Nonparametric snakes.

Active contours, or so-called snakes, require some parameters to determine the form of the external force or to adjust the tradeoff between the internal forces and the external forces acting on the active contour. However, the optimal values of these parameters cannot be easily identified in a general sense. The usual way to find these required parameters is to run the algorithm several times for a different set of parameters, until a satisfactory performance is obtained. Our nonparametric formulation translates the problem of seeking these unknown parameters into the problem of seeking a good edge probability density estimate. Density estimation is a well-researched field, and our nonparametric formulation allows using well-known concepts of density estimation to get rid of the exhaustive parameter search. Indeed, with the use of kernel density estimation these parameters can be defined locally, whereas, in the original snake approach, all the shape parameters are defined globally. We tested the proposed method on synthetic and real images and obtained comparatively better results.     

Multiple criteria evaluation of current energy resources for Turkish manufacturing industry

Energy is the main component of natural resources of developing, as well as developed, countries like Turkey. Because of economic and social developments, the demand for energy, in general, has increased considerably in Turkey. Since Turkey is not an oil or natural gas (NG) producing country, the energy resource usage for energy consumption should be effective. The Turkish industrial sector comprises approximately 36% of Turkey’s primary energy consumption, and the manufacturing industry is the largest industrial sector. In this study, the focus was on the manufacturing industry as the major energy consuming sector in Turkey, and it was analyzed in terms of efficient use of energy resources. The most widely used energy resources in the Turkish manufacturing industry, namely fuel-oil, coal, electricity, LPG and NG were taken into account. Evaluation and selection of current energy resources in this selected industry can be viewed as a multiple criteria decision making (MCDM) problem, including human judgments, tangible and intangible criteria and priorities and trade offs between goals and criteria. The analytic network process (ANP), one of the MCDM methods, was used to evaluate the most suitable energy resources for the manufacturing industry in this study.     

Effect of Liquid Oil on the Distribution and Reactivity of a Hydrophobic Solute in Solid Lipid Nanoparticles

The performance of solid lipid nanoparticles is often modified by the addition of small amounts of liquid oil. The effects of added liquid lipid (tetradecane, C14) on the distribution and reactivity of the spin probe 4-phenyl-2,2,5,5-tetramethyl-3-imidazoline-1-oxyl nitroxide (PTMIO) in solid lipid nanoparticles (eicosane, C20) were investigated as a function of storage time and temperature. Emulsions prepared with blends of C14:C20 (100 % C14, 90 % C20, 99 % C20, and 100 % C20) and stabilized by sodium caseinate (1 wt%) were stored at 21.5 °C or 5 °C for 5 or 24 h prior to EPR analyses. In the liquid C14 droplets the PTMIO partitioned between the droplet and aqueous phases (70 and 30 %, respectively) independent of storage conditions. However, the proportion of probe in droplets decreased with increasing crystalline C20 concentration. The fraction of PTMIO in droplets containing C20 decreased in the following sequence: 5 h at room temperature >24 h at room temperature >24 h at refrigerated temperature and was lower in droplets with a higher proportion of C20. The residual PTMIO in semicrystalline droplets has higher polarity and lower mobility than PTMIO in liquid oil droplets suggesting it is in a layer surrounding the crystalline lipid core, and partly immobilized by interaction with the surface layer. The model of PTMIO distribution was consistent with the kinetics of PTMIO reduction by aqueous ascorbate ions.     

Surface Morphology, Structural and Magnetic Properties of Electrodeposited NiFeCu/Cu Films

The magnetic and structural properties of the NiFeCu/Cu films electrodeposited on polycrystalline titanium (Ti) substrates and their characterizations were studied. The structural analysis by X-ray diffraction (XRD) has revealed that all films have face-centred cubic (FCC) structure. On the other hand, the XRD analysis showed that the degree of (111) texture is dependent on the Cu content within the film. The composition analysis was carried out by energy-dispersive X-ray spectroscopy (EDX). The result of EDX indicated that the Cu content within the film increases with increasing of non-magnetic Cu layer thickness. The hysteresis loops of the films measured by vibrating sample magnetometer (VSM) showed that all films have a small coercivity typical for soft magnetic materials. The surface morphological structure of the films was investigated by atomic force microscopy (AFM). AFM images indicated that all films have main grains (globular islands) and smaller secondary grains on the main grains with different sizes. The differences observed in the magnetic properties of the films were attributed to the Cu content within the films.     

