonly used block bootstrap confidence intervals including the percentile intervals and bias-corrected intervals. KEYWORDS: Autocorrelation; Bias-Correction; Centering; Dependent Data; Percentile; Resampling; Simulation; Time Series

Uncertainty dynamics in energy planning models: An autoregressive and Markov chain modeling approach

This paper deals with the modeling of stochastic processes in long-term multi-stage energy planning problems when limited information is available about the distributions of such processes. Starting from simple estimates of variation intervals for uncertain parameters, such as energy demands and costs, we model the temporal correlation of these parameters through carefully constructed autoregressive (AR) models that respect the intervals defined in each period. We introduce a coefficient for “zigzag” effects in the evolution of uncertain processes, which controls the correlation across periods and also the likelihood of extreme scenarios. To preserve the convexity of the stochastic problem, we discretize the AR models associated with the cost parameters involved in the objective function by Markov chains. The resulting formulation is then solved using a Stochastic Dual Dynamic Programming (SDDP) algorithm available in the literature that handles finite-state Markov chains. Our numerical experiments, carried out on the Swiss energy system, show a very desirable adaptation strategy of investment decisions to uncertainty scenarios, a behavior that is not observed when the temporal correlation is ignored. Moreover, the solutions lead to better out-of-sample cost performances, especially on extreme scenario realizations, than the non-correlated ones which usually result in overcapacities to protect against high, but unlikely, parameter variations over time.

Ultrasound based technology for removal of scale from downhole production tubing, an experimental verification

Deposition and blockages due to scale formation inside the production tubing are the most common problems experienced during the production of oil and gas, and this significantly leads to a decline in the production rate. Progressive scale formation limits production which subsequently leads to abandonment of the well. There is a great cost attached to preventing the occurrence and remediation of scales. Chemical and mechanical techniques for scale removal in production tubing have drawbacks like environmental concerns, equipment damage, and incomplete removal of stubborn scale. In contrast, ultrasound-based methods offer potential benefits such as non-destructiveness, enhanced efficiency, reduced chemical usage, and increased safety for workers. Despite the extensive research about the application of ultrasound to improve oil recovery, there remains a significant gap in the comprehensive exploration of optimum ultrasound parameters (frequency, power, radiation time, interval time, and location) for the removal of in-situ built scales in a simulated production tubing under different flow rates. This study addresses this gap by investigating the impact of ultrasound parameters on its performance for removal of calcium carbonate (CaCO3) and gypsum scales in a simulated production tubing system under different flow rate (100% and 50%). The ultrasound parameters include frequency (in the range of 20 kHz–120 kHz), power (50 W and 100 W), operation time, and location (externally attached and inserted into the production tubing).Initial tests revealed that adjusting the operating frequency improves the impedance matching, resulting in enhanced scale removal. The experiments also explored the influence of flow rate on scale removal, showing a general increase in removal with higher flow rates, specially at operating frequencies 20 kHz and 28 kHz. It was also demonstrated that the higher frequencies of 40 kHz, 68 kHz, and 120 kHz exhibit limited removal efficiency. The effectiveness of scale removal exhibited nonlinear variation over time, with the 28 kHz, 100 W transducer demonstrating the most significant improvement.In-pipe ultrasonic rod, operating at a constant frequency of 26 kHz, was employed to assess its performance for scale removal. Pulsed treatment was introduced to manage rod heating issues. Results demonstrated that both interval times and flow rates influenced CaCO3 removal, with shorter intervals yielding better results. The ultrasonic rod's efficacy was also observed in removing gypsum scale layers, suggesting potential applications in treating scales with various strengths. The results of this study can contribute to a better understanding of how the frequency, power, operating time and interval, and flow rate influence ultrasonic scale removal. The experimental findings provide valuable insights in optimizing practical applications for removal of scales from production tubing.

