DETERMINATION OF DYSLIPIDEMIA BY DISCRETE AND PSEUDO-DISCRETE FEATURES

The necessity of controlling the lipid state of the organism originates from the association of dyslipidemia with atherosclerosis, heart diseases, diabetes mellitus, etc. In the clinical practice, the determination of the exact type of dyslipidemia is not straightforward due to certain problems: daily biological fluctuations, dietary effects, strong overlapping in characteristic plasma lipid levels in some classes of type llb, III and IV, frequent inavailability of a complete set of diagnostic measurements, as well as certain overlapping in the borderline values. These provide the objective to create a computer program for diagnostics* of dyslipidemia in 16 classes. The apparatus of Bayes classification has been applied using 13 discrete and 7 pseudo-discrete features. The proposed system is suitable for monitoring the treatment of dyslipidemia as well as for the purposes of students' education and post doctoral training

Local risk proneness in analytically approximated utility functions under monotonically decreasing preferences

We discuss an analytical arctan form to approximate decreasing utilitiesbased on several nodes of its graphics elicited in interval form. We demonstratethe process on two types of nodes originating from different subjective elicitation approaches. Our focus is also on the local risk attitude estimator, whichin the case of decreasing preferences gets interpreted as local risk proneness vsthe local risk aversion for increasing preferences

Health risk assessment of engine exhaust emissions within Australian ports: a case study of Port of Brisbane

Emissions from ocean-going vessels present a significant health risk to populations surrounding ports and damage the environment. Emissions from ships using heavy fuel oil include substantial amounts of sulphur dioxide, nitrogen oxides, and particulate matter. In order to assess the risk of these emissions, a complete methodology has been developed, based on the Australian Environmental Health Risk Assessment Framework. The method includes a detailed inventory of in-port and at-sea emissions using an activity-based approach applying downwash and near-field areas from first principles equations as well as the air-shed regions from CALPUFF dispersion modeling results for Port of Brisbane in 2013. The final risk values are validated against national and European guidelines. Various health impact assessments, as well as carcinogenic and ecological effects, are discussed in depth. This study offers a significant contribution to developing a baseline measurement of the current state of risk from emissions of the ocean-going vessels visiting the port, and suggests that, given the expected development of many Australian ports in the near future, the need for continual monitoring of shipping emissions is an essential and necessary area of research

Regression diagnostics with predicted residuals of linear model with improved singular value classification applied to forecast the hydrodynamic efficiency of wave energy converters

In the preliminary stages of design of the oscillating water column (OWC) type of wave energy converters (WECs), we need a reliable cost- and time-effective method to predict the hydrodynamic efficiency as a function of the design parameters. One of the cheapest approaches is to create a multiple linear regression (MLR) model using an existing data set. The problem with this approach is that the reliability of the MLR predictions depend on the validity of the regression assumptions, which are either rarely tested or tested using sub-optimal procedures. We offer a series of novel methods for assumption diagnostics that we apply in our case study for MLR prediction of the hydrodynamics efficiency of OWC WECs. Namely, we propose: a novel procedure for reliable identification of the zero singular values of a matrix; a modified algorithm for stepwise regression; a modified algorithm to detect heteroskedasticity and identify statistically significant but practically insignificant heteroscedasticity in the original model; a novel test of the validity of the nullity assumption; a modified Jarque–Bera Monte Carlo error normality test. In our case study, the deviations from the assumptions of the classical normal linear regression model were fully diagnosed and dealt with. The newly proposed algorithms based on improved singular value decomposition (SVD) of the design matrix and on predicted residuals were successfully tested with a new family of goodness-of-fit measures. We empirically investigated the correct placement of an elaborate outlier detection procedure in the overall diagnostic sequence. As a result, we constructed a reliable MLR model to predict the hydrodynamic efficiency in the preliminary stages of design. MLR is a useful tool at the preliminary stages of design and can produce highly reliable and time-effective predictions of the OWC WEC performance provided that the constructing and diagnostic procedures are modified to reflect the latest advances in statistics. The main advantage of MLR models compared to other modern black box models is that their assumptions are known and can be tested in practice, which increases the reliability of the model predictions

Effect of Phosphorus and Strontium Additions on Formation Temperature and Nucleation Density of Primary Silicon in Al-19 Wt Pct Si Alloy and Their Effect on Eutectic Temperature

The influence of P and Sr additions on the formation temperature and nucleation density of primary silicon in Al-19 wt pct Si alloy has been determined, for small volumes of melt solidified at cooling rates _T of ~0.3 and 1 K/s. The proportion of ingot featuring primary silicon decreased progressively with increased Sr addition, which also markedly reduced the temperature for first formation of primary silicon and the number of primary silicon particles per unit volume �Nv: When combined with previously published results, the effects of amount of P addition and cooling rate on �Nv are in reasonable accord with �Nv� _T ¼ ðp=6fÞ1=2 109 [250 � 215 (wt pct P)0.17]�3, where �Nv is in mm�3, _T is in K/s, and f is volume fraction of primary silicon. Increased P addition reduces the eutectic temperature, while increased Sr appears to generate a minimum in eutectic temperature at about 100 ppmw Sr