Establishing minimum clinically important difference values for the Patient-Reported Outcomes Measurement Information System Physical Function, hip disability and osteoarthritis outcome score for joint reconstruction, and knee injury and osteoarthritis out

AIM To establish minimum clinically important difference(MCID) for measurements in an orthopaedic patient population with joint disorders.METHODS Adult patients aged 18 years and older seeking care for joint conditions at an orthopaedic clinic took the Patient-Reported Outcomes Measurement Information System Physical Function(PROMIS~? PF) computerized adaptive test(CAT), hip disability and osteoarthritis outcome score for joint reconstruction(HOOS JR), and the knee injury and osteoarthritis outcome score for joint reconstruction(KOOS JR) from February 2014 to April 2017. MCIDs were calculated using anchorbased and distribution-based methods. Patient reports of meaningful change in function since their first clinic encounter were used as an anchor.RESULTS There were 2226 patients who participated with a mean age of 61.16(SD = 12.84) years, 41.6% male, and 89.7% Caucasian. Mean change ranged from 7.29 to 8.41 for the PROMIS~? PF CAT, from 14.81 to 19.68 for the HOOS JR, and from 14.51 to 18.85 for the KOOS JR. ROC cut-offs ranged from 1.97-8.18 for the PF CAT, 6.33-43.36 for the HOOS JR, and 2.21-8.16 for the KOOS JR. Distribution-based methods estimated MCID values ranging from 2.45 to 21.55 for the PROMIS~? PF CAT; from 3.90 to 43.61 for the HOOS JR, and from 3.98 to 40.67 for the KOOS JR. The median MCID value in the range was similar to the mean change score for each measure and was 7.9 for the PF CAT, 18.0 for the HOOS JR, and 15.1 for the KOOS JR.CONCLUSION This is the first comprehensive study providing a wide range of MCIDs for the PROMIS? PF, HOOS JR, and KOOS JR in orthopaedic patients with joint ailments.

Semantic model and optimization of creative processes at mathematical knowledge formation

The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.

Reservoir Porosity Measurement Uncertainty and its Influence on Shale Gas Resource Assessment

Reservoir porosity is a critical parameter for the process of unconventional oil and gas resources assessment. It is difficult to determine the porosity of a gas shale reservoir, and any large deviation will directly reduce the credibility of any shale gas resources evaluation. However, there is no quantitative explanation for the accuracy of porosity measurement. In this paper, measurement uncertainty, an internationally recognized index, was used to evaluate the results of porosity measurement of gas shale plugs, and its impact on the credibility of shale gas resources assessment was determined. The following conclusions are drawn:(1) the measurement uncertainty of porosity of a shale plug is 1.76%–3.12% using current measurement methods, the upper end of which is too large to be acceptable. It is suggested that the measurement uncertainty should be factored into the standard helium gas injection porosity determination experiment, and the uncertainty should be less than 2.00% when using a high-precision pressure gauge;(2) in order to reduce the risk for exploration and decision-making, attention should be paid to the large uncertainty(30% at least) of shale gas resource assessment results, sometimes with corrections being made based on the practical considerations;(3) a pressure gauge with an accuracy of 0.25% of the full scal cannot meet the requirements of porosity measurement, and a high-precision plug cutting method or high-precision bulk volume measurement method such as one using 3 D scanning, is recommended to effectively reduce porosity uncertainty;(4) the method and process for evaluating the measurement uncertainty of gas shale porosity could also be referred for assessment of experimental quality by other laboratories.

A New Version of Special Relativity Absorbed the Uncertainty Principle: Its Content as Well as Application and Experimental Test

Based on the space spherical symmetry of 3-dimensional and the translational symmetry of time and the uncertainty principle, a 4-dimensional space-time cylinder model of quarks and leptons is established. With this model, equations of the special relativity can be extended more perfectly, thereby achieving a unity of the special relativity and quantum mechanics in deeper level. New equations can not only interpret issues explained by old equations but also solve several important pending problems. For example, a formula to strictly calculate the coefficient ξ of Lorentz invariance violation (LIV) is derived, to above 4 × 1019 eV UHECR protons the calculated |ξ| -30, although there is the LIV effect it is too weak to change the GZK cutoff, which is consistent with observations of HiRes and Auger;Also, a relation formula between the Hubble constant and several basic constants is derived, thus theoretically calculated H0 = 70.937 km·s-1·Mpc-1, which is well consistent with the final observation result of HST Key Project. In addition, an unusual effect predicted by new equations can be experimentally tested in the electron storage ring;a preliminary experiment result has hinted its signs of existence.

