Measuring process capability for bivariate non-normal process using the bivariate burr distribution

As is well known, process capability analysis for more than one quality variables is a complicated and sometimes contentious area with several quality measures vying for recognition. When these variables exhibit non-normal characteristics, the situation becomes even more complex. The aim of this paper is to measure Process Capability Indices (PCIs) for bivariate non-normal process using the bivariate Burr distribution. The univariate Burr distribution has been shown to improve the accuracy of estimates of PCIs for univariate non-normal distributions (see for example, [7] and [16]). Here, we will estimate the PCIs of bivariate non-normal distributions using the bivariate Burr distribution. The process of obtaining these PCIs will be accomplished in a series of steps involving estimating the unknown parameters of the process using maximum likelihood estimation coupled with simulated annealing. Finally, the Proportion of Non-Conformance (PNC) obtained using this method will be compared with those obtained from variables distributed under the bivariate Beta, Weibull, Gamma and Weibull-Gamma distributions

Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: Application in Indonesia

BackgroundBirth weight is one of the most important indicators of neonatal survival. A reliable estimate of foetal weight at different stages of pregnancy would facilitate intervention plans for medical practitioners to prevent the risk of low birth weight delivery. This study has developed reliable models to more accurately predict estimated foetal weight at a given gestation age in the absence of ultrasound facilities.MethodsA primary health care centre was involved in collecting retrospective non-identified Indonesian data. The best subset model selection criteria, coefficient of determination, standard deviation, variance inflation factor, Mallows C-p, and diagnostic tests of residuals were deployed to select the most significant independent variables. Simple and multivariate linear regressions were used to develop the proposed models. The efficacy of models for predicting foetal weight at a given gestational age was assessed using multi-prediction accuracy measures.ResultsFour weight prediction models based on fundal height and its combinations with gestational age (between 32 and 41weeks) and ultrasonic estimates of foetal head circumference and foetal abdominal circumference have been developed. Multiple comparison criteria show that the proposed models were more accurate than the existing models (mean prediction errors between -0.2 and 2.4g and median absolute percentage errors between 4.1 and 4.2%) in predicting foetal weight at a given gestational age (between 35 and 41weeks).ConclusionsThis research has developed models to more accurately predict estimated foetal weight at a given gestational age in the absence of ultrasound machines and trained ultra-sonographers. The efficacy of the models was assessed using retrospective data. The results show that the proposed models produced less error than the existing clinical and ultrasonic models. This research has resulted in the development of models where ultrasound facilities do not exist, to predict the est

Optimal profile limits for maternal mortality rate (MMR) in South Sudan

© 2018 The Author(s). Background: Reducing Maternal Mortality Rate (MMR) is considered by the international community as one of the eight Millennium Development Goals. Based on previous studies, Skilled Assistant at Birth (SAB), General Fertility Rate (GFR) and Gross Domestic Product (GDP) have been identified as the most significant predictors of MMR in South Sudan. This paper aims for the first time to develop profile limits for the MMR in terms of significant predictors SAB, GFR, and GDP. The paper provides the optimal values of SAB and GFR for a given MMR level. Methods: Logarithmic multi- regression model is used to model MMR in terms of SAB, GFR and GDP. Data from 1986 to 2015 collected from Juba Teaching Hospital was used to develop the model for predicting MMR. Optimization procedures are deployed to attain the optimal level of SAB and GFR for a given MMR level. MATLAB was used to conduct the optimization procedures. The optimized values were then used to develop lower and upper profile limits for yearly MMR, SAB and GFR. Results: The statistical analysis shows that increasing SAB by 1.22% per year would decrease MMR by 1.4% (95% CI (0.4-5%)) decreasing GFR by 1.22% per year would decrease MMR by 1.8% (95% CI (0.5-6.26%)). The results also indicate that to achieve the UN recommended MMR levels of minimum 70 and maximum 140 by 2030, the government should simultaneously reduce GFR from the current value of 175 to 97 and 75, increase SAB from the current value of 19 to 50 and 76. Conclusions: This study for the first time has deployed optimization procedures to develop lower and upper yearly profile limits for maternal mortality rate targeting the UN recommended lower and upper MMR levels by 2030. The MMR profile limits have been accompanied by the profile limits for optimal yearly values of SAB and GFR levels. Having the optimal level of predictors that significantly influence the maternal mortality rate can effectively aid the government and international or

Video Fragmentation and Reverse Search on the Web

This chapter is focused on methods and tools for video fragmentation and reverse search on the web. These technologies can assist journalists when they are dealing with fake news—which nowadays are being rapidly spread via social media platforms—that rely on the reuse of a previously posted video from a past event with the intention to mislead the viewers about a contemporary event. The fragmentation of a video into visually and temporally coherent parts and the extraction of a representative keyframe for each defined fragment enables the provision of a complete and concise keyframe-based summary of the video. Contrary to straightforward approaches that sample video frames with a constant step, the generated summary through video fragmentation and keyframe extraction is considerably more effective for discovering the video content and performing a fragment-level search for the video on the web. This chapter starts by explaining the nature and characteristics of this type of reuse-based fake news in its introductory part, and continues with an overview of existing approaches for temporal fragmentation of single-shot videos into sub-shots (the most appropriate level of temporal granularity when dealing with user-generated videos) and tools for performing reverse search of a video on the web. Subsequently, it describes two state-of-the-art methods for video sub-shot fragmentation—one relying on the assessment of the visual coherence over sequences of frames, and another one that is based on the identification of camera activity during the video recording—and presents the InVID web application that enables the fine-grained (at the fragment-level) reverse search for near-duplicates of a given video on the web. In the sequel, the chapter reports the findings of a series of experimental evaluations regarding the efficiency of the above-mentioned technologies, which indicate their competence to generate a concise and complete keyframe-based summary of the video content, and the use of this fragment-level representation for fine-grained reverse video search on the web. Finally, it draws conclusions about the effectiveness of the presented technologies and outlines our future plans for further advancing them

