GEOMETRIC PROGRAMMING. A NEW HYBRID ALGORITHM BASED ON LIAPUNOV CONCEPTS (MADLAP)

This article concerns the development of a simple yet very efficient heuristic procedure for optimizing the design or a reactor system employing continuous stirred tanks in series using Michaelis-Menten kinetics. The heuristic procedure employs a modified form or the well known Golden Search method to estimate the optimal number of reactors to be employed. The procedure was tested on an IBM personal computer under a wide range of values for three model parameters, namely the economy or scale factor, the scaled Michaelis-Menten constant and the desired degree of conversion to be attained. The results of this study indicated that the heuristic optimization procedure is capable of obtaining solutions that are either identical or very close to the actual optimal solutions in a very efficient manner.     

Experimental determination of mechanical parameters in sensorless vector-controlled induction motor drive

High-performance industrial drives widely employ induction motors with position sensorless vector control (SLVC). The state-of-the-art SLVC is first reviewed in this paper. An improved design procedure for current and flux controllers is proposed for SLVC drives when the inverter delay is significant. The speed controller design in such a drive is highly sensitive to the mechanical parameters of the induction motor. These mechanical parameters change with the load coupled. This paper proposes a method to experimentally determine the moment of inertia and mechanical time constant of the induction motor drive along with the load driven. The proposed method is based on acceleration and deceleration of the motor under constant torque, which is achieved using a sensorless vector-controlled drive itself. Experimental results from a 5-hp induction motor drive are presented.     

Identification of large scale distributed parameter systems—some simplifications in the multidimensional Poisson moment functional (MDPMF) approach

This paper is concerned with two practically important aspects of identification of large scale distributed parameter systems by the multidimensional Poisson moment functional (MDPMF) method (Saha and Prasada Rao 1980). The existing methods of (i) development and diagrammatic representations of the relations among the MDPMFs of partial derivative terms and those of the original multivariable function, and (ii) elimination of the effects of boundary functions and their partial derivatives from the identification equations, become extremely unwieldy as the order and dimensions of the model increase. This paper suggests alternative techniques in these two situations, leading to a simplification of the algorithm and an enormous reduction of the related analytical and computational burden. In the former situation, the suggested alternative uses the concept of separated variables. In the latter, the boundary function effects are estimated and then inserted into the algorithm to simplify it.     

Improved cuckoo search with particle swarm optimization for classification of compressed images

The need for a general purpose Content Based Image Retrieval (CBIR) system for huge image databases has attracted information-technology researchers and institutions for CBIR techniques development. These techniques include image feature extraction, segmentation, feature mapping, representation, semantics, indexing and storage, image similarity-distance measurement and retrieval making CBIR system development a challenge. Since medical images are large in size running to megabits of data they are compressed to reduce their size for storage and transmission. This paper investigates medical image retrieval problem for compressed images. An improved image classification algorithm for CBIR is proposed. In the proposed method, RAW images are compressed using Haar wavelet. Features are extracted using Gabor filter and Sobel edge detector. The extracted features are classified using Partial Recurrent Neural Network (PRNN). Since training parameters in Neural Network are NP hard, a hybrid Particle Swarm Optimization (PSO) – Cuckoo Search algorithm (CS) is proposed to optimize the learning rate of the neural network.     

EFFECT OF COMBINATION DRYING ON THE PHYSICO-CHEMICAL CHARACTERISTICS OF CARROT AND PUMPKIN

The quality of dehydrated carrot and pumpkin pieces produced by combination drying employing partial freeze-drying and hot air-drying were investigated. The drying rate, the total energy requirement and the physico-chemical properties of the combination dried (CD) products were compared with those of hot air-dried (HAD) and freeze-dried (FD) products. The total carotenoid content of the two vegetables (1050 ppm and 160 ppm) was significantly affected by drying processes. Destruction of carotenoids during storage at different temperatures was less in the CD samples. The HAD vegetables exhibited shrinkage, case hardening and poor rehydration (25 and 28 min in cold water, rehydration ratio 1:2.6 and 1:2.9, respectively). The FD vegetables appeared wholesome, porous, well formed with excellent rehydration features at room temperature (rehydration time 2 and 3 min in cold water, rehydration ratio 1:7 and 1:6.9, respectively). The CD vegetables were comparatively superior to HAD products and were nearer in quality to FD products with respect to appearance, rehydration (9 and 10 min in cold water, rehydration ratio 1:5 and 1:4, respectively). The drying time and total energy for CD processing was 50% less than for FD but similar to HAD. The combination dehydration process is effective in obtaining high quality dehydrated vegetables.     

IDENTIFICATION OF GOAT MEAT USING HIGHLY SPECIES‐SPECIFIC POLYMERASE CHAIN REACTION

ABSTRACT

A highly species‐specific polymerase chain reaction (PCR) assay was developed for the authentic identification of goat. A product of 436 bp was amplified using newly designed primers against mitochondrial D‐loop region. The possibility of cross‐amplification was ruled out by considering as many as 25 other animal species. Suitability of the developed goat species‐specific PCR assay was confirmed for in raw, cooked (60, 80 and 100C for 30 min) and micro‐oven‐processed meat samples (n = 20 each). A sensitivity of 0.1% was established for detection of adulteration and limit of detection of goat DNA was 0.1 pg. This investigation presents a novel PCR assay with its newly designed primers that could be used for the authentic identification of goat species.

PRACTICAL APPLICATIONS

This work details about a novel diagnostic polymerase chain reaction, which could be used for authentic identification of goat species. This approach could be used for the confirmation of goat tissues in raw, cooked, as well as adulterated samples. The developed technique has also applications in the forensic analysis of wild animal‐related disputes, where this work could solve the problem of goat‐related issues.     

Machining characteristics of fine grained AZ91 Mg alloy processed by friction stir processing

AZ91 Mg alloy was considered and friction stir processing (FSP) was adopted to achieve grain refinement to investigate the effect of grain size and secondary phase on machining characteristics during drilling at various speeds and feeds. Super saturated AZ91 Mg alloy was obtained after FSP and the grain refinement was achieved from (166.5±8.7) µm to (21.7±13.5) µm. Surprisingly, hardness reduced for FSP AZ91 Mg alloy (88.95±6.1) compared with AZ91 alloy (108.2±15.6), which was attributed to the reduced secondary phase. However, the mean cutting force for FSP-treated (FSPed) AZ91 Mg alloy was marginally increased. The edge damage of the drilled holes was lower for FSPed AZ91 Mg alloy compared with unprocessed AZ91 Mg alloy. Hence, it can be understood that the grain refinement may slightly increase the cutting forces during drilling but better edge finishing can be achieved in machining of AZ91 Mg alloy.     

Effect of loading condition,specimen geometry,size-effect and softening function on double-<Emphasis Type="BoldItalic">K</Emphasis> fracture parameters of concrete

This paper presents numerical investigation of the influence of the specimen geometry, loading condition, size-effect and softening function of concrete on double-K fracture parameters. The input data needed for computation of the double-K fracture parameters are obtained from the well-known version of Fictitious Crack Model (FCM). FCM is developed for three standard specimens: three-point bend test, compact tension specimen and four-point bend test of size range 100–600 mm at relative size of initial crack length 0.3. The analysis of numerical results shows some interesting behaviour of double-K fracture parameters.     

Separately balanced realization of two-dimensional separable-denominator transfer functions†

In this paper a method is developed for the computation of a separately balanced state-space model for a given two-dimensional transfer function with separable denominator. The procedure relies on the eigenvalue/eigenvector decomposition (or singular-value decomposition) of two real symmetric matrices determined directly from the given transfer function.