Uncertain Fuzzy Reasoning: A Case Study in Modelling Expert Decision Making

This paper presents a case study in which the introduction of vagueness or uncertainty into the membership functions of a fuzzy system was investigated in order to model the variation exhibited by experts in a medical decision-making context. A conventional (type-1) fuzzy expert system had previously been developed to assess the health of infants immediately after birth by analysis of the biochemical status of blood taken from infants' umbilical cords. Variation in decision making was introduced into the fuzzy expert system by means of membership functions which altered in small, predetermined manners over time. Three types of variation in membership functions were investigated: i) variation in the centre points, ii) variation in the widths, and iii) the addition of "white noise". Different levels (amounts) of uniformly distributed random variation were investigated for each of these types. Monte Carlo simulations were carried out to propagate the variation through the inferencing process in order to determine distributions of the conclusions reached. Interval valued type-2 fuzzy systems were also implemented to investigate the boundaries of variability in decisions. The results obtained were compared to the experts' decisions in order to determine which type and size of membership function variability best matched the experts' variability. The novel reasoning technique introduced in this study is termed nonstationary fuzzy reasoning     

Differentiation of mixtures of monovarietal olive oils by mid‐infrared spectroscopy and chemometrics

Fourier transform infrared (FT‐IR) spectroscopy in combination with chemometric techniques has become a useful tool for authenticity determination of extra‐virgin olive oils. Spectroscopic analysis of monovarietal extra‐virgin olive oils obtained from three different olive cultivars (Erkence, Ayvalik and Nizip) and mixtures (Erkence‐Nizip and Ayvalik‐Nizip) of monovarietal olive oils was performed with an FT‐IR spectrometer equipped with a ZnSe attenuated total reflection sample accessory and a deuterated tri‐glycine sulfate detector. Using spectral data, principal component analysis successfully classified each cultivar and differentiated the mixtures from pure monovarietal oils. Quantification of two different monovarietal oil mixtures (2–20%) is achieved using partial least square (PLS) regression models. Correlation coefficients (R²) of the proposed PLS regression models are 0.94 and 0.96 for the Erkence‐Nizip and Ayvalik‐Nizip mixtures, respectively. Cross‐validation was applied to check the goodness of fit for the PLS regression models, and R² of the cross‐validation was determined as 0.84 and 0.91, respectively, for the two mixtures.     

Determination of antioxidant activities of various extracts and essential oil compositions of Thymus praecox subsp. skorpilii var. skorpilii

The aim of this work is to examine the chemical composition and antioxidant activity of separated essential oils and different solvent extracts of Thymus praecox subsp. skorpilii var. skorpilii (TPS). The ethanol, acetone, methanol, hexane, aqueous extracts and separated essential oils of TPS were assessed for their antioxidant activities. Antioxidant activities were evaluated by reduction of Mo(VI) to Mo(V), reducing power, superoxide scavenging activity, free radical-scavenging activity, metal chelating activity, linoleic acid peroxidation, hydrogen peroxide scavenging activity and peroxide scavenging activity. Essential oils were characterized in total to be 41 components, whereas 9 components were isolated by column chromatography for antioxidant activity. TPS essential oil was found to contain thymol (40.31%) and o-cymene (13.66%) as the major components. The ethanol, methanol and water extracts exerted significant free radical-scavenging activity. The methanol and water extracts displayed highest superoxide scavenging activity. The water extract has the highest total phenolics (6.211 mg gallic acid (GAE)/g DW) and flavonoids (0.809 mg quercetin/g DW).     

Phenolic Characterization and Geographical Classification of Commercial Extra Virgin Olive Oils Produced in Turkey

The aim of this research was to characterize the extra virgin olive oil samples from different locations in the Aegean coastal area of Turkey in terms of their phenolic compositions for two consecutive years to show the classification of oil samples with respect to harvest year and geography. Forty seven commercial olive oil samples were analyzed with HPLC–DAD, and 17 phenolic compounds were quantified. Hydroxytyrosol, tyrosol, vanillic acid, p-coumaric acid, ferulic acid, cinnamic acid, luteolin and apigenin were the characteristic phenols observed in all oil samples for two harvest years. Syringic acid, vanillin and m-coumaric acid were the phenolic compounds appeared in the olive oil depending on the harvest year. Partial least square-discriminant analysis (PLS-DA) of data revealed that oils from the north Aegean and south Aegean areas had different phenolic profiles. The phenolic compounds, which played significant roles in the discrimination of the olive oils, were tyrosol, oleuropein aglycon, cinnamic acid, apigenin and hydroxytyrosol to tyrosol ratio. The Aegean coastal region is the largest olive oil producer and exporter of Turkey. This study shows that the olive oils from different parts of the region have their own defining characteristics that can be used in the authentication studies and geographical labeling of Turkish olive oils.     