Profile likelihoods for parameters in trans-Gaussian geostatistical models

Profile likelihoods are rarely used in geostatistical models due to the computational burden imposed by repeated decompositions of large variance matrices. Accounting for uncertainty in covariance parameters can be highly consequential in geostatistical models as some covariance parameters are poorly identified, the problem is severe enough that the differentiability parameter of the Matern correlation function is typically treated as fixed. The problem is compounded with anisotropic spatial models as there are two additional parameters to consider. In this paper, we make the following contributions: Firstly, a methodology is created for profile likelihoods for Gaussian spatial models with Matérn family of correlation functions, including anisotropic models. This methodology adopts a novel reparameterization for generation of representative points, and uses GPUs for parallel profile likelihoods computation in software implementation. Then, we show the profile likelihood of the Matérn shape parameter is often quite flat but still identifiable, it can usually rule out very small values. Finally, simulation studies and applications on real data examples show that profile-based confidence intervals of covariance parameters and regression parameters have superior coverage to the traditional standard Wald type confidence intervals.

Analysis of Differentially Private Synthetic Data: A Measurement Error Approach

Differentially private (DP) synthetic datasets have been receiving significant attention from academia, industry, and government. However, little is known about how to perform statistical inference using DP synthetic datasets. Naive approaches that do not take into account the induced uncertainty due to the DP mechanism will result in biased estimators and invalid inferences. In this paper, we present a class of maximum likelihood estimator (MLE)-based easy-to-implement bias-corrected DP estimators with valid asymptotic confidence intervals (CI) for parameters in regression settings, by establishing the connection between additive DP mechanisms and measurement error models. Our simulation shows that our estimator has comparable performance to the widely used sufficient statistic perturbation (SSP) algorithm in some scenarios but with the advantage of releasing a synthetic dataset and obtaining statistically valid asymptotic CIs, which can achieve better coverage when compared to the naive CIs obtained by ignoring the DP mechanism.

Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China

The rapid advancement of remote sensing technology has given rise to numerous global- and regional-scale medium- to high-resolution land cover (LC) datasets, making significant contributions to the exploration of worldwide environmental shifts and the sustainable governance of natural resources. Nonetheless, owing to the inherent uncertainties embedded within remote sensing imagery, LC datasets inevitably exhibit inaccuracies. In this study, a local accuracy assessment of LC datasets in Southwest China was conducted. The datasets utilized in our analysis include ESA WorldCover, CLCD, Esri Land Cover, CRLC, FROM-GLC10, GLC_FCS30, GlobeLand30, and SinoLC-1. This study employed a sampling approach that combines proportional allocation and stratified random sampling (SRS) to gather sample points and compute confusion matrices to validate eight LC products. The local accuracy of the eight LC maps differs significantly from the overall accuracy provided by the original authors in Southwest China. ESA WorldCover and CLCD demonstrate higher local accuracy than other products in Southwest China, with their overall accuracy (OA) values being 87.1% and 85.48%, respectively. Simultaneously, we computed the area for each LC map based on categories, quantifying uncertainty through the reporting of confidence intervals for both accuracy and area parameters. This study aims to validate and compare eight LC datasets and assess precision and area of diverse spatial resolution datasets for mapping and monitoring across Southwest China.

Numerical and data-driven uncertainty quantification of process parameters on clinching joint geometries

Clinching is a prevalent mechanical joining method involving clamping and locking two sheet work pieces using a punch and die. Numerical simulation offers a cost-effective alternative to time-consuming experiments for design. Our study employs an ABAQUS explicit dynamic model with remeshing to accurately replicate clinching joint geometry. However, the challenge of hard-to-measure parameters and the investigation of these parameters is limited leading to different simulation results compared to the millimeters-scale experiments. To address this, we apply PyMC3-based uncertainty quantification (UQ) to explore the material parameter effects on clinching dimensions. Our data-driven Bayesian inference models highlight friction and high-plastic-strain flow stress as significant geometry influencers. We propose estimating challenging-to-measure parameters from experiments, leveraging UQ for confident parameter intervals. Through PyMC3, our research offers insights into parameter impact on clinching dimensions, enhancing numerical simulations for process design optimization.

Inclusion of higher-order terms in the border-collision normal form: Persistence of chaos and applications to power converters

The dynamics near a border-collision bifurcation are approximated to leading order by a continuous, piecewise-linear map. The purpose of this paper is to consider the higher-order terms that are neglected when forming this approximation. For two-dimensional maps we establish conditions under which a chaotic attractor created in a border-collision bifurcation persists for an open interval of parameters beyond the bifurcation. We apply the results to a prototypical power converter model to prove the model exhibits robust chaos.