Synthesis of the intermetallic clathrate Na2Ba6Si46 by oxidation of Na2BaSi4 with HCl

A new preparation route to the intermetallic clathrate-I compound Na₂Ba₆Si₄₆ is introduced, which allows one to make large amounts of product with standard laboratory equipment. The precursor Na₂BaSi₄ is oxidized with gaseous HCl at 673 K to Na₂Ba₆Si₄₆, NaCl and BaCl₂. Full-profile refinement of the crystal structure from the X-ray powder diffraction data revealed a composition close to Na₂Ba₆Si₄₆ (Na_1.94(1)Ba_6.06(1)Si₄₆, space group , a=10.281(1) Å). Differential scanning calorimetry showed an exothermic effect at 874 K, indicating that Na₂Ba₆Si₄₆ is metastable. The product was additionally characterized by scanning electron microscopy. The electronic structure of Na₂Ba₆Si₄₆ was investigated by a first-principles, all-electron full-potential method, predicting metallic conductivity. Na₂Ba₆Si₄₆ obtained by oxidation with HCl shows Pauli paramagnetism; no bulk superconductivity was found down to 1.8 K in a magnetic field of 20 Oe.     

Interactions between β-lactoglobulin and dextran sulfate at near neutral pH and their effect on thermal stability

The effect of interactions between β-lactoglobulin (β-LG) and dextran sulfate (DS) on thermal stability at near neutral pH was investigated. Samples containing 6% w/w β-LG and DS (M_w = 5–500 kDa) at different biopolymer weight ratios, pH (5.6–6.2), and NaCl concentrations (0–30 mM) were heated at 85 °C for 15 min. Turbidity results showed that the presence of DS at appropriate biopolymer weight ratio and pH significantly lowered the turbidity of heated β-LG. Solutions containing DS:β-LG weight ratios of 0.02 or less showed improved heat stability as indicated by decreased turbidity. Analysis of the unheated mixture by size exclusion chromatography coupled with multi-angle laser light scattering (SEC–MALLS) showed an interaction between β-LG and DS. The size of the aggregates increased as pH decreased. The β-LG–DS aggregates had a greater negative charge as seen from electrophoretic mobility measurement. Addition of 30 mM NaCl inhibited complex formation and the effect of DS on reducing the turbidity of heated β-LG, suggesting that the interaction was electrostatic in nature. Other than charge property, the amount and size of native aggregates appeared to be the major factor in determining how DS altered heat-induced aggregation. The presence of DS decreased denaturation temperature of β-LG, indicating that DS did not improve thermal stability of β-LG by stabilizing its native state but rather by altering its aggregation. The results provide information that will facilitate the application of whey proteins and polysaccharides as functional ingredients in foods and beverages.     

Characterization of Microstructural and Morphological Properties in As-deposited Ta/NiFe/IrMn/CoFe/Ta Multilayer System

Surface morphology and its relationship with microstructure in Ta/NiFe/IrMn/CoFe/Ta multilayer system deposited by pulsed DC magnetron sputtering have been investigated in dependence of Ta buffer and NiFe seed layer thicknesses using atomic force microscopy.The structural parameters such as grain size,dislocation density,texture and strain were calculated.For each surface,a self-affinity behavior with mean fractal dimensions in the range of 2.03-2.18 was found.Additionally,it was also observed that the surface of all samples has locally smooth textured surface structure in the short range.The texture aspect parameter and texture direction index have been obtained for isotropy/anisotropy surface texture.A significant relationship between the surface texture and the strength of the〈111〉texture in IrMn layer has been found.The analysis indicated that the surface roughness is strongly affected by the thicknesses of the NiFe seed and Ta buffer layers.     

Effect of HCl concentration on TiB2 separation from a self-propagating high-temperature synthesis (SHS) product

This paper presents a synthesis of TiB₂ powder via self-propagating high-temperature synthesis (SHS) method using a mixture of TiO₂, B₂O₃ and Mg followed by acid leaching. In the acid leaching step, the MgO content in the SHS product was leached in different HCl concentrations. X-ray diffraction (XRD) analysis showed that when 9.3 M HCl was used, the leached SHS product was found similar to that of the commercial TiB₂ powder. However, scanning electron microscopy (SEM) and BET surface area analysis revealed that the leached product was agglomerated and exhibited very high surface area.     

Relevance vector machines approach for long-term flow prediction

Over the past years, some artificial intelligence techniques like artificial neural networks have been widely used in the hydrological modeling studies. In spite of their some advantages, these techniques have some drawbacks including possibility of getting trapped in local minima, overtraining and subjectivity in the determining of model parameters. In the last few years, a new alternative kernel-based technique called a support vector machines (SVM) has been found to be popular in modeling studies due to its advantages over popular artificial intelligence techniques. In addition, the relevance vector machines (RVM) approach has been proposed to recast the main ideas behind SVM in a Bayesian context. The main purpose of this study is to examine the applicability and capability of the RVM on long-term flow prediction and to compare its performance with feed forward neural networks, SVM, and multiple linear regression models. Meteorological data (rainfall and temperature) and lagged data of rainfall were used in modeling application. Some mostly used statistical performance evaluation measures were considered to evaluate models. According to evaluations, RVM method provided an improvement in model performance as compared to other employed methods. In addition, it is an alternative way to popular soft computing methods for long-term flow prediction providing at least comparable efficiency.