A novel variable step size adjustment method based on channel output autocorrelation for the LMS training algorithm

The least mean squares (LMS) algorithm, the most commonly used channel estimation and equalization technique, converges very slowly. The convergence rate of the LMS algorithm is quite sensitive to the adjustment of the step‐size parameter used in the update equation. Therefore, many studies have concentrated on adjusting the step‐size parameter in order to improve the training speed and accuracy of the LMS algorithm. A novel approach in adjusting the step size of the LMS algorithm using the channel output autocorrelation (COA) has been proposed for application to unknown channel estimation or equalization in low‐SNR in this paper. Computer simulations have been performed to illustrate the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed variable step size LMS (VSS‐LMS) algorithm has considerably better performance than conventional LMS, recursive least squares (RLS), normalized LMS (N‐LMS) and the other VSS‐LMS algorithms. Copyright © 2011 John Wiley & Sons, Ltd.     

Effects of interesterified vegetable oils and sugarbeet fiber on the quality of frankfurters

The effects of interesterified vegetable oils (IVOs) prepared from palm, cottonseed and olive oil, respectively, and sugarbeet fiber (SBF) on quality of frankfurters have been studied. Beef fat (10%) was replaced by one of the IVOs for 60% and 100%. Incorporation of IVOs in frankfurters improved the nutritional content of product due to altering the fatty acid composition. The oleic acid content of frankfurters increased from 28.76% to 45.57% and 47.15% as the interesterified palm oil (IPO) and interesterified olive oil (IOO) contents increased from 0% to 10% and 6%, respectively. The linoleic acid contents of 6% and 10% interesterified cottonseed oil (ICO) added frankfurters were, respectively, 10- and 19.6-fold higher than treatments without ICO. Addition of SBF (<425 μm size and 1% level) significantly increased (p<0.05) the total dietary fiber content and water-holding capacity (WHC) of frankfurters. Incorporation of IVOs and SBF did not lead to significant changes in appearance, colour, texture, flavour or sensory scores. It is concluded that IVOs and SBF may be successfully applied as beef fat substitute in frankfurters since this combination offset some of the changes brought about by beef fat replacement.     

Natural fiber blend—nylon 6 composites

In this study, engineering thermoplastic composites were prepared from natural fiber blend–filled nylon 6. Natural fiber blend from a mixture of kenaf, flax, and hemp fibers were added to nylon 6 using melt mixing to produce compounded pellets. The natural fibers/ nylon6 composites with varying concentrations of natural fibers (from 5 to 20 wt%) were prepared by injection molding. The tensile and flexural properties of the nylon 6 composites were increased significantly with the addition of the natural fiber blend. The maximum strength and modulus of elasticity for the nylon 6 composites were achieved at a natural fiber blend weight fraction of 20%. The Izod impact strength of composites decreased with the incorporation of natural fibers without any surface treatments and coupling agent. The melt flow index (MFI) also decreased with increasing natural fiber blend loading. The results of tensile and flexural modulus of elasticity (FMOE) are in accordance with the rheological data from the MFI measurements. The increase in the tensile and flexural properties indicated that efficient bonding occurred between the natural fibers and nylon 6. No fiber pullout was observed during the scanning electron microscopic analysis of the fracture surfaces. The higher mechanical results with lower density demonstrate that a natural fiber blend can be used as a sufficient reinforcing material for low‐cost, eco‐friendly composites in the automotive industry and in other applications such as the building and construction industries, packaging, consumer products, etc.POLYM. COMPOS., 2013. © 2013 Society of Plastics Engineers     

nm23 protein expression in renal cell tumors: the role of the cell type

This study investigated nm23 protein expression in renal cell carcinomas to determine the relationship between nm23 protein expression and grade, stage, prognosis and the cell type. 89 cases were examined by immunohistochemistry. Tubular epithelia were homogeneously stained. Cytoplasmic nm23 protein levels were reduced in renal cell carcinoma. nm23 protein levels persisted in oncocytomas, which are accepted to be benign. Cytoplasmic nm23 staining intensity did not show any correlation with stage and grade of tumor nor prognosis. Reduction in nm23 protein levels may have a role during renal cell carcinoma pathogenesis but not in progression or metastasis suppression.