Titanium Dioxide Nanoparticles: Synthesis, X-Ray Line Analysis and Chemical Composition Study

TiO2 nanoparticleshave been synthesized by the sol-gel method using titanium alkoxide and isopropanolas a precursor. The structural properties and chemical composition of the TiO2 nanoparticles were studied usingX-ray diffraction, scanning electron microscopy, and X-ray photoelectron spectroscopy.The X-ray powder diffraction pattern confirms that the particles are mainly composed of the anatase phase with the preferential orientation along [101] direction.The physical parameters such as strain, stress and energy density were investigated from the Williamson- Hall (W-H) plot assuming a uniform deformation model (UDM), and uniform deformation energy density model (UDEDM). The W-H analysis shows an anisotropic nature of the strain in nanopowders. The scanning electron microscopy image shows clear TiO2 nanoparticles with particle sizes varying from 60 to 80nm. The results of mean particle size of TiO2 nanoparticles show an inter correlation with the W-H analysis and SEM results. Our X-ray photoelectron spectroscopy spectra show that nearly a complete amount of titanium has reacted to TiO2

Assessment of the physical characteristics and stormwater effluent quality of permeable pavement systems containing recycled materials

This paper evaluates the physical characteristics of two recycled materials and the pollutant removal efficiencies of four 0.2 m2 tanked permeable pavement rigs in the laboratory, that contained either natural aggregates or these recycled materials in the sub-base. The selected recycled materials were Crushed Concrete Aggregates (CCA) and Cement-bounded Expanded Polystyrene beads (C-EPS) whilst the natural aggregates were basalt and quartzite. Natural stormwater runoff was used as influent. Effluent was collected for analysis after 7–10 mins of discharge. Influent and effluent were analysed for pH, Chemical Oxygen Demand (COD), Dissolved Oxygen (DO), Electroconductivity (EC), turbidity, Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Nitrate-Nitrogen (NO3-N), reactive phosphorous (PO43-) and sulphates (SO42-). Both CCA and C-EPS had suitable physical properties for use as sub-base materials in PPS. However, C-EPS is recommended for use in pavements with light to no traffic because of its relatively low compressive strength. In terms of pollutant removal efficiencies, significant differences (p 0.05) were found with respect to TSS, turbidity, COD and NO3-N. Effluent from rigs containing CCA and C-EPS saw significant increases in pH, EC and TDS measurements whilst improvements in DO, TSS, turbidity, COD, PO43- and SO42- were observed. All mean values except pH were, however, within the Maximum Permissible Levels (MPLs) of water pollutants discharged into the environment according to the Trinidad and Tobago Environmental Management Authority (EMA) or the United States Environmental Protection Agency (US EPA). In this regard, the CCA and C-EPS performed satisfactorily as sub-base materials in the permeable pavement rigs. It is noted, however, that further analysis is recommended through leaching tests on the recycled materials

The impact of body mass index on low birth weight

It is well-documented that low birth weight (LBW) is the most significant factor influencing Neonatal mortality rate (NMR). Over recent decades, accumulating evidence around the world has suggested that LBW may be associated with an increased risk of subsequent development of a variety of complications in adulthood including cardiovascular disease, non-insulin-dependent diabetes mellitus, hypertension, and dyslipidemia. Neonatal birth weight is determined by several criteria such as, maternal age, pre-pregnancy Body Mass Index (BMI), gestation age and neonatal gender. This paper deploys regression analysis to explore the effect of pre-pregnancy BMI and other characteristics on the weight of low birth weight babies. The results indicate that the inclusion of the BMI in the regression model can improve the coefficient of the determination significantly

Capability analysis for modulus of elasticity and modulus of rupture

Sawn softwood timber is used as a structural component in house walls and roofs. Consequently, the consumption trends generally follow those of the housing industry. Therefore, Government imposes tough quality control and quality assurance on the timber industry to grantee product standard meets the specifications in building industry. Capability Analysis on the timber product plays an important role in assessing the capability of the timber in meeting the market functionality requirements. Two characteristics continuously monitored are the Modulus of Elasticity MOE and the Modulus of Rupture MOR. In this paper, we analyse the data collected from three different mills located in three different states based on both, the government recommended Specification Limits and the Natural Statistical Specification Limits. The analyses show that the government tough recommended Specification Limits results in many timbers to be downgraded

Forecasting wet land rice production for food security

Rice is one of the major crops feeding the world population and is one of the most substantial ingredients in the food security chain. Therefore, a reliable forecast of rice production would have a predominant impact on assessing the world food security. In this paper we develop models to forecast the wet land rice production in two provinces of Indonesia. The four-monthly data are used to construct and develop the forecasting models. To forecast the rice production, we first forecast the harvested area and the yield. We then use a mathematical model to estimate the rice production in terms of the harvested area and yield. The proposed models are used to forecast the recorded data. The error of the forecasted data are analysed to assess the efficacy of the models. The analysis of the errors shows that ARIMA(p, q, d)) and Bayesian models are the best models for forecasting harvested area and yield. However, the results clearly indicate that the optimal model for one province it not necessarily the best model for the other province