Confidence Intervals for Parameters of Unobserved Events

Consider a finite sample from an unknown distribution over a countable alphabet. Unobserved events are alphabet symbols which do not appear in the sample. Estimating the probabilities of unobserved events is a basic problem in statistics and related fields, which was extensively studied in the context of point estimation. In this work we introduce a novel interval estimation scheme for unobserved events. Our proposed framework applies selective inference, as we construct confidence intervals (CIs) for the desired set of parameters. Interestingly, we show that obtained CIs are dimension-free, as they do not grow with the alphabet size. Further, we show that these CIs are (almost) tight, in the sense that they cannot be further improved without violating the prescribed coverage rate. We demonstrate the performance of our proposed scheme in synthetic and real-world experiments, showing a significant improvement over the alternatives. Finally, we apply our proposed scheme to large alphabet modeling. We introduce a novel simultaneous CI scheme for large alphabet distributions which outperforms currently known methods while maintaining the prescribed coverage rate. Supplementary materials for this article are available online including a standardized description of the materials available for reproducing the work.

Numerical investigation of flow patterns in cuttings transport for extended-reach horizontal wells with rotation drillpipe

During the drilling process of extended-reach horizontal wells, the formation of the cuttings bed at the bottom of the wellbore is prone to cause drilling sticking and pump accidents. A coupled method of Computational Fluid Dynamics and Discrete Element Method (CFD-DEM) is used here to study the flow patterns and transition of cuttings transport. Firstly, the model is validated with experimental results, which shows a good agreement. Then, the impact of the rotation speed, eccentricity, and conveying velocity on cuttings flow pattern are analyze. The total Reynolds number is introduced here to established a curve with dimensionless pressure drop, which divides the parameter interval of each flow pattern, and the change rule of cuttings flow pattern is also revealed. This study will establish a theoretical foundation for enhancing borehole cleaning efficiency and hold practical significance in guiding the drilling field construction of extended-reach wells.

Simple Lévy α-Stable Model Analysis of Elastic pp and pp¯ Low-|t| Data from SPS to LHC Energies

A simple Lévy α-stable (SL) model is used to describe the data on elastic pp and pp¯ scattering at low-|t| from SPS energies up to LHC energies. The SL model is demonstrated to describe the data with a strong non-exponential feature in a statistically acceptable manner. The energy dependence of the parameters of the model is determined and analyzed. The Lévy α parameter of the model has an energy-independent value of 1.959 ± 0.002 following from the strong non-exponential behavior of the data. We strengthen the conclusion that the discrepancy between TOTEM and ATLAS elastic pp differential cross section measurements arises only in the normalization and not in the shape of the distribution of the data as a function of t. We find that the slope parameter has different values for pp and pp¯ elastic scattering at LHC energies. This may be the effect of the odderon exchange or the jump in the energy dependence of the slope parameter in the energy interval 3 GeV ≲s≲ 4 GeV.

Serum Biochemistry Parameters of the Endangered Miranda's Donkey Breed: Reference Intervals and the Influence of Gender and Age.

Miranda's donkey is an endangered, autochthone breed from Northern Portugal. Understanding the physiological and pathological conditions of Miranda's donkey is crucial for the conservation of the breed. Our study aimed to establish reference intervals (RIs) for blood biochemistry parameters and to evaluate the influence of gender and age on these parameters. Blood samples from 75 clinically healthy animals were analyzed for 21 blood biochemistry parameters using Respons® 920 and Start® 4-Diagnostica-Stago. RIs were calculated according to the ASVCP guidelines, utilizing Reference Advisor software V. 2.1 and the statistical program SPSS version 29 to analyze the effects of gender and age. Significant gender-related differences (p < 0.05) were observed in cholesterol, chlorine, creatinine (CREA), glucose (GLU), sodium, and triglycerides (with higher values in females) and in aspartate aminotransferase, creatine phosphokinase (CK), gamma-glutamyl transferase, potassium, magnesium (Mg), and urea (with higher values in males). Age-related differences (p < 0.05) were noted for alkaline phosphatase, CK, fibrinogen, GLU, and phosphorus (higher in young animals) and for globulin, Mg, and total protein (higher in adults). The RIs described here are invaluable for assessing and monitoring the health status of individual animals and herds. Our study highlights the importance of considering gender and age in the interpretation of biochemical parameters, providing critical insights for the conservation and management of this endangered breed.