Normal Mixture Research Articles

Up- and Down-Correlations in Normal Variance Mixture Models

Up- and Down-Correlations in Normal Variance Mixture Models

Cleaning Nanoceria Particles by Diluted HNO3 with H2O2 Mixture (NPM) Solution at Different Temperatures

It is difficult to remove nanoceria abrasives from the SiO2 substrate after the shallow trench isolation (STI) chemical mechanical polishing process. In this work, we studied the cleaning behavior of ceria particles by using an acidic cleaning solution instead of normal sulfuric acid and hydrogen peroxide mixture solution (SPM) at high temperatures (above 85 °C) and low temperatures (below 30 °C). The solution, named as NPM, consists of HNO3 (1–2 vol%), H2O2 (5–10 vol%), and deionized water (DIW). It is found that NPM can dissolve nanoceria particles at high temperatures with higher cleaning efficiency (CE) than that of SPM. NPM can clean the A90 (90 nm ceria) particles under ultrasonic/megasonic at low temperatures, while SPM has poor CE at 20 °C. The redox reaction of NPM and its effect on cleaning mechanism were systematically studied.

The time series modelling on exchange rate and inflation rate: finite normal mixture model

The time series modelling on exchange rate and inflation rate: finite normal mixture model

In Situ Damage Monitoring of CFRPs by Electromagnetic Tomography With the Compatible Multitemplate Supervised Descent Method

In this paper, an in-situ damage detection framework for carbon fiber-reinforced plastics (CFRPs) is proposed. The methodology involves the design of an electromagnetic tomography (EMT) sensor and developing an absolute image reconstruction method for electromagnetic tomography. A linear EMT sensor is designed for in-situ structural health monitoring of CFRPs tensile load test specimens. A compatible multi-template supervised descent method (cmt-SDM) based on a normal mixture distribution model of pixels is proposed for EMT image reconstruction. The cmt-SDM was developed to overcome the ill-posed problem in absolute image reconstruction. Simulation and experimental results show that the method proposed in this paper can be employed to monitor and evaluate the local damage degree of CFRPs specimens under quasi-static tensile loading. In addition, when the local fiber-breaking ratio reaches 40%, the damage location can be accurately reflected by the imaging results. Compared with the traditional SDM method, the method proposed in this paper shows smaller estimation error and delivers more accurate reconstructed images.

The time series modelling on exchange rate and inflation rate: finite normal mixture model

The time series modelling on exchange rate and inflation rate: finite normal mixture model

Experimental and Statistical Study of the Effect of Steel Fibers and Design Strength on the Variability in Repeated Impact Test Results

The ACI 544-2R repeated impact test is known as a low-cost and simple qualitative test to evaluate the impact strength of concrete. However, the test’s main deficiency is the high variability in its results. The effect of steel fibers and the compressive strength of concrete on the variability in repeated impact test results was investigated experimentally and statically in this study. Two batches from four mixtures were prepared and tested for this purpose. Hooked-end steel fibers were utilized in the fibrous mixtures. The mixtures NC, NC-SF0.5 and NC-SF1.0 were normal strength mixtures with 0, 0.5 and 1.0% of steel fibers, respectively, while HC was a plain high-strength mixture. The impact tests were conducted using an automatic testing machine following the setup of the ACI 544-2R repeated impact test. The impact numbers at cracking (N1) and at failure (N2) were recorded for both batches of the four mixtures. The results were also analyzed using the normal probability and Weibull distribution tests. The test results showed that the fibers increased the impact results at the cracking stage and significantly increased the failure impact resistance. Adding 0.5 and 1.0% of steel fibers increased the N1 by up to 66 and 111%, respectively, and increased the N2 by 114 and 374%, respectively. The test results also showed that duplicating the design compressive strength from 40 to 80 MPa increased the impact resistance by up to approximately 190%. The test results revealed no clear trend of an effect of steel fibers and compressive strength on the variability in the test results.

Effectiveness and safety of tetanus vaccine administration by intramuscular vs. subcutaneous route in anticoagulated patients: Randomized clinical trial in primary care.