The Evaluation of Measurement Uncertainty and Its Application in the Vacuum Pressure Measurement

In order to accurately measure the pressure and the pressure difference between two points in the vacuum chamber, a large number of experimental data were used to research the performance of the three capacitance diaphragm gauge and analysis the main influences of the uncertainly degree of pressure in the process. In this paper, three kind of uncertainty, such as the single uncertainty, the synthesis uncertainty and the expanded uncertainty of the three capacitance diaphragm gauges are introduced in detail in pressure measurement. The results show that the performance difference of capacitance diaphragm gauge can be very influential to the accuracy of the pressure difference measurement and the uncertainty of different pressure can be very influential to pressure measurement. That for accurately measuring pressure and pressure difference has certain reference significance.

Calculation of Measurement Uncertainty for Stiffness Modulus of Asphalt Mixture

Asphalt mixture is a highly heterogeneous material, which is one of the reasons for high measurements uncertainty when subjected to tests. The results of such tests are often unreliable, which may lead to making bad professional judgments. They can be avoided by carrying out reliable analyses of measurement uncertainty adequate for the research methods used and conducted before the actual research is done. This paper presents the calculation of measurements uncertainty using as an example--the determination of the stiffness modulus of the asphalt mixture, which, in turn, was accomplished using the indirect tension method. The paper also shows the employment of the basic methods of statistical analysis, such as testing two mean values and conformity tests. Essential concepts in measurements uncertainty have been compiled and the determination of the stiffness module parameters are discussed. It has been demonstrated that the biggest source of error in the stiffness modulus measuring process is the displacement measure. The aim of the research was to find the measurement uncertainty for stiffness modulus by an indirect tensile test and the presentation of examples of the used statistical methods.

Analysis and Applications of the Measurement Uncertainty in Electrical Testing

Recently, uncertainty measurement is more and more recognizable in modern data management, conformity assessment, and laboratory accreditation system because of its importance. In this paper, a set of reasonable probability explanations are introduced and an effective method is pro- posed to quantify the assessment indices for the uncertainty measurement of electrical testing laboratory. First of all, the influence from uncertainty factors during the test process is taken into account. With the use of ISO/IEC Guide 98-3 standard and probability theory, the index and model for the measurement uncertainty assessment of a laboratory is then derived. From the simulation results of safety testing, laboratory uncertainty measurement assessment activity for actual electrical appliances, and the confirmation of Monte Carlo simulation method, the appropriateness and correctness of proposed method are verified.

On the Probable Cause of the Discrepancies between Hipparcos and VLBI Pleiades Distance Measurements

It will show, a recent extension of special relativity on the grounds of a novel concept of velocity, which also predicts the speed of transversal motions on the plane of the sky to increase with enduring observation time, to fully explain the differences of the observational results of the former experiments referring to the distance of the Pleiades from Earth.

Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

A Measurement Theoretical Foundation of Statistics

It is a matter of course that Kolmogorov’s probability theory is a very useful mathematical tool for the analysis of statistics. However, this fact never means that statistics is based on Kolmogorov’s probability theory, since it is not guaranteed that mathematics and our world are connected. In order that mathematics asserts some statements concerning our world, a certain theory (so called “world view”) mediates between mathematics and our world. Recently we propose measurement theory (i.e., the theory of the quantum mechanical world view), which is characterized as the linguistic turn of quantum mechanics. In this paper, we assert that statistics is based on measurement theory. And, for example, we show, from the pure theoretical point of view (i.e., from the measurement theoretical point of view), that regression analysis can not be justified without Bayes’ theorem. This may imply that even the conventional classification of (Fisher’s) statistics and Bayesian statistics should be reconsidered.

Dose-Injury Relation as a Model for Uncertainty Propagation from Input Dose to Target Dose

We study a general framework for assessing the injury probability corresponding to an input dose quantity. In many applications, the true value of input dose may not be directly measurable. Instead, the input dose is estimated from measurable/controllable quantities via numerical simulations using assumed representative parameter values. We aim at developing a simple modeling framework for accommodating all uncertainties, including the discrepancy between the estimated input dose and the true input dose. We first interpret the widely used logistic dose-injury model as the result of dose propagation uncertainty from input dose to target dose at the active site for injury where the binary outcome is completely determined by the target dose. We specify the symmetric logistic dose-injury function using two shape parameters: the median injury dose and the 10 - 90 percentile width. We relate the two shape parameters of injury function to the mean and standard deviation of the dose propagation uncertainty. We find 1) a larger total uncertainty will spread more the dose-response function, increasing the 10 - 90 percentile width and 2) a systematic over-estimate of the input dose will shift the injury probability toward the right along the estimated input dose. This framework provides a way of revising an established injury model for a particular test population to predict the injury model for a new population with different distributions of parameters that affect the dose propagation and dose estimation. In addition to modeling dose propagation uncertainty, we propose a new 3-parameter model to include the skewness of injury function. The proposed 3-parameter function form is based on shifted log-normal distribution of dose propagation uncertainty and is approximately invariant when other uncertainties are added. The proposed 3-parameter function form provides a framework for extending skewed injury model from a test population to a target population in application.

