Change Point Estimation in the Mean of Multivariate Linear Profiles with No Change Type Assumption via Dynamic Linear Model

Change point estimation is a useful concept that helps quality engineers to effectively search for assignable causes and improve quality of the process or product. In this paper, the maximum likelihood approach is developed to estimate change point in the mean of multivariate linear profiles in Phase II. After the change point, parameters are estimated through filtering and smoothing approaches in dynamic linear model. The proposed change point estimator can be applied without any prior knowledge about the change type against existing estimators which assume change type is known in advance. Besides, sporadic change point can be identified as well. Simulation results show the effectiveness of the proposed estimators to estimate step, drift and monotonic, as well as sporadic changes in small to large shifts. In addition, effect of different values of the Multivariate Exponentially Weighted Moving Average (MEWMA) control chart smoothing coefficient on the performance of the proposed estimator is investigated presenting that the smoothing estimator has more uniform performance. Copyright © 2015 John Wiley & Sons, Ltd.     

Production of surface-active sophorolipid biosurfactant and crude oil degradability by novel Rhodotorula mucilaginosa strain SKF2

Biosurfactants are produced by important types of microorganisms such as bacteria, yeast, and filamentous fungi and have been used in a variety of industries. Among the 15 crude oil-degrading fungi, the two molds and one yeast were identified by 18S rDNA sequences as Mucor circinelloides strain SKMC, Fusarium fujikuroi strain DB2, and Rhodotorula mucilaginosa strain SKF2. These strains were isolated from crude oil–contaminated soil, diesel oil–contaminated soil, and activated sludge in the Oil Refinery Plant in Isfahan, Iran, respectively. The yeast strain was identified as a novel crude oil–degrading and biosurfactant-producing fungi in the presence of (1% v/v) Iranian light crude oil in the minimal salt medium (MSM). The highest amount of the dry weight of produced biosurfactant was measured at 6.2 g L⁻¹. Chemical nature of produced biosurfactant was determined as a surface-active sophorolipid biosurfactant compound by thin-layer chromatography, Fourier transform infra-red spectroscopy, and gas chromatography–mass spectrometry (GC–MS) analysis. The residual hydrocarbons in the MSM were analyzed by GC–MS, and it was shown that octadecane and docosane were eliminated by this novel strain completely.     

Functional Process Capability Indices for Circular Profile

Profile is a relation between one response variable and one or more explanatory variables that represent quality of a product or performance of a process. On the other hand, process capability indices are measures to help practitioners in improving the processes to satisfy the customer's expectations. Few researches are done to account for the process capability index in the areas of profile monitoring. All of these researches are focused on process capability index in simple linear profile. In all of these methods, response variables in different levels of explanatory variable are considered, and the relationship in all range of explanatory variable is neglected. In this paper, a functional method is proposed to measure process capability index of circular profiles in all range of explanatory variable. The proposed method follows the traditional definition of process capability indices. The functional method uses reference profile, functional specification limits and functional natural tolerance limits to present a functional form of process capability indices. This functional form results in measuring the process capability in each level of explanatory variable in circular profile as well as a unique value of process capability index for circular profile. The application of the proposed method is illustrated through a real case in automotive industry. Copyright © 2013 John Wiley & Sons, Ltd.     

Discrete size optimization of steel trusses using a refined big bang–big crunch algorithm

This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang–big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of Steel Construction Allowable Stress Design (AISC-ASD) specifications. Furthermore, the performance of the proposed BB-BC algorithm is compared to its standard version as well as other well-known metaheuristic techniques. The numerical results confirm the efficiency of the proposed algorithm in practical design optimization of truss structures.     

Experimental investigation into Fe3O4/SiO2 nanoparticle performance and comparison with other nanofluids in enhanced oil recovery

Nanofluids because of their surface characteristics improve the oil production from reservoirs by enabling different enhanced recovery mechanisms such as wettability alteration, interfacial tension (IFT) reduction, oil viscosity reduction, formation and stabilization of colloidal systems and the decrease in the asphaltene precipitation. To the best of the authors’ knowledge, the synthesis of a new nanocomposite has been studied in this paper for the first time. It consists of nanoparticles of both SiO₂ and Fe₃O₄. Each nanoparticle has its individual surface property and has its distinct effect on the oil production of reservoirs. According to the previous studies, Fe₃O₄ has been used in the prevention or reduction of asphaltene precipitation and SiO₂ has been considered for wettability alteration and/or reducing IFTs in enhanced oil recovery. According to the experimental results, the novel synthesized nanoparticles have increased the oil recovery by the synergistic effects of the formed particles markedly by activating the various mechanisms relative to the use of each of the nanoparticles in the micromodel individually. According to the results obtained for the use of this nanocomposite, understanding reservoir conditions plays an important role in the ultimate goal of enhancing oil recovery and the formation of stable emulsions plays an important role in oil recovery using this method.     