Prospective, double-blind clinical trial comparing tetanus-diphtheria vaccine administration routes, intramuscular (IM) vs. subcutaneous (SC) injection, in patients with oral anticoagulants. ISRCTN69942081. Patients treated with oral anticoagulants, 15 health centers, Vigo (Spain). Sample size, 117 in each group. Safety analysis: systemic reactions and, at the vaccine administration site, erythematic, swelling, hematoma, granuloma, pain.Effectiveness analysis: differences in tetanus toxoid antibody titers.Independent variables: route, sex, age, baseline serology, number of doses administered. Following the CONSORT guidelines, we performed an intention-to-treat analysis. We conducted a descriptive study of the variables included in both groups (117 in each group) and a bivariate analysis. Fewer than 5% of missing values. Imputation in baseline and final serology with the median was performed. Lost values were assumed to be values missing at random. We conducted a descriptive study of the variables and compared routes. For safety, multivariate logistic regression was applied, with each safety criterion as outcome and the independent variables. Odds ratios (ORs) were calculated. For effectiveness, a generalized additive mixed model, with the difference between final and initial antibody titers as outcome. Due to the bimodal distribution of the outcome, the normal mixture fitting with gamlssMX was used. All statistical analyses were performed with the gamlss.mx and texreg packages of the R free software environment. A previously published protocol was used across the 6-year study period. The breakdown by sex and route showed: 102 women and 132 men; and 117 IM and 117 SC, with one dose administered in over 80% of participants. There were no differences between groups in any independent variable. The second and third doses administered were not analyzed, due to the low number of cases. In terms of safety, there were no severe general reactions. Locally, significant adjusted differences were observed: in pain, by sex (male, OR: 0.39) and route (SC, OR: 0.55); in erythema, by sex (male, OR: 0.34) and route (SC, OR: 5.21); and in swelling, by sex (male, OR: 0.37) and route (SC, OR: 2.75). In terms of effectiveness, the model selected was the one adjusted for baseline serology.

Parametric testing for normality against bimodal and unimodal alternatives using higher moments

This study examines population and small sample properties of the standardized fifth and sixth moments – the “higher moments” – for assessing univariate normality against bimodal and selected unimodal alternatives. Population parameters and distributions for selected bimodal mixtures are calculated and contrasted with those for the normal distribution. Using Gram-Charlier series expansion methods, an omnibus goodness of fit test incorporating the higher moments is specified and Monte Carlo simulation used to compare test power with parametric tests based on the standardized third and fourth sample moments: the asymptotic and size corrected versions of the Jarque-Bera score test and the omnibus D’Agostino K2 test. The studentized range and directional tests using the third through sixth moments are also considered. The results demonstrate that incorporating the fifth and sixth moments can provide enhanced parametric normality test power for bimodal normal mixture alternatives but not for various unimodal alternatives.

Health State Estimation of On-Board Lithium-Ion Batteries Based on GMM-BID Model

As a single feature parameter cannot comprehensively evaluate the health status of a battery, a multi-source information fusion method based on the Gaussian mixture model and Bayesian inference distance is proposed for the health assessment of vehicle batteries. The missing and abnormal data from real-life vehicle operations are preprocessed to extract the sensitive characteristic parameters which determine the battery performance. The normal state Gaussian mixture model is established using the fault-free state data, whereas the Bayesian inference distance is constructed as an index to quantitatively evaluate the battery performance state. In order to solve the problem that abnormal data may exist in the measured data and introduce errors into evaluation results, the determination rules of abnormal data are formulated. The verification of real-life vehicle operation data reveals that the proposed method can accurately evaluate the onboard battery state and reduce safety hazards of electric vehicles during the normal operation process.

Finite Normal Mixture Models for the Ensemble Learning of Recurrent Neural Networks with Applications to Currency Pairs

Finite Normal Mixture Models for the Ensemble Learning of Recurrent Neural Networks with Applications to Currency Pairs

Pengaruh aditif limbah kerang darah (anadara granosa) terhadap kualitas beton K-225

A rapid development of the concrete construction sector has resulted in an increase in the need for concrete raw materials that are obtained directly from nature. The need for environmentally friendly materials is also increasing along with the development of construction engineering technology, so several studies have been conducted to search for an alternative to raw materials additives or concrete mixtures. Anadara granosa clam shell can be utilized as one of the alternative materials to substitute material for coarse aggregates. In this research, Anadara granosa clam shells of 10% and 13% were added to normal concrete mixtures, aged for 28 days, and then analyzed for characteristics and compressive strength. From the analysis of the results, it was found that an increase in the concrete compressive strength up to 103.67% or 233.47 Kg/cm2 with the addition of clam shells 10% to normal concrete mixtures, while the addition of more than 10% can reduce the concrete compressive strength. Scanning Electron Microscopy results showed a relatively rough surface and many pores on the surface of the concrete due to the addition of a clam shell. Finally, it can be concluded that Anadara granosa clam shells can be used as concrete additives with a maximum addition of 10% of the total weight of normal concrete.

Estimating the Relationship Between EQ-5D-5L and EQ-5D-3L: Results from a UK Population Study.

