Supercritical fluid extraction of daphne (Laurus nobilis L.) seed oil

Laurus nobilis L., commonly known as daphne tree, is an evergreen that belongs to the Lauraceae family. Daphne trees produce grape-sized shiny purplish berries having three parts: flesh, skin, and an inner kernel (single seed). This study examines supercritical CO₂ (SC-CO₂) extraction of oil from daphne seeds. The oil yield of ground seeds varied from 14 to 28% depending on the method and particle size used for oil recovery. Yields were similar for both petroleum ether and SC-CO₂ extraction. The extraction yield decreased significantly with increasing particle size. The amount of extract collected increased exponentially with increasing SC-CO₂ pressure. The highest extraction yield was obtained at the highest temperature studied, 75°C. More than 45% of the oil was lauric acid. SC-CO₂ is a viable technique to obtain high-purity L. nobilis L. seed oil, which is a potential ingredient for the cosmetic industry.     

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.     

Pressurised solvent extraction of policosanol from wheat straw,germ and bran

Policosanols (PCs) are a group of long chain aliphatic alcohols that have been reported to have low-density lipoprotein (LDL) cholesterol-lowering properties. Wheat is a good source of these compounds. This study examined the effect of solvent type and temperature on extract yields and PC content and composition in the extracts. Wheat germ, straw and bran samples were extracted with petroleum ether, chloroform, n-hexane and ethanol at various temperatures ranging from 80 to 125 °C.     

Artificial neural networks in their simplest forms for analysis and synthesis of RF/microwave planar transmission lines

In this work, the multiplayer perceptron (MLP) and radial basis function (RBF) neural networks in their simplest forms are employed in function approximation for highly nonlinear and complex analysis and synthesis of the most commonly used planar RF/microwave transmission lines, that is, microstrip lines, coupled microstrip lines, and basic and shielded coplanar‐waveguides. Since the analysis and synthesis processes for these systems have “one‐to‐one mapping” relations with each other, a forward model is defined for the analysis process for all these types of the planar transmission lines; on the other hand, a reverse model is also considered for the synthesis of the same lines. This reverse model is realized by swapping some of the inputs/outputs in the analysis model, and training the neural networks accordingly. Both MLP and RBF types of neural models are applied to the four widely used anisotropic and isotropic dielectric materials: PTFE/microstrip glass, RT/Duroid 6006, alumina and gallium arsenide. The results are shown to agree very well with the targets. A low‐pass filter with 30‐dB attenuation frequency at 3.5 GHz on an alumina substrate is designed by the use of a neural‐network synthesis and its resulting performance agrees well with the one using analytical formulas for the synthesis. © 2005 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2005.     

A new method for adaptive IIR filter design based on tabu search algorithm

Adaptive digital filters have proven their worth in a wide range of applications such as channel equalisation, noise reduction, echo cancelling, and system identification. These filters can be broadly classified into two groups: finite impulse–response (FIR) and infinite impulse–response (IIR) filters. IIR filters have become the target of increasing interest because these filters can reduce the filter order significantly as compared to FIR filters. Tabu search is a heuristic optimisation algorithm which has been originally developed for combinatorial optimisation problems. It simulates the general rules of intelligent problem solving and has the ability of discovering the global minima in a multi-modal search space. In this work, a novel method based on tabu search is described for the design of adaptive IIR filters.