A new nickel metal organic framework (Ni-MOF) porous nanostructure as a potential novel electrochemical sensor for detecting glucose

Journal of Porous Materials - A Ni-MOF-based novel electrochemical sensor was synthesized with high surface area of 1381 m2/g, significant porosity of 1.14–9.6 nm and average...     

Estimating multivariate linear profiles change point with a monotonic change in the mean of response variables

In this paper, a maximum likelihood estimator (MLE) is developed to estimate change point when monotonic change occurs in the mean of response variables in multivariate linear profiles in Phase II. Performance of the proposed estimator is compared to the performance of step change and linear drift estimators under different shift types. To conduct comparisons, accuracy and precision of the estimators are considered as performance measures. Simulation results show that the average change point estimate of the proposed estimator is less biased than the one for the step and drift estimators in small shifts, because \( {\overline{\widehat{\tau}}}_{\mathrm{monotonic}} \) is closer to the actual change point of 25 in small shifts. Also, the precision of the proposed estimator is approximately better than that of the step and drift estimators, because its precision values are higher. Hence, the proposed estimator has better performance in terms of both accuracy and precision in small shifts under any kinds of increasing changes. In single step and linear drift changes when the magnitude of shifts increases, the accuracy and precision of their corresponding estimators become better than the accuracy and precision of the proposed estimator. However, the proposed estimator has an advantage that it does not require assumptions about the change type, and its only assumption is that the mean of the response variables changes in an increasing manner. Additional evaluations on the effect of smoothing constant show that with smaller values of the smoothing constant, the proposed change point estimator has less biased estimates and smaller values of mean square error in small shifts rather than the step and drift estimators, leading to a better performance. Also, the larger values of smoothing constant lead to the better performance of the monotonic estimator in large shifts. Finally, the application of the proposed estimator is shown through a real case in the calibration process in the automotive industry.     

Spatio-Temporal Analysis of Regional Trends and Shift Changes of Autocorrelated Temperature Series in Urmia Lake Basin

Recently, the Urmia Lake located in northwestern Iran which is the second largest hyper saline in the world suffers from the significant fluctuations of water level and surface area. The current study tries to investigate the spatiotemporal trends of mean (T_mean), maximum (T_max) and minimum (T_min) temperatures of monthly, seasonal and annual time-series. To do so, the data of 15 temperature gauge stations within the Urmia Lake basin, for the period 1972–2011 was employed. The pre-whitening approach was applied to remove the effects of serial correlation in the air temperature series based on the Mann-Kendall (MK) test. The results of Ljung-Box test showed positive serial correlation in the T_mean and T_max series for all of the stations at the 0.05 significance level. In the monthly series, the significant warming trends in the T_mean series were more perceptible than the same ones in T_max series; however, T_max trend was found more than T_min series. The Mann–Whitney (MW) test detected a significance upward shift changes in the annual T_mean, T_max and T_min series of about 86, 73 and 80 % of the stations, respectively. The average magnitude of significant warming trends in annual T_mean, T_max and T_min series were (+) 0.58 °C, (+) 0.52 °C and (+) 0.69 °C per decade, respectively. Furthermore, the interpolation maps showed that warming trends in the east and west of Urmia Lake were more than southern area. Therefore, the results showed that the basin has suffered from increasing trends in the T_mean, T_max and T_min over the recent decades. Finally, significant changes were found in 1980s and 1990s based on the Mann-Kendall ranks and change point tests. In this study, it is interesting that the period of significant changes in warming trends were close to the beginning of decreasing water level of the Lake.     

Morphology enhancement of TiO2/PVP composite nanofibers based on solution viscosity and processing parameters of electrospinning method

In this work, different sol solutions with various titanium tetraisopropoxide (TIP)/glacial acetic acid ratios in 2‐propanol with 5 wt % poly(vinyl pyrrolidone) (PVP) (M_w = 360,000 g/mol) were prepared and electrospun. Composition of the prepared sols and as‐spun TiO₂/PVP nanofibers were determined by Fourier transform infrared and Raman spectroscopy methods. Morphology of the electrospun TiO₂/PVP nanofibers was studied by scanning electron microscopy and transmission electron microscopy (TEM) techniques. Rheometry measurements of the sol solutions showed decrease of viscosity upon the addition of TIP to the polymer solutions with constant polymer and acid concentrations. The sol solution having the lowest viscosity (at shear rate 10 s^?1) but the highest TIP/glacial acetic acid ratio showed beaded nanofibers morphology when electrospun under 10 and 12 kV applied voltage while injection rate, needle tip to collector distance, and needle gauge were kept constant. However, smooth electrospun TiO₂/PVP composite nanofibers with the average nanofibers diameters (148 ± 79 nm) were achieved under the same condition when applied voltage increased to 15 kV. TEM micrographs of the electrospun TiO₂/PVP nanofiber showed that the TiO₂ particles with continuous structure are formed at the middle of the nanofiber and distributed along its axis. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46337.