Discrete Event System Framework for Fault Diagnosis with Measurement Inconsistency:Case Study of Rogue DHCP Attack

Fault detection and diagnosis(FDD) facilitates reliable operation of systems. Various approaches have been proposed for FDD like Analytical redundancy(AR), Principal component analysis(PCA), Discrete event system(DES) model etc., in the literature. Performance of FDD schemes greatly depends on accuracy of the sensors which measure the system parameters.Due to various reasons like faults, communication errors etc.,sensors may occasionally miss or report erroneous values of some system parameters to FDD engine, resulting in measurement inconsistency of these parameters. Schemes like AR, PCA etc.,have mechanisms to handle measurement inconsistency, however,they are computationally heavy. DES based FDD techniques are widely used because of computational simplicity, but they cannot handle measurement inconsistency efficiently. Existing DES based schemes do not use Measurement inconsistent(MI)parameters for FDD. These parameters are not permanently unmeasurable or erroneous, so ignoring them may lead to weak diagnosis. To address this issue, we propose a Measurement inconsistent discrete event system(MIDES) framework, which uses MI parameters for FDD at the instances they are measured by the sensors. Otherwise, when they are unmeasurable or erroneously reported, the MIDES invokes an estimator diagnoser that predicts the state(s) the system is expected to be in, using the subsequent parameters measured by the other sensors. The efficacy of the proposed method is illustrated using a pumpvalve system. In addition, an MIDES based intrusion detection system has been developed for detection of rogue dynamic host configuration protocol(DHCP) server attack by mapping the attack to a fault in the DES framework.

Velocity Correction and Measurement Uncertainty Analysis of Light Screen Velocity Measuring Method

Light screen velocity measuring method with unique advantages has been widely used in the velocity measurement of various moving bodies.For large air resistance and friction force which the big moving bodies are subjected to during the light screen velocity measuring,the principle of velocity correction was proposed and a velocity correction equation was derived.A light screen velocity measuring method was used to measure the velocity of big moving bodies which have complex velocity attenuation,and the better results were gained in practical tests.The measuring uncertainty after the velocity correction was calculated.

An Improved Measurement Uncertainty Calculation Method of Profile Error for Sculptured Surfaces

The current researches mainly adopt "Guide to the expression of uncertainty in measurement(GUM)" to calculate the profile error. However, GUM can only be applied in the linear models. The standard GUM is not appropriate to calculate the uncertainty of profile error because the mathematical model of profile error is strongly non-linear. An improved second-order GUM method(GUMM) is proposed to calculate the uncertainty. At the same time, the uncertainties in different coordinate axes directions are calculated as the measuring points uncertainties. In addition, the correlations between variables could not be ignored while calculating the uncertainty. A k-factor conversion method is proposed to calculate the converge factor due to the unknown and asymmetrical distribution of the output quantity. Subsequently, the adaptive Monte Carlo method(AMCM) is used to evaluate whether the second-order GUMM is better. Two practical examples are listed and the conclusion is drawn by comparing and discussing the second-order GUMM and AMCM. The results show that the difference between the improved second-order GUM and the AMCM is smaller than the difference between the standard GUM and the AMCM. The improved second-order GUMM is more precise in consideration of the nonlinear mathematical model of profile error.

Adaptive cubature Kalman filter based on variational Bayesian inference under measurement uncertainty

A novel variational Bayesian inference based on adaptive cubature Kalman filter(VBACKF)algorithm is proposed for the problem of state estimation in a target tracking system with time-varying measurement noise and random measurement losses.Firstly,the Inverse-Wishart(IW)distribution is chosen to model the covariance matrix of time-varying measurement noise in the cubature Kalman filter framework.Secondly,the Bernoulli random variable is introduced as the judgement factor of the measurement losses,and the Beta distribution is selected as the conjugate prior distribution of measurement loss probability to ensure that the posterior distribution and prior distribution have the same function form.Finally,the joint posterior probability density function of the estimated variables is approximately decoupled by the variational Bayesian inference,and the fixed-point iteration approach is used to update the estimated variables.The simulation results show that the proposed VBACKF algorithm considers the comprehensive effects of system nonlinearity,time-varying measurement noise and unknown measurement loss probability,moreover,effectively improves the accuracy of target state estimation in complex scene.