The aim of this study was to estimate the relationship between EQ-5D-3L and EQ-5D-5L, in both directions, using a single model. An online survey containing both variants of EQ-5D, with randomised ordering, was administered to a large UK sample in 2020. A joint statistical model of the ten EQ-5D responses (five at 5L, five at 3L), using a multi-equation ordinal regression framework was estimated. The joint model ensures mappings in either direction are fully consistent with the information in the sample and satisfy Bayes' rule. Three extensions enhance model flexibility: a copula specification allows differing degrees of correlation between the 3L and 5L responses at the upper and lower extremes of health; a normal mixture residual distribution gives flexibility in the distributional form of responses; and a common factor captures correlations in responses across the five dimensions. Almost 50,000 responses were received. Thirty-five percent of respondents reported an existing medical condition. Ninety percent of possible 3L and 43% of possible 5L health states were observed. The preferred model specification includes age, sex and the responses to the EQ-5D instrument. Close alignment to the observed data was observed both in within-sample and out-of-sample comparisons. The results from this study provide a means of translating evidence to or from EQ-5D-3L to or from 5L based on a large-scale UK population survey with randomised ordering. Mapping can be performed either using descriptive system responses, individual utility scores or summary statistics.

Experimental Investigation of the Fracture Properties for Crumb Rubber Modified (CRM) Asphalt Mixtures

Cracks that develop daily and seasonally due to the environmental or mechanical effects caused by axle loads, propagate over time and become an important type of distress in asphalt layers. This type of distress can significantly increase the maintenance and rehabilitation costs of pavements. The use of rubber powder or fine granules in certain proportions to the bitumen content can extend the life of the pavements and reduce the environmental problems caused by waste tire disposal. In this study, the fracture behavior of normal and rubber-modified asphalt mixtures was investigated in accordance with AASHTO TP105 by adding waste tire granules at the ratio of 20% by weight of bitumen to hot mix asphalt. It has been determined that when the waste tire powders are added to the hot mix asphalt by replacing 20% of the bitumen weight, coatings with 37% more elastic ability could be made on sustainable pavements. Waste tire powder-mixes performed 118% higher in maximum load and 97% higher in fracture toughness compared to control-mixes. It has been shown that low temperature performance could be improved when waste tire powder-added bitumen processed by dry method is mixed to hot mix asphalt up to 20%.

Quality measures for fully automatic CT histogram-based fat estimation on a corpse sample

In a previous article a new algorithm for fully automatic ‘CT histogram based Fat Estimation and quasi-Segmentation’ (CFES) was validated on synthetic data, on a special CT phantom, and tested on one corpse. Usage of said data in FE-modelling for temperature-based death time estimation is the investigation’s number one long-term goal. The article presents CFES’s results on a human corpse sample of size R = 32, evaluating three different performance measures: the τ-value, measuring the ability to differentiate fat from muscle, the anatomical fat-muscle misclassification rate D, and the weighted distance S between the empirical and the theoretical grey-scale value histogram. CFES-performance on the sample was: D = 3.6% for weight exponent α = 1, slightly higher for α ≥ 2 and much higher for α ≤ 0. Investigating τ, S and D on the sample revealed some unexpected results: While large values of τ imply small D-values, rising S implies falling D and there is a positive linear relationship between τ and S. The latter two findings seem to be counter-intuitive. Our Monte Carlo analysis detected a general umbrella type relation between τ and S, which seems to stem from a pivotal problem in fitting Normal mixture distributions.

Robust mixture regression modeling based on the normal mean-variance mixture distributions

Mixture regression models (MRMs) are widely used to capture the heterogeneity of relationships between the response variable and one or more predictors coming from several non-homogeneous groups. Since the conventional MRMs are quite sensitive to departures from normality caused by extra skewness and possible heavy tails, various extensions built on more flexible distributions have been put forward in the last decade. The class of normal mean-variance mixture (NMVM) distributions that arise from scaling both the mean and variance of a normal random variable with a common mixing distribution encompasses many prominent (symmetric or asymmetrical) distributions as special cases. A unified approach to robustifying MRMs is proposed by considering the class of NMVM distributions for component errors. An expectation conditional maximization either (ECME) algorithm, which incorporates membership indicators and the latent scaling variables as the missing data, is developed for carrying out maximum likelihood (ML) estimation of model parameters. Four simulation studies are conducted to examine the finite-sample property of ML estimators and the robustness of the proposed model against outliers for contaminated and noisy data. The usefulness and superiority of our methodology are demonstrated through applications to two real datasets.

A New Class of Weighted CUSUM Statistics.

A change point is a location or time at which observations or data obey two different models: before and after. In real problems, we may know some prior information about the location of the change point, say at the right or left tail of the sequence. How does one incorporate the prior information into the current cumulative sum (CUSUM) statistics? We propose a new class of weighted CUSUM statistics with three different types of quadratic weights accounting for different prior positions of the change points. One interpretation of the weights is the mean duration in a random walk. Under the normal model with known variance, the exact distributions of these statistics are explicitly expressed in terms of eigenvalues. Theoretical results about the explicit difference of the distributions are valuable. The expansions of asymptotic distributions are compared with the expansion of the limit distributions of the Cramér-von Mises statistic and the Anderson and Darling statistic. We provide some extensions from independent normal responses to more interesting models, such as graphical models, the mixture of normals, Poisson, and weakly dependent models. Simulations suggest that the proposed test statistics have better power than the graph-based statistics. We illustrate their application to a detection problem with video data.