Advancement in Wide Area Monitoring Protection and Control Using PMU’s Model in MATLAB/SIMULINK

A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power systems worldwide and has led to operation of power systems closer to their stability limits and to power exchange in new patterns. These issues, as well as the on-going worldwide trend towards deregulation of the entire industry on the one hand and the increased need for accurate and better network monitoring on the other hand, force power utilities exposed to this pressure to demand new solutions for wide area monitoring, protection and control. Wide-area monitoring, protection, and control require communicating the specific-node information to a remote station but all information should be time synchronized so that to neutralize the time difference between information. It gives a complete simultaneous snap shot of the power system. The conventional system is not able to satisfy the time-synchronized requirement of power system. Phasor Measurement Unit (PMU) is enabler of time-synchronized measurement, it communicate the synchronized local information to remote station.

Measurement and Analysis of PDDs Profile and Output Factors for Small Field Sizes by cc13 and Micro-Chamber cc01

Small radiation fields are abundantly used in modern radiotherapy techniques like in IMRT and SRS. In order to commission these techniques, dosimetric data for small fields is required. The purpose of this study is to compare dosimetric measurements with two different ion chambers cc13, and cc01 for smaller fields. Dosimetric measurements are beam profile, output factor, pdds, and collimator factor. Dosimetric data is acquired in water phantom for two different photon beam energies 6 MV and 15 MV with zero gantry angle. In beam profiles cc13 chamber, measure wider penumbra as compare to cc01. And this wider measurement of penumbra occurs for smaller as well as for larger field sizes. Accumulated relative error in the measurement of penumbra for number of field sizes and 6 MV at dmax, and at 10 cm depth are 34.32% and 27.72% respectively. Accumulated relative error in the measurement of penumbra for number of field sizes and 15 MV at dmax, and at 10 cm depth are 28.49% and 23.92%. In case of output factor for smaller fields cc13 underestimates the output factor relative to cc01, with non-linear increase for smaller fields. But for larger fields, this increase in output factor is almost linear difference of two chambers is decreased. For very smaller fields × 2 cm, relative error in output factor of cc13 and cc01 is greater than 5% and rapidly increases with decreasing field size. But for lager fields, this relative error is negligible. In measurement of pdds after the buildup region difference occurs in the response of two chambers cc13 and cc01 for smaller fields. For field sizes ≤2 cm × 2 cm average cc13-cc01 at various depths 30 cm, 40 cm, 50 cm, 60 cm, 70 cm, and 80 cm is almost greater than 0.5 cm. And similarly as output factor, this difference (cc13-cc01) increases with field size decreasing.

Reduced-Order GPIO Based Dynamic Event-Triggered Tracking Control of a Networked One-DOF Link Manipulator Without Velocity Measurement

In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.

极区中层顶区域重力波谱的季节变化

使用MAP/WINE和MAC/SINE两次试验中测量的25m高分辨率水平速度数据和1km低分辨率温度数据,研究极区中层顶区域重力波谱的季节变化.温度的直接测量使计算的谱振幅和Richardson数更接近真实大气.结果显示,极区中层顶区域水平速度垂直波数谱的斜率和振幅存在相当大的变率,这些大的观测变率用各种饱和模式及普适垂直波数谱不能解释.然而平均垂直波数谱显示了明显的季节变化,在夏季,平均谱具有饱和特性;在冬季,平均谱具有非饱和特性.这意味着饱和过程存在于夏季而不是冬季.因此,夏季比冬季应有更强的湍流.这个结果与湍流季节变化的观测大致一致.从Brunt-Vaisala频率N和水平风切变计算的Richardson数Ri剖面也显示出季节差异,Ri<1/4的动力不稳定区出现在夏季,而Ri>0.4的稳定区出现在冬季.这些不稳定区与夏季谱结合很好,而稳定区则与冬季谱结合很好.

Revisiting the methods for gas permeability measurement in tight porous medium

Permeability is a key parameter to describe fluid transport properties of porous medium; however, the permeability measurement is extremely difficult for tight porous medium, e.g. fine-grained rock or dense soil. In this paper, three methods for gas permeability measurement, i.e. steady state method, pulse decay method(PDM) and pressure oscillation method(POM), are first reviewed and then their advantages and drawbacks are discussed. Both analytical and numerical solutions of gas permeability are presented for the tight porous medium. The results show that the analytical method is relatively simple but only valid under certain conditions, whilst the numerical method is more robust and generic, which can take into account several factors such as porosity, saturation, gas leakage, and unconventional boundary conditions. The influence of the effective porosity on the permeability determination is further analyzed using the proposed numerical method. In this study, new pressure data interpretation procedures for PDM and POM are proposed, and the obtained results can serve as a guidance to define a proper method for permeability measurement of the tight porous medium.