Determining Strain Threshold Values for Bridge Condition Assessment Using Normal Mixture Models

Structural health monitoring (SHM) enables bridge owners to evaluate bridge conditions efficiently and accurately. When implementing SHM, a popular method to detect the abnormal response of a structure is statistical pattern recognition. This often involves unsupervised statistical analysis due to a lack of measured SHM data from abnormal conditions. In this study, a novel methodology to calculate strain threshold indices (STIs) and establish decision boundaries (DBs) was used to detect the abnormal responses of the Indian River Inlet Bridge (IRIB), Sussex County, Delaware. First, a series of statistical models were applied and compared. Gaussian three mixture distributions were the optimal statistical models for the heavy vehicle-induced strain peaks. Threshold values for the strain gauges were selected using 99% uppers limits (USLs), and these limits were used to detect the abnormal response of the IRIB. The outlier ratios (R) for the sensors were calculated based on the threshold values. Corresponding STIs were defined by analyzing R, and DBs were determined using a t-distribution. The abnormal responses of the IRIB were detected by comparing the STI and DBs. The validity and sensitivity of the proposed methodology were demonstrated through simulated data that was created by perturbing the actual collected SHM data. Varying degrees of simulated damage were successfully detected using the proposed DBs. The proposed methodology showed promise when short and long-term abnormal responses and could provide practical guidance for bridge owners when using SHM data in their decision-making process.

Pemanfaatkan Subtitusi Fly Ash dan Bahan Kapur Alam untuk Peningkatan Mutu Paving Block

Utilization of waste materials as building materials is a solution to reduce waste materials that exist in nature.Fly ash as a waste product from coal combustion contains silica which can be used to increase the compressivestrength of concrete/mortar. Paving Block as a building material made of mortar composition can be increasedits compressive strength by substituting some cement material with fly ash. Fine aggregate material in the formof sand can also be substituted with natural limestone waste material. In this study, paving blocks were madeusing limestone as a substitute for fine aggregate and fly ash as a cement substitute. The ratio of materials formaking paving blocks is 1: 4. For variations of substitution materials, fly ash is used as a cement substitution.The variation of fly ash is 20% and while the limestone waste is used variations of 0%, 10%, 20%, 30% and 40%.The compressive strength test was carried out at the age of 7 days, 14 days, and 28 days. The results of the studyof compressive strength at the age of 7 days obtained a value of 12.24 MPa at a natural limestone substitutionconcentration of 20.7%. For the age of 14 days the compressive strength value is 15.27 MPa with an optimumconcentration of 20.1% at the concentration of natural limestone, while at the age of 28 days the compressivestrength value is 17.11 MPa, with the optimum concentration of natural limestone material being 20. .15%. Theincrease in compressive strength from the optimum mixture to the normal mixture was 28.93%. Based on SNI 03-0691-1996 the paving blocks produced in this study include Quality B.

UTILITY INDIFFERENCE PRICING AND MEAN-VARIANCE APPROACH WHEN THE DEGREE OF RISK AVERSION IS SMALL

We study the properties of the risk-sensitive value measure and mean-variance approach studied by Hodoshima et al. [2] when the degree of risk aversion is small. We show that the two value measures work similarly in normal mixture distributions as well as any distribution when the degree of risk aversion is small. Therefore, the advantage of the risk-sensitive value measure disappears compared to mean- variance approach in any distribution when the degree of risk aversion is small. We obtain the result by approximating the risk-sensitive value measure by Taylor series expansion.

STATISTIKA DESKRIPTIF T-TEST UNTUK MEMPERMUDAH PEMILIHAN DATA DARI HASIL PENGUJIAN BETON MENGGUNAKAN SPSS 16.0

This study discusses the application of descriptive statistics in the world of construction projects to analyze and interpret the data under study. Considering that time is a crucial thing in the project, it is necessary to have auxiliary tools to increase the time usage effectively for all important elements in the construction project. One of them is to shorten the time to analyze research results from testing concrete or concrete mixtures with case studies. To achieve maximum results, it takes a lot of samples that produce a lot of data. Hence, this study tries to use T-Test analysis of descriptive statistics which can help compare related groups to find out whether there are differences between groups. The results of the case study showed that there was no significant difference between concrete with normal mixture and other mixtures. Thus, the results of the study analysis can be concluded immediately whether the quality of the concrete according to the design criteriaKeywords: Descriptive Statistic, T-Test, The Quality of concrete